Multigene Mutation Profiling and Clinical Characteristics of Small-Cell Lung Cancer in Never-Smokers vs. Heavy Smokers (Geno1.3-CLICaP)

Cardona, Andrés Felipe; Rojas, Leonardo; Zatarain-Barrón, Zyanya Lucía; Ruíz-Patiño, Alejandro; Ricaurte, Luisa; Corrales, Luis; Martín, Claudio; Freitas, Helano; Lima, Vladmir Cláudio Cordeiro de; Rodríguez, July; Ávila, Jenny; Bravo, Melissa; Archila, Pilar; Carranza, Hernán; Vargas, Carlos; Otero, Jorge; Barrón, Feliciano; Karachaliou, Niki; Rosell, Rafael; Arrieta, Óscar

doi:10.3389/fonc.2019.00254

Cited by 24 publications

(32 citation statements)

References 38 publications

(40 reference statements)

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“…Additionally, we identified a previously reported relationship between SMAD4 and carboplatin. Mutations in the SMAD4 gene have been linked to resistance of platinum-based drugs like carboplatin 15 , 16 , and our data suggest that head and neck cancer patients on carboplatin stratified by pre-treatment SMAD4 expression have significantly differential survival between the strata (Fig. 3 D).…”

Section: Resultsmentioning

confidence: 62%

Identifying gene expression patterns associated with drug-specific survival in cancer patients

Neary

Zhou

Qiu

2021

Sci Rep

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The ability to predict the efficacy of cancer treatments is a longstanding goal of precision medicine that requires improved understanding of molecular interactions with drugs and the discovery of biomarkers of drug response. Identifying genes whose expression influences drug sensitivity can help address both of these needs, elucidating the molecular pathways involved in drug efficacy and providing potential ways to predict new patients’ response to available therapies. In this study, we integrated cancer type, drug treatment, and survival data with RNA-seq gene expression data from The Cancer Genome Atlas to identify genes and gene sets whose expression levels in patient tumor biopsies are associated with drug-specific patient survival using a log-rank test comparing survival of patients with low vs. high expression for each gene. This analysis was successful in identifying thousands of such gene–drug relationships across 20 drugs in 14 cancers, several of which have been previously implicated in the respective drug’s efficacy. We then clustered significant genes based on their expression patterns across patients and defined gene sets that are more robust predictors of patient outcome, many of which were significantly enriched for target genes of one or more transcription factors, indicating several upstream regulatory mechanisms that may be involved in drug efficacy. We identified a large number of genes and gene sets that were potentially useful as transcript-level biomarkers for predicting drug-specific patient survival outcome. Our gene sets were robust predictors of drug-specific survival and our results included both novel and previously reported findings, suggesting that the drug-specific survival marker genes reported herein warrant further investigation for insights into drug mechanisms and for validation as biomarkers to aid cancer therapy decisions.

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Section: Resultsmentioning

confidence: 62%

Identifying gene expression patterns associated with drug-specific survival in cancer patients

Neary

Zhou

Qiu

2021

Sci Rep

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“…In terms of clinical characteristics, several studies proposed that never-smoker SCLC was related to a female-gender predisposition. 33,34 In the study by Cardo et al the authors also found that SCLC patients with a smoking history presented with a higher incidence of brain metastasis, which might partly explain the poorer survival of smoker SCLC patients. 33 Overall, the mechanism behind the prognostic difference between smokers and never-smokers in SCLC still needs further investigation.…”

Section: Discussionmentioning

confidence: 96%

Prognostic value of pretreatment smoking status for small cell lung cancer: A meta‐analysis

