scholarly journals WAKMAR2, a Prognosis-related Enhancer RNA in Gastric Cancer

2020 ◽  
Author(s):  
Yankai Zhang ◽  
Yichao Yan ◽  
Ning Ning ◽  
Zhanlong Shen ◽  
Yingjiang Ye
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Immune Checkpoint ◽  
Target Genes ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
High Expression ◽  
Enhancer Rna ◽  
Kaplan Meier ◽  
High Expression Group

Abstract Purpose An increasing number of long non-coding RNAs (lncRNAs) are thought to be associated with gastric cancer (GC). A lncRNA subclass that promotes enhancer function is called enhancer RNA (eRNA). We aimed to identify an eRNA that can predict GC prognosis and response to immune checkpoint inhibitors (ICIs).Methods Kaplan–Meier survival analysis was utilized to screen eRNA which can predict the prognosis of GC (P <0.05). The method of Spearman correlation analysis was employed in the filtration of target genes related to eRNA (r> 0.4, P <0.001). According to the median of WAKMAR2 expression, the patients were subdivided into low expression group and high expression group. Subsequently, differences of immune checkpoint-related genes and immune cell infiltration between the two groups were further explored. Furthermore, we analyzed the correlation of WAKMAR2 with tumor mutation burden (TMB) and microsatellite instability (MSI) in GC and other types of cancer.Results WAKMAR2 and its target gene TNFAIP3 entered the subsequent analysis. Patients with high-WAKMAR2 expression had a favorable prognosis compared to patients with low-WAKMAR2 expression (P = 0.048). Immune checkpoint-related genes (PD-L1, CTLA4, PDCD1, LAG3) in the WAKMAR2 high-expression group were also highly expressed, except for B7-H3. In addition, infiltration levels of B cells naive, T cells CD8, T cells CD4 memory activated, as well as Macrophages M1 in high-WAKMAR2 group were greater than in low-WAKMAR2 group. Last, the expression of WAKMAR2 in GC was significantly correlated with TMB and MSI.Conclusion WAKMAR2, a new eRNA, is a promising biomarker that can be used to predict the overall survival (OS) of GC patients, and WAKMAR2 expression can be utilized to identify ICB responders in GC, providing new insights for immunotherapy strategies.

Analysis of PDL1 expression and T cells infiltration in 1014 gastric cancer patients.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 50-50 ◽  
Author(s):  
Xiaofang Xing ◽  
Ziyu Li ◽  
Jiping Wang ◽  
Jiafu Ji
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Tumor Cells ◽  
Cell Density ◽  
Immune Cells ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Automated Image Analysis ◽  
Continuous Variables ◽  
Cd8 Cell

50 Background: Although immune checkpoint inhibitors have demonstrated promising results in melanoma and lung cancer, their effects on gastrointestinal cancer are still under investigation. Understand the prognostic effect of PDL1 expression, infiltration by CD8+ and CD3+ T cells in gastric cancer (GC) might help the identification of candidate patient who might benefit from immunotherapy. Methods: Immunohistochemistry were performed on a tissue microarray including 1,014 GC specimens with PD-L1 antibodies. Immune cell markers CD3 and CD8 were also stained and the quantitative differences were calculated using automated image analysis. Results: 37.8% of the cases showed a membranous PD-L1 expression in tumor cells and 74.9% in tumor infiltrating immune cells. GC patients with high level PDL1 expression in tumor cells or in immune cells were both associated with better survival compared with those with negative expression (5-year OS, 61% vs. 48%, P = 0.000, and 55% vs. 45%, P < 0.0001, respectively). As continuous variables, higher CD3+ and CD8+ cell density were associated with patients’ overall survival and the associations remained as the significant prognostic factors that predict favorable outcomes even after adjusting other unknown confounding factors.(HR: 0.974, 95%CI: 0.963-0.985, P = 0.000; and HR: 0.973, 95%CI: 0.960-0.986, P = 0.000 for CD3 and CD8 respectively). We also observed the close relationship between CD3+, CD8+ cell density and PDL1 expression both in tumor cells and in infiltrating immune cells. Conclusions: This study indicates that PDL1 expression, and TILs in particular, are important prognostic biomarkers. Patients with higher CD8 and CD3 T cell densities also have higher PD-L1 expression, indicating an adaptive immune resistance mechanism may be occurring. The counterintuitive observation that higher PD-L1 expression associating with better patients’ outcome highlights the need to assess both PDL1 expression in all tumor compartments and the characterization of the GC immune microenvironment.

