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

New Insights in the Era of Clinical Biomarkers as Potential Predictors of Systemic Therapy-Induced Cardiotoxicity in Women with Breast Cancer: A Systematic Review

Cardiotoxicity induced by breast cancer therapies is a potentially serious complication associated with the use of various breast cancer therapies. Prediction and better management of cardiotoxicity in patients receiving chemotherapy is of critical importance. However, the management of cancer therapy-related cardiac dysfunction (CTRCD) lacks clinical evidence and is based on limited clinical studies.

AIM

To provide an overview of existing and potentially novel biomarkers that possess a promising predictive value for the early and late onset of CTRCD in the clinical setting.

METHODS

A systematic review of published studies searching for promising biomarkers for the prediction of CTRCD in patients with breast cancer was undertaken according to PRISMA guidelines. A search strategy was performed using PubMed, Google Scholar, and Scopus for the period 2013-2023. All subjects were >18 years old, diagnosed with breast cancer, and received breast cancer therapies.

RESULTS

The most promising biomarkers that can be used for the development of an alternative risk cardiac stratification plan for the prediction and/or early detection of CTRCD in patients with breast cancer were identified.

CONCLUSIONS

We highlighted the new insights associated with the use of currently available biomarkers as a standard of care for the management of CTRCD and identified potentially novel clinical biomarkers that could be further investigated as promising predictors of CTRCD.

Risk factors from Framingham risk score for anthracyclines cardiotoxicity in breast cancer: A systematic review and meta-analysis

Background

Framingham risk score (FRS) is an effective tool for evaluating the 10-year risk of cardiovascular diseases. However, the sensitivity of FRS for anthracycline-induced cardiotoxicity is unclear. This meta-analysis aims to evaluate the correlation between risk factors (hypertension, hyperlipidemia, diabetes, smoking, and obesity) in FRS and anthracycline-induced cardiotoxicity in breast cancer.

Methods

We searched PubMed, EMBASE, and Cochrane Library for studies published from inception to January 2022 which reported cardiotoxicity due to anthracycline. Cardiotoxicity defined as any cardiac events were used as the primary endpoint. A total of 33 studies involving 55,708 breast cancer patients treated with anthracyclines were included in this meta-analysis.

Results

At least one risk factor was identified at baseline for the 55,708 breast cancer patients treated with anthracycline. Hypertension [I ² = 45%, Fixed, RR (95% CI) = 1.40 (1.22, 1.60), p < 0.00001], hyperlipidemia [I ² = 0%, Fixed, RR (95% CI): 1.35 (1.12, 1.62), p = 0.002], diabetes [I ² = 0%, Fixed, RR (95% CI): 1.29 (1.05, 1.57), p = 0.01], and obesity [I ² = 0%, Fixed, RR (95% CI): 1.32 (1.05, 1.67), p = 0.02] were associated with increased risks of cardiac events. In addition, smoking was also associated with reduced left ventricular ejection fraction (LVEF) during anthracycline chemotherapy [I ² = 0%, Fixed, OR (95% CI): 1.91 (1.24, 2.95), p = 0.003] in studies that recorded only the odds ratio (OR).

Conclusion

Hypertension, hyperlipidemia, diabetes, smoking, and obesity are associated with increased risks of anthracycline-induced cardiotoxicity. Therefore, corresponding measures should be used to manage cardiovascular risk factors in breast cancer during and after anthracycline treatment.

Pharmacogenomics in drug-induced cardiotoxicity: Current status and the future

Drug-induced cardiotoxicity (DICT) is an important concern of drug safety in both drug development and clinical application. The clinical manifestations of DICT include cardiomyopathy, arrhythmia, myocardial ischemia, heart failure, and a series of cardiac structural and functional changes. The occurrence of DICT has negative impacts on the life quality of the patients, brings additional social and economic burden. It is important to identify the potential factors and explore the mechanisms of DICT. Traditional cardiovascular risk factors can only partially explain the risk of DICT. Pharmacogenomic studies show accumulated evidence of genetics in DICT and suggest the potential to guide precision therapy to reduce risk of cardiotoxicity. The comprehensive application of technologies such as third-generation sequencing, human induced pluripotent stem (iPS) cells and genome editing has promoted the in-depth understanding of the functional role of susceptible genes in DICT. This paper reviewed drugs that cause DICT, the clinical manifestations and laboratory tests, as well as the related content of genetic variations associated with the risk of DICT, and further discussed the implication of new technologies in pharmacogenomics of DICT.

