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Diagnostics
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Gastric Cancer: Diagnosis and Management
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Gastric Cancer: Diagnosis and Management

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 8291

Special Issue Editors

Dr. Takayuki Ando

E-Mail Website
Guest Editor
Third Department of Internal Medicine, University of Toyama, Toyama, Japan
Interests: cancer chemotherapy; translational research; endoscopy
Dr. Ayumu Hosokawa

E-Mail Website
Guest Editor
Department of Clinical Oncology, University of Miyazakidisabled, Miyazaki, Japan
Interests: oncology

Special Issue Information

Dear Colleagues,

Gastric cancer has ranked as the third leading cause of cancer mortality worldwide, although recent innovation of surgery and chemotherapy, including targeted therapies and immune checkpoint inhibitors, has changed clinical practice. Therefore, early detection and improvement of cancer management has been required. In this Special Issue, we will discuss the recent discovery of molecular alteration to detect cancer development and progression, advances in endoscopic diagnosis and surgical treatment, and new findings of chemotherapy, targeted therapy and immunotherapy for gastric cancer. We intend for this Special Issue to be informative for all researchers of gastric cancer.

Dr. Takayuki Ando
Dr. Ayumu Hosokawa
Guest Editors

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. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

16 pages, 3378 KiB  
Article
MAGEA11 as a STAD Prognostic Biomarker Associated with Immune Infiltration
by Chen Xiao, Linhui Yang, Liangzi Jin, Faqin Zhang, Jingbo Liu, Chunyu Yu, Lei Tao and Changfu Li
Diagnostics 2022, 12(10), 2506; https://doi.org/10.3390/diagnostics12102506 - 16 Oct 2022
Cited by 2 | Viewed by 1988
Abstract
Expression of MAGE family member A11 (MAGEA11) is upregulated in different tumors. However, in gastric cancer, the prognostic significance of MAGEA11 and its relationship with immune infiltration remain largely unknown. The expression of MAGEA11 in pan-cancer and the receiver operating characteristic [...] Read more.
Expression of MAGE family member A11 (MAGEA11) is upregulated in different tumors. However, in gastric cancer, the prognostic significance of MAGEA11 and its relationship with immune infiltration remain largely unknown. The expression of MAGEA11 in pan-cancer and the receiver operating characteristic (ROC) and survival impact of gastric cancer were evaluated by The Cancer Genome Atlas (TCGA). Whether MAGEA11 was an independent risk factor was assessed by Cox analysis. Nomograms were constructed from MAGEA11 and clinical variables. Gene functional pathway enrichment was obtained based on MAGEA11 differential analysis. The relationship between MAGEA11 and immune infiltration was determined by the Tumor Immunity Estimation Resource (TIMER) and the Tumor Immune System Interaction Database (TISIDB). Finally, MAGEA11-sensitive drugs were predicted based on the CellMiner database. The results showed that the expression of MAGEA11 mRNA in gastric cancer tissues was significantly higher than that in normal tissues. The ROC curve indicated an AUC value of 0.667. Survival analysis showed that patients with high MAGEA11 had poor prognosis (HR = 1.43, p = 0.034). In correlation analysis, MAGEA11 mRNA expression was found to be associated with tumor purity and immune invasion. Finally, drug sensitivity analysis found that the expression of MAGEA11 was correlated with seven drugs. Our study found that upregulated MAGEA11 in gastric cancer was significantly associated with lower survival and invasion by immune infiltration. It is suggested that MAGEA11 may be a potential biomarker and immunotherapy target for gastric cancer. Full article
(This article belongs to the Special Issue Gastric Cancer: Diagnosis and Management)
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14 pages, 14280 KiB  
Article
Demarcation Line Determination for Diagnosis of Gastric Cancer Disease Range Using Unsupervised Machine Learning in Magnifying Narrow-Band Imaging
by Shunsuke Okumura, Misa Goudo, Satoru Hiwa, Takeshi Yasuda, Hiroaki Kitae, Yuriko Yasuda, Akira Tomie, Tatsushi Omatsu, Hiroshi Ichikawa, Nobuaki Yagi and Tomoyuki Hiroyasu
Diagnostics 2022, 12(10), 2491; https://doi.org/10.3390/diagnostics12102491 - 14 Oct 2022
Viewed by 2545
Abstract
Background and Aims: It is important to determine an accurate demarcation line (DL) between the cancerous lesions and background mucosa in magnifying narrow-band imaging (M-NBI)-based diagnosis. However, it is difficult for novice endoscopists. We aimed to automatically determine the accurate DL using a [...] Read more.
