Association of Genome-Wide Association Study (GWAS) Identified SNPs and Risk of Breast Cancer in an Indian Population

Association of ESR1, HER1, and HER2 Polymorphisms with Breast Cancer Risk in the KP Population, A Case-Control Study

Breast cancer is a complex disease characterized by the uncontrolled growth of breast cells. Genetic variants in ESR1, HER1, and HER2 have been associated with breast cancer risk across different populations, with varying results. This study aimed to validate the association of ESR1 (rs2234693 and rs2046210), HER1 (rs11543848), and HER2 (rs1136201) variants with breast cancer risk in the KP population of Pakistan using a larger dataset. The study cohort included 528 patients with BC and 530 healthy controls. Blood samples were collected, and DNA was extracted using a non-enzymatic method. Genotyping was performed using the T-ARMS-PCR protocol. Our results for ESR1 (rs2234693) indicated a non-significant association between the mutant C allele (P = 0.102), TC (P = 0.1002), and CC genotype (P = 0.398) and breast cancer risk. In contrast, ESR1 and rs2046210 showed a significant association with the mutant A allele (P = 0.001), GA (P = 0.001), and AA genotype (P = 0.001), indicating an increased risk. HER1 and rs11543848 showed an increased risk of breast cancer, with the mutant allele A (P = 0.001), GA (P = 0.001), and AA genotype (P = 0.001). Similarly, alleles G (P = 0.004), AG (P = 0.001), and GG genotype (P = 0.003) of HER2 (rs1136201) were associated with higher breast cancer risk. Furthermore, ESR1 (rs2234693) was significantly associated with PR status, while both HER1 (rs11543848) and HER2 (rs1136201) were considerably associated with HER2 receptor status. In conclusion, this study explored the association of the selected variants of ESR1, HER1, and HER2 with breast cancer risk in the KP population using a larger data set, providing valuable insights into the genetic factors contributing to breast cancer risk and corresponding value added to breast cancer management.

Genetic diversity of 'Very Important Pharmacogenes' in two South-Asian populations

OBJECTIVES

Reliable identification of population-specific variants is important for building the single nucleotide polymorphism (SNP) profile. In this study, genomic variation using allele frequency differences of pharmacologically important genes for Gujarati Indians in Houston (GIH) and Indian Telugu in the U.K. (ITU) from the 1000 Genomes Project vis-à-vis global population data was studied to understand its role in drug response.

METHODS

Joint genotyping approach was used to derive variants of GIH and ITU independently. SNPs of both these populations with significant allele frequency variation (minor allele frequency ≥ 0.05) with super-populations from the 1000 Genomes Project and gnomAD based on Chi-square distribution with p-value of ≤ 0.05 and Bonferroni's multiple adjustment tests were identified. Population stratification and fixation index analysis was carried out to understand genetic differentiation. Functional annotation of variants was carried out using SnpEff, VEP and CADD score.

RESULTS

Population stratification of VIP genes revealed four clusters viz., single cluster of GIH and ITU, one cluster each of East Asian, European, African populations and Admixed American was found to be admixed. A total of 13 SNPs belonging to ten pharmacogenes were identified to have significant allele frequency variation in both GIH and ITU populations as compared to one or more super-populations. These SNPs belong to VKORC1 (rs17708472, rs2359612, rs8050894) involved in Vitamin K cycle, cytochrome P450 isoforms CYP2C9 (rs1057910), CYP2B6 (rs3211371), CYP2A2 (rs4646425) and CYP2A4 (rs4646440); ATP-binding cassette (ABC) transporter ABCB1 (rs12720067), DPYD1 (rs12119882, rs56160474) involved in pyrimidine metabolism, methyltransferase COMT (rs9332377) and transcriptional factor NR1I2 (rs6785049). SNPs rs1544410 (VDR), rs2725264 (ABCG2), rs5215 and rs5219 (KCNJ11) share high fixation index (≥ 0.5) with either EAS/AFR populations. Missense variants rs1057910 (CYP2C9), rs1801028 (DRD2) and rs1138272 (GSTP1), rs116855232 (NUDT15); intronic variants rs1131341 (NQO1) and rs115349832 (DPYD) are identified to be 'deleterious'.

