IL-31, IL-32 and IL-33 May Serve as Diagnosis Biomarkers in Gastric Cancer

Abstract To determine whether IL-31, IL-32 and IL-33 can be used as biomarkers for the detection of gastric cancer (GC), via evaluating the correlations between IL-31, IL-32 and IL‑33 expression and clinicopathological parameters of GC patients. Tissue array (n=180) gastric specimens were utilised. IL-31, IL-32 and IL-33 in GC and non-GC tissues were detected immunohistochemically. The correlations between IL-31, IL-32 and IL-33 in GC and severity of clinicopathological parameters were evaluated. Survival curves were plotted using the Kaplan-Meier/Cox regression. IL-31, IL-32 and IL-33 in circulation were detected by ELISA. We found that IL-31, IL-32 and IL-33 were all lower in GC than that in adjacent non-GC gastric tissue (p all <0.05). IL-33 in peripheral blood of GC patients was significantly lower than that of healthy individuals (1.50 ± 1.11 vs 9.61 ± 8.00 ng/ml) (p<0.05). Decreased IL-31, IL-32 and IL-33 in GC were observed in younger patients (<60 years), and IL-32 and IL-33 were lower in female patients (p all <0.05). Higher IL-32 correlated with longer survival in two GC subgroups: T4 invasion depth and TNM I-II stage. Univariate/multivariate analysis revealed that IL-32 is an independent prognostic factor for GC within the T4 stage subgroup. Circulation IL-33 was significantly lower in GC patients than healthy people (p <0.05). Our findings provide new insights into the roles of IL-31, IL-32 and IL-33 in carcinogenesis of GC and demonstrate their relative usefulness as prognostic markers for GC. The underlying mechanism of IL-31, IL-32 and IL-33 in GC is further discussed.

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IL-31, IL-32 and IL-33 may Serve as Diagnosis Biomarkers in Gastric Cancer

10.21203/rs.3.rs-128062/v1 ◽

2020 ◽

Author(s):

Shisan Bao ◽

Qinghua Liu ◽

Jiwei Zhang ◽

Lei Xia ◽

Steven Wise ◽

...

Keyword(s):

Gastric Cancer ◽

Prognostic Markers ◽

Cox Regression ◽

Underlying Mechanism ◽

Tissue Array ◽

Clinicopathological Parameters ◽

Gastric Tissue ◽

Invasion Depth ◽

Kaplan Meier ◽

T4 Stage

Abstract Background: To determine whether IL-31, IL-32 and IL-33 can be used as biomarkers for the detection of gastric cancer (GC), via evaluating the correlations between IL-31, IL-32 and IL‑33 expression and clinicopathological parameters of GC patients.Methods: Tissue array (n=180) gastric specimens were utilised. IL-31, IL-32 and IL-33 in GC and non-GC tissues were detected immunohistochemically. The correlations between IL-31, IL-32 and IL-33 in GC and severity of clinicopathological parameters were evaluated. Survival curves were plotted using the Kaplan-Meier/Cox regression. IL-31, IL-32 and IL-33 in circulation were detected by ELISA. Results: IL-31, IL-32 and IL-33 were all lower in GC than that in adjacent non-GC gastric tissue (p all <0.05). IL-33 in peripheral blood of GC patients was significantly lower than that of healthy individuals (1.50 ± 1.11 vs 9.61 ± 8.00 ng/ml) (p<0.05). Decreased IL-31, IL-32 and IL-33 in GC were observed in younger patients (<60 years), and IL-32 and IL-33 were lower in female patients (p all <0.05). Higher IL-32 correlated with longer survival in two GC subgroups: T4 invasion depth and TNM I-II stage. Univariate/multivariate analysis revealed that IL-32 is an independent prognostic factor for GC within the T4 stage subgroup. Circulation IL-33 was significantly lower in GC patients than healthy people (p <0.05). Conclusions: Our findings provide new insights into the roles of IL-31, IL-32 and IL-33 in carcinogenesis of GC and demonstrate their relative usefulness as prognostic markers for GC. The underlying mechanism of IL-31, IL-32 and IL-33 in GC is further discussed.

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Prognostic values, ceRNA network, and immune regulation function of SDPR in KRAS-mutant lung cancer

Cancer Cell International ◽

10.1186/s12935-021-01756-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiaoqing Luo ◽

Shunli Peng ◽

Sijie Ding ◽

Qin Zeng ◽

Rong Wang ◽

...

