Prognostic Value of Germline Copy Number Variants and Environmental Exposures in Non-small Cell Lung Cancer

Germline copy number variant (gCNV) has been studied as a genetic determinant for prognosis of several types of cancer, but little is known about how it affects non-small cell lung cancer (NSCLC) prognosis. We aimed to develop a prognostic nomogram for NSCLC based on gCNVs. Promising gCNVs that are associated with overall survival (OS) of NSCLC were sorted by analyzing the TCGA data and were validated in a small Chinese population. Then the successfully verified gCNVs were determined in a training cohort (n = 570) to develop a prognostic nomogram, and in a validation cohort (n = 465) to validate the nomogram. Thirty-five OS-related gCNVs were sorted and were reduced to 15 predictors by the Lasso regression analysis. Of them, only CNVR395.1 and CNVR2239.1 were confirmed to be associated with OS of NSCLC in the Chinese population. High polygenic risk score (PRS), which was calculated by the hazard effects of CNVR395.1 and CNVR2239.1, exerted a significantly higher death rate in the training cohort (HR = 1.41, 95%CI: 1.16–1.74) and validation cohort (HR = 1.42, 95%CI: 1.13–1.77) than low PRS. The nomogram incorporating PRS and surrounding factors, achieved admissible concordance indexes of 0.678 (95%CI: 0.664–0.693) and 0.686 (95%CI: 0.670–0.702) in predicting OS in the training and validation cohorts, respectively, and had well-fitted calibration curves. Moreover, an interaction between PRS and asbestos exposure was observed on affecting OS (Pinteraction = 0.042). Our analysis developed a nomogram that achieved an admissible prediction of NSCLC survival, which would be beneficial to the personalized intervention of NSCLC.

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CT-Based Sarcopenic Nomogram for Predicting Progressive Disease in Advanced Non-Small-Cell Lung Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.643941 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaoping Yi ◽

Qiurong Chen ◽

Jingying Yang ◽

Dengke Jiang ◽

Liping Zhu ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Progressive Disease ◽

Validation Cohort ◽

Small Cell ◽

Small Cell Lung ◽

Skeletal Muscle Index ◽

Training Cohort ◽

Platinum Based Chemotherapy

BackgroundIt is prudent to identify the risk for progressive disease (PD) in patients with non-small-cell lung cancer (NSCLC) who undergo platinum-based chemotherapy. The present study aimed to develop a CT imaging-based sarcopenic nomogram for predicting the risk of PD prior to chemotherapy treatment.MethodsWe retrospectively enrolled patients with NSCLC who underwent platinum-based chemotherapy. Imaging-based body composition parameters such as skeletal muscle index (SMI) for assessment of sarcopenia were obtained from pre-chemotherapy chest CT images at the level of the eleventh thoracic vertebral body (T11). Sarcopenic nomogram was constructed using multivariate logistic regression and performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve.ResultsSixty (14.7%) of the 408 patients in the study cohort developed PD during chemotherapy. The prediction nomogram for developing PD achieved a moderate efficiency with an area under the curve (AUC) of 0.75 (95% CI: 0.69-0.80) for the training cohort, and 0.76 (95%CI: 0.68-0.84) for the validation cohort, as well as a good performance of consistence (bootstrap for training cohort: 0.75 ± 0.02; validation cohort: 0.74 ± 0.06). Favorable clinical application was observed in the decision curve analysis.ConclusionOur CT-based sarcopenic nomogram showed the potential for an individualized prediction of progression for patients with NSCLC receiving platinum-based chemotherapy.

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Development and Validation of a Nomogram Prognostic Model for Resected Limited-Stage Small Cell Lung Cancer Patients

Annals of Surgical Oncology ◽

10.1245/s10434-020-09552-w ◽

2021 ◽

Author(s):

Qingpeng Zeng ◽

Jiagen Li ◽

Fengwei Tan ◽

Nan Sun ◽

Yousheng Mao ◽

...