Pharmacogenomics for Prediction of Cardiovascular Toxicity: Landscape of Emerging Data in Breast Cancer Therapies

Pharmacogenomics is an emerging field in oncology, one that could provide valuable input on identifying patients with inherent risk of toxicity, thus allowing for treatment tailoring and personalization on the basis of the clinical and genetic characteristics of a patient. Cardiotoxicity is a well-known side effect of anthracyclines and anti-HER2 agents, although at a much lower incidence for the latter. Data on single-nucleotide polymorphisms related to cardiotoxicity are emerging but are still scarce, mostly being of retrospective character and heterogeneous. A literature review was performed, aiming to describe current knowledge in pharmacogenomics and prediction of cardiotoxicity related to breast cancer systemic therapies and radiotherapies. Most available data regard genes encoding various enzymes related to anthracycline metabolism and HER2 polymorphisms. The available data are presented, together with the challenges and open questions in the field.

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

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 results

The 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.

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

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.

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

Simple Summary

A deep learning model based on multi-omics data to classify Nottingham prognostic Index score levels. The model represents each omic dataset using 2-dimensional map before integrating all omics maps into the prediction model. The literature confirms the relationship between the extracted omics features with the progression and survival of breast cancer.

Abstract

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.

Effects of Oleuropein on Epirubicin and Cyclophosphamide Combination Treatment in Rats

Objectives

Oleuropein is the main bioactive polyphenolic compound in olive leaves, olive, and olive oil. Its anticancer, antioxidant, and antiinflammatory effects have been proven through several in vitro and in vivo studies. This study aimed to explore the effects of oleuropein on cyclophosphamideand epirubicin-induced toxicity in female rats.

Materials and Methods

Seven groups containing eight rats in each group were formed. Four cycles of 16 mg/kg/week of cyclophosphamide and 2.5 mg/kg/week of epirubicin were administered to the rats through intraperitoneal injection. Oleuropein (150 mg/kg/week) was simultaneously applied via oral gavage. The effects of oleuropein were examined with hemogram tests in whole blood samples and biochemical analysis in serum samples. Interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the serum samples were analyzed through enzyme-linked immunosorbent assay. Subsequently, a comet assay was performed using lymphocyte DNA. The levels of oxidant [i.e., malondialdehyde (MDA)] and antioxidants [i.e., catalase (CAT), glutathione (GSH), and superoxide dismutase (SOD)] were measured in the heart, kidney, and liver tissues.

Results

Oleuropein could reduce DNA damage and serum TNF-α and IL-6 levels. It also ameliorated some hemogram and biochemical parameters that deteriorated due to antineoplastic drugs. It increased the amounts of antioxidants (GSH, SOD, and CAT) and reduced the level of MDA in the heart, kidney, and liver tissues.

Conclusion

Oleuropein might be a beneficial agent against toxicity caused by the combination treatment of cyclophosphamide and epirubicin. Further studies should be performed to demonstrate the protective effects of oleuropein against antineoplastic induced-toxicity precisely.

Single nucleotide polymorphisms as the efficient prognostic markers in breast cancer

BACKGROUND

Breast cancer (BC) is known as the most common malignancy in women. Environmental and genetic factors are associated with BC progression. Genetic polymorphisms have been reported as important risk factors of BC prognosis and drug response. Main body: Therefore, in the present review, we have summarized all single nucleotide polymorphisms (SNPs) which have been significantly associated with drug response in BC patients around the world. We have also categorized the reported SNPs based on their related genes functions to clarify the molecular biology of drug responses in BC.

