scholarly journals Evaluation of Important Molecular Pathways and Candidate Diagnostic Biomarkers of Noninvasive to Invasive Stages in Gastric Cancer by In Silico Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Sara Tutunchi ◽  
Saeedeh Akhavan ◽  
Ahmad Bereimipour ◽  
Sayyed Mohammad Hossein Ghaderian
Keyword(s):  
Gastric Cancer ◽  
Extracellular Matrix ◽  
Bioinformatics Analysis ◽  
In Silico Analysis ◽  
Protein Network ◽  
Diagnostic Biomarkers ◽  
Highly Expressed Genes ◽  
Diagnosis Of Cancer ◽  
Speed Up ◽  
Gastric Cancer Patients

Gastric cancer affects millions of people each year; it is the fifth deadliest cancer globally. Due to failure to perform routine tests such as endoscopy, it is usually diagnosed in the invasive stages. Therefore, finding diagnostic biomarkers in blood can help to speed up the initial diagnosis of cancer. This study aimed to find appropriate diagnostic biomarkers in the extracellular matrix of noninvasive to invasive stages of gastric cancer patients, using bioinformatics analysis. First, we selected the appropriate datasets from the GEO database. We evaluated the genes’ signaling pathways, biological processes, and molecular functions. More accurately, we assessed the genes, in which their protein products are released into the extracellular matrix; we evaluated their protein network. Then, we validated the candidate proteins in the GEPIA and TCGA databases. The extracellular matrix, tyrosine kinase receptors, and immune response pathways are effective factors, which are related to the highly expressed genes and metabolism; cell cycle pathways are also impressive on low-expression genes. 69 highly expressed proteins are released into the extracellular matrix. After drawing the protein network, 5 proteins were selected as more suitable candidates for further studies. These proteins’ expression significantly increases in the human samples, and the survival chart showed up to about 80% mortality in the individuals over time. With integrated bioinformatics analysis, BGN, LOX, MMP-9, SERPINE1, and TGFB1 proteins have been selected as suitable diagnostic biomarkers for noninvasive to invasive stages of gastric cancer. Further studies are needed to evaluate more precise mechanisms between these proteins.

scholarly journals The Extracellular Matrix: An Accomplice in Gastric Cancer Development and Progression

Cells ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 394 ◽  
Author(s):  
Ana Margarida Moreira ◽  
Joana Pereira ◽  
Soraia Melo ◽  
Maria Sofia Fernandes ◽  
Patrícia Carneiro ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Extracellular Matrix ◽  
Expression Patterns ◽  
Predictive Biomarkers ◽  
Gastric Epithelium ◽  
Comprehensive Overview ◽  
Diagnostic Biomarkers ◽  
Malignant Lesions ◽  
And Behavior ◽  
Disease Stages

The extracellular matrix (ECM) is a dynamic and highly organized tissue structure, providing support and maintaining normal epithelial architecture. In the last decade, increasing evidence has emerged demonstrating that alterations in ECM composition and assembly strongly affect cellular function and behavior. Even though the detailed mechanisms underlying cell-ECM crosstalk are yet to unravel, it is well established that ECM deregulation accompanies the development of many pathological conditions, such as gastric cancer. Notably, gastric cancer remains a worldwide concern, representing the third most frequent cause of cancer-associated deaths. Despite increased surveillance protocols, patients are usually diagnosed at advanced disease stages, urging the identification of novel diagnostic biomarkers and efficient therapeutic strategies. In this review, we provide a comprehensive overview regarding expression patterns of ECM components and cognate receptors described in normal gastric epithelium, pre-malignant lesions, and gastric carcinomas. Important insights are also discussed for the use of ECM-associated molecules as predictive biomarkers of the disease or as potential targets in gastric cancer.

Prevalence and incidence of comorbidities associated with gastric cancer.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 39-39 ◽  
Author(s):  
Mark D. Danese ◽  
Michelle L. Gleeson ◽  
Wendy J. Langeberg ◽  
Juan Ke ◽  
Michael A. Kelsh
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
Index Date ◽  
Diagnostic Testing ◽  
Incidence Rates ◽  
Physician Visits ◽  
Diagnosis Of Cancer ◽  
Gastric Cancer Patients ◽  
New Treatments ◽  
Treatment Table

39 Background: Understanding the burden of comorbidities in patients with gastric cancer may aid in treatment planning and evaluating the safety of new treatments. Methods: Using the Surveillance, Epidemiology, and End Results (SEER)–Medicare combined dataset, we identified 12,612 patients diagnosed with gastric cancer 2000–2007. A cohort of 12,612 cancer-free individuals was frequency-matched by Medicare enrollment year and county of residence. Subjects were ≥66 years-old at index date to allow for ≥1 full year of Medicare coverage. Prevalence the year before index date and 3- and 12-month incidence rates (per 100 person-years) after index date were estimated for 42 common comorbidities. Results: Comorbidities with the highest (≥8%) 3-month incidence in patients with gastric cancer are shown. Conclusions: Comorbidity prevalence before index date was modestly higher, and incidence rates after index date were much higher in gastric cancer patients than in cancer-free individuals. The potential reasons for this include the increased diagnostic testing, physician visits, and reporting of morbidities that occurs with the diagnosis of cancer, as well as the effects of cancer and its treatment. [Table: see text]