scholarly journals Identification of Novel Prognostic Biomarkers to Predict Pembrolizumab Response in Gastric Cancer by Bioinformatics Analysis

2021 ◽  
Author(s):  
Si-Yu Liu ◽  
Ling-yan He ◽  
Mei-ling Lv ◽  
Wei-liang Sun
Keyword(s):  
Gastric Cancer ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Predictive Ability ◽  
Metastatic Gastric Cancer ◽  
Gene Expression Omnibus ◽  
High Expression ◽  
Hub Gene ◽  
Low Sensitivity

Abstract Immune checkpoint inhibitors (ICIs), especially pembrolizumab, have improved outcomes in patients with advanced or metastatic gastric cancer (GC). However, there are no reliable markers for the evaluation of its efficacy. GC samples from the UCSC Xena Browser and Gene Expression Omnibus (GEO) databases were performed by bioinformatics analysis. The single sample gene set enrichment (ssGSEA) algorithm was used to calculate the prognostic genes expression differences score (ssGSEA score) for each sample. Weighted gene co-expression network analysis (WGCNA) was applied to identify the score-related key model. The hub gene was identified based on the intersection between tumor-related transcription factors (TFs) and the key module. The predictive ability for pembrolizumab response of the hub gene was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). The correlations between the hub gene and immune infiltration in GC were investigated by the CIBERSORT algorithm. According to the ssGSEA score, patients with GC were divided into the high- and low-score group. RUNX1T1 was the hub gene of the ICIs treatment in GC. Its high expression was related to the low-score group, which indicated low sensitivity to pembrolizumab and poor prognosis. RUNX1T1 showed good predictive power for pembrolizumab response (AUC = 0.742). The CIBERSORT analysis showed that a high expression for RUNX1T1 weakened the anti-tumor immune response by affecting the immune cell infiltration.Runx1T1 may be a potential predictor of pembrolizumab efficacy in GC and be a prognostic marker for GC.

Immune Cell Profiling in CML Bone Marrow By Multiplex Immunohistochemistry

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1897-1897
Author(s):  
Brück Oscar ◽  
Sami Blom ◽  
Riku Turkki ◽  
Panu E Kovanen ◽  
Antonio Ribeiro ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Checkpoint ◽  
Cd4 T Cells ◽  
Research Funding ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Cytotoxic T Cells ◽  
Helper T Cells ◽  
Analysis Software

