The Landscape of Actionable Genomic Alterations by Next-Generation Sequencing in Tumor Tissue Versus Circulating Tumor DNA in Chinese Patients With Non-Small Cell Lung Cancer

Clinical application of ctDNA in early diagnosis, treatment and prognosis of patients with non-small cell lung cancer

Lung cancer is one of the most common malignancies worldwide, with non-small cell lung cancer (NSCLC) being the most common type. As understanding of precise treatment options for NSCLC deepens, circulating tumor DNA (ctDNA) has emerged as a potential biomarker that has become a research hotspot and may represent a new approach for the individualized diagnosis and treatment of NSCLC. This article reviews the applications of ctDNA for the early screening of patients with NSCLC, guiding targeted therapy and immunotherapy, evaluating chemotherapy and postoperative efficacy, assessing prognosis and monitoring recurrence. With the in-depth study of the pathogenesis of NSCLC, plasma ctDNA may become an indispensable part of the precise treatment of NSCLC, which has great clinical application prospects.

[Progress of BRAF Gene Alteration in Non-small Cell Lung Cancer]

V-Raf murine sarcoma viral oncogene homolog B (BRAF) alteration is one of the most essential driver genes of non-small cell lung cancer (NSCLC). BRAF encodes serine/threonine protein kinases, and its mutations typically lead to protein compositional activation, thereby activating the mitogen-activated protein kinase kinase (MEK) signaling pathway. A promising new approach for the treatment of mutated BRAF and/or downstream MEK may provide customized treatment opportunities for BRAF driven NSCLC patients. However, combination therapy is necessary to overcome the difficulties such as short duration of benefit, poor therapeutic effect of non-V600 BRAF mutations and susceptibility to drug resistance. This article reviewed the progress in structural characteristics, related signaling pathways, mutation types of BRAF gene, and the clinical pathological relationship between BRAF mutations and NSCLC, as well as the therapy, in order to provide more evidences for clinical doctors to make treatment decisions.
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A comparative study on ctDNA and tumor DNA mutations in lung cancer and benign cases with a high number of CTCs and CTECs

BACKGROUND

Liquid biopsy provides a non-invasive approach that enables detecting circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) using blood specimens and theoretically benefits early finding primary tumor or monitoring treatment response as well as tumor recurrence. Despite many studies on these novel biomarkers, their clinical relevance remains controversial. This study aims to investigate the correlation between ctDNA, CTCs, and circulating tumor-derived endothelial cells (CTECs)  while also evaluating whether mutation profiling in ctDNA is consistent with that in tumor tissue from lung cancer patients. These findings will help the evaluation and utilization of these approaches in clinical practice.

METHODS

104 participants (49 with lung cancer and 31 with benign lesions) underwent CTCs and CTECs detection using integrating subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH) strategy. The circulating cell-free DNA (cfDNA) concentration was measured and the mutational profiles of ctDNA were examined by Roche AVENIO ctDNA Expanded Kit (targeted total of 77 genes) by next generation sequencing (NGS) in 28 patients (20 with lung cancer and 8 with benign lesions) with highest numbers of CTCs and CTECs. Mutation validation in matched tumor tissue DNA was then performed in 9 patients with ctDNA mutations using a customized xGen pan-solid tumor kit (targeted total of 474 genes) by NGS.

RESULTS

The sensitivity and specificity of total number of CTCs and CTECs for the diagnosis of NSCLC were 67.3% and 77.6% [AUC (95%CI): 0.815 (0.722-0.907)], 83.9% and 77.4% [AUC (95%CI): 0.739 (0.618-0.860)]. The concentration of cfDNA in plasma was statistically correlated with the size of the primary tumor (r = 0.430, P = 0.022) and CYFRA 21-1 (r = 0.411, P = 0.041), but not with the numbers of CTCs and CTECs. In this study, mutations were found to be poorly consistent between ctDNA and tumor DNA (tDNA) in patients, even when numerous CTCs and CTECs were present.

