Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment.

BACKGROUND: The perineural invasion (PNI)-mediated inflammation of the tumor microenvironment (TME) varies among gastric cancer (GC) patients and exhibits a close relationship with prognosis and immunotherapy. Assessing the neuroinflammation of TME is important in predicting the response to immunotherapy in GC patients. METHODS: Fifteen independent cohorts were enrolled in this study. An inflammatory score was developed and validated in GC. Based on PNI-related prognostic inflammatory signatures, patients were divided into Clusters A and B using unsupervised clustering. The characteristics of clusters and the potential regulatory mechanism of key genes were verified by RT-PCR, western-blot, immunohistochemistry and immunofluorescence in cell and tumor tissue samples.The neuroinflammation infiltration (NII) scoring system was developed based on principal component analysis (PCA) and visualized in a nomogram together with other clinical characteristics. RESULTS: Inflammatory scores were higher in GC patients with PNI compared with those without PNI (P < 0.001). NII.clusterB patients with PNI had abundant immune cell infiltration in the TME but worse prognosis compared with patients in the NII.clusterA patients with PNI and non-PNI subgroups. Higher immune checkpoint expression was noted in NII.clusterB-PNI. VCAM1 is a specific signature of NII.clusterB-PNI, which regulates PD-L1 expression by affecting the phosphorylation of STAT3 in GC cells. Patients with PNI and high NII scores may benefit from immunotherapy. Patients with low nomogram scores had a better prognosis than those with high nomogram scores. CONCLUSIONS: Inflammation mediated by PNI is one of the results of tumor-nerve crosstalk, but its impact on the tumor immune microenvironment is complex. Assessing the inflammation features of PNI is a potential method in predicting the response of immunotherapy effectively.

Neurotransmitters: promising immune modulators in the tumor microenvironment.

The tumor microenvironment (TME) is modified by its cellular or acellular components throughout the whole period of tumor development. The dynamic modulation can reprogram tumor initiation, growth, invasion, metastasis, and response to therapies. Hence, the focus of cancer research and intervention has gradually shifted to TME components and their interactions. Accumulated evidence indicates neural and immune factors play a distinct role in modulating TME synergistically. Among the complicated interactions, neurotransmitters, the traditional neural regulators, mediate some crucial regulatory functions. Nevertheless, knowledge of the exact mechanisms is still scarce. Meanwhile, therapies targeting the TME remain unsatisfactory. It holds a great prospect to reveal the molecular mechanism by which the interplay between the nervous and immune systems regulate cancer progression for laying a vivid landscape of tumor development and improving clinical treatment.

An artificial intelligence model to predict survival and chemotherapy benefits for gastric cancer patients after gastrectomy development and validation in international multicenter cohorts.

BACKGROUND: Gastric cancer (GC) is a major health problem worldwide, with high prevalence and mortality. The present GC staging system provides inadequate prognostic information and does not reflect the chemotherapy benefit of GC. METHODS: Two hundred fifty-five patients who underwent surgical resection were enrolled in our study (training cohort = 212, internal validation cohort = 43). Nine clinicopathologic features were obtained to construct an support vector machine (SVM) model. The cohorts from 4 domestic centres and The Cancer Genome Atlas (TCGA) were used for external validation. RESULTS: In the training cohort, the AUCs were 0.773 (95% CI 0.708-0.838) for 5-year overall survival (OS) and 0.751 (95% CI 0.683-0.820) for 5-year disease-free survival (DFS); in the domestic validation cohort, the AUCs were 0.852 (95% CI 0.810-0.894) and 0.837 (95% CI 0.792-0.882), respectively. The model performed better than the TNM staging system according to the receiver operator characteristic(ROC) curve. GC patients were significantly divided into low, moderate and high risk based on the SVM. High-risk TNM stage Ⅱ and Ⅲ patients were more likely to benefit from adjuvant chemotherapy than low-risk patients. CONCLUSIONS: The SVM-based model may be used to predict OS and DFS in GC patients and the benefit of adjuvant chemotherapy in TNM stage Ⅱ and Ⅲ GC patients.

An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy.

