Genome‐wide copy number variation pattern analysis and a classification signature for non‐small cell lung cancer

Qiu, Zhe; Bi, Jia; Gazdar, Adi F.; Song, Kai

doi:10.1002/gcc.22460

Cited by 52 publications

(43 citation statements)

References 55 publications

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“…Using our strategy in combination with cross-validation, binary accuracies of respectively 86.8%, 84.8%, and 92.2% were settled on a classbalanced subset of the same public dataset (n = 204; no additional filtering). Two more large studies performed (binary) classification using copy numbers between LUAD and LUSC: the work of Li et al claims an accuracy of 86.1% (n = 301), whilst Qiu and colleagues report 84.0% (n = 986) [35,36]. Likewise, the in-house SBs (89.7%, 92.3%, and 97.4%, respectively) Histology-wise mean IS histograms of LBs, with transparent background waves, which indicate the 95% CI.…”

Section: Discussionmentioning

confidence: 99%

Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma

et al. 2020

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Background: Accurate lung cancer classification is crucial to guide therapeutic decisions. However, histological subtyping by pathologists requires tumor tissue-a necessity that is often intrinsically associated with procedural difficulties. The analysis of circulating tumor DNA present in minimal-invasive blood samples, referred to as liquid biopsies, could therefore emerge as an attractive alternative. Methods: Concerning adenocarcinoma, squamous cell carcinoma, and small cell carcinoma, our proof of concept study investigates the potential of liquid biopsy-derived copy number alterations, derived from single-end shallow whole-genome sequencing (coverage 0.1-0.5×), across 51 advanced stage lung cancer patients. Results: Genomic abnormality testing reveals anomalies in 86.3% of the liquid biopsies (16/20 for adenocarcinoma, 13/16 for squamous cell, and 15/15 for small cell carcinoma). We demonstrate that copy number profiles from formalin-fixed paraffin-embedded tumor biopsies are well represented by their liquid equivalent. This is especially valid within the small cell carcinoma group, where paired profiles have an average Pearson correlation of 0.86 (95% CI 0.79-0.93). A predictive model trained with public data, derived from 843 tissue biopsies, shows that liquid biopsies exhibit multiple deviations that reflect histological classification. Most notably, distinguishing small from non-small cell lung cancer is characterized by an area under the curve of 0.98 during receiver operating characteristic analysis. Additionally, we investigated how deeper paired-end sequencing, which will eventually become feasible for routine diagnosis, empowers tumor read enrichment by insert size filtering: for all of the 29 resequenced liquid biopsies, the tumor fraction could be increased in silico, thereby "rescuing" three out of five cases with previously undetectable alterations.(Continued on next page)

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Section: Discussionmentioning

confidence: 99%

Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma

et al. 2020

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“…And NSCLC can be classified into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). 3,4 Known factors like smoking, air pollution and ionizing radiation are considered to be associated with the initiation and development of LUSC, 5,6 but the pathology of LUSC remains unclear.…”

Section: Introductionmentioning

confidence: 99%

<p>Long Noncoding MAGI2-AS3 Suppresses Several Cellular Processes of Lung Squamous Cell Carcinoma Cells by Regulating miR-374a/b-5p/CADM2 Axis</p>

He¹,

Zhou²,

Li³

et al. 2020

CMAR

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Background: Lung squamous cell carcinoma (LUSC) accounts for approximately 30% of all lung cancers that possesses the highest occurrence and mortality in all cancer types. Long noncoding RNAs have been reported to modulate tumor development for several decades. Aim of the Study: This research aims to investigate the role of MAGI2-AS3 in LUSC. Methods: RT-qPCR tested genes (including MAGI2-AS3, miR-374a/b-5p and CADM2) expression. Cell proliferation was detected by colony formation and EdU assays. Cell migration and invasion were evaluated by transwell assay. Flow cytometry analysis of apoptotic cells and Western blot analysis on apoptosis-related genes were applied to measure cell apoptosis. Nuclear-cytoplasmic fractionation and FISH assay positioned MAGI2-AS3. The combination between miR-374a/b-5p and MAGI2-AS3 (or CADM2) was determined by luciferase reporter assay and RIP assay. Results: MAGI2-AS3 inhibited the proliferative, migratory and invasive capability of LUSC cells with upregulated expression. Additionally, MAGI2-AS3 overexpression promoted cell apoptosis. We discovered that MAGI2-AS3 was located in the cytoplasm. Hereafter, we found out that MAGI2-AS3 targeted miR-374a/b-5p. CADM2 was targeted by miR-374a/ b-5p. Finally, rescue assays indicated that the promoting effects of miR-374a/b-5p amplification on biological activities were restored by CADM2 addition. Conclusion: In conclusion, lncRNA MAGI2-AS3 suppressed LUSC by regulating miR-374a/b-5p/CADM2 axis, which might potentially serve as a therapeutic marker for LUSC patients.

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“…Genome-wide gene expression patterns, shown in the volcano plot in Fig. 2, differed greatly between current smokers vs. nonsmokers in the TCGA LUAD samples even after using a Bonferroni-correction, which is the most conservative family-wise control (Qiu et al, 2017). Thirty-two out of forty-three identified GE signature genes (Table S2) are significantly different with large fold changes in gene expression values between the two groups.…”

Section: Resultsmentioning

confidence: 99%

“…Lung cancer is currently the most common malignant disease and the leading cause of mortality in the world (Siegel, Miller & Jemal, 2018;Tian, 2019). Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma are the two major histological types of non-small cell lung cancer (NSCLC) covering over 90% of cases; NSCLC itself accounts for 75-80% of lung cancer cases (Qiu et al, 2017;Chen et al, 2015;Tian, 2015). Large cell cancer samples represent undifferentiated NSCLCs that do not show morphological or immunostaining evidence of glandular or squamous differentiation.…”

Section: Introductionmentioning

confidence: 99%

Multiple genome pattern analysis and signature gene identification for the Caucasian lung adenocarcinoma patients with different tobacco exposure patterns

Dong

Qin

Tong

et al. 2020

PeerJ

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Background: When considering therapies for lung adenocarcinoma (LUAD) patients, the carcinogenic mechanisms of smokers are believed to differ from those who have never smoked. The rising trend in the proportion of nonsmokers in LUAD urgently requires the understanding of such differences at a molecular level for the development of precision medicine. Methods: Three independent LUAD tumor sample sets-TCGA, SPORE and EDRNwere used. Genome patterns of expression (GE), copy number variation (CNV) and methylation (ME) were reviewed to discover the differences between them for both smokers and nonsmokers. Tobacco-related signature genes distinguishing these two groups of LUAD were identified using the GE, ME and CNV values of the whole genome. To do this, a novel iterative multi-step selection method based on the partial least squares (PLS) algorithm was proposed to overcome the high variable dimension and high noise inherent in the data. This method can thoroughly evaluate the importance of genes according to their statistical differences, biological functions and contributions to the tobacco exposure classification model. The kernel partial least squares (KPLS) method was used to further optimize the accuracies of the classification models. Results: Forty-three, forty-eight and seventy-five genes were identified as GE, ME and CNV signatures, respectively, to distinguish smokers from nonsmokers. Using only the gene expression values of these 43 GE signature genes, ME values of the 48 ME signature genes or copy numbers of the 75 CNV signature genes, the accuracies of TCGA training and SPORE/EDRN independent validation datasets all exceed 76%. More importantly, the focal amplicon in Telomerase Reverse Transcriptase in nonsmokers, the broad deletion in ChrY in male nonsmokers and the greater amplification of MDM2 in female nonsmokers may explain why nonsmokers of both genders tend to suffer LUAD. These pattern analysis results may have clear biological interpretation in the molecular mechanism of tumorigenesis. Meanwhile, the identified signature genes may serve as potential drug targets for the precision medicine of LUAD.How to cite this article Dong Y-m, Qin L-d, Tong Y-f, He Q-e, Wang L, Song K. 2020. Multiple genome pattern analysis and signature gene identification for the Caucasian lung adenocarcinoma patients with different tobacco exposure patterns. PeerJ 8:e8349

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Genome‐wide copy number variation pattern analysis and a classification signature for non‐small cell lung cancer

Cited by 52 publications

References 55 publications

Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma

Shallow whole-genome sequencing of plasma cell-free DNA accurately differentiates small from non-small cell lung carcinoma

<p>Long Noncoding MAGI2-AS3 Suppresses Several Cellular Processes of Lung Squamous Cell Carcinoma Cells by Regulating miR-374a/b-5p/CADM2 Axis</p>

Multiple genome pattern analysis and signature gene identification for the Caucasian lung adenocarcinoma patients with different tobacco exposure patterns

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