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Article

Pharmacogenetics as a Future Tool to Risk-Stratify Breast Cancer Patients According to Chemotoxicity Potential from the Doxorubicin Hydrochloride and Cyclophosphamide (AC) Regimen

by
Esraa K. Abdelfattah
1,
Sanaa M. Hosny
1,
Amira B. Kassem
2,*,
Hebatallah Ahmed Mohamed Moustafa
3,*,
Amany M. Tawfeik
4,5,
Marwa N. Abdelhafez
6,
Wael El-Sheshtawy
7,
Bshra A. Alsfouk
8,
Asmaa Saleh
8 and
Hoda A. Salem
9
1
Department of Clinical Pharmacy, Faculty of Pharmacy (Girls), Al-Azhar University, Cairo 11651, Egypt
2
Clinical Pharmacy and Pharmacy Practice Department, Faculty of Pharmacy, Damanhour University, Damanhour 22514, Egypt
3
Clinical Pharmacy and Pharmacy Practice Department, Faculty of Pharmacy, Badr University in Cairo, Cairo 11829, Egypt
4
Medical Microbiology and Immunology Department, Faculty of Medicine, Badr University in Cairo, Cairo 11829, Egypt
5
Medical Microbiology and Immunology Department, Faculty of Medicine, Al Azhar University (Girls) Cairo, Cairo 11754, Egypt
6
Department of Medical Oncology, National Cancer Institute, Cairo University, Al Giza 12613, Egypt
7
Department of Medical Oncology, Faculty of Medicine, Al Azhar University, Cairo 11651, Egypt
8
Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
9
Department of Pharmacy Practice, University of Tabuk, Tabuk 47512, Saudi Arabia
*
Authors to whom correspondence should be addressed.
Pharmaceuticals 2025, 18(4), 539; https://doi.org/10.3390/ph18040539
Submission received: 13 March 2025 / Revised: 31 March 2025 / Accepted: 1 April 2025 / Published: 7 April 2025
(This article belongs to the Special Issue The Application of Pharmacogenetics in Toxicity Prevention and Drug Effect Improvement)
Versions Notes

Abstract

:
Background: Studying single-nucleotide polymorphisms (SNPs) in xenobiotic-transporting and metabolizing enzyme genes before administering the doxorubicin hydrochloride and cyclophosphamide (AC) regimen may help optimize breast cancer (BC) treatment for individual patients. Objective: Genotyping specific SNPs on genes encoding for the transport and metabolism of the AC regimen and study their association with its chemotherapeutic toxicity. Method: This prospective cohort study was conducted in two hospitals in Egypt. Before receiving AC therapy, venous blood was collected from female patients with BC for DNA extraction and the genotyping of four SNPs: rs2228100 in ALDH3A1 gene, rs12248560 in CYP2C19 gene, rs1045642 in ABCB1 gene, and rs6907567 in SLC22A16 gene. Patients were then prospectively monitored for hematological, gastrointestinal, and miscellaneous toxicities throughout the treatment cycles. Results: The ALDH3A1 gene polymorphism demonstrated a significant increase in nausea, stomachache, and peripheral neuropathy among patients carrying the GC+CC genotype, compared to those with the GG genotype (p = 0.023, 0.036, and 0.008, respectively). Conversely, patients with the GG genotype exhibited significantly higher fever grades after cycles 1, 2, and 3 of the AC regimen compared to those with the GC+CC genotype (p = 0.009, 0.017, and 0.018, respectively). Additionally, fatigue severity was significantly increased among patients with the GG genotype compared to those with the GC+CC genotype following AC administration (p = 0.008). Conclusions: The SNP variation of ALDH3A1 (rs2228100) gene significantly influenced AC regimen toxicity in female BC patients. Meanwhile, SNPs in CYP2C19 (rs12248560), ABCB1 (rs1045642), and SLC22A16 (rs6907567) genes showed a significant influence on the recurrence rate of certain toxicities.

1. Introduction

Breast cancer (BC) is the most frequent cancer among females, with substantial morbidity and mortality, making it a primary public health concern [1,2]. The majority of breast cancers are adenocarcinomas, primarily categorized into ductal and lobular types [3]. In addition, BC onset is influenced by mutations in BRCA1 and BRCA2 genes [2,4]. Invasive forms of the disease are classified as infiltrative, whereas non-infiltrative cases are referred to as “in situ” carcinoma [5]. Risk factors for BC development include smoking, alcohol intake, obesity, advanced age, exposure to radiation, and use of hormone replacement therapy [2,6,7].
BC treatment involves a combination of local modalities, such as surgery and radiotherapy, along with pharmacological approaches, including hormonal therapy (e.g., anti-estrogens and aromatase inhibitors), chemotherapy (e.g., cyclophosphamide, anthracycline drugs, platinum-based drugs, and taxanes), and targeted therapy, with variable response in practice [8,9]. Therapeutic decisions on BC are based on its three main subtypes, luminal (A and B), which express the hormone receptor such as estrogen receptor or progesterone receptor); human epidermal growth factor receptor 2-positive; and triple-negative, which lacks the expressions of all three receptors (estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2) [10]. Additional factors, including age at diagnosis, tumor histotype, and tumor-node-metastasis (TNM) staging, also play a crucial role in determining the appropriate treatment strategy [11].
Despite advancements in BC therapies, drug resistance and treatment-related toxicities remain significant challenges that can limit treatment success and overall survival [12,13]. Several clinical factors, including molecular subtype [14,15,16], receptor status [17], age [18], and tumor size [19] correlate with the response to chemotherapy. However, even among patients with similar clinical and pathological characteristics, genetic variations may significantly influence individual treatment outcomes [13,20]. In addition, subjects may develop heterogenicity in toxicities after the administration of equal doses [12,20,21,22], further complicating treatment management.
Chemotherapy is integral to the standardized systemic management of BC. It can be used as a neoadjuvant to diminish tumor size before surgery or as an therapy in early-stage BC cases with a favorable prognosis [23,24,25]. The toxicities of the chemotherapy may affect the quality of life of the individual and necessitate dose reductions or cycle delays, which may ultimately compromise the efficacy of the therapy [26]. Some patients may even refuse subsequent chemotherapy cycles due to concerns about adverse effects, increasing the risk of cancer recurrence or premature death [27,28]. Therefore, it is essential for patients receiving chemotherapy to be fully informed about both its potential benefits and the associated acute and long-term toxic effects [29].
The AC regimen was associated with an elevated risk of multiple toxicities, including gastrointestinal toxicities, such as nausea and vomiting, as well as hematological toxicities, such as neutropenia and leukopenia [30,31]. Pharmacogenetics is a science that studies genetically determined variations in pharmacokinetics including the absorption, distribution, metabolism, and excretion (ADME) of a drug. While demographic, clinical, concurrent medication, and environmental factors influence drug efficacy and toxicity, pharmacogenetics studies specifically associate the efficacy and toxicity of drugs with genetic variations among subjects [32,33].
Pharmacogenetic polymorphism is a monogenic trait arising from the presence of multiple alleles at the same genetic locus, leading to phenotypic variability in drug response within a population. The frequency of the least common allele exceeds 1%, influencing the medication metabolism, efficacy, and safety. Variations in DNA sequences may present as nucleotide insertions or deletions, alterations in the copy number of repetitive sequences, or single-nucleotide polymorphisms (SNPs) [34,35]. Incorporating these SNPs into clinical procedures allows for informed decision-making, enabling clinicians to personalize chemotherapy regimens and optimize the treatment outcomes [36].
Pharmacokinetics or pharmacodynamics (drug actions on the body) play a critical role in determining the response to chemotherapeutic drugs. These processes rely on receptor metabolizing and transporter proteins encoded with various genes [8,37,38]. Genetic polymorphisms influence both the onset and progression of cancer, as well as the efficacy and adverse effects of chemotherapy [8,39]. Although pharmacogenetic research on chemotherapeutic toxicities is important for patients’ quality of life and survivorship, studies are still sparse [12,31,40,41]. While some drug–gene correlations have strong or moderate evidence, many remain inconclusive, with low levels of supporting data [8,42].
Alterations in the genes encoding drug metabolizing enzymes can influence their activities and expression, with subsequent differences in treatment outcomes [43]. The majority of published research examined the correlation between genetic polymorphisms and clinical outcomes of BC, including disease-free survival (DFS) and overall survival (OS) [44,45], with scarce evidence on treatment response and toxicity [25,46]. Expanding this research area could contribute to more personalized and effective cancer treatment strategies.
Phase I CYP450, CYP2C19 is one of multiple metabolizing isoenzymes catalyzing the oxidation of the pro-drug, cyclophosphamide, into its active form [25,47,48], which diffuses into cancer cells and exerts cytotoxic effects through alkylation [49,50]. CYP2C19*17 genetic polymorphism alters enzymatic expression and metabolism between individuals [51,52] leading to the ultra-rapid metabolism of CYP2C19 substrates [53]. CYP2C19*17 (-806 C>T, or rs12248560) is an SNP that is characterized by high enzyme activities due to increased gene transcription, arising from the attachment of a specific nuclear protein to the 5′ flanking region [52]. It was detected in about 18% of African populations and 18-28% of Europeans, and it was less common in Asians [52]. Due to its exceptional rapid clearance function, the CYP2C19*17 allele can justify the lack of response to common doses of some proton pump inhibitors and antidepressants [54].
Aldehyde dehydrogenase (ALDH) family genes metabolize the toxic cyclophosphamide [41,55]. ALDH3A1 belongs to the aldehyde dehydrogenase 3 family and it is located on chromosome 17p11.2 [56]. It metabolizes endogenous and exogenous aldehydes involved in cell division, migration, and oxidative stress response [57]. The rs2228100 polymorphism is positioned at the 8th exon of ALDH3A1 gene. It is a missense mutation (P329A), where C allele is the minor (rare) variant, the G allele is the major (common) variant (GG genotype representing the wild-type) [58].
SNPs can lead to genetic variations that influence the expression and activity of transporters and enzymes, impacting the AC regimen response and tolerance [25,28,59,60]. The transport systems, including importers and exporters, regulate intracellular drug concentrations and modulate the treatment response and toxicity development [31]. SLC22A16 [61] and ABCB1 genes, also referred to as MDR1; P-gp [62] code for the influx and efflux of doxorubicin, respectively, influencing its systemic pharmacology [25,63].
SLC22A16 encodes a membrane uptake transporter that facilitates doxorubicin entry into cells [25]. The overexpression of SLC22A16 in cancer cells enhances their sensitivity to the cytotoxic effects of doxorubicin [48,61]. rs6907567 is a missense SNP of SLC22A16 [64] which is located at the second exon having A>G alleles; in the other words, A is the major [25,65] and G is the altered (mutated) allele. Patients carrying the common A allele may be at a higher risk for neutropenia and require dose delay when they receive cyclophosphamide, doxorubicin, and fluorouracil, compared to the AG and GG genotypes [25].
ATP-binding cassette, subfamily B, member 1 (ABCB1) is a major efflux p-glycoprotein transporter for doxorubicin. It belongs to the ATC-binding cassette family, which protects normal cells against environmental toxins, by the pumping-out mechanism, causing their excretion into the bile [25,63,66]. It transports doxorubicin via ATP hydrolysis across the membrane, opposing the concentration gradient and plays a role in the resistance to doxorubicin [63]. SNPs in ABCB1 were related to the doxorubicin concentration [67], and its removal from BC cells, affecting its effectiveness [11,30]. The overexpression of efflux transporters enhances drug elimination, potentially mitigating drug-induced harm [68].
At present, there are no established techniques for identifying patients at increased risk of chemotherapy-related toxicities before AC therapy administration. Consequently, all patients receiving the AC regimen must be meticulously monitored by their physician [69]. Identifying polymorphisms in genes coding for AC regimen transporter and metabolizing enzymes before the initiation of the AC regimen may present novel opportunities for individualized treatment optimization.
This is, to our knowledge, the first study in Egypt that evaluates the effect of SNPs in metabolic enzymes genes CYP2C19 (rs12248560) and ALDH3A1 (rs2228100), which play a role in the metabolism of cyclophosphamide drug in an AC regimen in female BC patients, along with SNPs in two transporter genes ABCB1 (rs1045642) and SLC22A16 (rs6907567), on the occurrence of adverse effects. Understanding these genetic variations could be valuable in predicting individual susceptibility to AC regimen-related toxicities, paving the way for personalized BC treatment strategies.

2. Results

2.1. Count and Percentage of Each Genotype Group Among the 96 Patients Along the CYP2C19, ALDH3A1, SLC22A16, and ABCB1 Genes

Among the 106 Egyptian female patients diagnosed with breast cancer who met the inclusion criteria, only 96 cases provided written consent to participate. Of these, 64 patients carried the CC genotype (66.67%) of the CYP2C19 metabolizing enzyme gene, 28 carried the CT genotype (29.17%), and only 4 carried the TT genotype (4.17%). When combining the CT and TT genotypes, 32 patients (33.33%) carried the CT+TT genotypes. For the ALDH3A1 metabolizing enzyme gene, 46 patients carried the GG genotype (47.92%), 39 carried the GC genotype (40.63%), and 11 carried the CC genotype (11.46%). When combining the GC and CC genotypes, 46 patients (47.92%) had the GC+CC genotypes. Regarding the SLC22A16 gene, 47 patients (48.96%) carried the AA genotype, 38 carried the GA genotype (39.58%), and 11 carried the GG genotype (11.46%). When combining the GG and GA genotypes, 49 patients (51.04%) had the GG+GA genotypes. For the ABCB1 gene, 47 patients (48.96%) carried the GG genotype, 11 carried the AA genotype (11.46%), and 38 carried the GA genotype (39.58%). When combining the GA and AA genotypes, 47 patients (48.96%) had the GA+AA genotypes (Table A1).

