A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

ABHD6 suppresses colorectal cancer progression via AKT signaling pathway.

Colorectal cancer (CRC) continues to be a prevalent malignancy, posing a significant risk to human health. The involvement of alpha/beta hydrolase domain 6 (ABHD6), a serine hydrolase family member, in CRC development was suggested by our analysis of clinical data. However, the role of ABHD6 in CRC remains unclear. This study seeks to elucidate the clinical relevance, biological function, and potential molecular mechanisms of ABHD6 in CRC. We investigated the role of ABHD6 in clinical settings, conducting proliferation, migration, and cell cycle assays. To determine the influence of ABHD6 expression levels on Oxaliplatin sensitivity, we also performed apoptosis assays. RNA sequencing and KEGG analysis were utilized to uncover the potential molecular mechanisms of ABHD6. Furthermore, we validated its expression levels using Western blot and reactive oxygen species (ROS) detection assays. Our results demonstrated that ABHD6 expression in CRC tissues was notably lower compared to adjacent normal tissues. This low expression correlated with a poorer prognosis for CRC patients. Moreover, ABHD6 overexpression impeded CRC cell proliferation and migration while inducing G0/G1 cell cycle arrest. In vivo experiments revealed that downregulation of ABHD6 resulted in an increase in tumor weight and volume. Mechanistically, ABHD6 overexpression inhibited the activation of the AKT signaling pathway and decreased ROS levels in CRC cells, suggesting the role of ABHD6 in CRC progression via the AKT signaling pathway. Our findings demonstrate that ABHD6 functions as a tumor suppressor, primarily by inhibiting the AKT signaling pathway. This role establishes ABHD6 as a promising prognostic biomarker and a potential therapeutic target for CRC patients.