Correlation of UGT2B7 Polymorphism with Cardiotoxicity in Breast Cancer Patients Undergoing Epirubicin/Cyclophosphamide-Docetaxel Adjuvant Chemotherapy

Li, Hai; Hu, Bo; Guo, Zhe; Jiang, Xin; Su, Xinyu; Zhang, Xiaoyi

doi:10.3349/ymj.2019.60.1.30

Cited by 16 publications

(17 citation statements)

References 17 publications

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“…Li et al studied the occurrence of cytotoxicity in breast cancer patients undergoing chemotherapy along with the expression of the UGT2B7 gene. Their results showed that breast cancer patients with the UGT2B7 gene had a lower occurrence of cardiotoxicity [ 42 ]. It has also been found by Mou et al that a gene in the UGT2B7 gene called RS745335 was associated with breast cancer patients receiving chemotherapy, therefore making RS745335 and UGT2B7 potential biomarkers for breast cancer [ 43 ].…”

Section: Biological Insightmentioning

confidence: 99%

Classification of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding and Residual Neural Network

Zhou

Rueda

Alkhateeb

2022

Cancers

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The Nottingham Prognostics Index (NPI) is a prognostics measure that predicts operable primary breast cancer survival. The NPI value is calculated based on the size of the tumor, the number of lymph nodes, and the tumor grade. Next-generation sequencing advancements have led to measuring different biological indicators called multi-omics data. The availability of multi-omics data triggered the challenge of integrating and analyzing these various biological measures to understand the progression of the diseases. High-dimensional embedding techniques are incorporated to present the features in the lower dimension, i.e., in a 2-dimensional map. The dataset consists of three -omics: gene expression, copy number alteration (CNA), and mRNA from 1885 female patients. The model creates a gene similarity network (GSN) map for each omic using t-distributed stochastic neighbor embedding (t-SNE) before being merged into the residual neural network (ResNet) classification model. The aim of this work was to (i) extract multi-omics biomarkers that are associated with the prognosis and prediction of breast cancer survival; and (ii) build a prediction model for multi-class breast cancer NPI classes. We evaluated this model and compared it to different high-dimensional embedding techniques and neural network combinations. The proposed model outperformed the other methods with an accuracy of 98.48%, and the area under the curve (AUC) equals 0.9999. The findings in the literature confirm associations between some of the extracted omics and breast cancer prognosis and survival including CDCA5, IL17RB, MUC2, NOD2 and NXPH4 from the gene expression dataset; MED30, RAD21, EIF3H and EIF3E from the CNA dataset; and CENPA, MACF1, UGT2B7 and SEMA3B from the mRNA dataset.

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Section: Biological Insightmentioning

confidence: 99%

Classification of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding and Residual Neural Network

Zhou

Rueda

Alkhateeb

2022

Cancers

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“…Eighteen new studies describe the significant association of 57 polymorphic variations with cardiac toxicity induced by cancer therapy [40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57] (Table 3 and Supporting Information, Table S3, Sheet G). These DNA polymorphisms are presented in genes associated with drug metabolism and detoxification.…”

Section: Novel Dna Biomarkers Associated With Cardiotoxicitymentioning

confidence: 99%

“…The first approach utilizes highthroughput analysis to identify new biomarkers among the total of molecules studied. 33,35,37,40,43,[45][46][47][48][49][50][51][52][53]58,62,64,67 The second approach, used in the most of articles, is a directed selection based on a previous literature search. Further, in an attempt to provide a biological context of these novel molecular biomarkers with cancer therapy-induced cardiotoxicity, three articles performed a network analysis where they identified an over-representation of biological processes involved in apoptosis, immune response, drug/response transport, collagen metabolism, and activation of matrix metalloproteinases.…”

