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Collaboration uses molecular analysis to study breast cancer in India

Kidwai Memorial Institute of Oncology, the Indian Institute of Science, and Strand Life Sciences are using integrated molecular omics analysis to study breast cancer in the Indian population. This research programme is aimed at identification and validation of molecular signatures and biomarkers for Indian breast cancer patients.

The integrated molecular omics study addresses a significant medical need in India, where breast cancer is the second leading cause of death among women. Over the past decade, the incidence of breast cancer is on the rise and has over taken cervical cancer incidence in all urban centres’ including Bangalore. An alarming indication of the trend suggests that one in every 22 women in India is likely to suffer from breast cancer in the coming year. Recent data also suggests that a startling number of pre-menopausal, young Indian women are falling victim to the deadly disease. This data is in stark contrast to that of Caucasian women who suffer from breast cancer mostly, post-menopause.

The study involves more than 300 consented adult Indian women who suffer from breast cancer. The objective of this study is to largely generate prognostic molecular signatures responsible for response to various therapies and treatments, metastasis, relapse and disease-free survival of affected Indian women.

Strand plans to compare the publicly available data from Caucasian and African cohorts with data obtained at the end of this study. Further it will utilise these results to develop and identify biological markers that can characterise subtypes and develop suitable diagnostic kits towards therapeutic prognosis predictions.

The project team in Bangalore will use breast tumor samples provided by the Kidwai Memorial Institute of Oncology and profiled by Professor P Kondaiah's lab at IISc, Bangalore. Strand's in silico data analysis tools and bioinformatics expertise will be leveraged by the team to find and validate potential signatures that could lead to biomarkers.


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