Background: A growing amount of evidence has suggested the clinical importance of stromal and immune cells in the gastric cancer microenvironment. However, reliable prognostic signatures based on assessments of stromal and immune components have not been well-established. This study aimed to develop a stromal-immune score-based gene signature in gastric cancer. Methods: Stromal and immune scores were estimated from transcriptomic profiles of a gastric cancer cohort from TCGA using the ESTIMATE algorithm. A robust partial likelihood-based Cox proportional hazard regression model was applied to select prognostic genes and to construct a stromal-immune score-based gene signature. Two independent datasets from GEO were used for external validation. Results: Favorable overall survivals were found in patients with high stromal score (p = 0.014) and immune score (p = 0.045). Forty-five stromal-immune score-related differentially expressed genes were identified. Using a robust partial likelihood-based Cox proportional hazard regression model, a gene signature containing SOX9, LRRC32, CECR1, and MS4A4A was identified to develop a risk stratification model. Multivariate analysis revealed that the stromal-immune risk score was an independent prognostic factor (p = 0.018). Based on the risk stratification model, the cohort was classified into three groups yielding incremental survival outcomes (log-rank test p = 0.0004). A nomogram integrating the risk stratification model and clinicopathologic factors was developed. Calibration and decision curves showed a better performance and net benefits for the nomogram. Similar findings were validated in two independent cohorts. Conclusion: The stromal-immune score-based gene signature represents a prognosis stratification tool in gastric cancer.

Increasing evidences have found that the clinical importance of the interaction between hypoxia and immune status in gastric cancer microenvironment. However, reliable prognostic signatures based on combination of hypoxia and immune status have not been well-established. This study aimed to develop a hypoxia-immune-based gene signature for risk stratification in gastric cancer. Hypoxia and immune status was estimated with transcriptomic profiles for a discovery cohort from GEO database using the t-SNE and ESTIMATE algorithms, respectively. The Cox regression model with the LASSO method was applied to identify prognostic genes and to develop a hypoxia-immune-based gene signature. The TCGA cohort and two independent cohorts from GEO database were used for external validation. Low hypoxia status (p < 0.001) and high immune status (p = 0.005) were identified as favorable factors for patients’ overall survival. By using the LASSO model, four genes, including CXCR6, PPP1R14A and TAGLN, were identified to construct a gene signature for risk stratification. In the discovery cohort (n = 357), patients with low risk yielded better outcomes than those with high risk regarding overall survival across and within TNM stage subgroups. Multivariate analysis identified the hypoxia-immune-based gene signature as an independent prognostic factor (p < 0.001). A nomogram integrating the gene signature and known risk factors yielded better performance and net benefits in calibration and decision curve analyses. Similar results were validated in the TCGA (n = 321) and two independent GEO (n = 300 and n = 136, respectively) cohorts. The hypoxia-immune-based gene signature represents a promising tool for risk stratification tool in gastric cancer. It might serve as a prognostic classifier for clinical decision-making regarding individualized prognostication and treatment, and follow-up scheduling.

Colorectal cancer (CRC) is one of the most common malignancies worldwide with poor prognosis. Studies have showed that abnormal microRNA (miRNA) expression can affect CRC pathogenesis and development through targeting critical genes in cellular system. However, it is unclear about which miRNAs play central roles in CRC’s pathogenesis and how they interact with transcription factors (TFs) to regulate the cancer-related genes. To address this issue, we systematically explored the major regulation motifs, namely feed-forward loops (FFLs), that consist of miRNAs, TFs and CRC-related genes through the construction of a miRNA-TF regulatory network in CRC. First, we compiled CRC-related miRNAs, CRC-related genes, and human TFs from multiple data sources. Second, we identified 13,123 3-node FFLs including 25 miRNA-FFLs, 13,005 TF-FFLs and 93 composite-FFLs, and merged the 3-node FFLs to construct a CRC-related regulatory network. The network consists of three types of regulatory subnetworks (SNWs): miRNA-SNW, TF-SNW, and composite-SNW. To enhance the accuracy of the network, the results were filtered by using The Cancer Genome Atlas (TCGA) expression data in CRC, whereby we generated a core regulatory network consisting of 58 significant FFLs. We then applied a hub identification strategy to the significant FFLs and found 5 significant components, including two miRNAs (hsa-miR-25 and hsa-miR-31), two genes (ADAMTSL3 and AXIN1) and one TF (BRCA1). The follow up prognosis analysis indicated all of the 5 significant components having good prediction of overall survival of CRC patients. In summary, we generated a CRC-specific miRNA-TF regulatory network, which is helpful to understand the complex CRC regulatory mechanisms and guide clinical treatment. The discovered 5 regulators might have critical roles in CRC pathogenesis and warrant future investigation.

