Next Article in Journal
Voltage Problems on Farms with Agricultural Biogas Plants—A Case Study
Previous Article in Journal
Physics-Informed Neural Networks for Cantilever Dynamics and Fluid-Induced Excitation
Previous Article in Special Issue
Cardiac Troponins I and T as Biomarkers of Cardiomyocyte Injury—Advantages and Disadvantages of Each
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 14
Issue 16
10.3390/app14166998
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Serum Concentrations of IGF-1R, ERK2, and EGFR and Their Clinical Significance in Patients with Neuroendocrine Tumors

by
Roksana Duszkiewicz
1,*,
Janusz Strzelczyk
2,
Elżbieta Chełmecka
3 and
Joanna Katarzyna Strzelczyk
1,*
1
Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 19 Jordana St., 41-808 Zabrze, Poland
2
Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 35 Ceglana St., 40-514 Katowice, Poland
3
Department of Medical Statistics, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, 30 Ostrogórska St., 40-055 Katowice, Poland
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2024, 14(16), 6998; https://doi.org/10.3390/app14166998
Submission received: 30 June 2024 / Revised: 2 August 2024 / Accepted: 6 August 2024 / Published: 9 August 2024
(This article belongs to the Special Issue Recent Advancements in Biomarkers for Noncommunicable Diseases)
Browse Figure
Versions Notes

Abstract

:
Neuroendocrine tumors are a heterogeneous group of tumors located mainly in the gastrointestinal tract or the respiratory system. We aimed to determine the concentrations of IGF-1R, ERK2, and EGFR using the ELISA method in serum samples from patients with NETs and from a control group. Results were evaluated with the selected demographic, clinicopathological, and biochemical characteristics. The analyses performed on a group of patients (80 in the study group and 62 in the control group) showed that the concentration of EGFR in patients with neuroendocrine tumors was significantly higher (p < 0.001) compared to the control group. Additionally, a significantly higher (p < 0.001) EGFR concentration was found in GEP-NET. Our results indicate that impaired EGFR signaling pathways are important in the context of neuroendocrine tumors. The data presented are a good starting point for further analysis of these proteins.

1. Introduction

Neuroendocrine tumors (NETs) belong to a widespread, diverse group of tumors, most often solid tumors, originating from neuroendocrine cells [1]. The vast majority of them are located in the gastrointestinal tract or the respiratory system, and less frequently in the genitourinary system [1,2].
Biochemical diagnostics in NETs include non-specific markers, such as serum chromogranin A, and specific ones, such as serotonin and 5-hydroxyindole acetic acid (5-HIAA) [3]. The choice of an appropriate NET marker depends on the type of suspected tumor and its location [3,4]. Many potential predictive markers for NETs are currently being studied [5,6,7]. Insulin-like growth factor 1 receptor (IGF-1R), extracellular signal-regulated kinase 2 (ERK2), and epidermal growth factor receptor (EGFR) are interesting choices for evaluation in the group of patients with neuroendocrine tumors. These proteins have not been previously studied in the same manner as in our research, although the literature review indicated that the concentration levels of these proteins have been analyzed before, but in other diseases.
IGF-1R is a heterotetrameric tyrosine kinase receptor on the cell surface with strong anti-apoptotic and pro-survival properties. It is involved in carcinogenesis, as indicated by the high expression of IGF-1R in various cancers [8,9,10,11]. Numerous studies show that IGF-1R interferes with mTOR inhibitors [12,13], making it an interesting potential target for NET treatment. ERK is part of the mitogen-activated protein kinase pathway, and recent studies confirm its effect on signal transmission in signaling cascades [14]. The ERK/MAPK pathway is associated with the neuroendocrine phenotype due to the presence of IL-8 [15,16]. It has also been proven that EGFR is expressed in many cancers and is associated with poor prognosis for patients [17,18,19]. EGFR activation pathways occur through autophosphorylation [20]. Subsequently, the phosphorylation of further signaling molecules, such as ERK1/2 and PKB/Akt, leads to increased survival and proliferation of cancer cells. These data justify considering the use of EGFR inhibitors in NET treatment. Additionally, direct effects on Akt and ERK1/2 may be important therapeutic targets for treating NETs in the future [21].
These three proteins are components of the canonical Wnt signaling pathway, which plays an important role in the regulation of cellular metabolism. Therefore, analyzing the concentrations of selected proteins in the blood serum of patients with neuroendocrine tumors is justified. According to available data (COCHRANE, EMBASE, and MEDLINE database searches), this is one of the few studies evaluating IGF-1R, ERK2, and EGFR in NET patients [22,23,24]. However, so far, no one has analyzed them using ELISA tests.
The aim of this study was to assess the concentrations of IGF-1R, ERK2, and EGFR in serum samples from patients with NETs and from a control group. Our results were evaluated in relation to selected demographic, clinicopathological, and biochemical characteristics.

2. Materials and Methods

Patients were recruited at the Department of Endocrinology and Neuroendocrine Tumors, Medical University of Silesia in Katowice, Poland. The main inclusion criteria for the study group were a diagnosis of neuroendocrine tumors, age ≥ 18, and signed consent to participate in the study. The main inclusion criteria for the control group were healthy volunteers, age ≥ 18, signed consent to participate in the study, and no history of any malignancy at the time of blood draw. Peripheral blood from patients was collected into S-Monovette tubes with a clotting activator (Sarstedt, Germany). To obtain serum, blood was centrifuged for 15 min at 3500 rpm. Serum was stored at −80 °C for further analysis. The serum concentrations of IGF-1R, ERK2, and EGFR were assessed using ELISA, following the procedures described by the manufacturers. All ELISA tests were performed at the Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia. The analytical procedure adhered to the manufacturer’s guidelines outlined in the technological manuals provided with the kits. To determine the concentrations of the tested samples, a standard curve was prepared using the standards supplied in the kit. All standards and serum samples were run in duplicates; additionally, serum samples were diluted as specified by the instructions (IGF-1R 2x, ERK2 none, EGFR 50x). For all ELISA tests, plates were read by a Bio-Tek µQuant Universal Microplate Spectrophotometer (Bio-Tek, Winooski, VT, USA) using 450 nm as the primary wavelength. Data analysis software KCJunior (Bio-Tek, Winooski, VT, USA) was used. The absorbance was transformed into a concentration of pg/mL for all three proteins. The following tests were used: RayBiotech Life, Inc., Peachtree Corners, GA, USA (Catalog No. ELH-IGF1R) for IGF-1R; Cloud-Clone Corp., Katy, TX, USA (Catalog No. SEA930Hu) for ERK2; and Wuhan Fine Biotech Co., Ltd., Wuhan, China (Catalog No. EH0010) for EGFR. The minimum detectable dose is 6.00 pg/mL for IGF-1R, 15.99 pg/mL for ERK2, and 9.375 pg/mL for EGFR.

3. Characteristic of the Study Group

A total of 142 individuals participated in the study. The study group comprised 80 patients (56%), and the control group comprised 62 healthy individuals (44%) with no history of any malignancy at the time of blood draw. More details about biochemical parameters from the study group are presented in Table 1 and in Supplementary Materials (Table S1).
In the study group, 16 patients (20%) had neuroendocrine tumors of the respiratory system (BP-NETs) and 64 patients (80%) had neuroendocrine tumors of the digestive tract (GEP-NETs). More details about parameters from the study group are presented in Table 2.

4. Statistical Analysis

Qualitative data are presented using percentages. For quantitative data, the normality of the distribution was assessed using the Shapiro–Wilk test. Normally distributed data are presented as mean value ± standard deviation (M ± SD). For skewed distributions, medians (low and upper quartile) were used (Me (Q1–Q3)). Comparisons between variables were made with the Student’s t-test or the Mann–Whitney U test. The Spearman correlation coefficient test was used to assess the relationship between variables. A significance level of 0.05 was adopted, and all tests were two-sided. Statistical analysis was performed using the Statistica program (TIBCO Software Inc., Palo Alto, CA, USA, (2017). Statistica (data analysis software system), version 13. http://statistica.io, 23 November 2023).