Keyword(s):

Lung Cancer ◽

Immune Checkpoint ◽

Cox Regression ◽

Tissue Array ◽

Lung Cancers ◽

Cox Regression Analysis ◽

Immune Checkpoint Molecules ◽

Cerna Network ◽

Kaplan Meier ◽

Infiltration Models

Abstract Background Serum Deprivation Protein Response (SDPR) plays an important role in formation of pulmonary alveoli. However, the functions and values of SDPR in lung cancer remain unknown. We explored prognostic value, expression pattern, and biological function of SDPR in non-small cell lung cancer (NSCLC) and KRAS-mutant lung cancers. Methods SDPR expression was evaluated by quantitative real-time PCR (RT-qPCR), immunohistochemistry (IHC), and Western blot on human NSCLC cells, lung adenocarcinoma tissue array, KRAS-mutant transgenic mice, TCGA and GEO datasets. Prognostic values of SDPR were evaluated by Kaplan–Meier and Cox regression analysis. Bioinformatics implications of SDPR including SDPR-combined transcription factors (TFs) and microRNAs were predicted. In addition, correlations between SDPR, immune checkpoint molecules, and tumor infiltration models were illustrated. Results SDPR expression was downregulated in tumor cells and tissues. Low SDPR expression was an independent factor that correlated with shorter overall survival of patients both in lung cancer and KRAS-mutant subgroups. Meanwhile, ceRNA network was constructed to clarify the regulatory and biological functions of SDPR. Negative correlations were found between SDPR and immune checkpoint molecules (PD-L1, TNFRSF18, TNFRSF9, and TDO2). Moreover, diversity immune infiltration models were observed in NSCLC with different SDPR expression and copy number variation (CNV) patterns. Conclusions This study elucidated regulation network of SDPR in KRAS-mutant NSCLC, and it illustrated correlations between low SDPR expression and suppressed immune system, unfolding a prognostic factor and potential target for the treatment of lung cancer, especially for KRAS-mutant NSCLC.

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Expression and Clinical Significance of Serum Exosomal miR-375 in Patients with Gastric Cancer

Tobacco Regulatory Science ◽

10.18001/trs.7.5.1.162 ◽

2021 ◽

Vol 7 (5) ◽

pp. 3896-3904

Author(s):

Daoting Deng ◽

Hong Zhang ◽

Junxi Liu ◽

Lina Ma ◽

Xinrui Lei ◽

...

Keyword(s):

Gastric Cancer ◽

Cancer Patients ◽

Cox Regression ◽

Prognostic Significance ◽

Cox Regression Analysis ◽

Healthy Group ◽

Cancer Group ◽

Kaplan Meier ◽

Gastric Cancer Patients ◽

Gastric Cancer Group

To explore exosomal miR-375 expression in gastric cancer patients and its relationship with patient prognosis. A total of 53 patients diagnosed with gastric cancer in our hospital from May 2014 to May 2016 were included as the gastric cancer group, and 46 healthy women who came to our hospital for physical examination during the same period were enrolled as the healthy group. Exosomal miR-375 expression level was detected using qRT-PCR, and the diagnostic performance and prognostic significance of exosomal miR-375 in gastric cancer were explored. The gastric cancer group showed increased exosomal miR-375 expression than the healthy group (P< 0.05); Kaplan-Meier survival analysis exhibited that serum exosomal miR-375 has an AUC of 0.778, sensitivity of 69.57%, and specificity of 75.47%, whereas Cox regression analysis showed that the miR-375 expression in exosomes was an independent risk factor affecting the prognosis of gastric cancer patients (P< 0.05). Patient with gastric cancer showed upregulated miR-375 expression in serum exosomes. Serum exosomal miR-375 was found to has positive sensitivity and specificity in the diagnosis of gastric cancer, which may be associated with poor prognosis of gastric cancer patients.

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Matrix metalloproteinase 12 is an independent prognostic factor predicting postoperative relapse of conventional renal cell carcinoma - a short report

Cellular Oncology ◽

10.1007/s13402-021-00650-9 ◽

2021 ◽

Author(s):

Bence Beres ◽

Maria Yusenko ◽

Lehel Peterfi ◽

Gyula Kovacs ◽

Daniel Banyai

Keyword(s):