2.2. Demographic Data Analysis

2.2.1. General Demographic Data

Quantitative general demographic variables included age, body surface area, number of positive lymph nodes, and the number of lymph nodes removed. No significant differences were observed between the allele groups for the CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes (p-value > 0.05) (Table 1). Qualitative general demographic variables, including marital status, menopausal status, oral contraception, family history, and smoking history, also showed no significant differences across the allele groups of CYP2C19, ALDH3A1, and SLC22A16 genes (p-value > 0.05). However, a significantly higher proportion of married patients was observed in the GG genotype group of the ABCB1 gene compared to the AA+GA group (p-value < 0.05) (Table 1).

2.2.2. Surgical Demographic Data

Qualitative surgical demographic variables, including the type of surgery, affected breast, tumor grade, tumor stage (T stage, N stage), and adjuvant/neoadjuvant treatment setting, showed no significant differences among the allele groups of CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes (p-value > 0.05) (Table 1).

2.2.3. Pathological Demographic Data

Qualitative pathological variables, including pathological breast cancer type, progesterone receptor status, estrogen receptor status, and human epidermal growth factor receptor 2 status, showed no significant correlation with the different allele groups of CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes demonstrated no significant difference (p-value > 0.05) (Table 1).

2.3. Toxicity Analysis

2.3.1. CYP2C19, ALDH3A1, SLC22A16, and ABCB1 Genes Data Analysis Related to Toxicity Assessed at Different Time Points

CYP2C19, ALDH3A1, SLC22A16, and ABCB1 Genes Data Analysis Related to Hematological Toxicity Assessed at Different Time Points

Qualitative hematological toxicity variables, including thrombocytopenia, leukopenia, neutropenia, lymphocytopenia, and anemia, were assessed at five different time points for their correlation with various alleles of the CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes. No significant differences were observed among the allele groups (p-value > 0.05) (Table 2, Table 3, Table 4 and Table 5).

CYP2C19, ALDH3A1, SLC22A16, and ABCB1 Genes Data Analysis Related to Gastrointestinal (GIT) Toxicity at Different Time Points

The correlation between qualitative gastrointestinal (GIT) toxicity variables (nausea, vomiting, diarrhea, constipation, mucositis, and stomachache) and different alleles of the CYP2C19 gene at five time points showed no significant differences between allele groups (p-value > 0.05) (Table 6). However, as shown in Table 7, the correlation of these GIT toxicity variables with different alleles of the ALDH3A1 gene revealed a significant increase in nausea among patients carrying the GC+CC genotype compared to those with the GG genotype after the third cycle of the AC regimen (p = 0.023). Additionally, a significant increase in stomachache was observed among patients with the GC+CC genotype versus the GG genotype after the third cycle of the AC regimen (p = 0.036).
Conversely, no significant differences were observed between the ALDH3A1 gene and its different alleles concerning other GIT toxicity variables (p-value > 0.05). Similarly, there was no significant difference in GIT side effects between the patients carrying the GG+GA genotype and those with the AA genotype of the SLC22A16 gene, as shown in Table 8.
There was no significant difference in gastrointestinal side effects between patients carrying the AA+GA genotype and those carrying the GG genotype of the ABCB1 gene (Table 9).

The CYP2C19, ALDH3A1, SLC22A16, and ABCB1 Genes Data Analysis Related to Miscellaneous Toxicity at Different Time Points

Qualitative miscellaneous toxicity variables, including fever, fatigue, amenorrhea, alopecia, headache, skin toxicity, and peripheral neuropathy, were assessed across five time points. The correlation between these variables and different alleles of the CYP2C19 gene showed no significant differences between the allele groups (p-value > 0.05) (Table 10).
As presented in Table 11, the correlation between qualitative miscellaneous toxicities and different alleles of the ALDH3A1 gene revealed a significant increase in fever among patients carrying the GG genotype compared to those with the GC+CC genotype after the first, second, and third cycles of the AC regimen (p = 0.009, p = 0.017, and p = 0.018, respectively). Additionally, there was a significant increase in fatigue among patients carrying the GG genotype, versus the GC+CC genotype after cycle one of the AC regimen (p = 0.008). Peripheral neuropathy also showed a significant increase in patients carrying the GC+CC genotype compared to those with the GG genotype after the second cycle of the AC regimen (p = 0.008). However, no significant differences were observed between ALDH3A1 alleles concerning other toxicity variables (p-value > 0.05).
Analysis of qualitative data for miscellaneous toxicities showed no significant differences between the allele groups of the SLC22A16 transporter gene (Table 12) or the ABCB1 transporter gene (Table 13).

2.3.2. Toxicity Among the Same Genotype Group Data Analysis Using Two-Way with One-Repeated-Measure ANOVA Test Results

Hematological Toxicity Among the Same Genotype Group Data Analysis Using Two-Way with One-Repeated-Measure ANOVA Test Results

A two-way analysis of variance (ANOVA) using the fit general linear model was conducted to assess the correlation between different genotypes and the quantitative hematological toxicity variables, including thrombocytopenia, leukopenia, neutropenia, lymphocytopenia, and anemia grades. The analysis revealed a significant increase in the mean leukopenia and lymphocytopenia grades after the fourth cycle of the AC regimen compared to baseline (point A) among patients carrying the CC genotype of the CYP2C19 gene (p < 0.05). Additionally, the neutropenia grade significantly increased following the second and fourth cycles of chemotherapy in the same genotype group (p-value < 0.05).
Similarly, among patients with the GG genotype of the ALDH3A1 gene, the mean anemia grade showed a significant increase after the fourth cycle of the AC regimen compared to baseline (p < 0.05). Furthermore, thrombocytopenia grades significantly increased after the first, second, and third cycles of chemotherapy, while neutropenia grades were significantly elevated after the first and third cycles in the same genotype group (p < 0.05). Patients carrying the GC+CC genotype of the ALDH3A1 gene also demonstrated a significant increase in thrombocytopenia grades after the first, second, and third cycles of the AC regimen (p-value < 0.05).
Regarding the SLC22A16 gene, the neutropenia grade increased significantly following the second and fourth cycles, while the lymphocytopenia grade increased significantly after the fourth cycle among patients with the AA genotype (p < 0.05). Among patients carrying the GG+GA genotype of the SLC22A16 gene, leukopenia grade significantly increased after the fourth cycle, and neutropenia grade increased after the second cycle compared to baseline p-value < 0.05) (Table 14).
During the AC chemotherapy cycles, patients carrying the GG genotype of the ABCB1 gene exhibited a significant increase in neutropenia grade after the second and fourth cycles, while lymphocytopenia grade significantly increased after the third and fourth cycles compared to baseline (p < 0.05). Similarly, among patients with the GA+AA genotype of the ABCB1 gene, the neutropenia grade showed a significant increase following the second cycle, and the lymphocytopenia grade significantly increased after the fourth cycle compared to pre-treatment levels (p-value < 0.05) (Table 14).

GIT Toxicity Among the Same Genotype Group Data Analysis Using Two-Way with One-Repeated-Measure ANOVA Test Results

Quantitative gastrointestinal toxicity variables, including nausea, vomiting, diarrhea, constipation, mucositis, and stomachache grades, were analyzed for their correlation with different genotypes using a two-way analysis of variance (ANOVA) under the fit general linear model.
Among patients carrying the CC genotype of the CYP2C19 gene, the mean grades of vomiting and mucositis significantly increased after each chemotherapy (AC regimen) cycle (p < 0.05). Additionally, nausea severity significantly increased after cycles one and two, while constipation severity significantly increased after cycle two compared to pre-treatment levels (point A) (p-value < 0.05). Similarly, among patients with the CT+TT genotype of the CYP2C19 gene, nausea severity was significantly higher after cycles one and two compared to before chemotherapy (p-value < 0.05) (Table 15).
For the ALDH3A1 gene, patients carrying the GG genotype experienced a significant increase in constipation severity after each chemotherapy cycle, nausea severity significantly increased after cycles one and two, vomiting severity significantly increased after cycles one, two, and four, and stomachache severity significantly increased after cycle one compared to baseline (point A) (p-value < 0.05). Patients with the GC+CC genotype exhibited significantly higher nausea severity after each chemotherapy cycle, while vomiting severity increased after cycles one and two compared to before chemotherapy (p-value < 0.05) (Table 15).
Regarding the SLC22A16 gene, nausea and vomiting severity significantly increased after cycles one and two, mucositis severity significantly increased after cycles one and three, and stomachache severity significantly increased after cycle one in patients carrying the AA genotype compared to before chemotherapy (p < 0.05). In the GG+GA genotype group, nausea and constipation severity significantly increased after cycles one and two, while vomiting severity increased after each chemotherapy cycle compared to pre-treatment levels (p-value < 0.05) (Table 15).
For the ABCB1 gene, patients carrying the GG genotype showed a significant increase in nausea severity after cycles one, two, and three, while vomiting severity increased after cycle one compared to before chemotherapy (p-value < 0.05). Among patients with the GA+AA genotype, nausea and mucositis severity significantly increased after cycles one and two, while vomiting severity increased after cycles one, two, and three compared to the baseline (p-value < 0.05) (Table 15).

Miscellaneous Toxicities Among the Same Genotype Group Data Analysis Using Two-Way with One-Repeated-Measure ANOVA Test Results

Quantitative toxicity variables, including fever, fatigue, amenorrhea, alopecia, headache, skin toxicity, and peripheral neuropathy grades, were analyzed for their correlation with different genotypes using a two-way analysis of variance (ANOVA) under the fit general linear model.
Among patients carrying the CC genotype of the CYP2C19 gene, fatigue severity significantly increased after cycles one and two, while amenorrhea and skin toxicity severity significantly increased after cycle one. Additionally, alopecia severity significantly increased after all chemotherapy cycles compared to pre-treatment levels (point A) (p < 0.05). In patients with the CT+TT genotype of the CYP2C19 gene, fatigue severity significantly increased after cycle one, and alopecia severity increased after all chemotherapy cycles compared to baseline (p-value < 0.05) (Table 16).
For the ALDH3A1 gene, patients with the GG genotype experienced a significant increase in fatigue severity after cycles one and two, while amenorrhea and fever severity significantly increased after cycle one. Alopecia severity also increased after all chemotherapy cycles compared to pre-treatment levels (p < 0.05). Among patients carrying the GC+CC genotype of the ALDH3A1 gene, peripheral neuropathy severity significantly increased after cycle two, skin toxicity severity increased after cycle one, and alopecia severity increased after all chemotherapy cycles compared to baseline (p-value < 0.05) (Table 16).
Regarding the SLC22A16 gene, patients carrying the GG+GA genotype exhibited a significant increase in fatigue and skin toxicity severity after cycle one compared to before chemotherapy (p < 0.05). In the AA genotype group, fatigue severity increased significantly after cycles one and two. Alopecia severity significantly increased throughout all chemotherapy cycles in patients carrying the AA, GG, and GA genotypes compared to pre-treatment levels (p-value < 0.05) (Table 16). For the ABCB1 gene, fatigue severity significantly increased after cycles one and two, while alopecia severity increased after all chemotherapy cycles among patients carrying the GG genotype (p < 0.05). In patients with the GA+AA genotype, fatigue, and skin toxicity severity significantly increased after cycle one, and alopecia severity increased after all cycles compared to pre-treatment levels (p-value < 0.05) (Table 16).