CONCLUSION

Detection of CTCs and CTECs could be the potential adjunct tool for the early finding of lung cancer. The cfDNA levels are associated with the tumor burden, rather than the CTCs or CTECs counts. Moreover, the poorly consistent mutations between ctDNA and tDNA require further exploration.

Differences of genomic alterations and heavy metals in non-small cell lung cancer with different histological subtypes

PURPOSE

This study aimed to explore the correlations among heavy metals concentration, histologic subtypes and molecular characteristics in patients with non-small cell lung cancer (NSCLC).

METHODS

In this study, an NGS panel of 82 tumor-associated genes was used to identify genomic alternations in 180 newly diagnosed patients with NSCLC. The concentrations of 18 heavy metals in the serum samples were detected by inductively coupled plasma emission spectrometry (ICP-MS).

RESULTS

A total of 243 somatic mutations of 25 mutant genes were identified in 115 of 148 patients with LUAD and 45 somatic mutations of 15 mutant genes were found in 24 of 32 patients with LUSC. The genomic alternations, somatic interactions, traditional serum biomarkers, and heavy metals were markedly different between patients with LUAD and LUSC. Moreover, patients with LUSC were significantly positively correlated with Ba, but not LUAD. Lastly, patients with EGFR mutations presented significant negative correlations with Cd and Sr, whereas patients with TP53 mutations showed a significant positive correlation with Pb.

CONCLUSION

The genomic alternations, somatic interactions, traditional serum biomarkers, and heavy metals were different between patients with LUAC and LUSC, and heavy metals (e.g., Ba, Pb, and Cd) may contribute to the tumorigenesis of NSCLC with different histological and molecular subtypes.

TERT Mutations in Non-Small Cell Lung Cancer: Clinicopathologic Features and Prognostic Implications

INTRODUCTION

The associations between the clinical characteristics of non-small cell lung cancer (NSCLC) and mutations in telomerase reverse transcriptase (TERT) gene remain unclear. In this study, we used next-generation sequencing (NGS) to investigate the incidence rate and clinical correlates of TERT mutations in patients with NSCLC.

METHODS

In total, 283 tumor samples from patients with NSCLC were tested using an NGS panel from September 2017 to May 2020. The genetic testing results and clinical data of all patients were collected.

RESULTS

TERT mutations were found in 30 patients, which were significantly associated with age, smoking history, sex, and metastasis (P < 0.05). Survival analyses showed that patients who carried TERT mutations had a poorer prognosis. Of the 30 TERT-mutation carriers, 17 harbored epidermal growth factor receptor (EGFR) mutations, which were significantly associated with sex, histopathology type, and metastasis (P < 0.05; overall survival [OS], 21 months; 95% confidence interval [CI], 8.153-33.847 months). Three TERT mutation patients harbored Kirsten rat sarcoma virus (KRAS) mutations, which were significantly associated with metastasis risk (P < 0.05), KRAS mutations carriers had a worse prognosis, with an OS of 10 months (95% CI, 8.153-33.847 months). Multivariate Cox regression analyses showed that age, cancer stage, and TERT mutation carrier status were independent risk factors for NSCLC, and the TERT mutation was 2.731 times higher than that without TERT mutation (95% CI, 1.689-4.418, P < 0.001).

CONCLUSIONS

TERT mutations were present in 11% of patients with NSCLC. TERT mutations were associated with age, smoking history, sex, and distant metastasis. Co-mutations in TERT and EGFR/KRAS indicated a poor prognosis. The co-mutations of TERT and EGFR differed according to sex, histopathology type, and metastasis, whereas TERT and KRAS co-mutations were only associated with patient metastasis. Age, cancer stage, and TERT mutation carrier status were independent risk factors for poor prognosis in patients with NSCLC.

