Whole-genome analysis of a patient with early-stage small-cell lung cancer

Jin, Han; Ys, Lee; Bc, Kim; Gk, Lee; S, Lee; Eh, Kim; Hm, Kim; Bhak, Jong

doi:10.1038/tpj.2014.17

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…There was no difference in protein‐altering SNV and mutation rate between NAC and CTN group. In the present study, in addition to the recurrent deletion of regions harboring FHIT and RB1 , amplifications of MYCL1 and SOX2 were confirmed 33,34 . Xiaohui Ni et al confirmed that circulating tumor cells (CTCs) from an individual patient exhibited reproducible CNV patterns, 35 and CNV patterns remained constant during treatment.…”

Section: Discussionsupporting

confidence: 73%

“…In the present study, in addition to the recurrent deletion of regions harboring FHIT and RB1 , amplifications of MYCL1 and SOX2 were confirmed. 33 , 34 Xiaohui Ni et al confirmed that circulating tumor cells (CTCs) from an individual patient exhibited reproducible CNV patterns, 35 and CNV patterns remained constant during treatment. Different from the study by Xiaohui Ni, NAC group demonstrated more deletions than CTN group, especially on 5q31.3 and 17p13.1.…”

Section: Discussionmentioning

confidence: 97%

“…In the present study, in addition to the recurrent deletion of regions harboring FHIT and RB1, amplifications of MYCL1 and SOX2 were confirmed. 33,34 Mutation signature analysis divided patients into two groups. Patients in PR and SD groups had a different mutation signatures from those CTN patients, whose signatures were more similar to patients with disease progression.…”

Section: Discussionmentioning

confidence: 99%

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Whole exome analysis reveals the genomic profiling related to chemo‐resistance in Chinese population with limited‐disease small cell lung cancer

Zhao

et al. 2022

Cancer Medicine

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Purpose The mechanism of chemo‐resistance in small cell lung cancer (SCLC) is unclear. This study aims to explore the resistance‐related genomic profiles of residual tumors after neo‐adjuvant chemotherapy (NAC) in SCLC through the whole‐exome sequencing (WES). Experimental design A total of 416 limited diseases (LD) SCLC patients underwent surgery were retrospectively analyzed, of which 40 patients received NAC. Then we selected 29 patients undergoing NAC (n = 19) and chemotherapy naïve (CTN, n = 10) to perform WES sequence with formalin‐fixed paraffin‐embedded samples including tumor and paired para‐tumor. Results In total, single nucleotide variation and mutation rate were similar between NAC and CTN groups. The mutation signatures were significantly discrepant between NAC and CTN groups, as well as among patients with partial response (PR), stable disease (SD), and progressive disease. There were more copy number variation deletions in NAC group compared with CTN group. The inactivation of TP53 and RB1 were the most significantly events in both NAC and CTN groups. RB1 nonsense mutations were recurrent in NAC group (9/19 vs. 0/9, 47.4% vs. 0%) with favorable survival, while the frame‐shift deletions were frequent in CTN group (3/9 vs. 3/19, 33.3% vs.15.8%). Integrated function enrichment revealed that the frequently mutant genes were involved in cell cycle, metabolic reprogramming, and oncogenic signaling pathways in NAC group, such as BTG2 pathway, glycolysis in senescence and P53 pathway. A total of 27 genes presented frequently mutant in NAC group and might played a positive role in drug resistance. Multiple genes including BRINP3, MYH6, ST18, and PCHD15, which were associated with prognosis, occurred mutant frequently in PR and SD groups. Conclusion Residual tumors after neo‐adjuvant therapy exhibited different mutation signature spectrum. Multiple genes including RB1 nonsense mutations, BRINP3, MYH6, ST18, and PCHD15 were with frequent mutation in residual tumors, which might participate chemo‐resistance and influenced the prognosis in patients with limited disease SCLC.

