Bioinformatics

The use of digital pathology for the histomorphology profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States.

Kaiso (ZBTB33) subcellular partitioning functionally links LC3A/B, the tumor microenvironment, and breast cancer survival

This study identified a list of genes and pathways differently significantly changed after the arsenic exposure in humans and its association with cancer biology. We developed bladder cancer risk predictive models that would be very helpful to forecast the outcomes of arsenic exposed in humans.

https://ascopubs.org/doi/abs/10.1200/JCO.2021.39.15_suppl.e16523

Role of HRTPT in kidney proximal epithelial cell regeneration: Integrative differential expression and pathway analysis using microarray and scRNA-seq

Damage to proximal tubules due to exposure to toxicants can lead to conditions such as acute kidney injury (AKI), chronic kidney disease (CKD), and ultimately end-stage renal failure (ESRF). Studies have shown that kidney proximal epithelial cells can regenerate particularly after acute injury. The goal of this study is to characterize and understand the global gene expression differences, upregulated pathways as well as gene interaction using scRNA-seq in HRTPT cells.

https://pubmed.ncbi.nlm.nih.gov/34626063/

^{Gene expression data distribution}

In this study, we found gp78/AMFR is an independent predictor of breast cancer survival and response to therapy, based on race, thus implicating a role for this protein, and potentially the UPR, as underlying biological differences in tumor properties linked to genetic ancestry.

https://ascopubs.org/doi/abs/10.1200/JCO.2021.39.15_suppl.553

The goal of the study is to characterize the somatic mutation profile of early-onset tumors from Puerto Ricans, a Hispanic subpopulation with a high CRC burden, in order to better understand early-onset CRC biology.

Reference

In this project, we are developing a novel application of persistent homology to characterize the spatial arrangement of immune and epithelial (tumor) cells within the breast cancer immune microenvironment.

https://drops.dagstuhl.de/opus/volltexte/2020/12169/pdf/LIPIcs-SoCG-2020-11.pdf

^{Microscopic image of a stained tissue sample.}

Different subtypes of lung cancer respond differently to treatment. To understand the signaling pathways that dictate the aggressive behavior of lung adenocarcinoma vs. lung squamous cell carcinoma, we performed a survival analysis that demonstrated that the protein Schlafen 12 correlates with better survival in patients with lung adenocarcinoma but not patients with lung squamous cell carcinoma, indicating specificity of the effect of the SLFN12 pathway in lung cancer subtypes.

https://www.mdpi.com/836462

The BARDA Community Challenge is sponsored by Biomedical Advanced Research and Development Authority (BARDA) in partnership with the National Institute of Health’s National Center for Advancing Translational Sciences (NCATS), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) at the National Institutes of Health and Health Resources & Services Administration (HRSA) Maternal & Child Health Bureau.

We are analyzing the Gene expression data from blood to identify potential biomarkers that may be useful for distinguishing between Mild cognitive impairment (MCI) and Alzheimer’s disease dementia compared to normal people. We have developed a large dataset and are working on model development. 

We are developing a Health Intelligence platform that delivers an all-in-one personalized health guide by interpreting human genetic, metabolite, protein and microbial molecular profiles and providing a tailored health action plan. The tool provides predictive and prescriptive health insights and personalized action plans based on human molecular profile. This is a monitoring tool for individuals where suggestions for nutrition, supplements, exercise, medication, stress reduction and rest are itemized that can improve their health over time.

While maps allow us to follow the coronavirus in near real time, federal and local officials who manage COVID-19 response actions are also looking into projections about how the virus might behave in the future.

“Adams and Singhal are cooperating with the epidemiology group within the Department of Health, who have met with Doctor Anthony Fauci, who leads the National Institute of Allergy and Infectious Diseases and serves on the administration’s coronavirus taskforce, and Doctor Deborah Birx, response coordinator for the White House. At that meeting, Dr. Birx outlined coronavirus predictions for North Dakota that aligned well with Adams’ model”

https://blogs.und.edu/und-today/2020/04/und-researchers-track-map-model-the-pandemic/

^{The analysis also charts a comparison between North Dakota and the rest of the USA population.}

We determine the weather-related variables that are influencing mosquito populations. Using the information from the glms, we identify for each species, at what time points those significant variables are playing a role.

Lung cancer is the most common cause of cancer-related deaths worldwide. Early diagnosis is crucial to increase the curability chance of the patients. Low dose CT screening can reduce lung cancer mortality, but it is associated with several limitations. Metabolomics is a promising technique for cancer diagnosis due to its ability to provide chemical phenotyping data.

https://www.mdpi.com/2072-6694/11/8

Article published on the cover page of the Journal

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.

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 from the addition of everolimus to letrozole⁵.

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 aims to investigate the association between chemotherapy response and gene expression modules and uncover key biological processes and pathways in breast cancer subtypes².

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.

Following are some article which appeared in some of the most competitive and prestigious journals in the field

1. Peer-reviewed article first-authored by Dr. Singhal, Kaiso (ZBTB33) subcellular partitioning functionally links LC3A/B, the tumor microenvironment, and breast cancer survival. Nature - Communications biology 4 (1), 1-132021
2. Peer-reviewed article co-authored by Dr. Singhal, SK Singhal Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction. Nature genetics 53 (1), 65-75
3. Peer-reviewed article co-authored by Dr. Singhal, Ancestry-dependent gene expression correlates with reprogramming to pluripotency and multiple dynamic biological processes. Sci Adv. 2020 Nov;6(47). doi: 10.1126/sciadv.abc3851. Print 2020 Nov. PubMed PMID: 33219026; PubMed Central PMCID: PMC7679169.
4. 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
5. 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
6. 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
7. 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
8. 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
9. 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

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 provide a new perspective regarding the microenvironment in breast cancer, which holds implications for better management of breast cancer patients. In a collaborative study with different 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 patients 1,2. This research is extremely useful and informative in minimizing the side effects of systemic therapy, which will overcome the existing limitations of toxic manifestation, often encountered in conventional therapeutic interventions, such as chemotherapy, endocrine or hormonal therapy.

1. 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
2. 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
3. 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

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 patients 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 evaluate its prediction ability. All patients were treated with External beam radiotherapy (EBRT) & brachytherapy. In a large collaborative study, we identified a refined set of candidate variants substantially increasing 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 profiling^3,4.

1. 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
2. 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
3. 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
4. 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