Renal Cell ◽

Cox Regression ◽

Tissue Array ◽

Short Report ◽

Free Survival ◽

Cox Regression Analysis ◽

Conventional Renal Cell Carcinoma ◽

Kaplan Meier ◽

Matrix Metalloproteinase 12

Abstract Purpose Approximately 15% of clinically localised conventional renal cell carcinomas (cRCC) develop metastases within 5 years of follow-up. Sarcomatous cRCC is a highly malignant cancer of the kidney. The aim of our study was to identify biomarkers for estimating the postoperative progression of cRCCs. Methods Global microarray-based gene expression analysis of RCCs with and without sarcomatous changes revealed that a high MMP12 expression was associated with a sarcomatous histology. Additionally, we analysed MMP12 expression using a multi-tissue array comprising 736 cRCC patients without metastasis at the time of surgery. The median follow-up time was 66 ± 29 months. Results Immunohistochemistry revealed MMP12 expression in 187 of 736 cRCCs with good follow-up data. Subsequent Kaplan–Meier analysis revealed that patients with MMP12 positive tumours exhibited a significantly shorter tumour-free survival (p < 0.001). In multivariate Cox regression analysis a weak to strong MMP12 expression indicated a 2.4–2.8 times higher risk of postoperative tumour relapse (p < 0.001; p < 0.003, respectively). Conclusions MMP12 may serve as a biomarker to estimate postoperative cRCC relapse and as a possible target for penfluridol therapy.

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Overexpression of a novel oncogene Cadherin 6 correlates with tumor progression and poor prognosis in gastric cancer

10.21203/rs.3.rs-153934/v1 ◽

2021 ◽

Author(s):

Zongxian Zhao ◽

Shuliang Li ◽

Shilong Li ◽

Jun Wang ◽

Hai Lin ◽

...

Keyword(s):

Gastric Cancer ◽

Overall Survival ◽

Roc Curve ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

Expression Level ◽

Diagnostic Efficiency ◽

Gastric Tissue ◽

Diagnosis And Prognosis ◽

T Classification

Abstract BackgroundGastric cancer (GC) is one of the most common and fatal cancers worldwide and effective biomarkers aids in GC management and prognosis. Hence, we explored the role and function of cadherin 6 (CDH6) in diagnosis and prognosis of gastric cancer. MethodsThe expression level of CDH6 in GC tissue and normal gastric tissue were analyzed using multiple public databases. Gene set enrichment analysis (GSEA) was performed using The Cancer Genome Atlas dataset (TCGA). The diagnostic efficiency of CDH6 expression in GC patients was determined through receiver operating characteristic (ROC) curve analysis. The associations between clinical variables and expression of CDH6 were evaluated statistically and the prognostic factors for overall survival were analyzed by univariate and multivariate Cox regression. Forty-four GC tissues, corresponding adjacent normal tissues (n=20), and detailed clinical information were collected from Tianjin Medical University General Hospital, CDH6 expression level was detected for further validation. ResultsCDH6 was upregulated in GC samples compared with normal gastric tissue, and GSEA identified the citrate cycle tricarboxylic (TCA) cycle, extracellular matrix (ECM) receptor interaction, glyoxylate and dicarboxylate metabolism oxidative phosphorylation, and pentose phosphate pathway as differentially enriched in GCs. According to the area under the ROC curve (AUC) (AUC=0.829 in TCGA and 0.966 in GSE54129), CDH6 had high diagnostic efficiency. Patients with high expression of CDH6 was associated with higher T classification and worse prognoses than those with low CDH6 expression in GC. Univariate and multivariate Cox regression analysis showed that CDH6 was an independent risk factor for overall survival (univariate: HR = 1.305, P = 0.002, multivariate: HR = 1.481, P < 0.001). ConclusionCDH6 was upregulated in GC and high CDH6 expression indicated higher T classification and worse prognoses. CDH6 could be a potentially independent molecular biomarker for diagnosis and prognosis of GC.

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High TRAF3IP3 Level Predicts Poor Prognosis of Patients with Gliomas

10.21203/rs.3.rs-96115/v1 ◽

2020 ◽

Author(s):

Guorong Yang ◽

Shu Tang ◽

Jie Zhang ◽

Ling Qin

Keyword(s):

