Biology subjects

Soldatov, R.

Publications and source records attributed to Soldatov, R..

6 recordsLinked to original sources

bioRxiv2025

Disrupted priming within draining lymph nodes drives immune quiescence in gastric cancer

The gastric mucosa is characterized by continuous innate immune surveillance and inflammatory signaling, yet a high proportion of gastric carcinomas (GCs) are recalcitrant to immune-directed therapies. The mechanisms by which GCs evade adaptive immune surveillance within the highly antigenic microenvironment of the gastric mucosa remains unknown. To address this, we collected patient-matched tumor tissue, distant normal tissue, metastasis, and draining lymph nodes to generate a large-scale single-cell immune profiling dataset from 64 patients (n=179 samples, >150,000 cells). From single cell analysis, we identified two distinct sources of impaired tumor surveillance within tumor draining lymph nodes. First, we observed that a significant fraction of tumor draining lymph nodes had undergone cytokine-driven reprogramming, leading to reduced dendritic cell homing and limited T cell priming. Second, T cells undergoing successful activation exhibited limited expansion and constrained differentiation, marked by expression of the quiescence-associated transcription factor Kruppel-like Factor 2 (KLF2). Overexpression of KLF2 in primary T cells limited both their differentiation and cytotoxic capacity. These findings implicate both impaired T cell priming and KLF2-dependent T cell quiescence in limiting T cell immunity in gastric adenocarcinoma. We suggest these findings represent an emerging model for immune silencing in tumors developing from tissues with chronic inflammation.

immunology↗

bioRxiv2025

Inherited resilience to clonal hematopoiesis by modifying stem cell RNA regulation

Somatic mutations that increase hematopoietic stem cell (HSC) fitness drive their expansion in clonal hematopoiesis (CH) and predispose to blood cancers. Although CH frequently occurs with aging, it rarely progresses to overt malignancy. Population variation in the growth rate and potential of mutant clones suggests the presence of genetic factors protecting against CH, but these remain largely undefined. Here, we identify a non-coding regulatory variant, rs17834140-T, that significantly protects against CH and myeloid malignancies by downregulating HSC-selective expression and function of the RNA-binding protein MSI2. By modeling variant effects and mapping MSI2 binding targets, we uncover an RNA network that maintains human HSCs and influences CH risk. Importantly, rs17834140-T is associated with slower CH expansion rates in humans, and stem cell MSI2 levels modify ASXL1-mutant HSC clonal dominance in experimental models. These findings leverage natural resilience to highlight a key role for post-transcriptional regulation in human HSCs, and offer genetic evidence supporting inhibition of MSI2 or its downstream targets as rational strategies for blood cancer prevention.

genetics↗

bioRxiv2022

scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single cell data

scFates provides an extensive toolset for analysis of dynamic trajectories comprising tree learning, feature association testing, branch differential expression and with a focus on cell biasing and fate splits at the level of bifurcations. It is meant to be fully integrated into scanpy ecosystem for seamless analysis of trajectories from single cell data of various modalities (e.g. RNA, ATAC). Availability and implementationscFates is released as open-source software under the BSD 3-Clause "New" License and is available from the Python Package Index at https://pypi.org/project/scFates/. The source code is available on Github at https://github.com/LouisFaure/scFates/ Supplementary informationA supplementary document is provided with a complete explanation of the underlying statistics, and two figures showing examples of analysis.

bioinformatics↗

bioRxiv2022

Haplotype-enhanced inference of somatic copy number profiles from single-cell transcriptomes

Genome instability and aberrant alterations of transcriptional programs both play important roles in cancer. However, their relationship and relative contribution to tumor evolution and therapy resistance are not well-understood. Single-cell RNA sequencing (scRNA-seq) has the potential to investigate both genetic and non-genetic sources of tumor heterogeneity in a single assay. Here we present a computational method, Numbat, that integrates haplotype information obtained from population-based phasing with allele and expression signals to enhance detection of CNVs from scRNA-seq data. To resolve tumor clonal architecture, Numbat exploits the evolutionary relationships between subclones to iteratively infer the single-cell copy number profiles and tumor clonal phylogeny. Analyzing 21 tumor samples composed of multiple myeloma, breast, and thyroid cancers, we show that Numbat can accurately reconstruct the tumor copy number profile and precisely identify malignant cells in the tumor microenvironment. We uncover additional subclonal complexity contributed by allele-specific alterations, and identify genetic subpopulations with transcriptional signatures relevant to tumor progression and therapy resistance. We hope that the increased power to characterize genomic aberrations and tumor subclonal phylogenies provided by Numbat will help delineate contributions of genetic and non-genetic mechanisms in cancer.

bioinformatics↗

bioRxiv2020

Population sequencing data reveal a compendium of mutational processes in human germline

Mechanistic processes underlying human germline mutations remain largely unknown. Variation in mutation rate and spectra along the genome is informative about the biological mechanisms. We statistically decompose this variation into separate processes using a blind source separation technique. The analysis of a large-scale whole genome sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. Seven of these processes lend themselves to a biological interpretation. One process is driven by bulky DNA lesions that resolve asymmetrically with respect to transcription and replication. Two processes independently track direction of replication fork and replication timing. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions. We also demonstrate that a recently discovered mutagenic process specific to oocytes can be localized solely from population sequencing data. This process is spread across all chromosomes and is highly asymmetric with respect to the direction of transcription, suggesting a major role of DNA damage.

genetics↗

bioRxiv2017

RNA velocity in single cells

RNA abundance is a powerful indicator of the state of individual cells, but does not directly reveal dynamic processes such as cellular differentiation. Here we show that RNA velocity--the time derivative of RNA abundance--can be estimated by distinguishing unspliced and spliced mRNAs in standard single-cell RNA sequencing protocols. We show that RNA velocity is a vector that predicts the future state of individual cells on a timescale of hours. We validate the accuracy of RNA velocity in the neural crest lineage, demonstrate its use on multiple technical platforms, reconstruct the branching lineage tree of the mouse hippocampus, and measure RNA kinetics in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

genomics↗