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Genome Research and Personalized Medicine in Breast Cancer

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A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Methodology, Drug and Device Discovery".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 14497

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Special Issue Editors

Prof. Dr. Matthias Schwab

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Guest Editor

Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart and Department of Clinical Pharmacology, Institute of Experimental and Clinical Pharmacology and Toxicology and Interfaculty Center for Pharmacogenomics and Drug Research (ICEPHA), University Hospital, Tuebingen Auerbachstrasse 112, 70376 Stuttgart, Germany
Interests: pharmacogenomics/epigenetics of drug metabolizing enzymes; drug transporters and nuclear receptors; pharmacogenomics of anticancer and immunosuppressive drugs; drug interaction
Special Issues, Collections and Topics in MDPI journals

Dr. Werner Schroth

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Co-Guest Editor

Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Auerbachstrasse 112, 70376 Stuttgart, Germany
Interests: pharmacogenomics of breast cancer; estrogen receptor regulation and signaling; treatment prediction; tumor profiling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Despite improved outcomes due to advanced systemic and targeted treatments, many breast cancer patients experience cancer relapse or drug-induced toxicities. Treatment-refractory outcomes result from intrinsic tumor biology, treatment-induced resistance traits, as well as host factors such as impaired drug metabolism and endogenous ligands interfering with drug–target action. Personalized treatment that utilizes precise patient selection and/or multimodal target approaches holds promise to mitigate clinical resistance to therapy.

This Special Issue of the Journal of Personalized Medicine aims to highlight the role of personalized medicine in both early and advanced breast cancer. Investigations at the level of tumor (epi)genome, pharmacogenomics and other omics technologies, immuno-oncology, or bioinformatic prediction tools are appreciated. Articles comprising basic science, clinical research, implementation or reviews are solicited that demonstrate how personalized medicine may improve outcomes of early (aggressive) or advanced breast cancer stages and help to avoid drug failure and toxicities.

Prof. Dr. Matthias Schwab
Dr. Werner Schroth
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Breast cancer
Personalized medicine
Genome research
Pharmacogenomics
Immuno-oncology
Omics Technologies
Prediction tools
Adverse drug reaction
Multimodal cancer treatment

Published Papers (6 papers)

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Editorial

Jump to: Research

2 pages, 174 KiB

Open AccessEditorial

Variable Drug-Target Exposure, Tumor Signatures, and Combinatorial Targeted Treatment: Approaches of Personalized Medicine in Breast Cancer

by Werner Schroth and Matthias Schwab

J. Pers. Med. 2022, 12(6), 917; https://doi.org/10.3390/jpm12060917 - 1 Jun 2022

Viewed by 1277

Abstract

The Special Issue “Genome Research and Personalized Medicine in Breast Cancer” presents studies on personalized medicine in breast cancer, originally with a focus on genomic treatment prediction at all stages of disease [...] Full article

(This article belongs to the Special Issue Genome Research and Personalized Medicine in Breast Cancer)

Research

Jump to: Editorial

10 pages, 961 KiB

Open AccessArticle

(Z)-Endoxifen and Early Recurrence of Breast Cancer: An Explorative Analysis in a Prospective Brazilian Study

by Thais Almeida, Werner Schroth, Jeanine Nardin, Thomas E. Mürdter, Stefan Winter, Solane Picolotto, Reiner Hoppe, Jenifer Kogin, Elisa Gaio, Angela Dasenbrock, Raquel Cristina Skrsypcsak, Lucia de Noronha, Matthias Schwab, Hiltrud Brauch and José Claudio Casali-da-Rocha

J. Pers. Med. 2022, 12(4), 511; https://doi.org/10.3390/jpm12040511 - 22 Mar 2022

Cited by 4 | Viewed by 1976

Abstract

Adherence to treatment and use of co-medication, but also molecular factors such as CYP2D6 genotype, affect tamoxifen metabolism, with consequences for early breast cancer prognosis. In a prospective study of 149 tamoxifen-treated early-stage breast cancer patients from Brazil followed up for 5 years, we investigated the association between the active tamoxifen metabolite (Z)-endoxifen at 3 months and event-free survival (EFS) adjusted for clinico-pathological factors. Twenty-five patients (16.8%) had recurred or died at a median follow-up of 52.3 months. When we applied a putative 15 nM threshold used in previous independent studies, (Z)-endoxifen levels below the threshold showed an association with shorter EFS in univariate analysis (p = 0.045) and after adjustment for stage (HR 2.52; 95% CI 1.13–5.65; p = 0.024). However, modeling of plasma concentrations with splines instead of dichotomization did not verify a significant association with EFS (univariate analysis: p = 0.158; adjusted for stage: p = 0.117). Hence, in our small exploratory study, the link between impaired tamoxifen metabolism and early breast cancer recurrence could not be unanimously demonstrated. This inconsistency justifies larger modeling studies backed up by mechanistic pharmacodynamic analyses to shed new light on this suspected association and the stipulation of an appropriate predictive (Z)-endoxifen threshold. Full article