BACKGROUND: The tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts. METHODS: The ImmunoScore (IS) was developed in the TCGA cohort and validated in GEO cohorts. The Radiomic ImmunoScore (RIS) was developed in the TCGA cohort and validated in the Nanfang cohort. A nomogram was developed and validated in the Nanfang cohort based on RIS and clinical features. RESULTS: For IS, the area under the curves (AUCs) were 0.798 for 2-year overall survival (OS) and 0.873 for 4-year overall survival. For RIS, in the TCGA cohort, the AUCs distinguishing High-IS or Low-IS and predicting prognosis were 0.85 and 0.81, respectively; in the Nanfang cohort, the AUC predicting prognosis was 0.72. The nomogram performed better than the TNM staging system according to the ROC curve (all P < 0.01). Patients with TNM stage II and III in the High-nomogram group were more likely to benefit from adjuvant chemotherapy than Low-nomogram group patients. CONCLUSIONS: The RIS and the nomogram can be used to assess the TME, prognosis and adjuvant chemotherapy benefit of GC patients after radical gastrectomy and are valuable additions to the current TNM staging system. High-nomogram GC patients may benefit more from adjuvant chemotherapy than Low-nomogram GC patients.

CT-based radiomics nomograms for preoperative prediction of diffuse-type and signet ring cell gastric cancer: a multicenter development and validation cohort.

BACKGROUND: The prevalence of diffuse-type gastric cancer (GC), especially signet ring cell carcinoma (SRCC), has shown an upward trend in the past decades. This study aimed to develop computed tomography (CT) based radiomics nomograms to distinguish diffuse-type and SRCC GC preoperatively. METHODS: A total of 693 GC patients from two centers were retrospectively analyzed and divided into training, internal validation and external validation cohorts. Radiomics features were extracted from CT images, and the Lauren radiomics model was established with a support vector machine (SVM) classifier to identify diffuse-type GC. The Lauren radiomics nomogram integrating radiomics features score (Rad-score) and clinicopathological characteristics were developed and evaluated regarding prediction ability. Further, the SRCC radiomics nomogram designed to identify SRCC from diffuse-type GC was developed and evaluated following the same procedures. RESULTS: Multivariate analysis revealed that Rad-scores was significantly associated with diffuse-type GC and SRCC (p < 0.001). The Lauren radiomics nomogram showed promising prediction performance with an area under the curve (AUC) of 0.895 (95%CI, 0.957-0.932), 0.841 (95%CI, 0.781-0.901) and 0.893 (95%CI, 0.831-0.955) in each cohort. The SRCC radiomics nomogram also showed good discrimination, with AUC of 0.905 (95%CI,0.866-0.944), 0.845 (95%CI, 0.775-0.915) and 0.918 (95%CI, 0.842-0.994) in each cohort. The radiomics nomograms showed great model fitness and clinical usefulness by calibration curve and decision curve analysis. CONCLUSION: Our CT-based radiomics nomograms had the ability to identify the diffuse-type and SRCC GC, providing a non-invasive, efficient and preoperative diagnosis method. They may help guide preoperative clinical decision-making and benefit GC patients in the future.

Identification and validation of methylated differentially expressed miRNAs and immune infiltrate profile in EBV-associated gastric cancer.

BACKGROUND: The recent discovery of cancer/tissue specificity of miRNA has indicated its great potential as a therapeutic target. In Epstein-Barr virus-associated gastric cancer (EBVaGC), host genes are affected by extensive DNA methylation, including miRNAs. However, the role of methylated miRNA in the development of EBVaGC and immune cell infiltration has largely remained elusive. RESULTS: After crossmatching the DNA methylation and expression profile of miRNA and mRNA in the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas Research Network (TCGA), we discovered that miR-129-2-3p was significantly suppressed due to hypermethylation on its enhancer in EBVaGC. The differentially expressed genes (DEGs) added up to 30, among which AKAP12 and LARP6 were predicted to be the target genes of miR-129-2-3p and negatively correlated with patients' survival. Accordingly, miR-129-2-3p was significantly down-regulated in tumor samples in 26 (65%) out of 40 cases in our cohort (P < 0.0001). The proliferation, migration and invasion functions of GC cells were significantly promoted when transfected with miR-129-2-3p inhibitor and suppressed when transfected with mimics or treated with 5-aza-2'-deoxycytidine. Moreover, a comprehensive regulation network was established by combining the putative transcription factors, miRNA-mRNA and protein-protein interaction (PPI) analysis. Pathway enrichment analysis showed that cytokine activity, especially CCL20, was the most prominent biological process in EBVaGC development. Immune cell infiltration analysis demonstrated CD4+ T cell, macrophage and dendritic cell infiltrates were significantly enriched for the prognostic-indicated hub genes. CONCLUSION: This study has provided a comprehensive analysis of differentially expressed miRNAs and mRNAs associated with genome-wide DNA methylation by integrating multi-source data including transcriptome, methylome and clinical data from GEO and TCGA, QPCR of tumor samples and cell function assays. It also gives a hint on the relationships between methylated miRNA, DEGs and the immune infiltration. Further experimental and clinical investigations are warranted to explore the underlying mechanism and validate our findings.

