Browsing by Subject "Gastric cancer"

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Open Access
A novel gene list identifies tumors with a stromal-mesenchymal phenotype and worse prognosis in gastric cancer
(MDPI, 2023-06-02) Demirkol Canlı, Seçil; Üner, M.; Küçükkaraduman, Barış; Karaoğlu, D. A.; Işık, A.; Turhan, N.; Akyol, A.; Gömceli, I.; Güre, A. O. A
Background: Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors. Methods: Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively. Results: A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression (“Stromal-UP” (SU) and “Stromal-DOWN” (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival. Conclusions: A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested.
Open Access
A-To-I RNA editing events, potential biomarkers for prognosis and chemosensitivity in gastric cancer
(2022-09) Çela, Isli
Gastric cancer (GC) is one of the leading causes of cancer mortality, and it frequently presents in advanced stages with a poor prognosis and response to treatment. Although extensive research has identified many potential biomarkers in GC, the heterogeneity of the disease is an impediment to validation, so only a small number find limited application in clinics. RNA editing is an epigenetic modification that results in nucleotide changes in the RNA sequence. Adenosine to Inosine (A-to-I) substitutions are the most common editing events in humans, and they are mediated by Adenosine deaminases acting on RNA (ADAR) enzymes. Inosine (I) mimics Guanosine (G) and creates pairs with Cytidine (C), resulting in changes in RNA structure and stability, amino acid substitutions, alternative splicing, or gene expression regulation via miRNA target site modifications.RNA editing dysregulations have been found in breast, lung, kidney, brain, and gastric cancers, but the utility of specific editing events as biomarkers is largely unexplored. In this study we investigate the potential of A-to-I editing events as chemosensitivity and prognostic biomarkers in GC. Across multiple datasets, our analysis shows that RNA editing events at 305 unique positions correlate with drug sensitivity measures of 17 approved chemotherapeutics in GC cell lines.The most significant editing event-drug sensitivity correlations indicate that higher editing levels are associated with higher chemosensitivity. Interestingly, the expression levels of genes with identified editing events have a weaker or no correlation with drug sensitivity, implying that editing events are biomarkers independent of transcript levels. We show that, while ADAR enzymes mediate editing events, ADAR expression levels are not interchangeable with editing frequencies as chemosensitivity biomarkers in GC. We discovered a non-synonymous editing event in the C11orf80 coding sequence, resulting in an amino acid substitution (S.p133G). Also, we identified an editing event in the 3'UTR of SOGA1 that correlates with increased SOGA1 expression. The presence of this editing site in a putative target site of miR-9-5p suggests that gene expression might be regulated by miRNA target site modifications. In the TCGA and Singapore cohorts, the prognostic role of editing events in GC was investigated. Overall, higher levels of editing are associated with better survival in GC patients. In both cohorts, we found an editing event in the CLPX gene at the position 65442098 to be an independent good prognostic factor. We chose editing events that would best categorize our patients into "High" and "Low" edited groups using the Log Rank Multiple Cut-off (LRMC) plot distribution. In each dataset, we propose two editing events, one good and one bad prognostic factor that independently correlate with survival in GC patients. In the Singapore Cohort, high editing levels in ZNF587 are associated with a good prognosis, while those in DCAF16 are associated with a poor prognosis.High editing levels in CTSB correlate with better overall survival (OS) in the TCGA cohort, while those in NUP43 correlate with worse OS. Because transcript levels do not correlate with survival, the prognostic effects of these editing events are unaffected by gene expression levels.We believe that editing levels at specific positions can be used as prognostic biomarkers in a significant way, providing a more cost-effective and applicable alternative to prognostic editing signature models. Our findings suggest that editing events could be used as independent biomarkers for chemosensitivity and prognosis in gastric cancer, however more investigation is required to elucidate the mechanisms underlying the observed relationships.
