scholarly journals What’s New in Gastric Cancer: The Therapeutic Implications of Molecular Classifications and Future Perspectives

2018 ◽  
Vol 19 (9) ◽  
pp. 2659 ◽  
Author(s):  
Giuseppe Tirino ◽  
Luca Pompella ◽  
Angelica Petrillo ◽  
Maria Laterza ◽  
Annalisa Pappalardo ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
New Technologies ◽  
Standard Of Care ◽  
The Cancer Genome Atlas ◽  
Therapeutic Implications ◽  
Genetic Landscape ◽  
Cancer Genome Atlas ◽  
Selection Of Patients ◽  
Selection Of ◽  
Strong Barrier

Despite some remarkable innovations and the advent of novel molecular classifications the prognosis of patients with advanced gastric cancer (GC) remains overall poor and current clinical application of new advances is disappointing. During the last years only Trastuzumab and Ramucirumab have been approved and currently used as standard of care targeted therapies, but the systemic management of advanced disease did not radically change in contrast with the high number of molecular drivers identified. The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) classifications paved the way, also for GC, to that more contemporary therapeutic approach called “precision medicine” even if tumor heterogeneity and a complex genetic landscape still represent a strong barrier. The identification of specific cancer subgroups is also making possible a better selection of patients that are most likely to respond to immunotherapy. This review aims to critically overview the available molecular classifications summarizing the main druggable molecular drivers and their possible therapeutic implications also taking advantage of new technologies and acquisitions.

scholarly journals Genomically Driven Precision Medicine to Improve Outcomes in Anaplastic Thyroid Cancer

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Nicole Pinto ◽  
Morgan Black ◽  
Krupal Patel ◽  
John Yoo ◽  
Joe S. Mymryk ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Surgical Resection ◽  
Standard Of Care ◽  
Anaplastic Thyroid Cancer ◽  
Genetic Alterations ◽  
The Cancer Genome Atlas ◽  
Genetic Landscape ◽  
Cancer Genome Atlas ◽  
Well Differentiated

Thyroid cancer is an endocrine malignancy with an incidence rate that has been increasing steadily over the past 30 years. While well-differentiated subtypes have a favorable prognosis when treated with surgical resection and radioiodine, undifferentiated subtypes, such as anaplastic thyroid cancer (ATC), are far more aggressive and have a poor prognosis. Conventional therapies (surgical resection, radiation, chemotherapy, and radioiodine) have been utilized for treatment of ATC, yet these treatments have not significantly improved the overall mortality rate. As cancer is a genetic disease, genetic alterations such as mutations, fusions, activation of oncogenes, and silencing of tumor suppressors contribute to its aggressiveness. With the use of next-generation sequencing and the Cancer Genome Atlas, mutation-directed therapy is recognized as the upcoming standard of care. In this review, we highlight the known genetic landscape of ATC and the need for a comprehensive genetic characterization of this disease in order to identify additional therapeutic targets to improve patient outcomes.

scholarly journals Krüppel-Like Factor 7 is a Marker of Aggressive Gastric Cancer and Poor Prognosis

2017 ◽  
Vol 43 (3) ◽  
pp. 1090-1099 ◽  
Author(s):  
Zhonghua Jiang ◽  
Tingting Yu ◽  
Zhining Fan ◽  
Hongmei Yang ◽  
Xin Lin
Keyword(s):  
Gastric Cancer ◽  
Disease Free Survival ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Strong Negative Correlation ◽  
Functional Studies ◽  
Expression Of Genes ◽  
Cancer Genome Atlas

Background/Aims: Krüppel-like factor (KLF) 7 protein is a member of the KLF transcription factor family, which plays important roles in regulating the expression of genes involved in cell growth, proliferation, differentiation and metabolism. However, the role of KLF7 in gastric cancer (GC) is unknown. The aim of this study is to explore the role of KLF7 in GC and its correlation with clinicopathological characteristics and prognosis of GC patients. Methods: We first systematically evaluated dysregulation of the KLF family in The Cancer Genome Atlas (TCGA) GC database. Then, 252 patients who underwent surgery for GC were enrolled to validate the results from the TCGA. Functional studies were also used to explore the role of KLF7 in GC. Results: In the TCGA database, we found that KLF7 was an independent predictor for survival by both univariate and multivariate analysis (P<0.05). In a validation cohort, KLF7 expression was significantly increased in GC tissues compared with adjacent normal controls (P=0.013). High KLF7 expression correlated with inferior prognostic factors, such as T stage (P=0.022), N stage (P =0.005) and lymphovascular invasion (P=0.009). Furthermore, we observed a strong negative correlation between KLF7 expression and 5-year overall survival and disease-free survival in GC patients (P<0.05). Moreover, our in vitro studies showed a notable decrease in migration in KLF7 knockdown cells. Conclusion: KLF7 has an important role in GC progression, as it inhibits GC cell migration and may serve as a prognostic marker.