(This article belongs to the Special Issue Genome Research and Personalized Medicine in Breast Cancer)

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Graphical abstract

10 pages, 717 KiB

Open AccessArticle

Feasibility of Adjuvant Treatment with Abemaciclib—Real-World Data from a Large German Breast Center

by Dominik Dannehl, Lea L. Volmer, Martin Weiss, Sabine Matovina, Eva-Maria Grischke, Ernst Oberlechner, Anna Seller, Christina B. Walter, Markus Hahn, Tobias Engler, Sara Y. Brucker and Andreas D. Hartkopf

J. Pers. Med. 2022, 12(3), 382; https://doi.org/10.3390/jpm12030382 - 2 Mar 2022

Cited by 7 | Viewed by 2812

Abstract

Abemaciclib significantly improves invasive disease-free survival when combined with endocrine therapy in clinical high-risk patients with HR+/Her2− early breast cancer (eBC). The objective of the following study was to model how many patients with eBC would be available for adjuvant treatment with abemaciclib in a real-world setting. Patients that underwent complete surgical treatment for eBC between January 2018 and December 2020 in a large single-center university hospital in Germany were eligible. Descriptive statistics were used to describe the patient population that could benefit from abemaciclib according to the inclusion criteria of monarchE. Of 1474 patients with eBC, 1121 (76.1%) had a HR+/Her2− subtype. Of these, 217 (19.4%) fulfilled the monarchE inclusion criteria. Within patients that fulfilled the monarchE inclusion criteria, 48.9% received no adjuvant or neoadjuvant chemotherapy. Thus, in a real-world situation, fewer patients will be pretreated with chemotherapy than was the case in monarchE. Breast care units are facing a significant patient burden, since the 2-year abemaciclib therapy requires regular monitoring of toxicities. Specific care concepts to strengthen therapy adherence as well as further studies to deescalate adjuvant systemic treatment and individualize CDK 4/6 inhibitor therapy are therefore needed. Full article

(This article belongs to the Special Issue Genome Research and Personalized Medicine in Breast Cancer)

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16 pages, 3931 KiB

Open AccessArticle

Molecular Prognostic Factors for Distant Metastases in Premenopausal Patients with HR+/HER2− Early Breast Cancer

by Hua Ni, Jörg Kumbrink, Doris Mayr, Alina Seiler, Friederike Hagemann, Tom Degenhardt, Sabine Sagebiel, Rachel Würstlein, Ronald Kates, Nadia Harbeck and Tanja K. Eggersmann

J. Pers. Med. 2021, 11(9), 835; https://doi.org/10.3390/jpm11090835 - 25 Aug 2021

Cited by 5 | Viewed by 2116

Abstract

Molecular factors that drive metastasis in premenopausal patients with hormone receptor positive (HR+), human epidermal growth factor receptor 2 negative (HER2−), early breast cancer (EBC) are largely unknown. To identify markers/signatures contributing to metastasis, we analyzed molecular changes in tumors from premenopausal patients who developed metastasis (M1) and who did not (M0). Ninety-seven premenopausal patients with HR+/HER2− EBC were included (M1, n = 48, median distant metastasis-free survival (DMFS): 54 (7–184) months; M0, n = 49, median follow-up: 149 (121–191) months). Gene expression profiling on tumor RNA (Breast Cancer 360^TM panel, Nanostring) was performed, followed by comprehensive bioinformatic and statistical analyses. Significantly enhanced ROR (risk of recurrence) scores and reduced signature scores of PGR (progesterone receptor), claudin-low, and mammary stemness were determined in M1. These differences were significantly associated with shorter DMFS in univariate survival analyses. Gene set enrichment analysis showed an enriched mTORC1 pathway in M1. Moreover, a metastasis signature of 19 differentially expressed genes (DEGs) that were DMFS-related was defined. Multivariate analysis including the four signatures, 19 DEGs, pN, and pT status, identified LRP2, IBSP, and SCUBE2 as independent prognostic factors. We identified prognostic gene signatures and single-gene markers for distant metastasis in premenopausal HR+/HER2− EBC potentially applicable in future clinical practice. Full article

(This article belongs to the Special Issue Genome Research and Personalized Medicine in Breast Cancer)

