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Molecular Diagnostic Strategies for Prediction and Prognosis of Gastric Cancer
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Molecular Diagnostic Strategies for Prediction and Prognosis of Gastric Cancer

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".

Deadline for manuscript submissions: 20 January 2025 | Viewed by 8236

Special Issue Editor

Dr. Matteo Curtarello

E-Mail Website
Guest Editor
Istituto Oncologico Veneto IOV - IRCCS, Padova, Italy
Interests: liquid biopsy; cancer

Special Issue Information

Dear Colleagues,

Gastric cancer is the fifth most common cancer and the third cause of cancer death. The clinical outcomes of these patients are not encouraging, with a low survival rate of 5 years. Often, the disease is diagnosed at advanced stages and this negatively affects patients’ outcomes. Intra-tumoural and inter-tumoural heterogeneity is a feature of gastric cancer, which leads to diagnostic and therapeutic challenges.

Currently, diagnostic typing is based on immunohistochemistry evaluation of the expression of a few specific biomarkers that are correlated with disease prognosis. Moreover, to date, no validated biomarkers that are predictive of the treatment response to targeted therapies are available, with the exception of HER2 overexpression and MSI status. Taking into account this scenario, there is an urgent need to develop new predictive and prognostic diagnostic strategies for gastric cancer patients’ management.

For this reason, this Special Issue will embrace papers that reveal new diagnostic molecular approaches that support pathological diagnosis with high specificity and sensitivity and studies that assess the role of liquid biopsy as a new valuable diagnostic method.  In addition, new manuscripts that investigate biomarkers mirroring the prognosis or response to therapy will be highly valued. All these studies will have a significant impact on these patients’ outcomes in the era of personalized medicine.

In this Special Issue, original articles and reviews are both welcome.

Dr. Matteo Curtarello
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • prognostic biomarker
  • predictive biomarker
  • gastric cancer
  • molecular diagnostic strategy
  • solid biopsy
  • liquid biopsy
  • real-time PCR
  • digital PCR
  • next-generation sequencing

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Published Papers (4 papers)

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Research

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16 pages, 8949 KiB  
Article
Exploring the Prognosis-Related Genetic Variation in Gastric Cancer Based on mGWAS
by Yuling Zhang, Yanping Lyu, Liangping Chen, Kang Cao, Jingwen Chen, Chenzhou He, Xuejie Lyu, Yu Jiang, Jianjun Xiang, Baoying Liu and Chuancheng Wu
Int. J. Mol. Sci. 2023, 24(20), 15259; https://doi.org/10.3390/ijms242015259 - 17 Oct 2023
Cited by 3 | Viewed by 1779
Abstract
The use of metabolome genome-wide association studies (mGWAS) has been shown to be effective in identifying functional genes in complex diseases. While mGWAS has been applied to biomedical and pharmaceutical studies, its potential in predicting gastric cancer prognosis has yet to be explored. [...] Read more.
The use of metabolome genome-wide association studies (mGWAS) has been shown to be effective in identifying functional genes in complex diseases. While mGWAS has been applied to biomedical and pharmaceutical studies, its potential in predicting gastric cancer prognosis has yet to be explored. This study aims to address this gap and provide insights into the genetic basis of GC survival, as well as identify vital regulatory pathways in GC cell progression. Genome-wide association analysis of plasma metabolites related to gastric cancer prognosis was performed based on the Generalized Linear Model (GLM). We used a log-rank test, LASSO regression, multivariate Cox regression, GO enrichment analysis, and the Cytoscape software to visualize the complex regulatory network of genes and metabolites and explored in-depth genetic variation in gastric cancer prognosis based on mGWAS. We found 32 genetic variation loci significantly associated with GC survival-related metabolites, corresponding to seven genes, VENTX, PCDH 7, JAKMIP1, MIR202HG, MIR378D1, LINC02472, and LINC02310. Furthermore, this study identified 722 Single nucleotide polymorphism (SNP) sites, suggesting an association with GC prognosis-related metabolites, corresponding to 206 genes. These 206 possible functional genes for gastric cancer prognosis were mainly involved in cellular signaling molecules related to cellular components, which are mainly involved in the growth and development of the body and neurological regulatory functions related to the body. The expression of 23 of these genes was shown to be associated with survival outcome in gastric cancer patients in The Cancer Genome Atlas (TCGA) database. Based on the genome-wide association analysis of prognosis-related metabolites in gastric cancer, we suggest that gastric cancer survival-related genes may influence the proliferation and infiltration of gastric cancer cells, which provides a new idea to resolve the complex regulatory network of gastric cancer prognosis. Full article
(This article belongs to the Special Issue Molecular Diagnostic Strategies for Prediction and Prognosis of Gastric Cancer)
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16 pages, 8630 KiB  
Article
Prognostic Implication of Plasma Metabolites in Gastric Cancer
by Kang Cao, Yanping Lyu, Jingwen Chen, Chenzhou He, Xuejie Lyu, Yuling Zhang, Liangping Chen, Yu Jiang, Jianjun Xiang, Baoying Liu and Chuancheng Wu
Int. J. Mol. Sci. 2023, 24(16), 12774; https://doi.org/10.3390/ijms241612774 - 14 Aug 2023
Cited by 6 | Viewed by 2023
Abstract
Gastric cancer (GC) typically carries a poor prognosis as it is often diagnosed at a late stage. Altered metabolism has been found to impact cancer outcomes and affect patients’ quality of life, and the role of metabolites in gastric cancer prognosis has not [...] Read more.
Gastric cancer (GC) typically carries a poor prognosis as it is often diagnosed at a late stage. Altered metabolism has been found to impact cancer outcomes and affect patients’ quality of life, and the role of metabolites in gastric cancer prognosis has not been sufficiently understood. We aimed to establish a prognostic prediction model for GC patients based on a metabolism-associated signature and identify the unique role of metabolites in the prognosis of GC. Thus, we conducted untargeted metabolomics to detect the plasma metabolites of 218 patients with gastric adenocarcinoma and explored the metabolites related to the survival of patients with gastric cancer. Firstly, we divided patients into two groups based on the cutoff value of the abundance of each of the 60 metabolites and compared the differences using Kaplan–Meier (K-M) survival analysis. As a result, 23 metabolites associated with gastric cancer survival were identified. To establish a risk score model, we performed LASSO regression and Cox regression analysis on the 60 metabolites and identified 8 metabolites as an independent prognostic factor. Furthermore, a nomogram incorporating clinical parameters and the metabolic signature was constructed to help individualize outcome predictions. The results of the ROC curve and nomogram plot showed good predictive performance of metabolic risk features. Finally, we performed pathway analysis on the 24 metabolites identified in the two parts, and the results indicated that purine metabolism and arachidonic acid metabolism play important roles in gastric cancer prognosis. Our study highlights the important role of metabolites in the progression of gastric cancer and newly identified metabolites could be potential biomarkers or therapeutic targets for gastric cancer patients. Full article
(This article belongs to the Special Issue Molecular Diagnostic Strategies for Prediction and Prognosis of Gastric Cancer)
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Review

