ABSTRACT
PURPOSE: A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I-III colon cancer. METHODS: A Treg-related prognostic classifier was built through a variety of bioinformatic methods, whose performance was assessed by KM survival curves, time-dependent receiver operating characteristic (tROC), and Harrell's concordance index (C-index). A prognostic nomogram was generated using this classifier and other traditional clinical parameters. Moreover, the predictive values of this classifier for immunotherapy and chemotherapy therapeutic efficacy were tested using multiple immunotherapy sets and R package "pRRophetic". RESULTS: A nine Treg-related classifier categorized CC patients into high- and low-risk groups with distinct RFS in the multiple datasets (all p < 0.05). The AUC values of 5-year RFS were 0.712, 0.588, 0.669, and 0.662 in the training, 1st, 2nd, and entire validation sets, respectively. Furthermore, this classifier was identified as an independent predictor of RFS. Finally, a nomogram combining this classifier and three clinical variables was generated, the analysis of tROC, C-index, calibration curves, and the comparative analysis with other signatures confirmed its predictive performance. Moreover, KM analysis exhibited an obvious discrepancy in the subgroups, especially in different TNM stages and with adjuvant chemotherapy. We detected the difference between the two risk subsets of immune cell sub-population and the response to immunotherapy and chemotherapy. CONCLUSIONS: We built a robust Treg-related classifier and generated a prognostic nomogram that predicts recurrence-free survival in stage I-III colon cancer that can identify high-risk patients for more personalized and effective therapy.
ABSTRACT
【Objective】 To select and identify miRNA signatures to predict TMB level in gastric cancer based on The Cancer Genome Atlas (TCGA) database and machine learning methods. 【Methods】 MiRNA expression and somatic mutation profiles of gastric cancer (GC) were downloaded from TCGA database. R "limma" package was performed to select differentially expressed miRNAs between high-TMB and low-TMB groups. Two machine learning algorisms, random forest (RF), and Support Vector Machine-Recursive Feature Elimination were utilized to identify miRNAs with the highest discriminative ability. ROC was used to test the predictive ability of these signatures in multiple datasets. Besides, immune cells of different TMB levels were compared by the CIBERSORT method. 【Results】 A total of 56 differentially expressed miRNAs (DE-miRNAs) were filtered. Functional enrichment analysis showed that these DE miRNAs are mainly enriched in signaling pathways related to tumor occurrence and development as well as immunity-related biological processes. The RF and SVM-RFE algorithms jointly identified 10 diagnostic features of miRNAs, among which only hsa-miR-210-3p is considered the most relevant predictive biomarker for TMB classification. The AUC value of hsa-miR-210-3p in the training, testing, and total sets is 0.822, 0.721, and 0.793, respectively, and has been validated in other cancer types. Besides, CIBERSORT analysis suggests differences in immune cell infiltration between high- and low-TMB groups. Meanwhile, there is a significant positive correlation between the expression of immune checkpoint related genes and mismatch repair related genes and hsa-miR-210-3p. 【Conclusion】 This study successfully identified hsa-miR-210-3p as a predictive biomarker for TMB classification, which can effectively predict TMB values in gastric cancer and other cancer patients and may provide some guidance for immunotherapy.
ABSTRACT
Breast cancer is the most common cancer type among female worldwide. Cisplatin (cDDP) is one of the most effective chemotherapies for the treatment of breast cancer. Nevertheless, there is an urgent requirement to reduce its systemic side effects and chemoresistance. In this present study, pivalopril (PP), a clinically used antihypertensive drug, has been verified as a chemosensitizer that extremely improves the sensitivity of breast cancer cells to cDDP. PP treatment markedly promoted the capacity of cDDP to reduce the proliferation of breast cancer cells. The combination of PP and cDDP significantly induced apoptosis and inhibited vascular endothelial growth factor (VEGF) expression in breast cancer cells, accompanied with reduced angiogenesis. Furthermore, PP plus cDDP effectively reduced the cell migration and invasion in breast cancer cells. The in vivo studies confirmed that the anti-metastatic effect of cDDP was further improved by PP, as evidenced by the markedly decreased number of metastatic nodules in lungs. Moreover, we confirmed that PP combined with cDDP cooperatively suppressed tumor growth in breast cancer xenograft mouse models without extra toxicity. Together, the present study provided the first evidence that PP greatly sensitized breast cancer cells to cDDP without additional toxicity, and the synergistic effect may be mainly through cooperatively inhibiting proliferation, angiogenesis, metastasis, and inducing apoptotic cell death.
Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Breast Neoplasms/drug therapy , Cisplatin/therapeutic use , Cyclopentanes/therapeutic use , Neovascularization, Pathologic/drug therapy , Animals , Apoptosis/drug effects , Breast Neoplasms/blood supply , Breast Neoplasms/pathology , Cell Line, Tumor , Cell Movement/drug effects , Cell Proliferation/drug effects , Female , Humans , Mice, Nude , Neoplasm Invasiveness , Neoplasm MetastasisABSTRACT
Objective To conduct a case-control study on the association of the nucleotide polymorphisms in the promoter region of the matrix metalloproteinase-9 (MMP-9) gene with phenotype of esophageal cancer. Methods All subjects were unrelated residents in northern regions of China. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis was used to determine the MMP-9 genotypes. Results The overall distribution of genotypes in the patients was not different from that in the controls (OR=0.77, 95% CI=0.45-1.34; P=0.36). There were no significant differences between the patients and the control subjects in terms of the distributions of sex and age, smoking status, alcohol dependence, pickled diet status, or history of environmental exposure. The patients were further examined with stratifications by age, sex, grade, depth of tumor invasion, lymphatic invasion, venous invasion and TNM staging. The results showed no pronounced association among the stratifications. Conclusion There is no significant association between the MMP-9 single nucleotide polymorphism genotypes and phenotype of esophageal cancer.
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Objective Systemic chemotherapy for metastatic pancreatic cancer is still a difficult problem in clinical practice. The standard chemotherapy of pancreatic cancer has been gemcitabine, but the response rate is low. Therefore, it is in urgent need to explore an effective clinical therapy for this cancer. This paper, a case report, is aimed at discussing the effectiveness of vinorelbine and cisplatin combined with endostatin as the first-line therapy for metastatic pancreatic cancer. Methods A 52-year-old female patient was diagnosed with pancreas cancer with liver metastasis at the time of the first visit to our hospital. Systemic chemotherapy with vinorelbine and cisplatin combined with endostatin was conducted. Results Liver metastases almost disappeared after the first cycle of chemotherapy. The primary tumor decreased by one third in size after four cycles and disappeared after the sixth cycle according to the CT scan evaluation. Conclusion Vinorelbine and cisplatin combined with endostatin can be a promising regimen for metastatic pancreatic cancer.
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Objective To study the identification rate of sentinel lymph node (SLN) in patients with breast cancer (BC) and the accuracy in predicting axillary lymph node(ALN) metastasis using methylene blue (MB) and patent blue violet (PBV) injection. Methods From October, 1999 to April, 2001, 94 patients with BC were selected for this study. Of them, 32 patients were injected with 1% MB and 62 patients with 1% PBV to identify SLN. All 94 patients underwent the axillary lymph node dissection. Results In MB group and PBV group , the SLN identification rate were 65.6% (21/32), 88.7% (55/62); the accuracy rate to predict axillary lymph node status were 90.5% (19/21), 98.2% (54/55) respectively. Conclusion Compared with MB ,PVB is the more ideal vital blue dye in identification of SNB.