Background: Lung cancer is the leading cause of cancer-related death worldwide. Few effective biomarkers for lung adenocarcinoma have been adapted for clinical practice to assist in prognosis evaluation and treatment plan implementation. Our study’s goal was to find a new biological marker associated with the prognosis of lung adenocarcinoma after curative resection and the benefit of adjuvant chemotherapy (ACT). Methods: Using the clinical information and RNA-Seq expression from The Cancer Genome Atlas (TCGA) database, prognostic genes were screened out and analyzed by Subpopulation Treatment Effect Pattern Plot (STEPP) in GSE42127 to filter out the drug-related gene. The relationship between the gene expression and clinicopathological parameters was assessed in the TCGA database. The prognostic significance was evaluated by Cox proportional hazards (PHs) regression analysis with 1,000 bootstrap replications. Gene set enrichment analysis (GSEA) was performed using high-throughput RNA sequencing data in TCGA and functional gene sets derived from the Molecular Signatures Database (MSigDB). Results: A total of 297 prognostic genes were analyzed by STEPP in GSE42127. The results indicated a beneficial effect of adjuvant paclitaxel-carboplatin in patients with high TMEM213 expression. Its expression correlated with gender (P=0.013), and Kaplan-Meier analysis showed that patients with high TMEM213 expression had significantly longer overall survival (OS) (P=0.014, 0.027, and 0.000). Multivariate analysis showed TMEM213 to be an independent predictor for improved OS of patients (P=0.020), and the result was verified with the bootstrapping methodology and online “Kaplan-Meier Plotter” database analysis. Moreover, enriched pathway analysis indicated that TMEM213 expression was associated with the two gene sets of KEGG_DRUG_METABOLISM_CYTOCHROME_P450 and KEGG_ABC_TRANSPORTERS. Conclusions: Based on bioinformatics analysis, we found that TMEM213 expression independently predicted better OS for lung adenocarcinoma. Patients in the high TMEM213 group appear to benefit more from adjuvant paclitaxel-carboplatin, but this needs further validation.

To establish a pre-therapy prognostic index model (PIM) of the first-line chemotherapy aiming to achieve accurate prediction of time to progression (TTP) and overall survival among the patients diagnosed with locally advanced (stage III) or distant metastasis (stage IV) lung squamous cell carcinoma (LSCC).

Intestinal-type gastric cancer (IGC) is associated with a multi-step carcinogenic process, comprising non-atrophic gastritis, chronic atrophic gastritis, intestinal metaplasia, and gastric dysplasia. The risk of developing IGC gradually increases as the disease progresses. However, the origin of cell differentiation and its carcinogenic potential in different stages of gastric disease remains poorly understood. To address this issue, we analyzed the differentiation trajectory of epithelial cells in different disease stages from gastric antrum biopsies in patients with precancerous lesions and early GC using single-cell sequencing data. Our findings revealed that progenitor cells (PCs) act as the ancestors of antral gland mucous cells (GMCs) and pit mucous cells (PMCs) in the NAG/CAG stage. In the IM stage, GMCs, as well as PCs, may acquire the ability to become intestinal-like stem cell phenotypes, eventually differentiating into mature enterocyte cells. Secretory progenitor cells may differentiate into pre-secretory cells and goblet cells. In the early IGC stage, KIAA0101⁺PRAP1⁺ PCs may be the potential origin of early IGC. These findings provide valuable insights for further research into the molecular mechanisms underlying the development of IGC and may contribute to the development of novel prevention and treatment strategies.

E15570 Background: Gastric cancer is a leading cause of cancer death worldwide, and its prognostic factors remain unclear. TNM staging was used to predict the prognosis of GC, however, it cannot meet current demands. To improve prediction efficiency, a model that reflects both tumor-related factor and host's local immune response in tumor microenvironment (TME) is needed. Immune checkpoint proteins regulate T-cell function to promote cancer immune escape. PDL1/PD-1 pathway, one of the immune checkpoint pathways, has become a new target in cancer treatment. Here, we aimed to illuminate the prognostic roles of immune checkpoint protein in GC. Methods: Immune checkpoint proteins expressed in tumor microenvironment (TME) were detected by IHC staining. Survival analysis was performed by the Kaplan-Meier method. A prognostic model was constructed from 174 gastric cancer patients using a scoring system, which was based on hazard ratios in a Cox proportional hazard model. Results: We examined PD-L1, PD-1, CD8 protein expression in TME from 174 GC patients (pts), and explored their effects on pt’s overall survival (OS). Our results showed that TC PD-L1⁺ was associated with better clinical outcomes, including longer OS et al (P < 0.05). However, PD-L1⁺ or PD-1⁺ IC was correlated with poorer OS (P = 0.0244, P = 0.024). Furthermore, multivariate analysis identified PD-L1⁺ TC, PD-L1⁺ IC, PD-1⁺ IC, CD8^high IC, lauren classify, lymphatic invasion and AJCC stage were independent prognostic factors. A prognostic model was established by combination of these factors. Patients were categorized into low-/median-/high-risk groups according to their scores, and the 5-year survival rates were 96%, 56.23% and 18.36%, respectively (P < 0.0001). Our seven-factors prognostic model yielded an area under the ROC curve (AUC) of 0.855 for prediction of mortality at 5 years, which was superior to TNM stage with an AUC of 0.685. Conclusions: This study showed a prognostic model based on different prognostic roles of immune checkpoint proteins, which was more accuracy than TNM staging and might provide guidance for immunotherapy options in GC.