Biology subjects

Rothberg, M.

Publications and source records attributed to Rothberg, M..

2 recordsLinked to original sources

bioRxiv2020

Phosphate dysregulation via the XPR1:KIDINS220 protein complex is a therapeutic vulnerability in ovarian cancer

Clinical outcomes for patients with ovarian and uterine cancers have not improved greatly in the past twenty years. To identify ovarian and uterine cancer vulnerabilities, we analyzed genome-scale CRISPR/ Cas9 loss-of-function screens across 739 human cancer cell lines. We found that many ovarian cancer cell lines overexpress the phosphate importer SLC34A2, which renders them sensitive to loss of the phosphate exporter XPR1. We extensively validated the XPR1 vulnerability in cancer cell lines and found that the XPR1 dependency was retained in vivo. Overexpression of SLC34A2 is frequently observed in tumor samples and is regulated by PAX8 -a transcription factor required for ovarian cancer survival. XPR1 overexpression and copy number amplifications are also frequently observed. Mechanistically, SLC34A2 overexpression and impaired phosphate efflux leads to the accumulation of intracellular phosphate and cell death. We further show that proper localization and phosphate efflux by XPR1 requires a novel binding partner, KIDINS220. Loss of either XPR1 or KIDINS220 results in acidic vacuolar structures which precede cell death. These data point to the XPR1:KIDINS220 complex - and phosphate dysregulation more broadly -as a therapeutic vulnerability in ovarian cancer.

cancer biology↗

bioRxiv2019

Multiplexed single-cell profiling of post-perturbation transcriptional responses to define cancer vulnerabilities and therapeutic mechanism of action

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate or the expression of a marker gene. Information-rich assays, such as gene-expression profiling, are generally not amenable to efficient profiling of a given perturbation across multiple cellular contexts. Here, we developed MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines, and combine it with Cell Hashing to further multiplex additional experimental conditions, such as multiple post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and can be used to predict long-term cell viability from short-term transcriptional responses to treatment.

cancer biology↗