CONCLUSIONS

Analysis of SNPs pertaining to pharmacogenes in GIH and ITU populations using population structure, fixation index and allele frequency variation provides a premise for understanding the role of genetic diversity in drug response in Asian Indians.

Symposium report: breast cancer in India-trends, environmental exposures and clinical implications

PURPOSE

Incidence of breast cancer (BC), particularly in young women, are rising in India. Without population-based mammography screening, rising rates cannot be attributed to screening. Investigations are needed to understand the potential drivers of this trend.

METHODS

An international team of experts convened to discuss the trends, environmental exposures, and clinical implications associated with BC in India and outlined recommendations for its management.

RESULTS

Panels were structured across three major BC themes (n = 10 presentations). The symposium concluded with a semi-structured Think Tank designed to elicit short-term and long-term goals that could address the challenges of BC in India.

CONCLUSION

There was consensus that the prevalence of late-stage BC and the high BC mortality rates are associated with the practice of detection, which is primarily through clinical and self-breast exams, as opposed to mammography. Triple-Negative BC (TNBC) was extensively discussed, including TNBC etiology and potential risk factors, the limited treatment options, and if reported TNBC rates are supported by rigorous scientific evidence. The Think Tank session yielded long-term and short-term goals to further BC reduction in India and included more regional etiological studies on environmental exposures using existing India-based cohorts and case-control studies, standardization for molecular subtyping of BC cases, and improving the public's awareness of breast health.

The Implementation of the Three Rs in Regulatory Toxicity and Biosafety Assessment: The Indian Perspective

Animal models have long served as a basis for scientific experimentation, biomedical research, drug development and testing, disease modelling and toxicity studies, as they are widely thought to provide meaningful, human-relevant predictions. However, many of these systems are resource intensive and time-consuming, have low predictive value and are associated with great social and ethical dilemmas. Often drugs appear to be effective and safe in these classical animal models, but later prove to be ineffective and/or unsafe in clinical trials. These issues have paved the way for a paradigm shift from the use of in vivo approaches, toward the 'science of alternatives'. This has fuelled several research and regulatory initiatives, including the ban on the testing of cosmetics on animals. The new paradigm has been shifted toward increasing the relevance of the models for human predictivity and translational efficacy, and this has resulted in the recent development of many new methodologies, from 3-D bio-organoids to bioengineered 'human-on-a-chip' models. These improvements have the potential to significantly advance medical research globally. This paper offers a stance on the existing strategies and practices that utilise alternatives to animals, and outlines progress on the incorporation of these models into basic and applied research and education, specifically in India. It also seeks to provide a strategic roadmap to streamline the future directions for the country's policy changes and investments. This strategic roadmap could be a useful resource to guide research institutions, industries, regulatory agencies, contract research organisations and other stakeholders in transitioning toward modern approaches to safety and risk assessment that could replace or reduce the use of animals without compromising the safety of humans or the environment.

Overexpression of RAD50 is the Marker of Poor Prognosis and Drug Resistance in Breast Cancer Patients

BACKGROUND

The prevalence of breast cancer is increasing at an alarming rate and thus demands exploration of the most relevant diagnostic biomarkers. RAD50 is a cancer susceptibility gene that encodes a DNA damage repairing protein. Its role in breast cancer as clinico-pathological specific biomarker has yet to be explored.

OBJECTIVE

This study was aimed to investigate the RAD50 expression and its promoter's methylation level variations in breast invasive carcinoma patients having different clinico-pathological features. This study further explored the mutational spectrum of RAD50 and the correlation of its expression with the survival of patients and the effectiveness of drugs used for treatment.

METHODS

Enrichment analysis of RAD50 was accomplished using the platform of GeneCards. The information regarding RAD50 expression, its promoter methylation and impact on survival of patient was retrieved from TCGA and CPTAC databases. However, the effect of RAD50 expression on tumor's response to various drugs was deduced through the analysis of CCLE and genomic of GDSC dataset.

RESULTS

The promoter hyper-methylation and elevated expression of RAD50 was documented in various subgroups of breast invasive carcinoma. The subjects having low/medium expression levels were observed to survive longer than patients exhibiting high expression of RAD50 except for post-menopausal subjects. The frequency of missense mutations was higher in RAD50 than truncating mutations. Most of the drugs were found to have a positive correlation with RAD50 expression.

