A5059617425- CAR-T cell therapy research
- Cutaneous Melanoma Detection and Management
- Melanoma and MAPK Pathways
- Cancer Immunotherapy and Biomarkers
- Immunotherapy and Immune Responses
- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Pancreatic and Hepatic Oncology Research
- Educational Curriculum and Learning Methods
- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Gut microbiota and health
- Computational Drug Discovery Methods
- Cancer Research and Treatments
- Cell Image Analysis Techniques
- Ferroptosis and cancer prognosis
- Microbial Community Ecology and Physiology
- Lung Cancer Treatments and Mutations
- DNA Repair Mechanisms
- Functional Brain Connectivity Studies
- Mycobacterium research and diagnosis
- Phagocytosis and Immune Regulation
- Epigenetics and DNA Methylation
- Bacteriophages and microbial interactions
- Evolution and Genetic Dynamics
National Cancer Institute
2018-2024
Center for Cancer Research
2020-2024
University of Maryland, College Park
2017-2024
National Institutes of Health
2020-2024
University College London
2024
London Cancer
2024
University Hospital of Lausanne
2021
Institute of Bioinformatics
2019
The Medical Center of Aurora
2016
University of Colorado System
2008
Anticancer therapies have been limited by the emergence of mutations and other adaptations. In bacteria, antibiotics activate SOS response, which mobilizes error-prone factors that allow for continuous replication at cost mutagenesis. We investigated whether treatment lung cancer with EGFR inhibitors (EGFRi) similarly engages hypermutators. cycling drug-tolerant persister (DTP) cells in EGFRi-treated patients presenting residual disease, we observed upregulation GAS6, whereas ablation GAS6's...
While synthetic lethality (SL) holds promise in developing effective cancer therapies, SL candidates found via experimental screens often have limited translational value. Here we present a data-driven approach, ISLE (identification of clinically relevant lethality), that mines TCGA cohort to identify the most likely interactions (cSLi) from given candidate set lab-screened SLi. We first validate benchmark large-scale drug response and by predicting efficacy mouse xenograft models. then...
Abstract The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect growth and clinical outcome. To discover such interactions, we developed CODEFACS (COnfident DEconvolution For All Cell Subsets), tool deconvolving type–specific gene expression in each sample from bulk expression, LIRICS (Ligand–Receptor Interactions between statistical framework prioritizing clinically relevant ligand–receptor the deconvolved data. We first demonstrate superiority versus...
Abstract Purpose: Immune checkpoint blockade (ICB) agents and adoptive cell transfer (ACT) of tumor-infiltrating lymphocytes (TIL) are prominent immunotherapies used for the treatment advanced melanoma. Both therapies rely on activation that target shared tumor antigens or neoantigens. Recent analysis patients with metastatic melanoma who underwent TIL ACT at NCI demonstrated decreased responses in previously treated anti–PD-1 agents. We aimed to find a basis difference response rates...
The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and analyzing differential abundance taxa. Using series controlled experiments analyses, we performed first systematic evaluation efficacy recovering unique molecular identifiers by multiple scRNA-seq technologies, which identified newer 10x chemistries (3' v3 5') as best suited...
Article12 March 2019Open Access Transparent process Genome-wide prediction of synthetic rescue mediators resistance to targeted and immunotherapy Avinash Das Sahu Corresponding Author [email protected] orcid.org/0000-0002-2193-6276 Department Biostatistics Computational Biology, Harvard School Public Health, Boston, MA, USA Medicine Medical School, Massachusetts General Hospital Cancer Center, University Maryland Institute Advanced Computer Science (UMIACS), Maryland, College Park, MD,...
Abstract Background Studies of cancer mutations have typically focused on identifying driving that confer growth advantage to cells. However, genomes accumulate a large number passenger somatic resulting from various endogenous and exogenous causes, including normal DNA damage repair processes or cancer-related aberrations maintenance machinery as well triggered by carcinogenic exposures. Different mutagenic often produce characteristic mutational patterns called signatures. Identifying...
Abstract Computational identification and quantification of distinct microbes from high throughput sequencing data is crucial for our understanding human health. Existing methods either use accurate but computationally expensive alignment-based approaches or less fast alignment-free approaches, which often fail to correctly assign reads genomes. Here we introduce CAMMiQ, a combinatorial optimization framework identify quantify genomes (specified by database) in metagenomic dataset. As key...
Somatic mutations result from processes related to DNA replication or environmental/lifestyle exposures. Knowing the activity of mutational in a tumor can inform personalized therapies, early detection, and understanding tumorigenesis. Computational methods have revealed 30 validated signatures active human cancers, where each signature is pattern single base substitutions. However, half these no known etiology, some similar distinct etiologies, making patterns mutation hard interpret....
