Yongchun Zhou

Epidermal growth factor receptor (EGFR) gene mutation stands as one of the most prevalent driver genetic alterations in non-small cell lung cancer (NSCLC). While targeted therapies against EGFR have substantially enhanced patient prognosis, acquired resistance remains a core challenge that limits therapeutic efficacy. Patients with stage IV NSCLC generally exhibit a dismal prognosis, with only about 7% of those with stage IVB disease surviving beyond five years. Herein, we report a case of a 47-year-old female patient diagnosed with advanced lung adenocarcinoma, whose clinical course has persisted for nearly a decade. Initial genetic testing identified an EGFR exon 19 deletion (19del). Following treatment with osimertinib, the patient developed concurrent cis-arranged EGFR T790M/C797S double mutations and a neurotrophic receptor tyrosine kinase 1 (NTRK1) gene rearrangement. Subsequently, through a multimodal therapeutic strategy integrating local intervention, radiation therapy, and targeted therapy, the patient’s disease has been sustainably controlled for several years, and she remains alive with stable clinical status to date. NTRK1 fusions are a well-defined mechanism of acquired resistance to EGFR-TKIs, but they are uncommon. This case reports a KIF26B-NTRK1 rearrangement not previously described in lung cancer; however, its functional significance remains to be confirmed. The principal value of this report lies in the completeness of the longitudinal molecular and clinical record, which documents how an on-target mutation and a bypass rearrangement can coexist and persist.

Lung cancer is the world's leading cause of cancer deaths. Early detection through low-cost metabolite screening approaches could reduce lung cancer mortality. Here we report the results of a large-scale, quantitative metabolomics study aimed at identifying plasma biomarkers for lung cancer detection in a Chinese population. A cohort of 410 patients, including 137 healthy controls, 189 biopsy-confirmed individuals with stage I/II lung cancer, and 84 individuals with biopsy-confirmed stage III/IV cancer, were studied. Plasma samples were collected and analyzed using an in-house-developed, targeted liquid chromatography-mass spectrometry (LC-MS) metabolomics method that detects and quantifies 138 metabolites. Logistic regression was used to develop an optimal biomarker panel that could distinguish all-stage lung cancer patients from healthy controls. The resulting six-metabolite panel achieved an area under the curve (AUC) of 95.0%. A second biomarker panel was developed to distinguish early-stage lung cancer from healthy controls and reached an AUC of 94.3%. All models were developed on an initial training set and then fully validated on a separate holdout set. Our proposed biomarker models show significant improvements over previously published models for metabolite-based lung cancer diagnosis and detection. These metabolite biomarker panels are intended for the development of a low-cost, minimally invasive blood test for lung cancer screening in China.

Objective: This study aims to identify key genes that are common to both breast cancer and thyroid cancer, as well as to determine shared therapeutic targets relevant to both conditions. Methods: We utilized transcriptome data from both breast and thyroid cancers, along with single-cell data, and applied cell deconvolution techniques to evaluate the extent of monocyte infiltration. Tumor-related gene modules were identified through weighted gene co-expression network analysis (WGCNA), followed by enrichment analysis to uncover significant signals shared within these gene modules. A machine learning approach was then employed to pinpoint hub genes. Additionally, RT-qPCR was performed to validate the expression levels of these hub genes in tumor and adjacent non-tumor tissues from patients with both cancer types. Results: Our analyses revealed that the transcriptional networks of breast cancer and thyroid cancer display significant similarities. WGCNA identified two consensus modules that are strongly associated with both cancers and monocyte infiltration. Enrichment analysis highlighted glycosaminoglycan synthesis pathways as critical signals that are common to both cancers. A total of seven hub genes were identified using the machine-learning approach. Results from RT-qPCR and immunohistochemistry in clinical samples showed that the expression levels of PILRA, Mki67, and UBE2C were markedly different between cancerous and adjacent tissues. Conclusion: PILRA, MKI67, and UBE2C, as potential diagnostic and prognostic biomarkers, are anticipated to serve as promising therapeutic targets for the clinical management of both breast cancer and thyroid cancer.

