Biology subjects

Sivajothi, S.

Publications and source records attributed to Sivajothi, S..

6 recordsLinked to original sources

bioRxiv2025

Prediction of Outcome from Spatial Protein Profiling of Triple-Negative Breast Cancers

In tumors, reciprocal spatial interactions between immune cells, their mediators, the extracellular matrix, and mutated neoplastic cells impact all aspects of treatment resistance. The operational mechanisms of these interactions are foundational for developing insights and targets for cancer therapy and prevention. Spatial quantification of the tumor microenvironment system from image data has untapped potential for patient stratification. Here, we present SparTile, a powerful computational approach for analysis of multiplex proteomics images to reveal clinically relevant structural organization in the tumor microenvironment. SparTile enables the robust unbiased identification and characterization of tumor microenvironments based on spatial relationships among protein markers without the need for cell segmentation or classification. Applied to tissues of patients with triple negative breast cancer (TNBC), an aggressive subtype of breast cancer, SparTile identified repeatable microenvironments with specific cellular relationships. These included microenvironments characterized by risk markers such as Ki67+ (p-value= 0.052) and vimentin+ (p-value<0.01) tumor cells, which correlate with poor survival. Furthermore, myeloid markers in an MX1 positive tumor environment correlate with shorter survival (p-value=0.04). Finally, we identified a relative distance between tumor and myeloid cell markers as a strong prognostic risk factor in multivariate Cox models (p-value=0.01). This distance metric was externally validated on two datasets of breast cancer multiplex images (p-values<0.01). Thus, unbiased protein-based and segmentation-free spatial analysis is effective for identifying clinically relevant biomarkers from multiplex tumor images and identifies novel predictive biology.

cancer biology↗

bioRxiv2024

STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging

We introduce Single-Cell Transcriptomics Analysis and Multimodal Profiling (STAMP), a scalable profiling approach of individual cells. Leveraging transcriptomics and proteomics imaging platforms, STAMP eliminates sequencing costs, to enable single-cell genomics from hundreds to millions of cells at an unprecedented low cost. Stamping cells in suspension onto imaging slides, STAMP supports single-modal (RNA or protein) and multimodal (RNA and protein) profiling and flexible, ultra-high-throughput formats. STAMP allows the analysis of a single or multiple samples within the same experiment, enhancing experimental flexibility, throughput and scale. We tested STAMP with diverse sample types, including peripheral blood mononuclear cells (PBMCs), dissociated cancer cells and differentiated embryonic stem cell cultures, as well as whole cells and nuclei. Combining RNA and protein profiling, we applied immuno-phenotyping of millions of blood cells simultaneously. We also used STAMP to identify ultra-rare cell populations, simulating clinical applications to identify circulating tumor cells (CTCs). Performing in vitro differentiation studies, we further showed its potential for large-scale perturbation studies. Together, STAMP establishes a new standard for cost-effective, scalable single-cell analysis. Without the need for sequencing, STAMP makes high-resolution profiling more affordable and accessible. Designed to meet the needs of research labs, diagnostic cores and pharmaceutical companies, STAMP holds the promise to transform our capacity to map human biology, diagnose diseases and drug discovery.

genomics↗

bioRxiv2021

A Cellular Reference Resource for the Mouse Urinary Bladder

The urinary bladder functions as a reservoir to store and extrude liquid bodily waste. Significant debate exists as to this tissues cellular composition and genes associated with their functions. We use a repertoire of cell profiling tools to comprehensively define and spatial resolve cell types. We characterize spatially validated, basal-to-luminal gene expression dynamics within the urothelium, the cellular source of most bladder cancers. We define three distinct populations of fibroblasts that spatially organize from the sub-urothelial layer through to the detrusor muscle, clarifying knowledge around these controversial interstitial cells, and associate increased fibroblasts with aging. We overcome challenges of profiling the detrusor muscle, absence from earlier single cell studies, to report on its transcriptome with many novel and neuronal-like features presumably associated with neuromuscular junctions. Our approach provides a blueprint for tissue atlas construction and the data provides the foundation for future studies of bladder function in health and disease.

genomics↗

bioRxiv2021

Single cell analysis of endometriosis reveals a coordinated transcriptional program driving immunotolerance and angiogenesis across eutopic and ectopic tissues.

