POTEE drives colorectal cancer development via regulating SPHK1/p65 signaling

Shen, Zhiyong; Feng, Xiaochuang; Fang, Yuan; Li, Yongsheng; Li, Zhenkang; Zhan, Yizhi; Lin, Mingdao; Li, Guoxin; Ding, Yi; Deng, Haijun

doi:10.1038/s41419-019-2046-7

Cited by 32 publications

(28 citation statements)

References 41 publications

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“…High-risk genes in the model, including GPX3, AKR1C4, SPHK1and ADCY5, have been reported to promote hypermethylation, rare mutations, cancer progression, poor prognosis, and the developmental process of malignant cells in CRC patient samples or cell lines ( Gylfe et al, 2013 ; Kawamori et al, 2009 ; Liang et al, 2013 ; Pan et al, 2019 ; Zhou et al, 2019 ). SPHK1 promotes the phosphorylation and activation of p65, thus promoting the occurrence of CRC ( Shen et al, 2019b ). The expressions of NAT2, ADCY5, SPHK1, GPX3, and risk score were significantly correlated with the clinicopathological features of CRC, and the risk score was closely correlated with the malignant clinicopathological characteristics of CRC and is an independent prognostic factor.…”

Section: Discussionmentioning

confidence: 99%

Prognostic implications of metabolism-associated gene signatures in colorectal cancer

Miao

Wang

et al. 2020

PeerJ

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Colorectal cancer (CRC) is one of the most common and deadly malignancies. Novel biomarkers for the diagnosis and prognosis of this disease must be identified. Besides, metabolism plays an essential role in the occurrence and development of CRC. This article aims to identify some critical prognosis-related metabolic genes (PRMGs) and construct a prognosis model of CRC patients for clinical use. We obtained the expression profiles of CRC from The Cancer Genome Atlas database (TCGA), then identified differentially expressed PRMGs by R and Perl software. Hub genes were filtered out by univariate Cox analysis and least absolute shrinkage and selection operator Cox analysis. We used functional enrichment analysis methods, such as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis, to identify involved signaling pathways of PRMGs. The nomogram predicted overall survival (OS). Calibration traces were used to evaluate the consistency between the actual and the predicted survival rate. Finally, a prognostic model was constructed based on six metabolic genes (NAT2, XDH, GPX3, AKR1C4, SPHK1, and ADCY5), and the risk score was an independent prognostic prognosticator. Genetic expression and risk score were significantly correlated with clinicopathologic characteristics of CRC. A nomogram based on the clinicopathological feature of CRC and risk score accurately predicted the OS of individual CRC cancer patients. We also validated the results in the independent colorectal cancer cohorts GSE39582 and GSE87211. Our study demonstrates that the risk score is an independent prognostic biomarker and is closely correlated with the malignant clinicopathological characteristics of CRC patients. We also determined some metabolic genes associated with the survival and clinical stage of CRC as potential biomarkers for CRC diagnosis and treatment.

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Section: Discussionmentioning

confidence: 99%

Prognostic implications of metabolism-associated gene signatures in colorectal cancer

Miao

Wang

et al. 2020

PeerJ

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“…Colorectal cancer (CRC) is the second most occurring neoplasia in men and the third in women, and the second leading cause of cancer-related deaths worldwide. Solid epidemiologic data show that in 2018 there were over 1.8 million new cases [ 1 ], raising a significant scientific interest [ 2 , 3 , 4 , 5 , 6 ]. Unfortunately, about 30–40% of patients have at diagnosis a metastatic CRC (mCRC), and an additional 30% will develop it later.…”

Section: Introductionmentioning

confidence: 99%

Evolution of Mutational Landscape and Tumor Immune-Microenvironment in Liver Oligo-Metastatic Colorectal Cancer

Ottaiano

Caraglia

Mauro

et al. 2020

Cancers

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Genetic dynamics underlying cancer progression are largely unknown and several genes involved in highly prevalent illnesses (e.g., hypertension, obesity, and diabetes) strongly concur to cancer phenotype heterogeneity. To study genotype-phenotype relationships contributing to the mutational evolution of colorectal cancer (CRC) with a focus on liver metastases, we performed genome profiling on tumor tissues of CRC patients with liver metastatic disease and no co-morbidities. We studied 523 cancer-related genes and tumor-immune microenvironment characteristics in primary and matched metastatic tissues. We observed a loss of KRAS and SMAD4 alterations and a high granzyme-B+ T-cell infiltration when the disease did not progress. Conversely, gain in KRAS, PIK3CA and SMAD4 alterations and scarce granzyme-B+ T-cells infiltration were observed when the tumor evolved towards a poly-metastatic spread. These findings provide novel insights into the identification of tumor oligo-metastatic status, indicating that some genes are on a boundary line between these two clinical settings (oligo- vs. poly-metastatic CRC). We speculate that the identification of these genes and modification of their evolution could be a new approach for anti-cancer therapeutic strategies.

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“…SPHK1 promotes the phosphorylation and activation of p65, thus promoting the occurrence of CRC (Shen et al 2019b). The expressions of NAT2, ADCY5, SPHK1, GPX3, and risk score were significantly correlated with the clinicopathological features of CRC, and the risk score was closely correlated with the malignant clinicopathological characteristics of CRC and is an independent prognostic factor.…”

Section: Discussionmentioning

confidence: 90%

Peer Review #3 of "Prognostic implications of metabolism-associated gene signatures in colorectal cancer (v0.2)"

2020

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Colorectal cancer (CRC) is one of the most common and deadly malignancies. Novel biomarkers for the diagnosis and prognosis of this disease must be identified. Besides, metabolism plays an essential role in the occurrence and development of CRC. This article aims to identify some critical prognosis-related metabolic genes (PRMGs) and construct a prognosis model of CRC patients for clinical use. We obtained the expression profiles of CRC from The Cancer Genome Atlas database (TCGA), then identified differentially expressed PRMGs by R and Perl software. Hub genes were filtered out by univariate Cox analysis and least absolute shrinkage and selection operator Cox analysis. We used functional enrichment analysis methods, such as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis, to identify involved signaling pathways of PRMGs. The nomogram predicted overall survival (OS) Calibration traces were used to evaluate the consistency between the actual and the predicted survival rate. Finally, a prognostic model was constructed based on six metabolic genes (NAT2, XDH, GPX3, AKR1C4, SPHK1, and ADCY5), and the risk score was an independent prognostic prognosticator. Genetic expression and risk score were significantly correlated with clinicopathologic characteristics of CRC. A nomogram based on the clinicopathological feature of CRC and risk score accurately predicted the OS of individual CRC cancer patients. We also validated the results in the independent colorectal cancer cohorts GSE39582 and GSE87211. Our study demonstrates that the risk score is an independent prognostic biomarker and is closely correlated with the malignant clinicopathological characteristics of CRC patients. We also determined some metabolic genes associated with the survival and clinical stage of CRC as potential biomarkers for CRC diagnosis and treatment.

show abstract

POTEE drives colorectal cancer development via regulating SPHK1/p65 signaling

Cited by 32 publications

References 41 publications

Prognostic implications of metabolism-associated gene signatures in colorectal cancer

Prognostic implications of metabolism-associated gene signatures in colorectal cancer

Evolution of Mutational Landscape and Tumor Immune-Microenvironment in Liver Oligo-Metastatic Colorectal Cancer

Peer Review #3 of "Prognostic implications of metabolism-associated gene signatures in colorectal cancer (v0.2)"

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