Open Access
Assessing the genetic impact of Enterococcus faecalis infection on gastric cell line MKN74
(Springer, 2021-12) Türk, Seyhan; Türk, Can; Temirci, Elif Sena; Malkan, Umit Yavuz; Ucar, Gulberk; Ozguven, Sukru Volkan
Purpose Enterococcus faecalis (E. faecalis) is an important commensal microbiota member of the human gastrointestinal tract. It has been shown in many studies that infection rates with E. faecalis in gastric cancer significantly increase. It has been scientifically proven that some infections develop during the progression of cancer, but it is still unclear whether this infection factor is beneficial (reduction in metastasis) or harmful (increase in proliferation, invasion, stem cell-like phenotype) of the host. These opposed data can significantly contribute to the understanding of cancer progress when analyzed in detail. Methods The gene expression data were retrieved from Array Express (E-MEXP-3496). Variance, t test and linear regression analysis, hierarchical clustering, network, and pathway analysis were performed. Results In this study, we identified altered genes involved in E. faecalis infection in the gastric cell line MKN74 and the relevant pathways to understand whether the infection slows down cancer progression. Twelve genes corresponding 15 probe sets were downregulated following the live infection of gastric cancer cells with E. faecalis. We identified a network between these genes and pathways they belong to. Pathway analysis showed that these genes are mostly associated with cancer cell proliferation. Conclusion NDC80, NCAPG, CENPA, KIF23, BUB1B, BUB1, CASC5, KIF2C, CENPF, SPC25, SMC4, and KIF20A genes were found to be associated with gastric cancer pathogenesis. Almost all of these genes are effective in the proliferation of cancer cells, especially during the infection process. Therefore, it is hypothesized that downregulation of these genes may affect gastric cancer pathogenesis by reducing cell proliferation. And, it is predicted that E. faecalis infection may be an important factor for gastric cancer.
Open Access
Colon cancer associated transcript-1 (CCAT1) expression in adenocarcinoma of the stomach
(Ivyspring International Publisher, 2015) Mizrahi, I.; Mazeh, H.; Grinbaum, R.; Beglaibter, N.; Wilschanski, M.; Pavlov, V.; Adileh, M.; Stojadinovic, A.; Avital, I.; Gure, A. O.; Halle, D.; Nissan, A.
Background: Long non-coding RNAs (lncRNAs) have been shown to have functional roles in cancer biology and are dys-regulated in many tumors. Colon Cancer Associated Transcript -1 (CCAT1) is a lncRNA, previously shown to be significantly up-regulated in colon cancer. The aim of this study is to determine expression levels of CCAT1 in gastric carcinoma (GC). Methods: Tissue samples were obtained from patients undergoing resection for gastric carcinoma (n=19). For each patient, tumor tissue and normal appearing gastric mucosa were taken. Normal gastric tissues obtained from morbidly obese patients, undergoing laparoscopic sleeve gastrectomy served as normal controls (n=19). A human gastric carcinoma cell line (AGS) served as positive control. RNA was extracted from all tissue samples and CCAT1 expression was analyzed using quantitative real time-PCR (qRT-PCR). Results: Low expression of CCAT1 was identified in normal gastric mucosa samples obtained from morbidly obese patients [mean Relative Quantity (RQ) = 1.95±0.4]. AGS human gastric carcinoma cell line showed an elevated level of CCAT1 expression (RQ=8.02). Expression levels of CCAT1 were approximately 10.8 fold higher in GC samples than in samples taken from the negative control group (RQ=21.1±5 vs. RQ=1.95±0.4, respectively, p<0.001). Interestingly, CCAT1 expression was significantly overexpressed in adjacent normal tissues when compared to the negative control group (RQ = 15.25±2 vs. RQ=1.95±0.4, respectively, p<0.001). Tissues obtained from recurrent GC cases showed the highest expression levels (RQ = 88.8±31; p<0.001). Expression levels increased with tumor stage (T4- 36.4±15, T3- 16.1±6, T2- 4.7±1), however this did not reach statistical significance (p=0.2). There was no difference in CCAT1 expression between intestinal and diffuse type GC (RQ=22.4±7 vs. 22.4±16, respectively, p=0.9). Within the normal gastric tissue samples, no significant difference in CCAT1 expression was observed in helicobacter pylori negative and positive patients (RQ= 2.4±0.9 vs. 0.93±0.2, respectively, p=0.13). Conclusion: CCAT1 is up-regulated in gastric cancer, and may serve as a potential bio-marker for early detection and surveillance.
