Identification and validation of critical alternative splicing events and splicing factors in gastric cancer progression.

Gene expression and alternative splicing (AS) interact in complex ways to regulate biological process which is associated with cancer development. Here, by integrated analysis of gene expression and AS events, we aimed to identify the hub AS events and splicing factors relevant in gastric cancer development (GC). RNA-seq data, clinical data and AS events of 348 GC samples were obtained from the TCGA and TCGASpliceSeq databases. Cox univariable and multivariable analyses, KEGG and GO pathway analyses were performed to identify hub AS events and splicing factor/spliceosome genes, which were further validated in 53 GCs. By bioinformatics methods, we found that gene AS event- and gene expression-mediated GC progression shared the same mechanisms, such as PI3K/AKT pathway, but the involved genes were different. Though expression of 17 hub AS events were confirmed in 53 GC tissues, only 10 AS events in seven genes were identified as critical candidates related to GC progression, notably the AS events (Exon Skip) in CLSTN1 and SEC16A. Expression of these AS events in GC correlated with activation of the PI3K/AKT pathway. Genes with AS events associated with clinical parameters and prognosis were different from the genes whose mRNA levels were related to clinical parameters and prognosis. Besides, we further revealed that QKI and NOVA1 were the crucial splicing factors regulating expression of AS events in GC, but not spliceosome genes. Our integrated analysis revealed hub AS events in GC development, which might be the potential therapeutic targets for GC.

Discovering the molecular differences between right- and left-sided colon cancer using machine learning methods.

BACKGROUND: In recent years, the differences between left-sided colon cancer (LCC) and right-sided colon cancer (RCC) have received increasing attention due to the clinicopathological variation between them. However, some of these differences have remained unclear and conflicting results have been reported. METHODS: From The Cancer Genome Atlas (TCGA), we obtained RNA sequencing data and gene mutation data on 323 and 283 colon cancer patients, respectively. Differential analysis was firstly done on gene expression data and mutation data between LCC and RCC, separately. Machine learning (ML) methods were then used to select key genes or mutations as features to construct models to classify LCC and RCC patients. Finally, we conducted correlation analysis to identify the correlations between differentially expressed genes (DEGs) and mutations using logistic regression (LR) models. RESULTS: We found distinct gene mutation and expression patterns between LCC and RCC patients and further selected the 30 most important mutations and 17 most important gene expression features using ML methods. The classification models created using these features classified LCC and RCC patients with high accuracy (areas under the curve (AUC) of 0.8 and 0.96 for mutation and gene expression data, respectively). The expression of PRAC1 and BRAF V600E mutation (rs113488022) were the most important feature for each model. Correlations of mutations and gene expression data were also identified using LR models. Among them, rs113488022 was found to have significance relevance to the expression of four genes, and thus should be focused on in further study. CONCLUSIONS: On the basis of ML methods, we found some key molecular differences between LCC and RCC, which could differentiate these two groups of patients with high accuracy. These differences might be key factors behind the variation in clinical features between LCC and RCC and thus help to improve treatment, such as determining the appropriate therapy for patients.

[Clinical study of reduced-port laparoscopy-assisted resection for cancer at the sigmoid colon and upper rectum].

OBJECTIVE: To explore the safety and feasibility of reduced-port laparoscopic-assisted resection for cancer at the sigmoid colon and upper rectum. METHODS: Clinical data of 70 patients with sigmoid colon or upper rectal cancer undergoing laparoscopic-assisted resection in our department from February 2013 to July 2014 were retrospectively reviewed. Patients were divided into reduced-port group (44 cases, 3 or 4 ports) and conventional group (26 cases, 5 ports). The operative time, blood loss, retrieved lymph nodes, postoperative exhaust recovery, dietary recovery, hospital stay and morbidity of complication were compared between two the groups. RESULTS: No significant differences were observed in operative time [(144.0 ± 40.1) min vs. (115.8 ± 30.8) min], blood loss [(72.9 ± 50.2) ml vs. (45.5 ± 52.4) ml], number of retrieved lymph nodes [(10.2 ± 8.4) vs. (12.0 ± 5.6)], time to bowel function return [(3.2 ± 0.7) d vs. (2.8 ± 0.8) d], time to liquid diet [(4.2 ± 1.1) d vs. (3.8 ± 0.9) d], time to semisolid diet [(8.6 ± 2.1) d vs (8.1 ± 1.7) d], and postoperative hospital stay [(13.0 ± 3.4) d vs. (12.8 ± 7.2) d] between two groups (all P>0.05). Complication rate of conventional group and the reduced-port group was 15.4% and 7.2% without significant difference (P=0.233). CONCLUSIONS: For cancer at the sigmoid colon and upper rectum, reduced-port laparoscopic surgery is feasible, safe and radical as the five-port in terms of technical and oncologic issues. These two procedures have the same short-term outcome.