Biology subjects

Poultsides, G. A.

Publications and source records attributed to Poultsides, G. A..

4 recordsLinked to original sources

bioRxiv2026

A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping

Bulk RNA sequencing enables pan-cancer transcriptional analyses, but obscures cancer cell-specific programs due to admixture with nonmalignant cells, thereby limiting direct comparison between experimental models and primary tumors. Single-cell RNA sequencing (scRNA-seq) overcomes these limitations; however, the biological interpretability of public datasets is often compromised by variable data quality, inconsistent annotation, and atlas-scale aggregation strategies that prioritize data volume over biological coherence. We therefore developed a stringent integration framework that prioritizes representative malignant transcriptional states. Using Mahalanobis distance-based selection within batch-corrected latent space, we constructed a pan-cancer atlas comprising 135,424 high-quality malignant cells from 499 samples across 36 adult and pediatric cancers. Atlas-derived cancer signatures were used to determine tumor-cell line concordance and project ElasticNet models trained on DepMap CRISPR screens to infer cancer-specific gene dependencies. The scTumor Atlas establishes a scalable framework for tumor identity inference, cancer cell line benchmarking, and systematic identification of genetic vulnerabilities.

cancer biology↗

bioRxiv2025

Multidimensional Single-Cell Transcriptomic Profiling of Uterine Leiomyosarcomas Identifies Molecular Subtypes with Distinct Therapeutic Vulnerabilities

Uterine leiomyosarcoma (ULMS) is an orphan disease that frequently recurs and metastasizes, with patients undergoing multiple lines of chemotherapy due to lack of effective therapeutic targets. To address this gap, we used single-cell RNA sequencing and spatial transcriptomic analysis to comprehensively profile ULMS. We uncovered multiple states of tumor cells, including tumor cells with mesenchyme-like features, ischemic tumor cells defined by a MYC program, inflammatory tumor cells with active interferon signaling, and stem cell-like hormone receptor-positive cells. The inferred spatial correlates of these tumor cell states demonstrated unique localization patterns. By correlating these signatures to bulk RNA sequencing data, we demonstrate the relevance of these findings to clinical outcomes. Finally, using the single-cell integration and drug response prediction algorithm (scIDUC), we propose drug predictions that may target specific tumor states. Our findings suggest new avenues for further exploration of individualized and multifaceted therapeutic strategies to treat ULMS.

cancer biology↗

bioRxiv2022

Distinct cell states define the developmental trajectories of mucinous appendiceal neoplasms towards pseudomyxoma metastases

Appendiceal mucinous neoplasms (AMN) are rare tumors of the gastrointestinal tract. They metastasize with widespread abdominal dissemination leading to pseudomyxoma peritonei (PMP), a disease with poor prognosis. The cellular features of origin, differentiation and progression in AMN and PMP remain largely unknown. We characterized the distinct cell states of AMN and PMP using single-cell RNA-sequencing in 31 samples including AMNs, PMP metastases and matched normal tissues. We identified previously undescribed cellular features and heterogeneity in AMN and PMP. We discovered developmental cell states in tumor epithelial cells that ranged from progenitor phase to goblet cell differentiation, which was accompanied by elevated mucin gene expression. Metastatic PMP cells had a distinct cell state with increased mTOR and RAS signaling pathways and a series of upregulated cancer genes. We observed heterogeneity in a single PMP tumor as well as PMP metastases from the same patient. We validated our findings with immunohistochemistry, mass spectrometry on malignant ascites from PMP patients and gene expression data from an independent set of 63 PMPs.

cancer biology↗

bioRxiv2018

Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression

Sequencing the genomes of individual cancer cells provides the highest resolution of intratumoral heterogeneity. To enable high throughput single cell DNA-Seq across thousands of individual cells per sample, we developed a droplet-based, automated partitioning technology for whole genome sequencing. We applied this approach on a set of gastric cancer cell lines and a primary gastric tumor. In parallel, we conducted a separate single cell RNA-Seq analysis on these same cancers and used copy number to compare results. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection - where the percentage of replicating cells per clone is higher than expected - indicating ongoing tumor evolution. Our study demonstrates that joining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology. SIGNIFICANCEWe conducted a massively parallel DNA sequencing analysis on a set of gastric cancer cell lines and a primary gastric tumor in combination with a joint single cell RNA-Seq analysis. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection where the percentage of replicating cells per clone is higher than expected indicating ongoing tumor evolution. Our study demonstrates that combining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology.

genomics↗