Keyword(s):

Lung Cancer ◽

Prognostic Factors ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Calibration Curve ◽

Validation Cohort ◽

Small Cell ◽

Small Cell Lung ◽

Training Cohort ◽

Limited Stage

Abstract Background In this study, we developed and validated nomograms for predicting the survival in surgically resected limited-stage small cell lung cancer (SCLC) patients. Methods The SCLC patients extracted from the Surveillance, Epidemiology, and End Results database between 2000 and 2014 were reviewed. Significant prognostic factors were identified and integrated to develop the nomogram using multivariable Cox regression. The model was then validated internally by bootstrap resampling, and externally using an independent SCLC cohort diagnosed between 2000 and 2015 at our institution. The prognostic performance was measured by the concordance index (C-index) and calibration curve. Results A total of 1006 resected limited-stage SCLC patients were included in the training cohort. Overall, 444 cases from our institution constituted the validation cohort. Seven prognostic factors were identified and entered into the nomogram construction. The C-indexes of this model in the training cohort were 0.723, 0.722, and 0.746 for predicting 1-, 3-, and 5-year overall survival (OS), respectively, and 0.816, 0.710, and 0.693, respectively, in the validation cohort. The calibration curve showed optimal agreement between nomogram-predicted survival and actual observed survival. Additionally, significant distinctions in survival curves between different risk groups stratified by prognostic scores were also observed. The proposed nomogram was then deployed into a website server for convenient application. Conclusions We developed and validated novel nomograms for individual prediction of survival for resected limited-stage SCLC patients. These models perform better than the previously widely used staging system and may offer clinicians instructions for strategy making and the design of clinical trials.

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Functional Polymorphisms on Chromosome 5p15.33 Disturb Telomere Biology and Confer the Risk of Non-Small Cell Lung Cancer in Chinese Population

SSRN Electronic Journal ◽

10.2139/ssrn.3255814 ◽

2018 ◽

Author(s):

Ying Li ◽

Cheng Xiang ◽

Na Shen ◽

Lingyan Deng ◽

Xia Luo ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Chinese Population ◽

Small Cell ◽

Small Cell Lung ◽

Functional Polymorphisms ◽

Telomere Biology

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Circulating tumor cell copy-number heterogeneity in ALK-rearranged non-small-cell lung cancer resistant to ALK inhibitors

npj Precision Oncology ◽

10.1038/s41698-021-00203-1 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Marianne Oulhen ◽

Patrycja Pawlikowska ◽

Tala Tayoun ◽

Marianna Garonzi ◽

Genny Buson ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Copy Number ◽

Epithelial To Mesenchymal Transition ◽

Kinase Inhibitors ◽

Small Cell ◽

Small Cell Lung ◽

Mesenchymal Transition ◽

Anaplastic Lymphoma

AbstractGatekeeper mutations are identified in only 50% of the cases at resistance to Anaplastic Lymphoma Kinase (ALK)-tyrosine kinase inhibitors (TKIs). Circulating tumor cells (CTCs) are relevant tools to identify additional resistance mechanisms and can be sequenced at the single-cell level. Here, we provide in-depth investigation of copy number alteration (CNA) heterogeneity in phenotypically characterized CTCs at resistance to ALK-TKIs in ALK-positive non-small cell lung cancer. Single CTC isolation and phenotyping were performed by DEPArray or fluorescence-activated cell sorting following enrichment and immunofluorescence staining (ALK/cytokeratins/CD45/Hoechst). CNA heterogeneity was evaluated in six ALK-rearranged patients harboring ≥ 10 CTCs/20 mL blood at resistance to 1st and 3rd ALK-TKIs and one presented gatekeeper mutations. Out of 82 CTCs isolated by FACS, 30 (37%) were ALK+/cytokeratins-, 46 (56%) ALK-/cytokeratins+ and 4 (5%) ALK+/cytokeratins+. Sequencing of 43 CTCs showed highly altered CNA profiles and high levels of chromosomal instability (CIN). Half of CTCs displayed a ploidy >2n and 32% experienced whole-genome doubling. Hierarchical clustering showed significant intra-patient and wide inter-patient CTC diversity. Classification of 121 oncogenic drivers revealed the predominant activation of cell cycle and DNA repair pathways and of RTK/RAS and PI3K to a lower frequency. CTCs showed wide CNA heterogeneity and elevated CIN at resistance to ALK-TKIs. The emergence of epithelial ALK-negative CTCs may drive resistance through activation of bypass signaling pathways, while ALK-rearranged CTCs showed epithelial-to-mesenchymal transition characteristics potentially contributing to ALK-TKI resistance. Comprehensive analysis of CTCs could be of great help to clinicians for precision medicine and resistance to ALK-targeted therapies.

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