Identification of Early Diagnostic and Prognostic Biomarkers via WGCNA in Stomach Adenocarcinoma

Stomach adenocarcinoma (STAD) is a leading cause of cancer deaths, and the outcome of the patients remains dismal for the lack of effective biomarkers of early detection. Recent studies have elucidated the landscape of genomic alterations of gastric cancer and reveal some biomarkers of advanced-stage gastric cancer, however, information about early-stage biomarkers is limited. Here, we adopt Weighted Gene Co-expression Network Analysis (WGCNA) to screen potential biomarkers for early-stage STAD using RNA-Seq and clinical data from TCGA database. We find six gene clusters (or modules) are significantly correlated with the stage-I STADs. Among these, five hub genes, i.e., MS4A1, THBS2, VCAN, PDGFRB, and KCNA3 are identified and significantly de-regulated in the stage-I STADs compared with the normal stomach gland tissues, which suggests they can serve as potential early diagnostic biomarkers. Moreover, we show that high expression of VCAN and PDGFRB is associated with poor prognosis of STAD. VCAN encodes a large chondroitin sulfate proteoglycan that is the main component of the extracellular matrix, and PDGFRB encodes a cell surface tyrosine kinase receptor for members of the platelet-derived growth factor (PDGF) family. Consistently, Gene Ontology (GO) analysis of differentially expressed genes in the STADs indicates terms associated with extracellular matrix and receptor ligand activity are significantly enriched. Protein-protein network interaction analysis (PPI) and Gene Set Enrichment Analysis (GSEA) further support the core role of VCAN and PDGFRB in the tumorigenesis. Collectively, our study identifies the potential biomarkers for early detection and prognosis of STAD.

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Construction of Prognostic Prediction Model for Stomach Adenocarcinoma Based on the TCGA Database.

10.21203/rs.3.rs-114928/v1 ◽

2020 ◽

Author(s):

Zhengzhong Gu ◽

Xiaohan Cui ◽

Xudong Wang

Keyword(s):

Gastric Cancer ◽

Extracellular Matrix ◽

Protein Kinase ◽

Network Analysis ◽

Differentially Expressed Genes ◽

Differentially Expressed ◽

Stomach Adenocarcinoma ◽

Matrix Organization ◽

Prognostic Prediction ◽

New Biomarkers

Abstract Background: Prognostic prediction models have been developed to detect new biomarkers of gastric cancer (GC). The identification of new biomarkers could provide theoretical foundations for the application of molecular targeted therapy in advanced GC. The aim of this study was to construct a prognostic prediction model for stomach adenocarcinoma (STAD) based on The Cancer Genome Atlas (TCGA) database. Methods: First, we used the "limma" package to screen differentially expressed genes (DEGs) based on TCGA database. Gene ontology (GO) analysis was performed using the "ClusterProfiler" package. The interactions between proteins and the relationships between differentially expressed genes and clinical features were analyzed by protein-protein interaction (PPI) network analysis and weighted gene coexpression network analysis (WGCNA), respectively. Then, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to identify differentially enriched pathways. The GenVisR package and CIBERSORT were used to identify mutations and assess immune infiltration. Finally, the expression of COL3A1 in STAD tissues was verified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blotting.Results: Six differentially expressed genes were screened out, namely, COL3A1, ADAMTS12, BGN, FNDC1, AEBP1 and HTRA3. The enrichment results showed that differentially expressed genes were involved in multiple pathways in STAD, such as those related to the extracellular matrix, extracellular structure organization, and extracellular matrix organization. The differentially expressed genes were related to immune infiltration via the mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathways. The western blotting and RT-qPCR results suggested that COL3A1 was overexpressed in STAD tissues compared with normal tissues.Conclusion: COL3A1, ADAMTS12, BGN, FNDC1, AEBP1 and HTRA3 could play important roles in the tumorigenesis and progression of STAD via various pathways, including those involving the extracellular matrix, extracellular structure organization, and extracellular matrix organization. COL3A1, ADAMTS12, BGN, FNDC1, AEBP1, and HTRA3 act as oncogenes in most cancers and may be biomarkers. Additionally, the identification of COL3A1 as a candidate biomarker provides a direction for further research on the role of tumor immunity in gastric cancer.