5. Results

There was no significant difference in patient age and BMI between the study group and the control group (age: p = 0.083, BMI: p = 0.385). Details are presented in Table 3.
There was no correlation between sex in the considered groups (p = 0.343). Similarly, no association was found for hypertension (p = 0.205) and smoking (p = 0.911). However, a correlation was found between the occurrence of diabetes (p < 0.05). In the study group, the calculated odds ratio indicates that the chance of developing diabetes was more than five times higher than in the control group (OR = 5.8, 95% CI: 1.3–26.9). Details are presented in Table 4.
Comparisons of the concentrations of measured parameters showed that the concentrations of IGF-1R (p = 0.289) and ERK2 (p = 0.901) did not show statistically significant differences between groups. The concentration of EGFR was significantly lower (p < 0.001) in the control group compared to the study group (Table 5). Details of EGFR are shown in Figure 1 and the Supplementary Material (Table S2).
There was no significant difference between concentrations of proteins and age, Ki-67, and clinical stage. However, a significant negative correlation was found between EGFR and BMI in the control group (p < 0.05). Details are presented in Table 6. There was also no significant difference between concentrations of proteins and other parameters like histological grade, metastasis, liver metastasis, lymph node metastasis, and bone metastasis.
There were no differences depending on the location of the primary tumor in the IGF-1R variable (p = 0.968) and in the ERK2 variable (p = 0.980); however, there were differences in EGFR concentration (p < 0.001). Higher EGFR values were found in GEP-NETs (Table 7). Analyses performed for the location of the primary lesion (lung, pancreas, small intestine, duodenum, stomach, rectum) did not show any statistically significant differences for IGF-1R (p = 0.603), ERK2 (p = 0.665), and EGFR (p = 0.130).
There was no relationship between any of the concentration proteins and the concentration of chromogranin A, serotonin, and 5-HIAA. However, a close-to-significant correlation was found between chromogranin A and EGFR (p < 0.05). Details are presented in Table 8. There was also no relationship between any of the concentrations of proteins and the concentrations of glucose, TCH, and TG.
There were no statistically significant differences for all smokers (study group N = 9, control group N = 12) in the concentrations of IGF-1R (z = 0.174, p = 0.862), ERK2 (z = −1.176, p = 0.861), and EGFR (z = 0.931, p = 0.352). In addition, the relationships between the concentrations of individual proteins were also analyzed. There was no correlation between ERK2 and IGF-1R (ρ = −0.058, p = 0.625) and EGFR (ρ = 0.087, p = 0.476). There was also no correlation between IGF-1R and EGFR (ρ = 0.086, p = 0.474).

6. Discussion

The incidence of neuroendocrine tumors (NETs) has been steadily increasing in recent years [25]. Despite the fact that NETs develop slowly, in advanced cases, they are incurable and lead to death [26]. The diagnosis and therapy of neuroendocrine tumors (NETs) involve a variety of approaches due to their complexity and heterogeneity. Advanced imaging techniques, such as PET/CT with labeled somatostatin analogs, are crucial for accurately locating tumors and assessing their spread [27]. The treatment of NETs includes both surgical methods and pharmacological therapy, such as the use of somatostatin analogs and new targeted therapies like tyrosine kinase inhibitors, which show promising results in controlling tumor growth [28]. Additionally, radionuclide therapy with agents like 177Lu-Dotatate offers an effective treatment option for patients with advanced NETs, significantly improving quality of life and extending survival [29].
Despite many years of research, treatment options are still limited. The three selected proteins were chosen for their roles in the Wnt signaling pathway, vital for regulating cell metabolism, proliferation, differentiation, and apoptosis [23]. The focus on these proteins aims to offer a clearer understanding of the molecular mechanisms in neuroendocrine tumors. An interesting target for treatment is mTOR inhibitors in patients with NETs. Mutations in the mammalian target of rapamycin (mTOR) pathway are estimated to occur in approximately 14% of pancreatic NETs (pNETs), and such abnormalities have also been associated with more aggressive tumors [30,31,32]. Clinical trials with everolimus, an oral mTOR inhibitor, in patients with NETs showed a significant improvement in progression-free survival after its use [33]. Studies show that IGF-1 is the main regulator of neuroendocrine secretion and growth [34,35]. Moreover, in vitro studies have shown that IGF-1R blockade results in inhibition of NET cell growth and induction of apoptosis [36]. Other preclinical studies suggest that IGF-1 protects cancer cells from rapamycin-induced cell death and that inhibition of IGF-1R prevents rapamycin-induced Akt activation and sensitizes cancer cells to mTOR inhibitors, providing a rationale for the combined blockade of these pathways [37]. IGF-1R from rapamycin-induced apoptosis is independent of Ras-Erk1-Erk2 and phosphatidylinositol 3′-kinase-Akt signaling pathways [38].
The results of studies in patients with thyroid cancer show that the IGF-1–IGF-1R axis plays an important role in the development of PTC (papillary thyroid cancer) and ATC (anaplastic thyroid cancer) [39]. This suggests that serum concentrations of both cytokines can be considered additional markers of malignancy differentiation in the preoperative diagnosis of patients with thyroid cancer [40]. Moreover, IGF-1R values in serum seem to be a better predictor than IGF-1 concentrations [39,41]. The two proteins differ in their sensitivity. For example, research indicates a strong association between elevated IGF-1R expression and increased resistance to radiation therapy in cancers such as cervical, prostate, lung, HPV-negative head and neck cancers, and melanoma [42,43,44,45,46]. Moreover, higher IGF-1R expression levels are linked to more aggressive tumor grades and reduced patient survival rates across various cancer types [47,48,49]. Our results show no statistically significant differences between the study and control groups for IGF-1R. There are no studies on the concentration of IGF-1R in patients with neuroendocrine tumors, nor are there studies on animal models. The only available research on IGF-1R concerns breast cancer patients [50,51,52,53,54,55,56].
The second analyzed protein, mitogen-activated protein (MAP) kinase ERK2 (p42), in association with ERK1 (p44), is a key component of the regulatory mechanism underlying cell proliferation [57]. The currently accepted model assumes that ERK1 and ERK2 are similarly regulated and contribute to intracellular signaling through phosphorylation [58]. Study results indicate an interplay between ERK1 and ERK2 in the transduction of Ras-dependent cell signaling and proliferation [59]. While ERK2 seems to play a positive role in controlling normal and Ras-dependent cell proliferation, ERK1 probably influences the overall cell signaling power by antagonizing ERK2 activity [60]. The molecular pathogenesis of gastrointestinal neuroendocrine tumors (GP-NETs) is unknown [61]. Serine/threonine kinase B-Raf has been identified as an oncogene in endocrine cancers such as thyroid cancer [62]. In endocrine cells, the small G protein Rap1 stimulates mitogen-activated protein kinase (MAPK) signaling by activating B-Raf [60]. The results of studies on the expression of Rap1 and B-Raf in GI NETs and their involvement in MAPK signaling in neuroendocrine cell lines indicate that Rap1-B-Raf signaling may contribute to the pathogenesis of GI NETs and provides a molecular target for GI NET treatment [63,64]. There are no studies on the concentration of ERK2 in patients with neuroendocrine tumors, nor are there studies on animal models using immunoenzymatic methods. There are also no data for oncology patients. Our results show no statistically significant differences between the study and control groups for ERK2. This suggests that this protein may not be characteristic of neuroendocrine tumors, and therefore its potential as a predictor of this disease is low, or it should be analyzed using other molecular biology methods.
Another molecule associated with the Akt signaling pathway is EGFR [25,65,66,67,68,69]. Although EGFR expression has been identified in neuroendocrine tumor tissue, its activation and the subsequent impact on downstream signaling molecules such as ERK1/2 and Akt remain unexplored. Further research is needed to elucidate these mechanisms and their potential implications for the behavior and treatment of neuroendocrine tumors [70]. Therefore, it was crucial to ascertain the role of EGFR in neuroendocrine tumors (NETs) by examining its expression and activation patterns, followed by the activation of additional signaling molecules [17,25]. The study designed for this purpose included tumor tissue material from 98 patients with NETs. Immunohistochemical evaluation of EGFR, p-EGFR, p-Akt, and p-ERK1/2 expression was performed. A total of 96% of the tumors were positive for EGFR expression, 63% tested positive for activated EGFR, 76% were positive for activated Akt, and 96% were positive for activated ERK1/2. Importantly, the histology score for Akt and ERK1/2 activation correlated with the histology score for activated EGFR [71]. The obtained results justify considering the use of EGFR inhibitors in the treatment of NETs [71,72]. In addition, directly inhibiting Akt and ERK1/2 could present further therapeutic options for the treatment of neuroendocrine tumors (NETs) in the future. Exploring these pathways may lead to the development of novel strategies that enhance the effectiveness of existing treatments and improve patient outcomes [72,73]. There are studies aimed at determining the clinical significance of serum EGFR concentrations in patients with breast cancer (BC) [74,75,76,77]. Serum EGFR concentrations were determined by ELISA. Baseline serum EGFR concentrations were significantly higher than in healthy controls (p < 0.001). Other known clinical variables, including histological grade or disease stage, were not correlated. In BC patients, despite elevated serum EGFR concentrations, EGFR concentrations have no predictive value [78].
The obtained results suggest that EGFR is the most interesting among the selected proteins. In our study, we observed that EGFR concentrations in patients with neuroendocrine tumors were significantly higher (p < 0.001) in the study group compared with the control. This is consistent with findings in the literature [25,79,80]. EGFR concentration depending on the location of the primary tumor has been noted. Significantly higher (p < 0.001) EGFR concentration was found in GEP-NETs than in BP-NETs. EGFR kinase is frequently overexpressed in various cancers, including non-small cell lung cancer, metastatic colorectal cancer, glioblastoma multiforme, head and neck cancer, pancreatic cancer, and breast cancer [79]. Genetic alterations result in the overactivation of downstream pro-oncogenic signaling pathways, which can initiate a cascade of biological processes that are crucial for cancer cell proliferation [80]. Lung neuroendocrine tumors and gastroenteropancreatic neuroendocrine tumors are distinct types of neuroendocrine tumors from different origins but have often been treated similarly. Despite sharing phenotypic characteristics and neuroendocrine marker expression, they differ in microenvironment, molecular mutations, and therapeutic responses. Recent research highlights genetic differences, the role of EGFR in carcinogenesis, the presence of transcription factors, and tumor immunogenicity [81]. There are no clear data to verify the differences observed for BP-NETs and GEP-NETs. It seems that they should be found in different molecular pathways. Also, it should be noted that the BP-NET group was smaller (N = 20), which suggests that further research is needed to confirm these findings and use this knowledge in clinical practice.
A close-to-significant correlation was found between EGFR and chromogranin A (p < 0.05). This is particularly interesting because chromogranin A is the most important general circulating tumor marker, being expressed in 80–90% of all patients with gastroenteropancreatic neuroendocrine tumors. Determining chromogranin A levels is also useful for staging, prognosis, and follow-up, as its serum concentration correlates with tumor mass [82]. This relationship indicates that EGFR may be a good future indicator that can be used in the evaluation of patients with neuroendocrine tumors, particularly GEP-NETs.
Next, in our study, we found a significant negative correlation between EGFR and BMI, but only in the control group (p < 0.05). These results suggest that body mass index (BMI) may have an effect on EGFR concentration. Although there are no data in the literature on the relationship between BMI and EGFR in NET patients, EGFR mutations are the most common oncogenic drivers in non-small-cell lung cancer (NSCLC) [83,84,85]. Studies have investigated the standard of care in patients with or without EGFR T790M mutation who had progressed following prior EGFR tyrosine kinase inhibitor (TKI) therapy. The investigators found that pretreatment BMI, specifically a BMI of less than 18.5 kg/m2, was a significant prognostic factor for poor progression-free survival and overall survival in EGFR TKI treatment [86,87,88,89].
This study is the first to use ELISA tests to analyze these proteins in serum for neuroendocrine tumor patients. Although two proteins showed no significant differences, the remaining ones had higher or comparable concentrations. These results can still offer valuable insights into protein expression profiles, despite the lack of statistical significance.
Our results also show no correlation between groups in terms of sex, hypertension, and smoking. Moreover, there is no correlation of these parameters with IGF-1R, ERK2, or EGFR. However, there is a correlation between groups in terms of diabetes (p < 0.05). In the study group, the chance of developing diabetes was more than five times higher than in the control group. The results are consistent with the latest research that shows the impact of diabetes in patients with pancreatic NETs [90,91]. Diabetes and pancreatic neuroendocrine tumors (pNETs) are closely related entities. Diabetes has been identified as a risk factor for the development and aggressiveness of pNETs. Conversely, diabetes resulting from pNETs is often undiagnosed or misclassified as type 2 diabetes when it is actually type 3 diabetes. The strong correlation between diabetes and the likelihood of developing NETs, particularly pancreatic NETs, aligns with current research and emphasizes the importance of metabolic health in cancer prognosis and management [89,90].
Overall, our results contribute to the growing body of knowledge on the molecular underpinnings of NETs and support the continued exploration of targeted therapies, including mTOR and EGFR inhibitors, to improve patient outcomes. Future research should focus on validating these findings in larger cohorts and exploring the potential of combined pathway blockades to enhance therapeutic efficacy in NETs. Although two of the proteins did not show statistical significance, we believe their inclusion still contributes valuable insights to the field. However, further research is needed to validate these findings and to investigate additional proteins that could strengthen and support the conclusions of this manuscript.