Abstract Background In most solid tumors, CD8+ cytotoxic T-cells and type 1 T-helper cells are associated with a positive prognosis, but a strong immunosuppressive microenvironment may hamper their effectiveness. This notion has contributed to the development of new immune-activating therapies, such as immune checkpoint inhibitors. Although having demonstrated long-term remissions in many different solid tumor types, immune checkpoint inhibitors have not been evaluated comprehensively in hematological malignancies. In this study, we aimed to characterize the cellular and molecular immunological profiles of chronic myeloid leukemia (CML) patients' bone marrow (BM) samples. Methods BM biopsies were taken at the time of diagnosis from chronic phase CML patients (n=57) treated in the Helsinki University Hospital during years 2005-2015. We used non-leukemic (NL) BM biopsies (n=10) as controls. Using hematopathologic expertise, we constructed tissue microarray (TMA) blocks from duplicate BM spots characterized with high leukemic cell infiltration. We stained TMA slides using multiplexed immunohistochemistry (IHC) combining fluorescent and chromogenic staining allowing detection of up to six markers and nuclei simultaneously. Marker panels included T and B-lymphoid (CD3, CD4, CD8, CD20), myeloid dendritic (CD11c, BDCA-1, BDCA-3), macrophage (CD68, pSTAT1, c-MAF), natural killer cell (CD3 and CD56) and leukemia cell (CD34) markers. In addition, we examined immune checkpoint molecules (PD1, CTLA4, OX40, LAG3, TIM3) and their ligands in leukemic cells (HLA-G, PD-L1, PD-L2, HLA-ABC), as well as activation markers (CD25, CD27, CD57, Granzyme B and CD45RO). We analyzed leukemia patients' immune checkpoint expression profiles quantitatively using the image analysis software Cell Profiler and cell analysis software FlowJo and compared results with NL BMs' immune cell profiles. Results The proportion of CD3+ T cells of all cells was significantly higher in CML BM vs. NL BM (median 6.0% [interquartile range (IQR) 3.6-10.7] vs. 2.1% [IQR 1.5-4.5], p=0.001). There was no significant difference in CD8+ cytotoxic T cell levels, but CD4+ helper T cells were 8-fold more abundant in CML as compared to non-leukemic BM (p<0.0001). The proportion of both memory CD45RO+CD8+ T cells (62.2% [IQR 47.4-69.8] vs. 47.3% [IQR 27.9-56.2] of CD8+ T cells, p=0.03) and memory CD45RO+CD4+ T cells (61.8% [IQR 51.8-68.5] vs. 40.0% [IQR 25.6-57.9] of CD4+ T cells, p=0.004) were significantly higher in leukemic patients. Although the proportion of PD1+CD8+ T cells did not differ between CML and NL BM, there was a significantly lower proportion of PD1+CD4+ T cells in CML BM vs. NL BM (25.1% [IQR 17.0-38.7] vs. 69.5% [IQR 50.7-77.9], p<0.0001). However, as the number of CD4+ T cells was increased in CML, the absolute number of CD4+PD1+ T cells of total cell population was 3-fold higher in CML BM than in NL BM (p=0.02). Both the proportion of OX40+CD4+ T cells (42.3% [IQR 28.7-51.6] vs. 18.1% [IQR 13.2-22.9], p=0.001) and OX40+CD8+ T cells (42.6% [IQR 25.8-60.7] vs. 12.7% [IQR 5.0-15.8], p<0.0001) were increased in leukemic patients. Interestingly, also the proportion of OX40+PD1+CD8+ T cells (25.7% [IQR 15.4-36.4] vs. 11.9% [IQR 5.0-15.8], p=0.0019) was higher in CML samples. Conclusion Multiplex IHC allows detailed characterization of immune cell subtypes and their phenotypes in BM biopsy samples. Our data show significant heterogeneity in immune cell subsets between individual patients. The CML BM is characterized with an increase in CD3+ T cells, especially helper T cells and CD45RO+ memory T cells, when compared to non-leukemic BM. Phenotypically, OX40+PD1neg T cells and OX40+PD1+ cytotoxic T cells were elevated in CML patients. The analysis of other immune cell subclasses, including inhibitory immune cells, and the correlation of histologic findings to prognostic data are ongoing. Together, they will provide a detailed understanding of BM immune cell composition in CML. Disclosures Mustjoki: Novartis: Honoraria, Research Funding; Ariad: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding.

scholarly journals Systemic Blood Immune Cell Populations as Biomarkers for the Outcome of Immune Checkpoint Inhibitor Therapies

2020 ◽  
Vol 21 (7) ◽  
pp. 2411 ◽  
Author(s):  
Carlos Hernandez ◽  
Hugo Arasanz ◽  
Luisa Chocarro ◽  
Ana Bocanegra ◽  
Miren Zuazo ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Suppressor Cells ◽  
Immune Checkpoints ◽  
Immune Cell Subsets ◽  
Immunosuppressive Cells ◽  
Activation Status

The development of cancer immunotherapy in the last decade has followed a vertiginous rhythm. Nowadays, immune checkpoint inhibitors (ICI) which include anti-CTLA4, anti-PD-1 and anti-PD-L1 antibodies are in clinical use for the treatment of numerous cancers. However, approximately only a third of the patients benefit from ICI therapies. Many efforts have been made for the identification of biomarkers allowing patient stratification into potential responders and progressors before the start of ICI therapies or for monitoring responses during treatment. While much attention is centered on biomarkers from the tumor microenvironment, in many cases biopsies are not available. The identification of systemic immune cell subsets that correlate with responses could provide promising biomarkers. Some of them have been reported to influence the response to ICI therapies, such as proliferation and activation status of CD8 and CD4 T cells, the expression of immune checkpoints in peripheral blood cells and the relative numbers of immunosuppressive cells such as regulatory T cells and myeloid-derived suppressor cells. In addition, the profile of soluble factors in plasma samples could be associated to response or tumor progression. Here we will review the cellular subsets associated to response or progression in different studies and discuss their accuracy in diagnosis.

