Characterizing suicidal ideation, suicidal behaviors, and service utilization among unhoused individuals using a health information exchange.

INTRODUCTION: Unhoused individuals have high rates of suicidal ideation (SI) and suicidal behaviors (SB), but few have studied the relative timing of homelessness and SI/SB. Our study examines the potential to use state-wide electronic health record data from Rhode Island's health information exchange (HIE) to identify temporal relationships, service utilization, and associations of SI/SB among unhoused individuals. METHODS: We use timestamped HIE data for 5368 unhoused patients to analyze service utilization and the relative timing of homelessness versus SI/SB onset. Multivariable models identified associations of SI/SB, hospitalization, and repeat acute care utilization within 30 days from clinical features representing 10,000+ diagnoses captured within the HIE. RESULTS: The onset of SI typically precedes homelessness onset, while the onset of SB typically follows. Weekly rates of suicide-related service utilization increased over 25 times the baseline rate during the week before and after homelessness onset. Over 50% of encounters involving SI/SB result in hospitalization. Of those engaging in acute care for suicide-related reasons, we found high rates of repeat acute care encounters. CONCLUSION: HIEs are a particularly valuable resource for understudied populations. Our study demonstrates how longitudinal, multi-institutional data from an HIE can be used to characterize temporal associations, service utilization, and clinical associations of SI and behaviors among a vulnerable population at scale. Increasing access to services that address co-occurring SI/SB, mental health, and substance use is needed.

Developing SHP2-based combination therapy for KRAS-amplified cancer.

Gastroesophageal adenocarcinomas (GEAs) harbor recurrent amplification of KRAS, leading to marked overexpression of WT KRAS protein. We previously demonstrated that SHP2 phosphatase, which acts to promote KRAS and downstream MAPK pathway activation, is a target in these tumors when combined with MEK inhibition. We hypothesized that SHP2 inhibitors may serve as a foundation for developing novel combination inhibitor strategies for therapy of KRAS-amplified GEA, including with targets outside the MAPK pathway. Here, we explore potential targets to effectively augment the efficacy of SHP2 inhibition, starting with genome-wide CRISPR screens in KRAS-amplified GEA cell lines with and without SHP2 inhibition. We identify candidate targets within the MAPK pathway and among upstream RTKs that may enhance SHP2 efficacy in KRAS-amplified GEA. Additional in vitro and in vivo experiments demonstrated the potent cytotoxicity of pan-ERBB kinase inhibitions in vitro and in vivo. Furthermore, beyond targets within the MAPK pathway, we demonstrate that inhibition of CDK4/6 combines potently with SHP2 inhibition in KRAS-amplified GEA, with greater efficacy of this combination in KRAS-amplified, compared with KRAS-mutant, tumors. These results suggest therapeutic combinations for clinical study in KRAS-amplified GEAs.

Reprogramming of the esophageal squamous carcinoma epigenome by SOX2 promotes ADAR1 dependence.

Esophageal squamous cell carcinomas (ESCCs) harbor recurrent chromosome 3q amplifications that target the transcription factor SOX2. Beyond its role as an oncogene in ESCC, SOX2 acts in development of the squamous esophagus and maintenance of adult esophageal precursor cells. To compare Sox2 activity in normal and malignant tissue, we developed engineered murine esophageal organoids spanning normal esophagus to Sox2-induced squamous cell carcinoma and mapped Sox2 binding and the epigenetic and transcriptional landscape with evolution from normal to cancer. While oncogenic Sox2 largely maintains actions observed in normal tissue, Sox2 overexpression with p53 and p16 inactivation promotes chromatin remodeling and evolution of the Sox2 cistrome. With Klf5, oncogenic Sox2 acquires new binding sites and enhances activity of oncogenes such as Stat3. Moreover, oncogenic Sox2 activates endogenous retroviruses, inducing expression of double-stranded RNA and dependence on the RNA editing enzyme ADAR1. These data reveal SOX2 functions in ESCC, defining targetable vulnerabilities.

Genome-Wide Interrogation of Human Cancers Identifies EGLN1 Dependency in Clear Cell Ovarian Cancers.

We hypothesized that candidate dependencies for which there are small molecules that are either approved or in advanced development for a nononcology indication may represent potential therapeutic targets. To test this hypothesis, we performed genome-scale loss-of-function screens in hundreds of cancer cell lines. We found that knockout of EGLN1, which encodes prolyl hydroxylase domain-containing protein 2 (PHD2), reduced the proliferation of a subset of clear cell ovarian cancer cell lines in vitro. EGLN1-dependent cells exhibited sensitivity to the pan-EGLN inhibitor FG-4592. The response to FG-4592 was reversed by deletion of HIF1A, demonstrating that EGLN1 dependency was related to negative regulation of HIF1A. We also found that ovarian clear cell tumors susceptible to both genetic and pharmacologic inhibition of EGLN1 required intact HIF1A. Collectively, these observations identify EGLN1 as a cancer target with therapeutic potential. SIGNIFICANCE: These findings reveal a differential dependency of clear cell ovarian cancers on EGLN1, thus identifying EGLN1 as a potential therapeutic target in clear cell ovarian cancer patients.

Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration.

The availability of multiple datasets comprising genome-scale RNAi viability screens in hundreds of diverse cancer cell lines presents new opportunities for understanding cancer vulnerabilities. Integrated analyses of these data to assess differential dependency across genes and cell lines are challenging due to confounding factors such as batch effects and variable screen quality, as well as difficulty assessing gene dependency on an absolute scale. To address these issues, we incorporated cell line screen-quality parameters and hierarchical Bayesian inference into DEMETER2, an analytical framework for analyzing RNAi screens ( https://depmap.org/R2-D2 ). This model substantially improves estimates of gene dependency across a range of performance measures, including identification of gold-standard essential genes and agreement with CRISPR/Cas9-based viability screens. It also allows us to integrate information across three large RNAi screening datasets, providing a unified resource representing the most extensive compilation of cancer cell line genetic dependencies to date.