Fundamental Research Projects
Breast Cancer Biology
Uncontrolled proliferation, metastasis, and immune evasion are among the few major attributes of cancer. These attributes are uniquely controlled by distinct genes and pathways in each cancer type or subtype. Breast cancer is categorized into luminal, HER2, and TNBC subtypes—we aim to identify those unique driver genes and pathways that fuel cancer cell growth and invasion in each subtype. We integrate transcriptomic and genomic analyses with experimental tools of biochemistry, molecular biology, immunohistochemistry, and immunofluorescence to ask fundamental questions.
We investigate the Kelch, ELMO, immunoglobulin superfamily, GrpE family, and RNA-binding protein families. Their expression and function are evaluated in breast cancer cells using mRNA and protein analysis, overexpression, and knockdown approaches, followed by studies of proliferation, survival, cell-cycle regulation, migration, and invasion. We further investigate the upstream signaling mechanisms that regulate these candidates using growth factor and cytokine stimulation and pathway-specific inhibition. Our studies have established IGF-1-Kelch, EGF-GrpE, TGF-β-ELMO, and IFN-γ-immunoglobulin superfamily signaling axis. Protein interactions and molecular mechanisms are subsequently studied using co-immunoprecipitation, deletion mapping, and site-directed mutagenesis to identify interacting partners, functional domains, and downstream targets. A major focus of our work is understanding how these novel proteins contribute to tumor growth and metastasis.
Brief About the Genes and Pathways We Are Exploring
Kelch-Family Proteins
Function as substrate adaptors for Cullin-based ubiquitin ligases and regulate the stability of tumor-suppressor proteins. We identified IGF-1 as an upstream regulator of kelch expression. This finding prompts us to investigate the IGF-1-Kelch Tumor suppressor axis in TNBC.
ELMO-Family Proteins
Regulators of cell motility and migration; we study how they contribute to cancer cell invasion.
Matrix Remodeling Associated (MXRA) Family
Cell–cell adhesion and extracellular matrix (ECM) remodeling are fundamental processes that maintain tissue architecture and influence tumor progression. The MXRA family comprises proteins that associate with the cellular and extracellular environments, yet their roles in cancer remain poorly understood.
GrpE-Family Proteins
Chaperones that aid in mitochondrial protein folding and transport, thereby maintaining mitochondrial homeostasis. Since mitochondria influence cell survival upon oxidative stress, in cancer cells, moderate levels of this stress support tumor progression. Our preliminary studies show that GrpE- family proteins are upregulated in breast cancer. We are investigating whether GrpE-family proteins help cancer cells adapt to oxidative stress and their contribution to tumor progression.
Immunoglobulin Superfamily & RNA-Binding Proteins
In parallel, we study immunoglobulin superfamily proteins in cell-cycle regulation and proliferation and RNA-binding proteins, including STAR- and KH-domain-containing proteins, in the regulation of MYC stability and signaling.
Based on our research into proteins and the regulatory mechanisms in cancer biology, we are also investigating how alterations in the transcriptome affect the complexity and progression of breast cancer.
Breast cancer is associated with changes in transcriptome complexity; hence, we are studying chimeric transcripts (CTs) using RNA-sequencing data to identify CTs linked to different cancer stages and molecular subtypes. We also aim to understand their potential roles in disease progression, treatment resistance, and tumor-immune regulation, providing insights into their biological significance.
Promising molecular candidates are advanced to mouse models of breast cancer to validate their roles in tumor growth and metastasis in vivo.
Our research identifies novel oncogenes and uncovers their mechanism of action in cancer cell proliferation and metastasis. With a state-of-the-art animal facility in place, we are encouraged to expand our basic cancer research into cancer immunology - to explore how to leverage immune system tools to counter tumor growth and metastasis.
Computational Oncology
Our group and the institute have computer science and data science experts who know which computational methods to use for a biological question and how to feed data so that machine learning can capture more variation and learn more effectively. The strength of our lab is having an exceptional disease biology understanding of how the disease progresses, how the immune system influences the disease outcome, which are very complex phenomena. We collaborate to develop machine learning models and validate them using experimental setups and expertise. In brief, we use biological datasets (RNA-seq, WES, WGS, drug sensitivity, etc.) and a process that involves data science, machine learning, and probabilistic modeling.
- Drug response prediction: We combine large-scale molecular data with clinical information to develop neural network-based models and try to understand why patients respond differently to drugs.
- Metastatic site prediction: We analyze patient methylation datasets to understand the preferential metastasis of breast cancer to distinct organs. This involves using statistical machine learning and Bayesian models.
- Pathogenic mutations in regulatory regions: We study the pathogenic variants in the regulatory regions in the genomic data of Indian TNBC patients. We aim to identify population-specific mutations and the pathways involved in TNBC progression.
Translational Research Projects
ctDNA-Based Liquid Biopsy Assays
We aim to develop a minimally invasive, blood-based assay for breast cancer monitoring and management, using circulating tumor DNA (ctDNA) as a molecular biomarker. The study integrates next-generation sequencing (NGS) and digital PCR (dPCR) platforms to enable highly sensitive and precise detection of tumor-derived genetic alterations.
MMR Deficiency in Endometrial Cancer & Lynch Syndrome Screening
We are developing and validating an integrated molecular workflow for detecting mismatch repair (MMR) deficiency in endometrial cancer using MMR immunohistochemistry, MLH1 promoter methylation analysis, and targeted molecular testing. The workflow aims to identify patients with MMR-deficient tumors who may benefit from targeted therapies and further evaluation for Lynch syndrome. The project seeks to establish a standardized, clinically applicable approach for MMR assessment in the Indian population.
Therapeutics – Development of PI3K-Alpha Mutant- and Isoform-Specific Inhibitor
The therapeutics project began as a fun project with a former postdoctoral fellow who had expertise in chemistry, docking, and MD simulations. Our hypothesis-driven bioinformatics pipeline identified a few potential small-molecule inhibitors of PI3K-alpha, which we biochemically validated for activity and synthesized derivatives with improved activity (to be published soon). With that project, our lab utilizes established expertise in identifying new molecules, an experimental setup to validate their activities, and collaboration (with Prof. Vinit Kumar, GBU, Noida; Dr. Reshma Rani) to synthesize them, with the aim of bringing clinically relevant molecules with minimal toxicity.