scholarly journals A review on immune checkpoint blockage therapy

2020 ◽  
Vol 2 (1) ◽  
pp. 12-17
Author(s):  
Thamrook s Shajahan ◽  
Shaiju S Dharan ◽  
Merlin Nj
Keyword(s):  
T Cells ◽  
Immune System ◽  
T Cell ◽  
Cancer Cells ◽  
T Cell Activation ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Checkpoint Inhibitor ◽  
Checkpoint Inhibitors ◽  
The Body

Activating the immune system to eliminate cancer cells and produce clinically relevant response has been a long standing goal of cancer research. Most promising therapeutic approaches of activating antitumor immunity include immune checkpoint inhibitors. Our immune system protect us from disease, killing bacteria and virus. One main type of immune cell called T-cells. T-cells have protein that turn it off. These are called checkpoint. Immune checkpoint are accessory molecules that either promote or inhibit T-cell activation. Checkpoint inhibitor are a type of immunotherapy. They block protein that stops the immune system from attacking the cancer cells. Checkpoint inhibitor are a type of monoclonal antibody or targeted treatment. Immune system cells, such as T-cells and Antigen presenting cells (APCs), defend and protect the body. Immune system play an important role in controlling and eradicating cancer. Cytotoxic T lymphocytes associated protein 4(CTLA-4) and Programmed cell dealth protein (PD-1) are checkpoint protein which is the negative regulation of T-cell immune function. Inhibition of the target, results in increased activation of immune system.

scholarly journals Pulsed focused ultrasound can improve the anti-cancer effects of immune checkpoint inhibitors in murine pancreatic cancer

2021 ◽  
Vol 18 (180) ◽  
pp. 20210266
Author(s):  
Petros X. E. Mouratidis ◽  
Marcia Costa ◽  
Ian Rivens ◽  
Elizabeth E. Repasky ◽  
Gail ter Haar
Keyword(s):  
Pancreatic Cancer ◽  
T Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Focused Ultrasound ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Acoustic Cavitation ◽  
High Intensity Focused Ultrasound ◽  
Pulsed Focused Ultrasound

Pulsed high-intensity focused ultrasound (pHIFU) uses acoustic pressure to physically disrupt tumours. The aim of this study was to investigate whether pHIFU can be used in combination with immune checkpoint inhibitors (ICIs) to enhance survival of tumour-bearing animals. Murine orthotopic pancreatic KPC tumours were exposed both to a grid of pHIFU lesions (peak negative pressure = 17 MPa, frequency = 1.5 MHz, duty cycle = 1%, 1 pulse s −1 , duration = 25 s) and to anti-CTLA-4/anti-PD-1 antibodies. Acoustic cavitation was detected using a weakly focused passive sensor. Tumour dimensions were measured with B-mode ultrasound before treatment and with callipers post-mortem. Immune cell subtypes were quantified with immunohistochemistry and flow cytometry. pHIFU treatment of pancreatic tumours resulted in detectable acoustic cavitation and increased infiltration of CD8 + T cells in the tumours of pHIFU and pHIFU + ICI-treated subjects compared with sham-exposed subjects. Survival of subjects treated with pHIFU + ICI was extended relative to both control untreated subjects and those treated with either pHIFU or ICI alone. Subjects treated with pHIFU + ICI had increased levels of CD8 + IFNγ + T cells, increased ratios of CD8 + IFNγ + to CD3 + CD4 + FoxP3 + and CD11b + Ly6G + cells, and decreased CD11c high cells in their tumours compared with controls. These results provide evidence that pHIFU combined with ICI may have potential for use in pancreatic cancer therapy.

scholarly journals Immune cell infiltration signatures identified molecular subtypes and underlying mechanisms in gastric cancer

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yilin Lin ◽  
Xiaoxian Pan ◽  
Long Zhao ◽  
Changjiang Yang ◽  
Zhen Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Immune Checkpoint ◽  
Therapeutic Efficacy ◽  
Evaluation System ◽  
Immune Cell ◽  
Immune Escape ◽  
Checkpoint Inhibitors ◽  
Cell Infiltration ◽  
Epstein Barr Virus Infection ◽  
Immune Cell Infiltration