scholarly journals CPXM1: a novel biomarker for gastric cancer prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Mengxiang Zhu ◽  
Wenwu Yan ◽  
Changsheng Yao ◽  
Qingyi Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Poor Prognosis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Signal Pathways ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background The molecular role of carboxypeptidase X, M14 family member (CPXM1) in oncogenesis or tumor progression remains unclear. The aim of this study was to determine whether CPXM1 can be used as a potential prognostic biomarker for gastric cancer (GC). Methods We first demonstrated the relationship between CPXM1 expression and GC in various public databases. Secondly, the expression of CPXM1 in GC tissues was further verified by immunohistochemical staining using tissue microarray containing 96 cases of GC patients. Kaplan–Meier analysis and a Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CPXM1 and the survival of GC patients. Finally, we used the expression data of CPXM1 in The Cancer Genome Atlas database to predict CPXM1-related signaling pathways through bioinformatics analysis. Results The expression level of CPXM1 in GC tissues was significantly correlated with tumor size (p = 0.041) and lymph node metastasis (p = 0.014). In addition, Kaplan–Meier analysis showed that the expression of CPXM1 in GC tissues was significantly associated with poor prognosis (p = 0.011). Multivariate analysis indicated that CPXM1 is a potential predictor of poor prognosis in GC patients (p = 0.026). The results of biosynthesis analysis demonstrated that the data set of CPXM1 high expression was mainly enriched in cancer-related signal pathways. Conclusion CPXM1 is an effective biomarker for the prognosis of GC patients and may play a key role in the occurrence and progression of GC.

scholarly journals Why MUC16 mutations lead to a better prognosis: A study based on The Cancer Genome Atlas gastric cancer cohort

2021 ◽  
Vol 9 (17) ◽  
pp. 4143-4158
Author(s):  
Yu-Jie Huang ◽  
Zhi-Fei Cao ◽  
Jie Wang ◽  
Jian Yang ◽  
Yi-Jun Wei ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database

2020 ◽  
Vol 9 (4) ◽  
pp. 2599-2608
Author(s):  
Xiqiao Liu ◽  
Liying Gao ◽  
Dongqiong Ni ◽  
Chengao Ma ◽  
Yuping Lu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Candidate Genes ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals An analytical pipeline for DNA Methylation Array Biomarker Studies

2021 ◽  
Author(s):  
Jennifer Lu ◽  
Darren Korbie ◽  
Matt Trau
Keyword(s):  
Dna Methylation ◽  
Feature Selection ◽  
Differential Methylation ◽  
The Cancer Genome Atlas ◽  
Methylation Array ◽  
Epigenetic Biomarkers ◽  
Cancer Genome Atlas ◽  
Dna Methylation Array ◽  
Methylation Patterns ◽  
Selection Of

DNA methylation is one of the most commonly studied epigenetic biomarkers, due to its role in disease and development. The Illumina Infinium methylation arrays still remains the most common method to interrogate methylation across the human genome, due to its capabilities of screening over 480, 000 loci simultaneously. As such, initiatives such as The Cancer Genome Atlas (TCGA) have utilized this technology to examine the methylation profile of over 20,000 cancer samples. There is a growing body of methods for pre-processing, normalisation and analysis of array-based DNA methylation data. However, the shape and sampling distribution of probe-wise methylation that could influence the way data should be examined was rarely discussed. Therefore, this article introduces a pipeline that predicts the shape and distribution of normalised methylation patterns prior to selection of the most optimal inferential statistics screen for differential methylation. Additionally, we put forward an alternative pipeline, which employed feature selection, and demonstrate its ability to select for biomarkers with outstanding differences in methylation, which does not require the predetermination of the shape or distribution of the data of interest. Availability: The Distribution test and the feature selection pipelines are available for download at: https://github.com/uqjlu8/DistributionTest Keywords: DNA methylation, Biomarkers, Cancers, Data Distribution, TCGA, 450K

scholarly journals Tumor microenvironment characterization in stage IV gastric cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Xianxue Zhang ◽  
Feng Yang ◽  
Zhenbao Wang
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Stage Iv ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Stage Iv Gastric Cancer ◽  
Th 17 ◽  
Cancer Genome Atlas

Abstract Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment’s clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. The identification of stage IV GC subtypes has potential clinical implications in stage IV GC treatment.

