Lung cancer is the leading cause of cancer-related human death. It is a heterogeneous disease, classified in two main histotypes, small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC), which is further subdivided into squamous-cell carcinoma (SCC) and adenocarcinoma (AD) subtypes. Despite the introduction of innovative therapeutics, mainly designed to specifically treat AD patients, the prognosis of lung cancer remains poor. In particular, available treatments for SCLC and SCC patients are currently limited to platinum-based chemotherapy and immune checkpoint inhibitors. In this work, we used an integrative approach to identify novel vulnerabilities in lung cancer. First, we compared the data from a CRISPR/Cas9 dependency screening performed in our laboratory with Cancer Dependency Map Project data, essentiality comprising information on 73 lung cancer cell lines. Next, to identify relevant therapeutic targets, we integrated dependency data with pharmacological data and TCGA gene expression information. Through this analysis, we identified CSNK1A1, KDM2A, and LTB4R2 as relevant druggable essentiality genes in lung cancer. We validated the antiproliferative effect of genetic or pharmacological inhibition of these genes in two lung cancer cell lines. Overall, our results identified new vulnerabilities associated with different lung cancer histotypes, laying the basis for the development of new therapeutic strategies.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305418 | PMC |
http://dx.doi.org/10.3390/cancers13143477 | DOI Listing |
Genet Epidemiol
January 2025
Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C).
View Article and Find Full Text PDFCancer Med
January 2025
The Huntsman Cancer Institute at the University of Utah, Salt Lake City, Utah, USA.
Introduction: The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).
Methods: This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively.
Explor Target Antitumor Ther
December 2024
Division of Hematology and Medical Oncology, Mayo Clinic, Jacksonville, FL 32224, US.
The emergence of immunotherapy has ushered in a new era in the management of non-small cell lung cancer (NSCLC). Various immune check point inhibitors have demonstrated significant benefit in the management of locally advanced NSCLC that are treated with either surgery or concurrent chemoradiation. We provide a comprehensive and up-to-date review of data from key studies, discuss the challenging clinical issue regarding the timing and duration of immunotherapy in patients undergoing surgery, and highlight the unmet needs and future directions of immunotherapy in NSCLC.
View Article and Find Full Text PDFExplor Target Antitumor Ther
December 2024
Department of Thoracic Oncology, Georges Pompidou European Hospital, Paris Cité University, AP-HP, CARPEM, 75015 Paris, France.
Aim: Immune checkpoint inhibitors improved the survival of advanced non-small cell lung cancer. However, only 20% of patients respond to these treatments and the search for predictive biomarkers of response is still topical. The objective of this work is to analyze the anti-PD-1 monotherapy benefit based on genetic alterations diagnosed by next generation sequencing (NGS), in advanced non-small cell lung cancer.
View Article and Find Full Text PDFExplor Target Antitumor Ther
November 2024
Division of Pulmonary, Critical Care, and Sleep Disorders Medicine, Department of Medicine, University of Louisville School of Medicine, Louisville, KY 40202, USA.
There has been a rapid expansion of immunotherapy options for non-small cell lung cancer (NSCLC) over the past two decades, particularly with the advent of immune checkpoint inhibitors. Despite the emerging role of immunotherapy in adjuvant and neoadjuvant settings though, relatively few patients will respond to immunotherapy which can be problematic due to expense and toxicity; thus, the development of biomarkers capable of predicting immunotherapeutic response is imperative. Due to the promise of a noninvasive, personalized approach capable of providing comprehensive, real-time monitoring of tumor heterogeneity and evolution, there has been wide interest in the concept of using circulating tumor DNA (ctDNA) to predict treatment response.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!