The MIR100HG expression was observed to be up-regulated or down-regulated in human cancer tissues depending on tumor types. However, there was no report about the role of MIR100HG in gastric cancer. In our study, we first found levels of MIR100HG expression were increased in gastric cancer cell lines and tissue samples compared with normal gastric epithelial cell line and adjacent normal gastric mucosa tissue samples, respectively. Moreover, high MIR100HG expression was positively associated with clinical stage, tumor invasion, lymph node metastasis, and distant metastasis in gastric cancer patients. Survival analysis showed MIR100HG expression was negative correlated with clinical outcome in gastric cancer patients from The Cancer Genome Atlas (TCGA) database or our study, and high MIR100HG expression served as an independent poor prognostic factor for gastric cancer patient’s overall survival. The study in vitro suggested down-regulation of MIR100HG expression inhibits cell proliferation, migration, and invasion in gastric cancer. In conclusion, MIR100HG is a credible prognostic biomarker and functions as an oncogenic lncRNA in gastric cancer.

/pdf/mir100hg-a-credible-prognostic-biomarker-and-an-oncogenic-r8iet0br8o.pdf

MIR100HG: a credible prognostic biomarker and an oncogenic lncRNA in gastric cancer

Background: The systematic expression characteristics and functions of collagen genes in gastric cancer (GC) have not been reported. Through public data integration, combined with bioinformatics analysis, we identified a panel of collagen genes overexpressed in GC. The functions of these genes were analyzed and validated in a GC-related cohort. microRNAs that may potentially target such genes were investigated in vitro.

Methods: Four GC-related datasets retrieved from the Gene Expression Omnibus (GEO) were used to extract differentially expressed genes (DEGs) in GC. Functional annotation was performed to identify the potential roles of the identified DEGs. The association of candidate genes involved in the prognosis of GC patients (n=876) was determined using data provided by the Kaplan–Meier-plotter database, The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) repository, and a GC-related dataset ({"type":"entrez-geo","attrs":{"text":"GSE15459","term_id":"15459"}}GSE15459). The expression characteristics of candidate genes and their associations with clinical parameters were validated in our in-house cohort (n=58). MicroRNAs able to target the identified candidate genes were predicted and confirmed using qRT-PCR, Western blotting, and dual-luciferase reporter assays in vitro.

Results: After the integration of four GEO datasets, 76 DEGs were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that these DEGs were significantly enriched in ECM-related functions and pathways. A group of collagen genes was significantly upregulated in the GC tissues and constituted a protein–protein interaction network as important nodes. Some of these collagen genes were closely associated with poor prognosis in GC patients. Overexpression of COL1A1 and COL4A1 was confirmed in our in-house cohort, and this was related to prognosis and certain clinicopathological parameters. We found that microRNA-29c-3p could directly target COL1A1 and COL4A1 in BGC-823 cells.

Conclusions: Collagen genes identified in this study were associated with patient prognosis in GC and may represent diagnostic markers or potential therapeutic targets. Aberrant expression of such candidate genes may be induced by microRNA-29c-3p.

/pdf/a-panel-of-collagen-genes-are-associated-with-prognosis-of-6m71t8stmm.pdf

A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation.

Triptonide effectively suppresses gastric tumor growth and metastasis through inhibition of the oncogenic Notch1 and NF-κB signaling pathways.

Gastric cancer is the fourth most common cancer and the second most frequent cause of cancer death worldwide. Chemotherapy is an important treatment. However, traditional chemotherapy drugs have low bioavailability and targeting ability. Therefore, we developed curcumin-encapsulated micelles for the treatment of gastric cancer and investigated their antitumor efficacy and active mechanism. Gastric cancer cells were treated with different concentrations of curcumin micelles. MTS cell proliferation assays, flow cytometry (FCM), real time cellular analysis (RTCA) and nude mice xenografts were used to evaluate the effects of curcumin micelles on gastric cancer cell growth in vitro and in vivo. Western blotting was performed to analyze the protein levels of the indicated molecules. A Seahorse bioenergetics analyzer was used to investigate alterations in oxygen consumption and the aerobic glycolysis rate. Curcumin micelles significantly inhibited proliferation and colony formation and induced apoptosis in gastric tumor cells compared to the control groups. We further investigated the mechanism of curcumin micelles on gastric tumor cells and demonstrated that curcumin micelles acted on mitochondrial proteins, causing changes in mitochondrial function and affecting mitochondrial bioenergetics. Furthermore, curcumin micelles decreased mitochondrial membrane potential, increased reactive oxygen species (ROS) generation and disrupted redox equilibrium. The nude mouse model verified that curcumin micelle treatment significantly attenuated tumor growth in vivo. Curcumin micelles suppress gastric tumor cell growth in vitro and in vivo. The mechanism may be related to increasing ROS generation, disrupting redox equilibrium and affecting mitochondrial bioenergetics.

Curcumin micelles suppress gastric tumor cell growth by upregulating ROS generation, disrupting redox equilibrium and affecting mitochondrial bioenergetics

Gastric cancer (GC) is highly heterogeneous in the stromal and immune microenvironment, genome instability (GI), and oncogenic signatures. However, a classification of GC by combining these features remains lacking. Using the consensus clustering algorithm, we clustered GCs based on the activities of 15 pathways associated with immune, DNA repair, oncogenic, and stromal signatures in three GC datasets. We identified three GC subtypes: immunity-deprived (ImD), stroma-enriched (StE), and immunity-enriched (ImE). ImD showed low immune infiltration, high DNA damage repair activity, high tumor aneuploidy level, high intratumor heterogeneity (ITH), and frequent TP53 mutations. StE displayed high stromal signatures, low DNA damage repair activity, genomic stability, low ITH, and poor prognosis. ImE had strong immune infiltration, high DNA damage repair activity, high tumor mutation burden, prevalence of microsatellite instability, frequent ARID1A mutations, elevated PD-L1 expression, and favorable prognosis. Based on the expression levels of four genes (TAP2, SERPINB5, LTBP1, and LAMC1) in immune, DNA repair, oncogenic, and stromal pathways, we developed a prognostic model (IDOScore). The IDOScore was an adverse prognostic factor and correlated inversely with immunotherapy response in cancer. Our identification of new GC subtypes provides novel insights into tumor biology and has potential clinical implications for the management of GCs.

/pdf/identification-of-gastric-cancer-subtypes-based-on-pathway-5c9pt98bp0.pdf

Identification of gastric cancer subtypes based on pathway clustering.

Metastatic gastric cancer is associated with a poor prognosis and novel treatment options are desperately needed. The development of targeted therapies heralded a new era for the management of metastatic gastric cancer, however results from clinical trials of numerous targeted agents have been mixed. The advent of immune checkpoint inhibitors has yielded similar promise and results from early trials are encouraging. This review provides an overview of the systemic treatment options evaluated in metastatic gastric cancer, with a focus on recent evidence from clinical trials for targeted therapies and immune checkpoint inhibitors. The failure to identify appropriate predictive biomarkers has hampered the success of many targeted therapies in gastric cancer, and a deeper understanding of specific molecular subtypes and genomic alterations may allow for more precision in the application of novel therapies. Identifying appropriate biomarkers for patient selection is essential for future clinical trials, for the most effective use of novel agents and in combination approaches to account for growing complexity of treatment options.

https://journals.sagepub.com/doi/pdf/10.1177/1756284818808072

Wasek Faisal

Papers

New drug developments in metastatic gastric cancer

Adjuvant anti‐VEGF therapy for overall survival and relapse‐free survival in patients with resected non‐metastatic colorectal cancer