Data driven translational research
We believe in patient data-driven cancer research. As part of this, our lab is involved in large-scale patient cohort multi-omics profiling including collaborations with clinicians and clinical trial governing bodies. This enables large-scale patient tumor data generation to prioritize therapeutics-centric patient stratification leading to precision and translational research.
DNA damage repair and replication defects in cancer
Role of single-strand DNA damage repair defects as a class of endocrine treatment resistance drivers has been established in estrogen-receptor positive breast cancer (Haricharan et al., Cancer Discovery 2017; Anurag et al., CCR 2018). Moving forward, we are interested in exploring other DNA repair defects and associated disease phenotype across multiple cancer types and subtypes including different breast cancer subtypes.
We have recently unraveled the importance of DNA replication genes in chemotherapy resistance. Currently, my lab is focused on studying LIG1 and POLD1 as a biomarker of chemotherapy resistance. We are invested in studying the molecular makeup of a tumor cell with LIG1 loss and associated therapeutic vulnerabilities.
Immune tolerance and therapeutic response
Exploring the cause-and-effect relationship further, we are trying to understand the contribution of immune-checkpoint and other immune-tolerance factors, including IDO1 and LAG1, in therapeutic resistant and advancement of estrogen-receptor positive disease (Anurag et al, JNCI 2020). This warrants for integration of the patient's genome, transcriptome and proteome with their clinical phenotype.
Rare cancers
Small population or rare forms of cancers remain under-explored and less understood within the realms of cancer research. Despite multiple efforts, knowledge of rare cancers is often very superficial and is derived from individual case reports or a case series. Conclusions drawn from such selected studies may be biased. Such studies do not necessarily reflect the characteristics of the underlying population and its uniqueness in comparison to related but high-incidence cancer forms. This is a major challenge when identifying features unique to a given rare form of cancer. Singular attention is required for development of computation and bio-statistical pipelines, for translational research in rare cancers. My lab is currently studying specific rare forms of cancer at molecular levels including Male breast cancer and carcinoma in situ.
