NECTIN2 is a prognostic biomarker and potential therapeutic target in lung adenocarcinoma.

INTRODUCTION: NECTINs are transmembrane proteins mediating cell-to-cell adhesion. NECTINs interact with integrins or other membrane receptors to trigger multiple cellular functions. Aberrant NECTIN expression is associated with cancer progression and poor outcomes. While NECTIN2 is overexpressed in various cancer types, its role in lung cancer is not well understood. MATERIAL AND METHODS: We investigated the function of NECTIN2 in lung adenocarcinoma (LUAD) using the Cancer Genome Atlas (TCGA) dataset and clinical samples of 105 LUAD patients who had undergone surgical resection. Cell proliferation, apoptosis, migration and invasion were investigated using human lung adenocarcinoma cell lines. RESULTS: We found that high NECTIN2 expression correlated with reduced overall survival in LUAD in TCGA database. In clinical samples, high NECTIN2 expression was associated with lower recurrence-free survival in all patients (P < 0.001) and in stage I patients (P = 0.001). Functional analyses demonstrated that NECTIN2 knockout promoted cell apoptosis and diminished cell proliferation and migration capacity. NECTIN2 overexpression did not significantly affect cellular functions. DISCUSSION: Our results suggest that NECTIN2 plays a significant role in cell apoptosis and cancer cell migration, leading to increased postoperative recurrence. Furthermore, NECTIN2 serves as a prognostic indicator and a potential therapeutic target in LUAD. CONCLUSIONS: High NECTIN2 expression in LUAD was found to be associated with postoperative recurrence, and was observed to play an important role in cell apoptosis and migration.

Patient survey on cancer genomic medicine in Japan under the national health insurance system.

In Japan, comprehensive genomic profiling (CGP) tests have been reimbursed under the national health care system for solid cancer patients who have finished standard treatment. More than 50,000 patients have taken the test since June 2019. We performed a nation-wide questionnaire survey between March 2021 and July 2022. Questionnaires were sent to 80 designated Cancer Genomic Medicine Hospitals. Of the 933 responses received, 370 (39.7%) were web based and 563 (60.3%) were paper based. Most patients (784, 84%) first learned about CGP tests from healthcare professionals, and 775 (83.1%) gave informed consent to their treating physician. At the time of informed consent, they were most worried about test results not leading to novel treatment (536, 57.4%). On a scale of 0-10, 702 respondents (75.2%) felt that the explanations of the test result were easy to understand (7 or higher). Ninety-one patients (9.8%) started their recommended treatment. Many patients could not receive recommended treatment because no approved drugs or clinical trials were available (102/177, 57.6%). Ninety-eight patients (10.5%) did not wish their findings to be disclosed. Overall satisfaction with the CGP test process was high, with 602 respondents (64.5%) giving a score of 7-10. The major reason for choosing 0-6 was that the CGP test result did not lead to new treatment (217/277, 78.3%). In conclusion, satisfaction with the CGP test process was high. Patients and family members need better access to information. More patients need to be treated with genomically matched therapy.

Mobile element variation contributes to population-specific genome diversification, gene regulation and disease risk.

Mobile genetic elements (MEs) are heritable mutagens that recursively generate structural variants (SVs). ME variants (MEVs) are difficult to genotype and integrate in statistical genetics, obscuring their impact on genome diversification and traits. We developed a tool that accurately genotypes MEVs using short-read whole-genome sequencing (WGS) and applied it to global human populations. We find unexpected population-specific MEV differences, including an Alu insertion distribution distinguishing Japanese from other populations. Integrating MEVs with expression quantitative trait loci (eQTL) maps shows that MEV classes regulate tissue-specific gene expression by shared mechanisms, including creating or attenuating enhancers and recruiting post-transcriptional regulators, supporting class-wide interpretability. MEVs more often associate with gene expression changes than SNVs, thus plausibly impacting traits. Performing genome-wide association study (GWAS) with MEVs pinpoints potential causes of disease risk, including a LINE-1 insertion associated with keloid and fasciitis. This work implicates MEVs as drivers of human divergence and disease risk.