Comprehensive Next-Generation Sequencing Unambiguously Distinguishes Separate Primary Lung Carcinomas From Intrapulmonary Metastases: Comparison with Standard Histopathologic Approach

Chang, Jason C.; Alex, Deepu; Bott, Matthew; Tan, Kay See; Seshan, Venkatraman; Golden, Andrew; Sauter, Jennifer L.; Buonocore, Darren J.; Vanderbilt, Chad; Gupta, Sounak; Desmeules, Patrice; Bodd, Francis M.; Riely, Gregory J.; Rusch, Valerie W.; Jones, David R.; Arcila, Maria E.; Travis, William D.; Ladanyi, Marc; Rekhtman, Natasha

doi:10.1158/1078-0432.ccr-19-1700

Cited by 80 publications

(108 citation statements)

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“…Unlike conventional small gene panels, large panel next-generation sequencing assys can avoid the limitations of non-information in quite a few cases. A previous study on 76 tumor pairs from sixty patients have shown the utility of the large-scale gene assay (341–468 gene) for assessment of tumor clonal relationships 29 , but Asian populations were unrepresented in this cohort. More recently, the 464 gene panel have been applied to solve the problem of separating MPs from IMs 18 .…”

Section: Discussionmentioning

confidence: 93%

“…Based on the low prevalence of these genes, the odds of coincidental co-occurrence of { EGFR (p.L858R) and ATRX (p.S1012A)} or { EGFR (p.L747_T751del) and RBM10 (p.V467fs)} in two independent tumors were lower than 2.20E − 04 and 3.36E − 04, repectively. Therefore, these two pairs were classified as high-probability IMs 29 .…”

Section: Resultsmentioning

confidence: 99%

“…Recent studies have pointed out that large panel next-generation sequencing assys can be utilized not only to guide targeted therapies, but also to determine the clonal relationships among MLCs 18 , 29 . Unlike conventional small gene panels, large panel next-generation sequencing assys can avoid the limitations of non-information in quite a few cases.…”

Section: Discussionmentioning

confidence: 99%

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Application of large-scale targeted sequencing to distinguish multiple lung primary tumors from intrapulmonary metastases

Duan

Peng

et al. 2020

Sci Rep

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The effective differentiation between multiple primary lung tumors (MPs) and intrapulmonary metastases (IMs) in patients is imperative to discover the exact disease stage and to select the most appropriate treatment. In this study, the authors was to evaluate the efficacy and validity of large-scale targeted sequencing (LSTS) as a supplement to estimate whether multifocal lung cancers (MLCs) are primary or metastatic. Targeted sequencing of 520 cancer-related oncogenes was performed on 36 distinct tumors from 16 patients with MPs. Pairing analysis was performed to evaluate the somatic mutation pattern of MLCs in each patient. A total of 25 tumor pairs from 16 patients were sequenced, 88% (n = 22) of which were classified as MPs by LSTS, consistent with clinical diagnosis. One tumor pair from a patient with lymph node metastases had highly consistent somatic mutation profiles, thus predicted as a primary-metastatic pair. In addition, some matched mutations were observed in the remaining two paired ground-glass nodules (GGNs) and classified as high-probability IMs by LSTS. Our study revealed that LSTS can potentially facilitate the distinction of MPs from IMs. In addition, our results provide new genomic evidence of the presence of cancer invasion in GGNs, even pure GGNs.

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Section: Discussionmentioning

confidence: 93%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Application of large-scale targeted sequencing to distinguish multiple lung primary tumors from intrapulmonary metastases

Duan

Peng

et al. 2020

Sci Rep

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“…Subsequently, NGS screening from 20 to 468 cancer-related genes was applied to identify MPLCs. [52][53][54][55][56][57][58] Seven small studies enrolled a total of 237 patients (range, 11 to 60) and compared the diagnostic efficacy and robustness of the molecular classification with the different histological classifications (Table 2). Overall, NGS provides better discrimination than the clinicopathological classification because it is able to classify more indefinite cases, indicating the importance of NGS.…”

Section: Molecular Characteristicsmentioning

confidence: 99%

“…This study sequencing only 20 genes had no equivocal cases, in part because some indefinite cases sharing only one hotspot driver mutation were classified as IM. 55 In other studies, 53,54,[56][57][58] relationship of 95% of lung adenocarcinomas although the most appropriate detection number of genes remains unknown. Additionally, as shown in Table 2, the molecular classification by NGS conflicts with the histological classification in many cases, and to some extent compensates for the shortcomings of a histological classification.…”

Section: Molecular Characteristicsmentioning

confidence: 99%

<p>Multiple Primary Lung Cancers: A New Challenge in the Era of Precision Medicine</p>

