Dataset Information

Molecular profiling of non-small cell lung cancer.

ABSTRACT: Lung cancer is generally treated with conventional therapies, including chemotherapy and radiation. These methods, however, are not specific to cancer cells and instead attack every cell present, including normal cells. Personalized therapies provide more efficient treatment options as they target the individual's genetic makeup. The goal of this study was to identify the frequency of causal genetic mutations across a variety of lung cancer subtypes in the earlier stages. 833 samples of non-small cell lung cancer from 799 patients who received resection of their lung cancer, were selected for molecular analysis of six known mutations, including EGFR, KRAS, BRAF, PIK3CA, HER2 and ALK. A SNaPshot assay was used for point mutations and fragment analysis searched for insertions and deletions. ALK was evaluated by IHC +/- FISH. Statistical analysis was performed to determine correlations between molecular and clinical/pathological patient data. None of the tested variants were identified in most (66.15%) of cases. The observed frequencies among the total samples vs. only the adenocarcinoma cases were notable different, with the highest frequency being the KRAS mutation (24.49% vs. 35.55%), followed by EGFR (6.96% vs. 10.23%), PIK3CA (1.20% vs. 0.9%), BRAF (1.08% vs. 1.62%), ALK (0.12% vs. 0.18%), while the lowest was the HER2 mutation (0% for both). The statistical analysis yielded correlations between presence of a mutation with gender, cancer type, vascular invasion and smoking history. The outcome of this study will provide data that helps stratify patient prognosis and supports development of more precise treatments, resulting in improved outcomes for future lung cancer patients.

SUBMITTER: Forsythe ML

PROVIDER: S-EPMC7406040 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Molecular profiling of non-small cell lung cancer.

Forsythe Marika L ML Alwithenani Akram A Bethune Drew D Castonguay Mathieu M Drucker Arik A Flowerdew Gordon G French Daniel D Fris John J Greer Wenda W Henteleff Harry H MacNeil Mary M Marignani Paola P Morzycki Wojciech W Plourde Madelaine M Snow Stephanie S Xu Zhaolin Z

PloS one 20200805 8

Lung cancer is generally treated with conventional therapies, including chemotherapy and radiation. These methods, however, are not specific to cancer cells and instead attack every cell present, including normal cells. Personalized therapies provide more efficient treatment options as they target the individual's genetic makeup. The goal of this study was to identify the frequency of causal genetic mutations across a variety of lung cancer subtypes in the earlier stages. 833 samples of non-smal ...[more]

PMID: 32756609

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Project description:Molecular profiling of NSCLC is essential for optimising treatment decisions, but often incomplete. We assessed the efficacy of protocolised molecular profiling in the current standard-of-care (SoC) in a prospective observational study in the Netherlands and measured the effect of providing standardised diagnostic procedures. We also explored the potential of plasma-based molecular profiling in the primary diagnostic setting. This multi-centre prospective study was designed to explore the performance of current clinical practice during the run-in phase using local SoC tissue profiling procedures. The subsequent phase was designed to investigate the extent to which comprehensive molecular profiling (CMP) can be maximized by protocolising tumour profiling. Successful molecular profiling was defined as completion of at least EGFR and ALK testing. Additionally, PD-L1 tumour proportions scores were explored. Lastly, the additional value of centralised plasma-based testing for EGFR and KRAS mutations using droplet digital PCR was evaluated. Total accrual was 878 patients, 22.0% had squamous cell carcinoma and 78.0% had non-squamous NSCLC. Stage I-III was seen in 54.0%, stage IV in 46.0%. Profiling of EGFR and ALK was performed in 69.9% of 136 patients included in the run-in phase, significantly more than real-world data estimates of 55% (p<0.001). Protocolised molecular profiling increased the rate to 77.0% (p = 0.049). EGFR and ALK profiling rates increased from 77.9% to 82.1% in non-squamous NSCLC and from 43.8% to 57.5% in squamous NSCLC. Plasma-based testing was feasible in 98.4% and identified oncogenic driver mutations in 7.1% of patients for whom tissue profiling was unfeasible. This study shows a high success rate of tissue-based molecular profiling that was significantly improved by a protocolised approach. Tissue-based profiling remains unfeasible for a substantial proportion of patients. Combined analysis of tumour tissue and circulating tumour DNA is a promising approach to allow adequate molecular profiling of more patients.

