Tumor microenvironment (TME) cells constitute a vital element of tumor tissue. Increasing evidence has elucidated their clinicopathologic significance in predicting outcomes and therapeutic efficacy. Nonetheless, no studies have reported a systematic analysis of cellular interactions in the TME. In this study, we comprehensively estimated the TME infiltration patterns of 1,524 gastric cancer patients and systematically correlated the TME phenotypes with genomic characteristics and clinicopathologic features of gastric cancer using two proposed computational algorithms. Three TME phenotypes were defined, and the TMEscore was constructed using principal component analysis algorithms. The high TMEscore subtype was characterized by immune activation and response to virus and IFNg. Activation of transforming growth factor b, epithelial-mesenchymal transition, and angiogenesis pathways were observed in the low TMEscore subtype, which are considered T-cell suppressive and may be responsible for significantly worse prognosis in gastric cancer [hazard ratio (HR), 0.42; 95% confidence interval (CI), 0.33-0.54; P < 0.001]. Multivariate analysis revealed that the TMEscore was an independent prognostic biomarker, and its value in predicting immunotherapeutic outcomes was also confirmed (IMvigor210 cohort: HR, 0.63; 95% CI, 0.46-0.89; P ¼ 0.008; GSE78220 cohort: HR, 0.25; 95% CI, 0.07-0.89; P ¼ 0.021). Depicting a comprehensive landscape of the TME characteristics of gastric cancer may, therefore, help to interpret the responses of gastric tumors to immunotherapies and provide new strategies for the treatment of cancers.

Cancer cells are frequently confronted with metabolic stress in tumor microenvironments due to their rapid growth and limited nutrient supply. Metabolic stress induces cell death through ROS-induced apoptosis. However, cancer cells can adapt to it by altering the metabolic pathways. AMPK and AKT are two primary effectors in response to metabolic stress: AMPK acts as an energy-sensing factor which rewires metabolism and maintains redox balance. AKT broadly promotes energy production in the nutrient abundance milieu, but the role of AKT under metabolic stress is in dispute. Recent studies show that AMPK and AKT display antagonistic roles under metabolic stress. Metabolic stress-induced ROS signaling lies in the hub between metabolic reprogramming and redox homeostasis. Here, we highlight the cross-talk between AMPK and AKT and their regulation on ROS production and elimination, which summarizes the mechanism of cancer cell adaptability under ROS stress and suggests potential options for cancer therapeutics.

Nonpeptide agonists of each of the five somatostatin receptors were identified in combinatorial libraries constructed on the basis of molecular modeling of known peptide agonists. In vitro experiments using these selective compounds demonstrated the role of the somatostatin subtype-2 receptor in inhibition of glucagon release from mouse pancreatic alpha cells and the somatostatin subtype-5 receptor as a mediator of insulin secretion from pancreatic beta cells. Both receptors regulated growth hormone release from the rat anterior pituitary gland. The availability of high-affinity, subtype-selective agonists for each of the somatostatin receptors provides a direct approach to defining their physiological functions.

Tumour-infiltrating immune cells are a source of important prognostic information for patients with resectable colon cancer. We developed a novel immune model based on systematic assessments of the immune landscape inferred from bulk tumor transcriptomes of stage I–III colon cancer patients. The “Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT)” algorithm was used to estimate the fraction of 22 immune cell types from six microarray public datasets. The random forest method and least absolute shrinkage and selection operator model were then used to establish immunoscores for diagnosis and prognosis. By comparing immune cell compositions in samples of 870 colon cancer patients and 70 normal controls, we constructed a diagnostic model, designated the diagnostic immune risk score (dIRS), that showed high specificity and sensitivity in both the training [area under the curve (AUC) = 0.98, p < 0.001] and validation (AUC 0.96, p < 0.001) sets. We also established a prognostic immune risk score (pIRS) that was found to be an independent prognostic factor for relapse-free survival in every series (training: HR 2.23; validation: HR 1.65; entire: HR 2.01; p < 0.001 for all), which showed better prognostic value than TNM stage. In addition, integration of the pIRS with clinical characteristics in a composite nomogram showed improved accuracy of relapse risk prediction, providing a higher net benefit than TNM stage, with well-fitted calibration curves. The proposed dIRS and pIRS models represent promising novel signatures for the diagnosis and prognosis prediction of colon cancer.Electronic supplementary materialThe online version of this article (10.1007/s00262-018-2289-7) contains supplementary material, which is available to authorized users.

Recent advances in next-generation sequencing (NGS) technologies have triggered the rapid accumulation of publicly available multi-omics datasets. The application of integrated omics to explore robust signatures for clinical translation is increasingly emphasized, and this is attributed to the clinical success of immune checkpoint blockades in diverse malignancies. However, effective tools for comprehensively interpreting multi-omics data are still warranted to provide increased granularity into the intrinsic mechanism of oncogenesis and immunotherapeutic sensitivity. Therefore, we developed a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing a comprehensive investigation of the estimation of reported or user-built signatures, TME deconvolution, and signature construction based on multi-omics data. Notably, IOBR offers batch analyses of these signatures and their correlations with clinical phenotypes, long non-coding RNA (lncRNA) profiling, genomic characteristics, and signatures generated from single-cell RNA sequencing (scRNA-seq) data in different cancer settings. Additionally, IOBR integrates multiple existing microenvironmental deconvolution methodologies and signature construction tools for convenient comparison and selection. Collectively, IOBR is a user-friendly tool for leveraging multi-omics data to facilitate immuno-oncology exploration and to unveil tumor-immune interactions and accelerating precision immunotherapy.