3. Discussion

Pharmacogenetics aims to establish screening tools to optimize pharmacological therapy. This work aimed to identify pharmacogenetic polymorphism that may predict hematological, GIT, and other toxicities in BC patients receiving the AC regimen. Our findings demonstrate that the AC regimen-related chemotoxicity is influenced by a polymorphism in genes involved in drug metabolism (CYP2C19 and ALDH3A1) and drug transport (ABCB1 and SLC22A16).
For the CYP2C19 gene (rs12248560), the C allele was the predominant homozygous variant, observed in 66.67% of individuals, while the T allele (CT and TT genotypes) represented the minor variant. The ALDH3A1 gene (rs2228100) had the G allele as the most frequent homozygous variant (47.92%), whereas the C allele (GC and CC genotypes) was less common. For the SLC22A16 gene (rs6907567), 48.96% of patients carried the AA genotype, while the GA and GG genotypes were less prevalent. The G allele of ABCB1 gene (rs1045642) was the wild type (GG genotype in 51.04% of participants), while the AA genotype and the GA genotype were the minor variants.
The frequencies of genetic variants are associated with the subject’s ethnic group [70,71,72], which is based on environmental factors and epigenetics [30].
No significant correlation was found between CYP2C19, ALDH3A1, SLC22A16, or ABCB1 genotypes and age, body surface area, number of positive lymph nodes, and number of lymph nodes removed (p-value > 0.05). However, the GG genotype of ABCB1 was significantly more frequent in married participants.
The CYP2C19*17 variant (rs12248560) contributed to the ultra-rapid metabolism of the CYP2C19 enzyme substrates [53], including cyclophosphamide [31]. Our study revealed that the CYP2C19*17 variant had the CC as the homozygote major genotype, in line with previous Polish work [31]. Our study found that the CC genotype was linked to an increased recurrence of neutropenia, vomiting, mucositis, and fatigue. According to previous work, the polymorphisms in the CYP450 metabolizing genes had a significant influence on hematological and gastrointestinal toxicity [31]. In addition, higher-grade leukopenia occurred after taking the AC regimen cycles in CC carriers due to slower cyclophosphamide metabolism, consistent with Tecza et al. [31]. Increased lymphocytopenia, amenorrhea, constipation, and skin toxicity grades were also observed in CC carriers. On the other hand, TT and CT genotypes (associated with increased CYP2C19 enzymatic activity) showed lower toxicity risks due to faster cyclophosphamide deactivation [73,74,75].
The GG genotype of ALDH3A1 was predominant (47.92%), aligning with findings from Afsar et al. and Berdyński et al. [58,76]. The G allele was first described as common and benign, after being detected in subjects with Sjögren–Larsson syndrome [77]. The GG genotypes was associated with a higher risk of fever and recurrent fatigue, while recurrent neutropenia and constipation occurred exclusively in GG carriers.
Anemia severity increased significantly after AC treatment in GG genotype carriers, consistent with previous research by Tecza et al. [31]. Moreover, in the groups that did not carry the G allele, they found no cases of recurrent anemia [31], in line with our findings. This can be explained by the significant role ALDH3A1 plays in the metabolism of aldophosphamide (one of the cyclophosphamide metabolites) to carboxyphosphamide, influencing its hematological and non-hematological chemotoxicity [78]. The slower rate of detoxification of cyclophosphamide and its accumulation inside the cells may be associated with the presence of the GG genotype of the ALDH3A1 gene [31].
On the other hand, the GC and CC genotypes exert a significantly higher clearance of cyclophosphamide due to increased ALDH3A1 expression [79,80].
Tecza et al. reported that the common homozygote allele G of polymorphism (rs2228100; *2) of the ALDH3A1 gene present in the pathway of the cyclophosphamide metabolism affected leukopenia risks due to weaker detoxification [31]. However, we found no correlation between leukopenia occurrence and the presence of different allele groups of the ALDH3A1 gene.
On the other hand, the GC and CC genotypes of rs2228100 of the ALDH3A1 gene showed a significantly higher risk for peripheral neuropathy, recurrent nausea, and stomachache. Also, recurrent thrombocytopenia, alopecia, and vomiting were observed in GG and GC+CC groups. Previous research did not find a direct effect of ALDH3A1 on cyclophosphamide clearance [81].
Our findings highlight the influence of the SLC22A16 importer gene on the AC regimen tolerance and efficacy as it regulates intracellular drug concentrations [31]. SlC22A16 (rs6907567) is an SNP where A is the wild allele and G is the minor one [25,65], in compliance with our findings. The expression of the SLC22A16 gene is limited to the hematopoietic cells of the bone marrow, which can be explained by its role in hematopoiesis [61]. However, when overexpressed, inflow and susceptibility to the side effects of doxorubicin in the bone marrow increases [31], which may result in dose delay [25]. The AA genotype was associated with recurrent neutropenia, mucositis, and fatigue due to altered drug transport, similar to prior study by Tecza et al. [31]. It was hypothesized that early toxicity occurring before reaching a certain concentration threshold of the cytotoxic drug can occur due to changes in its import and export transporters before the metabolic enzymes start their actions [31]. The polymorphic G allele of the SLC22A16 gene was reported previously to influence gastrointestinal toxicities, including nausea [31]. However, no significant difference was found between both genotype groups in nausea occurrence. On the other hand, constipation was recurrent in the AG and GG genotypes only.
This study investigated the effect of the common polymorphisms in ABCB1 (rs1045642), which is an efflux transporter gene, highly expressed in the GIT, bile ducts, kidneys, and blood–tissue barriers. It protects against drugs and endogenous molecules [82]. An association of ABCB1 with the incidence of anthracyclines toxicity was reported previously [25], especially neutropenia [83,84]. While we found no significant genotype-related differences in neutropenia and lymphocytopenia incidence, recurrent neutropenia and thrombocytopenia were observed only in the GG genotype carriers. The expression of the ABCB1 efflux transporter is high in the hematopoietic and lymphocyte cells [85]. The myelocyte efflux of doxorubicin may be impaired by having the G allele of ABCB1 (rs1045642), increasing its hematological toxicity.
Likewise, previous research aimed to assess the use of ABCB1 polymorphism as a predictor of neutropenia with amrubicin, which is one of the anthracyclines. They found that carriers of the homozygous common type (GG) of ABCB1 (rs1045642) were at higher risk of developing severe amrubicin-induced neutropenia. The results indicated that ABCB1 SNP might be a good predictor of worse AC regimen-induced neutropenia [84]. Conversely, there was no influence of the ABCB1 genetic polymorphism on hematological toxicity in previous research [41]. Polymorphic variants in the efflux transporter gene ABCB1 may predict fluorouracil, adriamycin, and cytoxan (FAC) regimen’s myelotoxicity, except for leukopenia [31]. Tecza et al. linked ABCB1 polymorphisms (p.Ile1145=, C allele) to recurrent anemia due to slower drug clearance [31]. However, our study found no significant difference between the ABCB1 genotypes, concerning anemia occurrence.
Hair follicles express ABCB1 transporter proteins, which protect against chemotherapy-induced alopecia by reducing its accumulation in the hair follicle epithelium [86,87]. However, although recurrent alopecia occurred in all genotype groups of the ABCB1 gene, no significant difference was found between ABCB1 genotypes and its occurrence. Recurrent mucositis and vomiting only occurred in the AA and the GA genotype carriers.
Factors that could justify that some of this study’s results differ from the aforementioned studies are the differences in ethnicity, sample size, and cancer characteristics [72,88]. Studying genetic polymorphisms in transporter and metabolizing genes is a reliable pharmacological tool that can be utilized to understand differences in chemotoxicity. The current study presents evidence of the importance of assessing gene polymorphisms that influence chemotherapy. Particularly, we found that certain functional alleles are significantly associated with AC chemotoxicity in BC patients. This can be used in the future as a screening tool for subjects carrying at-risk genotypes, paving the road for precision medicine and providing a rational use of resources [89,90].
Nonetheless, further pretreatment could be employed at high risk for chemotoxicity patients. Patients at increased risk of AC therapy-induced myelosuppression may be pre-treated with iron, vitamin B6, folic acid, erythropoiesis-stimulating drugs, or colony-stimulating factors, based on their genotype. Those at higher risk for gastrointestinal toxicity may need a modified antiemetic regimen and a modified diet [31].
The present study has several strengths. To date, our research is the first to explore the effect of the SNPs in the CYP2C19 (rs12248560), ALDH3A1 (rs2228100), ABCB1 (rs1045642), and SLC22A16 (rs6907567) genes on the AC regimen toxicity in Egyptian female patients. Unlike most previous research that focused on a single toxicity type, our study considered several types of toxicities (hematological, gastrointestinal, and miscellaneous). Moreover, we analyzed a prospective cohort. However, this study has some limitations.
First, the small cohort size may limit our ability to detect true associations. Therefore, studying larger cohorts in the future may provide more robust evidence for these associations, facilitating translational research based on the efficacy of the genotype-guided individualization of BC patients. However, the cost-effectiveness of testing large population samples is still questionable. So, this potential benefit should be weighed against the genotyping patients to detect those carrying rare variants of interest. Second, we analyzed only four genes involved in the AC regimen pharmacokinetic pathway, which does not completely cover all the important genes in the transport and metabolism pathways. Finally, our study was carried on Egyptian female BC patients only. Future research should examine genetic variations in male patients and more ethnically diverse groups.

4. Materials and Methods

4.1. Setting

National Cancer Institute and Al-Hussain University Hospital, Cairo, Egypt.

4.2. Study Design

This research follows a prospective cohort study design.

4.3. Inclusion Criteria

The study included female breast cancer patients aged 18 to 69 years who were receiving the doxorubicin and cyclophosphamide (AC) chemotherapy regimen. The AC regimen consisted of intravenous administration of 60 mg/m2 of doxorubicin (Adriamycin, Pfizer, New York, NY, USA) and 600 mg/m2 of cyclophosphamide (Endoxan, Baxter, Halle, Germany) on the first day of a 21-day cycle, repeated for four cycles.

4.4. Exclusion Criteria

Patients with any other types of malignancies, previously treated for metastatic disease, with any bone marrow disease, serious cardiac disease, uncontrolled medical conditions, pregnancy, or breastfeeding females were excluded.

4.5. Study Procedure and Endpoints

4.5.1. Demographic and Clinical Data

Demographic and clinical data were collected from patient records. Patient data were extracted from medical records and included age, body surface area, marital status, menopausal status, history of oral contraception use, family history, smoking history, affected breast, tumor staging, lymph node involvement, receptor status, histopathological classification, age at diagnosis, type of surgery, chemotherapy setting (neoadjuvant/adjuvant), and number of treatment cycles.

4.5.2. Adverse Events Reporting

Adverse events that occurred at any time point during therapy were reported in accordance with the Common Terminology Criteria for Adverse Events (CTCAEs) [91]. The reported toxicity of the AC regimen included the following:
(a)
Hematological toxicities included thrombocytopenia, leukopenia, neutropenia, lymphocytopenia, and anemia. These were assessed through using complete blood count analysis using venous blood samples and were collected in tubes coated with the corresponding amount of ethylenediamine-tetra acetic acid (EDTA). Blood films were stained with Giemsa stain and analyzed before treatment initiation and after each chemotherapy cycle using a Sysmex XN-550 hematology analyzer [92].
(b)
Non-hematological toxicities: Data were collected from patient records and telephone follow-ups. Non-hematological toxicities included gastrointestinal (GIT) symptoms such as nausea, vomiting, diarrhea, constipation, mucositis, and stomachache, as well as other miscellaneous toxicities such as fever, fatigue, amenorrhea, alopecia, headache, skin toxicity, and peripheral neuropathy.

4.5.3. Sampling and Genotyping

Venous blood samples (5 mL) were withdrawn from each participant. Baseline hematological parameters, including absolute neutrophil count, absolute lymphocyte count, platelet count, liver and kidney function tests, were recorded to assess toxicity at baseline and after each chemotherapy cycle. DNA was extracted from venous blood samples, using Gene JET Whole Blood Genomic DNA Purification Mini Kit (Thermo Fisher Scientific, Vilnius, Lithuania). Then, the extracted DNA concentration was measured by a Nanodrop-2000 (Thermo Scientific) by measuring the optical density at a wave-length of 260 nm to check the purification of the samples. The genotyping of CYP2C19, ALDH3A1, ABCB1, and SLC22A16 was performed using real-time PCR (Stepone plus Real-Time PCR, Applied Biosystem, Foster City, CA, USA).
Analysis of data were based on the TaqMan® MGB Probes for allelic discrimination, following the manufacturer’s instructions. Genotyping data were analyzed using TaqMan® Genotyper™ Software (version V1.7.1).

4.6. Statistical Analysis

Data were cleaned and analyzed using Excel 365, Minitab 20, and IBM SPSS 26. Quantitative variables included age, body surface area, number of positive lymph nodes, and number of lymph nodes removed. Qualitative variables, including marital status, menopausal status, oral contraception use, family history of BC, smoking history, type of surgery, affected breast, tumor staging (T and N stage), histopathological classification, hormone receptor status (estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2), and chemotherapy setting (adjuvant/neoadjuvant). Descriptive statistics, including the mean and standard error of the mean were calculated for each genotype. The count and percentage were calculated for the qualitative variables of hormonal status concerning each genotype. Inferential statistics were used to compare between different groups. Box–Cox transformation was used for non-normally distributed variables, following the optimal lambda (λ) method. Data transformations were applied where necessary to meet parametric assumptions. Model fit was assessed using normal residual probability plots.
Qualitative variables (thrombocytopenia, thrombocytosis, leucopenia, leukocytosis, neutropenia, lymphocytopenia, lymphocytosis, anemia, fever, fatigue, nausea, vomiting, diarrhea, constipation, mucositis, amenorrhea, alopecia, headache, skin toxicity, stomachache, and peripheral neuropathy) were analyzed for association with different alleles of CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes and tested using Chi-square (X2) test.
Quantitative variables (age, body surface area, number of positive lymph nodes, number of lymph nodes removed, hemoglobin, platelets, absolute neutrophil count, white blood cell (WBC) count, absolute lymphocyte count, thrombocytopenia, thrombocytosis, leucopenia, leukocytosis, neutropenia, lymphocytopenia, lymphocytosis, anemia, fever, fatigue, nausea, vomiting, diarrhea, constipation, mucositis, amenorrhea, alopecia, headache, skin toxicity, stomachache, and peripheral neuropathy) correlation with different alleles were tested using different tests including Student’s t-test, one-way ANOVA and two-way analysis of variance (ANOVA) under fit general linear model, with one-repeated-measure analysis where five-time points were included for each side effect (before treatment initiation and after each of the four treatment cycles).
Results showed a good fit for different models. The normal residual probability plots showed a linear attitude for all analyses after the transformation of the data. The p-value was considered significant at p < 0.05. Post hoc analyses of the interactions among all groups were performed using the Tukey test for pairs comparison. The results of the post hoc analyses were represented as letters where groups with the same letters were non-significantly different, while different letters meant significant variation among different groups. Interval plots of quantitative variables showing the mean and median of each variable concerning different genotypes with a 95% confidence interval were generated using Minitab 20.

5. Conclusions

In conclusion, this study identified a significant correlation between the SNP variations of the ALDH3A1 (rs2228100) gene, which plays a role in drug metabolism, and AC regimen-related toxicities in female BC patients. Although the SNPs in CYP2C19 (rs12248560), ABCB1 (rs1045642), and SLC22A16 (rs6907567) genes did not show significant differences between variant alleles in the occurrence of toxicities from the AC regimen, certain genotypes showed a significant influence on the recurrence of certain adverse effects. Given the modest impact linked to each genetic variant identified in our study, future research utilizing multifactorial polymorphic models in larger cohorts is necessary to validate these findings. Such studies may offer valuable insights for personalizing breast cancer treatments, ensuring that genetic screening can be incorporated into clinical practice. The results of this study may provide a rapid, high-accuracy pre-treatment test that helps to spare patients who are likely to exhibit low tolerance to AC treatment, hence increasing the likelihood of completing chemotherapy without delays or morbidity and preserving quality of life by prescribing an alternative treatment.

Author Contributions

Conceptualization, H.A.S. and A.B.K.; methodology, M.N.A., E.K.A., and S.M.H.; software, B.A.A. and A.S.; validation, M.N.A.; formal analysis, W.E.-S.; investigation, M.N.A.; resources, M.N.A.; data curation, A.M.T.; writing—original draft preparation, H.A.M.M., E.K.A., and S.M.H.; writing—review and editing, H.A.M.M. and A.B.K.; visualization, H.A.M.M. and W.E.-S.; supervision, H.A.S. and A.M.T.; project administration, A.B.K., H.A.M.M., and H.A.S.; funding acquisition, B.A.A. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R142), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

This research was approved by the Research Ethical Committee (REC) and the Medical Ethics Committee of the National Cancer Institute, Egypt, number (201819010.4). The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of AL-Azhar University, Egypt, number (0000012) on 19 March 2019, where the patients were recruited and injected. This work was registered as two studies in the “ClinicalTrials.gov” public website (identifier: NCT04654195) where the patients were recruited and injected.