Signaling Pathway ◽

Cox Regression ◽

The Body ◽

High Expression ◽

Clinicopathological Parameters ◽

Signal Pathways ◽

Primary Therapy ◽

Kaplan Meier ◽

Wilcoxon Rank Sum Test ◽

The Relationship

Abstract Purpose: TRAF3IP3 is involved in the maturation of immune cells, the development of immune tissues and the immune response of the body. TRAF3IP3 is shown to expressed in a variety of malignant tumor cell lines. Down-regulated expression of TRAF3IP3 in malignant melanoma can inhibit tumor growth. However, the role of TRAF3IP3 in glioma is still unknown. In this study, we aimed to study the relationship between TRAF3IP3 and glioma based on TCGA data.Method: We used the Wilcoxon rank sum test to compare the expression of TRAF3IP3 in glioma and normal tissues. Subsequently, Kruskal-Wallis test, Wilcoxon rank sum test, and logistics regression were used to evaluate the relationship between TRAF3IP3 and clinicopathological parameters of glioma patients. GSEA was used to verify the key signal pathways involved in TRAF3IP3. We used the ssGSEA method to analyze the relationship between the expression level of TRAF3IP3 and the immune infiltration in the glioma tumor microenvironment. Finally, we used Kaplan-Meier and COX regression to evaluate the prognostic value of TRAF3IP3.Results: TRAF3IP3 transcription level was highly expressed in gliomas(P<0.001). And the high expression of TRAF3IP3 and WHO grade(OR=3.57(2.42-5.34), P<0.001), IDH status (OR=4.79(3.40-6.83), P<0.001), 1P /19q codeletion (OR=0.07(0.04-0.11), P<0.001), EGFR status (OR=2.77(1.65-4.81), P<0.001), histological type (OR=3.64(2.48-5.43), P<0.001), age (OR=1.64(1.13-2.41), P=0.01), and primary therapy outcome (OR=2.29(1.47-3.61), P<0.001) were significantly correlated. GSEA showed that six signaling pathways were significantly enriched in the TRAF3IP3 high expression phenotype group, including JAK STAT signaling pathway, interferon-γ signaling pathway, apoptosis, P53 signaling pathway, PD-1 signaling pathway, and CTLA4 signaling pathway. ssGSEA showed that the expression of TRAF3IP3 was significantly positively correlated with the infiltration of Macrophages, Th17 cells, etc. Multivariate COX regression showed that TRAF3IP3 was an independent prognostic factor for glioma OS (HR=2.169(1.301-3.615), P=0.003). Kaplan-Meier analysis showed that high expression of TRAF3IP3 was associated with worse PFS(HR=2.39(1.39-3.01), P<0.001), DFS(HR=3.02(2.27-4.01), P<0.001) and OS(HR=2.87(2.20-3.75), P<0.001).Conclusion: TRAF3IP3 may play an important role in the occurrence and development of glioma, and may be a potential biomarker for the diagnosis and prognosis of glioma.

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A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

Frontiers in Oncology ◽

10.3389/fonc.2020.584733 ◽

2020 ◽

Vol 10 ◽

Author(s):

Zuhua Chen ◽

Bo Liu ◽

Minxiao Yi ◽

Hong Qiu ◽

Xianglin Yuan

Keyword(s):

Gastric Cancer ◽

Dna Methylation ◽

Mrna Expression ◽

Risk Model ◽

Cox Regression ◽

Risk Group ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Clinicopathological Parameters ◽

Dna Hypomethylation

PurposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).MethodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.Results5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139–0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.ConclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

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A Novel Ferroptosis-Related Long Non-coding RNA Prognostic Risk Model for Gastric Cancer

10.21203/rs.3.rs-718468/v1 ◽

2021 ◽

Author(s):

Shenglan Huang ◽

Dan Li ◽

Lingling Zhuang ◽

Liying Sun ◽

Jianbing Wu

Keyword(s):

Gastric Cancer ◽

Risk Score ◽

Roc Curve ◽

Cox Regression ◽

Risk Group ◽

Clinical Stage ◽

Curve Analysis ◽

Clinicopathological Features ◽

Roc Curve Analysis ◽

Kaplan Meier

Abstract Background：Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is a novel and distinct type of non-apoptotic cell death that is closely associated with metabolism, redox biology, and tumor prognosis. Recently, ferroptosis-related long non-coding RNAs (lncRNAs) have received increasing attention in predicting cancer prognosis. Thus, we aimed to construct an ferroptosis-related lncRNAs signature for predicting the prognosis of patients with gastric cancer.Methods：We built an ferroptosis-related lncRNA risk signature by using Cox regression based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. Cox regression was performed to explore whether the signature could be used as an independent factor. A nomogram was built involving the risk score and clinicopathological features. Furthermore, we explored the biological functions and immune states in two groups.Results：Eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in gastric cancer. Kaplan–Meier curve analysis revealed that patients in the high-risk group had worse survival than those in the low-risk group. The survival outcome was also appropriate for subgroup analysis, including age, sex, grade, and clinical stage. Multivariate Cox regression analysis and receiver operating characteristic (ROC) curve analysis demonstrated that the risk score was an independent prognostic factor and superior to traditional clinicopathological features in predicting GC prognosis. Next, we established a nomogram according to clinical parameters (age, sex, grade, and clinical stage) and risk score. All the verified results, including ROC curve analysis, calibration curve, and decision curve analysis, demonstrated that the nomogram could accurately predict the survival of patients with gastric cancer. Gene set enrichment analysis revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation.Conclusion: We established a novel ferroptosis-related prognostic risk signature including eight lncRNAs and constructed a nomogram to predict the prognosis of gastric cancer patients, which may improve prognostic predictive accuracy and guide individualized treatment for patients with GC.