Importance: Patients with EGFR mutations who have advanced-stage non-small cell lung cancer (NSCLC) already receive tyrosine kinase inhibitors (TKIs) as the standard first-line therapy. Notably, Yunnan is a regional high incidence area of lung cancer in the highlands with a high rate of rare EGFR mutations. Overall, lung cancer patients in Xuanwei may present a distinct subgroup globally. Recent studies suggested that the NSCLC cohort in Xuanwei harbored a significantly higher uncommon mutation rate. However, little was known about the clinicopathological features and treatment efficacy of EGFR-TKI in Yunnan NSCLC patients.Objective: This study aimed to investigate the clinical impact of histologic type on the survival outcomes of patients with stage IIIB and IV NSCLC receiving EGFR-TKI treatment of Yunnan in southwestern China.Methods: In this retrospective study, we enrolled advanced NSCLC patients (IIIB-IV) with EGFR mutations who were first diagnosed and treated at Yunnan Cancer hospital from January 2016 to December 2019. Sociodemographics, lifestyle, survival, and clinicopathological characteristics of the patients were collected. The Kaplan-Meier method was used to assess the OS and PFS of patients. An analysis of prognostic factors was conducted using Cox regression.Results: A total of 468 eligible patients were included. The median progression-free survival (PFS) and overall survival(OS) were 11.30(95% CI, 10.12-12.48) months and 30.30(95% CI, 26.24-34.36) months. Based on survival analysis among all the patients,females(HR=0.815;95% CI:0.671-0.989; P=0.017), Xuanwei origin (HR=0.776; 95% CI: 0.609-0.989; P=0.040), sample types(HR=0.780; 95% CI: 0.642-0.947; P=0.012) had a longer PFS. Multivariable analysis showed that only the sample type was an independent factor on median PFS with EGFR-TKI therapy. Patients less than 60 years old (HR=1.433; 95% CI:1.134-1.812, P=0.003)had better OS, but objectives with BMI≥24kg/m²(HR=0.653; 95% CI: 0.500-0.864; P=0.002), females(HR=0.776; 95% CI:0.613-0.982; P=0.035)and patients with tissue sample type (HR=0.760; 95% CI:0.600-.0961; P=0.022) had better OS. Notably, subgroup analysis of our study also found that PFS was significantly better in patients with G719X, L861Q, S768I, G719X+L861Q, and G719X+S768I in Xuanwei than classical mutation ones, including 19-Del and L858R (median 22.7 vs. 12.0 months, HR=0.523, P=0.010), while PFS was inferior in patients with rare mutations of EGFR in non-Xuanwei than the classical mutation ones (median 5.10 vs. 11.10 months, HR=1.760, P=0.015).Conclusion: NSCLC patients in Yunnan displayed a unique EGFR mutation profile, especially a higher prevalence of EGFR uncommon and compound mutations subtype. This study indicates prognostic factors of NSCLC treated with EGFR-TKI in Yunan and Xuanwei. This study will provide new clinical evidence for EGFR-TKI-targeted therapy in patients with rare EGFR mutations in China and worldwide. More researchs were needed for NSCLC EGFR-TKI therapy and medical insurance policy-making in Yunnan, Xuanwei area and uncommon especially.

Background: China’s southwestern region, Qujing, harbors a high incidence of non-small cell lung cancer (NSCLC) and related mortality. This study was designed to reveal the impact of an immune-related prognostic signature (IRPS) on advanced NSCLC in the Qujing.Methods: Tissue specimens from an independent cohort of 37 patients with advanced NSCLC were retrospectively evaluated to determine the relationship between the IRPS estimated by next-generation sequencing (NGS) and clinical outcome. To compare the IRPS in tissue and the clinical outcomes between Qujing and non-Qujing populations, we analyzed datasets of 23 patients with advanced NSCLC from The Cancer Genome Atlas (TCGA) database. In addition, an independent cohort (n=111) of blood specimens was retrospectively analyzed to determine the relationship between the IRPS and clinical outcome. Finally, we evaluated the utility of the blood IRPS in classifying 24 patients with advanced NSCLC who might benefit from immunotherapy.Results: In cohort 1, the Qujing population with tTMB-H (≥ 10 mutations/Mb) or KRAS mutations had shorter progression-free survival (PFS) (hazard ratio [HR] 0.37, 0.14 to 0.97, P = 0.04; HR 0.23, 0.08 to 0.66, P < 0.01) and overall survival (OS) (HR 0.05, 0.01 to 0.35, P < 0.01; HR 0.22, 0.07 to 0.66, P < 0.01). In cohort 2 of the Qujing population, bTMB-H (≥ 6 mutations per Mb) and KRAS mutations were related to PFS (HR 0.59, 0.36 to 0.99, P = 0.04; HR 0.50, 0.26 to 0.98, P = 0.04) and OS (HR 0.58, 0.35 to 0.96, P = 0.03; HR 0.48, 0.25 to 0.93, P = 0.03). Notably, the Qujing population with bTMB-H had superior PFS (HR 0.32, 0.09 to 1.09, P = 0.01), OS (HR 0.33, 0.10 to 1.13, P < 0.01) and objective response rates (ORRs) (83.3% vs. 14.3% vs. 20.0%, P <0.01) to immunotherapy than other populations.Conclusions: These findings show that tTMB, bTMB and KRAS mutations appear to be independent validated IRPSs that predict the clinical outcomes of Qujing populations with advanced NSCLC and that bTMB may be used as a reliable IRPS to predict the clinical benefit from anti-PD-1 therapies among populations from Qujing with advanced NSCLC.