Project description:BackgroundLung cancer, one of the most common malignant tumors, exhibits high inter- and intra-tumor heterogeneity which contributes significantly to treatment resistance and failure. Single-cell RNA sequencing (scRNA-seq) has been widely used to dissect the cellular composition and characterize the molecular properties of cancer cells and their tumor microenvironment in lung cancer. However, the transcriptomic heterogeneity among various cancer cells in non-small cell lung cancer (NSCLC) warrants further illustration.MethodsTo comprehensively analyze the molecular heterogeneity of NSCLC, we performed high-precision single-cell RNA-seq analyses on 7364 individual cells from tumor tissues and matched normal tissues from 19 primary lung cancer patients and 1 pulmonary chondroid hamartoma patient.ResultsIn 6 of 16 patients sequenced, we identified a significant proportion of cancer cells simultaneously expressing classical marker genes for two or even three histologic subtypes of NSCLC-adenocarcinoma (ADC), squamous cell carcinoma (SCC), and neuroendocrine tumor (NET) in the same individual cell, which we defined as mixed-lineage tumor cells; this was verified by both co-immunostaining and RNA in situ hybridization. These data suggest that mixed-lineage tumor cells are highly plastic with mixed features of different types of NSCLC. Both copy number variation (CNV) patterns and mitochondrial mutations clearly showed that the mixed-lineage and single-lineage tumor cells from the same patient had common tumor ancestors rather than different origins. Moreover, we revealed that patients with high mixed-lineage features of different cancer subtypes had worse survival than patients with low mixed-lineage features, indicating that mixed-lineage tumor features were associated with poorer prognosis. In addition, gene signatures specific to mixed-lineage tumor cells were identified, including AKR1B1. Gene knockdown and small molecule inhibition of AKR1B1 can significantly decrease cell proliferation and promote cell apoptosis, suggesting that AKR1B1 plays an important role in tumorigenesis and can serve as a candidate target for tumor therapy of NSCLC patients with mixed-lineage tumor features.ConclusionsIn summary, our work provides novel insights into the tumor heterogeneity of NSCLC in terms of the identification of prevalent mixed-lineage subpopulations of cancer cells with combined signatures of SCC, ADC, and NET and offers clues for potential treatment strategies in these patients.

Project description:Current paradigms hold that lung carcinomas arise from pleuripotent stem cells capable of differentiation into one or several histological types. These paradigms suggest lung tumor cell ontogeny is determined by consequences of gene expression that recapitulate events important in embryonic lung development. Using oligonucleotide microarrays, we acquired gene profiles from 32 microdissected non-small-cell lung tumors. We determined the 100 top-ranked marker genes for adenocarcinoma, squamous cell, large cell, and carcinoid using nearest neighbor analysis. Results were validated by immunostaining for 11 selected proteins using a tissue microarray representing 80 tumors. Gene expression data of lung development were accessed from a publicly available dataset generated with the murine Mu11k genome microarray. Self-organized mapping identified two temporally distinct clusters of murine orthologues. Supervised clustering of lung development data showed large-cell carcinoma gene orthologues were in a cluster expressed in pseudoglandular and canalicular stages whereas adenocarcinoma homologues were predominantly in a cluster expressed later in the terminal sac and alveolar stages of murine lung development. Representative large-cell genes (E2F3, MYBL2, HDAC2, CDK4, PCNA) are expressed in the nucleus and are associated with cell cycle and proliferation. In contrast, adenocarcinoma genes are associated with lung-specific transcription pathways (SFTPB, TTF-1), cell adhesion, and signal transduction. In sum, non-small-cell lung tumors histology gene profiles suggest mechanisms relevant to ontogeny and clinical course. Adenocarcinoma genes are associated with differentiation and glandular formation whereas large-cell genes are associated with proliferation and differentiation arrest. The identification of developmentally regulated pathways active in tumorigenesis provides insights into lung carcinogenesis and suggests early steps may differ according to the eventual tumor morphology.

Dataset Information

Molecular profiling of non-small cell lung cancer.

Publications

Molecular profiling of non-small cell lung cancer.

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