AbstractIncreasing evidence has clarified that the tumor microenvironment (TME) is closely related to the prognosis and therapeutic efficacy of cancer. However, there is no reliable TME evaluation system used to accurately predict the prognosis of and therapeutic efficacy in gastric cancer. We evaluated the immune microenvironment score (IMS) of 1422 gastric cancer samples based on 51 immune cell signatures. We explored the relationship between the IMS and prognosis, immune cell infiltration, cancer subtype, and potential immune escape mechanisms. The results show that activation of the stroma and decreased levels of immune infiltration were associated with a low IMS. A high IMS was characterized by Epstein–Barr virus infection, increased mutation load, microsatellite instability, and immune cell infiltration. A high IMS was also related to high expression of immune checkpoint molecules (PD-1/PD-L1). Finally, patients with a high IMS had a better response to PD-1/PD-L1 inhibitors and may be more suitable for immune checkpoint inhibitors (area under the curve = 0.81). In addition, a low IMS may be converted into the immune-infiltrating subtype after romidepsin treatment. Stratification based on the IMS may enable gastric cancer patients to benefit more from immunotherapy and help identify new cancer treatment strategies.

Immune-desert tumor microenvironment in SMARCA4-deficient thoracic sarcomas with limited efficacy of immune checkpoint inhibitors.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 11552-11552
Author(s):  
Justine Gantzer ◽  
Guillaume Davidson ◽  
Bujamin Vokshi ◽  
Noëlle Weingertner ◽  
Antoine Bougoüin ◽  
...  
Keyword(s):  
T Cells ◽  
Cell Line ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Fibroblast Cell ◽  
Small Cell ◽  
Limited Efficacy ◽  
Cell Ontogeny

11552 Background: SMARCA4-deficient thoracic sarcomas (SDS) are rare and aggressive sarcomas characterized by inactivating SMARCA4 mutations, with no approved treatment to date. Previous data linking SWI/SNF deficiency with tumor immune microenvironment (TME) are contradictory. While an immunogenic microenvironment and efficacy of immune checkpoint inhibitors (ICI) were described in SMARCA4-deficient small cell carcinoma of the ovary, the TME phenotype of SDS is unknown; in addition, response of patients to ICI is lacking. Methods: All consecutive patients diagnosed with SDS between 2016 and 2019 in Strasbourg University Hospital were included and clinical outcomes collected. Immunostainings for immune cell markers, immune checkpoints and tertiary lymphoid structures (TLS) were assessed on available samples. Validation was performed using an independent transcriptomes dataset of SDS (n = 12), not otherwise specified (NOS) non-small cell lung cancer (NSCLC) with/without SMARCA4 mutations (n = 14) and undifferentiated thoracic sarcoma (n = 5). Finally, chemokines (CXL9 and CXCL10) and PD-L1 expressions were assessed in NSCLC and thoracic fibroblast cell lines, treated with/without interferon gamma (IFNG). Results: Nine patients were identified and had all metastatic disease at presentation, with a median overall survival of 1.8 months (0.3-NR). Among them, 4 received ICI as part of their treatment. Out of 11 evaluated tumors samples, all but one case showed no TLS, consistent with an immune desert TME phenotype charted by low densities of CD3+ T-cells, CD8+ T-cells, CD20+ B-cells from one side and high density of CD68+ macrophage-cells from the other side. Conversely, the unique tumor with TLS aggregate showed an immune-rich TME phenotype associated with high mutational tumor burden. While the patient with TLS harboring tumor showed an exceptional long-lasting response, the 3 remaining patients without TLS had progressive disease at best response to ICI. Using an independent cohort, unsupervised clustering using immune cell scores identified two clusters tightly associated with cell ontogeny of cancer subtypes and immunity; while cluster 1 (C1) was enriched for NOS NSCLC independently from SMARCA4 status (n = 9/10; 90%) (p = 0.001), C2 was enriched for SDS (n = 11/12; 91.7%) (p = 0.005) and undifferentiated thoracic sarcomas (n = 5/5; 100%) (p = 0.0005). Finally, SMARCA4 loss of function experiments revealed upregulation of chemokines (CXL9 and CXCL10) and PD-L1 expression in the NSCLC cell line with no effect on thoracic fibroblast cell line. Conclusions: SDS harbor an immune desert TME phenotype with limited efficacy to ICI, similar to other sarcomas. Our data suggest that TME of SMARCA4-driven tumors might vary according to the cell of origin. Further studies are needed to understand the interplay between SWI/SNF mutations, cell ontogeny and immunity.