Informed Consent Statement

Written informed consent has been obtained from the patients to publish this paper.

Data Availability Statement

Data are available from the corresponding author (H.A.A.M.) upon reasonable request due to patients privacy.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Count and percentage of each genotype group among the 96 patients along the CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes.
Table A1. Count and percentage of each genotype group among the 96 patients along the CYP2C19, ALDH3A1, SLC22A16, and ABCB1 genes.
CYP2C19Count (%)CYP2C19Count (%)
CC64 (66.67)CC64 (66.67)
CT28 (29.17)CT+TT32 (33.33)
TT4 (4.17)N=96 (100)
N=96 (100)
ALDH3A1Count (%)ALDH3A1Count (%)
CC11 (11.46)GC+CC50 (52.08)
GC39 (40.63)GG46 (47.92)
GG46 (47.92)N=96 (100)
N=96 (100)
SLC22A16Count (%)SLC22A16Count (%)
AA47 (48.96)AA47 (48.96)
GA38 (39.58)GG+GA49 (51.04)
GG11 (11.46)N=96 (100)
N=96 (100)
ABCB1Count (%)ABCB1Count (%)
AA11 (11.46)GA+AA47(48.96)
GA38 (39.58)GG49(51.04)
GG47 (48.96)N=96 (100)
N=96 (100)
Data expressed as n (%).

