Dataset Information

Development of an oncogenic dedifferentiation SOX signature with prognostic significance in hepatocellular carcinoma.

ABSTRACT:

Background

Gradual loss of terminal differentiation markers and gain of stem cell-like properties is a major hall mark of cancer malignant progression. The stem cell pluripotent transcriptional factor SOX family play critical roles in governing tumor plasticity and lineage specification. This study aims to establish a novel SOX signature to monitor the extent of tumor dedifferentiation and predict prognostic significance in hepatocellular carcinoma (HCC).

Methods

The RNA-seq data from The Cancer Genome Atlas (TCGA) LIHC project were chronologically divided into the training (n?=?188) and testing cohort (n?=?189). LIRI-JP project from International Cancer Genome Consortium (ICGC) data portal was used as an independent validation cohort (n?=?232). Kaplan-Meier and multivariable Cox analyses were used to examine the clinical significance and prognostic value of the signature genes.

Results

The SOX gene family members were found to be aberrantly expressed in clinical HCC patients. A five-gene SOX signature with prognostic value was established in the training cohort. The SOX signature genes were found to be closely associated with tumor grade and tumor stage. Liver cancer dedifferentiation markers (AFP, CD133, EPCAM, and KRT19) were found to be progressively increased while hepatocyte terminal differentiation markers (ALB, G6PC, CYP3A4, and HNF4A) were progressively decreased from HCC patients with low SOX signature scores to patients with high SOX signature scores. Kaplan-Meier survival analysis further indicated that the newly established SOX signature could robustly predict patient overall survival in both training, testing, and independent validation cohort.

Conclusions

An oncogenic dedifferentiation SOX signature presents a great potential in predicting prognostic significance in HCC, and might provide novel biomarkers for precision oncology further in the clinic.

SUBMITTER: Li MM

PROVIDER: S-EPMC6714407 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Development of an oncogenic dedifferentiation SOX signature with prognostic significance in hepatocellular carcinoma.

Li Mei-Mei MM Tang Yun-Qiang YQ Gong Yuan-Feng YF Cheng Wei W Li Hao-Long HL Kong Fan-En FE Zhu Wen-Jie WJ Liu Shan-Shan SS Huang Li L Guan Xin-Yuan XY Ma Ning-Fang NF Liu Ming M

BMC cancer 20190828 1

<h4>Background</h4>Gradual loss of terminal differentiation markers and gain of stem cell-like properties is a major hall mark of cancer malignant progression. The stem cell pluripotent transcriptional factor SOX family play critical roles in governing tumor plasticity and lineage specification. This study aims to establish a novel SOX signature to monitor the extent of tumor dedifferentiation and predict prognostic significance in hepatocellular carcinoma (HCC).<h4>Methods</h4>The RNA-seq data ...[more]

PMID: 31462277

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Project description:BackgroundHepatocellular carcinoma (HCC) ranks the sixth prevalent tumors with high mortality globally. Alternative splicing (AS) drives protein diversity, the imbalance of which might act an important factor in tumorigenesis. This study aimed to construct of AS-based prognostic signature and elucidate the role in tumor immune microenvironment (TIME) and immunotherapy in HCC.MethodsUnivariate Cox regression analysis was performed to determine the prognosis-related AS events and gene set enrichment analysis (GSEA) was employed for functional annotation, followed by the development of prognostic signatures using univariate Cox, LASSO and multivariate Cox regression. K-M survival analysis, proportional hazards model, and ROC curves were conducted to validate prognostic value. ESTIMATE R package, ssGSEA algorithm and CIBERSORT method and TIMER database exploration were performed to uncover the context of TIME in HCC. Quantitative real-time polymerase chain reaction was implemented to detect ZDHHC16 mRNA expression. Cytoscape software 3.8.0 were employed to visualize AS-splicing factors (SFs) regulatory networks.ResultsA total of 3294 AS events associated with survival of HCC patients were screened. Based on splicing subtypes, eight AS prognostic signature with robust prognostic predictive accuracy were constructed. Furthermore, quantitative prognostic nomogram was developed and exhibited robust validity in prognostic prediction. Besides, the consolidated signature was significantly correlated with TIME diversity and ICB-related genes. ZDHHC16 presented promising prospect as prognostic factor in HCC. Finally, the splicing regulatory network uncovered the potential functions of splicing factors (SFs).ConclusionHerein, exploration of AS patterns may provide novel and robust indicators (i.e., risk signature, prognostic nomogram, etc.,) for prognostic prediction of HCC. The AS-SF networks could open up new approach for investigation of potential regulatory mechanisms. And pivotal players of AS events in context of TIME and immunotherapy efficiency were revealed, contributing to clinical decision-making and personalized prognosis monitoring of HCC.

Project description:BackgroundSOCS1 and SOCS3 genes are considered tumor suppressors in hepatocellular carcinoma (HCC) due to frequent epigenetic repression. Consistent with this notion, mice lacking SOCS1 or SOCS3 show increased susceptibility to diethylnitrosamine (DEN)-induced HCC. As SOCS1 and SOCS3 are important regulators of cytokine and growth factor signaling, their loss could activate oncogenic signaling pathways. Therefore, we examined the correlation between SOCS1/SOCS3 and key oncogenic signaling pathway genes as well as their prognostic significance in HCC.MethodsThe Cancer Genome Atlas dataset on HCC comprising clinical and transcriptomic data was retrieved from the cBioportal platform. The correlation between the expression of SOCS1 or SOCS3 and oncogenic pathway genes was evaluated using the GraphPad PRISM software. The inversely correlated genes were assessed for their impact on patient survival using the UALCAN platform and their expression quantified in the regenerating livers and DEN-induced HCC tissues of mice lacking Socs1 or Socs3. Finally, the Cox proportional hazards model was used to evaluate the predictive potential of SOCS1 and SOCS3 when combined with the genes of select oncogenic signaling pathways.ResultsSOCS1 expression was comparable between HCC and adjacent normal tissues, yet higher SOCS1 expression predicted favorable prognosis. In contrast, SOCS3 expression was significantly low in HCC, yet it lacked predictive potential. The correlation between SOCS1 or SOCS3 expression and key genes of the cell cycle, receptor tyrosine kinase, growth factor and MAPK signaling pathways were mostly positive than negative. Among the negatively correlated genes, only a few showed elevated expression in HCC and predicted survival. Many PI3K pathway genes showed mutual exclusivity with SOCS1 and/or SOCS3 and displayed independent predictive ability. Among genes that negatively correlated with SOCS1 and/or SOCS3, only CDK2 and AURKA showed corresponding modulations in the regenerating livers and DEN-induced tumors of hepatocyte-specific Socs1 or Socs3 deficient mice and predicted patient survival. The Cox proportional hazards model identified the combinations of SOCS1 or SOCS3 with CXCL8 and DAB2 as highly predictive.ConclusionsSOCS1 expression in HCC has an independent prognostic value whereas SOCS3 expression does not. The predictive potential of SOCS1 expression is increased when combined with other oncogenic signaling pathway genes.

Dataset Information

Development of an oncogenic dedifferentiation SOX signature with prognostic significance in hepatocellular carcinoma.

Background

Methods

Results

Conclusions

Publications

Development of an oncogenic dedifferentiation SOX signature with prognostic significance in hepatocellular carcinoma.

Similar Datasets

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