Huang

Shi

2020

Thoracic Cancer

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Background Although tobacco exposure remains the most important risk factor of tumorigenesis of small cell lung cancer (SCLC), its prognostic value has failed to reach a consensus until now. Accordingly, we conducted a meta‐analysis to investigate the prognostic value of pretreatment smoking status (smokers vs. never‐smokers) in SCLC. Methods The four databases PubMed, Medline, Embase, and Cochrane library were searched to identify the relevant literature from the inception dates to 24 June 2020. The primary outcome was overall survival (OS), and the secondary endpoint was progression‐free survival (PFS). The hazard ratios (HRs) with 95% confidence intervals (CIs) were extracted to assess the relationship between pretreatment smoking status and patient survival. Sensitivity analysis was performed to assess the stability of the pooled results. Begg's funnel plot and Egger's test were applied to detect the publication bias. All statistical analyses were performed using RevMan V.5.3 and STATA version 15.0 software. Results A total of 27 studies involving 12 047 patients with SCLC (9137 smokers and 2910 never‐smokers) were included in this meta‐analysis. The results showed that smoking history was closely related to poorer survival outcome (OS: HR = 1.17, 95% CI: 1.12–1.23, P < 0.00001; I 2 = 0%; PFS: HR = 1.20, 95% CI: 1.06–1.35, P = 0.004; I 2 = 0%). Conclusions Smoking history should be considered as an independent poor prognostic factor for patients with SCLC. More large‐scale prospective studies are warranted to testify the prognostic value of pretreatment smoking status.

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“…However, the low frequency of clinically actionable driver mutations hinders the successful application of targeted therapies in SCLC. A difference in the mutational profile in SCLC according to the smoking status has also been reported (Cardona et al, 2019;Sun et al, 2015;Varghese et al, 2014). One study by Cardona et al demonstrated that EGFR, MET, and SMAD4 are more frequently mutated in never smokers, while RB1, CDKN2A, and CEBPA are more frequent in smokers (Cardona et al, 2019).…”

Section: Introductionmentioning

confidence: 95%

Genomic and pathological heterogeneity in clinically diagnosed small cell lung cancer in never/light smokers identifies therapeutically targetable alterations

et al. 2020

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Small‐cell lung cancer (SCLC) occurs infrequently in never/former light smokers. We sought to study this rare clinical subset through next‐generation sequencing (NGS) and by characterizing a representative patient‐derived model. We performed targeted NGS, as well as comprehensive pathological evaluation, in 11 never/former light smokers with clinically diagnosed SCLC. We established a patient‐derived model from one such patient (DFCI168) harboring an NRASQ61K mutation and characterized the sensitivity of this model to MEK and TORC1/2 inhibitors. Despite the clinical diagnosis of SCLC, the majority (8/11) of cases were either of nonpulmonary origin or of mixed histology and included atypical carcinoid (n = 1), mixed non‐small‐cell lung carcinoma and SCLC (n = 4), unspecified poorly differentiated carcinoma (n = 1), or small‐cell carcinoma from different origins (n = 2). RB1 and TP53 mutations were found in four and five cases, respectively. Predicted driver mutations were detected in EGFR (n = 2), NRAS (n = 1), KRAS (n = 1), BRCA1 (n = 1), and ATM (n = 1), and one case harbored a TMPRSS2‐ERG fusion. DFCI168 (NRASQ61K) exhibited marked sensitivity to MEK inhibitors in vitro and in vivo. The combination of MEK and mTORC1/2 inhibitors synergized to prevent compensatory mTOR activation, resulting in prolonged growth inhibition in this model and in three other NRAS mutant lung cancer cell lines. SCLC in never/former light smokers is rare and is potentially a distinct disease entity comprised of oncogenic driver mutation‐harboring carcinomas morphologically and/or clinically mimicking SCLC. Comprehensive pathologic review integrated with genomic profiling is critical in refining the diagnosis and in identifying potential therapeutic options.

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Multigene Mutation Profiling and Clinical Characteristics of Small-Cell Lung Cancer in Never-Smokers vs. Heavy Smokers (Geno1.3-CLICaP)

Cited by 24 publications

References 38 publications

Identifying gene expression patterns associated with drug-specific survival in cancer patients

Identifying gene expression patterns associated with drug-specific survival in cancer patients

Prognostic value of pretreatment smoking status for small cell lung cancer: A meta‐analysis

Genomic and pathological heterogeneity in clinically diagnosed small cell lung cancer in never/light smokers identifies therapeutically targetable alterations

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