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Moreira FC, Sarquis DP, de Souza JES, Avelar DDS, Araújo TMT, Khayat AS, dos Santos SEB, de Assumpção PP. Treasures from trash in cancer research. Oncotarget 2022; 13:1246-1257. [PMID: 36395362 PMCID: PMC9671455 DOI: 10.18632/oncotarget.28308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Cancer research has significantly improved in recent years, primarily due to next-generation sequencing (NGS) technology. Consequently, an enormous amount of genomic and transcriptomic data has been generated. In most cases, the data needed for research goals are used, and unwanted reads are discarded. However, these eliminated data contain relevant information. Aiming to test this hypothesis, genomic and transcriptomic data were acquired from public datasets. MATERIALS AND METHODS Metagenomic tools were used to explore genomic cancer data; additional annotations were used to explore differentially expressed ncRNAs from miRNA experiments, and variants in adjacent to tumor samples from RNA-seq experiments were also investigated. RESULTS In all analyses, new data were obtained: from DNA-seq data, microbiome taxonomies were characterized with a similar performance of dedicated metagenomic research; from miRNA-seq data, additional differentially expressed sncRNAs were found; and in tumor and adjacent to tumor tissue data, somatic variants were found. CONCLUSIONS These findings indicate that unexplored data from NGS experiments could help elucidate carcinogenesis and discover putative biomarkers with clinical applications. Further investigations should be considered for experimental design, providing opportunities to optimize data, saving time and resources while granting access to multiple genomic perspectives from the same sample and experimental run.
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Affiliation(s)
- Fabiano Cordeiro Moreira
- 1Núcleo de Pesquisas em Oncologia/Universidade Federal do Pará, Belém, Pará, Brazil,*Co-first authors
| | - Dionison Pereira Sarquis
- 1Núcleo de Pesquisas em Oncologia/Universidade Federal do Pará, Belém, Pará, Brazil,*Co-first authors
| | | | | | | | - André Salim Khayat
- 1Núcleo de Pesquisas em Oncologia/Universidade Federal do Pará, Belém, Pará, Brazil
| | - Sidney Emanuel Batista dos Santos
- 1Núcleo de Pesquisas em Oncologia/Universidade Federal do Pará, Belém, Pará, Brazil,3Instituto de Ciências Biológicas/Universidade Federal do Pará, Belém, Pará, Brazil
| | - Paulo Pimentel de Assumpção
- 1Núcleo de Pesquisas em Oncologia/Universidade Federal do Pará, Belém, Pará, Brazil,Correspondence to:Paulo Pimentel de Assumpção, email:
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Koulis A, Di Costanzo N, Mitchell C, Lade S, Goode D, Busuttil RA, Boussioutas A. CD10 and Das1: a biomarker study using immunohistochemistry to subtype gastric intestinal metaplasia. BMC Gastroenterol 2022; 22:197. [PMID: 35448971 PMCID: PMC9026694 DOI: 10.1186/s12876-022-02268-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Accepted: 03/30/2022] [Indexed: 12/24/2022] Open
Abstract
Background Intestinal metaplasia (IM) is considered a key pivot point in the Correa model of gastric cancer (GC). It is histologically subtyped into the complete and incomplete subtypes, the latter being associated with a greater risk of progression. However, the clinical utility of IM subtyping remains unclear, partially due to the absence of reliable defining biomarkers. Methods Based on gene expression data and existing literature, we selected CD10 and Das1 as candidate biomarkers to distinguish complete and incomplete IM glands in tissues from patients without GC (IM-GC) and patients with GC (IM + GC). Immunohistochemical staining of individually subtyped IM glands was scored after blinding by two researchers using tissue belonging to both IM-GC and IM + GC patients. Whole tissue Das1 staining was further assessed using digital image quantification (cellSens Dimension, Olympus). Results Across both cohorts CD10 stained the IM brush border and was shown to have a high sensitivity (87.5% and 94.9% in IM-GC and IM + GC patients respectively) and specificity (100.0% and 96.7% respectively) with an overall AUROC of 0.944 for complete IM glands. By contrast Das1 stained mainly goblet cells and the apical membrane of epithelial cells, mostly of incomplete IM glands with a low sensitivity (28.6% and 29.3% in IM-GC and IM + GC patients respectively) but high specificity (98.3% and 85.1% respectively) and an overall AUROC of 0.603 for incomplete IM glands. A combined logistic regression model showed a significant increase in AUROC for detecting complete IM glands (0.955 vs 0.970). Whole tissue digital quantification of Das1 staining showed a significant association with incomplete IM compared to complete IM, both in IM-GC and in IM + GC patients (p = 0.016 and p = 0.009 respectively, Mann–Whitney test and unpaired t test used). Additionally, complete IM in IM + GC patients exhibited significantly more Das1 staining than in IM-GC patients (p = 0.019, Mann–Whitney test). Conclusions These findings suggest that CD10 is an outstanding biomarker for complete IM and Das1 may be useful as a secondary biomarker for IM glands at greater risk of progression irrespective of IM subtype. Overall, the clinical use of these biomarkers could lead to improved patient stratification and targeted surveillance. Supplementary Information The online version contains supplementary material available at 10.1186/s12876-022-02268-z.