Open Access
In silico validation of prognostic mRNA signature in gastric cancer and identification and validation of novel gastric tissue specific reference genes for quantitative PCR
(2021-07) Ishraq, Marzana
Gastric adenocarcinoma is a molecularly and histologically heterogeneous neoplasm with a predictively disastrous outcome if undiagnosed at early stages. Amidst global declines of gastric cancer rates, it remains the 5th most common malignancy with the 4th worst outcome of all cancers. Predictive and prognostic clinical biomarkers are scarce in gastric cancer due to its immense heterogeneity. Identifying novel biomarkers for gastric cancer is an emerging field. Previously in our lab, a 20 gene mRNA signature was developed which successfully stratified gastric cancer patients into poor and good prognosis. In this thesis, we attempted to shorten this list to a five gene signature which will successfully stratify patients into similar clusters as the 20 genes. The 5 genes being, HEYL, CALD1, ACTA2, TAGLN and TPM2. Moreover, we validated the efficacy of our 5-gene signature to stratify patients based on their prognoses in silico. The second half of the thesis focuses on identifying a set of gastric tissue specific reference genes by analyzing high-throughput gene expression data. Most commonly used reference genes are known to have varying expression in cancer tissue which often leads to an issue with reproducibility in cancer research. We aimed to design an algorithm which identifies a list of stable transcripts within a particular tissue type. We identified 3 genes EWSR1, SF1 and HNRNPK which showed stable expression throughout gastric tissue, both in normal and cancer in silico. Ex vivo validation experiments using gastric tumor and adjacent normal RNA show promise for the efficacy of our genes compared to GAPDH and B2M.
Open Access
Prediction of prognosis and chemosensitivity in gastrointestinal cancers
(2017-12) Demirkol, Seçil
Colon and gastric cancers are the third and fifth cancer types with the poorest survival. Surgery is considered the primary treatment option, which can be curative. However the decision as to whether chemotherapy administration after surgery is needed, is critical for especially stage 2 colon cancer; since a group of patients who receive chemotherapy do not have significantly improved clinical outcome. For this purpose, clinical risk factors are currently evaluated to determine patients with a high risk of progression. However this is not standardized by guidelines yet. Therefore, in this thesis my first aim was to ex vivo validate two novel independent mRNA based biomarkers, ULBP2 and SEMA5A, which have been previously identified in our lab, and to generate a prognostic signature which could stratify colon cancer patients with differential prognostic profiles using the best stratification method. I showed that a 3-group prognostic signature, SU-GIB, based on expression of these two genes is associated with cancer-specific, disease-free, and overall survival independent of clinical confounding factors in colon cancer. I performed in silico analysis in order to understand the biological details of the prognostic distinction, and revealed that patients with poorer prognosis show higher expression of pro-inflammatory cytokines and a more mesenchymal profile. Patients with better clinical outcome exhibit a more epithelial profile with higher levels of phosphorylated EGFR and Shc proteins. Analysis of high-throughput drug cytotoxicity databases also showed that colon cancer cell lines with „Bad‟ SU-GIB signature are more sensitive to a dual PI3K-MTOR inhibitor, BEZ235. In this thesis, my second goal was to define prognostic and molecular sub-groups for gastric cancer and characterize the specific biology of each sub-group. Utilizing an unsupervised approach on publicly available microarray data, I identified 3 biological groups, which harbor differential characteristics related to ECM involvement, EMT, proliferation and cell cycle. Moreover I identified distinct prognostic groups which are related to this molecular classification which can further stratify patients with known pathologic subtypes (diffuse and intestinal). I found that EMT was an important parameter for molecular and prognostic classifications for both types of cancers. I therefore, studied high-throughput drug cytotoxicity databases in order to identify selective compounds with selective growth inhibition on epithelial or mesenchymal cancer cells. I identified EGFR inhibitors as being significantly more effective on epithelial cancer cells regardless of the tissue type. My future plans include the large scale validation of SU-GIB, ex vivo validation of the gastric prognostic signature, and in vitro studies that would demonstrate effectivity of EGFR inhibitors on epithelial cancer cells and combination of EGFR inhibitors with MET inducers.