CONCLUSION

The majority of SNPs were reported in detoxifying enzymes, which introduced such genes as the main genetic risk factors during BC drug responses. This review paves the way for introducing a prognostic panel of SNPs for the BC patients in the world.

Influences of UGT2B7 rs7439366 and rs12233719 Polymorphisms on Fentanyl Sensitivity in Chinese Gynecologic Patients

Background

This study discussed potential influences of UDP glucuronosyltransferase family 2 member B7 (UGT2B7) rs7439366 and rs12233719 polymorphisms on fentanyl sensitivity among Chinese gynecologic patients.

Material/Methods

UGT2B7 polymorphisms were genotyped by polymerase chain reaction (PCR) and direct sequencing. Before surgery, baseline latency to pain perception (PPLpre) and pain perception latency of the dominant hand (PPLpost) at 3 minutes after injecting fentanyl were measured by cold pressor-induced pain test. Perioperative fentanyl adoption referred to the total of fentanyl administration during and after operation. Intensity of spontaneous pain was appraised adopting 100-mm visual analog scale (VAS). Factorial analysis was performed by Mann-Whitney U test and Kruskal-Wallis H test.

Results

Significant differences of PPLpost (CC/CT/TT, P=0.038) and preoperative analgesic effect (CC/CT/TT, P=0.028) were discovered between the rs7439366 genotypes. PPLpost was significantly different between the CT and TT groups (P=0.009) and the CC+CT and TT groups (P=0.026). Preoperative analgesic effect was significantly different between the CT and TT groups (P=0.007) and the CC+CT and TT groups (P=0.009). All of the clinical features studied had no close association with rs12233719 SNP.

Conclusions

Gynecologic patients with rs7439366 TT genotype had significantly lower fentanyl sensitivity than the other 2 genotype carriers.

Toxicity and Pharmacogenomic Biomarkers in Breast Cancer Chemotherapy

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.

Correlation of HER2 codon 655 polymorphism with cardiotoxicity risk in Chinese HER2-positive breast cancer patients undergoing epirubicin/cyclophosphamide followed by docetaxel plus trastuzumab adjuvant chemotherapy

This study aimed to determine the correlation of human epidermal growth factor receptor 2 (HER2) codon 655 A>G polymorphism with cardiotoxicity risk in HER2-positive breast cancer patients undergoing epirubicin/cyclophosphamide followed by docetaxel plus trastuzumab (EC-D-T) adjuvant chemotherapy. Peripheral blood from 91 HER2-positive breast cancer patients was collected for HER2 codon 655 A>G genotyping before initiation of EC-D-T adjuvant chemotherapy (M0). Left ventricular ejection fraction (LVEF), cardiac troponin I (cTnI), and N terminal pro B type natriuretic peptide (NT-proBNP) levels were measured at M0, M3, M6, M9, M12 and M15. Cardiotoxicity was assessed at each time point after initiation of adjuvant chemotherapy. There were 77 cumulative cardiotoxicity events, and totally 26 patients had cardiotoxicity with incidence of 28.6% during the study. LVEF was decreased, cTnI was increased but NT-proBNP was similar in cardiotoxicity patients compared to non-cardiotoxicity patients at each time point. Additionally, the prevalences of HER2 codon 655 AA, AG, GG genotypes were 70.3%, 26.4% and 3.3% respectively. LVEF was lower at each time point after initiation of adjuvant chemotherapy and incidence of cardiotoxicity was increased in patients with HER2 codon 655 AG/GG genotypes compared to those with HER2 codon 655 AA genotype. Logistic regression analysis further revealed that HER2 codon 655 A>G, smoking and baseline cTnI were independent predictive factors for increased cardiotoxicity risk. In conclusion, HER2 codon 655 A>G was an independent predictive factor for increased cardiotoxicity risk in HER2-positive breast cancer patients undergoing EC-D-T adjuvant chemotherapy.