Biology subjects

Sarachakov, A.

Publications and source records attributed to Sarachakov, A..

3 recordsLinked to original sources

bioRxiv2026

AI-based separation of malignant cell- and microenvironment-specific gene expression from bulk RNA sequencing enhances biomarker interpretation

Bulk RNA sequencing (RNA-seq)-based gene expression analysis is a promising tool for personalized cancer diagnostics, disease monitoring, and treatment decision-making. However, its clinical utility is limited by interference from non-malignant tumor microenvironment cells, which can dominate transcript data in low-purity tumors. While cell deconvolution methods like Kassandra can predict digital cell percentages from bulk RNA-seq, approaches for delineating the gene expression contribution of tumor compartments remain limited. To overcome this limitation, we developed Helenus, a machine-learning-based tool that separates gene expression between malignant and non-malignant cells. Trained on over 200 million synthetic RNA profiles representing diverse tumor types and purities, Helenus demonstrated high accuracy in separating gene expression origin. Helenus also uncovered true genomic-RNA correlations such as copy number alterations and the expression of therapeutic antibody-drug conjugate targets specifically on tumor cells. Helenus provides critical insights into tumor biology and immunotherapy response by precisely identifying biomarker expressions, paving the way for more effective personalized cancer care. SignificanceHelenus extracts gene expression profiles of cancerous and non-cancerous compartments of tumor biopsies from bulk RNA-seq data, enabling the determination of how the expression of specific genes affects malignancy and tumor immunity.

cancer biology↗

bioRxiv2025

A simple circuit to sustain intact tumor microenvironments for complex drug interrogations

Deep learning and large language models can integrate complex datasets to uncover biological insights that are often undetectable through conventional analyses. With application to translational cancer research, these computational tools have positioned 3D patient-derived tumor avatars front and center as crucial data input sources. However, a major challenge remains: the lack of standardization in media composition in 3D patient-derived tumor models unpredictably affects cell behavior and limit the utility beyond predicting treatment responses. To address this unmet need, we developed a simple, reproducible perfusion circuit system to approximate in vivo physiology using autologous patient plasma. With peritoneal metastases and core needle biopsies across multiple tumor histologies, we demonstrate preservation of the tumor microenvironment for up to 48 hours using multi-modal interrogation techniques. With proof-of-concept experiments, we display the systems ability to unveil complex drug-dependent biology within this time window. Standardizable, physiologically relevant platforms for 3D patient-derived tumor avatars will yield unprecedented insights through the integration of data from broad groups of patients and the use of an expanding armamentarium of artificial intelligence capabilities.

cancer biology↗

bioRxiv2023

SINGLE CELL RESOLUTION SPATIAL MAPPING OF HUMAN HEMATOPOIESIS REVEALS AGING-ASSOCIATED TOPOGRAPHIC REMODELING

The spatial anatomy of hematopoiesis in bone marrow has been extensively studied in mice and other preclinical models, but technical challenges have precluded a commensurate exploration in humans. Institutional pathology archives contain thousands of paraffinized bone marrow core biopsy tissue specimens, providing a rich resource for studying the intact human bone marrow topography in a variety of physiologic states. Thus, we developed an end-to-end pipeline involving multiparameter whole tissue staining, in situ imaging at single-cell resolution, and artificial intelligence (AI)-based digital image analysis, and then applied it to a cohort of disease-free samples to survey alterations in the hematopoietic topography associated with aging. Our data indicate heterogeneity in marrow adipose tissue (MAT) content within each age group, and an inverse correlation between MAT content and proportions of early myeloid and erythroid precursors, irrespective of age. We identify consistent endosteal and perivascular positioning of hematopoietic stem and progenitor cells (HSPCs) with medullary localization of more differentiated elements and, importantly, uncover new evidence of aging-associated changes in cellular and vascular morphologies, microarchitectural alterations suggestive of inflammaging, and diminution of a potentially active megakaryocytic niche. Overall, our findings suggest that there is topographic remodeling of human hematopoiesis associated with aging. More generally, we demonstrate the potential to deeply unravel the spatial biology of normal and pathologic human bone marrow states using intact archival tissue specimens.

systems biology↗