7. Conclusions

The increasing incidence of neuroendocrine tumors (NETs) highlights the urgent need for effective treatment strategies. The results of our work suggest that EGFR is the most important of the three proteins tested, especially for GEP-NET patients. This is also supported by the oncology literature. IGF-1R and ERK2 seem to be less important; however, currently, our study is the only one that examined their concentration in NET patients. Therefore, it is also important to conduct further analyses of these proteins. The lack of significant differences in IGF-1R and ERK2 concentrations between study and control groups suggests that these proteins may not be characteristic markers for NETs, highlighting the need for further molecular biology studies to explore alternative pathways and markers. However, our findings emphasize the importance of impaired EGFR signaling pathways in neuroendocrine tumors. These results lay the groundwork for deeper exploration of these proteins.

8. Advantages of the Study

According to the available data (COCHRANE, EMBASE, and MEDLINE database search), this is the only study evaluating serum concentrations of IGF-1R, ERK2, and EGFR in NET patients using ELISA tests.

9. Limitations of the Study

This study has potential limitations. There is no information on the survival of patients; therefore, this information is not included in the analyses. However, these issues will be addressed in further research.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app14166998/s1, Table S1: Description statistics of biochemical parameters in study group; Table S2: Description statistics of insulin-like growth factor 1 receptor (IGF-1R, pg/mL), extracellular signal regulated kinase 2 (ERK2, pg/mL), and epidermal growth factor receptor (EGFR, pg/mL) broken down into groups; Individual parameters were determined in the study group and presented also as the mean (SD): chromogranin A 122.8 ± 215.7 µg/L, serotonin 270.7 ± 343.8 ng/mL, 5-HIAA 11.5 ± 31.8 mg/24 h, glucose 98.5 ± 17.1 mg/dL, TCH 206.2 ± 48.0 mg/dL and TG 109.4 ± 57.8 mg/dL. A detailed summary of the descriptive statistics of the above parameters is presented in the table.

Author Contributions

Conceptualization, R.D. and J.K.S.; methodology, R.D. and J.K.S.; software, R.D., E.C. and J.K.S.; validation, R.D., J.S., E.C. and J.K.S.; formal analysis, R.D. and J.K.S.; investigation, R.D.; resources, R.D., J.S. and J.K.S.; data curation, R.D. and J.K.S.; writing—original draft preparation, R.D.; visualization, R.D. and E.C.; supervision, J.K.S.; project administration, R.D. and J.K.S.; All authors have read and agreed to the published version of the manuscript.

Funding

This research was founded by a grant from the Medical University of Silesia (PCN-1-014/N/1/I).

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee of the Medical University of Silesia (No. PCN/CBN/0052/KB1/24/II/22, 20 September 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data used to support the findings of this research are available upon request from the corresponding authors, Roksana Duszkiewicz: [email protected], Joanna Katarzyna Strzelczyk: [email protected].

