High TNFAIP6 level is associated with poor prognosis of urothelial carcinomas

Chan, Ti Chun; Li, Chien‐Feng; Ke, Hung‐Lung; Wei, Yu; Shiue, Yow Ling; Li, Ching Chia; Yeh, Hsin Chih; Lee, Hsiang Ying; Huang, Steven Kuan-Hua; Wu, Wen‐Jeng; Li, Wei Ming

doi:10.1016/j.urolonc.2018.12.009

Cited by 26 publications

(23 citation statements)

References 28 publications

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“…According to pharmacogenomics, NRG3 rs1649942 genetic variants have been validated to affect epithelial ovarian cancer first-line treatment outcomes, which confirmed patients carrying the NRG3 rs1649942 A allele presented a significantly longer OS time (34). In addition, CLC and TNFAIP6, which are cytokine receptors, are involved in disease progression and the immune response (35) in a variety of tumors, such as gastric cancer (36), breast cancer (37) and urothelial carcinomas (38). STEM was used to reveal temporal gene expression profiles and identify significant patterns from the day before TACE (day 0) to day 21 post-TACE that were >2-fold different (P<0.05).…”

Section: Discussionmentioning

confidence: 97%

Time‑series clustering of cytokine expression after transarterial chemoembolization in patients with hepatocellular carcinoma

et al. 2019

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Cytokines play an important role in the development of tumors. The purpose of the present study was to evaluate the mechanisms and cytokine level changes after transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC). The Short Time-series Expression Miner (STEM) program was utilized to cluster cytokine expression profiles from the day before TACE to day 21 post-TACE. Based on the identified significant signatures, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed. Cytokines were serially monitored in 60 evaluable patients to identify the results of the STEM program. Examination of the significant signatures identified 6 significant time-varied expression patterns for 507 cytokines (profiles 16, 18, 28, 41, 42 and 43). GO analysis was enriched in 'cytokine receptor-binding' and 'cytokine receptor activity', and the identified signaling pathways included 'cytokine-cytokine receptor interaction' and the 'JAK-STAT signaling pathway'. Ciliary neurotrophic factor (CNTF) level was increased early after TACE, reaching a peak on day 7 before finally decreasing from day 14 onwards, and was significantly positively correlated with aminotransferase level. Serum levels of pre-TACE IL-10 predicted the local tumor response and overall survival (OS) of the patients, while serum levels of post-TACE IL-1β only indicated the local tumor response of the patient. Overall, the present study identified cytokine time-series expression profiles of patients with HCC undergoing TACE. Early phase increases in CNTF after TACE were associated with post-treatment hepatic injury. IL-1β may reflect an objective response after TACE, while IL-10 may represent a biomarker for OS and the objective response pre-TACE, which may help patients with HCC to benefit from TACE.

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Section: Discussionmentioning

confidence: 97%

Time‑series clustering of cytokine expression after transarterial chemoembolization in patients with hepatocellular carcinoma

et al. 2019

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“…A study suggests that MEOX2 may play a role in the carcinogenic process of colon adenocarcinoma 47 , but the specific mechanism is still unclear. TNFα-stimulated gene-6 (TNFAIP6) plays a vital role in the prognosis of various tumors 48 , 49 , but few studies on the specific mechanism of TNFAIP6 in the progression of CRC. However, we are particularly interested in TNFAIP6 among these six prognostic-related genes.…”

Section: Discussionmentioning

confidence: 99%

Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods

Liu

Cheng

et al. 2021

Sci Rep

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Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to the malignant progression of CRC (metastasis, p = 0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein–protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine–cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in two independent cohorts (GSE17538 and GSE161158). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.

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“…It is reported to be an inflammation-associated protein regulated by proinflammatory cytokines such as TNFα, interferon-γ, and interleukin-1 ( 35 , 36 ). It had been demonstrated that high TNFAIP6 expression is significantly associated with aggressive pathological features in urothelial cancer and gastric cancer ( 37 , 38 ). Incorporating TNFAIP6 immunostaining in current pathological examinations may be useful for identifying high-risk patients to assist in personalized medical decision-making and therapy.…”

Section: Discussionmentioning

confidence: 99%

An Exploration of the Tumor Microenvironment Identified a Novel Five-Gene Model for Predicting Outcomes in Bladder Cancer

Feng

Sun

et al. 2021

Front. Oncol.

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Bladder cancer (BC) is one of the top ten most common cancer types globally, accounting for approximately 7% of all male malignancies. In the last few decades, cancer research has focused on identifying oncogenes and tumor suppressors. Recent studies have revealed that the interplay between tumor cells and the tumor microenvironment (TME) plays an important role in the initiation and development of cancer. However, the current knowledge regarding its effect on BC is scarce. This study aims to explore how the TME influences the development of BC. We focused on immune and stromal components, which represent the major components of TME. We found that the proportion of immune and stromal components within the TME was associated with the prognosis of BC. Furthermore, based on the scores of immune and stromal components, 811 TME-related differentially expressed genes were identified. Three subclasses with distinct biological features were divided based on these TME-genes. Finally, five prognostic genes were identified and used to develop a prognostic prediction model for BC patients based on TME-related genes. Additionally, we validated the prognostic value of the five-gene model using three independent cohorts. By further analyzing features based on the five-gene signature, higher CD8+ T cells, higher tumor mutational burden, and higher chemosensitivity were found in the low-risk group, which presented a better prognosis. In conclusion, our exploration comprehensively analyzed the TME and identified TME-related prognostic genes for BC, providing new insights into potential therapeutic targets.

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High TNFAIP6 level is associated with poor prognosis of urothelial carcinomas

Cited by 26 publications

References 28 publications

Time‑series clustering of cytokine expression after transarterial chemoembolization in patients with hepatocellular carcinoma

Time‑series clustering of cytokine expression after transarterial chemoembolization in patients with hepatocellular carcinoma

Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods

An Exploration of the Tumor Microenvironment Identified a Novel Five-Gene Model for Predicting Outcomes in Bladder Cancer

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