Project description:Extracellular RNA (exRNA) is an emerging paradigm as endocrine signals in cellular communication, biomarker development, therapeutic applications and systemic physiology. This project is to test the hypothesis that salivary extracellular RNA (exRNA) can be developed for the clinical detection of human diseases. Our laboratory first reported the existence of a transcriptome and microRNA profile in cell free saliva followed by its scientific characterizations and clinical utilities including biomarker development for molecular oncology applications. Most recently we have performed RNA-sequencing in cell free saliva and reported three major types of RNA in saliva (mRNA, miRNA and snoRNA). This study is to test the hypothesis that salivary exRNA can be developed to detect gastric cancer by performing a biomarker development study to definitively validate salivary exRNA biomarkers for the detection of gastric cancer. Overall design: 198 total samples from 198 donors were analyzed. The study contains 100 non-gastric cancer controls and 98 gastric cancer patients with no replicates. All samples are saliva. -------------------------------- Submitter states "We are currently working on submitting the data for these protected datasets to dbGaP, but wanted to submit the processed data to GEO in the mean time."
Project description:Preoperative chemo- and radiotherapeutic strategies followed by surgery are currently a standard approach for treating locally advanced gastric and esophagogastric junction cancer in Western countries. However, in a large number of cases, the tumor is extremely resistant to these treatments and the patients are exposed to unnecessary toxicity and delayed surgical therapy. The current clinical trials evaluating the combination of preoperative systemic therapies with modern targeted and immunotherapeutic agents represent a unique opportunity for identifying predictive biomarkers of response to select patients that would benefit the most from these treatments. However, it is of utmost importance that these potential biomarkers are corroborated by extensive preclinical and translational research. The aim of this review article is to present the most promising biomarkers of response to classic chemotherapeutic, anti-HER2, antiangiogenic, and immunotherapeutic agents that can be potentially useful for personalized preoperative systemic therapies in gastric cancer patients.
Project description:Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer.
Project description:The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort... (for more see dbGaP study page.)
Project description:Overall survival of gastric cancer remains low, as patients are often diagnosed with advanced stage disease. In this review, we give an overview of current research on biomarkers in gastric cancer and their implementation in treatment strategies. The HER2-targeting trastuzumab is the first molecular targeted agent approved for gastric cancer treatment. Other promising biomarkers for targeted therapies that have shown relevance in clinical trials are VEGF and Claudin 18.2. Expression of MET has been shown to be a negative prognostic factor in gastric cancer. Targeting the PD-1/PD-L1 pathway with immune checkpoint inhibitors has proven efficacy in advanced gastric cancer. Recent technology advances allow the detection of circulating tumor cells that may be used as diagnostic and prognostic indicators and for therapy monitoring in gastric cancer patients. Prognostic molecular subtypes of gastric cancer have been identified using genomic data. In addition, transcriptome profiling has allowed a comprehensive characterization of the immune and stromal microenvironment in gastric cancer and development of novel risk scores. These prognostic and predictive markers highlight the rapidly evolving field of research in gastric cancer, promising improved treatment stratification and identification of molecular targets for individualized treatment in gastric cancer.
Project description:<h4>Background</h4>Gastric cancer is a fatal gastrointestinal cancer with high morbidity and poor prognosis. The dismal 5-year survival rate warrants reliable biomarkers to assess and improve the prognosis of gastric cancer. Distinguishing driver mutations that are required for the cancer phenotype from passenger mutations poses a formidable challenge for cancer genomics.<h4>Methods</h4>We integrated the multi-omics data of 293 primary gastric cancer patients from The Cancer Genome Atlas (TCGA) to identify key driver genes by establishing a prognostic model of the patients. Analyzing both copy number alteration and somatic mutation data helped us to comprehensively reveal molecular markers of genomic variation. Integrating the transcription level of genes provided a unique perspective for us to discover dysregulated factors in transcriptional regulation.<h4>Results</h4>We comprehensively identified 31 molecular markers of genomic variation. For instance, the copy number alteration of WASHC5 (also known as KIAA0196) frequently occurred in gastric cancer patients, which cannot be discovered using traditional methods based on significant mutations. Furthermore, we revealed that several dysregulation factors played a hub regulatory role in the process of biological metabolism based on dysregulation networks. Cancer hallmark and functional enrichment analysis showed that these key driver (KD) genes played a vital role in regulating programmed cell death. The drug response patterns and transcriptional signatures of KD genes reflected their clinical application value.<h4>Conclusions</h4>These findings indicated that KD genes could serve as novel prognostic biomarkers for further research on the pathogenesis of gastric cancers. Our study elucidated a multidimensional and comprehensive genomic landscape and highlighted the molecular complexity of GC.