Acknowledgments

We would like to thank Professor Beata Kos-Kudła, Head of the Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, for enabling the collection of material for the study group and Kinga Wołkowska-Pokrywa for help with the analysis.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Basu, B.; Sirohi, B.; Corrie, P. Systemic therapy for neuroendocrine tumours of gastroenteropancreatic origin. Endocr. Relat. Cancer 2010, 17, R75–R90. [Google Scholar] [CrossRef] [PubMed]
  2. Kos-Kudła, B.; Foltyn, W.; Malczewska, A.; Bednarczuk, T.; Bolanowski, M.; Borowska, M.; Chmielik, E.; Ćwikła, J.B.; Gisterek, I.; Handkiewicz-Junak, D.; et al. Update of the diagnostic and therapeutic guidelines for gastro-entero-pancreatic neuroendocrine neoplasms (recommended by the Polish Network of Neuroendocrine Tumours). Endokrynol. Pol. 2022, 73, 387–454. [Google Scholar] [CrossRef] [PubMed]
  3. Adaway, J.E.; Dobson, R.; Walsh, J.; Cuthbertson, D.J.; Monaghan, P.J.; Trainer, P.J.; Valle, J.W.; Keevil, B.G. Serum and plasma 5-hydroxyindoleacetic acid as an alternative to 24-h urine 5-hydroxyindoleacetic acid measurement. Ann. Clin. Biochem. 2016, 53, 554–560. [Google Scholar] [CrossRef] [PubMed]
  4. Tellez, M.R.; Mamikunian, G.; O’dorisio, T.M.; Vinik, A.I.; Woltering, E.A. A single fasting plasma 5-HIAA value correlates with 24-hour urinary 5-HIAA values and other biomarkers in midgut neuroendocrine tumors (NETs). Pancreas 2013, 42, 405–410. [Google Scholar] [CrossRef]
  5. Sansone, A.; Lauretta, R.; Vottari, S.; Chiefari, A.; Barnabei, A.; Romanelli, F.; Appetecchia, M. Specific and Non-Specific Biomarkers in Neuroendocrine Gastroenteropancreatic Tumors. Cancers 2019, 11, 1113. [Google Scholar] [CrossRef] [PubMed]
  6. Park, J.H.; Shin, S.-J.; Jeon, N.; Lim, B.J. Clinicopathologic characteristics of neuroendocrine tumors with assessment by digital image analysis for Ki-67 index with a focus on the gastroenteropancreatic tract: A single-center study. Int. J. Clin. Exp. Pathol. 2023, 16, 225–234. [Google Scholar] [PubMed]
  7. Tsoli, M.; Koumarianou, A.; Angelousi, A.; Kaltsas, G. Established and novel circulating neuroendocrine tumor biomarkers for diagnostic, predictive and prognostic use. Best. Pract. Res. Clin. Endocrinol. Metab. 2023, 37, 101785. [Google Scholar] [CrossRef] [PubMed]
  8. Werner, H.; Meisel-Sharon, S.; Bruchim, I. Oncogenic Fusion Proteins Adopt the Insulin-Like Growth Factor Signaling Pathway. Mol. Cancer 2018, 17, 28. [Google Scholar] [CrossRef]
  9. Cevenini, A.; Orrù, S.; Mancini, A.; Alfieri, A.; Buono, P.; Imperlini, E. Molecular Signatures of the Insulin-Like Growth Factor 1-Mediated Epithelial-Mesenchymal Transition in Breast, Lung and Gastric Cancers. Int. J. Mol. Sci. 2018, 19, 2411. [Google Scholar] [CrossRef]
  10. Werner, H.; Sarfstein, R.; Bruchim, I. Investigational IGF1R inhibitors in early stage clinical trials for cancer therapy. Expert Opin. Investig. Drugs 2019, 28, 1101–1112. [Google Scholar] [CrossRef]
  11. Motylewska, E.; Braun, M.; Kazimierczuk, Z.; Ławnicka, H.; Stępień, H. IGF1R and MAPK15 Emerge as Potential Targets of Pentabromobenzylisothioureas in Lung Neuroendocrine Neoplasms. Pharmaceuticals 2020, 13, 354. [Google Scholar] [CrossRef]
  12. Lamberti, G.; Brighi, N.; Maggio, I.; Manuzzi, L.; Peterle, C.; Ambrosini, V.; Ricci, C.; Casadei, R.; Campana, D. The Role of mTOR in Neuroendocrine Tumors: Future Cornerstone of a Winning Strategy? Int. J. Mol. Sci. 2018, 19, 747. [Google Scholar] [CrossRef]
  13. Wan, X.; Harkavy, B.; Shen, N.; Grohar, P.; Helman, L. Rapamycin induces feedback activation of Akt signaling through an IGF-1R-dependent mechanism. Oncogene 2007, 26, 1932–1940. [Google Scholar] [CrossRef]
  14. Guo, Y.J.; Pan, W.W.; Liu, S.B.; Shen, Z.F.; Xu, Y.; Hu, L.L. ERK/MAPK signalling pathway and tumorigenesis. Exp. Ther. Med. 2020, 19, 1997–2007. [Google Scholar] [CrossRef]
  15. Kim, J.; Jin, H.; Zhao, J.C.; Yang, Y.A.; Li, Y.; Yang, X.; Dong, X.; Yu, J. FOXA1 inhibits prostate cancer neuroendocrine differentiation. Oncogene 2017, 36, 4072–4080. [Google Scholar] [CrossRef]
  16. Xie, Y.; Ning, S.; Hu, J. Molecular mechanisms of neuroendocrine differentiation in prostate cancer progression. J. Cancer Res. Clin. Oncol. 2022, 148, 1813–1823. [Google Scholar] [CrossRef] [PubMed]
  17. Uribe, M.L.; Marrocco, I.; Yarden, Y. EGFR in Cancer: Signaling Mechanisms, Drugs, and Acquired Resistance. Cancers 2021, 13, 2748. [Google Scholar] [CrossRef] [PubMed]
  18. Sigismund, S.; Avanzato, D.; Lanzetti, L. Emerging functions of the EGFR in cancer. Mol. Oncol. 2018, 12, 3–20. [Google Scholar] [CrossRef] [PubMed]
  19. Li, X.; Zhao, L.; Chen, C.; Nie, J.; Jiao, B. Can EGFR be a therapeutic target in breast cancer? Biochim. Biophys. Acta Rev. Cancer 2022, 1877, 188789. [Google Scholar] [CrossRef]
  20. Schlessinger, J. Cell signalling by receptor tyrosine kinases. Cell 2000, 103, 211–225. [Google Scholar] [CrossRef]
  21. Zanini, S.; Renzi, S.; Giovinazzo, F.; Bermano, G. mTOR Pathway in Gastroenteropancreatic Neuroendocrine Tumor (GEP-NETs). Front. Endocrinol. 2020, 11, 562505. [Google Scholar] [CrossRef] [PubMed]
  22. Dasari, A.; Phan, A.; Gupta, S.; Rashid, A.; Yeung, S.-C.J.; Hess, K.; Chen, H.; Tarco, E.; Chen, H.; Wei, C.; et al. Phase I study of the anti-IGF1R antibody cixutumumab with everolimus and octreotide in advanced well-differentiated neuroendocrine tumors. Endocr. Relat. Cancer 2015, 22, 431–441. [Google Scholar] [CrossRef]
  23. Jin, X.-F.; Spöttl, G.; Maurer, J.; Nölting, S.; Auernhammer, C.J. Inhibition of Wnt/β-Catenin Signaling in Neuroendocrine Tumors in vitro: Antitumoral Effects. Cancers 2020, 12, 345. [Google Scholar] [CrossRef] [PubMed]
  24. Jiang, L.; Hochwald, S.; Deng, S.; Zhu, Y.; Tan, C.; Zhong, Q.; Zhou, Y.; Zhao, H.; Huang, H. Evaluation of EGF, EGFR, and E-cadherin as potential biomarkers for gastrointestinal cancers. Front. Lab. Med. 2017, 1, 135–140. [Google Scholar] [CrossRef]
