Identification of Cancer Stem Cell-related Gene by Single-cell and Machine Learning Predicts Immune Status, Chemotherapy Drug, and Prognosis in Lung Adenocarcinoma.

AIM: This study aimed to identify the molecular type and prognostic model of lung adenocarcinoma (LUAD) based on cancer stem cell-related genes. Studies have shown that cancer stem cells (CSC) are involved in the development, recurrence, metastasis, and drug resistance of tumors. METHOD: The clinical information and RNA-seq of LUAD were obtained from the TCGA database. scRNA dataset GSE131907 and 5 GSE datasets were downloaded from the GEO database. Molecular subtypes were identified by ConsensusClusterPlus. A CSC-related prognostic signature was then constructed via univariate Cox and LASSO Cox-regression analysis. RESULT: A scRNA-seq GSE131907 dataset was employed to obtain 11 cell clusters, among which, 173 differentially expressed genes in CSC were identified. Moreover, the CSC score and mRNAsi were higher in tumor samples. 18 of 173 genes were survival time-associated genes in both the TCGA-LUDA dataset and the GSE dataset. Next, two molecular subtypes (namely, CSC1 and CSC2) were identified based on 18 survival-related CSC genes with distinct immune profiles and noticeably different prognoses as well as differences in the sensitivity of chemotherapy drugs. 8 genes were used to build a prognostic model in the TCGA-LUAD dataset. High-risk patients faced worse survival than those with a low risk. The robust predictive ability of the risk score was validated by the time-dependent ROC curve revealed as well as the GSE dataset. TIDE analysis showed a higher sensitivity of patients in the low group to immunotherapy. CONCLUSION: This study has revealed the effect of CSC on the heterogeneity of LUAD, and created an 8 genes prognosis model that can be potentially valuable for predicting the prognosis of LUAD and response to immunotherapy.

Prediction scores of postoperative liver metastasis and long-term survival of pancreatic head cancer based on the distance between the mesenteric vessels and tumor, preoperative serum carbohydrate antigen 19-9 level, and lymph node metastasis rate.

BACKGROUND: The shortest distance between the superior mesenteric artery (SMA) or superior mesenteric vein (SMV) and the tumor margin was combined with preoperative serum carbohydrate antigen (CA) 19-9 and lymph node ratio (LNR) to evaluate joint effects on long-term survival and liver metastasis in patients with pancreatic head cancer after radical surgery. METHODS: This retrospective study included 149 patients who underwent pancreaticoduodenectomy for pancreatic head cancer at Harbin Medical University Tumor Hospital from May 2011 to March 2021. The preoperative serum CA 19-9 level and LNR were combined with the SMA or SMV distance. The joint association between long-term survival and postoperative liver metastasis was evaluated. RESULTS: Based on the receiver operating characteristic curve of postoperative liver metastasis or long-term survival, the optimal cut-off values of SMV distance were 3.1 and 0.7 mm, respectively, whereas the optimal cut-off value of SMA distance was 10.25 mm. The univariate model identified the liver metastasis score (p < 0.001) as a negative factor for postoperative liver metastasis of pancreatic head carcinoma. The SMV distance (p = 0.003), SMA distance (p < 0.001), LNR score (p < 0.001), and survival score (p < 0.001) were negatively correlated with long-term survival after pancreatic head cancer. The multivariate model highlighted SMA distance (p < 0.001), survival score (p = 0.001), and LNR score (p < 0.001) as independent risk factors for long-term survival in pancreatic head cancer. CONCLUSION: Liver metastasis score may be an independent predictor of postoperative liver metastasis in patients with pancreatic head cancer. Survival and LNR scores may be independent predictors of long-term postoperative survival in patients with pancreatic head cancer. However, the LNR score appears to improve long-term survival.

Inflammatory Markers Predict Survival in Patients With Advanced Gastric and Colorectal Cancers Receiving Anti-PD-1 Therapy.

There is a lack of useful biomarkers for predicting the efficacy of anti-programmed death-1 (PD-1) therapy for advanced gastric and colorectal cancer. To address this issue, in this study we investigated the correlation between inflammatory marker expression and survival in patients with advanced gastric and colorectal cancer. Data for 111 patients with advanced gastric and colorectal cancer treated with anti-PD-1 regimens were retrospectively analyzed. Neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and clinical characteristics of each patient were selected as the main variables. Overall response rate, disease control rate, and progression-free survival were primary endpoints, and overall survival and immune-related adverse events (irAEs) were secondary endpoints. The chi-squared test and Fisher's exact test were used to evaluate relationships between categorical variables. Uni- and multivariate Cox regression analyses were performed, and median progression-free survival and overall survival were estimated with the Kaplan-Meier method. The overall response rate and disease control rate of anti-PD-1therapy in advanced gastric and colorectal tumors were 12.61 and 66.66%, respectively. The patients with MLR < 0.31, NLR < 5, and PLR < 135 had a significantly higher disease control rate than those with MLR > 0.31, NLR > 5, and PLR > 135 (P < 0.05). The multivariate analysis revealed that MLR < 0.31, BMI > 18.5, and anti-PD-1 therapy in first-line were associated with prolonged PFS. MLR < 0.31 and BMI > 18.5 were associated with prolonged overall survival. The irAE rate differed significantly between PLR groups, and PLR < 135 was associated with an increased rate of irAEs (P = 0.028). These results indicate that the inflammatory markers NLR, MLR, and PLR have clinical utility for predicting survival or risk of irAEs in patients with advanced gastric cancer and colorectal cancer.