Abstract Advances in single-cell RNA sequencing (scRNAseq) technologies uncovered an unexpected complexity tumors, underlining the relevance of intratumor heterogeneity to cancer progression and therapeutic resistance. Heterogeneity mutational composition cells is a result distinct (sub)clonal expansions, each with metastatic potential resistance specific treatments. Unfortunately, due their low read coverage per cell, scRNAseq datasets are too sparse noisy be used for detecting expressed...
Abstract Idiopathic dilated cardiomyopathy (DCM) is a complex disorder with genetic and an environmental component involving multiple genes, many of which are yet to be discovered. We integrate genetic, epigenetic, transcriptomic, phenotypic, evolutionary features into method – Hridaya , infer putative functional genes underlying DCM in genome-wide fashion, using 213 human heart genomes transcriptomes. Many identified by experimentally shown cause cardiac complications. validate the top...
The characterization of mutational processes in terms their signatures activity relies mostly on the assumption that mutations a given cancer genome are independent one another. Recently, it was discovered certain segments mutations, termed processive groups, occur same DNA strand and generated by single process or signature. Here we provide first probabilistic model accounts for observed stickiness coordination. conditions each mutation allows signature to generate run mutations. It can...
Abstract The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data. Using series controlled experiments and analyses, we performed first systematic evaluation efficacy recovering UMIs by multiple scRNA-seq technologies, which identified newer 10x chemistries (3’ v3 5’) as best suited approach. Based on these findings, analyzed patient...
Abstract The identification and quantification of microbial abundance at the species or strain level from sequencing data is crucial for our understanding human health disease. Existing approaches estimation either use accurate but computationally expensive alignment-based species-level less fast alignment-free that fail to classify many reads accurately strain-level. Here we introduce CAMMiQ , a novel combinatorial solution problem, which performs better than best used tools on simulated...
Abstract Intratumoral heterogeneity arises as a result of genetically distinct subclones emerging during tumor progression. These are characterized by various types somatic genomic aberrations, with single nucleotide variants (SNVs) and copy number aberrations (CNAs) being the most prominent. While single-cell sequencing provides powerful data for studying progression, existing newly generated datasets obtained through conventional bulk sequencing. Most available methods progression from...
Abstract Background: Cancer immunotherapy has revolutionized cancer treatment in the last decade. However, most patients either do not respond to or eventually relapse so there is a need identify biomarkers of response and understand mechanisms resistance. Most biomarker studies have analyzed treated with immune checkpoint inhibitors (CPI) therapy while few adoptive cell transfer tumor infiltrating lymphocytes (TIL-ACT) relatively small patient cohorts. Methods: To systematically resistance...
<div>AbstractPurpose:<p>Immune checkpoint blockade (ICB) agents and adoptive cell transfer (ACT) of tumor-infiltrating lymphocytes (TIL) are prominent immunotherapies used for the treatment advanced melanoma. Both therapies rely on activation that target shared tumor antigens or neoantigens. Recent analysis patients with metastatic melanoma who underwent TIL ACT at NCI demonstrated decreased responses in previously treated anti–PD-1 agents. We aimed to find a basis difference...
Supplementary Figure from AXL and Error-Prone DNA Replication Confer Drug Resistance Offer Strategies to Treat EGFR-Mutant Lung Cancer
Abstract The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect growth and clinical outcome. To discover such interactions, we developed CODEFACS (COnfident DEconvolution For All Cell Subsets), tool deconvolving cell-type-specific gene expression in each sample from bulk expression, LIRICS (LIgand Receptor Interactions between statistical framework prioritizing clinically relevant ligand-receptor the deconvolved data. We first demonstrate superiority...
ABSTRACT Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts identify molecular events mediating therapy resistance. Many of these involve synthetic rescue (SR) interac tions, where the reduction in cell viability caused by gene inactivation is rescued an adaptive alteration another (the rescuer ). Here we perform a genome-wide prediction SR genes analyzing tumor transcriptomics and survival data 10,000 TCGA patients. Predicted...
Abstract Studies of cancer mutations typically focus on identifying driving mutations. However, in addition to the that confer a growth advantage, genomes accumulate large number passenger somatic resulting from normal DNA damage and repair processes as well triggered by carcinogenic exposures or related aberrations maintenance machinery. These mutagenic often produce characteristic mutational patterns called signatures. Understanding etiology signatures shaping genome is an important step...