  25. Xiao, Z.; Xu, H.; Strosberg, J.R.; Lu, R.; Zhu, X.; Deng, S.; Ding, L.; Ni, Q.; Warshaw, A.L.; Yu, X.; et al. EGFR is a potential therapeutic target for highly glycosylated and aggressive pancreatic neuroendocrine neoplasms. Int. J. Cancer 2023, 153, 164–172. [Google Scholar] [CrossRef] [PubMed]
  26. Yao, J.C.; Hassan, M.M.; Phan, A.T.; Dagohoy, C.G.; Leary, C.C.; Mares, J.E.; Abdalla, E.K.; Fleming, J.B.; Vauthey, J.-N.; Rashid, A.; et al. One hundred years after “carcinoid”: Epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J. Clin. Oncol. 2008, 26, 3063–3072. [Google Scholar] [CrossRef]
  27. Modica, R.; Benevento, E.; Liccardi, A.; Cannavale, G.; Minotta, R.; DI Iasi, G.; Colao, A. Recent advances and future challenges in the diagnosis of neuroendocrine neoplasms. Minerva Endocrinol. 2024, 49, 158–174. [Google Scholar] [CrossRef] [PubMed]
  28. Passhak, M.; McNamara, M.G.; Hubner, R.A.; Ben-Aharon, I.; Valle, J.W. Choosing the best systemic treatment sequence for control of tumour growth in gastro-enteropancreatic neuroendocrine tumours (GEP-NETs): What is the recent evidence? Best. Pract. Res. Clin. Endocrinol. Metab. 2023, 37, 101836. [Google Scholar] [CrossRef]
  29. Dicitore, A.; Cantone, M.C. Targeting receptor tyrosine kinases in neuroendocrine neoplasm: What’s going on with lung carcinoids? Minerva Endocrinol. 2022, 47, 261–263. [Google Scholar] [CrossRef]
  30. Meric-Bernstam, F.; Gonzalez-Angulo, A.M. Targeting the mTOR signaling network for cancer therapy. J. Clin. Oncol. 2009, 27, 2278–2287. [Google Scholar] [CrossRef]
  31. Jiao, Y.; Shi, C.; Edil, B.H.; de Wilde, R.F.; Klimstra, D.S.; Maitra, A.; Schulick, R.D.; Tang, L.H.; Wolfgang, C.L.; Choti, M.A.; et al. DAXX/ATRX, MEN1, and mTOR pathway genes are frequently altered in pancreatic neuroendocrine tumors. Science 2011, 331, 1199–1203. [Google Scholar] [CrossRef] [PubMed]
  32. Meric-Bernstam, F.; Akcakanat, A.; Chen, H.; Do, K.-A.; Sangai, T.; Adkins, F.; Gonzalez-Angulo, A.M.; Rashid, A.; Crosby, K.; Dong, M.; et al. PIK3CA/PTEN mutations and Akt activation as markers of sensitivity to allosteric mTOR inhibitors. Clin. Cancer Res. 2012, 18, 1777–1789. [Google Scholar] [CrossRef] [PubMed]
  33. Yao, J.C.; Shah, M.H.; Ito, T.; Bohas, C.L.; Wolin, E.M.; Van Cutsem, E.; Hobday, T.J.; Okusaka, T.; Capdevila, J.; de Vries, E.G.; et al. Everolimus for advanced pancreatic neuroendocrine tumors. N. Engl. J. Med. 2011, 364, 514–523. [Google Scholar] [CrossRef] [PubMed]
  34. von Wichert, G.; Jehle, P.M.; Hoeflich, A.; Koschnick, S.; Dralle, H.; Wolf, E.; Wiedenmann, B.; Boehm, B.O.; Adler, G.; Seufferlein, T. Insulin-like growth factor-I is an autocrine regulator of chromogranin A secretion and growth in human neuroendocrine tumor cells. Cancer Res. 2000, 60, 4573–4581. [Google Scholar] [PubMed]
  35. Münzberg, C.; Höhn, K.; Krndija, D.; Maaß, U.; Bartsch, D.K.; Slater, E.P.; Oswald, F.; Walther, P.; Seufferlein, T.; von Wichert, G. IGF-1 drives chromogranin A secretion via activation of Arf1 in human neuroendocrine tumour cells. J. Cell. Mol. Med. 2015, 19, 948–959. [Google Scholar] [CrossRef] [PubMed]
  36. Höpfner, M.; Baradari, V.; Huether, A.; Schöfl, C.; Scherübl, H. The insulin-like growth factor receptor 1 is a promising target for novel treatment approaches in neuroendocrine gastrointestinal tumours. Endocr. Relat. Cancer 2006, 13, 135–149. [Google Scholar] [CrossRef] [PubMed]
  37. Thimmaiah, K.N.; Easton, J.; Huang, S.; Veverka, K.A.; Germain, G.S.; Harwood, F.C.; Houghton, P.J. Insulin-like growth factor I-mediated protection from rapamycin-induced apoptosis is independent of Ras-Erk1-Erk2 and phosphatidylinositol 3’-kinase-Akt signaling pathways. Cancer Res. 2003, 63, 364–374. [Google Scholar]
  38. O’Reilly, K.E.; Rojo, F.; She, Q.-B.; Solit, D.; Mills, G.B.; Smith, D.; Lane, H.; Hofmann, F.; Hicklin, D.J.; Ludwig, D.L.; et al. mTOR inhibition induces upstream receptor tyrosine kinase signaling and activates Akt. Cancer Res. 2006, 6, 1500–1508. [Google Scholar] [CrossRef] [PubMed]
  39. Lawnicka, H.; Motylewska, E.; Borkowska, M.; Kuzdak, K.; Siejka, A.; Swietoslawski, J.; Stepien, H.; Stepien, T. Elevated serum concentrations of IGF-1 and IGF-1R in patients with thyroid cancers. Biomed. Pap. Med. Fac. Univ. Palacky. Olomouc Czech Repub. 2020, 164, 77–83. [Google Scholar] [CrossRef]
  40. Manzella, L.; Massimino, M.; Stella, S.; Tirrò, E.; Pennisi, M.S.; Martorana, F.; Motta, G.; Vitale, S.R.; Puma, A.; Romano, C.; et al. Activation of the IGF Axis in Thyroid Cancer: Implications for Tumorigenesis and Treatment. Int. J. Mol. Sci. 2019, 20, 3258. [Google Scholar] [CrossRef]
  41. Zhong, W.; Wang, X.; Wang, Y.; Sun, G.; Zhang, J.; Li, Z. Obesity and endocrine-related cancer: The important role of IGF-1. Front. Endocrinol. 2023, 14, 1093257. [Google Scholar] [CrossRef] [PubMed]
  42. Chitnis, M.M.; Lodhia, K.A.; Aleksic, T.; Gao, S.; Protheroe, A.S.; Macaulay, V.M. IGF-1R inhibition enhances radiosensitivity and delays double-strand break repair by both non-homologous end-joining and homologous recombination. Oncogene 2014, 33, 5262–5273. [Google Scholar] [CrossRef] [PubMed]
  43. Ramcharan, R.; Aleksic, T.; Kamdoum, W.P.; Gao, S.; Pfister, S.X.; Tanner, J.; Bridges, E.; Asher, R.; Watson, A.J.; Margison, G.P.; et al. IGF-1R inhibition induces schedule-dependent sensitization of human melanoma to temozolomide. Oncotarget 2015, 6, 39877–39890. [Google Scholar] [CrossRef] [PubMed]
  44. Lloret, M.; Lara, P.C.; Bordón, E.; Pinar, B.; Rey, A.; Falcón, O.; Molano, F.; Hernández, M.A. IGF-1R expression in localized cervical carcinoma patients treated by radiochemotherapy. Gynecol. Oncol. 2007, 106, 8–11. [Google Scholar] [CrossRef] [PubMed]
  45. Dale, O.T.; Aleksic, T.; Shah, K.A.; Han, C.; Mehanna, H.; Rapozo, D.C.; Sheard, J.D.H.; Goodyear, P.; Upile, N.S.; Robinson, M.; et al. IGF-1R expression is associated with HPV-negative status and adverse survival in head and neck squamous cell cancer. Carcinogenesis 2015, 36, 648–655. [Google Scholar] [CrossRef] [PubMed]