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23 pages, 708 KiB  
Review
Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer
by Tasuku Matsuoka and Masakazu Yashiro
Int. J. Mol. Sci. 2024, 25(11), 5880; https://doi.org/10.3390/ijms25115880 - 28 May 2024
Cited by 3 | Viewed by 2358
Abstract
Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of [...] Read more.
Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of “big data” and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment. Full article
(This article belongs to the Special Issue Molecular Diagnostic Strategies for Prediction and Prognosis of Gastric Cancer)
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27 pages, 1637 KiB  
Review
Non-Coding RNA as Biomarkers and Their Role in the Pathogenesis of Gastric Cancer—A Narrative Review
by Estera Bakinowska, Kajetan Kiełbowski, Patryk Skórka, Aleksandra Dach, Joanna Olejnik-Wojciechowska, Agata Szwedkowicz and Andrzej Pawlik
Int. J. Mol. Sci. 2024, 25(10), 5144; https://doi.org/10.3390/ijms25105144 - 9 May 2024
Cited by 1 | Viewed by 1403
Abstract
Non-coding RNAs (ncRNAs) represent a broad family of molecules that regulate gene expression, including microRNAs, long non-coding RNAs and circular RNAs, amongst others. Dysregulated expression of ncRNAs alters gene expression, which is implicated in the pathogenesis of several malignancies and inflammatory diseases. Gastric [...] Read more.
Non-coding RNAs (ncRNAs) represent a broad family of molecules that regulate gene expression, including microRNAs, long non-coding RNAs and circular RNAs, amongst others. Dysregulated expression of ncRNAs alters gene expression, which is implicated in the pathogenesis of several malignancies and inflammatory diseases. Gastric cancer is the fifth most frequently diagnosed cancer and the fourth most common cause of cancer-related death. Studies have found that altered expression of ncRNAs may contribute to tumourigenesis through regulating proliferation, apoptosis, drug resistance and metastasis. This review describes the potential use of ncRNAs as diagnostic and prognostic biomarkers. Moreover, we discuss the involvement of ncRNAs in the pathogenesis of gastric cancer, including their interactions with the members of major signalling pathways. Full article
(This article belongs to the Special Issue Molecular Diagnostic Strategies for Prediction and Prognosis of Gastric Cancer)
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