Extracellular Matrix Characterization in Gastric Cancer Helps to Predict Prognosis and Chemotherapy Response

Yang, Zhi; Xue, Feifei; Li, Minhuan; Zhu, Xuyou; Lu, Xiaofeng; Wang, Chao; Xu, En; Wang, Xingzhou; Zhang, Liang; Heng, Yu; Ren, Chuanfu; Wang, Hao; Wang, Yizhou; Chen, Jie; Guan, Wenxian; Xia, Xuefeng

doi:10.3389/fonc.2021.753330

Cited by 21 publications

(17 citation statements)

References 68 publications

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“…By comparing the stomach tissues of individuals with normal, premalignant, and malignant lesions, Zhao et al found that some collagen genes, such as COL4A1 and COL5A1, were significantly increased in malignant lesions of stomach compared with in premalignant lesions and were independent prognostic markers [24]. Further, ECM characterization in gastric cancer has been shown to predict treatment response and prognosis [25]. Thus, as more experimental and clinical observations are strongly indicating that ECM constituents, receptors and associated signaling molecules are promising biomarkers of prognosis and/or therapeutic targets; novel and more effective gastric cancer treatments that combine strategies targeting ECM with corresponding inhibitors or immuno-oncology agents could lead to improve therapeutic outcomes.…”

Section: Discussionmentioning

confidence: 99%

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

Ding

Zhang

Jiang

et al. 2022

Computational and Mathematical Methods in Medicine

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Objective. Gastric cancer is among the most common malignant tumors of the digestive system. This study explored the molecular mechanisms and potential therapeutic targets for gastric cancer occurrence and progression using bioinformatics. Methods. The gastric cancer microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. The R package was used for data mining and screening differentially expressed genes (DEGs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Based on the protein-protein interaction (PPI) network analysis, core targets and core subsets were screened. Then, the relationship between the expression level of the core genes and the prognosis of gastric cancer patients was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) database. Results. Using the GSE19826 and GSE54129 datasets, a total of 550 DEGs were identified, including 248 upregulated and 302 downregulated genes. GO and KEGG analyses showed that the upregulated DEGs were mainly enriched in the extracellular matrix (ECM) organization of the biological process (BP), the collagen-containing ECM of cellular component (CC), and the ECM structural constituent of molecular function (MF). DEGs were also enriched in human papillomavirus infections, the focal adhesion pathway, PI3K-Akt signaling pathway, and among others. The downregulated DEGs were mainly enriched in digestion, basal part of the cell, and aldo-keto reductase (NADP) activity. And the above pathways were enriched primarily in the metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, and retinol metabolism. Five core genes, including COL1A2, COL3A1, BGN, FN1, and VCAN, were significantly highly expressed in gastric cancer patients and were associated with poor prognosis. Conclusion. This study identified new potential molecular targets closely related to gastric cancer occurrence and development via mining public data using bioinformatics analysis methods.

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Section: Discussionmentioning

confidence: 99%

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

Ding

Zhang

Jiang

et al. 2022

Computational and Mathematical Methods in Medicine

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“…Reportedly, signalling pathways that drive epithelial to mesenchymal transition (EMT) and the IGF1/IGF1 receptor pathway are substantially active in mesenchymal gastric cancer. 4 Additionally, a high extracellular matrix score is associated with a poor prognosis for gastric cancer, 5 and proteoglycans and glycosaminoglycans are regulators of cancer stem cell (CSC) function. 6 In general, the SIG500 genes were enriched in pathways associated with CSCs and the mesenchymal subtype of gastric cancer.…”

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confidence: 99%

Prognosis‐related gene signature is enriched in cancer‐associated fibroblasts in the stem‐like subtype of gastric cancer

