India’s First Comprehensive Cancer Genomics Repository Launched by ICGA Foundation

September 22, 2024
Posted by: OptimizeIAS Team
Category: DPN Topics

India’s First Comprehensive Cancer Genomics Repository Launched by ICGA Foundation

Sub: Sci

Sec: Biotech

Why in News

The Indian Cancer Genome Atlas (ICGA) Foundation has launched India’s first comprehensive cancer genomics repository. This platform aims to improve the understanding of genetic variations in cancer specific to the Indian population, marking a significant advancement in cancer research and treatment. The repository provides crucial data that will help researchers, clinicians, and innovators in the field of oncology.

ICGA (Indian Cancer Genome Atlas) Repository: The ICGA aims to create a comprehensive genomic, transcriptomic, and proteomic dataset for Indian cancer patients, addressing the need for region-specific data for personalized treatments.

Data: The ICGA cancer multi-omics portal is the first in India to offer data that includes DNA, RNA, and protein profiles of breast cancer patients, integrated with clinical outcomes. Currently, the platform consists of data from 50 breast cancer patients, with plans to expand to over 500 patients in the coming year.

Significance: Historically, cancer treatments in India relied on Western datasets, which are not always applicable to the Indian population. ICGA seeks to fill this gap with India-specific data to enhance diagnosis, treatment, and outcomes.

Global Collaboration: The ICGA platform invites global researchers to access and contribute to its data, fostering collaborative cancer research on an international scale.

TCGA (The Cancer Genome Atlas):Launched in 2006, TCGA is a landmark project that molecularly characterized over 20,000 primary cancer samples across 33 cancer types. It provides large-scale data for understanding cancer at the genomic level.

Contributions: TCGA has generated more than 2.5 petabytes of data, offering insights into the genetic mutations driving cancer and improving diagnostic, therapeutic, and preventive measures.

Impact: The data has been used to develop more precise treatments by identifying specific mutations and pathways that contribute to cancer progression.

What is Atlas?

In the context of cancer genomics, an “Atlas” refers to a comprehensive collection of data that maps out genomic alterations, mutations, and molecular processes that underlie different cancer types.

Examples: Both ICGA and TCGA serve as “atlases” by compiling vast datasets that help researchers explore cross-cancer patterns, cellular origins, and oncogenic processes, which in turn supports the development of personalized therapies.

What is multi-omics?

Multi-Omics is an integrated approach in biological sciences that combines data from various “omics” fields, such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics. This allows researchers to explore multiple levels of biological processes simultaneously.

Multi-Omics and its key aspects:

Omics Group	Description	Key Features
Genomics	Study of an organism’s DNA, focusing on structure, function, and evolution.	DNA sequencing, gene mapping, mutations, and editing. Helps in understanding genetic contributions to diseases like cancer.
Transcriptomics	Study of RNA transcripts produced by the genome, understanding gene expression.	Helps reveal gene activity during different conditions or disease stages by evaluating mRNA levels.
Proteomics	Study of protein expression, structure, and function.	Understanding cellular processes, protein interactions, and responses to therapy. Important in drug discovery and treatment strategies.
Epigenomics	Study of heritable changes in gene expression without altering the DNA sequence.	Focuses on methylation, histone modifications, and environmental influences on genes, crucial in cancer and developmental biology.
Metabolomics	Study of metabolites (small molecules) involved in metabolic processes.	Tracks carbohydrates, lipids, peptides, and other metabolites. Critical in studying cellular responses and disease biomarkers.
Microbiomics	Study of microbial communities, especially in humans (gut, skin, mucosal surfaces).	Microbial balance affects health, digestion, immunity, and diseases like obesity. Sequencing of 16S rRNA or metagenomics quantifies and identifies microbial communities.
Omics Datasets	Collections characterizing specific biological features, like genes, proteins, or metabolites.	Omics datasets help in linking these features to biological processes, disease pathways, and therapeutic targets.
Multi-Omics Strategy	Integration of multiple omics data (e.g., genomics + proteomics) to study complex biological processes.	Provides a holistic view, identifying biomarkers, pathways, and mechanisms of action for disease diagnostics and therapy development.