A5040004367- Cancer Genomics and Diagnostics
- Cancer Immunotherapy and Biomarkers
- Immunotherapy and Immune Responses
- CAR-T cell therapy research
- Cancer-related molecular mechanisms research
- Genomics and Rare Diseases
- RNA regulation and disease
- Lung Cancer Treatments and Mutations
- Genetics, Bioinformatics, and Biomedical Research
- Bioinformatics and Genomic Networks
- Cutaneous Melanoma Detection and Management
- Radiomics and Machine Learning in Medical Imaging
- Genomics and Phylogenetic Studies
- Ferroptosis and cancer prognosis
- Melanoma and MAPK Pathways
- MicroRNA in disease regulation
- Molecular Biology Techniques and Applications
- Machine Learning in Bioinformatics
- Body Composition Measurement Techniques
- Advances in Oncology and Radiotherapy
- Genetic factors in colorectal cancer
- Gene expression and cancer classification
- Renal cell carcinoma treatment
- BRCA gene mutations in cancer
- Circular RNAs in diseases
Bristol-Myers Squibb (United States)
2018-2023
Predictive Science (United States)
2020-2023
Amazon (United States)
2022
Bristol-Myers Squibb (Germany)
2019
Rutgers, The State University of New Jersey
2005-2019
Indian Institute of Science Bangalore
2011-2014
Institute of Mental Health
2013
Sri Sathya Sai Institute of Higher Medical Sciences
2013
St James's University Hospital
1989
Abstract KRAS is the most common oncogenic driver in lung adenocarcinoma (LUAC). We previously reported that STK11/LKB1 (KL) or TP53 (KP) comutations define distinct subgroups of KRAS-mutant LUAC. Here, we examine efficacy PD-1 inhibitors these subgroups. Objective response rates to blockade differed significantly among KL (7.4%), KP (35.7%), and K-only (28.6%) (P < 0.001) Stand Up To Cancer (SU2C) cohort (174 patients) with LUAC patients treated nivolumab CheckMate-057 phase III...
Abstract Outcomes for patients with melanoma have improved over the past decade as a result of development and FDA approval immunotherapies targeting cytotoxic T lymphocyte antigen-4 (CTLA-4), programmed death-1 (PD-1), death ligand 1 (PD-L1). However, these therapies do not benefit all patients, an area intensive research investigation is identifying biomarkers that can predict which are most likely to from them. Here, we report exploratory analyses associations tumor mutational burden...
Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM survival, we analyzed miRNA data of patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided randomly into training testing sets equal number in each group. identified 10 significant miRNAs using Cox regression analysis on set formulated risk score based these segregated high low...
Abstract Glioblastoma (GBM) is the most common, malignant adult primary tumor with dismal patient survival, yet molecular determinants of survival are poorly characterized. Global methylation profile GBM samples (our cohort; n = 44) using high-resolution microarrays was carried out. Cox regression analysis identified a 9-gene signature that predicted in patients. A risk-score derived from univariate our and The Cancer Genome Atlas (TCGA) cohort. Multivariate risk score as an independent...
Tumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.Here we describe the in-depth evaluation bioinformatic analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from phase III clinical trial.In CheckMate 026 trial, was retrospectively assessed 312 patients non-small-cell...
Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; IV) are diffusely infiltrating tumors called malignant astrocytomas. The treatment regimen prognosis distinctly different between anaplastic patients. Although histopathology based current grading system is well accepted largely reproducible, intratumoral histologic variations often lead to difficulties in classification of samples. In order obtain a more robust molecular classifier, we analysed RT-qPCR expression data 175...
Abstract Background: Increased tumor mutational burden (TMB) and inflammation are associated with improved clinical outcomes to immuno-oncology (I-O) therapy in many types. Genomic correlates of response nivolumab (N) vs dacarbazine (D) (CheckMate [CM] 066; NCT01721772) N+ipilimumab (I) combination or N I (CM 067; NCT01844505) were evaluated for association TMB an inflammatory gene signature outcomes. Methods: In pretreatment samples from eligible patients (pts), was analyzed by whole-exome...
Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers these pipelines identify variants at the lowest possible granularity, single-nucleotide (SNV). As a result, multiple adjacent SNVs are called individually instead of as multi-nucleotide (MNV). With this approach, amino acid change from individual SNV within codon could be different based on MNV that results combining SNV, leading incorrect conclusions about...
Background: Increased tumor mutational burden (TMB) and inflammation are associated with improved clinical outcomes to immuno-oncology (I-O) therapy in many types. Genomic correlates of response nivolumab (N) vs dacarbazine (D) (CheckMate [CM] 066; NCT01721772) N+ipilimumab (I) combination or N I (CM 067; NCT01844505) were evaluated for association TMB an inflammatory gene signature outcomes.Methods: In pretreatment samples from eligible patients (pts), was analyzed by whole-exome sequencing...
In six normal subjects administered 5 μCi of an oral dose a commercially available 14 C-labelled cellulose, significant amounts CO 2 were detected in expired air within 30 min, suggesting that other non-cellulosic material was present. Chemical and microscopical examination confirmed starch the principal contaminant. The commercial preparation purified using amyloglucosidase ( EC 3.2.1.3) digestion following gelatinization by autoclaving. Subsequent administration cellulose to further...
Although next-generation sequencing assays are routinely carried out using samples from cancer trials, the data not always of required quality. There is a need to evaluate performance tissue collection sites and provide feedback about quality data. This study used modeling approach based on whole exome control (QC) metrics relative participating in Bristol Myers Squibb Immuno-Oncology clinical trials sample collection. We identified several events for swap. Overall, most performed well few...
Cyanobacteria are often used as an indicator of the presence and level pollutants in environment. They have been especially recognized for their ability to identify contamination heavy metals. Class II metallothioneins (MTs), usually found cyanobacteria, low molecular weight metal-binding proteins may be required metal tolerance. It would important examine phylogenetic pattern well prokaryotic evolution protein families among cyanobacteria. All available sequences cyanobacteria from GenBank,...
<div>Abstract<p>Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers these pipelines identify variants at the lowest possible granularity, single-nucleotide (SNV). As a result, multiple adjacent SNVs are called individually instead of as multi-nucleotide (MNV). With this approach, amino acid change from individual SNV within codon could be different based on MNV that results combining SNV, leading...
<p>PDF file - 5025K, Supplementary Figure SF1: ROC analysis and risk stratification in three groups ; SF2: Risk score distribution of TCGA our patients' cohort heatmap 9 genes SF3: Kaplan meier Bent et al data set SF4: NFkb network EMSA NFkB protein SF5: Heat map differentially expressed low high REMBRANDT Phillips datasets SF6: landscape SF7: NPTX2 expression level methylation correlation SF8: inhibits activity SF9: nuclear translocation SF10: by activating p53 dependent PTEN...
<p>Example knitr report based on CBio export for 26 TCGA melanoma samples</p>
<p>Example knitr report based on CBio export for 26 TCGA melanoma samples</p>
<p>PDF file - 5025K, Supplementary Figure SF1: ROC analysis and risk stratification in three groups ; SF2: Risk score distribution of TCGA our patients' cohort heatmap 9 genes SF3: Kaplan meier Bent et al data set SF4: NFkb network EMSA NFkB protein SF5: Heat map differentially expressed low high REMBRANDT Phillips datasets SF6: landscape SF7: NPTX2 expression level methylation correlation SF8: inhibits activity SF9: nuclear translocation SF10: by activating p53 dependent PTEN...