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Affiliation(s)
- Athanasios Koulis
- Upper Gastrointestinal Translational Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia
| | - Natasha Di Costanzo
- Upper Gastrointestinal Translational Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia
| | - Catherine Mitchell
- Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Stephen Lade
- Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - David Goode
- The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.,Computational Cancer Biology Program, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Rita A Busuttil
- Upper Gastrointestinal Translational Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Australia.,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.,Department of Medicine, Royal Melbourne Hospital, Melbourne, Australia
| | - Alex Boussioutas
- Upper Gastrointestinal Translational Research Laboratory, Peter MacCallum Cancer Centre, Melbourne, Australia. .,The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia. .,Department of Medicine, Royal Melbourne Hospital, Melbourne, Australia. .,Upper Gastrointestinal Translational Research Laboratory, Peter MacCallum Cancer Centre, 305 Grattan Street, Parkville, VIC, 3050, Australia.
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Cai C, Yang L, Zhuang X, He Y, Zhou K. A five-lncRNA model predicting overall survival in gastric cancer compared with normal tissues. Aging (Albany NY) 2021; 13:24349-24359. [PMID: 34751670 PMCID: PMC8610123 DOI: 10.18632/aging.203685] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 10/25/2021] [Indexed: 01/05/2023]
Abstract
Aims: In cancer research, normal tissues adjacent to the tumor are usually defined as controls to compare with tumor samples, in order to screen out cancer-related genes. Although there is no obvious difference in pathology between normal tissues adjacent to the tumor and healthy tissues, there are significant changes at the molecular level. We aim to explore more potential tumor biomarkers using healthy tissues as controls rather than normal tissues adjacent to the tumor. Methods: Here we combine the Genotype-Tissue Expression project and The Cancer Genome Atlas for differential gene analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were applied in order to predict the biological effects of related lncRNAs. Results: We established a 5-lncRNA prognosis model with an AUC value of 0.815. Pathway analysis indicated that 5-lncRNA mainly affected tissue carcinogenesis through PI3K-AKT signaling pathway, Focal adhesion, MAPK signaling pathway. Conclusion: The 5-lncRNA prognostic model we set up is more conducive to assess the overall survival time of gastric cancer patients.
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Affiliation(s)
- Congbo Cai
- Emergency Department of Yinzhou No. 2 Hospital, Ningbo 315000, Zhejiang, China
| | - Lei Yang
- Emergency Department of Yinzhou No. 2 Hospital, Ningbo 315000, Zhejiang, China
| | - Xieyan Zhuang
- Gynecology Department of Mingzhou Hospital, Ningbo 315000, Zhejiang, China
| | - Yi He
- Gastroenterology Department of Ningbo No. 9 Hospital, Ningbo 315000, Zhejiang, China
| | - Kena Zhou
- Gastroenterology Department of Ningbo No. 9 Hospital, Ningbo 315000, Zhejiang, China
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