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Table 1. Patients’ characteristics.
Table 1. Patients’ characteristics.
Gene type(a) Metabolizing enzyme genes(b) Transporting enzyme genes
GeneCYP2C19ALDH3A1SLC22A16ABCB1
ParameterCCCT+TTp-valueGC+CCGGp-valueAAGG+GAp-valueAA+GAGGp-value
Age (year)47.2 ± 9.8845 ± 11.33NS46.94 ± 10.6345.96 ± 10.2NS44.94 ± 11.6647.94 ± 8.86NS45.94 ± 1.547.02 ± 1.51NS
BSA (m2)1.86 ± 0.151.82 ± 0.19NS1.86 ± 0.161.83 ± 0.16NS1.83 ± 0.161.86 ± 0.16NS1.85 ± 0.021.84 ± 0.02NS
No. of lymph nodes removed13.12 ± 7.8914.28 ± 7.07NS14.4 ± 8.2412.64 ± 6.93NS13.27 ± 7.813.74 ± 7.48NS13.6 ± 1.3113.4 ± 0.98NS
No. of +ve lymph nodes2.42 ± 3.273.34 ± 6.22NS2.91 ± 5.342.91 ± 5.34NS2.8 ± 3.552.64 ± 5.23NS2.64 ± 0.552.8 ± 0.76NS
Marital statusMissed1 (2)0 (0)0.360 (0)1 (2)0.661 (2)0(0)0.221 (2)0(0)0.039 *
Married52(81)30(94) 42(84)40(87) 42(89)40(82) 37(75.5)45(95.7)
Single3(5)0(0) 2(4)1(2) 0(0)3(6) 3(6.1)0(0)
Was married8(13)2(6) 6(12)4(9) 4(9)6(12) 8(16.3)2(4.3)
Menopausal statusPostmenopausal24(38)13(41)0.7721(42)16(35)0.4715(32)22(45)0.1917(34.7)20(42.6)0.429
Premenopausal40(63)19(59) 29(58)30(65) 32(68)27(55) 32(65.3)27(57.4)
Oral contraceptionMissed4(6)4(13)0.384(8)4(9)0.993(6)5(10)0.735(10.2)3(6.4)0.726
No32(50)12(38) 23(46)21(46) 21(45)23(47) 21(42.9)23(48.9)
Yes28(44)16(50) 23(46)21(46) 23(49)21(43) 23(46.9)21(44.7)
Family historyMissed3(5)4(13)0.224(8)3(7)0.512(4)5(10)0.55(10.2)2(4.3)
No44(69)17(53) 34(68)27(59) 30(64)31(63) 32(65.3)29(61.7)0.375
Yes17(27)11(34) 12(24)16(35) 15(32)13(27) 12(24.5)16(34)
Smoking historyNo63(98)32(100)0.4849(98)46(100)0.3446(98)49(100)0.3149(100)46(97.9)0.305
Yes1(2)0(0) 1(2)0(0) 1(2)0(0) 0(0)1(2.1)
Type of surgeryMissed0(0)1(3)0.171(2)0(0)0.40(0)1(2)0.811(2.04)0(0)0.599
BCS6(9)2(6) 3(6)5(11) 4(9)4(8) 3(6.12)5(10.64)
MRM49(77)28(88) 39(78)38(83) 38(81)39(80) 39(79.59)38(80.85)
No surgery9(14)1(3) 7(14)3(7) 5(11)5(10) 6(12.24)4(8.51)
Breast affectedBilateral1(2)0(0)0.361(2)0(0)0.330(0)1(2)0.191(2.04)0(0)0.477
Left36(56)14(44) 23(46)27(59) 21(45)29(59) 27(55.1)23(48.94)
Right27(42)18(56) 26(52)19(41) 26(55)19(39) 21(42.86)24(51.06)
Grade11(0)0(0)0.460(0)1(0)0.470(0)1(0)0.531(2.04)0(0)0.401
247(0)22(0) 36(0)33(0) 33(0)36(0) 37(75.51)32(69.57)
316(0)8(0) 14(0)10(0) 13(0)11(0) 10(20.41)14(30.43)
40(0)1(0) 0(0)1(0) 0(0)1(0) 1(2.04)0(0)
Stage-T12(0)3(0)0.331(0)4(0)0.14(0)1(0)0.261(2.33)4(9.3)0.165
227(0)10(0) 15(0)22(0) 20(0)17(0) 16(37.21)21(48.84)
315(0)4(0) 12(0)7(0) 10(0)9(0) 13(30.23)6(13.95)
416(0)9 (0) 16 (0)9 (0) 9 (0)16(0) 13(30.23)12 (27.91)
Stage-N018(0)6 (0)0.1912 (0)12(0)0.1913 (0)11(0)0.7613(30.23)11 (25.58)0.919
128 (0)18 (0) 26 (0)20(0) 23 (0)23(0) 23(53.49)23 (53.49)
211(0)1 (0) 3(0)9(0) 6 (0)6(0) 5 (11.63)7 (16.28)
33 (0)1 (0) 3(0)1(0) 1(0)3(0) 2(4.65)2(4.65)
Adjuvant/NeoadjuvantAdjuvant31(48)14 (44)0.6821(42)24(52)0.621(45)24(49)0.8422 (44.9)23 (48.94)0.41
Neoadjuvant29 (45)17(53) 26(52)20(43) 23 (49)23(47) 23(46.94)23 (48.94)
Palliative4 (6)1(3) 3(6)2(4) 3(6)2(4) 4(8.16)1(2.13)
Pathological typeMissed0 (0)1(3)0.370(0)1(2)0.560 (0)1(2)0.681(2.04)0(0)0.549
Invasive duct/lobular carcinoma1(2)0(0) 0(0)1(2) 0(0)1(2) 1(2.04)0(0)
Invasive cribriform carcinoma1(2)0(0) 1(2)0(0) 1(2)0(0) 1(2.04)0(0)
Invasive duct carcinoma58(91)28 (88) 44(88)42(91) 42(89)44(90) 43 (87.76)43 (91.49)
Invasive lobular carcinoma2(3)2(6) 3(6)1(2) 2(4)2(4) 1(2.04)3(6.38)
Invasive mammary carcinoma2(3)0(0) 1(2)1(2) 1(2)1(2) 1(2.04)1(2.13)
Invasive micropapillary carcinoma0(0)1(3) 1(2)0(0) 1(2)0(0) 1(2.04)0(0)
ERMissed1(2)2 (6)0.571(2)2(4)0.442(4)1(2)0.641(2.04)2(4.26)0.692
Negative16(25)8 (25) 15(30)9(20) 13(28)11(22) 13(26.53)11(23.4)
Positive46(72)22 (69) 33(66)35(76) 32(68)36(73) 34(69.39)34(72.34)
Rt−/left+1(2)0 (0) 1(2)0(0) 0 (0)1(2) 1(2.04)0(0)
PRMissed1(2)2 (6)0.551 (2)2(4)0.682 (4)1(2)0.441(2.04)2 (4.26)0.853
Negative2(3)0 (0) 1(2)1(2) 0 (0)2(4) 1(2.04)1(2.13)
Negative17(27)8 (25) 11 (22)14(30) 11(23)14(29) 13(26.53)12 (25.53)
Positive43(67)22(69) 36(72)29(63) 34 (72)31(63) 33(67.35)32 (68.09)
Rt−/left+1(2)0(0) 1(2)0(0) 0(0)1(2) 1(2.04)0(0)
HER2Missed1(2)2(6)0.531(2)2(4)0.622(4)1(2)0.441(2.04)2(4.26)0.727
Equivocal3(5)1(3) 3(6)1(2) 3(6)1(2) 3(6.12)1(2.13)
Negative44(69)19(59) 31(62)32(70) 32 (68)31(63) 32(65.31)31(65.96)
Positive16(25)10(31) 15 (30)11(24) 10 (21)16(33) 13(26.53)13(27.66)
Data expressed as mean ± standard deviation (SD) or n (%). BCS: Breast-conserving surgery. BSA: body surface area. ER: estrogen receptor. HER2: human epidermal growth factor receptor. MRM: Modified radical mastectomy. No significant difference between the genotype groups (p-value > 0.05). PR: progesterone receptor. Stage-N: whether the tumor spread to the lymph node. Stage-T: size of tumor. *: means statistically significant.
Table 2. Hematological toxicity correlation with the genotype groups of CYP2C19 gene assessed at different time points.
Table 2. Hematological toxicity correlation with the genotype groups of CYP2C19 gene assessed at different time points.
CYP2C19
Parameter CCCT+TTp Value
Thrombocytopenia A063 (100)32 (100)NA
Thrombocytopenia B062 (97)29 (97)0.96
12 (3)1 (3)
Thrombocytopenia C062 (97)30 (97)0.98
12 (3)1 (3)
Thrombocytopenia D062 (100)29 (97)0.15
10 (0)1 (3)
Thrombocytopenia E054 (96)25 (96)0.68
11 (2)0 (0)
21 (2)1(4)
Leukopenia A064 (100)32 (100)NA
Leukopenia B059 (92)29 (97)0.66
14 (6)1 (3)
21 (2)0 (0)
Leukopenia C054 (86)30 (97)0.26
18 (13)1 (3)
21 (2)0 (0)
Leukopenia D053 (85)26 (87)0.84
16 (10)2 (7)
23 (5)2 (7)
Leukopenia E047 (84)25 (96)0.37
15 (9)0 (0)
23 (5)1 (4)
41 (2)0 (0)
Neutropenia A062 (100)32 (100)NA
Neutropenia B059 (92)30 (97)0.77
11 (2)0 (0)
23 (5)1 (3)
31 (2)0 (0)
Neutropenia C045 (70)26 (84)0.26
14 (6)0 (0)
23 (5)0 (0)
312(19)5 (16)
Neutropenia D056(90)29(97)0.49
12(3)0(0)
24(6)1(3)
Neutropenia E044(79)22(85)0.5
10(0)1(4)
24(7)1(4)
31(2)0(0)
47 (13)2(8)
Lymphocytopenia A064 (100)32(100)NA
Lymphocytopenia B057 (90)27(90)0.07
16 (10)1(3)
20 (0)2 (7)
Lymphocytopenia C054 (84)28(88)0.9
17 (11)3 (9)
22 (3)1 (3)
31 (2)0 (0)
Lymphocytopenia D048 (77)20 (67)0.48
111 (18)7 (23)
23 (5)3 (10)
Lymphocytopenia E035 (63)16 (62)0.9
113 (23)7 (27)
26 (11)3 (12)
31 (2)0 (0)
41 (2)0 (0)
Anemia A056 (89)26 (81)0.29
13 (5)5 (16)
23 (5)1 (3)
31 (2)0 (0)
Anemia B049 (78)23 (77)0.81
18 (13)5 (17)
26 (10)2 (7)
Anemia C043 (68)20 (65)0.87
114 (22)7(23)
26 (10)4 (13)
Anemia D041(67)18 (60)0.4
111(18)9 (30)
29 (15)3 (10)
Anemia E033 (60)14(54)0.41
114 (25)6 (23)
26 (11)6 (23)
32 (4)0 (0)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 3. Hematological toxicity correlation with the genotype groups of ALDH3A1 gene assessed at different time points.
Table 3. Hematological toxicity correlation with the genotype groups of ALDH3A1 gene assessed at different time points.
ALDH3A1
Parameter GC+CCGGp Value
Thrombocytopenia A050(100)45(100)NA
Thrombocytopenia B047(96)44(98)0.61
12(4)1(2)
Thrombocytopenia C048(98)44(96)0.52
11(2)2(4)
Thrombocytopenia D048(100)43(98)0.29
10 (0)1 (2)
Thrombocytopenia E041 (98)38 (95)0.22
11 (2)0 (0)
20 (0)2 (5)
Leukopenia A050 (100)46 (100)NA
Leukopenia B046 (94)42(93)0.55
13 (6)2 (4)
20 (0)1 (2)
Leukopenia C044 (90)40 (89)0.57
15 (10)4(9)
20 (0)1(2)
Leukopenia D044 (92)35 (80)0.21
13 (6)5 (11)
21 (2)4 (9)
Leukopenia E039 (93)33(83)0.45
12 (5)3(8)
21 (2)3(8)
40 (0)1(3)
Neutropenia A049 (100)45(100)NA
Neutropenia B047 (94)42(93)0.39
10 (0)1(2)
23 (6)1(2)
30(0)1(2)
Neutropenia C036 (73)35 (76)0.62
11 (2)3 (7)
22 (4)1 (2)
310 (20)7 (15)
Neutropenia D046 (96)39 (89)0.33
11 (2)1 (2)
21 (2)4 (9)
Neutropenia E036 (86)30 (75)0.45
10(0)1 (3)
22(5)3 (8)
31 (2)0 (0)
43 (7)6 (15)
Lymphocytopenia A050 (100)46 (100)NA
Lymphocytopenia B045 (94)39 (87)0.45
12 (4)5 (11)
21 (2)1 (2)
Lymphocytopenia C044 (88)38 (83)0.66
15(10)5 (11)
21 (2)2 (4)
30 (0)1 (2)
Lymphocytopenia D035 (73)33 (75)0.49
111 (23)7 (16)
22 (4)4 (9)
Lymphocytopenia E028 (67)23 (58)0.49
110 (24)10 (25)
23 (7)6 (15)
31 (2)0 (0)
40 (0)1 (3)
Anemia A041 (82)41 (91)0.43
16(12)2 (4)
22 (4)2 (4)
31 (2)0 (0)
Anemia B040 (82)32 (73)0.52
15 (10)8 (18)
24 (8)4 (9)
Anemia C035 (71)28 (62)0.59
110 (20)11(24)
24 (8)6 (13)
Anemia D035 (73)24 (56)0.17
17 (15)13 (30)
26 (13)6 (14)
Anemia E027 (64)20 (51)0.69
19 (21)11(28)
25 (12)7 (18)
31 (2)1 (3)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 4. Hematological toxicity correlation with the genotype groups of SLC22A16 gene assessed at different time points.
Table 4. Hematological toxicity correlation with the genotype groups of SLC22A16 gene assessed at different time points.
SLC22A16
ParameterSide EffectAAGG+GAp Value
Thrombocytopenia A047 (100)48 (100)NA
Thrombocytopenia B043(96)48 (98)0.51
12 (4)1(2)
Thrombocytopenia C046 (98)46 (96)0.57
11 (2)2 (4)
Thrombocytopenia D044 (98)47 (100)0.3
11(2)0 (0)
Thrombocytopenia E041 (95)38 (97)0.63
11 (2)0 (0)
21 (2)1 (3)
Leucopenia A047(100)49 (100)NA
Leucopenia B042 (93)46 (94)0.55
13 (7)2(4)
20 (0)1(2)
Leucopenia C041(87)43 (91)0.36
16 (13)3 (6)
20 (0)1 (2)
Leucopenia D038(84)41(87)0.68
15(11)3 (6)
22(4)3(6)
Leucopenia E041(95)31(79)0.17
11(2)4 (10)
21(2)3 (8)
40 (0)1 (3)
Neutropenic A046 (100)48 (100)NA
Neutropenia B043 (93)46 (94)0.39
10 (0)1 (2)
23 (7)1(2)
30 (0)1 (2)
Neutropenia C035 (74)36(75)0.32
12 (4)2 (4)
20 (0)3 (6)
310 (21)7(15)
Neutropenia D041(91)44 (94)0.32
12 (4)0 (0)
22 (4)3 (6)
Neutropenia E033(77)33 (85)0.56
11 (2)0 (0)
23 (7)2 (5)
30 (0)1 (3)
46 (14)3 (8)
Lymphocytopenia A047 (100)49 (100)NA
Lymphocytopenia B039 (87)45 (94)0.45
15 (11)2 (4)
21 (2)1 (2)
Lymphocytopenia C039 (83)43 (88)0.6
16 (13)4 (8)
22 (4)1 (2)
30 (0)1(2)
Lymphocytopenia D035 (78)33(70)0.64
17(16)11 (23)
23 (7)3 (6)
Lymphocytopenia E027(63)24 (62)0.23
18 (19)12 (31)
27 (16)2 (5)
31 (2)0 (0)
40 (0)1 (3)
Anemia A042 (89)40 (83)0.67
13(6)5 (10)
22 (4)2 (4)
30 (0)1 (2)
Anemia B035 (78)37 (77)0.98
16 (13)7 (15)
24 (9)4 (8)
Anemia C031 (66)32 (68)0.66
112 (26)9 (19)
24 (9)6 (13)
Anemia D029 (64)30 (65)1
110 (22)10(22)
26 (13)6 (13)
Anemia E024 (56)23 (61)0.35
111 (26)9 (24)
28 (19)4 (11)
30 (0)2 (5)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 5. Hematological toxicity correlation with the genotype groups of ABCB1 gene assessed at different time points.
Table 5. Hematological toxicity correlation with the genotype groups of ABCB1 gene assessed at different time points.
ABCB1
AA+GAGGp-value
Thrombocytopenia A048 (100)47 (100)NA
Thrombocytopenia B048 (97.96)43 (95.56)0.508
11 (2.04)2(4.44)
Thrombocytopenia C047 (97.92)45 (95.74)0.545
11 (2.08)2(4.26)
Thrombocytopenia D046 (100)45 (97.83)0.315
10 (0)1 (2.17)
Thrombocytopenia E040 (100)39 (92.86)0.227
10 (0)1(2.38)
20 (0)2 (4.76)
Leucopenia A049 (100)47 (100)NA
leucopenia B047 (95.92)41(91.11)0.486
12 (4.08)3 (6.67)
20 (0)1(2.22)
Leucopenia C046 (95.83)38 (82.61)0.105
12 (4.17)7 (15.22)
20 (0)1(2.17)
Leucopenia D041(89.13)38 (82.61)0.384
14 (8.7)4(8.7)
21 (2.17)4 (8.7)
Leucopenia E035 (87.5)37 (88.1)0.751
13 (7.5)2 (4.76)
22 (5)2 (4.76)
40(0)1 (2.38)
Neutropenia A047(100)47 (100)NA
Neutropenia B046 (93.88)43 (93.48)0.390
11(2.04)0 (0)
21(2.04)3 (6.52)
31(2.04)0 (0)
Neutropenia C037(77.08)34 (72.34)0.680
11(2.08)3 (6.38)
22 (4.17)1 (2.13)
38 (16.67)9 (19.15)
Neutropenia D043 (93.48)42 (91.3)0.149
12 (4.35)0 (0)
21 (2.17)4 (8.7)
Neutropenia E033 (82.5)33 (78.57)0.533
10 (0)1 (2.38)
23 (7.5)2 (4.76)
31 (2.5)0 (0)
43 (7.5)6 (14.29)
Lymphocytopenia A049 (100)47 (100)NA
Lymphocytopenia B045 (91.84)39 (88.64)0.315
14 (8.16)3 (6.82)
20 (0)2 (4.55)
Lymphocytopenia C043 (87.76)39 (82.98)0.207
16 (12.24)4 (8.51)
20 (0)3 (6.38)
30 (0)1 (2.13)
Lymphocytopenia D038 (82.61)30 (65.22)0.106
15 (10.87)13 (28.26)
23 (6.52)3 (6.52)
Lymphocytopenia E027 (67.5)24 (57.14)0.655
19 (22.5)11 (26.19)
24 (10)5 (11.9)
30 (0)1 (2.38)
40 (0)1 (2.38)
Anemia A043 (89.58)39 (82.98)0.535
14 (8.33)4 (8.51)
21 (2.08)3 (6.38)
30 (0)1 (2.13)
Anemia B036 (75)36 (80)0.058
110 (20.83)3 (6.67)
22 (4.17)6 (13.33)
Anemia C033 (70.21)30 (63.83)0.744
110 (21.28)11 (23.4)
24 (8.51)6 (12.77)
Anemia D033 (73.33)26 (56.52)0.134
19 (20)11 (23.91)
23 (6.67)9 (19.57)
Anemia E024 (61.54)23 (54.76)0.328
111 (28.21)9 (21.43)
24 (10.26)8 (19.05)
30(0)2(4.76)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 6. GIT toxicity correlation with the genotype groups of CYP2C19 gene assessed at different time points.
Table 6. GIT toxicity correlation with the genotype groups of CYP2C19 gene assessed at different time points.
CYP2C19
Parameter CCCT+TTp value
Nausea A064 (100)32 (100)NA
Nausea B047 (73)19 (59)0.16
117 (27)13 (41)
Nausea C164 (100)32 (100)NA
Nausea D053 (84)25 (78)0.47
110 (16)7 (22)
Nausea E055 (86)26 (81)0.55
19 (14)6 (19)
Vomiting A064 (100)32 (100)NA
Vomiting B038 (59)23 (72)0.53
115 (23)5 (16)
29 (14)4 (13)
32 (3)0 (0)
Vomiting C039 (61)24 (75)0.47
115 (23)4 (13)
27 (11)2 (6)
33 (5)2 (6)
Vomiting D041(65)22 (69)0.22
118 (29)5 (16)
24 (6)4 (13)
30 (0)1 (3)
Vomiting E041 (65)24 (75)0.41
113 (21)7 (22)
28 (13)1 (3)
31 (2)0 (0)
Diarrhea A064 (100)32 (100)NA
Diarrhea B057 (89)28 (88)0.19
16 (9)2 (6)
20 (0)2 (6)
31 (2)0 (0)
Diarrhea C057 (89)29 (91)0.84
15 (8)2 (6)
21 (2)1 (3)
31 (2)0 (0)
Diarrhea D057 (90)30 (94)0.74
15 (8)2 (6)
31 (2)0 (0)
Diarrhea E057 (90)30 (94)0.74
15 (8)2 (6)
21 (2)0 (0)
Constipation A064 (100)32 (100)NA
Constipation B051 (80)24 (75)0.81
112 (19)7 (22)
21 (2)1 (3)