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Autoantibodies as Potential Biomarkers in Breast Cancer

Biosensors ◽

10.3390/bios8030067 ◽

2018 ◽

Vol 8 (3) ◽

pp. 67 ◽

Cited By ~ 12

Author(s):

Jingyi Qiu ◽

Bailey Keyser ◽

Zuan-Tao Lin ◽

Tianfu Wu

Keyword(s):

Breast Cancer ◽

Early Detection ◽

Early Stage ◽

Healthy Tissue ◽

Imaging Technologies ◽

Specific Antigens ◽

Treatment Responses ◽

Disease Stratification ◽

Screening And Diagnosis ◽

Potential Biomarkers

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

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Predictive factors for metastasis in patients (pts) with gastric cancer

Journal of Clinical Oncology ◽

10.1200/jco.2007.25.18_suppl.15056 ◽

2007 ◽

Vol 25 (18_suppl) ◽

pp. 15056-15056

Author(s):

S. Kilickap ◽

O. Dizdar ◽

H. Harputluoglu ◽

S. Aksoy ◽

S. Yalcin

Keyword(s):

Risk Factors ◽

Gastric Cancer ◽

Early Stage ◽

Stage Iv ◽

Stage I ◽

Early Stage Disease ◽

Increased Risk ◽

Metastasis Development ◽

The Mean

15056 Background: Determination of patients (pts) with early stage disease who have a high risk for developing metastatic disease is crucial. We investigated the risk factors associated with metastases development in pts with operable gastric cancer. Patients and Methods: In this retrospective study, pts with stage I-III and non-metastatic stage IV gastric cancer diagnosed between 1990 and 2006 were evaluated. The medical records of all pts including patient characteristics, laboratory results, histopathological examinations, were reviewed. Logistic regression methods were used to determine the risk factors for developing metastasis and to calculate odds ratios (OR) with 95% confidence intervals (CI). Results: 184 pts (70% male, 30% female) were analyzed. The mean age ± standard deviation was 56.5±11.9. The mean age of female were higher than male (p=0.014). At the time of diagnosis, 13.6% of the pts had stage I, 19.0% had stage II, 53.3% had stage III, and 14.1% had non-metastatic stage IV disease. The tumors were distally localized in 80% of the cases. Median follow-up period was 35 months. During follow up, 51 pts developed metastases. Median time to metastases development was 14 months. Overall survival was shorter in pts who developed metastasis than those who did not. (20 months vs. not reached, respectively, p=0.002). In univariate analyses, stage (p=0.020), tumor localization (p=0.006), extracapsular lymphatic extension (ELE) (p<0.001), the number of metastatic lymph nodes (p=0.001), CEA level (p<0.001), lymphovascular invasion (LVI) (p=0.001), and perineural invasion (p=0.007) were associated with metastasis development. In multivariate analysis, elevated CEA levels (p=0.009; OR: 2.8; CI 95%: 1.29–6.19), LVI (p=0.041; OR: 2.2; CI 95%: 1.03–4.64) and ELE (p=0.029; OR: 2.3; CI 95%: 1.09–4.78) were associated with increased risk of metastasis development while distal localization (p=0.038; OR: 0.42; CI%: 0.18–0.95) was associated with decreased risk in pts with gastric cancer. Discussion: In pts with early stage or locally advanced gastric cancer, elevated CEA levels, LVI, proximal localization and ELE were associated with increased risk of developing metastasis. Aggressive treatment options and closer follow up should be considered for pts with these risk factors. No significant financial relationships to disclose.

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Plasma microRNAs serve as novel potential biomarkers for early detection of gastric cancer

Medical Oncology ◽

10.1007/s12032-012-0452-0 ◽

2013 ◽

Vol 30 (1) ◽

Cited By ~ 55

Author(s):

Hui Cai ◽

Yuan Yuan ◽

Yun-Fei Hao ◽

Tian-Kang Guo ◽

Xue Wei ◽

...

Keyword(s):

Gastric Cancer ◽

Early Detection ◽

Potential Biomarkers

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Evaluation of serum phosphopeptides as potential biomarkers of gastric cancer

RSC Advances ◽

10.1039/c7ra00827a ◽

2017 ◽

Vol 7 (35) ◽

pp. 21630-21637 ◽

Cited By ~ 3

Author(s):

Guijin Zhai ◽

Liping Yang ◽

Qun Luo ◽

Kui Wu ◽

Yao Zhao ◽

...

Keyword(s):

Gastric Cancer ◽

Cancer Diagnosis ◽

Early Stage ◽

Potential Biomarker ◽

Potential Biomarkers

A serum phosphopeptide (DpSGEGDFLAEGGGVR) was demonstrated to be a potential biomarker for gastric cancer diagnosis, particularly for early stage cases.

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A multiplex methylation-specific PCR assay for detection of early-stage ovarian cancer using cell-free serum DNA.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.5535 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 5535-5535

Author(s):

Beihua Kong ◽

Qing Zhang ◽

Guohong Hu ◽

Qifeng Yang ◽

Ruifen Dong ◽

...

