Biology subjects

Schwartz, G. K.

Publications and source records attributed to Schwartz, G. K..

5 recordsLinked to original sources

bioRxiv2025

Systematic elucidation and pharmacologic targeting on non-oncogene dependencies in imatinib-resistant gastrointestinal stromal tumor

Treatment of gastrointestinal stromal tumor (GIST) with imatinib and other KIT-targeting drugs has improved outcomes significantly. However, most patients with advanced GIST eventually develop imatinib resistance and succumb to disease. We have developed mutation-agnostic, network-based methodologies to systematically elucidate and pharmacologically target Master Regulator (MR) proteins--critical non-oncogene dependencies--in cancer cells. Unsupervised, MR-based clustering of 34 GIST patient tumor samples produced two clusters, one of which contained all imatinib-resistant tumors. Analysis of 9 single-cell RNA profiles of high-risk GIST revealed that tumors with clinical progression on imatinib harbored large subpopulations enriched for the MR-activity signature of imatinib-resistant tumors, while tumors with resistance-associated mutations but without overt progression showed smaller, variably sized enriched subpopulations. High-throughput profiling of transcriptional responses by two GIST cell lines to FDA-approved and late-stage experimental drugs identified six candidate drugs that reversed the MR activity of imatinib-resistant GIST. Predictions were validated in two imatinib-resistant, patient-derived xenograft (PDX) models. The top prediction, linifanib, induced marked tumor growth inhibition in both PDXs across a wide dose range; selinexor and selumetinib were also effective compared to imatinib. We confirmed in vivo MR-activity reversal by these drugs, but not by ineffective drugs.

cancer biology↗

bioRxiv2025

Single Nuclei-Derived Molecular Subtypes of Gastrointestinal Stromal Tumors Correlate with Clinicopathologic Features and Predict Clinical Outcomes

Historically, gastrointestinal stromal tumor (GIST) has been subtyped by oncogenic driver mutations. However, tumors with the same mutational profile can have variable biology. To further explore the impact of molecular diversity on GIST biology, we performed single nucleus RNA sequencing on 16 primary GIST and utilized an integrated single cell atlas of the normal GI tract composed from multiple publicly available datasets to identify six distinct GIST cell states. We then statistically estimated the relative abundances of these profiles in bulk transcriptomic data. These were used to define six common GIST molecular subtypes based upon one or two predominant tumor cell states. We found that these molecular subtypes correlate with tumor locations, mutational profiles, and patient outcomes, and validated these subtypes in an independent international cohort. These molecular subtypes have the potential to be used for clinical prognostication for patients with GIST, identifying new therapeutic targets, and studying the cell of transformation of GIST.

cancer biology↗

bioRxiv2022

The CD58:CD2 axis is co-regulated with PD-L1 via CMTM6 and governs anti-tumor immunity

The cell autonomous balance of immune-inhibitory and -stimulatory signals is a critical yet poorly understood process in cancer immune evasion. Using patient-derived co-culture models and humanized mouse models, we show that an intact CD58:CD2 interaction is necessary for anti-tumor immunity. Defects in this axis lead to multi-faceted immune evasion through impaired CD2-dependent T cell polyfunctionality, T cell exclusion, impaired intra-tumoral proliferation, and concurrent protein stabilization of PD-L1. We performed genome-scale CRISPR-Cas9 and CD58 coimmunoprecipitation mass spectrometry screens identifying CMTM6 as a key stabilizer of CD58, and show that CMTM6 is required for concurrent upregulation of PD-L1 in CD58 loss. Single-cell RNA-seq analysis of patient melanoma samples demonstrates that most TILs lack expression of primary costimulatory signals required for response to PD-1 blockade (e.g. CD28), but maintain strong CD2 expression, thus providing an opportunity to mobilize a so far therapeutically untapped pool of TILs for anti-tumor immunity. We identify two potential therapeutic avenues, including rescued activation of human CD2-expressing TILs using recombinant CD58 protein, and targeted disruption of PD-L1/CMTM6 interactions. Our work identifies an underappreciated yet critical axis at the nexus of cancer immunity and evasion, uncovers a fundamental mechanism of co-inhibitory and -stimulatory signal balancing, and provides new approaches to improving cancer immunotherapies.

cancer biology↗

bioRxiv2022

Multi-modal single-cell and whole-genome sequencing of minute, frozen specimens to propel clinical applications

Single-cell genomics are enabling technologies, but their broad clinical application remains challenging. We report an easily adaptable approach for single-cell transcriptome and T cell receptor (TCR)-sequencing, and matched whole-genome sequencing from tiny, frozen clinical specimens. We achieve similar quality and biological outputs while reducing artifactual signals compared to data from matched fresh tissue samples. Profiling sequentially collected melanoma samples from the KEYNOTE-001 trial, we resolve cellular, genomic, and clonotype dynamics that encapsulate molecular patterns of tumor evolution during anti-PD-1 therapy. To demonstrate applicability to banked biospecimens of rare diseases, we generate a large uveal melanoma liver metastasis single-cell and matched WGS atlas, which revealed niche-specific impairment of clonal T cell expansion. This study provides a foundational framework for propelling single-cell genomics to the clinical arena.

genomics↗

bioRxiv2021

Pre-clinical validation of an RNA-based precision oncology platform for patient-therapy alignment in a diverse set of human malignancies resistant to standard treatments

Predicting tumor sensitivity to antineoplastics remains an elusive challenge, with no methods demonstrating predictive power. Joint analysis of tumors--from patients with distinct malignancies who had progressed on multiple lines of therapy--and drug perturbation transcriptional profiles predicted sensitivity to 28 of 350 drugs, 26 of which (93%) were confirmed in low-passage, patient-derived xenograft (PDX) models. Drugs were prioritized based on their ability to either invert the activity of individual Master Regulator proteins, with available high-affinity inhibitors, or of the modules they comprise (Tumor-Checkpoints), based on de novo mechanism of action analysis. Of 138 PDX mice enrolled in 16 single and 18 multi-protein treatment arms, a disease control rate (DCR) of 68% and 91 %, and an objective response rate (ORR) of 12% and 17%, were achieved respectively, compared to 6% and 0% in the negative controls arm, with multi-protein drugs achieving significantly more durable responses. Thus, these approaches may effectively complement and expand current precision oncology approaches, as also illustrated by a case study.

systems biology↗