Biology subjects

Gohil, S. H.

Publications and source records attributed to Gohil, S. H..

3 recordsLinked to original sources

bioRxiv2021

Robust integration of single-cell cytometry datasets

Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. However, in many cases the full potential of co-analyses is not reached due to technical variance between data from different experimental batches. Here, we present cyCombine, a method to robustly integrate cytometry data from different batches, experiments, or even different experimental techniques, such as CITE-seq, flow cytometry, and mass cytometry. We demonstrate that cyCombine maintains the biological variance and the structure of the data, while minimizing the technical variance between datasets. cyCombine does not require technical replicates across datasets, and computation time scales linearly with the number of cells, allowing for integration of massive datasets. Robust, accurate, and scalable integration of cytometry data enables integration of multiple datasets for primary data analyses and the validation of results using public datasets.

bioinformatics↗

bioRxiv2020

Distinct evolutionary paths in chronic lymphocytic leukemia during resistance to graft-versus-leukemia

Resistance to the graft-versus-leukemia (GvL) effect remains the major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis of GvL resistance for advanced lymphoid malignancies remains incompletely understood. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell-intrinsic features shape GvL outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post- HSCT relapse are shaped by distinct molecular dynamics and suggest that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for HLA loss was observed, even when present in pre-transplant subpopulations. Regardless of post-transplant relapse kinetics, gain of stem cell modules was a common signature associated with leukemia relapse. These data elucidate the biological pathways that underlie GvL resistance and post-transplant relapse. One Sentence SummaryWe find that the clinical kinetics of chronic lymphocytic leukemia relapse after stem cell transplant are underwritten by distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are unlike those imposed by chemotherapy.

cancer biology↗

bioRxiv2019

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

genomics↗