Constipation C049 (77)27 (84)0.65
113 (20)4 (13)
21(2)1 (3)
31 (2)0 (0)
Constipation D052 (83)28 (88)0.36
110(16)3 (9)
21(2)0 (0)
30 (0)1 (3)
Constipation E052 (83)29 (91)0.55
19 (14)2 (6)
21 (2)1 (3)
31 (2)0 (0)
Mucositis A064 (100)32 (100)NA
Mucositis B049 (77)27 (87)0.23
115 (23)4 (13)
Mucositis C051 (80)27 (84)0.58
113 (20)5 (16)
Mucositis D049 (78)28 (88)0.25
114 (22)4 (13)
Mucositis E050 (79)30 (94)0.07
113 (21)2 (6)
Stomachache A064 (100)32 (100)NA
Stomachache B054 (84)26 (81)0.7
110 (16)6 (19)
Stomachache C057 (89)28 (88)0.82
17(11)4(13)
Stomachache D058 (91)27(84)0.37
16 (9)5 (16)
Stomachache E053 (85)28 (88)0.79
19 (15)4 (13)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 7. GIT toxicity correlation with the genotype groups of ALDH3A1 gene assessed at different time points.
Table 7. GIT toxicity correlation with the genotype groups of ALDH3A1 gene assessed at different time points.
ALDH3A1
Parameter GC+CCGGp value
Nausea A050 (100)46 (100)NA
Nausea B033 (66)33 (72)0.54
117 (34)13 (28)
Nausea C150 (100)46 (100)NA
Nausea D036 (73)42 (91)0.023 *
113(27)4 (9)
Nausea E039 (78)42 (91)0.07
111 (22)4 (9)
Vomiting A050 (100)46 (100)NA
Vomiting B031(62)30 (65)0.5
113 (26)7(15)
25 (10)8(17)
31 (2)1 (2)
Vomiting C036 (72)27(59)0.18
16 (12)13 (28)
26 (12)3 (7)
32 (4)3 (7)
Vomiting D033 (67)30 (65)0.66
112 (24)11 (24)
23 (6)5 (11)
31(2)0 (0)
Vomiting E035 (71)30 (65)0.66
19 (18)11 (24)
25(10)4 (9)
30(0)1 (2)
Diarrhea A050(100)46 (100)NA
Diarrhea B043(86)42 (91)0.42
14(8)4 (9)
22 (4)0 (0)
31 (2)0 (0)
Diarrhea C044 (88)42 (91)0.8
14 (8)3 (7)
21 (2)1 (2)
31 (2)0 (0)
Diarrhea D044 (90)43 (93)0.59
14 (8)3 (7)
31 (2)0 (0)
Diarrhea E044 (90)43 (93)0.59
14 (8)3 (7)
21 (2)0 (0)
Constipation A050 (100)46 (100)NA
Constipation B043 (86)32 (70)0.09
17 (14)12 (26)
20 (0)2 (4)
Constipation C043 (86)33 (72)0.2
17 (14)10 (22)
20 (0)2 (4)
30 (0)1 (2)
Constipation D045 (92)35 (76)0.17
14 (8)9 (20)
20 (0)1 (2)
30 (0)1 (2)
Constipation E045 (92)36 (78)0.19
14 (8)7 (15)
20 (0)2 (4)
30 (0)1 (2)
Mucositis A050 (100)46 (100)NA
Mucositis B040 (82)36 (78)0.68
19 (18)10 (22)
Mucositis C041(82)37 (80)0.84
19(18)9 (20)
Mucositis D041(84)36 (78)0.5
18(16)10 (22)
Mucositis E043(88)37 (80)0.33
16(12)9 (20)
Stomachache A050(100)46 (100)NA
Stomachache B045(90)35 (76)0.07
15(10)11 (24)
Stomachache C046(92)39(85)0.27
14(8)7 (15)
Stomachache D041(82)44 (96)0.036 *
19(18)2 (4)
Stomachache E044(92)37 (80)0.11
14(8)9 (20)
Data expressed as n (%). *: means statistically significant. NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 8. GIT toxicity correlation with the genotype groups of SLC22A16 gene assessed at different time points.
Table 8. GIT toxicity correlation with the genotype groups of SLC22A16 gene assessed at different time points.
ParameterSide EffectAAGG+GAp Value
Nausea A047(100)49(100)NA
Nausea B032(68)34(69)0.89
115(32)15(31)
Nausea C147(100)49(100)NA
Nausea D038(81)40(83)0.75
19(19)8(17)
Nausea E040(85)41(84)0.85
17(15)8(16)
Vomiting A047(100)49(100)NA
Vomiting B027(57)34(69)0.15
113(28)7(14)
25(11)8(16)
32(4)0(0)
Vomiting C032(68)31(63)0.75
110(21)9(18)
23(6)6(12)
32(4)3(6)
Vomiting D032(68)31(65)0.67
111(23)12(25)
23(6)5(10)
31(2)0(0)
Vomiting E034(72)31(65)0.51
19(19)11(23)
23(6)6(13)
31(2)0(0)
Diarrhea A047(100)49(100)NA
Diarrhea B043(91)42(86)0.4
14(9)4(8)
20(0)2(4)
30(0)1(2)
Diarrhea C044(94)42(86)0.51
12(4)5(10)
21(2)1(2)
30(0)1(2)
Diarrhea D044(94)43(90)0.56
13(6)4(8)
30(0)1(2)
Diarrhea E044(94)43(90)0.56
13(6)4(8)
20(0)1(2)
Constipation A047(100)49(100)NA
Constipation B039(83)36(73)0.28
18(17)11(22)
20(0)2(4)
Constipation C038(81)38(78)0.39
19(19)8(16)
20(0)2(4)
30(0)1(2)
Constipation D040(85)40(83)0.56
17(15)6(13)
20(0)1(2)
30(0)1(2)
Constipation E043(91)38(79)0.25
14(9)7(15)
20(0)2(4)
30(0)1(2)
Mucositis A047(100)49(100)NA
Mucositis B036(77)40(83)0.41
111(23)8(17)
Mucositis C037(79)41(84)0.53
110(21)8(16)
Mucositis D036(77)41(85)0.27
111(23)7(15)
Mucositis E037(79)43(90)0.15
110(21)5(10)
Stomachache A047(100)49(100)NA
Stomachache B037(79)43(88)0.24
110(21)6(12)
stomachache C041(87)44(90)0.69
16(13)5(10)
Stomachache D040(85)45(92)0.3
17(15)4(8)
Stomachache E038(83)43(90)0.33
18(17)5(10)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 9. GIT toxicity correlation with the genotype groups of ABCB1 gene assessed at different time points.
Table 9. GIT toxicity correlation with the genotype groups of ABCB1 gene assessed at different time points.
ParameterSide EffectAA+GAGGp-Value
Nausea A049(100)47(100)NA
Nausea B037(75.5)29(61.7)0.145
112(24.5)18(38.3)
Nausea C149(100)47(100)NA
Nausea D042(85.7)36(78.3)0.344
17(14.3)10(21.7)
Nausea E043(87.8)38(80.9)0.352
16(12.2)9(19.1)
Vomiting grade A049(100)47(100)NA
Vomiting grade B035(71.4)26(55.3)0.207
16(12.2)14(29.8)
27(14.3)6(12.8)
31(2)1(2.1)
Vomiting grade C032(65.3)31(66)0.252
17(14.3)12(25.5)
26(12.2)3(6.4)
34(8.2)1(2.1)
Vomiting grade D032(65.3)31(67.4)0.345
110(20.4)13(28.3)
26(12.2)2(4.3)
31(2)0(0)
Vomiting grade E036(73.5)29(63)0.054
16(12.2)14(30.4)
27(14.3)2(4.3)
30(0)1(2.2)
Diarrhea grade A049(100)47(100)
Diarrhea grade B043(87.8)42(89.4)0.396
14(8.2)4(8.5)
22(4.1)0(0)
30(0)1(2.1)
Diarrhea grade C042(85.7)44(93.6)0.232
15(10.2)2(4.3)
22(4.1)0(0)
30(0)1(2.1)
Diarrhea grade D044(89.8)43(93.5)0.332
15(10.2)2(4.3)
30(0)1(2.2)
Diarrhea grade E044(89.8)43(93.5)0.332
15(10.2)2(4.3)
20(0)1(2.2)
Constipation grade A049(100)47(100)
Constipation grade B037(75.5)38(80.9)0.800
111(22.4)8(17)
21(2)1(2.1)
Constipation grade C038(77.6)38(80.9)0.797
19(18.4)8(17)
21(2)1(2.1)
31(2)0(0)
Constipation grade D041(83.7)39(84.8)0.565
17(14.3)6(13)
21(2)0(0)
30(0)1(2.2)
Constipation grade E042(85.7)39(84.8)0.775
15(10.2)6(13)
21(2)1(2.2)
31(2)0(0)
Mucositis A049(100)47(100)
Mucositis B037(77.1)39(83)0.473
111(22.9)8(17)
Mucositis C038(77.6)40(85.1)0.343
111(22.4)7(14.9)
Mucositis D039(79.6)38(82.6)0.708
110(20.4)8(17.4)
Mucositis E041(83.7)39(84.8)0.882
18(16.3)7(15.2)
Stomachache A049(100)47(100)
Stomachache B041(83.7)39(83)0.927
18(16.3)8(17)
Stomachache C044(89.8)41(87.2)0.694
15(10.2)6(12.8)
Stomachache D044(89.8)41(87.2)0.694
15(10.2)6(12.8)
Stomachache E042(87.5)39(84.8)0.703
16(12.5)7(15.2)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 10. Miscellaneous toxicity correlation with the genotype groups of CYP2C19 gene assessed at different time points.
Table 10. Miscellaneous toxicity correlation with the genotype groups of CYP2C19 gene assessed at different time points.
CYP2C19
Parameter CCCT+TTp value
Fever A064(100)32(100)NA
Fever B058(92)31(97)0.36
15(8)1(3)
Fever C060(94)31(97)0.52
14(6)1(3)
Fever D060(95)30(94)0.76
13(5)2(6)
Fever E062(97)32(100)0.31
12(3)0(0)
Fatigue A064(100)32(100)NA
Fatigue B044(69)19(59)0.36
120(31)13(41)
Fatigue C050(78)23(72)0.5
114(22)9(28)
Fatigue D052(83)24(75)0.39
111(17)8(25)
Fatigue E054(84)25(78)0.45
110(16)7(22)
Amenorrhea A064(100)32(100)NA
Amenorrhea B057(89)30(94)0.46
17(11)2(6)
Amenorrhea C061(97)30(94)0.48
12(3)2(6)
Amenorrhea D063(98)30(94)0.21
11(2)2(6)
Amenorrhea E061(97)31(97)0.99
12(3)1(3)
Alopecia A064(100)32(100)NA
Alopecia B164(100)32(100)NA
Alopecia C164(100)32(100)NA
Alopecia D164(100)32(100)NA
Alopecia E164(100)32(100)NA
Headache A064(100)32(100)NA
Headache B057(89)28(88)0.82
17(11)4(13)
Headache C061(95)30(94)0.75
13(5)2(6)
Headache D061(95)29(91)0.37
13(5)3(9)
Headache E060(94)30(94)1
14(6)2(6)
Skin toxicity A064(100)32(100)NA
Skin toxicity B051(80)27(84)0.58
113(20)5(16)
Skin toxicity C059(92)30(94)0.78
15(8)2(6)
Skin toxicity D055(86)30(94)0.26
19(14)2(6)
Skin toxicity E055(89)29(91)0.78
17(11)3(9)
Peripheral neuropathy A064(100)32(100)NA
Peripheral neuropathy B060(94)31(97)0.52
14(6)1(3)
Peripheral neuropathy C058(91)31(97)0.27
16(9)1(3)
Peripheral neuropathy D060(94)32(100)0.15
14(6)0(0)
Peripheral neuropathy E058(92)31(97)0.36
15(8)1(3)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 11. Miscellaneous toxicity correlation with the genotype groups of ALDH3A1 gene assessed at different time points.
Table 11. Miscellaneous toxicity correlation with the genotype groups of ALDH3A1 gene assessed at different time points.
ALDH3A1
ParameterGC+CCGGp value
Fever A050(100)46(100)NA
Fever B049(100)40(87)0.009 *
10(0)6(13)
Fever C050(100)41(89)0.017 *
10(0)5(11)
Fever D049(100)41(89)0.018 *
10(0)5(11)
Fever E050(100)44(96)0.14
10(0)2(4)
Fatigue A050(100)46(100)NA
Fatigue B039(78)24(52)0.008 *
111(22)22(48)
Fatigue C041(82)32(70)0.15
19(18)14(30)
Fatigue D041(84)35(76)0.36
18(16)11(24)
Fatigue E042(84)37(80)0.65
18(16)9(20)
Amenorrhea A050(100)46(100)NA
Amenorrhea B047(94)40(87)0.24
13(6)6(13)
Amenorrhea C047(96)44(96)0.95
12(4)2(4)
Amenorrhea D048(96)45(98)0.61
12(4)1(2)
Amenorrhea E047(96)45(98)0.6
12(4)1(2)
Alopecia A050(100)46(100)NA
Alopecia B150(100)46(100)NA
Alopecia C150(100)46(100)NA
Alopecia D150(100)46(100)NA
Alopecia E150(100)46(100)NA
Headache A050(100)46(100)NA
Headache B044(88)41(89)0.86
16(12)5(11)
Headache C048(96)43(93)0.58
12(4)3(7)
Headache D048(96)42(91)0.34
12(4)4(9)
Headache E048(96)42(91)0.34
12(4)4(9)
Skin toxicity A050(100)46(100)NA
Skin toxicity B039(78)39(85)0.4
111(22)7(15)
Skin toxicity C045(90)44(96)0.29
15(10)2(4)
Skin toxicity D046(92)39(85)0.27
14(8)7(15)
Skin toxicity E041(84)43(96)0.06
18(16)2(4)
Peripheral neuropathy A050(100)46(100)NA
Peripheral neuropathy B046(92)45(98)0.2
14(8)1(2)
Peripheral neuropathy C043(86)46(100)0.008 *
17(14)0(0)
Peripheral neuropathy D048(96)44(96)0.93
12(4)2(4)
Peripheral neuropathy E046(94)43(93)0.94
13(6)3(7)
Data expressed as n (%). *: means statistically significant. NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 12. Miscellaneous toxicity correlation with the genotype groups of SLC22A16 gene assessed at different time points.
Table 12. Miscellaneous toxicity correlation with the genotype groups of SLC22A16 gene assessed at different time points.
ParameterSide EffectAAGG+GAp Value
Fever A047(100)49(100)NA
Fever B043(91)46(96)0.38
14(9)2(4)
Fever C045(96)46(94)0.68
12(4)3(6)
Fever D045(96)45(94)0.66
12(4)3(6)
Fever E046(98)48(98)0.98
11(2)1(2)
Fatigue A047(100)49(100)NA
Fatigue B031(66)32(65)0.95
116(34)17(35)
Fatigue C034(72)39(80)0.41
113(28)10(20)
Fatigue D037(79)39(81)0.76
110(21)9(19)
Fatigue E039(83)40(82)0.86
18(17)9(18)
Amenorrhea A047(100)49(100)NA
Amenorrhea B043(91)44(90)0.78
14(9)5(10)
Amenorrhea C046(98)45(94)0.32
11(2)3(6)
Amenorrhea D046(98)47(96)0.58
11(2)2(4)
Amenorrhea E046(98)46(96)0.57
11(2)2(4)
Alopecia A047(100)49(100)NA
Alopecia B147(100)49(100)NA
Alopecia C147(100)49(100)NA
Alopecia D147(100)49(100)NA
Alopecia E147(100)49(100)NA
Headache A047(100)49(100)NA
Headache B040(85)45(92)0.3
17(15)4(8)
Headache C044(94)47(96)0.61
13(6)2(4)
Headache D044(94)46(94)0.96
13(6)3(6)
Headache E043(91)47(96)0.37
14(9)2(4)
Skin toxicity A047(100)49(100)NA
Skin toxicity B039(83)39(80)0.67
18(17)10(20)
Skin toxicity C043(91)46(94)0.65
14(9)3(6)
Skin toxicity D042(89)43(88)0.8
15(11)6(12)
Skin toxicity E043(91)41(87)0.5
14(9)6(13)
Peripheral neuropathy A047(100)49(100)NA
Peripheral neuropathy B044(94)47(96)0.61
13(6)2(4)
Peripheral neuropathy C044(94)45(92)0.74
13(6)4(8)
Peripheral neuropathy D044(94)48(98)0.29
13(6)1(2)
Peripheral neuropathy E045(96)44(92)0.41
12(4)4(8)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 13. Miscellaneous toxicity correlation with the genotype groups of ABCB1 gene assessed at different time points.
Table 13. Miscellaneous toxicity correlation with the genotype groups of ABCB1 gene assessed at different time points.
ABCB1
AA+GAGGp value
Fever A049(100)47(100)NA
Fever B045(91.8)44(95.7)0.445
14(8.2)2(4.3)
Fever C047(95.9)44(93.6)0.612
12(4.1)3(6.4)
Fever D046(93.9)44(95.7)0.699
13(6.1)2(4.3)
Fever E047(95.9)47(100)0.162
12(4.1)0(0)
Fatigue A049(100)47(100)NA
Fatigue B031(63.3)32(68.1)0.619
118(36.7)15(31.9)
Fatigue C038(77.6)35(74.5)0.724
111(22.4)12(25.5)
Fatigue D038(77.6)38(82.6)0.538
111(22.4)8(17.4)
Fatigue E038(77.6)41(87.2)0.214
111(22.4)6(12.8)
Amenorrhea A049(100)47(100)NA
Amenorrhea B043(87.8)44(93.6)0.325
16(12.2)3(6.4)
Amenorrhea C047(95.9)44(95.7)0.949
12(4.1)2(4.3)
Amenorrhea D047(95.9)46(97.9)0.582
12(4.1)1(2.1)
Amenorrhea E047(95.9)45(97.8)0.595
12(4.1)1(2.2)
Alopecia A049(100)47(100)NA
Alopecia B149(100)47(100)NA
Alopecia C149(100)47(100)NA
Alopecia D149(100)47(100)NA
Alopecia E149(100)47(100)NA
Headache A049(100)47(100)NA
Headache B043(87.8)42(89.4)0.805
16(12.2)5(10.6)
Headache C047(95.9)44(93.6)0.612
12(4.1)3(6.4)
Headache D046(93.9)44(93.6)0.958
13(6.1)3(6.4)
Headache E047(95.9)43(91.5)0.370
12(4.1)4(8.5)
Skin toxicity A049(100)47(100)NA
Skin toxicity B038(77.6)40(85.1)0.343
111(22.4)7(14.9)
Skin toxicity C045(91.8)44(93.6)0.737
14(8.2)3(6.4)
Skin toxicity D043(87.8)42(89.4)0.805
16(12.2)5(10.6)
Skin toxicity E043(87.8)41(91.1)0.598
16(12.2)4(8.9)
Peripheral neuropathy A049(100)47(100)NA
Peripheral neuropathy B046(93.9)45(95.7)0.681
13(6.1)2(4.3)
Peripheral neuropathy C044(89.8)45(95.7)0.262
15(10.2)2(4.3)
Peripheral neuropathy D046(93.9)46(97.9)0.328
13(6.1)1(2.1)
Peripheral neuropathy E044(89.8)45(97.8)0.108
15(10.2)1(2.2)
