Comprehensive targeted super-deep next generation sequencing enhances differential diagnosis of solitary pulmonary nodules

Ye, Mingzhi; Li, Shiyong; Huang, Weiguo; Wang, Chunli; Liu, Liping; Li, Jun; Liu, Ji‐Long; Hui, Pei; Deng, Qiuhua; Tang, Hailing; Jiang, Long; Chen, Xi; Шао, Ди; Peng, Zhiyu; Wu, Renhua; Zhong, Jing; Wang, Zhe; Zhang, Xiaoping; Kristiansen, Karsten; Wang, Jian; Yin, Ye; Mao, Mao; He, Jianxing; Liang, Wenhua

doi:10.21037/jtd.2018.04.09

Cited by 17 publications

(14 citation statements)

References 31 publications

(30 reference statements)

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“…In CCGA, a set of 73 early to midstage (stages I–III) lung cancer samples showed a similar rate of 59% (95% CI 47% to 70%) 13. In another very small study of 31 paired lung cancer tissues and plasma DNA samples with 10 000-fold ctDNA sequencing depth, the concordance of mutation between tumour tissue DNA and ctDNA was merely 3.9% 24. Ours is more like CCGA in that we both sequenced ctDNA to the depth >40 000×.…”

Section: Discussionmentioning

confidence: 98%

Resectable lung lesions malignancy assessment and cancer detection by ultra-deep sequencing of targeted gene mutations in plasma cell-free DNA

Peng

Xie

Li³

et al. 2019

J Med Genet

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BackgroundEarly detection of lung cancer to allow curative treatment remains challenging. Cell-free circulating tumour (ct) DNA (ctDNA) analysis may aid in malignancy assessment and early cancer diagnosis of lung nodules found in screening imagery.MethodsThe multicentre clinical study enrolled 192 patients with operable occupying lung diseases. Plasma ctDNA, white cell count genomic DNA (gDNA) and tumour tissue gDNA of each patient were analysed by ultra-deep sequencing to an average of 35 000× of the coding regions of 65 lung cancer-related genes.ResultsThe cohort consists of a quarter of benign lung diseases and three quarters of cancer patients with all histopathology subtypes. 64% of the cancer patients are at stage I. Gene mutations detection in tissue gDNA and plasma ctDNA results in a sensitivity of 91% and specificity of 88%. When ctDNA assay was used as the test, the sensitivity was 69% and specificity 96%. As for the lung cancer patients, the assay detected 63%, 83%, 94% and 100%, for stages I, II, III and IV, respectively. In a linear discriminant analysis, combination of ctDNA, patient age and a panel of serum biomarkers boosted the overall sensitivity to 80% at a specificity of 99%. 29 out of the 65 genes harboured mutations in the patients with lung cancer with the largest number found in TP53 (30% plasma and 62% tumour tissue samples) and EGFR (20% and 40%, respectively).ConclusionPlasma ctDNA was analysed in lung nodule assessment and early cancer detection, while an algorithm combining clinical information enhanced the test performance.Trial registration numberNCT03081741.

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Section: Discussionmentioning

confidence: 98%

Resectable lung lesions malignancy assessment and cancer detection by ultra-deep sequencing of targeted gene mutations in plasma cell-free DNA

Peng

Xie

Li³

et al. 2019

J Med Genet

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“…In addition, some driver mutations, such as TP53, EGFR, and KRAS, have previously shown specifically emerged in the malignant adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) stages, but not the premalignant atypical adenomatous hyperplasia (AAH) stage . Based on the above findings, noninvasively harvesting the genomic information of lung lesions may facilitate clinicians to not only identify benign and malignant tumors, but also to formulate a better therapeutic plan …”

Section: Introductionmentioning

confidence: 99%

Decoding tumor mutation burden and driver mutations in early stage lung adenocarcinoma using CT‐based radiomics signature

Wang

Cheng

et al. 2019

Thoracic Cancer

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Background Tumor mutation burden (TMB) is an important determinant and biomarker for response of targeted therapy and prognosis in patients with lung cancer. The present study aimed to determine whether radiomics signature could non‐invasively predict the TMB status and driver mutations in patients with resectable early stage lung adenocarcinoma (LUAD). Methods A total of 61pulmonary nodules (PNs) from 51 patients post‐operatively diagnosed LUAD were enrolled for analysis. Two datasets were divided according to two‐thirds of patients from different commercial Comprehensive Genomic Profiling (CGP) panels: a training cohort including 41 PNs and a testing cohort including rest 20PNs. We sequenced all tumor specimens and paired blood cells using next generation sequencing (NGS), so as to detect TMB status and somatic mutations. We collected 718 quantitative 3D radiomics features extracted from segmented volumes of each PNs and 78 clinical and pathological features retrieved from medical records as well. Support vector machine methods were performed to establish the predictive model. Results We established an efficient fusion‐positive tumor prediction model that predicts TMB status and EGFR/TP53 mutations of early stage LUAD. The radiomics signature yielded a median AUC value of 0.606, 0.604, and 0.586 respectively. Combining radiomics with the clinical information can further improve the prediction performance, which the median AUC values are 0.671 for TMB, 0.697 and 0.656 for EGFR/TP53 respectively. Conclusion It is feasible and effective to facilitate TMB and somatic driver mutations prediction by using the radiomics signature and NGS data in early stage LUAD.

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“…In CCGA, a set of 73 early to mid-stage (stage I-III) lung cancer samples showed a similar rate of 59% (CI = 47-70%) (13). In another very small study of 31 paired lung cancer tissues and plasma DNA samples with 10,000-fold ctDNA sequencing depth, the concordance of mutation between tumor tissue DNA and ctDNA was merely 3.9% (21). Ours is more like CCGA in that we both sequenced ctDNA to the depth >40,000X.…”

Section: Discussionmentioning

confidence: 98%

Multi-Center Study of Resectable Lung Lesions by Ultra-Deep Sequencing of Targeted Genes in Plasma Cell-Free DNA to Assess Nodule Malignancy and Detect Lung Cancers

Xie

X²,

et al. 2018

Preprint

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BACKGROUND Early detection of lung cancer to allow curative treatment remains challenging.Cell-free circulating tumor DNA (ctDNA) analysis may aid in malignancy assessment and early cancer diagnosis of lung nodules found in screening imagery. METHODS The multi-center clinical study enrolled 192 patients with operable occupying lung diseases. Plasma ctDNA, white blood cell genomic DNA (gDNA) and tumor tissue gDNA of each patient were analyzed by ultra-deep sequencing to an average of 35,000X of the coding regions of 65 lung cancer-related genes.RESULTS The cohort consists of a quarter of benign lung diseases and three quarters of cancer patients with all histopathology subtypes. 64% of the cancer patients is at Stage I. Gene mutations detection in tissue gDNA and plasma ctDNA results in a sensitivity of 91% and specificity of 88%.When ctDNA assay was used as the test, the sensitivity was 69% and specificity 96%. As for the lung cancer patients, the assay detected 63%, 83%, 94% and 100%, for Stage I, II, III and IV, respectively. In a linear discriminant analysis, combination of ctDNA, patient age and a panel of serum biomarkers boosted the overall sensitivity to 80% at a specificity of 99%. 29 out of the 65 genes harbored mutations in the lung cancer patients with the largest number found in TP53 (30% plasma and 62% tumor tissue samples) and EGFR (20% and 40%, respectively).CONCLUSION Plasma ctDNA was analyzed in lung nodule assessment and early cancer detection while an algorithm combining clinical information enhanced the test performance.

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Comprehensive targeted super-deep next generation sequencing enhances differential diagnosis of solitary pulmonary nodules

Cited by 17 publications

References 31 publications

Resectable lung lesions malignancy assessment and cancer detection by ultra-deep sequencing of targeted gene mutations in plasma cell-free DNA

Resectable lung lesions malignancy assessment and cancer detection by ultra-deep sequencing of targeted gene mutations in plasma cell-free DNA

Decoding tumor mutation burden and driver mutations in early stage lung adenocarcinoma using CT‐based radiomics signature

Multi-Center Study of Resectable Lung Lesions by Ultra-Deep Sequencing of Targeted Genes in Plasma Cell-Free DNA to Assess Nodule Malignancy and Detect Lung Cancers

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