Keyword(s):

Ovarian Cancer ◽

Early Detection ◽

Early Stage ◽

Methylation Status ◽

Stage I ◽

Methylation Specific Pcr ◽

Specific Pcr ◽

Preoperative Serum ◽

Serum Dna ◽

Free Serum

5535 Background: Epithelial ovarian cancer (EOC) remains the most lethal disease among gynecological malignancies. Prompt diagnosis is challenging because of the non-specific symptoms exhibited during the early stage of the disease. So there is an urgent need for better detection methods. Here we performed this work to build up a platform of multiplex methylation-specific PCR (MSP) assay to improve the early detection of ovarian cancer, via identifying the methylation status of cell-free serum DNA. Methods: After screening, we chose seven genes (APC, RASSF1A, CDH1, RUNX3, TFPI2, SFRP5 and OPCML) with a high frequency of methylation as candidate genes to construct the multiplex-MSP assay. When methylation of at least one of the seven genes was observed, the multiplex-MSP assay was considered positive. We performed the retrospective and screening study to verify its specificity and sensitivity in the detection of EOC. Results: The methylation status of cell-free serum DNA was examined in the preoperative serum of 202 patients, including 87 EOC cases (stage I, n=41, stage II-IV, n=46), 53 benign ovarian tumors and 62 healthy controls. As expected, multiplex MSP assay achieved a sensitivity of 85.3% and a specificity of 90.5% in stage I EOC, strikingly higher than that of single CA125, producing a sensitivity of 56.1% at 64.15% specificity [p=0.0036](Table). Conclusions: Multiplex MSP assay analyzing the methylation status of cell-free serum DNA is a suitable and reliable approach to improve the early detection of ovarian cancer, potentially benefiting a broad range of applications in clinical oncology. [Table: see text]

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Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy

European Radiology ◽

10.1007/s00330-021-07962-2 ◽

2021 ◽

Author(s):

Qinmei Xu ◽

Zeyu Sun ◽

Xiuli Li ◽

Chen Ye ◽

Changsheng Zhou ◽

...

Keyword(s):

Gastric Cancer ◽

Computed Tomography ◽

Neoadjuvant Chemotherapy ◽

Early Detection ◽

Advanced Gastric Cancer ◽

Early Stage ◽

Preoperative Evaluation ◽

Predictive Ability ◽

Cross Combination ◽

Accurate Identification

Abstract Objectives To develop and evaluate machine learning models using baseline and restaging computed tomography (CT) for predicting and early detecting pathological downstaging (pDS) with neoadjuvant chemotherapy in advanced gastric cancer (AGC). Methods We collected 292 AGC patients who received neoadjuvant chemotherapy. They were classified into (a) primary cohort (206 patients with 3–4 cycles chemotherapy) for model development and internal validation, (b) testing cohort I (46 patients with 3–4 cycles chemotherapy) for evaluating models’ predictive ability before and after the complete course, and (c) testing cohort II (n = 40) for model evaluation on its performance at early treatment. We extracted 1,231 radiomics features from venous phase CT at baseline and restaging. We selected radiomics models based on 28 cross-combination models and measured the areas under the curve (AUC). Our prediction radiomics (PR) model is designed to predict pDS outcomes using baseline CT. Detection radiomics (DR) model is applied to restaging CT for early pDS detection. Results PR model achieved promising outcomes in two testing cohorts (AUC 0.750, p = .009 and AUC 0.889, p = .000). DR model also showed a good predictive ability (AUC 0.922, p = .000 and AUC 0.850, p = .000), outperforming the commonly used RECIST method (NRI 39.5% and NRI 35.4%). Furthermore, the improved DR model with averaging outcome scores of PR and DR models showed boosted results in two testing cohorts (AUC 0.961, p = .000 and AUC 0.921, p = .000). Conclusions CT-based radiomics models perform well on prediction and early detection tasks of pDS and can potentially assist surgical decision-making in AGC patients. Key Points • Baseline contrast-enhanced computed tomography (CECT)-based radiomics features were predictive of pathological downstaging, allowing accurate identification of non-responders before therapy. • Restaging CECT-based radiomics features were predictive to achieve pDS after and even at an early stage of neoadjuvant chemotherapy. • Combination of baseline and restaging CECT-based radiomics features was promising for early detection and preoperative evaluation of pathological downstaging of AGC.

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Colorectal Cancer Blood-Based Biomarkers

Gastroenterology Research and Practice ◽

10.1155/2017/2195361 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 10

Author(s):

Nina Hauptman ◽

Damjan Glavač

Keyword(s):

Colorectal Cancer ◽

Early Detection ◽

Sensitivity And Specificity ◽

Screening Test ◽

Early Stage ◽

High Sensitivity ◽

Recurrence Risk ◽

Liquid Biopsies ◽

Mortality And Morbidity ◽

Potential Biomarkers

Mortality and morbidity associated with colorectal cancer (CRC) are increasing globally, partly due to lack of early detection of the disease. The screening is usually performed with colonoscopy, which is invasive and unpleasant, discouraging participation in the screening. As a source of noninvasive and easily accessible biomarkers, liquid biopsies are emerging. Blood-based biomarkers have the potential as diagnostic and prognostic tool in CRC. Early stage detection of CRC with high sensitivity and specificity would likely lead to higher participation in the screening test. It would also improve the prognosis of the disease and improve the recurrence risk. In this review, we summarize the potential biomarkers for early detection and monitoring of CRC.

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