scholarly journals Reproduction of the Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) Gastric Cancer Molecular Classifications and Their Association with Clinicopathological Characteristics and Overall Survival in Moroccan Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jean Paul Nshizirungu ◽  
Sanae Bennis ◽  
Ihsane Mellouki ◽  
Mohammed Sekal ◽  
Dafr-Allah Benajah ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Research ◽  
Overall Survival ◽  
Molecular Subtypes ◽  
Clinicopathological Features ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Gastric Cancer Patients ◽  
Genome Atlas ◽  
E Cadherin

Introduction. The Cancer Genome Atlas (TCGA) project and Asian Cancer Research Group (ACRG) recently categorized gastric cancer into molecular subtypes. Nevertheless, these classification systems require high cost and sophisticated molecular technologies, preventing their widespread use in the clinic. This study is aimed to generating molecular subtypes of gastric cancer using techniques available in routine diagnostic practice in a series of Moroccan gastric cancer patients. In addition, we assessed the associations between molecular subtypes, clinicopathological features, and prognosis. Methods. Ninety-seven gastric cancer cases were classified according to TCGA, ACRG, and integrated classifications using a panel of four molecular markers (EBV, MSI, E-cadherin, and p53). HER2 status and PD-L1 expression were also evaluated. These markers were analyzed using immunohistochemistry (E-cadherin, p53, HER2, and PD-L1), in situ hybridization (EBV and HER2 equivocal cases), and multiplex PCR (MSI). Results. Our results showed that the subtypes presented distinct clinicopathological features and prognosis. EBV-positive gastric cancers were found exclusively in male patients. The GS (TCGA classification), MSS/EMT (ACRG classification), and E-cadherin aberrant subtype (integrated classification) presented the Lauren diffuse histology enrichment and tended to be diagnosed at a younger age. The MSI subtype was associated with a better overall survival across all classifications (TCGA, ACRG, and integrated classification). The worst prognosis was observed in the EBV subtype (TCGA and integrated classification) and MSS/EMT subtype (ACRG classification). Discussion/Conclusion. We reported a reproducible and affordable gastric cancer subtyping algorithms that can reproduce the recently recognized TCGA, ACRG, and integrated gastric cancer classifications, using techniques available in routine diagnosis. These simplified classifications can be employed not only for molecular classification but also in predicting the prognosis of gastric cancer patients.

scholarly journals Potential prognostic impact of EBV RNA‐seq reads in gastric cancer: a reanalysis of The Cancer Genome Atlas cohort

FEBS Open Bio ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 455-467 ◽  
Author(s):  
Daichi Sadato ◽  
Mina Ogawa ◽  
Chizuko Hirama ◽  
Tsunekazu Hishima ◽  
Shin‐Ichiro Horiguchi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Prognostic Impact ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals The Biological Role of Sponge Circular RNAs in Gastric Cancer: Main Players or Coadjuvants?

Cancers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1982
Author(s):  
Adenilson Leão Pereira ◽  
Leandro Magalhães ◽  
Rafael Pompeu Pantoja ◽  
Gilderlanio Araújo ◽  
Ândrea Ribeiro-dos-Santos ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Target Genes ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Interaction Network ◽  
Gastric Carcinogenesis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Circular Rnas ◽  
Cancer Genome Atlas

Circular RNAs (circRNAs) are a new class of long noncoding RNAs able to perform multiple functions, including sponging microRNAs (miRNAs) and RNA-Binding Proteins (RBPs). They play an important role in gastric carcinogenesis, but its involvement during gastric cancer (GC) development and progression are not well understood. We gathered miRNA and/or RBPs sponge circRNAs present in GC, and accessed their biological roles through functional enrichment of their target genes or ligand RBPs. We identified 54 sponge circRNAs in GC that are able to sponge 51 miRNAs and 103 RBPs. Then, we evaluated their host gene expression using The Cancer Genome Atlas (TCGA) database and observed that COL1A2 is the most overexpressed gene, which may be due to circHIPK3/miR-29b-c/COL1A2 axis dysregulation. We identified 27 GC-related pathways that may be affected mainly by circPVT1, circHIPK3 and circNF1. Our results indicate that circHIPK3/miR-107/BDNF/LIN28 axis may mediate chemoresistance in GC, and that circPVT1, circHIPK3, circNF1, ciRS-7 and circ_0000096 appear to be involved in gastrointestinal cancer development. Lastly, circHIPK3, circNRIP1 and circSMARCA5 were identified in different ethnic populations and may be ubiquitous modulators of gastric carcinogenesis. Overall, the studied sponge circRNAs are part of a complex RBP-circRNA-miRNA-mRNA interaction network, and are involved in the establishment, chemoresistance and progression of GC.

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