The role of selected non-coding RNAs in the biology of non-small cell lung cancer

Lung cancer is the second most frequently diagnosed cancer worldwide and a leading cause of cancer-related deaths. Non-small cell lung carcinoma (NSCLC) represents 85% of all cases. Accumulating evidence highlights the outstanding role of non-coding RNA (ncRNA) in regulating the tumorigenesis process by modulating crucial signaling pathways. Micro RNA (miRNA), long non-coding RNA (lncRNA) and circular RNA (circRNA) are either up- or downregulated in lung cancer patients and can promote or suppress the progression of the disease. These molecules interact with messenger RNA (mRNA) and with each other to regulate gene expression and stimulate proto-oncogenes or silence tumor suppressors. NcRNAs provide a new strategy to diagnose or treat lung cancer patients and multiple molecules have already been identified as potential biomarkers or therapeutic targets. The aim of this review is to summarize the current evidence on the roles of miRNA, lncRNA and circRNA in NSCLC biology and present their clinical potential.

Deep learning combined with radiomics for the classification of enlarged cervical lymph nodes

PURPOSE

To investigate the application of deep learning combined with traditional radiomics methods for classifying enlarged cervical lymph nodes.

METHODS

The clinical and computed tomography (CT) imaging data of 276 patients with enlarged cervical lymph nodes (150 with lymph-node metastasis, 65 with lymphoma, and 61 with benign lymphadenopathy) who were treated at the hospital from January 2015 to January 2021 were retrospectively analysed. The patients were randomly divided into a training group and a test group at a ratio of 8:2. The radiomics features were extracted using one-by-one convolution and neural network activation, filtered with the least absolute shrinkage and selection operator (LASSO) model, and used to construct a discrimination model with PyTorch. Then, the performance of the model was compared with the radiologists' diagnostic performance. The neural network model was evaluated using the area under the receiver-operator characteristic curve (AUC), and the accuracy, sensitivity, and specificity were analysed.

RESULTS

A total of 102 features, comprising five traditional radiomic features and 97 deep learning features, were selected with LASSO and used to construct a discrimination model, which achieved a total accuracy of 87.50%. The AUC value, specificity, and sensitivity were, respectively, 0.92, 92.30%, and 90.00% for metastatic lymph nodes, 0.87, 95.45%, and 83.33% for benign lymphadenopathy, and 0.88, 90.47%, and 85.71% for lymphoma. The accuracies of the radiologists' diagnoses were 62.68% and 62.68%. The diagnostic performance of the model was significantly different from that of the radiologists (p < 0.05).

CONCLUSION

CT-based deep learning combined with the traditional radiomics methods has a high diagnostic value for the classification of cervical enlarged lymph nodes.

Loss of ARID1A expression is associated with systemic inflammation markers and has important prognostic significance in gastric cancer

BACKGROUND

The tumor suppressor gene AT-rich interactive domain 1A (ARID1A) and systemic inflammatory response (SIR) have been reported to be related to the sensitivity to immunotherapy. This study intended to explore the relationship between ARID1A expression and SIR, and to further elucidate the prognostic value of ARID1A expression in gastric cancer (GC).

METHODS

The mRNA and protein expression of ARID1A were detected in 272 formalin-fixed paraffin-embedded (FFPE) tumor tissues. The data of nine systemic inflammation markers were collected 1 week before gastrectomy. Univariate and multivariate COX analysis were used to screen out independent predictors of GC.

RESULTS

Negative expression of ARID1A protein was related to GC with deficient mismatch repair (dMMR) (p = 0.033), positive programmed cell death-ligand 1 (PD-L1) (p = 0.005) and lower albumin level (p = 0.0064). Low expression of ARID1A mRNA was common in GC with abnormal E-cadherin (p = 0.020) and a higher platelet/lymphocyte ratio (PLR) (p = 0.0391). Multivariate COX analysis showed that the expression of ARID1A protein (p = 0.023), age (p = 0.004), T stage (p = 0.009) and N stage (p = 0.009) were independent predictors of GC. The nomogram established by independent predictors can accurately evaluate the survival risk of patients with GC.

CONCLUSIONS

The loss of ARID1A protein expression was associated with the dMMR subtype and high expression of PD-L1 in GC. Negative ARID1A protein and low expression of mRNA were associated with aberrant systemic inflammatory markers. The expression of ARID1A protein had important prognostic significance in GC.