Purpose: Lung adenocarcinoma (LUAD) is the most common type of cancer and the leading cause of cancer-related death worldwide, resulting in a huge economic and social burden. MiRNA-195-5p plays crucial roles in the initiation and progression of cancer. However, the significance of the miRNA-195-5p/polypyrimidine tract-binding protein 1 (miRNA-195-5p/PTBP1) axis in the progression of lung adenocarcinoma (LUAD) remains unclear.Methods: Data were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The starBase database was employed to examine the expression of miRNA-195-5p, while the Kaplan–Meier plotter, UALCAN, and Gene Expression Profiling Interactive Analysis (GEPIA) databases were utilized to analyze the tumor stage and prognostic value of miRNA and PTBP1. Quantitative reverse transcription-polymerase chain reaction assay was conducted to detect the expression levels of miRNA-195-5p in LUAD cell lines and tissues. The effects of miRNA-195-5p on cell proliferation and migration were examined using the cell growth curve, clone information, transwell assays, and wound healing assays.Results: We found that miRNA-195-5p was down-regulated in LUAD cancer and cell lines. Importantly, its low levels were related to the tumor stage, lymph node metastasis, and poor prognosis in LUAD. Overexpression of miR-195-5p significantly inhibited cell growth and migration promotes cell apoptosis. Further study revealed that PTBP1 is a target gene of miRNA-195-5p, and overexpression of miRNA-195-5p inhibited the progression of LUAD by inhibiting PTBP1 expression. MiRNA-195-5p expression was related to immune infiltration in lung adenocarcinoma. Moreover, PTBP1 was negatively correlated with diverse immune cell infiltration and drug sensitivity.Conclusion: Our findings uncover a pivotal mechanism that miRNA-195-5p by modulate PTBP1 expression to inhibit the progression of LUAD. MiRNA-195-5p could be a novel diagnostic and prognostic molecular marker for LUAD.

Objective: Lung cancer is the most common malignancy worldwide and exhibits both high morbidity and mortality. In recent years, scientists have made substantial breakthroughs in the early diagnosis and treatment of lung adenocarcinoma (LUAD), however, patient prognosis still shows vast individual differences. In this study, bioinformatics methods were used to identify and analyze ferroptosis-related genes to establish an effective signature for predicting prognosis in LUAD patients. Methods: The gene expression profiles of LUAD patients with complete clinical and follow-up information were downloaded from two public databases, univariate Cox regression and multivariate Cox regression analysis were used to obtain ferroptosis-related genes for constructing the prognos tic risk model, AUC and calibration plot were used to evaluate the predictive accuracy of the FRGS and nomogram. Results: A total of 74 ferroptosis-related differentially expressed genes (DEGs) were identi fied between LUAD and normal tissues from The Cancer Genome Atlas (TCGA) database. A five-gene panel for prediction of LUAD prognosis was established by multivariate regression and was verified using the GSE68465 cohort from the Gene Expression Omnibus (GEO) database. Patients were divided into two different risk groups according to the median risk score of the five genes. Based on Kaplan-Meier (KM) analysi, the OS rate of the high-risk group was markedly worse than that of the low-risk group. We also found that risk score was an independent prognostic indicator. The receiver operating characteristic ROC curve showed that the proposed model had good prediction ability. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses indicated that risk score was prominently enriched in ferroptosis processes. Moreover, at the score of immune-associated gene sets, significant differences were found between the two risk groups. Conclusions: This study demonstrated that ferroptosis-related gene signatures can be used as a potential predictor for the prognosis of LUAD, thus providing a novel strategy for individualized treatment in LUAD patients.

Purpose: To explore the impact between the tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) expression on NSCLC in the Yunnan region of southwestern China. Patients and Methods: Seventy-one NSCLC specimens that were pathologically confirmed were collected at first. The TMB and driver genetic alterations were evaluated accordingly by next-generation sequencing (NGS). Afterwards, clinical parameters and tumor PD-L1 expressions were collected. Finally, the relationship between TMB, PD-L1 expression and clinical outcome was evaluated. Results: The median TMB was 5 (0.6– 49) mutations/Mb by our NGS panel and the majority of patients (63/71, 88.7%) did not receive immunotherapy. The progression-free survival (PFS) was longer in TMB-low patients versus TMB-high ones (median 18.0 vs. 9.0 months, hazard ratio = 0.34, 95% confidence interval 0.14 to 0.84, p = 0.02) and the cut-off value was 10 mutations/Mb. The overall survival (OS) was longer in TMB-low patients vs. TMB-high ones (median 21.0 vs. 10.0 months, HR = 0.32, 95% CI 0.12 to 0.82, p = 0.02). Notably, our study also found that, excluding the eight patients with immunotherapy, the PFS was longer in patients with TMB-low vs. TMB-high (median 19.0 vs. 8.0 months, HR = 0.11, 95% CI 0.03 to 0.39, p < 0.01) and the OS was longer in TMB-low patients vs. TMB-high (median 21.0 vs 10.0 months, HR = 0.12, 95% CI 0.03 to 0.42, p < 0.01). Conclusion: TMB was a valid and independent prognostic biomarker for NSCLC patients’ clinical outcome and comprehensive screening of TMB based on NGS is recommended for individualized treatment strategies in Yunnan population.