Cellworks Omics Biology Model (CBM) to predict therapy response and identify novel biomarkers for 5FU-based combination therapy in gastric cancer patients.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16091-e16091
Author(s):  
Michael Castro ◽  
Ansu Kumar ◽  
Himanshu Grover ◽  
Vivek Patil ◽  
Ashish Agrawal ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
Copy Number ◽  
Therapy Response ◽  
Specific Protein ◽  
Protein Network ◽  
Cytotoxic Agents ◽  
Patient Specific ◽  
Cancer Hallmarks ◽  
Gastric Cancer Patients

e16091 Background: Using a 5FU backbone, a variety of combination chemotherapy regimens have been adopted for gastric cancer. However, the genetic heterogeneity of the disease suggests certain drugs would lead to better outcomes for specific patients. In principle, the incorporation of molecular profiling information into treatment selection can generate superior survival for patients. Therefore, we conducted a pilot study using the CBM to identify novel genomic biomarkers of response and resistance to several 5FU-based regimens. Methods: 12 gastric cancer patients treated with 5FU-cisplatin (N = 4), 5FU-VP16 (N = 5) and 5FU-cisplatin-docetaxel (N = 3) were selected from the TCGA database. Mutation and copy number aberrations from each case served as input for CBM to generate patient-specific protein network maps generated from PubMed and other resources. Disease-biomarkers unique to each patient were identified within protein network maps. Drug impact on the disease network was digitally simulated to determine treatment efficacy by measuring effect of chemotherapy on the cell growth score, i.e., a composite of cell proliferation, viability, apoptosis, metastasis, DNA damage and other cancer hallmarks. Effectively, the mechanism of action of each drug was mapped to each patient’s genome and the biological consequences of genomic abnormalities were correlated with response. Results: Of the 12 patients in the study, 10 patients responded to 5FU-based regimens and 2 were non-responders. CBM correctly predicted the therapy response in each therapy segment. Key response criteria were: 5FU-cisplatin - ARID1A (LOF), RAD51 (LOF), MBD1 (LOF), DUT (LOF). 5FU-VP16 - FBXW7 (DEL), RAD51D (DEL), RAD51C (DEL), XRCC2 (DEL), XRCC3 (DEL). 5FU-cisplatin-docetaxel - ARID1A (DEL), CHEK1 (DEL), REV3L (DEL), XRCC3(DEL) and TUBB (AMP). Resistance biomarkers were also identified for these drugs. FBXW7 loss caused cisplatin resistance, but also predicted sensitivity to VP16. Interestingly, all five 5FU-VP16 responders harbored FBXW7 loss. Similarly, in two 5FU-cisplatin-docetaxel non-responders, KIFC1 (GOF), YBX1(AMP), CDC20 (AMP) were key biomarkers for docetaxel resistance. In one of these patients, ATM (DEL), RBBP8 (DEL) and GSTP1 (DEL) predicted response to VP16. Conclusions: The efficacy of individual cytotoxic agents varies in the population. Mutations and copy number changes in DNA checkpoint, DNA repair, and tumor suppressor genes impact responsive to chemotherapy and should be routinely assessed. Notably, 5FU-VP16 combination could have delivered better antitumor efficacy for several non-responders or 25% of the patients in this small cohort. CBM is able to identify both the most active as well inefficacious components of the treatment upfront. We suggest that this approach should be prospectively evaluated in a larger cohort.

CLINICAL SIGNIFICANCE OF SERUM CAVEOLIN-1 LEVELS IN GASTRIC CANCER PATIENTS

2018 ◽  
Vol 40 (4) ◽  
pp. 323-327 ◽  
Author(s):  
F Tas ◽  
S Karabulut ◽  
K Erturk ◽  
D Duranyildiz
Keyword(s):  
Gastric Cancer ◽  
Cancer Patients ◽  
Histological Grade ◽  
Clinical Importance ◽  
Disease Stage ◽  
Control Group ◽  
Tissue Samples ◽  
Caveolin 1 ◽  
Study Results ◽  
Gastric Cancer Patients

Aim: Caveolin-1 plays a significant role in the pathogenesis of various carcinomas and its expression affects the survival of cancer patients. However, the molecular function of caveolin-1 and its possible clinical importance has remained uncertain in gastric cancer. No clinical trial has examined serum caveolin-1 levels in gastric cancer patients so far, instead all available results were provided from studies conducted on tissue samples. In the current study, we analyzed the soluble serum caveolin-1 levels in gastric cancer patients, and specified its associations with the clinical factors and prognosis. Material and Methods: Sixty-three patients with pathologically confirmed gastric cancer were enrolled into the trial. Serum caveolin-1 concentrations were detected by ELISA method. Thirty healthy subjects were also included in the study. Results: The median age of patients was 62 years, ranging from 28 to 82 years. The serum caveolin-1 levels in gastric cancer patients were significantly higher than those in control group (p < 0.001). The common clinical parameters including patient age, sex, lesion localization, histopathology, histological grade, disease stage, and various serum tumor markers (e.g. LDH, CEA, and CA 19.9) were not found to be associated with serum caveolin-1 levels (p > 0.05). Similarly, no correlation existed between serum caveolin-1 concentration and chemotherapy responsiveness (p = 0.93). Furthermore, serum caveolin-1 level was not found to have a prognostic role (p = 0.16). Conclusion: Even though it is neither predictive nor prognostic, serum caveolin-1 level may be a valuable diagnostic indicator in patients with gastric cancer. Key

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