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Genomic Landscape of Metastatic Lymph Nodes and Primary Tumors in Non-Small-Cell Lung Cancer.

ABSTRACT: Objective: To investigate the genetic mutation characteristics of non-small cell lung cancers (NSCLC) with and without lymph node metastasis. Methods: Primary lesions and metastatic lymph node lesions of 36 Chinese NSCLC patients were tested for somatic mutations, tumor mutation burden, phylogenetic and clonal evolutional analysis using a 1021-gene panel by next-generation sequencing (NGS) with an average sequencing depth of 671X. Results: In this study, eighteen patients with lung adenocarcinoma (LUAD) and 18 with lung squamous cell carcinoma (LUSC) were included. Different groups had distinct characteristics of gene mutations. CTNNB1 gene mutations were only present in Nome_LC LUAD patients (p < 0.05). ARID1A mutation was however the only gene with significant alterations (p < 0.05) in Nome_LC in LUSC. Phylogenetic trees of mutated genes were also constructed. Linear and parallel evolutions of metastatic lymph nodes were observed both in LUAD and LUSC. Conclusion: LUSC exhibited more genetic mutations than LUAD. Intriguingly, there was significant difference in gene mutations between Meta_LC and Nome_LC. CTNNB1 gene alteration was the key mutation in LUAD that seems to promote proliferation of the tumor and then determine T stage. On the other hand, proliferation of the tumor was characterized by ARID1A missense mutation in LUSC, thus influencing the T stage as well. Lymph node metastasis could display both linear and parallel evolutionary characteristics in NSCLC. Different metastatic lymph nodes might have exactly the same or different mutated genes, underlining the heterogeneous genomic characteristics of these cancer types.

SUBMITTER: Chen B

PROVIDER: S-EPMC9243222 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objectives18F-fluorodeoxyglucose (FDG) PET/CT has been widely used in tumor diagnosis, staging, and response evaluation. To determine an optimal therapeutic strategy for lung cancer patients, accurate staging is essential. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may fail to differentiate between benign and malignant lesions. Lymph nodes (LNs) in the mediastinal and pulmonary hilar regions with high FDG uptake due to granulomatous lesions such as tuberculosis, which has a high prevalence in China, pose a diagnostic challenge. This study aims to evaluate the diagnostic value of the quantitative metabolic parameters derived from dynamic 18F-FDG PET/CT in differentiating metastatic and non-metastatic LNs in lung cancer.MethodsOne hundred and eight patients with pulmonary nodules were enrolled to perform 18F-FDG PET/CT dynamic + static imaging with informed consent. One hundred and thirty-five LNs in 29 lung cancer patients were confirmed by pathology. Static image analysis parameters including LN-SUVmax, LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax), mediastinal blood pool SUVmax (MBP-SUVmax), LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter. Quantitative parameters including K1, k2, k3 and Ki and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was computed subsequently as a separate marker. We further divided the LNs into mediastinal LNs (N=82) and pulmonary hilar LNs (N=53). Wilcoxon rank-sum test or Independent-samples T-test and receiver-operating characteristic (ROC) analysis was performed on each parameter to compare the diagnostic efficacy in differentiating lymph node metastases from inflammatory uptake. P<0.05 were considered statistically significant.ResultsAmong the 135 FDG-avid LNs confirmed by pathology, 49 LNs were non-metastatic, and 86 LNs were metastatic. LN-SUVmax, MBP-SUVmax, LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter couldn't well differentiate metastatic from non-metastatic LNs (P>0.05). However, LN-SUVmax/PT-SUVmax have good performance in the differential diagnosis of non-metastatic and metastatic LNs (P=0.039). Dynamic metabolic parameters in addition to k3, the parameters including K1, k2, Ki, and Ki/K1, on the other hand, have good performance in the differential diagnosis of metastatic and non-metastatic LNs (P=0.045, P=0.001, P=0.001, P=0.001, respectively). For ROC analysis, the metabolic parameters Ki (AUC of 0.672 [0.579-0.765], sensitivity 0.395, specificity 0.918) and Ki/K1 (AUC of 0.673 [0.580-0.767], sensitivity 0.570, specificity 0.776) have good performance in the differential diagnosis of metastatic from non-metastatic LNs than SUVmax (AUC of 0.596 [0.498-0.696], sensitivity 0.826, specificity 0.388), included the mediastinal region and pulmonary hilar region.ConclusionCompared with SUVmax, quantitative parameters such as K1, k2, Ki and Ki/K1 showed promising results for differentiation of metastatic and non-metastatic LNs with high uptake. The Ki and Ki/K1 had a high differential diagnostic value both in the mediastinal region and pulmonary hilar region.

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Genomic Landscape of Metastatic Lymph Nodes and Primary Tumors in Non-Small-Cell Lung Cancer.

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