Biology subjects

Mohanty, V.

Publications and source records attributed to Mohanty, V..

5 recordsLinked to original sources

bioRxiv2020

Targeting uncoupling of copy number and gene expression in cancers

The high degree of aneuploidy in cancer is likely tolerated via extensive uncoupling of copy number (CN) and mRNA expression (UCNE) of deleterious genes located in copy number aberrations (CNAs). To test the extent and role of UCNE in cancer, we performed integrative analysis of multiomics data across The Cancer Genome Atlas (TCGA), encompassing [~] 5000 individual tumors. We found many genes having UCNE, the degree of which are associated with increased oncogenic signaling, proliferation and immune-suppression. The occurrence of UCNE appears to be orchestrated by complex epigenetic and regulatory changes, with transcription factors (TFs) playing a prominent role. To further dissect the regulatory mechanisms, we developed a systems-biological approach to identify candidate TFs, which upon perturbation can offset UCNE and reduce tumor fitness. Applying our approach on TCGA data, we identified 20 putative targets, 45% of which were validated by independent sources. Among them are IRF1, which plays a prominent role in anti-tumor immunity and response to immune checkpoint therapy, ETS1, TRIM21 and GATA3, which are associated with anti-tumor immunity, tumor proliferation and metastasis. Together, our study indicates that UCNE is likely an important mechanism in cancer development that can be exploited therapeutically.

cancer biology↗

bioRxiv2020

Sensei: How many samples to tell evolution in single-cell studies?

1AO_SCPLOWBSTRACTC_SCPLOWCellular heterogeneity underlies cancer evolution and metastasis. Advances in single-cell technologies such as single-cell RNA sequencing and mass cytometry have enabled interrogation of cell type-specific expression profiles and abundance across heterogeneous cancer samples obtained from clinical trials and preclinical studies. However, challenges remain in determining sample sizes needed for ascertaining changes in cell type abundances in a controlled study. To address this statistical challenge, we have developed a new approach, named Sensei, to determine the number of samples and the number of cells that are required to ascertain such changes between two groups of samples in single-cell studies. Sensei expands the t-test and models the cell abundances using a beta-binomial distribution. We evaluate the mathematical accuracy of Sensei and provide practical guidelines on over 20 cell types in over 30 cancer types based on knowledge acquired from the cancer cell atlas (TCGA) and prior single-cell studies. We provide a web application to enable user-friendly study design via https://kchen-lab.github.io/sensei/table_beta.html.

bioinformatics↗

bioRxiv2020

Single-cell copy number lineage tracing enabling gene discovery

Aneuploidy plays critical roles in genome evolution. Alleles, whose dosages affect the fitness of an ancestor, will have altered frequencies in the descendant populations upon perturbation. Single-cell sequencing enables comprehensive genome-wide copy number profiling of thousands of cells at various evolutionary stage and lineage. That makes it possible to discover dosage effects invisible at tissue level, provided that the cell lineages can be accurately reconstructed. Here, we present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles. We also present a statistical routine named lineage speciation analysis (LSA), which facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. We assessed our approaches using a variety of single-cell datasets. Overall, MEDALT appeared more accurate than phylogenetics approaches in reconstructing copy number lineage. From the single-cell DNA-sequencing data of 20 triple-negative breast cancer patients, our approaches effectively prioritized genes that are essential for breast cancer cell fitness and are predictive of patient survival, including those implicating convergent evolution. Similar benefits were observed when applying our approaches on single-cell RNA sequencing data obtained from cancer patients. The source code of our study is available at https://github.com/KChen-lab/MEDALT.

bioinformatics↗

bioRxiv2020

Inhibition of the av integrin-TGF-b axis improves natural killer cell function against glioblastoma stem cells

Glioblastoma, the most aggressive brain cancer, often recurs because glioblastoma stem cells (GSCs) are resistant to all standard therapies. Here, we show that patient-derived GSCs, but not normal astrocytes, are highly sensitive to lysis by healthy allogeneic natural killer (NK) cells in vitro. In contrast, single cell analysis of autologous, tissue infiltrating NK cells isolated from surgical samples of high-grade glioblastoma patient tumors using mass cytometry and single cell RNA sequencing revealed an abnormal phenotype associated with impaired lytic function compared with peripheral blood NK cells from GBM patients or healthy donors. This immunosuppression was attributed to an integrin-TGF-{beta} mechanism, activated by direct cell-cell contact between GSCs and NK cells. Treatment of GSC-engrafted mice with allogeneic NK cells in combination with inhibitors of integrin or TGF-{beta} signaling, or with TGF-{beta} receptor 2 gene-edited NK cells prevented GSC-induced NK cell dysfunction and tumor growth. Collectively, our findings reveal a novel mechanism of NK cell immune evasion by GSCs and implicate the integrin-TGF-{beta} axis as a useful therapeutic target to eliminate GSCs in this devastating tumor.

immunology↗

bioRxiv2020

CIS checkpoint deletion enhances the fitness of cord blood derived natural killer cells transduced with a chimeric antigen receptor

Immune checkpoint therapy has produced remarkable improvements in the outcome for certain cancers. To broaden the clinical impact of checkpoint targeting, we devised a strategy that couples targeting of the cytokine-inducible SH2-containing (CIS) protein, a key negative regulator of interleukin (IL)-15 signaling, with chimeric antigen receptor (CAR) engineering of natural killer (NK) cells. This combined strategy boosted NK cell effector function through enhancing the Akt/mTORC1 axis and c-MYC signaling, resulting in increased aerobic glycolysis. When tested in a lymphoma mouse model, this combined approach improved NK cell anti-tumor activity more than either alteration alone, eradicating lymphoma xenografts without signs of any measurable toxicity. We conclude that combining CIS checkpoint deletion with CAR engineering promotes the metabolic fitness of NK cells in an otherwise suppressive tumor microenvironment. This approach, together with the prolonged survival afforded by CAR modification, represents a promising milestone in the development of the next generation of NK cells for cancer immunotherapy.

immunology↗