Sung

Cheong

2022

Clinical & Translational Med

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related gene signature is enriched in cancer-associated fibroblasts in the stem-like subtype of gastric cancer Dear EditorPrognostic markers in gastric cancer 1 are not only used to clinically classify patients into groups but are also being studied extensively for assessing cancer progression and drug development. Hence, the mechanisms by which genes associated with different prognoses in gastric cancer affect stem-like molecular subtypes require further investigation. We selected the top 500 genes with significantly different prognostic values for stomach adenocarcinoma in The Cancer Genome Atlas (TCGA) (Figure 1A, Table S1). The genes differed significantly between the high and low expression samples (Figure 1B). Most of these 500 genes were enriched during synapse assembly, trans-synaptic signalling, and developmental growth (Figure 1C). The frequency of SIG500 detection in each molecular subtype of gastric cancer was determined, and 99% of the genes were found to be present in the stem-like molecular subtype corresponding to the high group (Figure 1D). The generated Kaplan-Meier plot showed that the group with a high SIG500 score had poor prognosis in three cohorts (Y497, GSE62254 and GSE15459) (Figure 1E). Additionally, we analysed the enriched biological pathways in each cohort in the high SIG500 group. Thus, we observed that in the Yonsei Hospital cohort, 2 biological pathways related to glycerophospholipid biosynthesis were enriched; in the GSE62254 cohort, pathways related to the M phase were enriched, while in the GSE15459 cohort, pathways related to muscle structure development and the NABA core matrix were enriched (Figure 2A). Thirty-two master regulators of cancer, blood vessel morphogenesis, NABA core matrisome, 3 insulin-like growth factor (IGF) transport, and uptake by IGF binding proteins were enriched in SIG500 genes (Figure 2B). Reportedly, signalling pathways that drive epithelial to mesenchymal transition (EMT) and the IGF1/IGF1 receptor pathway are substantiallyThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…For HER2-negative advanced GC patients, the primary treatment is still limited to platinum, fluoropyrimidine, and paclitaxel chemotherapeutic drugs ( 15 ). Furthermore, there are significant individual differences in prognosis even among patients at the same stage receiving the same treatment ( 10 , 18 , 49 – 51 ). Some patients clearly benefit from chemotherapy, while some patients do not and may have a worse prognosis due to the toxic effects of chemotherapy ( 10 , 16 , 17 ).…”

Section: Discussionmentioning

confidence: 99%

“…The S-II was mainly enriched in ECM-related pathways. Interestingly, it has been reported in relevant studies that ECM can form a physical barrier to anticancer drugs ( 54 , 55 ) and prevent the effects of chemotherapy and immunotherapy, so the deposition of ECM is associated with poor prognosis of various tumors ( 49 ). One of the representative ECM genes, FBN1 , is up-regulated in S-II.…”

Section: Discussionmentioning

confidence: 99%

“…One of the representative ECM genes, FBN1 , is up-regulated in S-II. Relevant studies have verified that knocking out this gene can make cancer cells sensitive to chemotherapy drugs ( 49 ). Therefore, determining the characteristics of the ECM microenvironment in patients with chemotherapy insensitivity can help predict prognosis and chemotherapy response and provide indications for treatment.…”

Section: Discussionmentioning

confidence: 99%

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Deep Learning-Based Protein Features Predict Overall Survival and Chemotherapy Benefit in Gastric Cancer

et al. 2022

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Gastric cancer (GC) is one of the most common malignant tumors with a high mortality rate worldwide and lacks effective methods for prognosis prediction. Postoperative adjuvant chemotherapy is the first-line treatment for advanced gastric cancer, but only a subgroup of patients benefits from it. Here, we used 833 formalin-fixed, paraffin-embedded resected tumor samples from patients with TNM stage II/III GC and established a proteomic subtyping workflow using 100 deep-learned features. Two proteomic subtypes (S-I and S-II) with overall survival differences were identified. S-I has a better survival rate and is sensitive to chemotherapy. Patients in the S-I who received adjuvant chemotherapy had a significant improvement in the 5-year overall survival rate compared with patients who received surgery alone (65.3% vs 52.6%; log-rank P = 0.014), but no improvement was observed in the S-II (54% vs 51%; log-rank P = 0.96). These results were verified in an independent validation set. Furthermore, we also evaluated the superiority and scalability of the deep learning-based workflow in cancer molecular subtyping, exhibiting its great utility and potential in prognosis prediction and therapeutic decision-making.

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Extracellular Matrix Characterization in Gastric Cancer Helps to Predict Prognosis and Chemotherapy Response

Cited by 21 publications

References 68 publications

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

Prognosis‐related gene signature is enriched in cancer‐associated fibroblasts in the stem‐like subtype of gastric cancer

Deep Learning-Based Protein Features Predict Overall Survival and Chemotherapy Benefit in Gastric Cancer

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