Project description:Carcinoma of the stomach is one of the most prevalent cancer types in the world. Although the incidence of gastric cancer is declining, the outcomes of gastric cancer patients remain dismal because of the lack of effective biomarkers to detect early gastric cancer. Modern biomedical research has explored many potential gastric cancer biomarker genes by utilising serum protein antigens, oncogenic genes or gene families through improving molecular biological technologies, such as microarray, RNA-Seq and the like. Recently, the small noncoding microRNAs (miRNAs) have been suggested to be critical regulators in the oncogenesis pathways and to serve as useful clinical biomarkers. This new class of biomarkers is emerging as a novel molecule for cancer diagnosis and prognosis, including gastric cancer. By translational suppression of target genes, miRNAs play a significant role in the gastric cancer cell physiology and tumour progression. There are potential implications of previously discovered gastric cancer molecular biomarkers and their expression modulations by respective miRNAs. Therefore, many miRNAs are found to play oncogenic roles or tumour-suppressing functions in human cancers. With the surprising stability of miRNAs in tissues, serum or other body fluids, miRNAs have emerged as a new type of cancer biomarker with immeasurable clinical potential.
Project description:Gastric cancer (GC) is the second most common cancer in China and the second leading cause of cancer-related death in the world. Identifying circulating biomarkers is helpful to improve theranostics of gastric cancer. Herein, we are for the first time to report miR-16-5p and miR-19b-3p were identified to be the novel potential plasma biomarkers to detect gastric cancer. Differentially expressed miRNAs were initially screened out by genome-wide miRNA profiling microarrays between 16 plasma samples of gastric cancer and 18 matched normal controls, and then were quantified and validated by quantitative reverse transcription-PCR method between 155 gastric cancer cases and 111 normal controls. Additionally, 30 plasma samples from precancerous lesions and 18 paired samples from gastric cancer patients with gastrectomy were further detected. Results showed that based on two normalization methods, miR-16-5p and miR-19b-3p in plasma were found to be capable of distinguishing normal population from GC cases with different TNM stages and differentiation grades, particularly including the early cancer cases (P<0.05). And the two miRNAs were down-regulated in GC cases (FC<0.5). Especially, the down-regulation degree was correlated with the progression of the GC cases from the early stage to the advanced stage (0.2< r s<0.3, P<0.01). And the same weak down-regulation of the two biomarkers as the early GC occurred initially in the precancerous diseases (P<0.05). The corresponding performance of the two miRNAs to detect GC in ROC analysis gradually performed better with the disease progression from the earlier stages or lower grades to the advanced stages (TNM ? stage: AUC=0.832 for miR-16-5p; TNM ? stage: AUC=0.822 for miR-19b-3p) or high grade (Poorly differentiated: AUC=0.801, 0.791 respectively for miR-16-5p and miR-19b-3p). Additionally, miR-19b-3p remained down-regulated in patient plasma within 9 days after gastrectomy. In conclusion, miR-19b-3p and miR-16-5p maybe prospective biomarkers to detect gastric cancer and indicate its progression, and thus may own great potential in applications such as early screening and progression evaluation of gastric cancer in the near future.