Chemotherapy is the preferred treatment for advanced stage gastric cancer (GC) patients and chemotherapy resistance is the major obstacle to effective cancer therapy. Increasing evidence suggests that mesenchymal stem cells (MSCs) make important contributions to development of drug resistance. However, the underlying mechanism remains elusive. In this study, we discovered that abundant MSCs in tumor tissues predicted a poor prognosis in GC patients. MSCs promoted stemness and chemoresistance in GC cells through fatty acid oxidation (FAO) in vitro and in vivo. Mechanically, transforming growth factor β1 (TGF-β1) secretion by MSCs activated SMAD2/3 through TGF-β receptors and induced long non-coding RNA (lncRNA) MACC1-AS1 expression in GC cells, which promoted FAO-dependent stemness and chemoresistance through antagonizing miR-145-5p. Moreover, pharmacologic inhibition of FAO with etomoxir (ETX) attenuated MSC-induced FOLFOX regiment resistance in vivo. These results suggest that FAO plays an important role in MSC-mediated stemness and chemotherapy resistance in GC and FAO inhibitors in combination with chemotherapeutic drugs present as a promising strategy to overcome chemoresistance.

BackgroundXB130 has been reported to be expressed by various types of cells such as thyroid cancer and esophageal cancer cells, and it promotes the proliferation and invasion of thyroid cancer cells. Our previous study demonstrated that XB130 is also expressed in gastric cancer (GC), and that its expression is associated with the prognosis, but the role of XB130 in GC has not been well characterized.MethodsIn this study, we investigated the influence of XB130 on gastric tumorigenesis and metastasis in vivo and in vitro using the MTT assay, clonogenic assay, BrdU incorporation assay, 3D culture, immunohistochemistry and immunofluorescence. Western blot analysis was also performed to identify the potential mechanisms involved.ResultsThe proliferation, migration, and invasion of SGC7901 and MNK45 gastric adenocarcinoma cell lines were all significantly inhibited by knockdown of XB130 using small hairpin RNA. In a xenograft model, tumor growth was markedly inhibited after shXB130-transfected GC cells were implanted into nude mice. After XB130 knockdown, GC cells showed a more epithelial-like phenotype, suggesting an inhibition of the epithelial-mesenchymal transition (EMT) process. In addition, silencing of XB130 reduced the expression of p-Akt/Akt, upregulated expression of epithelial markers including E-cadherin, α-catenin and β-catenin, and downregulated mesenchymal markers including fibronectin and vimentin. Expression of oncoproteins related to tumor metastasis, such as MMP2, MMP9, and CD44, was also significantly reduced.ConclusionsThese findings indicate that XB130 enhances cell motility and invasiveness by modulating the EMT-like process, while silencing XB130 in GC suppresses tumorigenesis and metastasis, suggesting that it may be a potential therapeutic target.

BackgroundMetabolic plasticity has been increasingly thought to be a determinant of tumor growth and metastasis. MACC1, a transcriptional regulator of MET, was recognized as an oncogene in gastric cancer (GC); however, its transcriptional or post-translational regulation was not clear. We previously reported the metabolic role of MACC1 in glycolysis to promote GC progression. MACC1-AS1 is the antisense lncRNA of MACC1, yet its function was previously unknown.MethodsWe profiled and analyzed the expression of MACC1-AS1 utilizing the TCGA database as well as in situ hybridization using 123 pairs of GC tissues and matched adjacent normal gastric mucosa tissues (ANTs). The biological role of MACC1-AS1 in cell growth and metastasis was determined by performing in vitro and in vivo functional experiments. Glycolysis and antioxidant capabilities were assayed to examine its metabolic function. Further, the specific regulatory effect of MACC1-AS1 on MACC1 was explored transcriptionally and post-transcriptionally.ResultsMACC1-AS1 was shown to be expressed significantly higher in GC tissues than in ANTs, which predicted poor prognosis in GC patients. MACC1-AS1 promoted GC cell proliferation and inhibited cell apoptosis under metabolic stress. Mechanistically, MACC1-AS1 stabilized MACC1 mRNA and post-transcriptionally augmented MACC1 expression. Further, MACC1-AS1 was shown to mediate metabolic plasticity through MACC1 upregulation and subsequent enhanced glycolysis and anti-oxidative capabilities, and this was suggested to be coordinated by the AMPK/Lin28 pathway.ConclusionsElevated expression of MACC1-AS1 in gastric cancer tissues is linked to poor prognosis and promotes malignant phenotype upon cancer cells. MACC1-AS1 is elevated under metabolic stress and facilitates metabolic plasticity by promoting MACC1 expression through mRNA stabilization. Our study implicates lncRNA MACC1-AS1 as a valuable biomarker for GC diagnosis and prognosis.Electronic supplementary materialThe online version of this article (10.1186/s12943-018-0820-2) contains supplementary material, which is available to authorized users.