Zhao¹,

Liu²,

Xie³

et al. 2020

CMAR

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With the widespread implementation of lung cancer screening, more and more patients are being diagnosed with multiple primary lung cancers (MPLCs). In the era of precision medicine, many controversies remain in differentiating MPLCs from intrapulmonary metastasis and the optimum treatment choice, especially in patients exhibiting similar histology. In this review, we summarize common diagnostic criteria and novel discrimination methods with a special emphasis on the emerging value of broad panel next-generation sequencing (NGS) for the diagnosis of MPLCs. We then discuss current advances regarding therapeutic approaches for MPLCs. Radical surgery is the main treatment modality, while stereotactic body radiotherapy (SBRT) is safe and feasible for early-stage MPLC patients with inoperable tumors. In addition, immunotherapy and targeted therapy, particularly epidermal growth factor receptor-tyrosine kinase inhibitors, are emerging therapeutic strategies that are still in their infancy. Characteristics of both genomic profiles and tumor microenvironment are currently being evaluated but warrant further exploration to facilitate the application of targeted systematic therapies in MPLC patients.

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A Genomic-Pathologic Annotated Risk Model to Predict Recurrence in Early-Stage Lung Adenocarcinoma

et al. 2021

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IMPORTANCERecommendations for adjuvant therapy after surgical resection of lung adenocarcinoma (LUAD) are based solely on TNM classification but are agnostic to genomic and high-risk clinicopathologic factors. Creation of a prediction model that integrates tumor genomic and clinicopathologic factors may better identify patients at risk for recurrence.OBJECTIVE To identify tumor genomic factors independently associated with recurrence, even in the presence of aggressive, high-risk clinicopathologic variables, in patients with completely resected stages I to III LUAD, and to develop a computational machine-learning prediction model (PRecur) to determine whether the integration of genomic and clinicopathologic features could better predict risk of recurrence, compared with the TNM system. DESIGN, SETTING, AND PARTICIPANTSThis prospective cohort study included 426 patients treated from January 1, 2008, to December 31, 2017, at a single large cancer center and selected in consecutive samples. Eligibility criteria included complete surgical resection of stages I to III LUAD, broad-panel next-generation sequencing data with matched clinicopathologic data, and no neoadjuvant therapy. External validation of the PRecur prediction model was performed using The Cancer Genome Atlas (TCGA). Data were analyzed from 2014 to 2018. MAIN OUTCOMES AND MEASURESThe study end point consisted of relapse-free survival (RFS), estimated using the Kaplan-Meier approach. Associations among clinicopathologic factors, genomic alterations, and RFS were established using Cox proportional hazards regression. The PRecur prediction model integrated genomic and clinicopathologic factors using gradient-boosting survival regression for risk group generation and prediction of RFS. A concordance probability estimate (CPE) was used to assess the predictive ability of the PRecur model. RESULTSOf the 426 patients included in the analysis (286 women [67%]; median age at surgery, 69 [interquartile range, 62-75] years), 318 (75%) had stage I cancer. Association analysis showed that alterations in SMARCA4 (clinicopathologic-adjusted hazard ratio [HR], 2.44; 95% CI, 1.03-5.77; P = .042) and TP53 (clinicopathologic-adjusted HR, 1.73; 95% CI, 1.09-2.73; P = .02) and the fraction of genome altered (clinicopathologic-adjusted HR, 1.03; 95% CI, 1.10-1.04; P = .005) were independently associated with RFS. The PRecur prediction model outperformed the TNM-based model (CPE, 0.73 vs 0.61; difference, 0.12 [95% CI, 0.05-0.19]; P < .001) for prediction of RFS. To validate the prediction model, PRecur was applied to the TCGA LUAD data set (n = 360), and a clear separation of risk groups was noted (log-rank statistic, 7.5; P = .02), confirming external validation. CONCLUSIONS AND RELEVANCEThe findings suggest that integration of tumor genomics and clinicopathologic features improves risk stratification and prediction of recurrence after surgical resection of early-stage LUAD. Improved identification of patients at risk for recurrence could enrich and enhance accrual to adjuv...

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Comprehensive Next-Generation Sequencing Unambiguously Distinguishes Separate Primary Lung Carcinomas From Intrapulmonary Metastases: Comparison with Standard Histopathologic Approach

Cited by 80 publications

References 50 publications

Application of large-scale targeted sequencing to distinguish multiple lung primary tumors from intrapulmonary metastases

Application of large-scale targeted sequencing to distinguish multiple lung primary tumors from intrapulmonary metastases

<p>Multiple Primary Lung Cancers: A New Challenge in the Era of Precision Medicine</p>

A Genomic-Pathologic Annotated Risk Model to Predict Recurrence in Early-Stage Lung Adenocarcinoma

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