CONCLUSION

The status of RAD50 promoter's methylation inversely correlates with the expression level of RAD50. While RAD50 is overexpressed in breast cancer patients and thus makes tumor resistant against many anti-cancer drugs.

A Review on the Challenges in Indian Genomics Research for Variant Identification and Interpretation

Today, genomic data holds great potential to improve healthcare strategies across various dimensions – be it disease prevention, enhanced diagnosis, or optimized treatment. The biggest hurdle faced by the medical and research community in India is the lack of genotype-phenotype correlations for Indians at a population-wide and an individual level. This leads to inefficient translation of genomic information during clinical decision making. Population-wide sequencing projects for Indian genomes help overcome hurdles and enable us to unearth and validate the genetic markers for different health conditions. Machine learning algorithms are essential to analyze huge amounts of genotype data in synergy with gene expression, demographic, clinical, and pathological data. Predictive models developed through these algorithms help in classifying the individuals into different risk groups, so that preventive measures and personalized therapies can be designed. They also help in identifying the impact of each genetic marker with the associated condition, from a clinical perspective. In India, genome sequencing technologies have now become more accessible to the general population. However, information on variants associated with several major diseases is not available in publicly-accessible databases. Creating a centralized database of variants facilitates early detection and mitigation of health risks in individuals. In this article, we discuss the challenges faced by genetic researchers and genomic testing facilities in India, in terms of dearth of public databases, people with knowledge on machine learning algorithms, computational resources and awareness in the medical community in interpreting genetic variants. Potential solutions to enhance genomic research in India, are also discussed.

Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

A meta-analysis and in silico analysis of polymorphic variants conferring breast cancer risk in the Indian subcontinent

Background: Genetic association studies on breast cancer on the Indian subcontinent have yielded conflicting results, and the precise effect of these variants on breast cancer pathogenesis is not known. Methods: Genomic variants, as obtained from selected studies from the Indian subcontinent, were subjected to random-effects and fixed-effect meta-analysis. Functional annotation of the relevant variants was done through a tried and tested in silico pipeline. Results: We found rs4646903/CYP1A1, rs1799814/CYP1A1, rs61886492/GCPII, del2/GSTM1, rs4680/COMT and rs1801394/MTRR to be associated with breast cancer. The del2/GSTM1 holds the association in premenopausal women. Conclusions: This is the first study of its kind from the Indian subcontinent analysing the extent of association of variants across populations followed by their functional annotation in the disease pathway.

Harnessing genomics to improve outcomes for women with cancer in India: key priorities for research

Cumulatively, breast, cervical, ovarian, and uterine cancer account for more than 70% of cancers in women in India. Distinct differences in the clinical presentation of women with cancer suggest underlying differences in cancer biology and genetics. The peak age of onset of breast and ovarian cancer appears to be a decade earlier in India (age 45-50 years) than in high-income countries (age >60 years). Understanding these differences through research to develop diagnosis, screening, prevention, and treatment frameworks that ar e specific to the Indian population are critical and essential to improving women's health in India. Since the sequencing of the human genome in 2001, applications of advanced technologies, such as massively parallel sequencing, have transformed the understanding of the genetic and environmental drivers of cancer. How can advanced technologies be harnessed to provide health-care solutions at a scale and to a budget suitable for a country of 1·2 billion people? What research programmes are necessary to answer questions specific to India, and to build capacity for innovative solutions using these technologies? In order to answer these questions, we convened a workshop with key stakeholders to address these issues. In this Series paper, we highlight challenges in tackling the growing cancer burden in India, discuss ongoing genomics research and developments in infrastructure, and suggest key priorities for future research in cancer in India.

Fibroblast Growth Factor Receptor 2 Signaling in Breast Cancer

Fibroblast growth factor receptor 2 (FGFR2) is a membrane-spanning tyrosine kinase that mediates signaling for FGFs. Recent studies detected various point mutations of FGFR2 in multiple types of cancers, including breast cancer, lung cancer, gastric cancer, uterine cancer and ovarian cancer, yet the casual relationship between these mutations and tumorigenesis is unclear. Here we will discuss possible interactions between FGFR2 signaling and several major pathways through which the aberrantly activated FGFR2 signaling may result in breast cancer development. We will also discuss some recent developments in the discovery and application of therapies and strategies for breast cancers by inhibiting FGFR2 activities.