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KK-LC-1 may be an effective prognostic biomarker for gastric cancer

10.21203/rs.3.rs-50773/v2 ◽

2020 ◽

Author(s):

Jun Ji ◽

Jiahui Chen ◽

Anqiang Wang ◽

Wei Zhang ◽

Hongge Ju ◽

...

Keyword(s):

Gastric Cancer ◽

Overall Survival ◽

Cox Regression ◽

Staining Intensity ◽

Good Prognosis ◽

Clinicopathological Parameters ◽

Chi Square ◽

Clinical Prognosis ◽

Cox Regression Analysis ◽

Normal Tissues

Abstract Background: To detect the expression of Kita-Kyushu lung cancer antigen-1 (KK-LC-1) in gastric cancer (GC) specimens and analyze the associations between KK-LC-1 expression and clinicopathological parameters and clinical prognosis. Methods: A total of 94 patients with GC who underwent surgical resection were enrolled in this study. The expression of KK-LC-1 in GC tissues was detected by immunohistochemistry. The assessment of KK-LC-1 expression was conducted using the H-scoring system. H-score was calculated by the multiplication of the overall staining intensity with the percentage of positive cells. The expression of KK-LC-1 in the cytoplasm and was scored to achieve respective H-score values. The correlations between KK-LC-1 expression and clinicopathological parameters and clinical prognosis were analyzed using Chi-square test, Kaplan-Meier method and Cox regression. Results: In the cytoplasm, the expression of KK-LC-1 in tumor tissues was significantly higher than that in normal tissues (P < 0.001, respectively). Using the median H-score as the cutoff value, it was discovered that, GC patients with higher levels of KK-LC-1expression in the cytoplasm, had favorable overall survival (P =0.016), and it was still statistically meaningful in Cox regression analysis. At the same time, the study found that there was a negative correlation between KK-LC-1’s protein expression and the pathological grade of the tumor (P = 0.036). Conclusions: Our research data shows that KK-LC-1’s expression in GC is higher than that of normal tissues, which is associated with a longer overall survival in GC. KK-LC-1 can be used as a biomarker for GC patients with good prognosis.

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Objective quantitation of EGFR protein levels using Quantitative Dot Blot (QDB) method for prognosis of gastric cancer patients

10.1101/2021.04.12.21255321 ◽

2021 ◽

Author(s):

Lei Xin ◽

Fangrong Tang ◽

Bo Song ◽

Maozhou Yang ◽

Jiandi Zhang

Keyword(s):

Gastric Cancer ◽

Lung Cancer ◽

Overall Survival ◽

Clinical Trials ◽

Cancer Patients ◽

Cox Regression ◽

Dot Blot ◽

Protein Levels ◽

Kaplan Meier ◽

Gastric Cancer Patients

Background: One causing factor underlying failures of several clinical trials of anti-EGFR therapies is the lack of effective method to select patients overexpressing EGFR protein. Quantitative Dot Blot method (QDB) is proposed here to measure EGFR protein levels objectively and quantitatively. Its feasibility was evaluated for prognosis of overall survival (OS) of gastric cancer patients. Methods: FFPE slices of 2X5 microM from gastric and Lung cancer specimens were used to extract total tissue lysates for QDB measurement. Absolutely quantitated EGFR protein levels were used for Kaplan-Meier Overall Survival (OS) analysis of gastric cancer patients. Results: EGFR protein levels ranged from 0 to 772 pmole/g for gastric cancer specimens (n=246), and from 0 to 2695 pmole/g for lung cancer patients (n=81). Poor correlation was observed between quantitated EGFR levels and IHC scores with r=0.018, p=0.786 from Spearman correlation analysis. EGFR was identified as an independent negative prognostic biomarker for gastric patients only through absolute quantitation, with HR at 2.29 (95%CI:1.23-4.26, p=0.0089) from multivariate cox regression OS analysis. A cutoff of 207.7 pmole/g was proposed to stratify gastric cancer patients, with 5-year survival probability at 37% for those whose EGFR levels were above the cutoff, and at 64% those below the cutoff based on Kaplan-Meier OS analysis. p=0.0057 from Log Rank test. Conclusion: A QDB-based assay was developed for both gastric and Lung cancer specimens to measure EGFR protein levels absolutely, quantitatively and objectively. This assay should facilitate clinical trials aiming to evaluate anti-EGFR therapies retrospectively and prospectively.

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