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Section: Discussionsupporting

confidence: 73%

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

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Whole exome analysis reveals the genomic profiling related to chemo‐resistance in Chinese population with limited‐disease small cell lung cancer

Zhao

et al. 2022

Cancer Medicine

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“…As the sequencing technology advances and the costs fall down, whole-genome sequencing (WGS) is turning to be a cost-effective way to obtain the comprehensive genetic information for tumors and other human complex genetic diseases [18–22]. A list of LUAD related somatic alterations have been identified through WGS and other high-throughput studies [4, 23–25].…”

Section: Introductionmentioning

confidence: 99%

LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features

et al. 2019

BMC Cancer

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BackgroundLung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction. Effective genetic markers and their based prediction models are also at a lack for prognosis evaluation.MethodsWe obtained the somatic mutation data and clinical data for 371 lung adenocarcinoma cases from The Cancer Genome Atlas. The cases were classified into two prognostic groups (3-year survival), and a comparison was performed between the groups for the somatic mutation frequencies of genes, followed by development of computational models to discrete the different prognosis.ResultsGenes were found with higher mutation rates in good (≥ 3-year survival) than in poor (< 3-year survival) prognosis group of lung adenocarcinoma patients. Genes participating in cell-cell adhesion and motility were significantly enriched in the top gene list with mutation rate difference between the good and poor prognosis group. Support Vector Machine models with the gene somatic mutation features could well predict prognosis, and the performance improved as feature size increased. An 85-gene model reached an average cross-validated accuracy of 81% and an Area Under the Curve (AUC) of 0.896 for the Receiver Operating Characteristic (ROC) curves. The model also exhibited good inter-stage prognosis prediction performance, with an average AUC of 0.846 for the ROC curves.ConclusionThe prognosis of lung adenocarcinomas is related with somatic gene mutations. The genetic markers could be used for prognosis prediction and furthermore provide guidance for personal medicine.Electronic supplementary materialThe online version of this article (10.1186/s12885-019-5433-7) contains supplementary material, which is available to authorized users.

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“…Thirdly, the TNM staging in this study utilized the sixth edition, rather than the currently used eighth edition TNM staging guildelines. Additionally, SCLC has a unique genome map, as demonstrated by next generation sequencing, and parameters such as gene mutation may be used to predict survival in future studies.…”

Section: Discussionmentioning

confidence: 99%

Nomogram to predict cause‐specific mortality in extensive‐stage small cell lung cancer: A competing risk analysis

Zhong

Zheng

et al. 2019

Thoracic Cancer

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Background Small‐cell lung cancer (SCLC) is one of the most aggressive types of lung cancer. The prognosis for SCLC patients depends on many factors. The intent of this study was to construct a nomogram model to predict mortality for extensive‐stage SCLC. Methods Original data was collected from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute in the United States. A nomogram prognostic model was constructed to predict death probability for extensive‐stage SCLC. Results A total of 16 554 extensive‐stage SCLC patients from 2004 to 2014 in the SEER database were included in this study. Gender, race, age, TNM staging (including tumor extent, nodal status, and metastasis), and treatment (surgery, chemotherapy, and radiotherapy) were identified as independent predictors for lung cancer‐specific death for extensive‐stage SCLC patients. A nomogram model was constructed based on multivariate models for lung cancer related death and other cause related death. Performance of the two models was validated by calibration and discrimination, with C‐index values of 0.714 and 0.638, respectively. Conclusion A prognostic nomogram model was established to predict death probability for extensive‐stage SCLC. This validated prognostic model may be beneficial for treatment strategy choice and survival prediction.

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Whole-genome analysis of a patient with early-stage small-cell lung cancer

Cited by 7 publications

References 31 publications

Whole exome analysis reveals the genomic profiling related to chemo‐resistance in Chinese population with limited‐disease small cell lung cancer

Whole exome analysis reveals the genomic profiling related to chemo‐resistance in Chinese population with limited‐disease small cell lung cancer

LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features

Nomogram to predict cause‐specific mortality in extensive‐stage small cell lung cancer: A competing risk analysis

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