Endometriosis is characterized by growth of endometrial-like tissue outside of the uterus affecting many women in their reproductive age, causing years of pelvic pain and potential infertility. Its pathophysiology remains largely unknown, limiting diagnosis and treatment. We characterized peritoneal and ovarian lesions at single-cell transcriptome resolution and compared to matched eutopic endometrium, control endometrium, and organoids derived from these tissues, generating data on over 100,000 cells across 12 individuals. We spatially localized many of the cell types using imaging mass cytometry. We identify a perivascular mural cell unique to the peritoneal lesions with dual roles in angiogenesis promotion and immune cell trafficking. We define an immunotolerant peritoneal niche, fundamental differences in eutopic endometrium and between lesions microenvironments, and a novel progenitor-like epithelial cell subpopulation. Altogether, this study provides a holistic view of the endometriosis microenvironment representing the first comprehensive cell atlas of the disease, essential information for advancing therapeutics and diagnostics.

genomics↗

bioRxiv2019

Antibody Targeting of B7-H4 Enhances the Immune Response in Urothelial Carcinoma

Locally advanced urothelial carcinoma has a poor survival despite a response to immunotherapy in approximately 25% of patients. To develop new therapies targeting other immune checkpoints, we identified increased expression of the T cell inhibitor protein, B7-H4 (VTCN1, B7S1, B7X), during tumor development of murine bladder cancer. Evaluation of B7-H4 in human bladder cancer by single-cell RNA-Seq and immune mass cytometry showed that B7-H4 is expressed by luminal tumors that are not normally responsive to PD-1 inhibitors. Additionally, overexpression B7-H4 was associated with significantly worse patient survival. In support of clinical translation, treatment of human monocyte and T cell co-cultures with a B7-H4 blocking antibody resulted in enhanced IFN-{gamma} secretion by CD4+ and CD8+ T cell. While the study of B7-H4 in mouse cancer models has been difficult using tumor cell lines, our findings show that B7-H4 expression increased at 3 months after exposure to BBN on CD11b+ monocytes/macrophages and delivery of anti-B7-H4 antibody resulted in decreased tumor size and increased CD8 immune cell infiltration with increased CD8+/IFN-{gamma}-producing T cells and a complimentary decrease in tumor infiltrating T regulatory cells (Tregs). Furthermore, treatment with a combination of anti-PD-1 and anti-B7-H4 antibodies resulted in a significant reduction in tumor stage. This data suggests that novel anti-B7-H4 antibodies maybe a viable target for bladder cancers unresponsive to PD-1 checkpoint inhibitors.

cancer biology↗

bioRxiv2017

Comprehensive Cell Type Specific Transcriptomics of the Human Kidney

The human kidney is a complex organ composed of specialized cell types. To better define this cellular complexity, we profiled the individual transcriptomes of 22,469 normal human kidney cells, identifying 27 cell types. We describe three distinct endothelial cell populations, a novel subset of intercalated cells, interstitial macrophage and dendritic cells, and identify numerous novel cell-type-specific markers, many validated using imaging mass cytometry and immunohistochemistry. Receptor-ligand analysis revealed previously unknown intercalated-endothelial and intercalated-distal nephron interactions, suggesting a role in maintenance of vascular integrity and intercalated cell survival. Notably, kidney disease-associated genes were largely expressed in proximal tubules, podocytes, endothelial and myeloid cells, highlighting an underappreciated role for endothelial cells in kidney pathologies. Our analysis also provides a resource of cell type enriched markers, solute carriers, channels and lncRNAs. In summary, this cell-type-specific transcriptome resource provides the foundation for a comprehensive understanding of kidney function and dysfunction at single cell resolution.

cell biology↗