Internet-based cognitive-behavioural therapy for insomnia (ICBT-i): a meta-analysis of randomised controlled trials.

OBJECTIVE: To evaluate the effectiveness of internet-based cognitive-behavioural therapy for insomnia (ICBT-i) in adults. DESIGN: A meta-analysis of ICBT-i. DATA SOURCES: Systematic searches of randomised controlled trials of ICBT-i were performed in the PubMed, EMBASE, PsycINFO and Cochrane Library databases up to 19 June 2016. REVIEW METHOD: 2 reviewers independently performed study selection, quality assessment and data extraction. Outcomes of interest included sleep onset latency (SOL), total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), number of nocturnal awakenings (NWAK), and Insomnia Severity Index (ISI). RevMan 5.2 and Stata 13.0 meta-analysis software were used to perform statistical analysis. RESULTS: 14 records for 15 studies (1013 experimental group participants, 591 waiting list group participants) were included. The meta-analysis indicated that, at the post-test time point, SOL decreased by 18.41 min (95% CI 13.60 to 23.21), TST increased by 22.30 min (95% CI 16.38 to 28.23), SE increased by 9.58% (95% CI 7.30% to 11.85%), WASO decreased by 22.31 min (95% CI 13.50 to 31.11), NWAK decreased by 0.52 (95% CI 0.28 to 0.76), and ISI decreased by 5.88 points (95% CI 4.29 to 7.46). Additionally SOL, TST, SE, and WASO exhibited statistically significant improvements at follow-up versus before treatment. CONCLUSIONS: ICBT-i is an effective treatment for adults with insomnia. This conclusion should be verified in further studies.

Internet-Based Cognitive Behavioral Therapy for Insomnia (ICBT-i) Improves Comorbid Anxiety and Depression-A Meta-Analysis of Randomized Controlled Trials.

As the internet has become popularized in recent years, cognitive behavioral therapy for insomnia (CBT-i) has shifted from a face-to-face approach to delivery via the internet (internet-based CBT-i, ICBT-i). Several studies have investigated the effects of ICBT-i on comorbid anxiety and depression; however, the results remain inconclusive. Thus, a meta-analysis was conducted to determine the effects of ICBT-i on anxiety and depression. Electronic databases, including PubMed, EMBASE, PsycINFO and the Cochrane Library (throughout May 28, 2015), were systematically searched for randomized controlled trials (RCTs) of ICBT-i. Data were extracted from the qualified studies and pooled together. The standardized mean difference (SMD) and 95% confidence interval (95% CI) were calculated to assess the effects of ICBT-i on comorbid anxiety and depression. Nine records that included ten studies were ultimately qualified. The effect sizes (ESs) were -0.35 [-0.46, -0.25] for anxiety and -0.36 [-0.47, -0.26] for depression, which were stable using a between-group or within-group comparison and suggest positive effects of ICBT-i on both comorbid disorders. Although positive results were identified in this meta-analysis, additional high-quality studies with larger sample sizes are needed in the future.

Propofol-induced sleep: efficacy and safety in patients with refractory chronic primary insomnia.

Insomnia, defined as difficulty in falling asleep and/or staying asleep, short sleep duration, or poor quality sleep, is a common sleep disorder affecting 30-40% of adult population. We have conducted a randomized, double-blind, placebo-controlled study to test if anesthesia is therapeutically beneficial in patients with refractory chronic primary insomnia. We have assessed the efficacy and safety of propofol-induced sleep in these patients. This study comprised of 103 patients with refractory chronic primary insomnia (including 59 non-pregnant, non-lactating women; 28-60 years) and the participants were randomized to receive either physiological saline (placebo) (n = 39) or 3.0 g/l propofol (n = 64) in a 2-h continuous intravenous infusion for five consecutive nights. The Leeds Sleep Evaluation Questionnaire was used for the subjective assessment of sleep, and polysomnography was used for the objective measurement of sleep architecture and patterns. The assessments were done prior to and at the end of the 5-day treatment and 6 months after treatment period. The adverse effects of the treatment were also recorded. A 2-h continuous intravenous infusion of 3.0 g/l propofol for five consecutive nights improved the subjective and objective assessments of sleep in 64 patients with refractory chronic primary insomnia. This improvement occurred immediately after the therapy and persisted for 6 months. No serious adverse events were noticed during the period of drug administration or 6 months after the treatment. Propofol therapy is an efficacious and safe choice for restoring normal sleep in patients with refractory chronic primary insomnia.