Immune checkpoint and checkpoint inhibitors in hepatocellular carcinoma

2018 ◽  
Vol 1 (1) ◽  
pp. 28-32
Author(s):  
Piyawat Komolmit
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Major Histocompatibility Complex ◽  
T Cell Receptor ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Cell Receptor ◽  
Immune Checkpoints ◽  
Histocompatibility Complex

การรักษามะเร็งด้วยแนวความคิดของการกระตุ้นให้ภูมิต้านทานของร่างกายไปทำลายเซลล์มะเร็งนั้น ปัจจุบันได้รับการพิสูจน์ชัดว่าวิธีการนี้สามารถหยุดยั้งการแพร่กระจายของเซลล์มะเร็ง โดยไม่ก่อให้เกิดภาวะแทรกซ้อนทางปฏิกิริยาภูมิต้านทานต่ออวัยวะส่วนอื่นที่รุนแรง สามารถนำมาใช้ทางคลินิกได้ ยุคของการรักษามะเร็งกำลังเปลี่ยนจากยุคของยาเคมีบำบัดเข้าสู่การรักษาด้วยภูมิต้านทาน หรือ immunotherapy ยากลุ่ม Immune checkpoint inhibitors โดยเฉพาะ PD-1 กับ CTLA-4 inhibitors จะเข้ามามีบทบาทในการรักษามะเร็งตับในระยะเวลาอันใกล้ จำเป็นแพทย์จะต้องมีความรู้ความเข้าใจในพื้นฐานของ immune checkpoints และยาที่ไปยับยั้งโมเลกุลเหล่านี้ Figure 1 เมื่อ T cells รับรู้แอนทิเจนผ่านทาง TCR/MHC จะมีปฏิกิริยาระหว่าง co-receptors หรือ immune checkpoints กับ ligands บน APCs หรือ เซลล์มะเร็ง ทั้งแบบกระตุ้น (co-stimulation) หรือยับยั้ง (co-inhibition) TCR = T cell receptor, MHC = major histocompatibility complex

Bioinformatics Analysis Identifies CPZ as a Tumor Immunology Biomarker For Gastric Cancer

2020 ◽  
Vol 15 ◽  
Author(s):  
Yuan Gu ◽  
Ying Gao ◽  
Xiaodan Tang ◽  
Huizhong Xia ◽  
Kunhe Shi
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Signaling Pathway ◽  
Tumor Immunology ◽  
Bioinformatics Analysis ◽  
Human Cancer ◽  
Disease Free Survival ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Pathway Regulation

Background: Gastric cancer (GC) is one of the most common malignancies worldwide. However, the biomarkers for the prognosis and diagnosis of Gastric cancer were still need. Objective: The present study aimed to evaluate whether CPZ could be a potential biomarker for GC. Method: Kaplan-Meier plotter (http://kmplot.com/analysis/) was used to determine the correlation between CPZ expression and overall survival (OS) and disease-free survival (DFS) time in GC [9]. We analyzed CPZ expression in different types of cancer and the correlation of CPZ expression with the abundance of immune infiltrates, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells, via gene modules using TIMER Database. Results: The present study identified that CPZ was overexpressed in multiple types of human cancer, including Gastric cancer. We found that overexpression of CPZ correlates to the poor prognosis of patients with STAD. Furthermore, our analyses show that immune infiltration levels and diverse immune marker sets are correlated with levels of CPZ expression in STAD. Bioinformatics analysis revealed that CPZ was involved in regulating multiple pathways, including PI3K-Akt signaling pathway, cGMP-PKG signaling pathway, Rap1 signaling pathway, TGF-beta signaling pathway, regulation of cell adhesion, extracellular matrix organization, collagen fibril organization, collagen catabolic process. Conclusion: This study for the first time provides useful information to understand the potential roles of CPZ in tumor immunology and validate it to be a potential biomarker for GC.

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