Crosstalk between NLRP12 and JNK during Hepatocellular Carcinoma

Khan, Shahanshah; Zaki, Hasan

doi:10.3390/ijms21020496

Cited by 15 publications

(7 citation statements)

References 92 publications

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“…Whether they play critical roles in the prognosis of cancer or a specific cancer type is a concern that needs further study. In addition, there were complex cross talks or interactions among different pathways working together to influence the occurrence and development of HCC (27,28). Our study quantified and differentially analyzed the activities of 50 hallmark pathways in five cohorts with GSVA.…”

Section: Discussionmentioning

confidence: 99%

Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma

Zhong

Chang³

2022

Front. Oncol.

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BackgroundThe initiation and progression of tumors were due to variations of gene sets rather than individual genes. This study aimed to identify novel biomarkers based on gene set variation analysis (GSVA) in hepatocellular carcinoma.MethodsThe activities of 50 hallmark pathways were scored in three microarray datasets with paired samples with GSVA, and differential analysis was performed with the limma R package. Unsupervised clustering was conducted to determine subtypes with the ConsensusClusterPlus R package in the TCGA-LIHC (n = 329) and LIRI-JP (n = 232) cohorts. Differentially expressed genes among subtypes were identified as initial variables. Then, we used TCGA-LIHC as the training set and LIRI-JP as the validation set. A six-gene model calculating the risk scores of patients was integrated with the least absolute shrinkage and selection operator (LASSO) and stepwise regression analyses. Kaplan–Meier (KM) and receiver operating characteristic (ROC) curves were performed to assess predictive performances. Multivariate Cox regression analyses were implemented to select independent prognostic factors, and a prognostic nomogram was integrated. Moreover, the diagnostic values of six genes were explored with the ROC curves and immunohistochemistry.ResultsPatients could be separated into two subtypes with different prognoses in both cohorts based on the identified differential hallmark pathways. Six prognostic genes (ASF1A, CENPA, LDHA, PSMB2, SRPRB, UCK2) were included in the risk score signature, which was demonstrated to be an independent prognostic factor. A nomogram including 540 patients was further integrated and well-calibrated. ROC analyses in the five cohorts and immunohistochemistry experiments in solid tissues indicated that CENPA and UCK2 exhibited high and robust diagnostic values.ConclusionsOur study explored a promising prognostic nomogram and diagnostic biomarkers in hepatocellular carcinoma.

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Section: Discussionmentioning

confidence: 99%

Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma

Zhong

Chang³

2022

Front. Oncol.

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“…Numerous diseases are correlated with its dysregulation, including steatosis, fibrosis, cirrhosis and hepatoma 22 , 23 , 24 . The abnormality or deficiency of JNK will inhibit the proliferation of HCC cells 25 , 26 , 27 . However, the factors related to the pathogenesis have not been completely identified because of its complicated mechanism, and the roles of TPM4 in HCC need to be further studied.…”

Section: Discussionmentioning

confidence: 99%

The expression and clinical significance of TPM4 in hepatocellular carcinoma

Li¹,

Tao²,

Zhang³

et al. 2021

Int. J. Med. Sci.

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Hepatocellular carcinoma (HCC) is known as the fifth most common cancer in the world for its poor prognosis. New diagnostic markers and treatments are urgent to discover. To evaluate the protein expression of Tropomyosin4 (TPM4) and investigate its prognostic value in HCC, we collected 110 patients with different degrees of HCC and 10 patients with normal hepatic tissues and performed immunohistochemistry. Western bot was used to evaluate the expression of TPM4 in three HCC cell lines (HepG2, Huh7, SMMC-7721) and normal liver cell line LO2, as well as 7 HCC tissues and 7 normal hepatic tissues. The results of TPM4 staining revealed that TPM4 expression in HCC was higher than that in normal hepatic tissues, which was positive in 51.8% (n=57) and negative in 48.2% (n=53) while in normal hepatic tissues positive staining was in 10% (n=1) and negative staining was in 90% (n=9) (P=0.011). And the expression of TPM4 was related to pT status, grade and stage (P<0.001, P=0.015 and P<0.001, respectively). Western blot results indicated that TPM4 was high expressed in HCC cell line and HCC tissues. In conclusion, we believe that TPM4 can be applied as a diagnostic and prognostic marker to assist the management of HCC.

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“…Although there was no association between VDR polymorphisms with HBV infection risk, the ApaI polymorphism might be a genetic factor associated with the clinical outcome and disease progression in HBV infected patients [ 37 ]. Khan et al has also reported that NLRP12 plays a critical role in suppressing the progression of HCC via negative regulation of the JNK pathway [ 38 ]. These reports all indicated that human nuclear receptors were closely associated with development of HCC and could be novel therapeutic targets.…”

Section: Discussionmentioning

confidence: 99%

Human nuclear receptors (NRs) genes have prognostic significance in hepatocellular carcinoma patients

Sun

Shen

2021

World J Surg Onc

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Background Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality in the world. Method We downloaded the mRNA profiles and clinical information of 371 HCC patients from The Cancer Genome Atlas (TCGA) database. The consensus clustering analysis with the mRNA levels of 48 nuclear receptors (NRs) was performed by the “ConsensusClusterPlus.” The univariate Cox regression analysis was performed to predict the prognostic significance of NRs on HCC. The risk score was calculated by the prognostic model constructed based on eight optimal NRs. Then multivariate Cox regression analysis was performed to determine whether the risk score is an independent prognostic signature. Finally, the nomogram based on multiple independent prognostic factors was used to predict the long-term survival of HCC patients. Results The prognostic model constructed based on the eight optimal NRs (NR1H3, ESR1, NR1I2, NR2C1, NR6A1, PPARD, PPARG, and VDR) could effectively predict the prognosis of HCC patients as an independent prognostic signature. Moreover, the nomogram was constructed based on multiple independent prognostic factors including risk score and tumor node metastasis (TNM) stage and could better predict the long-term survival for 3- and 5-year of HCC patients. Conclusion Our results provided novel evidences that NRs could act as the potential prognostic signatures for HCC patients.

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Crosstalk between NLRP12 and JNK during Hepatocellular Carcinoma

Cited by 15 publications

References 92 publications

Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma

Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma

The expression and clinical significance of TPM4 in hepatocellular carcinoma

Human nuclear receptors (NRs) genes have prognostic significance in hepatocellular carcinoma patients

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