Background and Aims: It is important to determine an accurate demarcation line (DL) between the cancerous lesions and background mucosa in magnifying narrow-band imaging (M-NBI)-based diagnosis. However, it is difficult for novice endoscopists. We aimed to automatically determine the accurate DL using a machine learning method. Methods: We used an unsupervised machine learning approach to determine the DLs. Our method consists of the following four steps: (1) an M-NBI image is segmented into superpixels using simple linear iterative clustering; (2) the image features are extracted for each superpixel; (3) the superpixels are grouped into several clusters using the k-means method; and (4) the boundaries of the clusters are extracted as DL candidates. The 23 M-NBI images of 11 cases were used for performance evaluation. The evaluation investigated the similarity of the DLs identified by endoscopists and our method, and the Euclidean distance between the two DLs was calculated. For the single case of 11 cases, the histopathological examination was also conducted to evaluate the proposed system. Results: The average Euclidean distances for the 11 cases were 10.65, 11.97, 7.82, 8.46, 8.59, 9.72, 12.20, 9.06, 22.86, 8.45, and 25.36. The results indicated that the proposed method could identify similar DLs to those identified by experienced doctors. Additionally, it was confirmed that the proposed system could generate pathologically valid DLs by increasing the number of clusters. Conclusions: Our proposed system can support the training of inexperienced doctors as well as enrich the knowledge of experienced doctors in endoscopy. Full article
(This article belongs to the Special Issue Gastric Cancer: Diagnosis and Management)
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10 pages, 1628 KiB  
Article
DNA Methylation of HOXA11 Gene as Prognostic Molecular Marker in Human Gastric Adenocarcinoma
by Povilas Ignatavicius, Albertas Dauksa, Justas Zilinskas, Mintaute Kazokaite, Romualdas Riauka and Giedrius Barauskas
Diagnostics 2022, 12(7), 1686; https://doi.org/10.3390/diagnostics12071686 - 11 Jul 2022
Cited by 2 | Viewed by 1503
Abstract
Hypermethylation of tumor suppressor genes and hypomethylation of oncogenes might be identified as possible biomarkers in gastric cancer (GC). We aimed to assess the DNA methylation status of selected genes in GC tissue samples and evaluate these genes’ prognostic importance on patient survival. [...] Read more.
Hypermethylation of tumor suppressor genes and hypomethylation of oncogenes might be identified as possible biomarkers in gastric cancer (GC). We aimed to assess the DNA methylation status of selected genes in GC tissue samples and evaluate these genes’ prognostic importance on patient survival. Patients (99) diagnosed with GC and who underwent gastrectomy were included. We selected a group of genes (RAD51B, GFRA3, AKR7A3, HOXA11, TUSC3, FLI1, SEZ6L, GLDC, NDRG) which may be considered as potential tumor suppressor genes and oncogenes. Methylation of the HOXA11 gene promoter was significantly more frequent in GC tumor tissue (p = 0.006) than in healthy gastric mucosa. The probability of surviving longer (71.2 months (95% CI 57–85.3) vs. 44.3 months (95% CI 34.8–53.9)) was observed with unmethylated HOXA11 promoter in cancer tissues. Survival in patients with a methylation of HOXA11 promoter either in healthy gastric mucosa or gastric cancer tissue was twice as high as in patients with a methylation of HOXA11 promoter in both healthy gastric mucosa and cancer tissue (61.2 months (95% CI 50.9–71.4) vs. 28.5 months (95% CI 20.8–36.2)). Multivariate Cox analysis revealed the HOXA11 methylation as significantly associated with patients’ survival (HR = 2.4, 95% CI 1.19–4.86). Our results suggest that the HOXA11 gene might be a potential prognostic molecular marker in patients with gastric adenocarcinoma. Full article
(This article belongs to the Special Issue Gastric Cancer: Diagnosis and Management)
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9 pages, 1650 KiB  
Article
ALK, NUT, and TRK Do Not Play Relevant Roles in Gastric Cancer—Results of an Immunohistochemical Study in a Large Series
by Marie-Isabelle Glückstein, Sebastian Dintner, Silvia Miller, Dmytro Vlasenko, Gerhard Schenkirsch, Abbas Agaimy, Bruno Märkl and Bianca Grosser
Diagnostics 2022, 12(2), 429; https://doi.org/10.3390/diagnostics12020429 - 7 Feb 2022
Cited by 4 | Viewed by 1497
Abstract
ALK, NUT, and TRK are rare molecular aberrations that are pathognomonic for specific rare tumors. In low frequencies, however, they are found in a wide range of other tumor entities. This study aimed to investigate the frequency, association with clinicopathological characteristics, and prognosis [...] Read more.
ALK, NUT, and TRK are rare molecular aberrations that are pathognomonic for specific rare tumors. In low frequencies, however, they are found in a wide range of other tumor entities. This study aimed to investigate the frequency, association with clinicopathological characteristics, and prognosis of the immunohistochemical expressions of ALK, NUT, and TRK in 477 adenocarcinomas of the stomach and gastroesophageal junction. Seven cases (1.5%) showed an expression of TRK. In NGS, no NTRK fusion was confirmed. No case with ALK or NUT expression was detected. ALK, NUT, and NTRK expression does not seem to play an important role in gastric carcinomas. Full article
(This article belongs to the Special Issue Gastric Cancer: Diagnosis and Management)
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