Biology subjects

Verschuren, E. W.

Publications and source records attributed to Verschuren, E. W..

5 recordsLinked to original sources

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) 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. MethodsParticipants 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. ResultsA 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 bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs 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 ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2022

Development of an adenosquamous carcinoma histopathology-selective lung cancer graft model

Preclinical tumor models with native tissue microenvironments provide essential tools to understand how heterogeneous tumor phenotypes relate to drug response. Here, we present syngeneic graft models of aggressive, metastasis-prone histopathology-specific NSCLC tumor types driven by KRAS mutation and loss of LKB1 (KL): adenosquamous carcinoma (ASC) and adenocarcinoma (AC). We show that subcutaneous injection of primary KL-ASC cells results in squamous cell carcinoma (SCC) tumors with high levels of stromal infiltrates, lacking the source heterogeneous histotype. Despite forming subcutaneous tumors, intravenously injected KL-AC cells were unable to form lung tumors. In contrast, intravenous injection of KL-ASC cells leads to their lung re-colonization and lesions recapitulating the mixed AC and SCC histopathology, tumor immune suppressive microenvironment and oncogenic signaling profile of source tumors, demonstrating histopathology-selective phenotypic dominance over genetic drivers. Pan-ERBB inhibition increased survival, while selective ERBB1/EGFR inhibition did not, suggesting a role of ERBB network crosstalk in resistance to ERBB1/EGFR. This immunocompetent NSCLC lung colonization model hence phenocopies key properties of the metastasis-prone ASC histopathology, and serves as a preclinical model to dissect therapy responses and metastasis-associated processes.

cancer biology↗

bioRxiv2021

PI3Kβ inhibition restores ALK inhibitor sensitivity in ALK-rearranged lung cancer

For non-small cell lung cancer (NSCLC) patients with ALK-rearranged tumors, treatment with ALK inhibitors can improve outcomes. However, clinical resistance typically develops over time, and in the majority of cases resistance mechanisms are ALK-independent. We generated tumor cell cultures from multiple regions of an ALK-rearranged clinical tumor specimen, and deployed functional drug screens to identify modulators of resistance to ALK inhibitors. This identified a role for PI3K{beta} and EGFR in regulating resistance to ALK inhibition. Furthermore, inhibition of ALK elicited activation of EGFR, and inhibition of PI3K{beta} rescued EGFR-mediated ALK inhibitor resistance. In ALK-rearranged primary cultures, cell lines and in vivo xenograft models, combined inhibition of ALK and PI3K{beta} prevented compensatory MAPK and PI3K-AKT pathway reactivation and selectively targeted the cancer cells. The combinatorial effect was seen even in the background of TP53 mutations and in epithelial-mesenchymal transformed cells. In conclusion, combinatorial ALK and PI3K{beta} inhibitor treatment carries promise as a treatment for ALK-rearranged NSCLC.

cancer biology↗

bioRxiv2020

The role of SOX9 in non-small cell lung cancer progression is histopathology-selective.

The transcription factor SOX9 is a key regulator of multiple developmental processes, and is frequently re-expressed in non-small cell lung cancer (NSCLC). Its precise role in the progression of NSCLC histopathologies has however remained elusive. We show that SOX9 expression relates to poor outcome and invasive histopathology in human adenocarcinomas, and is absent in murine early minimally invasive and human in situ adenocarcinoma. Interestingly, despite wide SOX9 expression across advanced NSCLC histotypes, its genetic deletion in the murine KrasG12D;Lkb1-/- model selectively disrupted only the growth of papillary NSCLC, without affecting the initiation of precursor lesions or growth of mucinous or squamous tissue. Spatial tissue phenotyping indicated a requirement of SOX9 expression for the progression of surfactant protein C-expressing progenitor cells, which gave rise to papillary tumours. Intriguingly, while SOX9 expression was dispensable for squamous tissue formation, its loss in fact led to enhanced squamous tumour metastasis, which was associated with altered collagen IV deposition in the basement membrane. Our work therefore demonstrates histopathology-selective roles for SOX9 in NSCLC progression, namely a requirement for papillary adenocarcinoma progression, but opposing metastasis-suppressing function in squamous histotype tissue. This attests to a pleiotropic SOX9 function, linked to the cell of origin and microenvironmental tissue contexts.

cancer biology↗

bioRxiv2020

Functional diagnostics using fresh uncultured lung tumor cells to guide personalized treatments

Functional profiling of a cancer patients tumor cells holds potential to tailor personalized cancer treatment. Here we report the utility of Fresh Uncultured Tumor-derived EpCAM+ epithelial Cells (FUTC) for ex vivo drug response interrogation. Analysis of murine Kras mutant FUTCs demonstrated pharmacological and adaptive signaling profiles comparable to subtype-matched cultured cells. Applying FUTC profiling on non-small cell lung cancer patient samples, we generated robust drug response data in 18 of 19 cases, where the cells exhibited targeted drug sensitivities corresponding to their oncogenic drivers. In one of these cases, an EGFR mutant lung adenocarcinoma patient refractory to osimertinib, FUTC profiling was used to guide compassionate treatment. FUTC profiling identified selective sensitivity to disulfiram and the combination of carboplatin plus etoposide and the patient received substantial clinical benefit from the treatment with these agents. We conclude that FUTC profiling provides a robust, rapid, and actionable assessment of personalized cancer treatment options.

cancer biology↗