Data expressed as n (%). NA = non-applicable. Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy. The occurrence of adverse effects was categorized as follows: A score of 0 indicated that the side effect did not appear at any of the five recorded time points before or after treatment. A score of 1 was assigned if the side effect was absent before treatment but emerged during the course of treatment. A score of 2 indicated that the side effect was already present before treatment, regardless of whether it changed after treatment. A score of 3 was used if the side effect was persistent both before and after treatment. Lastly, a score of 4 signified that the side effect was absent before treatment but appeared consistently after each chemotherapy cycle.
Table 14. Hematological toxicity among the same genotype group data analysis using two-way with one-repeated-measure ANOVA test results.
Table 14. Hematological toxicity among the same genotype group data analysis using two-way with one-repeated-measure ANOVA test results.
CYP2C19Anemia GradeThrombocytopenia GradeLeukopenia GradeNeutropenia GradeLymphocytopenia Grade
CC A0.19 ± 0.07 A0 ± 0 A0 ± 0 B0 ± 0 C0 ± 0 C
CC B0.31 ± 0.08 A0.03 ± 0.02 A0.09 ± 0.04 AB0.16 ± 0.07 BC0.09 ± 0.04 BC
CC C0.41 ± 0.08 A0.03 ± 0.02 A0.16 ± 0.05 AB0.72 ± 0.15 A0.22 ± 0.07 ABC
CC D0.45 ± 0.09 A0 ± 0 A0.19 ± 0.06 AB0.16 ± 0.06 BC0.27 ± 0.07 ABC
CC E0.5 ± 0.1 A0.05 ± 0.03 A0.23 ± 0.09 A0.61 ± 0.17 AB0.5 ± 0.11 A
CT+TT A0.22 ± 0.09 A0 ± 0 A0 ± 0 AB0 ± 0 C0 ± 0 BC
CT+TT B0.28 ± 0.1 A0.03 ± 0.03 A0.03 ± 0.03 AB0.06 ± 0.06 BC0.16 ± 0.09 ABC
CT+TT C0.47 ± 0.13 A0.03 ± 0.03 A0.03 ± 0.03 AB0.47 ± 0.2 ABC0.16 ± 0.08 ABC
CT+TT D0.47 ± 0.12 A0.03 ± 0.03 A0.19 ± 0.09 AB0.06 ± 0.06 BC0.41 ± 0.12 AB
CT+TT E0.56 ± 0.14 A0.06 ± 0.06 A0.06 ± 0.06 AB0.34 ± 0.18 ABC0.41 ± 0.12 AB
ALDH3A1Anemia gradeThrombocytopenia gradeLeukopenia gradeNeutropenia gradeLymphocytopenia grade
GC+CC A0.26 ± 0.09 AB0 ± 0 D0 ± 0 A0 ± 0 C0 ± 0 A
GC+CC B0.26 ± 0.08 AB0.04 ± 0.03 AB0.06 ± 0.03 A0.12 ± 0.07 BC0.08 ± 0.05 A
GC+CC C0.36 ± 0.09 AB0.02 ± 0.02 AB0.1 ± 0.04 A0.7 ± 0.17 C0.14 ± 0.06 A
GC+CC D0.38 ± 0.1 AB0 ± 0 AB0.1 ± 0.05 A0.06 ± 0.04 BC0.3 ± 0.08 A
GC+CC E0.44 ± 0.11 AB0.02 ± 0.02 BCD0.08 ± 0.05 A0.38 ± 0.15 C0.38 ± 0.1 A
GG A0.13 ± 0.07 B0 ± 0 CD0 ± 0 A0 ± 0 C0 ± 0 A
GG B0.35 ± 0.09 AB0.02 ± 0.02 AB0.09 ± 0.05 A0.13 ± 0.08 A0.15 ± 0.06 A
GG C0.5 ± 0.11 AB0.04 ± 0.03 A0.13 ± 0.06 A0.57 ± 0.16 C0.26 ± 0.1 A
GG D0.54 ± 0.11 AB0.02 ± 0.02 AB0.28 ± 0.09 A0.2 ± 0.09 AB0.33 ± 0.09 A
GG E0.61 ± 0.12 A0.09 ± 0.06 ABC0.28 ± 0.12 A0.67 ± 0.21 C0.57 ± 0.13 A
SLC22A16Anemia gradeThrombocytopenia gradeLeukopenia gradeNeutropenia gradeLymphocytopenia grade
AA A0.15 ± 0.07 A0 ± 0 A0 ± 0 B0 ± 0 D0 ± 0 C
AA B0.3 ± 0.09 A0.04 ± 0.03 A0.06 ± 0.04 AB0.13 ± 0.07 BCD0.15 ± 0.06 BC
AA C0.43 ± 0.09 A0.02 ± 0.02 A0.13 ± 0.05 AB0.68 ± 0.18 A0.21 ± 0.07 ABC
AA D0.47 ± 0.11 A0.02 ± 0.02 A0.19 ± 0.07 AB0.13 ± 0.07 BCD0.28 ± 0.08 ABC
AA E0.57 ± 0.11 A0.06 ± 0.05 A0.06 ± 0.05 AB0.66 ± 0.2 AB0.53 ± 0.12 A
GG+GA A0.24 ± 0.09 A0 ± 0 A0 ± 0 B0 ± 0 D0 ± 0 C
GG+GA B0.31 ± 0.09 A0.02 ± 0.02 A0.08 ± 0.05 AB0.12 ± 0.08 CD0.08 ± 0.05 BC
GG+GA C0.43 ± 0.1 A0.04 ± 0.03 A0.1 ± 0.05 AB0.59 ± 0.16 ABC0.18 ± 0.08 BC
GG+GA D0.45 ± 0.1 A0 ± 0 A0.18 ± 0.08 AB0.12 ± 0.07 CD0.35 ± 0.09 AB
GG+GA E0.47 ± 0.12 A0.04 ± 0.04 A0.29 ± 0.11 A0.39 ± 0.16 ABCD0.41 ± 0.11 AB
ABCB1Anemia gradeThrombocytopenia gradeLeukopenia gradeNeutropenia gradeLymphocytopenia grade
GA+AA A0.12 ± 0.06 B0 ± 0 A0 ± 0 A0 ± 0 D0 ± 0 C
GA+AA B0.29 ± 0.08 AB0.02 ± 0.02 A0.04 ± 0.03 A0.12 ± 0.08 BCD0.08 ± 0.04 BC
GA+AA C0.37 ± 0.09 AB0.02 ± 0.02 A0.04 ± 0.03 A0.59 ± 0.17 ABC0.12 ± 0.05 BC
GA+AA D0.31 ± 0.08 AB0 ± 0 A0.12 ± 0.06 A0.08 ± 0.05 CD0.22 ± 0.08 BC
GA+AA E0.39 ± 0.09 AB0 ± 0 A0.14 ± 0.07 A0.43 ± 0.16 ABCD0.35 ± 0.09 AB
GG A0.28 ± 0.1 AB0 ± 0 A0 ± 0 A0 ± 0 D0 ± 0 C
GG B0.32 ± 0.1 AB0.04 ± 0.03 A0.11 ± 0.05 A0.13 ± 0.07 BCD0.15 ± 0.07 BC
GG C0.49 ± 0.11 AB0.04 ± 0.03 A0.19 ± 0.07 A0.68 ± 0.18 A0.28 ± 0.1 ABC
GG D0.62 ± 0.12 A0.02 ± 0.02 A0.26 ± 0.09 A0.17 ± 0.08 ABCD0.4 ± 0.09 AB
GG E0.66 ± 0.13 A0.11 ± 0.06 A0.21 ± 0.11 A0.62 ± 0.2 AB0.6 ± 0.14 A
Data expressed as mean ± standard deviation (SD). Shared letters represent non-significant results while different letters represent significant results (p-value < 0.05). Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy.
Table 15. GIT toxicity among the same genotype group data analysis using two-way with one-repeated-measure ANOVA test results.
Table 15. GIT toxicity among the same genotype group data analysis using two-way with one-repeated-measure ANOVA test results.
CYP2C19Nausea GradeVomiting GradeDiarrhea GradeConstipation GradeMucositis GradeStomachache Grade
CC A0 ± 0 E0 ± 0 C0 ± 0 A0 ± 0 B0 ± 0 B0 ± 0 A
CC B0.27 ± 0.06 BC0.61 ± 0.11 A0.14 ± 0.06 A0.22 ± 0.06 AB0.23 ± 0.05 A0.16 ± 0.05 A
CC C1 ± 0 A0.59 ± 0.11 A0.16 ± 0.06 A0.28 ± 0.07 A0.2 ± 0.05 A0.11 ± 0.04 A
CC D0.16 ± 0.05 CDE0.41 ± 0.08 AB0.13 ± 0.06 A0.19 ± 0.05 AB0.22 ± 0.05 A0.09 ± 0.04 A
CC E0.14 ± 0.04 CDE0.5 ± 0.1 A0.11 ± 0.05 A0.22 ± 0.07 AB0.2 ± 0.05 A0.14 ± 0.04 A
CT+TT A0 ± 0 DE0 ± 0 BC0 ± 0 A0 ± 0 AB0 ± 0 AB0 ± 0 A
CT+TT B0.41 ± 0.09 B0.41 ± 0.13 ABC0.19 ± 0.09 A0.28 ± 0.09 AB0.13 ± 0.06 AB0.19 ± 0.07 A
CT+TT C1 ± 0 A0.44 ± 0.16 ABC0.13 ± 0.07 A0.19 ± 0.08 AB0.16 ± 0.07 AB0.13 ± 0.06 A
CT+TT D0.22 ± 0.07 BCD0.5 ± 0.15 AB0.06 ± 0.04 A0.19 ± 0.11 AB0.13 ± 0.06 AB0.16 ± 0.07 A
CT+TT E0.19 ± 0.07 BCDE0.28 ± 0.09 ABC0.06 ± 0.04 A0.13 ± 0.07 AB0.06 ± 0.04 AB0.13 ± 0.06 A
ALDH3A1Nausea gradeVomiting gradeDiarrhea gradeConstipation gradeMucositis gradeStomachache grade
GC+CC A0 ± 0 D0 ± 0 C0 ± 0 A0 ± 0 C0 ± 0 A0 ± 0 C
GC+CC B0.34 ± 0.07 B0.52 ± 0.11 A0.22 ± 0.09 A0.14 ± 0.05 ABC0.18 ± 0.06 A0.1 ± 0.04 ABC
GC+CC C1 ± 0 A0.48 ± 0.12 A0.18 ± 0.08 A0.14 ± 0.05 ABC0.18 ± 0.05 A0.08 ± 0.04 ABC
GC+CC D0.26 ± 0.06 BC0.42 ± 0.1 ABC0.14 ± 0.07 A0.08 ± 0.04 BC0.16 ± 0.05 A0.18 ± 0.05 ABC
GC+CC E0.22 ± 0.06 BC0.38 ± 0.09 ABC0.12 ± 0.05 A0.08 ± 0.04 BC0.12 ± 0.05 A0.08 ± 0.04 ABC
GG A0 ± 0 D0 ± 0 BC0 ± 0 A0 ± 0 C0 ± 0 A0 ± 0 BC
GG B0.28 ± 0.07 BC0.57 ± 0.13 A0.09 ± 0.04 A0.35 ± 0.08 AB0.22 ± 0.06 A0.24 ± 0.06 A
GG C1 ± 0 A0.61 ± 0.13 A0.11 ± 0.06 A0.37 ± 0.1 A0.2 ± 0.06 A0.15 ± 0.05 ABC
GG D0.09 ± 0.04 CD0.46 ± 0.1 AB0.07 ± 0.04 A0.3 ± 0.09 AB0.22 ± 0.06 A0.04 ± 0.03 ABC
GG E0.09 ± 0.04 CD0.48 ± 0.11 A0.07 ± 0.04 A0.3 ± 0.1 AB0.2 ± 0.06 A0.2 ± 0.06 AB
SLC22A16Nausea gradeVomiting gradeDiarrhea gradeConstipation gradeMucositis gradeStomachache grade
AA A0 ± 0 C0 ± 0 B0 ± 0 A0 ± 0 B0 ± 0 B0 ± 0 B
AA B0.32 ± 0.07 B0.62 ± 0.12 A0.09 ± 0.04 A0.17 ± 0.06 AB0.23 ± 0.06 A0.21 ± 0.06 A
AA C1 ± 0 A0.47 ± 0.12 A0.09 ± 0.05 A0.19 ± 0.06 AB0.21 ± 0.06 AB0.13 ± 0.05 AB
AA D0.19 ± 0.06 BC0.43 ± 0.1 AB0.06 ± 0.04 A0.15 ± 0.05 AB0.23 ± 0.06 A0.15 ± 0.05 AB
AA E0.15 ± 0.05 BC0.38 ± 0.1 AB0.06 ± 0.04 A0.09 ± 0.04 AB0.21 ± 0.06 AB0.17 ± 0.06 AB
GG+GA A0 ± 0 C0 ± 0 B0 ± 0 A0 ± 0 B0 ± 0 B0 ± 0 B
GG+GA B0.31 ± 0.07 B0.47 ± 0.11 A0.22 ± 0.09 A0.31 ± 0.08 A0.17 ± 0.05 AB0.12 ± 0.05 AB
GG+GA C1 ± 0 A0.61 ± 0.13 A0.2 ± 0.08 A0.31 ± 0.09 A0.16 ± 0.05 AB0.1 ± 0.04 AB
GG+GA D0.16 ± 0.05 BC0.45 ± 0.1 A0.14 ± 0.07 A0.22 ± 0.08 AB0.14 ± 0.05 AB0.08 ± 0.04 AB
GG+GA E0.16 ± 0.05 BC0.47 ± 0.1 A0.12 ± 0.06 A0.29 ± 0.09 AB0.1 ± 0.04 AB0.1 ± 0.04 AB
ABCB1Nausea gradeVomiting gradeDiarrhea gradeConstipation gradeMucositis gradeStomachache grade
GA+AA A0 ± 0 D0 ± 0 C0 ± 0 A0 ± 0 A0 ± 0C0 ± 0 A
GA+AA B0.24 ± 0.06 BC0.47 ± 0.12 A0.16 ± 0.07 A0.27 ± 0.07 A0.23 ± 0.06 A0.16 ± 0.05 A
GA+AA C1 ± 0 A0.63 ± 0.14 A0.18 ± 0.07 A0.29 ± 0.09 A0.22 ± 0.06 AB0.1 ± 0.04 A
GA+AA D0.14 ± 0.05 CD0.51 ± 0.11 A0.1 ± 0.04 A0.18 ± 0.06 A0.2 ± 0.06 ABC0.1 ± 0.04 A
GA+AA E0.12 ± 0.05 CD0.41 ± 0.11 ABC0.1 ± 0.04 A0.2 ± 0.08 A0.16 ± 0.05 ABC0.12 ± 0.05 A
GG A0 ± 0 D0 ± 0 BC0 ± 0 A0 ± 0 A0 ± 0 BC0 ± 0 A
GG B0.38 ± 0.07 B0.62 ± 0.12 A0.15 ± 0.07 A0.21 ± 0.07 A0.17 ± 0.06 ABC0.17 ± 0.06 A
GG C1 ± 0 A0.45 ± 0.11 AB0.11 ± 0.07 A0.21 ± 0.07 A0.15 ± 0.05 ABC0.13 ± 0.05 A
GG D0.21 ± 0.06 BC0.36 ± 0.08 ABC0.11 ± 0.07 A0.19 ± 0.08 A0.17 ± 0.06 ABC0.13 ± 0.05 A
GG E0.19 ± 0.06 BCD0.45 ± 0.1 AB0.09 ± 0.05 A0.17 ± 0.06 A0.15 ± 0.05 ABC0.15 ± 0.05 A
Data expressed as mean ± standard deviation (SD). Shared letters represent non-significant results while different letters represent significant results (p-value < 0.05). Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy.
Table 16. Miscellaneous toxicities among the same genotypes group data analysis using two-way with one-repeated-measure ANOVA test results.
Table 16. Miscellaneous toxicities among the same genotypes group data analysis using two-way with one-repeated-measure ANOVA test results.
CYP2C19Fever GradeFatigue GradeAmenorrhea GradeAlopecia GradeHeadache GradeSkin Toxicity GradePeripheral Neuropathy Grade
CC A0 ± 0 A0 ± 0 C0 ± 0 B0 ± 0 J0 ± 0 A0 ± 0 B0 ± 0 A
CC B0.08 ± 0.03 A0.31 ± 0.06 A0.11 ± 0.04 A1 ± 0 H0.11 ± 0.04 A0.2 ± 0.05 A0.06 ± 0.03 A
CC C0.06 ± 0.03 A0.22 ± 0.05 AB0.03 ± 0.02 AB1 ± 0 G0.05 ± 0.03 A0.08 ± 0.03 AB0.09 ± 0.04 A
CC D0.05 ± 0.03 A0.17 ± 0.05 ABC0.02 ± 0.02 AB1 ± 0 F0.05 ± 0.03 A0.14 ± 0.04 AB0.06 ± 0.03 A
CC E0.03 ± 0.02 A0.16 ± 0.05 ABC0.03 ± 0.02 AB1 ± 0 E0.06 ± 0.03 A0.11 ± 0.04 AB0.08 ± 0.03 A
CT+TT A0 ± 0 A0 ± 0 BC0 ± 0 AB0 ± 0 I0 ± 0 A0 ± 0 B0 ± 0 A
CT+TT B0.03 ± 0.03 A0.41 ± 0.09 A0.06 ± 0.04 AB1 ± 0 C0.13 ± 0.06 A0.16 ± 0.07 AB0.03 ± 0.03 A
CT+TT C0.03 ± 0.03 A0.28 ± 0.08 AB0.06 ± 0.04 AB1 ± 0 B0.06 ± 0.04 A0.06 ± 0.04 AB0.03 ± 0.03 A
CT+TT D0.06 ± 0.04 A0.25 ± 0.08 ABC0.06 ± 0.04 AB1 ± 0 A0.09 ± 0.05 A0.06 ± 0.04 AB0 ± 0 A
CT+TT E0 ± 0 A0.22 ± 0.07 ABC0.03 ± 0.03 AB1 ± 0 D0.06 ± 0.04 A0.09 ± 0.05 AB0.03 ± 0.03 A
ALDH3A1Fever gradeFatigue gradeAmenorrhea gradeAlopecia gradeHeadache gradeskin toxicity gradePeripheral neuropathy grade
GC+CC A0 ± 0 B0 ± 0 C0 ± 0 B0 ± 0 J0 ± 0 A0 ± 0 B0 ± 0 B
GC+CC B0 ± 0 B0.22 ± 0.06 BC0.06 ± 0.03 AB1 ± 0 H0.12 ± 0.05 A0.22 ± 0.06 A0.08 ± 0.04 AB
GC+CC C0 ± 0 B0.18 ± 0.05 BC0.04 ± 0.03 AB1 ± 0 G0.04 ± 0.03 A0.1 ± 0.04 AB0.14 ± 0.05 A
GC+CC D0 ± 0 B0.16 ± 0.05 BC0.04 ± 0.03 AB1 ± 0 E0.04 ± 0.03 A0.08 ± 0.04 AB0.04 ± 0.03 AB
GC+CC E0 ± 0 B0.16 ± 0.05 BC0.04 ± 0.03 AB1 ± 0 D0.04 ± 0.03 A0.16 ± 0.05 AB0.06 ± 0.03 AB
GG A0 ± 0 B0 ± 0 C0 ± 0 B0 ± 0 I0 ± 0 A0 ± 0 B0 ± 0 B
GG B0.13 ± 0.05 A0.48 ± 0.07 A0.13 ± 0.05 A1 ± 0 C0.11 ± 0.05 A0.15 ± 0.05 AB0.02 ± 0.02 AB
GG C0.11 ± 0.05 AB0.3 ± 0.07 AB0.04 ± 0.03 AB1 ± 0 B0.07 ± 0.04 A0.04 ± 0.03 AB0 ± 0 B
GG D0.11 ± 0.05 AB0.24 ± 0.06 ABC0.02 ± 0.02 AB1 ± 0 A0.09 ± 0.04 A0.15 ± 0.05 AB0.04 ± 0.03 AB
GG E0.04 ± 0.03 AB0.2 ± 0.06 BC0.02 ± 0.02 AB1 ± 0 F0.09 ± 0.04 A0.04 ± 0.03 AB0.07 ± 0.04 AB
SLC22A16FeverFatigueAmenorrheaAlopeciaHeadacheSkin toxicityPeripheral neuropathy
AA A0 ± 0 A0 ± 0 B0 ± 0 A0 ± 0 I0 ± 0 A0 ± 0 B0 ± 0 A
AA B0.09 ± 0.04 A0.34 ± 0.07 A0.09 ± 0.04 A1 ± 0 H0.15 ± 0.05 A0.17 ± 0.06 AB0.06 ± 0.04 A
AA C0.04 ± 0.03 A0.28 ± 0.07 A0.02 ± 0.02 A1 ± 0 G0.06 ± 0.04 A0.09 ± 0.04 AB0.06 ± 0.04 A
AA D0.04 ± 0.03 A0.21 ± 0.06 AB0.02 ± 0.02 A1 ± 0 F0.06 ± 0.04 A0.11 ± 0.05 AB0.06 ± 0.04 A
AA E0.02 ± 0.02 A0.17 ± 0.06 AB0.02 ± 0.02 A1 ± 0 E0.09 ± 0.04 A0.09 ± 0.04 AB0.04 ± 0.03 A
GG+GA A0 ± 0 A0 ± 0B0 ± 0 A0 ± 0 J0 ± 0 A0 ± 0 B0 ± 0 A
GG+GA B0.04 ± 0.03 A0.35 ± 0.07 A0.1 ± 0.04 A1 ± 0 D0.08 ± 0.04 A0.2 ± 0.06 A0.04 ± 0.03 A
GG+GA C0.06 ± 0.03 A0.2 ± 0.06 AB0.06 ± 0.03 A1 ± 0 C0.04 ± 0.03 A0.06 ± 0.03 AB0.08 ± 0.04 A
GG+GA D0.06 ± 0.03 A0.18 ± 0.06 AB0.04 ± 0.03 A1 ± 0 B0.06 ± 0.03 A0.12 ± 0.05 AB0.02 ± 0.02 A
GG+GA E0.02 ± 0.02 A0.18 ± 0.06 AB0.04 ± 0.03 A1 ± 0 A0.04 ± 0.03 A0.12 ± 0.05 AB0.08 ± 0.04 A
ABCB1FeverFatigueAmenorrheaAlopeciaHeadacheSkin toxicityPeripheral neuropathy
GA+AA A0 ± 0 A0 ± 0 B0 ± 0 A0 ± 0 J0 ± 0 A0 ± 0 B0 ± 0 A
GA+AA B0.08 ± 0.04 A0.37 ± 0.07 A0.12 ± 0.05 A1 ± 0 H0.12 ± 0.05 A0.22 ± 0.06 A0.06 ± 0.03 A
GA+AA C0.04 ± 0.03 A0.22 ± 0.06 AB0.04 ± 0.03 A1 ± 0 G0.04 ± 0.03 A0.08 ± 0.04 AB0.1 ± 0.04 A
GA+AA D0.06 ± 0.03 A0.22 ± 0.06 AB0.04 ± 0.03 A1 ± 0 F0.06 ± 0.03 A0.12 ± 0.05 AB0.06 ± 0.03 A
GA+AA E0.04 ± 0.03 A0.22 ± 0.06 AB0.04 ± 0.03 A1 ± 0 E0.04 ± 0.03 A0.12 ± 0.05 AB0.1 ± 0.04 A
GG A0 ± 0 A0 ± 0 B0 ± 0 A0 ± 0 I0 ± 00 ± 0 B0 ± 0 A
GG B0.04 ± 0.03 A0.32 ± 0.07 A0.06 ± 0.04 A1 ± 0 D0.11 ± 0.050.15 ± 0.05 AB0.04 ± 0.03 A
GG C0.06 ± 0.04 A0.26 ± 0.06 A0.04 ± 0.03 A1 ± 0 C0.06 ± 0.040.06 ± 0.04 AB0.04 ± 0.03 A
GG D0.04 ± 0.03 A0.17 ± 0.06 AB0.02 ± 0.02 A1 ± 0 B0.06 ± 0.040.11 ± 0.05 AB0.02 ± 0.02 A
GG E0 ± 0 A0.13 ± 0.05 AB0.02 ± 0.02 A1 ± 0 A0.09 ± 0.040.09 ± 0.04 AB0.02 ± 0.02 A
Data expressed as mean ± standard deviation (SD). Shared letters represent non-significant results while different letters represent significant results (p-value < 0.05). Toxicity was assessed at five time points (A, B, C, D, E) among the genotype group data analyses, where A represents the period before administering the chemotherapy, B means after taking the first cycle of chemotherapy, C means after taking the second cycle of chemotherapy, D means after taking the third cycle of chemotherapy, and E means after taking the fourth cycle of chemotherapy.
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Abdelfattah, E.K.; Hosny, S.M.; Kassem, A.B.; Moustafa, H.A.M.; Tawfeik, A.M.; Abdelhafez, M.N.; El-Sheshtawy, W.; Alsfouk, B.A.; Saleh, A.; Salem, H.A. Pharmacogenetics as a Future Tool to Risk-Stratify Breast Cancer Patients According to Chemotoxicity Potential from the Doxorubicin Hydrochloride and Cyclophosphamide (AC) Regimen. Pharmaceuticals 2025, 18, 539. https://doi.org/10.3390/ph18040539

