Biology subjects

Chandrashekar, D. S.

Publications and source records attributed to Chandrashekar, D. S..

6 recordsLinked to original sources

bioRxiv2025

Azurify integrates cancer genomics with machine learning to classify the clinical significance of somatic variants

Accurate classification of somatic variations from high-throughput sequencing data has become integral to diagnostics and prognostics across various cancers. However, the classification of these variations remains highly manual, inherently variable, and largely inaccessible outside specialized laboratories. Here, we introduce Azurify - a computational tool that integrates machine learning, public resources recommended by professional societies, and clinically annotated data to classify the pathogenicity of variations in precision cancer medicine. Trained on over 15,000 clinically classified variants from 8,202 patients across 138 cancer phenotypes, Azurify achieves 99.1% classification accuracy for concordant pathogenic variants in data from two external clinical laboratories. Additionally, Azurify reliably performs precise molecular profiling in leukemia cases. Azurifys unified, scalable, and modular framework can be easily deployed within bioinformatics pipelines and retrained as new data emerges. In addition to supporting clinical workflows, Azurify offers a high-throughput screening solution for research, enabling genomic studies to identify meaningful variant-disease associations with greater efficiency and consistency.

genomics↗

bioRxiv2021

TGF-B signaling suppresses TCA cycle metabolism in renal cancer.

The Warburg effect is one of most-well studied metabolic phenomenon in cancer cells. For the most part, these studies have focused on enhanced rates of glycolysis observed in various models. The presumption has been that mitochondrial metabolism is suppressed. However, recent studies indicate that the extent of mitochondrial metabolism is far more heterogeneous in tumors than originally presumed. One tumor type with suppression of mitochondrial metabolism is renal cell carcinoma (RCC). Prior studies indicate that suppressed TCA cycle enzyme mRNA expression is associated with aggressive RCC. Yet, the mechanisms that regulate the TCA cycle in RCC remain uncharacterized. Here, we demonstrate that loss of TCA cycle enzyme expression is retained in RCC metastatic tissues. Moreover, proteomic analysis demonstrates that reduced TCA cycle enzyme expression is far more pronounced in RCC relative to other tumor types. Loss of TCA cycle enzyme expression is correlated with reduced expression of the transcription factor peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1) which is also lost in RCC tissues. PGC-1 re-expression in RCC cells restores the expression of TCA cycle enzymes in vitro and in vivo and leads to enhanced glucose carbon incorporation into TCA cycle intermediates. Mechanistically, TGF-{beta} signaling, in concert with histone deacetylase 7 (HDAC7), suppresses TCA cycle enzyme expression. In turn, pharmacologic inhibition of TGF-{beta} restores expression of TCA cycle enzyme expression and suppresses tumor growth in an orthotopic model of RCC. Taken together, our findings reveal a novel role for the TGF-{beta} /HDAC7 axis in global suppression of TCA cycle enzymes in RCC and provide novel insight into the molecular basis of altered mitochondrial metabolism in this malignancy.

cancer biology↗

bioRxiv2021

ARID1A-mutant and deficient bladder cancer is sensitive to EZH2 pharmacologic inhibition

Metastatic urothelial carcinoma of the bladder is generally incurable by current systemic therapy. Molecular characterization of bladder cancer (BLCa) has revealed multiple candidate driver genes for BLCa tumorigenesis. Epigenetic/chromatin modifiers have been shown to be frequently mutated in BLCa, with ARID1A mutations highly prevalent in nearly 20% of early and late stage tumors. EZH2 is a histone methyltransferase that acts as an oncogene. The data herein show that ARID1A deficient tumors, but not ARID1A wild-type tumors are sensitive to EZH2 inhibition. Specifically, EZH2 inhibitor-treated ARID1A deficient bladder cancer cells show significantly reduced cell viability, colony formation, and in vivo tumor growth relative to ARID1A-wild type bladder cancer cells. Thus, our study suggests that a specific subset of bladder cancer patients with ARID1A mutations can be therapeutically treated with pharmacologic inhibitors targeting EZH2.

cancer biology↗

bioRxiv2020

Comparative transcriptome analyses reveal genes associated with SARS-CoV-2 infection of human lung epithelial cells