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18 pages, 4698 KiB

Open AccessArticle

Targeted Sequencing of Taiwanese Breast Cancer with Risk Stratification by the Concurrent Genes Signature: A Feasibility Study

by Ching-Shui Huang, Chih-Yi Liu, Tzu-Pin Lu, Chi-Jung Huang, Jen-Hwey Chiu, Ling-Ming Tseng and Chi-Cheng Huang

J. Pers. Med. 2021, 11(7), 613; https://doi.org/10.3390/jpm11070613 - 28 Jun 2021

Cited by 2 | Viewed by 2232

Abstract

Breast cancer is the most common female malignancy in Taiwan, while conventional clinical and pathological factors fail to provide full explanation for prognostic heterogeneity. The aim of the study was to evaluate the feasibility of targeted sequencing combined with concurrent genes signature to identify somatic mutations with clinical significance. The extended concurrent genes signature was based on the coherent patterns between genomic and transcriptional alterations. Targeted sequencing of 61 Taiwanese breast cancers revealed 1036 variants, including 76 pathogenic and 545 likely pathogenic variants based on the ACMG classification. The most frequently mutated genes were NOTCH, BRCA1, AR, ERBB2, FANCA, ATM, and BRCA2 and the most common pathogenic deletions were FGFR1, ATM, and WT1, while BRCA1 (rs1799965), FGFR2 (missense), and BRCA1 (rs1799949) were recurrent pathogenic SNPs. In addition, 38 breast cancers were predicted into 12 high-risk and 26 low-risk cases based on the extended concurrent genes signature, while the pathogenic PIK3CA variant (rs121913279) was significantly mutated between groups. Two deleterious SH3GLB2 mutations were further revealed by multivariate Cox’s regression (hazard ratios: 29.4 and 16.1). In addition, we identified several significantly mutated or pathogenic variants associated with differentially expressed signature genes. The feasibility of targeted sequencing in combination with concurrent genes risk stratification was ascertained. Future study to validate clinical applicability and evaluate potential actionability for Taiwanese breast cancers should be initiated. Full article

(This article belongs to the Special Issue Genome Research and Personalized Medicine in Breast Cancer)

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12 pages, 585 KiB

Open AccessFeature PaperArticle

Effect of Genetic Variability in 20 Pharmacogenes on Concentrations of Tamoxifen and Its Metabolites

by Yuanhuang Chen, Lauren A. Marcath, Finn Magnus Eliassen, Tone Hoel Lende, Havard Soiland, Gunnar Mellgren, Thomas Helland and Daniel Louis Hertz

J. Pers. Med. 2021, 11(6), 507; https://doi.org/10.3390/jpm11060507 - 4 Jun 2021

Cited by 5 | Viewed by 2883

Abstract

Background: Tamoxifen, as a treatment of estrogen receptor positive (ER+) breast cancer, is a weak anti-estrogen that requires metabolic activation to form metabolites with higher anti-estrogenic activity. Endoxifen is the most-studied active tamoxifen metabolite, and endoxifen concentrations are highly associated with CYP2D6 activity. Associations of tamoxifen efficacy with measured or CYP2D6-predicted endoxifen concentrations have been inconclusive. Another active metabolite, 4-OHtam, and other, less active metabolites, Z-4′-endoxifen and Z-4′-OHtam, have also been reported to be associated with tamoxifen efficacy. Method: Genotype for 20 pharmacogenes was determined by VeriDose^® Core Panel and VeriDose^®CYP2D6 CNV Panel, followed by translation to metabolic activity phenotype following standard activity scoring. Concentrations of tamoxifen and seven metabolites were measured by UPLC-MS/MS in serum samples collected from patients receiving 20 mg tamoxifen per day. Metabolic activity was tested for association with tamoxifen and its metabolites using linear regression with adjustment for upstream metabolites to identify genes associated with each step in the tamoxifen metabolism pathway. Results: A total of 187 patients with genetic and tamoxifen concentration data were included in the analysis. CYP2D6 was the primary gene associated with the tamoxifen metabolism pathway, especially the conversion of tamoxifen to endoxifen. CYP3A4 and CYP2C9 were also responsible for the metabolism of tamoxifen. CYP2C9 especially impacted the hydroxylation to 4-OHtam, and this involved the OATP1B1 (SLCO1B1) transporter. Conclusion: Multiple genes are involved in tamoxifen metabolism and multi-gene panels could be useful to predict active metabolite concentrations and guide tamoxifen dosing. Full article

(This article belongs to the Special Issue Genome Research and Personalized Medicine in Breast Cancer)

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