AMA Style

Abdelfattah EK, Hosny SM, Kassem AB, Moustafa HAM, Tawfeik AM, Abdelhafez MN, El-Sheshtawy W, Alsfouk BA, Saleh A, Salem HA. Pharmacogenetics as a Future Tool to Risk-Stratify Breast Cancer Patients According to Chemotoxicity Potential from the Doxorubicin Hydrochloride and Cyclophosphamide (AC) Regimen. Pharmaceuticals. 2025; 18(4):539. https://doi.org/10.3390/ph18040539

Chicago/Turabian Style

Abdelfattah, Esraa K., Sanaa M. Hosny, Amira B. Kassem, Hebatallah Ahmed Mohamed Moustafa, Amany M. Tawfeik, Marwa N. Abdelhafez, Wael El-Sheshtawy, Bshra A. Alsfouk, Asmaa Saleh, and Hoda A. Salem. 2025. "Pharmacogenetics as a Future Tool to Risk-Stratify Breast Cancer Patients According to Chemotoxicity Potential from the Doxorubicin Hydrochloride and Cyclophosphamide (AC) Regimen" Pharmaceuticals 18, no. 4: 539. https://doi.org/10.3390/ph18040539

APA Style

Abdelfattah, E. K., Hosny, S. M., Kassem, A. B., Moustafa, H. A. M., Tawfeik, A. M., Abdelhafez, M. N., El-Sheshtawy, W., Alsfouk, B. A., Saleh, A., & Salem, H. A. (2025). Pharmacogenetics as a Future Tool to Risk-Stratify Breast Cancer Patients According to Chemotoxicity Potential from the Doxorubicin Hydrochloride and Cyclophosphamide (AC) Regimen. Pharmaceuticals, 18(4), 539. https://doi.org/10.3390/ph18040539

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