Understanding the molecular mechanism of SARS-CoV-2 infection (the cause of COVID-19) is a scientific priority for 2020. Various research groups are working toward development of vaccines and drugs, and many have published genomic and transcriptomic data related to this viral infection. The power inherent in publicly available data can be demonstrated via comparative transcriptome analyses. In the current study, we collected high-throughput gene expression data related to human lung epithelial cells infected with SARS-CoV-2 or other respiratory viruses (SARS, H1N1, rhinovirus, avian influenza, and Dhori) and compared the effect of these viruses on the human transcriptome. The analyses identified fifteen genes specifically expressed in cells transfected with SARS-CoV-2; these included CSF2 (colony-stimulating factor 2) and S100A8 and S100A9 (calcium-binding proteins), all of which are involved in lung/respiratory disorders. The analyses showed that genes involved in the Type1 interferon signaling pathway and the apoptosis process are commonly altered by infection of SARS-CoV-2 and influenza viruses. Furthermore, results of protein-protein interaction analyses were consistent with a functional role of CSF2 in COVID-19 disease. In conclusion, our analysis has revealed cellular genes associated with SARS-CoV-2 infection of the human lung epithelium; these are potential therapeutic targets.

bioinformatics↗

bioRxiv2019

Therapeutically actionable PAK4 is amplified, overexpressed and involved in bladder cancer progression

Muscle-invasive bladder carcinomas (MIBCs) are aggressive genitourinary malignancies. Disease incidence and survival rates vary based on aggressiveness and treatment options. Metastatic urothelial carcinoma of the bladder is generally incurable by current chemotherapy and leads to early mortality. For a minority ([~]20%) of patients, T-cell checkpoint inhibitors provide durable benefits following prior platinum therapy. Recent studies have identified molecular subtypes of MIBCs with different sensitivities to frontline therapy, suggesting heterogeneity in these tumors and pointing to the importance of molecular characterization of MIBCs to provide effective treatment. We have performed multi-omic profiling of the kinome to identify therapeutic targets that are overexpressed in a subset of BLCAs. Our analyses revealed amplification and overexpression of P21 (RAC1) activated kinase 4 (PAK4) in a subset of BLCAs. For these tumors, multiplex kinase assay profiling identified corresponding PAK4 target substrates. By performing experiments using cultured bladder cancer cells, we confirmed the role of PAK4 in BLCA cell proliferation and invasion. Furthermore, our studies showed that a PAK4 inhibitor was effective in curtailing growth of BLCA cells. Transcriptomic analyses identified elevated expression of another kinase, Protein Tyrosine Kinase 6 (PTK6), upon treatment with a PAK4 inhibitor. Similarly, RNA interference of PAK4 led to elevated expression of PTK6. Treatment with a combination of kinase inhibitors (vandetanib and dasatinib) showed enhanced sensitivity compared to either drug alone. Thus, PAK4 may be therapeutically actionable for a subset of MIBC patients with amplified and/or overexpressed PAK4 in their tumors. Our results also indicate that combined inhibition of PAK4 and PTK6 may overcome resistance to PAK4. These observations warrant clinical investigations with selected BLCA patients.

cancer biology↗

bioRxiv2019

Pseudogene associated recurrent gene fusion in prostate cancer

Analysis of next generation transcriptome sequencing data of prostate cancer identified a novel gene fusion formed by the fusion of a protein coding gene (KLK4) with a non-coding pseudogene (KLKP1) and expression of its cognate protein. Screening of 659 prostate cancer TMA showed about 32% of positive cases predominantly expressed in higher Gleason grade tumors. Concomitant expression with ERG but not with SPINK1 and other ETS fusion positive tumors. Fusion gene expression potentially regulated by AR and ERG. Antibody specific to the KLK4-KLKP1 fusion protein was validated by immunohistochemistry and western blot methods. Oncogenic properties were validated by in vitro and in vivo functional studies. Clinical data analysis shows significant association with prostate cancer in young men and overall survival analysis indicate favorable prognosis. Non-invasive detection in urine samples has been confirmed. Taken together, we present a novel biomarker for routine screening of high Gleason grade prostate cancer at diagnosis.\n\nSIGNIFICANCEWe discovered and validated a novel prostate cancer (PCa) specific fusion gene involving a protein coding (KLK4) and a pseudogene (KLKP1) and its cognate protein. The unique feature of this fusion gene is the conversion of the noncoding pseudogene into a protein coding gene and its unique expression only in about 30% of high Gleason grade PCa. Expression of this gene is found to be concomitant in ERG fusion positive prostate cancer but mutually exclusive with SPINK1, ETV1, ETV4 and ETV5 positive tumors. Like other ETS family gene fusions, KLK4-KLKP1 can be detected in the urine samples of patients with prostate cancer enabling non-invasive detection of high Gleason grade prostate cancer. Given the unique feature of this fusion oncogenic potential, high Gleason grade specific expression and noninvasive detection, this novel gene fusion has a potential to be used as a biomarker for early detection of high-grade prostate cancer and a therapeutic target.

cancer biology↗