  46. Liu, X.; Chen, H.; Xu, X.; Ye, M.; Cao, H.; Xu, L.; Hou, Y.; Tang, J.; Zhou, D.; Bai, Y.; et al. Insulin-like growth factor-1 receptor knockdown enhances radiosensitivity via the HIF-1α pathway and attenuates ATM/H2AX/53BP1 DNA repair activation in human lung squamous carcinoma cells. Oncol. Lett. 2018, 16, 1332–1340. [Google Scholar] [CrossRef]
  47. Ferté, C.; Loriot, Y.; Clémenson, C.; Commo, F.; Gombos, A.; Bibault, J.-E.; Fumagalli, I.; Hamama, S.; Auger, N.; Lahon, B.; et al. IGF-1R targeting increases the antitumor effects of DNA-damaging agents in SCLC model: An opportunity to increase the efficacy of standard therapy. Mol. Cancer Ther. 2013, 12, 1213–1222. [Google Scholar] [CrossRef] [PubMed]
  48. Moreno-Acosta, P.; Gamboa, O.; Sanchez-Gomez, M.; Cendales, R.; Diaz, G.D.; Romero, A.; Serra, J.B.; Conrado, Z.; Levy, A.; Chargari, C.; et al. IGF1R gene expression as a predictive marker of response to ionizing radiation for patients with locally advanced HPV16-positive cervical cancer. Anticancer Res. 2012, 32, 4319–4325. [Google Scholar]
  49. Valsecchi, M.E.; McDonald, M.; Brody, J.R.; Hyslop, T.; Freydin, B.; Yeo, C.J.; Solomides, C.; Peiper, S.C.; Witkiewicz, A.K. Epidermal growth factor receptor and insulinlike growth factor 1 receptor expression predict poor survival in pancreatic ductal adenocarcinoma. Cancer 2012, 118, 3484–3493. [Google Scholar] [CrossRef]
  50. Obr, A.E.; Kumar, S.; Chang, Y.-J.; Bulatowicz, J.J.; Barnes, B.J.; Birge, R.B.; Lazzarino, D.A.; Gallagher, E.; LeRoith, D.; Wood, T.L. Insulin-like growth factor receptor signaling in breast tumor epithelium protects cells from endoplasmic reticulum stress and regulates the tumor microenvironment. Breast Cancer Res. 2018, 20, 138. [Google Scholar] [CrossRef]
  51. Ekyalongo, R.C.; Yee, D. Revisiting the IGF-1R as a breast cancer target. npj Precis. Oncol. 2017, 1, 14. [Google Scholar] [CrossRef] [PubMed]
  52. Christopoulos, P.F.; Msaouel, P.; Koutsilieris, M. The role of the insulin-like growth factor-1 system in breast cancer. Mol. Cancer 2015, 14, 43. [Google Scholar] [CrossRef] [PubMed]
  53. Lee, J.S.; Tocheny, C.E.; Shaw, L.M. The Insulin-like Growth Factor Signaling Pathway in Breast Cancer: An Elusive Therapeutic Target. Life 2022, 12, 1992. [Google Scholar] [CrossRef] [PubMed]
  54. Soni, U.K.; Jenny, L.; Hegde, R.S. IGF-1R targeting in cancer–does sub-cellular localization matter? J. Exp. Clin. Cancer Res. 2023, 42, 273. [Google Scholar] [CrossRef] [PubMed]
  55. Kruger, D.T.; Alexi, X.; Opdam, M.; Schuurman, K.; Voorwerk, L.; Sanders, J.; van der Noort, V.; Boven, E.; Zwart, W.; Linn, S.C. IGF-1R pathway activation as putative biomarker for linsitinib therapy to revert tamoxifen resistance in ER-positive breast cancer. Int. J. Cancer 2020, 146, 2348–2359. [Google Scholar] [CrossRef] [PubMed]
  56. Chan, Y.-T.; Lin, R.-J.; Wang, Y.-H.; Hung, T.-H.; Huang, Y.; Yu, J.; Yu, J.-C.; Yu, A.L. The interplay between IGF-1R signaling and Hippo-YAP in breast cancer stem cells. Cell Commun. Signal. 2023, 21, 81. [Google Scholar] [CrossRef] [PubMed]
  57. Vantaggiato, C.; Formentini, I.; Bondanza, A.; Bonini, C.; Naldini, L.; Brambilla, R. ERK1 and ERK2 mitogen-activated protein kinases affect Ras-dependent cell signaling differentially. J. Biol. 2006, 5, 14. [Google Scholar] [CrossRef] [PubMed]
  58. Hu, X.; Li, J.; Fu, M.; Zhao, X.; Wang, W. The JAK/STAT signaling pathway: From bench to clinic. Sig. Transduct. Target. Ther. 2021, 6, 402. [Google Scholar] [CrossRef] [PubMed]
  59. Lefloch, R.; Pouysségur, J.; Lenormand, P. Single and combined silencing of ERK1 and ERK2 reveals their positive contribution to growth signaling depending on their expression levels. Mol. Cell. Biol. 2008, 28, 511–527. [Google Scholar] [CrossRef]
  60. Karhoff, D.; Sauer, S.; Schrader, J.; Arnold, R.; Fendrich, V.; Bartsch, D.K.; Hörsch, D. Rap1/B-Raf signaling is activated in neuroendocrine tumors of the digestive tract and Raf kinase inhibition constitutes a putative therapeutic target. Neuroendocrinology 2007, 85, 45–53. [Google Scholar] [CrossRef]
  61. Ahmed, M. Gastrointestinal neuroendocrine tumors in 2020. World J. Gastrointest. Oncol. 2020, 12, 791–807. [Google Scholar] [CrossRef] [PubMed]
  62. Takahashi, M.; Li, Y.; Dillon, T.J.; Stork, P.J. Phosphorylation of Rap1 by cAMP-dependent Protein Kinase (PKA) Creates a Binding Site for KSR to Sustain ERK Activation by cAMP. J. Biol. Chem. 2017, 292, 1449–1461. [Google Scholar] [CrossRef] [PubMed]
  63. Buzzelli, J.N.; Chalinor, H.V.; Pavlic, D.I.; Sutton, P.; Menheniott, T.R.; Giraud, A.S.; Judd, L.M. Decoding the Molecular and Mutational Ambiguities of Gastroenteropancreatic Neuroendocrine Neoplasm Pathobiology. Cell Mol. Gastroenterol. Hepatol. 2015, 1, 131–153. [Google Scholar] [CrossRef]
  64. Modlin, I.M.; Oberg, K.; Chung, D.C.; Jensen, R.T.; de Herder, W.W.; Thakker, R.V.; Caplin, M.; Delle Fave, G.; Kaltsas, G.A.; Krenning, E.P.; et al. Gastroenteropancreatic neuroendocrine tumours. Lancet Oncol. 2008, 9, 61–72. [Google Scholar] [CrossRef] [PubMed]
  65. Freudlsperger, C.; Burnett, J.R.; Friedman, J.A.; Kannabiran, V.R.; Chen, Z.; Van Waes, C. EGFR-PI3K-AKT-mTOR signaling in head and neck squamous cell carcinomas: Attractive targets for molecular-oriented therapy. Expert. Opin. Ther. Targets 2011, 15, 63–74. [Google Scholar] [CrossRef]
  66. Gan, Y.; Shi, C.; Inge, L.; Hibner, M.; Balducci, J.; Huang, Y. Differential roles of ERK and Akt pathways in regulation of EGFR-mediated signaling and motility in prostate cancer cells. Oncogene 2010, 29, 4947–4958. [Google Scholar] [CrossRef] [PubMed]
  67. Liu, Q.; Yu, S.; Zhao, W.; Qin, S.; Chu, Q.; Wu, K. EGFR-TKIs resistance via EGFR-independent signaling pathways. Mol. Cancer 2018, 17, 53. [Google Scholar] [CrossRef] [PubMed]
  68. Kallergi, G.; Agelaki, S.; Kalykaki, A.; Stournaras, C.; Mavroudis, D.; Georgoulias, V. Phosphorylated EGFR and PI3K/Akt signaling kinases are expressed in circulating tumor cells of breast cancer patients. Breast Cancer Res. 2008, 10, R80. [Google Scholar] [CrossRef]