It is still controversial whether laparoscopy-assisted colectomy (LAC) is suitable for patients with stage T4 colon cancer. This study aimed to compare the short- and long-term outcomes of LAC and open colectomy (OC) for patients with pathologic T4 colon cancer. Data of eligible patients with colon cancer in our institution from March 2004 to September 2014 were retrospectively reviewed. The patients were followed up to September 2016. Propensity score matching was performed to control the bias. Two hundred and forty two patients were selected by propensity score matching, with 121 patients in the LAC group and 121 in the OC group. Mean operating time and rate of intraoperative blood transfusion were similar between two groups. In LAC group, shorter time to first flatus and first liquid intake were observed in patients with pT4b stage disease, but not for patients with pT4a stage disease. Less blood loss and shorter length of postoperative hospital stay were examined in LAC group, including pT4a and pT4b stages. Conversion was required in 9.1% (11 out of 121) cases. DFS and OS were similar between LAC and OC groups. The 5-year DFS rate was 64.2% for pT4a stage and 35.5% for pT4b stage in LAC group, and 62.9% and 33.7% in OC group for pT4a (p = 0.374) and pT4b (p = 0.385) stage respectively. For 5-year OS rates, two groups did not differ in pT4a stage (LAC 69.2% vs. OC 66.0%, p = 0.151) and pT4b stage (LAC 37.5% vs. OC 38.1%, p = 0.510). Laparoscopic colectomy appears to be safe for selected patients with pT4 colon cancer in centres with expertise in minimally invasive surgery.

Background: It is well known that neoadjuvant radiotherapy could reduce local recurrence followed by surgical resection. However, evidence about oncologic efficacy of radiotherapy and survival benefit of adjuvant chemotherapy after neoadjuvant radiotherapy is still lacking.Methods: This retrospective propensity score-matched cohort study identified patients with pathologically confirmed rectal cancer and receiving surgery with curative intent from the Surveillance, Epidemiology, and End Results database from 2004 through 2014. Overall survival was compared using the stratified log-rank test. Multivariate Cox regression analysis was used for identifying risk factor and developing prediction nomogram.Results: A total of 22,008 (11,004 for each group) propensity-matched patients were identified. In the context of receiving adjuvant chemotherapy after surgical resection, there was no significant difference in terms of overall survival between surgery alone group and neoadjuvant radiotherapy and surgery group, whether for stage I (log-rank test p = 0.467), stage II (log-rank test p = 0.310), or stage III (p = 0.994). In case of receiving a prior combination therapy of neoadjuvant radiotherapy and surgery, the following adjuvant chemotherapy could significantly improve overall survival for patients with stage I (log-rank test p &lt;0.001), stage II (log-rank test p = 0.038), and stage III (log-rank test p = 0.014). Nomogram integrating clinicopathologic factors was developed to predict survival benefit associated with neoadjuvant radiotherapy. Calibration and ROC curves validated promising performance for the nomogram.Conclusion: Patients with rectal cancer underwent neoadjuvant radiotherapy yield acceptable outcomes and are more likely to benefit from adjuvant chemotherapy in terms of overall survival. These data would be evidential for advocating consistency in guideline adherence to the use of adjuvant chemotherapy after neoadjuvant radiotherapy.