Biology subjects

Worley, J.

Publications and source records attributed to Worley, J..

6 recordsLinked to original sources

bioRxiv2023

Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential--often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel--a commonly used chemotherapeutic --displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations. Statement of significanceNetwork-based approaches, as shown in a study on metastatic breast cancer, can develop effective combinatorial therapies targeting complementary subpopulations. By analyzing scRNA-seq data and using clinically relevant drugs, researchers identified and depleted chemoresistant Cancer Stem-Like Cells, enhancing the efficacy of standard chemotherapies.

systems biology↗

bioRxiv2022

Single-Cell RNAseq Analysis Reveals Robust Anti-PD-1-Mediated Increase of Immune Infiltrate in Metastatic Castration-Sensitive Prostate Cancer

Compared to other malignancies, the tumor microenvironment (TME) of primary and castration-resistant prostate cancer (CRPC) is relatively devoid of immune infiltrates. While androgen deprivation therapy (ADT) induces a complex immune infiltrate in localized prostate cancer, both in animal models and humans, the TME composition of metastatic, castration-sensitive prostate cancer (mCSPC) is relatively unknown and the effects of ADT and other treatments are poorly characterized in this context. To address this challenge, we analyzed metastatic sites from patients enrolled on a phase 2 clinical trial (NCT03951831), in which men were treated with standard-of-care chemo-hormonal therapy with anti-PD-1 immunotherapy, at the single cell level. Longitudinal protein activity-based analysis of TME subpopulations identified immune subpopulations conserved across multiple metastatic sites, their dynamic, treatment-mediated evolution, and associated clinical response features. Our study revealed a therapy-resistant, transcriptionally distinct tumor subpopulation, which comprises an increasing number of cells in treatment-refractory patients, and identified several druggable targets in both tumor and immune cells as candidates to advance treatment and improve outcomes for patients with mCSPC.

cancer biology↗

bioRxiv2021

Interrogation of genome-wide, experimentally dissected gene regulatory networks reveals mechanisms underlying dynamic cellular state control

Pooled CRISPRi-mediated silencing of >1,000 transcriptional regulators expressed in single colorectal adenocarcinoma cells, followed by single-cell RNA-seq profiling at two timepoints, 1 day and 4 days, allowed reverse engineering the underlying tumor context-specific, causal regulatory network. Furthermore, the availability of experimentally derived, highly multiplexed gene reporter assays for each regulator, as identified by this analysis, allowed accurate assessment of differential protein activity following silencing of each regulator, thus providing proof-of-concept for generating comprehensive, tissue-specific networks of transcriptional and post-translational interactions. Analysis of this causal network allowed elucidation of complex autoregulatory mechanisms that have eluded previous computational approaches and supported systematic elucidation of cooperative mechanisms, where one regulatory protein can modulate the activity of another regulatory protein, as well as transcriptional mimicry, where one regulatory protein can phenocopy others.

systems biology↗

bioRxiv2021

PISCES: A pipeline for the Systematic, Protein Activity-based Analysis of Single Cell RNA Sequencing Data

While single-cell RNA sequencing provides a remarkable window on pathophysiologic tissue biology and heterogeneity, its high gene-dropout rate and low signal-to-noise ratio challenge quantitative analyses and mechanistic understanding. To address this issue, we developed PISCES, a platform for the network-based, single-cell analysis of mammalian tissue. PISCES accurately estimates the mechanistic contribution of regulatory and signaling proteins to cell state implementation and maintenance, based on the expression of their lineage-specific transcriptional targets, thus supporting discovery and visualization of Master Regulators of cell state and cell state transitions. Experimental validation assays, including by assessing concordance with antibody and CITE-Seq-based measurements, show significant improvement in the ability to identify rare subpopulations and to elucidate key lineage markers, compared to gene expression analysis. Systematic analysis of single cell profiles in the Human Protein Atlas (HPA) produced a comprehensive resource for human tissue studies, supporting fine-grain stratification of distinct cell states, molecular determinants, and surface markers.

systems biology↗

bioRxiv2020

Pancreatic Ductal Adenocarcinoma Comprises Coexisting Regulatory States with both Common and Distinct Dependencies

Despite extensive efforts, reproducible assessment of pancreatic ductal adenocarcinoma (PDA) heterogeneity and plasticity at the single cell level remains elusive. Systematic, network-based analysis of regulatory protein activity in single cells identified three PDA Developmental Lineages (PDLs), coexisting in virtually all tumors, whose transcriptional states are mechanistically driven by aberrant activation of Master Regulator (MR) proteins associated with gastrointestinal lineages (GLS state), morphogen and EMT pathways (MOS state), and acinar-to-ductal metaplasia (ALS state), respectively. Each PDL is further subdivided into sub-states characterized by low vs. high MAPK pathway activity. This taxonomy was remarkably conserved across multiple cohorts, cell lines, and PDX models, and harmonized with bulk profile analyses. Cross-state plasticity and MR essentiality was confirmed by barcode-based lineage tracing and CRISPR/Cas9 assays, respectively, while MR ectopic expression induced PDL transdifferentiation. Together these data provide a mechanistic foundation for PDA heterogeneity and a roadmap for targeting PDA cellular subtypes.

cancer biology↗

bioRxiv2019

High-Throughput Translational Profiling with riboPLATE-seq

Protein synthesis is dysregulated in many diseases, but we lack a systems-level picture of how signaling molecules and RNA binding proteins interact with the translational machinery, largely due to technological limitations. Here we present riboPLATE-seq, a scalable method for generating paired libraries of ribosome-associated and total mRNA. As an extension of the PLATE-seq protocol, riboPLATE-seq utilizes barcoded primers for pooled library preparation, but additionally leverages rRNA immunoprecipitation on whole polysomes to measure ribosome association (RA). We compare RA to its analogue in ribosome profiling and RNA sequencing, translation efficiency, and demonstrate both the performance of riboPLATE-seq and its utility in detecting translational alterations induced by specific inhibitors of protein kinases.

systems biology↗