  69. Novoplansky, O.; Shnerb, A.B.; Marripati, D.; Jagadeeshan, S.; Abu Shareb, R.; Conde-López, C.; Zorea, J.; Prasad, M.; Ben Lulu, T.; Yegodayev, K.M.; et al. Activation of the EGFR/PI3K/AKT pathway limits the efficacy of trametinib treatment in head and neck cancer. Mol. Oncol. 2023, 17, 2618–2636. [Google Scholar] [CrossRef]
  70. Toffoli, L.; Ditsiou, A.; Gagliano, T. Exploring Emerging Therapeutic Targets and Opportunities in Neuroendocrine Tumors: Updates on Receptor Tyrosine Kinases. Receptors 2024, 3, 145–154. [Google Scholar] [CrossRef]
  71. Smith, J.T.; Acohido, B.V.; Clifton, D.K.; Steiner, R.A. Epidermal growth factor receptor expression and activation in neuroendocrine tumours. J. Neuroendocrinol. 2006, 18, 355–360. [Google Scholar] [CrossRef]
  72. McClellan, K.; Chen, E.Y.; Kardosh, A.; Lopez, C.D.; Del Rivero, J.; Mallak, N.; Rocha, F.G.; Koethe, Y.; Pommier, R.; Mittra, E.; et al. Therapy Resistant Gastroenteropancreatic Neuroendocrine Tumors. Cancers 2022, 14, 4769. [Google Scholar] [CrossRef] [PubMed]
  73. Zhong, L.; Li, Y.; Xiong, L.; Wang, W.; Wu, M.; Yuan, T.; Yang, W.; Tian, C.; Miao, Z.; Wang, T.; et al. Small molecules in targeted cancer therapy: Advances, challenges, and future perspectives. Signal Transduct. Target. Ther. 2021, 6, 201. [Google Scholar] [CrossRef] [PubMed]
  74. Tas, F.; Bilgin, E.; Karabulut, S.; Duranyildiz, D. Clinical significance of serum epidermal growth factor receptor (EGFR) concentrations in patients with breast cancer. Cytokine 2015, 71, 66–70. [Google Scholar] [CrossRef] [PubMed]
  75. Asgeirsson, K.S.; Agrawal, A.; Allen, C.; Hitch, A.; Ellis, I.O.; Chapman, C.; Cheung, K.L.; Robertson, J.F. Serum epidermal growth factor receptor and HER2 expression in primary and metastatic breast cancer patients. Breast Cancer Res. 2007, 9, R75. [Google Scholar] [CrossRef] [PubMed]
  76. Kar, T.; Dugam, P.; Shivhare, S.; Shetty, S.R.; Choudhury, S.; Sen, D.; Deb, B.; Majumdar, S.; Debnath, S.; Das, A. Epidermal growth factor receptor inhibition potentiates chemotherapeutics-mediated sensitization of metastatic breast cancer stem cells. Cancer Rep. 2024, 7, e2049. [Google Scholar] [CrossRef] [PubMed]
  77. Kjær, I.M.; Olsen, D.A.; Brandslund, I.; Bechmann, T.; Jakobsen, E.H.; Bogh, S.B.; Madsen, J.S. Prognostic impact of serum levels of EGFR and EGFR ligands in early-stage breast cancer. Sci. Rep. 2020, 10, 16558. [Google Scholar] [CrossRef] [PubMed]
  78. Banys-Paluchowski, M.; Witzel, I.; Riethdorf, S.; Rack, B.; Janni, W.; Fasching, P.A.; Solomayer, E.F.; Aktas, B.; Kasimir-Bauer, S.; Pantel, K.; et al. Evaluation of serum epidermal growth factor receptor (EGFR) in correlation to circulating tumor cells in patients with metastatic breast cancer. Sci. Rep. 2017, 7, 17307. [Google Scholar] [CrossRef] [PubMed]
  79. Angelescu, R.; Burada, F.; Angelescu, C.; Gheonea, D.I.; Mixich, F.; Ioana, M.; Săftoiu, A. Expression of vascular endothelial growth factor and epidermal growth factor receptor in pancreatic ductal adenocarcinomas, neuroendocrine tumours and chronic pancreatitis. Endosc. Ultrasound. 2013, 2, 86–91. [Google Scholar] [CrossRef]
  80. Marcoux, N.; Gettinger, S.N.; O’kane, G.; Arbour, K.C.; Neal, J.W.; Husain, H.; Evans, T.L.; Brahmer, J.R.; Muzikansky, A.; Bonomi, P.D.; et al. EGFR-Mutant Adenocarcinomas That Transform to Small-Cell Lung Cancer and Other Neuroendocrine Carcinomas: Clinical Outcomes. J. Clin. Oncol. 2019, 37, 278–285. [Google Scholar] [CrossRef]
  81. Evangelou, G.; Vamvakaris, I.; Papafili, A.; Anagnostakis, M.; Peppa, M. Lung NETs and GEPNETs: One Cancer with Different Origins or Two Distinct Cancers? Cancers 2024, 16, 1177. [Google Scholar] [CrossRef] [PubMed]
  82. Cheng, Y.; Sun, Z.; Bai, C.; Yan, X.; Qin, R.; Meng, C.; Ying, H. Serum chromogranin A levels for the diagnosis and follow-up of well-differentiated non-functioning neuroendocrine tumors. Tumor Biol. 2016, 37, 2863–2869. [Google Scholar] [CrossRef]
  83. Chevallier, M.; Borgeaud, M.; Addeo, A.; Friedlaender, A. Oncogenic driver mutations in non-small cell lung cancer: Past, present and future. World J. Clin. Oncol. 2021, 12, 217–237. [Google Scholar] [CrossRef] [PubMed]
  84. O’leary, C.; Gasper, H.; Sahin, K.B.; Tang, M.; Kulasinghe, A.; Adams, M.N.; Richard, D.J.; O’byrne, K.J. Epidermal Growth Factor Receptor (EGFR)-Mutated Non-Small-Cell Lung Cancer (NSCLC). Pharmaceuticals 2020, 13, 273. [Google Scholar] [CrossRef] [PubMed]
  85. Gou, Q.; Gou, Q.; Gan, X.; Xie, Y. Novel therapeutic strategies for rare mutations in non-small cell lung cancer. Sci. Rep. 2024, 14, 10317. [Google Scholar] [CrossRef] [PubMed]
  86. Kim, T.; Jang, T.W.; Choi, C.M.; Kim, M.-H.; Lee, S.Y.; Chang, Y.S.; Lee, K.Y.; Kim, S.J.; Yang, S.H.; Ryu, J.S.; et al. Final Report on Real-World Effectiveness of Sequential Afatinib and Osimertinib in EGFR-Positive Advanced Non-Small Cell Lung Cancer: Updated Analysis of the RESET Study. Cancer Res. Treat. 2023, 55, 1152–1170. [Google Scholar] [CrossRef] [PubMed]
  87. Iyer, R.S.; Needham, S.R.; Galdadas, I.; Davis, B.M.; Roberts, S.K.; Man, R.C.H.; Zanetti-Domingues, L.C.; Clarke, D.T.; Fruhwirth, G.O.; Parker, P.J.; et al. Drug-resistant EGFR mutations promote lung cancer by stabilizing interfaces in ligand-free kinase-active EGFR oligomers. Nat. Commun. 2024, 15, 2130. [Google Scholar] [CrossRef] [PubMed]
  88. Halder, S.; Basu, S.; Lall, S.P.; Ganti, A.K.; Batra, S.K.; Seshacharyulu, P. Targeting the EGFR signaling pathway in cancer therapy: What’s new in 2023? Expert Opin. Ther. Targets 2023, 27, 305–324. [Google Scholar] [CrossRef]
  89. Friedlaender, A.; Perol, M.; Banna, G.L.; Parikh, K.; Addeo, A. Oncogenic alterations in advanced NSCLC: A molecular super-highway. Biomark. Res. 2024, 12, 24. [Google Scholar] [CrossRef]
