My areas of expertise include data mining, statistical modeling, and artificial intelligence with strong background in personalize medicine and cancer genomics especially in biomarker discovery and toxicity testing that I gained at various institutes in India, Europe, USA and Canada over past 16 years. My experience in the life science and healthcare fields has taught me different aspects to combined large multi-omicsdatasets and develop analytics methods, for instance, genetic profiles of large populations of cancer patients, combined with epigenetics and health records, lifestyle information and development of predictive models for patient response to a certain treatment. Such studies provide important clues about the molecular events at the genome level as well as the level of molecular networks, uncovering new approaches to the search for targeted drugs against a host of diseases.
My current research is focused on developing a better understanding of cancer biology by applying multiple layers omics approach to improved outcomes. Following are the main areas of my research:
Multi-omics biomarkers to improve prediction of response to treatment in cancer patients
Breast cancer is a complex disease whose classification has been significantly improved in recent years through the development of biomarkers. Currently, there are four clinically distinct breast cancer subtypes. These subtypes determine molecular classification, along with clinical factors such as age, stage at diagnosis and comorbidity, in assessing treatment options. However, significant disparity in clinical outcome still remains within each of these disease subtypes, calling for extensive and ongoing research in breast cancer biomarkers. This is particularly the case in the United States with regard to the Triple Negative Breast Cancer subtype that occurs with nearly two-fold higher frequency in women of African ancestry. A high immune signal has been linked with improved patient outcome in a variety of cancers, including subtypes of breast cancer. CD4+ T cells, specifically, are central components of the immune system. They perform critical roles in recruiting, activating, and regulating many facets of the adaptive immune response, with their helper functions. CD4+ T cells also influence innate immunity by helping to shape the character and magnitude of the inflammatory response1.
In one of my most influential contributions, I have developed a state-of-the-art model that identifies novel biomarkers to predict the response of drugs after short-term treatment for breast cancer, which, aimed to investigate the association between chemotherapy response and gene expression modules and uncover key biological processes and pathways in breast cancer subtypes2. I have identified that different biomarkers and pathways are associated with treatment outcomes in terms of pathological complete response (pCR) in different BC subtypes. This finding is incredibly useful for predicting the response of target drugs at early stages of treatment. Also, in a paired (i.e. at the beginning and after 10–14 days of neoadjuvant letrozole treatment) gene expression analysis of breast cancer patients shows that that the early assessment of proliferation after short-term endocrine therapy may be useful to evaluate endocrine responsiveness, particularly in genomic high-grade ER-positive breast cancer3.
I have also addressed young age adds extra biological complexity, which is independent of differences in breast cancer subtypes. This study provides significant scientific rationale to examine these findings in the clinical setting. Specifically, examining the inhibition of mammary stem cell function or RANKL-signaling pathways with specific drugs such as a RANKL inhibitor and their effects on mammary epithelial populations and tumor growth are beneficial for young women with newly diagnosed tumors. This is particularly clinically relevant for the young, given the risk for long-term side-effects of adjuvant systemic chemotherapy. In addition, I found Proliferation-related prognostic gene signatures that aid treatment in decision-making for young women with breast cancer4.
I am providing support to analyze high throughput data such as, ChlPSeq, RNASeq, ExomeSeq, microarray, peak calling etc. My current project has an integrated focus on to understand fundamental mechanisms of chromatin-based transcriptional control and epigenetic regulation with an emphasis on the role of metabolic imbalance in regulating these pathways in breast cancer (Proc Natl Acad Sci US A. 2009 Nov 17;106(46):19286-91; Nat Struct Mal Biol. 2010 Dec;17(12):1406-13; Nat Commun. 2012 Jan 17;3:633; Nat Commun. 2013;4:1449). Major goals include understanding the role of metabolism and transcriptional cross-talk between epigenetic co-regulators and hormone receptor-mediated signaling pathways in both enhancer function and promoter-targeted mechanisms of gene control. An essential component of this work is involve developing omicperspectives that will integrate next-generation sequencing with genomics, transcriptomics, epigenomics, proteomics and metabolomics using model systems and patient-derived samples. Furthermore, I was involved in a clinical trial that involved a randomized trial between letrozole and a placebo and letrozole and everolimus. In this trial, I have examined PIK3CA genotype and a PIK3CA mutation-related gene signature. His results indicated that the PIK3CA-GS identified ER-positive BCs that benefit for the addition of everolimus to letrozole5.
Following are some article which appeared in some of the most competitive and prestigious journals in the field:
- Peer-reviewed article co-first-authored by Dr. Singhal, "Racial Differences in the Association between Luminal Master Regulator Expression and Breast Cancer Survival". Clinical Cancer Research, 2020
- Peer-reviewed article co-authored by Dr. Singhal, “CD4+ follicular helper T cell infiltration predicts breast cancer survival,” The Journal of Clinical Investigation, 2013 & a testimonial letter confirming Dr. Singhal’s substantial contribution
- Peer-reviewed article co-first-authored by Dr. Singhal, “Gene modules and response to neoadjuvant chemotherapy in breast cancer subtypes: a pooled analysis,” Journal of Clinical Oncology, 2012J Clin Oncol 30:1996-2004, 2012
- Peer-reviewed article co-first-authored by Dr. Singhal, “Low residual proliferation after short-term letrozole therapy is an early predictive marker of response in high proliferative ER-positive breast cancer,” Endocrine-Related Cancer, 2011Endocr Relat Cancer 18:721-30, 2011
- Peer-reviewed article co-authored by Dr. Singhal, “Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling,” Clinical Cancer Research, 2012
- Peer-reviewed article co-authored by Dr. Singhal, “PIK3CA Genotype and a PIK3CA Mutation-Related Gene Signature and Response to Everolimus and Letrozole in Estrogen Receptor Positive Breast Cancer,” PLoS One, 2013 PLoS One 8:e53292, 2013
Epigenetic profiling reveals a predominant immune component in breast cancers
In another contribution, I have demonstrated that understanding genetics and epigenetics is essential to improving the diagnosis and treatment. I found that DNA methylation profiling can reflect the cell type composition of the tumor microenvironment, and in particular a T lymphocyte infiltration of the tumors. Furthermore, I identified a set of immune genes having a high prognostic value in specific tumor categories. These immune components that provides a new perspective regarding the microenvironment in breast cancer, which holds implications for better management of breast cancer patients. In a collaborative study with diffrent labs, we have demonstrated that understanding of genetics with epigenetics is essential to improve diagnosis and optimizing treatment. We showed that DNA methylation profiling can reflect the cell type composition of the tumor microenvironment, and in particular a T lymphocyte infiltration of the tumors. We identified a set of immune genes having high prognostic value in specific tumor categories. The immune component uncovered here by DNA methylation profiles provides a new perspective for the importance of the microenvironment in breast cancer, holding implications for better management of breast cancer patients1,2. This research is extremely useful and informative in minimizing the side effects of systematic therapy, which will overcome the existing limitations of toxic manifestation, often encountered in conventional therapeutic interventions, such as chemotherapy, endocrine or hormonal therapy.
- Peer-reviewed article co-authored by Dr. Singhal Epigenetic re-wiring of breast cancer by pharmacological targeting of C-terminal binding protein. Cell death & disease 10 (10), 1-15
- Peer-reviewed article co-authored by Dr. Singhal, “DNA methylation profiling reveals a predominant immune component in breast cancers,” EMBO Mol Med3:726-41, 2011
- Peer-reviewed article first-authored by Dr. Singhal, “Towards understanding the breast cancer epigenome: a comparison of genome-wide DNA methylation and gene expression data,” Oncotarget,Oncotarget 7:3002-17, 2016
Predict of toxicity after radiation therapy in prostate cancer patients
Radiotherapy is a mainstay of cancer treatment, used in either a curative or palliative manner to treat approximately 50% of patients with cancer. But damage to surrounding normal tissues can produce reactions ranging from bothersome symptoms that negatively affect quality of life to severe life-threatening complications. Improved ways of predicting, before treatment, the risk for development of normal tissue toxicity may allow for more personalized treatment and reduce the incidence and severity of late effects1. Urethral strictures (US) is a rare complication of prostate cancer patient treated with brachytherapy (BXT). I have developed a risk prediction model to predict the radiation toxicity US after BXT using clinical, dose- parameters2. This modeling approach, which is novel in BXT, helped to identify a combination of parameters with some predictive ability of radiation toxicity. Another major toxicity after radiation therapy is rectal bleeding. I have developed a validated model to predict the risk of radiation proctitis using clinical, radiation dose symmetric and high-throughput genomic (GWAS) data. A gwas pipeline has been created to pool data from different studies developed by our collaborators from the United States, United Kingdom and Spain and then divided as training set to develop a model and test dataset to evaluated its predication ability. All patients were treated with External beam radiotherapy (EBRT) & brachytherapy (Manuscript under review). In a large collaborative study, we identified a refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling3,4.
- Peer-reviewed article co-authored by Dr. Singhal, “The Prediction of Radiotherapy Toxicity Using Single Nucleotide Polymorphism-Based Models: A Step Toward Prevention,” Seminars in Radiation Oncology, 2015
- Peer-reviewed article first-authored by Dr. Singhal, “Clinical factors and dosimetry associated with development of prostate brachytherapy-related urethral strictures: A matched case-control study,” Brachytherapy, 2017
- Peer-reviewed article co-authored by Dr. Singhal, “Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci,” Nature Genetics, 2018
- Peer-reviewed article co-authored by Dr. Singhal, “Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants,” Nature Communications, 2018