Section: Summary Of Findingsmentioning

confidence: 99%

Novel molecular biomarkers of cancer therapy‐induced cardiotoxicity in adult population: a scoping review

et al. 2022

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Aim Cancer treatments are associated with cardiotoxic events that predispose to cardiac pathology and compromise the survival of patients, making necessary the identification of new molecular biomarkers to detect cardiotoxicity. This scoping review aims to identify the available evidence on novel molecular biomarkers associated with cardiotoxicity in the adult population undergoing cancer therapy. Methods and resultsThe databases Medline, Web of Science, Scopus, and Embase were screened for the identification of published studies until 23 August 2020, searching for novel molecular biomarkers reported in cancer therapy-related cardiac dysfunction in adult patients. A total of 42 studies that met the eligibility criteria were included. Fourteen studies reported 44 new protein biomarkers, 18 studies reported 57 new single nucleotide polymorphism biomarkers, and 11 studies reported 171 new gene expression profiles associated with cardiotoxicity. Data were extracted for 272 novel molecular biomarkers reported and evaluated in 7084 cancer patients, of which only 13 were identified in more than one study (MPO, sST2, GDF-15, TGF-B1, rs1056892, rs1883112, rs4673, rs13058338, rs1695, miR-1, miR-25-3p, miR-34a-5p, and miR-423-5p), showing values for area under the curve > 0.73 (range 0.74-0.85), odds ratio 0.26-7.17, and hazard ratio 1.28-1.80. Conclusions Multiple studies presented a significant number of novel molecular biomarkers as promising predictors for risk assessment of cardiac dysfunction related to cancer therapy, but the characteristics of the studies carried out and the determinations applied do not allow suggesting the clinical use of these molecular biomarkers in the assessment of cancer therapy-induced cardiotoxicity.

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“…Five candidate-gene studies with a total of 1,779 females BC only participants were screened for polymorphisms in selected genes (Vulsteke et al, 2015;Hertz et al, 2016;Reinbolt et al, 2016;Liu et al, 2018;Li et al, 2019). Although these studies were homogeneous in terms of patient inclusion, they used different cardiotoxicity definitions, different endpoints, and the rationale behind selected genes in each study.…”

Section: Pgx Studies Of Aicmentioning

confidence: 99%

“…T allele UGT2B7 -161 with decreased risk of ACT (P = 0.004) (Li et al, 2019) AIC, anthracycline-induced cardiotoxicity; BC, breast cancer; Epi, epirubicin; Dox, doxorubicin; EF, ejection fraction; ECG, elecrtocardiography; LVEF, left ventricular ejection fraction. *The mentioned genes were not fully covered in these studies, only specific polymorphisms in these genes were tested.…”

Section: Ugt2b7mentioning

confidence: 99%

Toxicity and Pharmacogenomic Biomarkers in Breast Cancer Chemotherapy

2020

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Breast cancer (BC) is one of the most prevalent types of cancer worldwide with high morbidity and mortality rates. Treatment modalities include systemic therapy, in which chemotherapy is a major component in many cases. Several chemotherapeutic agents are used in combinations or as single agents with many adverse events occurring in variable frequencies. These events can be a significant barrier in completing the treatment regimens. Germline genomic variants are thought of as potential determinants in chemotherapy response and the development of side effects. Some pharmacogenomic studies were designed to explore germline variants that can be used as biomarkers for predicting developing toxicity or adverse events during chemotherapy in BC. In this review, we reassess and summarize the major findings of pharmacogenomic studies of chemotherapy toxicity during BC management. In addition, deficiencies hampering utilizing these findings and the potential targets of future research are emphasized. Main insufficiencies in toxicity pharmacogenomics studies originate from study design, sample limitations, heterogeneity of selected genes, variants, and toxicity definitions. With the advent of high throughput genotyping techniques, researchers are expected to explore the identified as well as the potential genetic biomarkers of toxicity and efficacy to improve BC management. However, to achieve this, the limitations of previous work should be evaluated and avoided to reach more conclusive and translatable evidence for personalizing BC chemotherapy.

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Correlation of UGT2B7 Polymorphism with Cardiotoxicity in Breast Cancer Patients Undergoing Epirubicin/Cyclophosphamide-Docetaxel Adjuvant Chemotherapy

Cited by 16 publications

References 17 publications

Classification of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding and Residual Neural Network

Classification of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding and Residual Neural Network

Novel molecular biomarkers of cancer therapy‐induced cardiotoxicity in adult population: a scoping review

Toxicity and Pharmacogenomic Biomarkers in Breast Cancer Chemotherapy

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