  90. Hernandez-Rienda, L.; Del Olmo-García, M.I.; Merino-Torres, J.F. Impact of Diabetes Mellitus in Patients with Pancreatic Neuro-Endocrine Tumors: Causes, Consequences, and Future Perspectives. Metabolites 2022, 12, 1103. [Google Scholar] [CrossRef]
  91. Gallo, M.; Ruggeri, R.M.; Muscogiuri, G.; Pizza, G.; Faggiano, A.; Colao, A. NIKE Group. Diabetes and pancreatic neuroendocrine tumours: Which interplays, if any? Cancer Treat. Rev. 2018, 67, 1–9. [Google Scholar] [CrossRef] [PubMed]
Applsci 14 06998 g001
Figure 1. Median concentration of EGFR in the study and control groups.
Figure 1. Median concentration of EGFR in the study and control groups.
Applsci 14 06998 g001
Table 1. Biochemical characteristics of the study group (n = 80).
Table 1. Biochemical characteristics of the study group (n = 80).
ParametersStudy Group
Me (Q1–Q3)
Chromogranin A [µg/L]48.1 (29.7–82.2)
Serotonin [ng/mL]139.1 (91.2–259.4)
5-hydroxyindole acetic acid (5-HIAA) [mg/24 h]3.1 (2.0–4.7)
Glucose [mg/dL]96.0 (88.6–106.5)
Total cholesterol (TCH) [mg/dL]209.9 (169.5–235.0)
Triglycerides (TG) [mg/dL]96.5 (75.5–124.5)
Legend: Me—median, Q1—lower quartile, Q3—upper quartile.
Table 2. Characteristics of the study group.
Table 2. Characteristics of the study group.
Classificationn (% of Patients)
Location of the
primary
tumor		BP-NET casesLung16 (20%)
GEP-NET casesPancreas24 (30%)
Small intestine21 (26%)
Stomach8 (10%)
Rectum7 (9%)
Duodenum4 (5%)
Histological grade for
GEP-NET cases		NET G140 (50%)
NET G221 (26%)
NET G33 (4%)
Histological grade for
BP-NET cases		Typical carcinoid (TC)10 (11%)
Atypical (ATC)6 (8%)
MetastasisYes35 (44%)
No45 (56%)
Liver metastasisYes20 (25%)
No60 (75%)
Lymph node metastasisYes27 (34%)
No53 (66%)
Bone metastasisYes7 (9%)
No73 (91%)
Clinical stageI36 (45%)
II8 (10%)
III11 (14%)
IV25 (31%)
Ki-67<3%45 (56%)
3% to 20%31 (39%)
>21%4 (5%)
Legend: BP-NET—neuroendocrine tumor of the respiratory system, GEP-NET—neuroendocrine tumor of the digestive tract.
Table 3. Comparison of demographic characteristics between the study and the control group.
Table 3. Comparison of demographic characteristics between the study and the control group.
Control Group
M ± SD		Study Group
M ± SD		tp
Age [years]52.7 ± 11.556.2 ± 12.51.750.083
BMI [kg/m2]26.3 ± 4.126.2 ± 5.30.870.385
Legend: M ± SD—mean ± standard deviation, t—Student’s t-test statistic value, p—statistical significance.
Table 4. Characteristics of the study and control groups.
Table 4. Characteristics of the study and control groups.
VariantControl Group
n (%)		Study Group
n (%)		χ2p
SexMale23 (37%)36 (45%)0.900.343
Female39 (63%)44 (55%)
DiabetesYes2 (3%)13 (16%)6.27<0.05
No60 (97%)67 (84%)
HypertensionYes17 (27%)30 (38%)1.600.205
No45 (73%)50 (62%)
SmokingYes9 (14%)12 (15%)0.010.911
No53 (86%)68 (85%)
Legend: χ2—Chi-square test of independence statistic value, p—statistical significance.
Table 5. Comparison of IGF-1R, ERK2, and EGFR concentrations for the study and the control groups.
Table 5. Comparison of IGF-1R, ERK2, and EGFR concentrations for the study and the control groups.
ParametersControl Group
Me (Q1–Q3)		Study Group
Me (Q1–Q3)		zp
IGF-1R [pg/mL]22.9 (18.6–22.9)27.2 (22.9–27.2)1.050.289
ERK2 [pg/mL]432.9 (312.0–632.9)430.4 (359.2–568.9)0.120.901
EGFR [pg/mL]7771.1 (7296.5–8966.5)10,257.7 (9314.7–11,290.9)7.25<0.001
Legend: Me (Q1–Q3)—median (lower–upper quartile); z—Mann–Whitney U test statistic value, p—statistical significance.
Table 6. Correlation between age, BMI, Ki-67, clinical state, and the measured parameters for the study and control groups.
Table 6. Correlation between age, BMI, Ki-67, clinical state, and the measured parameters for the study and control groups.
ParametersControl GroupStudy Group
ρpρp
AgeIGF-1R [pg/mL]0.1200.3590.0730.523
ERK2 [pg/mL]0.1780.1650.0280.807
EGFR [pg/mL]0.1350.2940.1300.267
BMIIGF-1R [pg/mL]0.2470.0570.1430.207
ERK2 [pg/mL]−0.0420.7430.1190.298
EGFR [pg/mL]−0.289<0.05−0.6730.503
Ki-67IGF-1R [pg/mL]--0.0550.633
ERK2 [pg/mL]--0.1770.141
EGFR [pg/mL]--−0.0130.910
Clinical stageIGF-1R [pg/mL]--−0.0120.921
ERK2 [pg/mL]--−0.0590.606
EGFR [pg/mL]--0.2040.079
Legend: ρ—Spearman’s correlation coefficient; p—statistical significance.
Table 7. Concentrations of parameters related to BP-NETs and GEP-NETs.
Table 7. Concentrations of parameters related to BP-NETs and GEP-NETs.
ParametersBP-NET
Me (Q1–Q3)		GEP-NET
Me (Q1–Q3)		zp
IGF-1R [pg/mL]27.2 (22.9–27.2)27.2 (19.7–27.2)0.040.968
ERK2 [pg/mL]461.8 (378.0–560.5)430.4 (356.5–595.1)0.030.980
EGFR [pg/mL]10,087 (9413–10,852)10,408 (9314–11,291)0.27<0.001
Legend: Me (Q1–Q3)—median (lower–upper quartile); z—Mann–Whitney U test statistic value, p—statistical significance.
Table 8. Concentration of parameters related to known NET marker.
Table 8. Concentration of parameters related to known NET marker.
ParametersStudy Group
ρp
Chromogranin A [µg/L]IGF-1R−0.0410.722
ERK20.0250.830
EGFR0.296<0.05
Serotonin [ng/mL]IGF-1R0.0670.568
ERK2−0.1450.214
EGFR0.2220.061
5-hydroxyindole acetic acid (5-HIAA) [mg/24 h]IGF-1R0.0920.422
ERK20.1210.293
EGFR0.1500.200
Legend: ρ—Spearman’s correlation coefficient, p—statistical significance.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Duszkiewicz, R.; Strzelczyk, J.; Chełmecka, E.; Strzelczyk, J.K. Serum Concentrations of IGF-1R, ERK2, and EGFR and Their Clinical Significance in Patients with Neuroendocrine Tumors. Appl. Sci. 2024, 14, 6998. https://doi.org/10.3390/app14166998

AMA Style

Duszkiewicz R, Strzelczyk J, Chełmecka E, Strzelczyk JK. Serum Concentrations of IGF-1R, ERK2, and EGFR and Their Clinical Significance in Patients with Neuroendocrine Tumors. Applied Sciences. 2024; 14(16):6998. https://doi.org/10.3390/app14166998

Chicago/Turabian Style

Duszkiewicz, Roksana, Janusz Strzelczyk, Elżbieta Chełmecka, and Joanna Katarzyna Strzelczyk. 2024. "Serum Concentrations of IGF-1R, ERK2, and EGFR and Their Clinical Significance in Patients with Neuroendocrine Tumors" Applied Sciences 14, no. 16: 6998. https://doi.org/10.3390/app14166998

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop