A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients

Stathmin 1 is a biomarker for diagnosis of microvascular invasion to predict prognosis of early hepatocellular carcinoma

Microvascular invasion (MVI) is presently evaluated as a high-risk factor to be directly relative to postoperative prognosis of hepatocellular carcinoma (HCC). Up to now, diagnosis of MVI mainly depends on the postoperative pathological analyses with H&E staining assay, based on numbers and distribution characteristics of MVI to classify the risk levels of MVI. However, such pathological analyses lack the specificity to discriminate MVI in HCC specimens, especially in complicated pathological tissues. In addition, the efficiency to precisely define stages of MVI is not satisfied. Thus, any biomarker for both conforming diagnosis of MVI and staging its levels will efficiently and effectively promote the prediction of early postoperative recurrence and metastasis for HCC. Through bioinformatics analysis and clinical sample verification, we discovered that Stathmin 1 (STMN1) gene was significantly up-regulated at the locations of MVI. Combining STMN1 immunostaining with classic H&E staining assays, we established a new protocol for MVI pathological diagnosis. Next, we found that the degrees of MVI risk could be graded according to expression levels of STMN1 for prognosis prediction on recurrence rates and overall survival in early HCC patients. STMN1 affected epithelial-mesenchymal transformation (EMT) of HCC cells by regulating the dynamic balance of microtubules through signaling of “STMN1-Microtubule-EMT” axis. Inhibition of STMN1 expression in HCC cells reduced their lung metastatic ability in recipients of mouse model, suggesting that STMN1 also could be a potential therapeutic target for inhibiting HCC metastasis. Therefore, we conclude that STMN1 has potentials for clinical applications as a biomarker for both pathological diagnosis and prognostic prediction, as well as a therapeutic target for HCC.

A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion

BACKGROUND

Hepatocellular carcinoma (HCC) is prevalent worldwide with a high mortality rate. Prognosis prediction is crucial for improving HCC patient outcomes, but effective tools are still lacking. Characteristics related to vascular invasion (VI), an important process involved in HCC recurrence and metastasis, may provide ideas on prognosis prediction.

METHODS

Tools, including R 4.0.3, Funrich version 3, Cytoscape 3.8.2, STRING 11.5, Venny 2.1.0, and GEPIA 2, were used to perform bioinformatic analyses. The VI-related microRNAs (miRNAs) were identified using Gene Expression Omnibus HCC miRNA dataset GSE67140, containing 81 samples of HCC with VI and 91 samples of HCC without VI. After further evaluated the identified miRNAs based on The Cancer Genome Atlas database, a prognostic model was constructed via Cox regression analysis. The miRNAs in this model were also verified in HCC patients. Moreover, a nomogram was developed by integrating risk score from the prognostic model with clinicopathological parameters. Finally, a potential miRNA-mRNA network related to VI was established through weighted gene co-expression network analysis of HCC mRNA dataset GSE20017, containing 40 samples of HCC with VI and 95 samples of HCC without VI.

RESULTS

A prognostic model of 5 VI-related miRNAs (hsa-miR-126-3p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-30a-5p, hsa-miR-199a-5p) was constructed. The area under receiver operating characteristic curve was 0.709 in predicting 5-year survival rate, with a sensitivity of 0.74 and a specificity of 0.63. The nomogram containing risk score could also predict prognosis. Moreover, a VI-related miRNA-mRNA network covering 4 miRNAs and 15 mRNAs was established.

CONCLUSION

The prognostic model and nomogram might be potential tools in HCC management, and the VI-related miRNA-mRNA network gave insights into how VI was developed.

A novel qualitative signature based on lncRNA pairs for prognosis prediction in hepatocellular carcinoma

Background

Prognostic assessment is imperative for clinical management of patients with hepatocellular carcinoma (HCC). Most reported prognostic signatures are based on risk scores summarized from quantitative expression level of candidate genes, which are vulnerable against experimental batch effects and impractical for clinical application. We aimed to develop a robust qualitative signature to assess individual survival risk for HCC patients.

Methods

Long non-coding RNA (lncRNA) pairs correlated with overall survival (OS) were identified and an optimal combination of lncRNA pairs based on the majority voting rule was selected as a classification signature to predict the overall survival risk in the cancer genome atlas (TCGA). Then, the signature was further validated in two external datasets. Besides, biomolecular characteristics, immune infiltration status, and chemotherapeutics efficacy of different risk groups were further compared. Finally, we performed key lncRNA screening and validated it in vitro.

Results

A signature consisting of 50 lncRNA pairs (50-LPS) was identified in TCGA and successfully validated in external datasets. Patients in the high-risk group, when at least 25 of the 50-LPS voted for high risk, had significantly worse OS than the low-risk group. Multivariate Cox, receiver operating characteristic (ROC) curve and decision curve analyses (DCA) demonstrated that the 50-LPS was an independent prognostic factor and more powerful than other available clinical factors in OS prediction. Comparison analyses indicated that different risk groups had distinct biomolecular characteristics, immune infiltration status, and chemotherapeutics efficacy. TDRKH-AS1 was confirmed as a key lncRNA and associated with cell growth of HCC.

Conclusions

The 50-LPS could not only predict the prognosis of HCC patients robustly and individually, but also provide theoretical basis for therapy. Besides, TDRKH-AS1 was identified as a key lncRNA in the proliferation of HCC. The 50-LPS might guide personalized therapy for HCC patients in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02507-z.

Clinical implications and molecular mechanisms of Cyclin-dependent kinases 4 for patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) was frequently considered as a kind of malignant tumor with a poor prognosis. Cyclin-dependent kinases (CDK) 4 was considered to be cell-cycle-related CDK gene. In this study, we explored the clinical significance of CDK4 in HCC patients.

Methods

Data of HCC patients were obtained from The Cancer Genome Atlas database (TCGA) and the Gene Expression Omnibus (GEO) database. Kaplan–Meier analysis and Cox regression model were performed to calculate median survival time (MST) and the hazard ration (HR), respectively. The joint-effect analysis and prognostic risk score model were constructed to demonstrate significance of prognosis-related genes. The differential expression of prognostic genes was further validated using reverse transcription-quantitative PCR (RT-qPCR) of 58 pairs of HCC samples.

Results

CDK1 and CDK4 were considered prognostic genes in TCGA and GSE14520 cohort. The result of joint-effect model indicated patients in CDK1 and CDK4 low expression groups had a better prognosis in TCGA (adjusted HR = 0.491; adjusted P = 0.003) and GSE14520 cohort (adjusted HR = 0.431; adjusted P = 0.002). Regarding Kaplan–Meier analysis, high expression of CDK1 and CDK4 was related to poor prognosis in both the TCGA (P < 0.001 and = 0.001 for CDK1 and CDK4, respectively) and the GSE14520 cohort (P = 0.006 and = 0.033 for CDK1 and CDK4, respectively). However, only CDK4 (P = 0.042) was validated in RT-qPCR experiment, while CDK1 (P = 0.075) was not.

Conclusion

HCC patients with high CDK4 expression have poor prognosis, and CDK4 could be a potential candidate diagnostic biomarker for HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02152-w.

Adenosine triphosphate-binding cassette subfamily C members in liver hepatocellular carcinoma: Bioinformatics-driven prognostic value

Aberrant expression of adenosine triphosphate-binding cassette subfamily C (ABCC), one of the largest superfamilies and transporter gene families of membrane proteins, is associated with various tumors. However, its relationship with liver hepatocellular carcinoma (LIHC) remains unclear.We used the Oncomine, UALCAN, Human Protein Atlas, GeneMANIA, GO, Kyoto Encyclopedia of Genes and Genomes (KEGG), TIMER, and Kaplan-Meier Plotter databases. On May 20, 2021, we searched these databases for the terms ABCC1, ABCC2, ABCC3, ABCC4, ABCC5, ABCC6, ABCC7, ABCC8, ABCC9, ABCC10, ABCC11, ABCC12, ABCC13, and "liver cancer." The exposure group comprised LIHC patients, and the control group comprised normal patients (those with noncancerous liver tissue). All patients shown in the retrieval language search were included. We compared the mRNA expression of these proteins in LIHC and control patients to examine the potential role of ABCC1-13 in LIHC.Relative to the normal liver tissue, mRNA expression of ABCC1/2/3/4/5/6/10 was significantly upregulated (P < .001), and that of ABCC9/11 significantly downregulated (both P < .001), in LIHC. ABCC mRNA expression varied with gender (P < .05), except for ABCC11-13; with tumor grade (P < 0.05), except for ABCC7/12/13; with tumor stage (P < .05), except for ABCC11-13; and with lymph node metastasis status (P < .05), except for ABCC7/8/11/12/13. Based on KEGG enrichment analysis, these genes were associated with the following pathways: ABC transporters, Bile secretion, Antifolate resistance, and Peroxisome (P < .05). Except for ABCC12/13, the ABCCs were significantly associated with B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell infiltration (P < .05). High mRNA expression of ABCC1/4/5/8 (P < .05) and low expression of ABCC6/7/9/12/13 (P < .05) indicated poor prognosis. Prognostic significance was indicated for ABCC2/13 for both men and women (P < .05); for ABCC1/6/12/13 for tumor grades 1-3 (P < .05); for ABCC5/11/12/13 for all tumor stages (P < .05); for ABCC1/11/12/13 for American Joint Committee on Cancer T stages 1-3 (P < .05); and for ABCC1/5/6/13 for vascular invasion. None showed prognostic significance for microvascular invasion (P < .05).We identified ABCC1/2/3/4/5/6/9/10/11 as potential diagnostic markers, and ABCC1/4/5/6/7/8/9/12/13 as prognostic markers, of LIHC. Our future work will promote the use of ABCCs in the diagnosis and treatment of LIHC.

Comprehensive profiling of the TRIpartite motif family to identify pivot genes in hepatocellular carcinoma

INTRODUCTION

TRIpartite motif (TRIM) proteins are important members of the Really Interesting New Gene-finger-containing E3 ubiquitin-conjugating enzyme and are involved in the progression of hepatocellular carcinoma (HCC). However, the diverse expression patterns of TRIMs and their roles in prognosis and immune infiltrates in HCC have yet to be analyzed.

MATERIALS

Combined with previous research, we used an Oncomine database and the Human Protein Atlas to compare TRIM family genes' transcriptional levels between tumor samples and normal liver tissues, as verified by the Gene Expression Profiling Interactive Analysis database. We investigated the patient survival data of TRIMs from the Kaplan-Meier plotter database. Clinicopathologic characteristics associations and potential diagnostic and prognostic values were validated with clinical and expressional data collected from the cancer genome atlas.

RESULTS

We identified TRIM28, TRIM37, TRIM45, and TRIM59 as high-priority members of the TRIMs family that modulates HCC. Low expression of TRIM28 was associated with shorter overall survival (OS) than high expression (log-rank p = 0.009). The same trend was identified for TRIM37 (p = 0.001), TRIM45 (p = 0.013), and TRIM59 (p = 0.011). Multivariate analysis indicated that the level of TRIM37 was a significant independent prognostic factor for both OS (p = 0.043) and progression-free interval (p = 0.044). We performed expression and mutation analysis and functional pathways and tumor immune infiltration analysis of the changes in TRIM factors.

CONCLUSION

These data suggested that TRIM28, TRIM37, TRIM45, and TRIM59 could serve as efficient prognostic biomarkers and therapeutic targets in HCC.

Role of SLC39A6 in the development and progression of liver cancer

Liver cancer is one of the most common malignant solid tumor types worldwide. The solute carrier (SLC)39A family is a main member of the SLC group of membrane transport proteins, which transfer zinc to the cytoplasm when cells are depleted of zinc; thus, it may provide a novel therapeutic target for human cancer. However, the prognostic value of SLC39A genes in patients with liver cancer has remained elusive. Therefore, the present study aimed to explore whether SLC39A family genes are associated with the survival rate of patients with liver cancer and to investigate the role of key genes of the SLC39A family in liver cancer. The mRNA expression of the SLC39A family in liver cancer was obtained from the UALCAN database. Survival curve analysis was performed to investigate the prognostic value of SLC39A family genes in the overall survival of patients with liver cancer. In addition to the bioinformatics analysis, SLC39A6 was knocked down in HepG2 and Hep3B cells to examine the effect on the proliferation, migration and invasion of liver cancer cells. The results suggested that SLC39A6 was significantly upregulated in liver cancer tissues compared with normal liver tissues. High expression of SLC39A6 was significantly associated with poor overall survival of patients with liver cancer. Furthermore, knockdown of SLC39A6 inhibited the proliferation, migration and invasion of liver cancer cells in vitro and in vivo. Collectively, the results of the present study suggested that SLC39A6 may be a promising prognostic biomarker for liver cancer and is associated with the proliferation, migration and invasion of liver cancer.

Field cancerization profile-based prognosis signatures lead to more robust risk evaluation in hepatocellular carcinoma

The development of reliable biomarkers has been an urgent issue as well as a hot spot of research on the diagnosis, treatment, and prognostic evaluation of hepatocellular carcinoma (HCC). Here, we established and validated two field cancerization profile-based prognostic signatures (gene expression score [GES] and immune score [IS]) for HCC. Our study confirmed that field cancerization profile-based models outperform conventional models on risk evaluation, offering insights for further studies on prognostic model construction. The nomogram constructed by combining GES, IS, and TNM stage was proved effective in improving the individualized prediction of the overall risk of patients. Distinct peritumoral characteristics were observed in several immune cells (e.g., CD8 T cells and dendritic cells), which might explain the diversified prognosis and clinical benefit of immunotherapy. Moreover, a series of drug targets, prognosis-associated genes, and pathways were identified, which may contribute to molecular mechanism studies as well as therapeutic target development of HCC.

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Two field cancerization feature-based prognostic signatures for HCC were developed

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Joint nomogram is effective in improving individualized risk prediction

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Different peritumor signatures were observed in several immune cells

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Several peritumoral drug targets, prognostic genes, and pathways were identified

Identification Prognostic Value and Correlation with Tumor-Infiltrating Immune Cells of Tripartite-Motif Family Genes in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common and mortality types of malignant tumors in the world. The Tripartite-Motif (TRIM) protein family consists of more than 80 proteins with E3 ubiquitin ligase activity. Increasing studies have found that TRIM family proteins play an extremely important role in the occurrence and development of tumors. However, the expression and prognostic values of TRIMs in HCC have not been clarified.

Methods

We used bioinformatic methods to explore the potential function of TRIM family genes in the HCC. Web servers ONCOMINE, UALCAN, GEPIA, cBioPortal, STRING, DAVID 6.8 and TIMER were used in this research.

Results

We screened TRIM1-76 and found the expressions of TRIM6, TRIM11, TRIM16, TRIM18(MID1), TRIM24, TRIM28, TRIM31, TRIM37, TRIM45, TRIM52, TRIM59, TRIM66 were significantly changed in HCC. Among them, TRIM24, TRIM28, TRIM37, TRIM45 and TRIM59 had significant effects on pathological stages, overall survival and disease free survival. Functions of these genes are primarily related to transcriptional misregulation in cancer, p53 signaling pathway, alcoholism and viral carcinogenesis, FoxO signal pathway, PI3K-AKT pathway, cell cycle, microRNAs in cancer. Our results showed the significant correlation between TRIMs expression and infiltration of innate immune cells (macrophages, neutrophils, and dendritic cells).

Conclusion

Our result provides novel insights into the function of TRIM family genes, which may be used as potential references for drug targets and accurate survival predictions in patients with HCC.

S-adenosylmethionine inhibits la ribonucleoprotein domain family member 1 in murine liver and human liver cancer cells

BACKGROUND AND AIMS

Methionine adenosyltransferase 1A (MAT1A) is responsible for S-adenosylmethionine (SAMe) biosynthesis in the liver. Mice lacking Mat1a have hepatic SAMe depletion and develop NASH and HCC spontaneously. Several kinases are activated in Mat1a knockout (KO) mice livers. However, characterizing the phospho-proteome and determining whether they contribute to liver pathology remain open for study. Our study aimed to provide this knowledge.

APPROACH AND RESULTS

We performed phospho-proteomics in Mat1a KO mice livers with and without SAMe treatment to identify SAMe-dependent changes that may contribute to liver pathology. Our studies used Mat1a KO mice at different ages treated with and without SAMe, cell lines, in vitro translation and kinase assays, and human liver specimens. We found that the most striking change was hyperphosphorylation and increased content of La-related protein 1 (LARP1), which, in the unphosphorylated form, negatively regulates translation of 5'-terminal oligopyrimidine (TOP)-containing mRNAs. Consistently, multiple TOP proteins are induced in KO livers. Translation of TOP mRNAs ribosomal protein S3 and ribosomal protein L18 was enhanced by LARP1 overexpression in liver cancer cells. We identified LARP1-T449 as a SAMe-sensitive phospho-site of cyclin-dependent kinase 2 (CDK2). Knocking down CDK2 lowered LARP1 phosphorylation and prevented LARP1-overexpression-mediated increase in translation. LARP1-T449 phosphorylation induced global translation, cell growth, migration, invasion, and expression of oncogenic TOP-ribosomal proteins in HCC cells. LARP1 expression is increased in human NASH and HCC.

CONCLUSIONS

Our results reveal a SAMe-sensitive mechanism of LARP1 phosphorylation that may be involved in the progression of NASH to HCC.

A novel machine learning derived RNA-binding protein gene-based score system predicts prognosis of hepatocellular carcinoma patients

Background

Although the expression of RNA-binding protein (RBP) genes in hepatocellular carcinoma (HCC) varies and is associated with tumor progression, there has been no overview study with multiple cohorts and large samples. The HCC-associated RBP genes need to be more accurately identified, and their clinical application value needs to be further explored.

Methods

First, we used the robust rank aggregation (RRA) algorithm to extract HCC-associated RBP genes from nine HCC microarray datasets and verified them in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and International Cancer Genome Consortium (ICGC) Japanese liver cancer (ICGC-LIRI-JP) cohort. In addition, the copy number variation (CNV), single-nucleotide variant (SNV), and promoter-region methylation data of HCC-associated RBP genes were analyzed. Using the random forest algorithm, we constructed an RBP gene–based prognostic score system (RBP-score). We then evaluated the ability of RBP-score to predict the prognosis of patients. The relationships between RBP-score and other clinical characteristics of patients were analyzed.

Results

The RRA algorithm identified 30 RBP mRNAs with consistent expression patterns across the nine HCC microarray datasets. These 30 RBP genes were defined as HCC-associated RBP genes. Their mRNA expression patterns were further verified in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Among these 30 RBP genes, some showed significant copy number gain or loss, while others showed differences in the methylation levels of their promoter regions. Some RBP genes were risk factors or protective factors for the prognosis of patients. We extracted 10 key HCC-associated RBP genes using the random forest algorithm and constructed an RBP-score system. RBP-score effectively predicted the overall survival (OS) and disease-free survival (DFS) of HCC patients and was associated with the tumor, node, metastasis (TNM) stage, α-fetoprotein (AFP), and metastasis risk. The clinical value of RBP-score was validated in datasets from different platforms. Cox analysis suggested that a high RBP-score was an independent risk factor for poor prognosis in HCC patients. We also successfully established a combined RBP-score+TNM LASSO-Cox model that more accurately predicted the prognosis.

Conclusion

The RBP-score system constructed based on HCC-associated RBP genes is a simple and highly effective prognostic evaluation tool. It is suitable for different subgroups of HCC patients and has cross-platform characteristics. Combining RBP-score with the TNM staging system or other clinical parameters can lead to an even greater clinical benefit. In addition, the identified HCC-associated RBP genes may serve as novel targets for HCC treatment.

HELLS Is Negatively Regulated by Wild-Type P53 in Liver Cancer by a Mechanism Involving P21 and FOXM1

Simple Summary

The tumor suppressor protein P53 is a major player in preventing liver cancer development and progression. In this study we could show that P53 negatively regulates the expression of Helicase, lymphoid specific (HELLS), previously described as an important pro-tumorigenic epigenetic regulator in hepatocarcinogenesis. The regulatory mechanism included induction of the P53 target gene P21 (CDKN1A) resulting in repression of HELLS via downregulation of the transcription factor Forkhead Box Protein M1 (FOXM1). Our in vitro and in vivo findings indicate an important additional aspect of the tumor suppressive function of P53 in liver cancer linked to epigenetic regulation.

Abstract

The major tumor suppressor P53 (TP53) acts primarily as a transcription factor by activating or repressing subsets of its numerous target genes, resulting in different cellular outcomes (e.g., cell cycle arrest, apoptosis and senescence). P53-dependent gene regulation is linked to several aspects of chromatin remodeling; however, regulation of chromatin-modifying enzymes by P53 is poorly understood in hepatocarcinogenesis. Herein, we identified Helicase, lymphoid specific (HELLS), a major epigenetic regulator in liver cancer, as a strong and selective P53 repression target within the SNF2-like helicase family. The underlying regulatory mechanism involved P53-dependent induction of P21 (CDKN1A), leading to repression of Forkhead Box Protein M1 (FOXM1) that in turn resulted in downregulation of HELLS expression. Supporting our in vitro data, we found higher expression of HELLS in murine HCCs arising in a Trp53−/− background compared to Trp53+/+ HCCs as well as a strong and highly significant correlation between HELLS and FOXM1 expression in different HCC patient cohorts. Our data suggest that functional or mutational inactivation of P53 substantially contributes to overexpression of HELLS in HCC patients and indicates a previously unstudied aspect of P53′s ability to suppress liver cancer formation.

MicroRNA target-based network predicts androgen receptor-linked mycotoxin stress

Stress-responsive microRNAs (miRNAs) contribute to the regulation of cellular homeostasis or pathological processes, including carcinogenesis, by reprogramming target gene expression following human exposure to environmental or dietary xenobiotics. Herein, we predicted the targets of carcinogenic mycotoxin-responsive miRNAs and analyzed their association with disease and functionality. miRNA target-derived prediction indicated potent associations of oncogenic mycotoxin exposure with metabolism- or hormone-related diseases, including sex hormone-linked cancers. Mechanistically, the signaling network evaluation suggested androgen receptor (AR)-linked signaling as a common pivotal cluster associated with metabolism- or hormone-related tumorigenesis in response to aflatoxin B1 and ochratoxin A co-exposure. Particularly, high levels of AR and AR-linked genes for the retinol and xenobiotic metabolic enzymes were positively associated with attenuated disease biomarkers and good prognosis in patients with liver or kidney cancers. Moreover, AR-linked signaling was protective against OTA-induced genetic insults in human hepatocytes whereas it was positively involved in AFB1-induced genotoxic actions. Collectively, miRNA target network-based predictions provide novel clinical insights into the progression or intervention against malignant adverse outcomes of human exposure to environmental oncogenic insults.

Network-based prioritization of cancer biomarkers by phenotype-driven module detection and ranking

This paper describes an ensemble method with supervised module detection and further module prioritization for reliable network-based biomarker discovery. We design a module detection and ranking method called mRank to discover reliable network modules as cancer diagnostic biomarkers, with two procedures: (1) an iterative supervised module detection guided by phenotypic states in a specific network, (2) a block-based module ranking locally and globally via network topological centrality. We validate its effectiveness and efficiency by identifying hepatocellular carcinoma (HCC) network modules on a comprehensive gene regulatory network with specifying gene interactions by HCC RNA-seq data from the Cancer Genome Atlas (TCGA). These top-ranked modules by mRank get a mean AUC of 0.995 on TCGA HCC dataset with 371 tumor samples and 50 controls by cross-validation SVM. Based on the prior knowledge of cancer dysfunctions enriched in top-ranked modules, 69 genes are identified as HCC candidate biomarkers. They are further validated in independent cohorts with a classifier trained on TCGA HCC dataset. A mean AUC of 0.846 is achieved in distinguishing 976 disease samples from 827 controls. Moreover, some known HCC signatures such as AFP and SPP1 are also included in our identified biomarkers. mRank enables us to find more reliable network modules for cancer diagnosis. For a proof-of-concept study, we validate it in identifying HCC network biomarkers and it is generalizable to other cancers or complex disease. The overall results have demonstrated that mRank can find effective network biomarkers for cancer diagnosis which result in less false positives.

Overexpressed GNAZ predicts poor outcome and promotes G0/G1 cell cycle progression in hepatocellular carcinoma

AIMS

We aimed to investigate the role of G protein subunit alpha Z(GNAZ) in the progression and prognosis of patients with hepatocellular carcinoma (HCC).

METHODS

Oncomine, GEO, TCGA, GEPIA2, Kaplan-Meier Plotter, TIMER2, Metascape, CCLE, LinkedOmics, and UALCAN databases were used to analyze the differential expression of GNAZ in HCC and normal liver tissues, relationship between GNAZ expression and prognosis of patients with HCC, and expression of GNAZ in common human HCC cell lines. Western blotting was performed to analyze GNAZ expression, while the Cell Counting Kit 8 assay was used to determine cell proliferation, and flow cytometry was used to evaluate the cell cycle and apoptosis. Wound healing and transwell invasion assays were used to investigate cell metastasis and invasion.

RESULTS

Using Oncomine, Gene Expression Omnibus (GEO), and GEPIA2 databases, GNAZ was found to be overexpressed in HCC tissues compared with that in adjacent normal liver tissues, and western blotting analysis showed GNAZ overexpression in seven patients with HCC who underwent surgical resection of HCC and para-cancerous tissues (p < 0.01). Survival analysis revealed that high GNAZ expression was negatively associated with overall survival (OS), recurrence-free survival, progression-free survival, and disease-specific survival in patients with HCC (p < 0.05). GNAZ overexpression was associated with worse 4- month, 6- month, 12- month, 24- month, 36- month, 48- month, and 60-month OS, as well as with different clinicopathological characteristics of patients with HCC, including hepatitis virus infection state; alcohol consumption state; male; female; Asian; microvascular invasion, Stage I-II, Stage II-III, and Stage III-IV; and grade II (Cox regression, p < 0.05). KEGG/GO biological process enrichment indicated that the genes similar to GNAZ in HCC were mainly enriched in the cell cycle, cell cycle phase transition, DNA replication checkpoint, and regulation of G0 to G1 transition. siRNA-GNAZ significantly reduced the viability of JHH-2 and SNU-761 cells from 12 to 96 h; increased the percentage of cells in the G0/G1 phase and decreased that of cells in the S and G2/M phases (p < 0.05); and markedly downregulated the expression of cyclin D, cyclin E, and CDK2 protein. siRNA-GNAZ also significantly increased the percentage of JHH-2 and SNU-761 cell apoptosis at late stages, while the number of surviving cells decreased (p < 0.05), and upregulated the expression of apoptosis-related proteins Bax and caspase 3 protein. Furthermore, siRNA-GNAZ remarkably reduced the healing of scratch wounds in JHH-2 and SNU-761 cells and the number of invasive cells compared with that in the control group (p < 0.001).

CONCLUSION

Our study demonstrated that GNAZ plays a pivotal role as a potential oncogene and predicts poor prognosis in patients with HCC. It promotes tumor proliferation via cell cycle arrest, apoptosis, migration, and invasion. Thus, GNAZ may be a potential candidate biomarker providing useful insight into hepatocarcinogenesis and aggressiveness.

Comprehensive Pan-Cancer Genomic Analysis Reveals PHF19 as a Carcinogenic Indicator Related to Immune Infiltration and Prognosis of Hepatocellular Carcinoma

BACKGROUND

As a crucial constituent part of Polycomb repressive complex 2, PHD finger protein 19 (PHF19) plays a pivotal role in epigenetic regulation, and acts as a critical regulator of multiple pathophysiological processes. However, the exact roles of PHF19 in cancers remain enigmatic. The present research was primarily designed to provide the prognostic landscape visualizations of PHF19 in cancers, and study the correlations between PHF19 expression and immune infiltration characteristics in tumor microenvironment.

METHODS

Raw data in regard to PHF19 expression were extracted from TCGA and GEO data portals. We examined the expression patterns, prognostic values, mutation landscapes, and protein-protein interaction network of PHF19 in pan-cancer utilizing multiple databases, and investigated the relationship of PHF19 expression with immune infiltrates across TCGA-sequenced cancers. The R language was used to conduct KEGG and GO enrichment analyses. Besides, we built a risk-score model of hepatocellular carcinoma (HCC) and validated its prognostic classification efficiency.

RESULTS

On balance, PHF19 expression was significantly higher in cancers in comparison with that in noncancerous samples. Increased expression of PHF19 was detrimental to the clinical prognoses of cancer patients, especially HCC. There were significant correlations between PHF19 expression and TMB or MSI in several cancers. High PHF19 levels were critically associated with the infiltration of myeloid-derived suppressor cells (MDSCs) and Th2 subsets of CD4+ T cells in most cancers. Enrichment analyses revealed that PHF19 participated in regulating carcinogenic processes including cell cycle and DNA replication, and was correlated with the progression of HCC. Intriguingly, GSEA suggested that PHF19 was correlated with the cellular components including immunoglobulin complex and T cell receptor complex in HCC. Based on PHF19-associated functional gene sets, an eleven-gene prognostic signature was constructed to predict HCC prognosis. Finally, we validated pan-cancer PHF19 expression, and its impacts on immune infiltrates in HCC.

CONCLUSION

The epigenetic related regulator PHF19 participates in the carcinogenic progression of multiple cancers, and may contribute to the immune infiltration in tumor microenvironment. Our study suggests that PHF19 can serve as a carcinogenic indicator related to prognosis in pan-cancer, especially HCC, and shed new light on therapeutics of cancers for clinicians.

A metabolism-associated gene signature for prognosis prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the most frequently occurring type of cancer, is strongly associated with metabolic disorders. In this study, we aimed to characterize the metabolic features of HCC and normal tissue adjacent to the tumor (NAT). By using samples from The Cancer Genome Atlas (TCGA) liver cancer cohort and comparing 85 well-defined metabolic pathways obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG), 70 and 7 pathways were found to be significantly downregulated and upregulated, respectively, in HCC, revealing that tumor tissue lacks the ability to maintain normal metabolic levels. Through unsupervised hierarchical clustering of metabolic pathways, we found that metabolic heterogeneity correlated with prognosis in HCC samples. Thus, using the least absolute shrinkage and selection operator (LASSO) and filtering independent prognostic genes by the Cox proportional hazards model, a six-gene-based metabolic score model was constructed to enable HCC classification. This model showed that high expression of LDHA and CHAC2 was associated with an unfavorable prognosis but that high ADPGK, GOT2, MTHFS, and FTCD expression was associated with a favorable prognosis. Patients with higher metabolic scores had poor prognoses (p value = 2.19e-11, hazard ratio = 3.767, 95% CI = 2.555-5.555). By associating the score level with clinical features and genomic alterations, it was found that NAT had the lowest metabolic score and HCC with tumor stage III/IV the highest. qRT‒PCR results for HCC patients also revealed that tumor samples had higher score levels than NAT. Regarding genetic alterations, patients with higher metabolic scores had more TP53 gene mutations than those with lower metabolic scores (p value = 8.383e-05). Validation of this metabolic score model was performed using another two independent HCC cohorts from the Gene Expression Omnibus (GEO) repository and other TCGA datasets and achieved good performance, suggesting that this model may be used as a reliable tool for predicting the prognosis of HCC patients.

mRNAsi-related genes can effectively distinguish hepatocellular carcinoma into new molecular subtypes

Background

Recent studies have shown that the mRNA expression-based stemness index (mRNAsi) can accurately quantify the similarity of cancer cells to stem cells, and mRNAsi-related genes are used as biomarkers for cancer. However, mRNAsi-driven tumor heterogeneity is rarely investigated, especially whether mRNAsi can distinguish hepatocellular carcinoma (HCC) into different molecular subtypes is still largely unknown.

Methods

Using OCLR machine learning algorithm, weighted gene co-expression network analysis, consistent unsupervised clustering, survival analysis and multivariate cox regression etc. to identify biomarkers and molecular subtypes related to tumor stemness in HCC.

Results

We firstly demonstrate that the high mRNAsi is significantly associated with the poor survival and high disease grades in HCC. Secondly, we identify 212 mRNAsi-related genes that can divide HCC into three molecular subtypes: low cancer stemness cell phenotype (CSCP-L), moderate cancer stemness cell phenotype (CSCP-M) and high cancer stemness cell phenotype (CSCP-H), especially over-activated ribosomes, spliceosomes and nucleotide metabolism lead to the worst prognosis for the CSCP-H subtype patients, while activated amino acids, fatty acids and complement systems result in the best prognosis for the CSCP-L subtype. Thirdly, we find that three CSCP subtypes have different mutation characteristics, immune microenvironment and immune checkpoint expression, which may cause the differential prognosis for three subtypes. Finally, we identify 10 robust mRNAsi-related biomarkers that can effectively predict the survival of HCC patients.

Conclusions

These novel cancer stemness-related CSCP subtypes and biomarkers in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy of HCC patients.

Identification of HnRNP Family as Prognostic Biomarkers in Five Major Types of Gastrointestinal Cancer

BACKGROUND

Heterogeneous nuclear ribonucleoproteins (hnRNPs), a large family of RNAbinding proteins, have been implicated in tumor progression in multiple cancer types. However, the expression pattern and prognostic value of hnRNPs in five gastrointestinal (GI) cancers, including gastric, colorectal, esophageal, liver, and pancreatic cancer, remain to be investigated.

OBJECTIVE

The current research aimed to identify prognostic biomarkers of the hnRNP family in five major types of gastrointestinal cancer.

METHODS

Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), and Kaplan-Meier Plotter were used to explore the hnRNPs expression levels concerning clinicopathological parameters and prognostic values. The protein level of hnRNPU was validated by immunohistochemistry (IHC) in human tissue specimens. Genetic alterations of hnRNPs were analyzed using cBioportal, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to illustrate the biological functions of co-expressed genes of hnRNPs.

RESULTS

The vast majority of hnRNPs were highly expressed in five types of GI cancer tissues compared to their adjacent normal tissues, and mRNA levels of hnRNPA2B1, D, Q, R, and U were significantly different in various GI cancer types at different stages. In addition, Kaplan-Meier analysis revealed that the increased hnRNPs expression levels were correlated with better prognosis in gastric and rectal cancer patients (log-rank p < 0.05). In contrast, patients with high levels of hnRNPs exhibited a worse prognosis in esophageal and liver cancer (log-rank p < 0.05). Using immunohistochemistry, we further confirmed that hnRNPU was overexpressed in gastric, rectal, and liver cancers. In addition, hnRNPs genes were altered in patients with GI cancers, and RNA-related processing was correlated with hnRNPs alterations.

CONCLUSION

We identified differentially expressed genes of hnRNPs in tumor tissues versus adjacent normal tissues, which might contribute to predicting tumor types, early diagnosis, and targeted therapies in five major types of GI cancer.

FTH promotes the proliferation and renders the HCC cells specifically resist to ferroptosis by maintaining iron homeostasis

Background

Ferroptosis is a newly identified type of programmed cell death, which preferentially targets iron-rich cancer cells such as hepatocellular carcinoma (HCC). Ferritin heavy chain (FTH) is a major iron storing nanocage to store redox-inactive iron, and harbors ferroxidase activity to prevent the iron-mediated production of ROS. Our previous studies have demonstrated that FTH acts as a protective role to increase the cellular resistance to ferroptosis. However, the specific role of FTH in the development of HCC and ferroptosis resistance remains unclear.

Methods

The indicated databases were used for bioinformatics analysis. The abilities of cell proliferation, migration were measured by cell proliferation assay, transwell assay and wound healing assay. The levels of reactive oxygen species (ROS), lipid peroxide, free iron, mitochondrial superoxide, mitochondrial morphology and mitochondrial membrane potential (MMP) were determined by DCF-DA, C11-BODIPY, mitoSOX, mitoTracker, JC-10 and TMRM staining, respectively. The mitochondrial oxygen consumption rate was monitored by the Seahorse XF24 Analyzer.

Results

The pan-cancer analysis was performed and showed that FTH expression is upregulated in multiple cancers, such as LIHC, CHOL, HNSC, compared to corresponding normal tissues. In addition, the level of serum ferritin is positively associated with the progression of hepatitis, cirrhosis liver and hepatocellular carcinoma. Further investigation shed light on the strong correlation between FTH expression and tumor grades, cancer stages and prognosis of HCC. Importantly, the proteins interaction network elucidated that FTH is involved in iron homeostasis maintenance and lysosomal-dependent degradation. Enforced expression of FTH accelerates proliferation, migration and endows HCC cells specifically resistant to ferroptosis, but does not protect against cell death caused by cytotoxic compounds like oxaliplatin, irinotecan, and adriamycin. Mechanically, FTH reconstituted cells exhibit diminished peroxides accumulation, reduce mitochondrial ROS level, attenuate the impaired mitochondrial respiratory and rescue the mitochondrial homeostasis. Notably, FTH expression boosts tumorigenic potential in vivo with increased PCNA staining and lesser lipid peroxides generation.

Conclusion

These results provide new insights that FTH acts as an oncogene in the carcinogenesis and progression of HCC, and is hopeful to be a potential target for therapeutic intervention through ferroptosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02420-x.

Development of an Eight-gene Prognostic Model for Overall Survival Prediction in Patients with Hepatocellular Carcinoma

BACKGROUND AND AIMS

The overall survival (OS) of hepatocellular carcinoma (HCC) remains dismal. Bioinformatic analysis of transcriptome data could identify patients with poor OS and may facilitate clinical decision. This study aimed to develop a prognostic gene model for HCC.

METHODS

GSE14520 was retrieved as a training set to identify differential expressed genes (DEGs) between tumor and adjacent liver tissues in HCC patients with different OS. A DEG-based prognostic model was then constructed and the TCGA-LIHC and ICGC-LIRI datasets were used to validate the model. The area under the receiver operating characteristic curve (AUC) and hazard ratio (HR) of the model for OS were calculated. A model-based nomogram was established and verified.

RESULTS

In the training set, differential expression analysis identified 80 genes dysregulated in oxidation-reduction and metabolism regulation. After univariate Cox and LASSO regression, eight genes (LPCAT1, DHRS1, SORBS2, ALDH5A1, SULT1C2, SPP1, HEY1 and GOLM1) were selected to build the prognostic model. The AUC for 1-, 3- and 5-year OS were 0.779, 0.736, 0.754 in training set and 0.693, 0.689, 0.693 in the TCGA-LIHC validation set, respectively. The AUC for 1- and 3-year OS were 0.767 and 0.705 in the ICGC-LIRI validation set. Multivariate analysis confirmed the model was an independent prognostic factor (training set: HR=4.422, p<0.001; TCGA-LIHC validation set: HR=2.561, p<0.001; ICGC-LIRI validation set: HR=3.931, p<0.001). Furthermore, a nomogram combining the model and AJCC stage was established and validated, showing increased OS predictive efficacy compared with the prognostic model (p=0.035) or AJCC stage (p<0.001).

CONCLUSIONS

Our eight-gene prognostic model and the related nomogram represent as reliable prognostic tools for OS prediction in HCC patients.

Identification of Therapeutic Targets and Prognostic Biomarkers Among Chemokine (C-C Motif) Ligands in the Liver Hepatocellular Carcinoma Microenvironment

Background: Liver hepatocellular carcinoma (LIHC) is the third leading cause of cancer-related death and the sixth most common solid tumor worldwide. In the tumor microenvironment, the cross-talk between cancer cells, immune cells, and stromal cells exerts significant effects on neoplasia and tumor development and is modulated in part by chemokines. Chemokine (C-C motif) ligands (CCL) can directly target tumor cells and stromal cells, and they have been shown to regulate tumor cell proliferation, cancer stem-like cell properties, cancer invasiveness and metastasis, which directly and indirectly affect tumor immunity and influence cancer progression, therapy and patient outcomes. However, the prognostic values of chemokines CCL in LIHC have not been clarified.

Methods: In this study, we comprehensively analyzed the relationship between transcriptional chemokines CCL and disease progression of LIHC using the ONCOMINE dataset, GEPIA, UALCAN, STRING, WebGestalt, GeneMANIA, TRRUST, DAVID 6.8, LinkedOmics, TIMER, GSCALite, and Open Targets. We validated the protein levels of chemokines CCL through western blot and immunohistochemistry.

Results: The transcriptional levels of CCL5/8/11/13/15/18/20/21/25/26/27/28 in LIHC tissues were significantly elevated while CCL2/3/4/14/23/24 were significantly reduced. A significant correlation was found between the expression of CCL14/25 and the pathological stage of LIHC patients. LIHC patients with low transcriptional levels of CCL14/21 were associated with a significantly poor prognosis. The functions of differentially expressed chemokines CCL were primarily related to the chemokine signaling pathway, cytokine–cytokine receptor interactions, and TNF-α signaling pathway. Our data suggested that RELA/REL, NFKB1, STAT1/3/6, IRF3, SPI1, and JUN were key transcription factors for chemokines CCL. We found significant correlations among the expression of chemokines CCL and the infiltration of six types of immune cells (B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells) and immune checkpoints (PD-1. PD-L1, and CTLA-4). The western blot and immunohistochemistry results showed that protein expression levels of CCL5 and CCL20 were upregulated in LIHC. CCL5 and CCL20 were significantly correlated with the clinical outcome of patients with LIHC, and could be negatively regulated by some drugs or small molecules.

Conclusions: Our results may provide novel insights for the potential suitable targets of immunological therapy and prognostic biomarkers for LIHC.

General Features and Novel Gene Signatures That Identify Epstein-Barr Virus-Associated Epithelial Cancers

Epstein-Barr virus (EBV) is associated with various types of human malignancies, including nasopharyngeal carcinoma (NPC), EBV-associated gastric carcinoma (EBVaGC), and oral squamous cell carcinoma (OSCC). The present study aimed to identify gene signatures and common signaling pathways that can be used to predict the prognosis of EBV-associated epithelial cancers (EBVaCAs) by performing an integrated bioinformatics analysis of cell lines and tumor tissues. We identified 12 differentially expressed genes (DEGs) in the EBVaCA cell lines. Among them, only four DEGs, including BAMBI, SLC26A9, SGPP2, and TMC8, were significantly upregulated. However, SLC26A9 and TMC8, but not BAMBI and SGPP2, were significantly upregulated in EBV-positive tumor tissues compared to EBV-negative tumor tissues. Next, we identified IL6/JAK/STAT3 and TNF-α/NF-κB signaling pathways as common hallmarks of EBVaCAs. The expression of key genes related to the two hallmarks was upregulated in both EBV-infected cell lines and EBV-positive tumor tissues. These results suggest that SLC26A9 and TMC8 might be gene signatures that can effectively predict the prognosis of EBVaCAs and provide new insights into the molecular mechanisms of EBV-driven epithelial cancers.

Prognostic biomarker SMARCC1 and its association with immune infiltrates in hepatocellular carcinoma

Background

Epigenetic alterations contribute greatly to metastasis and dissemination in hepatocellular carcinoma (HCC). SMARCC1, as a SWI/SNF chromatin remodeling factor, has been reported to play important roles in many cancers. For the first time, with the bioinformatics analysis and wet-bench experiments, we explored the biological significance of SMARCC1 and its potential as putative therapeutic target in HCC.

Methods

The mRNA expression profiles and prognostic value of SMARCC1 were analyzed in the Oncomine, UALCAN and Kaplan–Meier Plotter databases. The expression of SMARCC1 and associated clinicopathological factors were further evaluated using a tissue microarray. Differentially expressed genes associated with SMARCC1 in HCC were obtained and analyzed via the LinkedOmics and GEPIA databases and Cytoscape software. To verify the important role of SMARCC1 in HCC, we knocked down and overexpressed SMARCC1 in different hepatic cell lines and conducted several functional experiments. Then, we evaluated the mutation profiles and transcriptional regulators of SMARCC1 using the cBioPortal, COSMIC, CistromeDB and TCGA databases. Finally, we addressed the relationship of SMARCC1 expression with immune cell infiltration via TIMER database analysis.

Results

Through data mining and tissue microarray verification, we found that the protein and mRNA levels of SMARCC1 are high in tumor tissues, which has remarkable diagnostic value in HCC patients. SMARCC1 and its hub genes showed prognostic value in HCC. Furthermore, we confirmed that SMARCC1 influenced the proliferation, migration, and invasion of HCC cells. Moreover, correlation analyses revealed that SMARCC1 expression was positively correlated with ZBTB40 transcription factors and negatively correlated with the DNA methylation level. Overall, we found that SMARCC1 affects immune infiltration and plays a tumor-promoting role in HCC.

Conclusions

SMARCC1 is overexpressed and is a putative prognostic predictor in HCC. Due to the tumor-promoting role of SMARCC1, treatments inhibiting DNA methyltransferases and transcription factors or weakening the role of SMARCC1 in immune infiltration might improve the survival of HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02413-w.

SPARC Overexpression Promotes Liver Cancer Cell Proliferation and Tumor Growth

Background: Secreted protein acidic and rich in cysteine (SPARC) plays an important role in cancer development. The roles of SPARC in the liver hepatocellular carcinoma (LIHC) are unclear. Methods: GEPIA2 and UALCAN were used to analyze the SPARC mRNA expression levels in LIHC based on the TCGA database. The GEO database was used to verify the analysis results. Immunohistochemical (IHC) analysis was used to investigate the SPARC protein levels in LIHC tissues. The Kaplan-Meier (KM) plotter was used to analyze the correlation between SPARC and prognosis. The serum SPARC levels were measured by ELISA. CCK8 and murine xenograft models were used to investigate the effect of SPARC on the liver cancer growth in vitro and in vivo. SPARC-correlated genes were screened by LinkedOmics. Results: Based on the TCGA and GEO databases, the analysis showed that the SPARC mRNA expression levels were increased in tumor tissues and peripheral blood mononuclear cell (PBMC) from LIHC compared to normal controls. The IHC analysis showed an increased level of SPARC in LIHC tissues compared to adjacent non-tumor tissues. However, we found that the serum SPARC levels were lower in LIHC than those in healthy controls. The KM plotter showed that there was no significant correlation between the SPARC mRNA levels and overall survival. However, in sorafenib-treated LIHC patients, the high SPARC expression predicts favorable prognosis. Furthermore, the endogenous SPARC overexpression promotes liver cancer cell proliferation in vitro and tumor growth in vivo, while there was no significant effect of exogenous SPARC treatment on liver cancer cell proliferation. Function enrichment analysis of SPARC-correlated genes indicated a critical role of interaction with an extracellular matrix in SPARC-promoting cancer cell proliferation. Conclusion: SPARC mRNAs were increased in LIHC tumor tissues, and SPARC overexpression may promote the liver cancer growth. Further studies are needed to clarify the potential prognostic value of SPARC, both in tissues and in circulation.

Comprehensive analysis of spatial architecture in primary liver cancer

Heterogeneity is the major challenge for cancer prevention and therapy. Here, we first constructed high-resolution spatial transcriptomes of primary liver cancers (PLCs) containing 84,823 spots within 21 tissues from seven patients. The progressive comparison of spatial tumor microenvironment (TME) characteristics from nontumor to leading-edge to tumor regions revealed that the tumor capsule potentially affects intratumor spatial cluster continuity, transcriptome diversity, and immune cell infiltration. Locally, we found that the bidirectional ligand-receptor interactions at the 100-μm-wide cluster-cluster boundary contribute to maintaining intratumor architecture and the PROM1⁺ and CD47⁺ cancer stem cell niches are related to TME remodeling and tumor metastasis. Last, we proposed a TLS-50 signature to accurately locate tertiary lymphoid structures (TLSs) spatially and unveiled that the distinct composition of TLSs is shaped by their distance to tumor cells. Our study provides previous unknown insights into the diverse tumor ecosystem of PLCs and has potential benefits for cancer intervention.

Expression and Clinical Significance of MPS-1 in Hepatocellular Carcinoma

Purpose

Ribosomal protein metallopanstimulin-1 (MPS-1) is implicated in tumorigenesis. However, to date, the underlying role of MPS-1 in the generation, progression and prognosis of hepatocellular carcinoma (HCC) remains unknown. This study aims to investigate the expression of MPS-1 in HCC and its significance for the prognosis of HCC.

Methods

The Oncomine and GEPIA databases were used to analyze the expression pattern of MPS-1 in HCC. Immunohistochemical staining was performed on tissue microarrays containing 169 HCC tissue samples to examine the expression of MPS-1. In addition, univariate and multivariate Cox regression analyses and Kaplan-Meier analysis were used to verify the correlation between clinicopathological factors in HCC patients and its clinical prognostic significance.

Results

MPS-1 was more highly expressed in HCC than in normal tissues, and MPS-1 expression was correlated with serum AFP levels (P = 0.003), liver cirrhosis (P = 0.024), tumor embolus (P = 0.009) and tumor recurrence (P < 0.003). MPS-1 was an independent prognostic factor for the overall survival of HCC (HR, 1.92; 95% CI, 1.01-3.68), and a higher expression of MPS-1 predicted poorer survival. Furthermore, high expression of MPS-1 indicated a poor prognosis in patients with AFP positivity, cirrhosis or HBsAg positivity.

Conclusion

These findings demonstrate that MPS-1 is highly expressed in HCC and serves as an independent prognostic marker, highlighting the potential role of MPS-1 as a novel biomarker and therapeutic target for HCC.

Role of CD5L and SRD5A2 as Prognostic Biomarkers for Hepatocellular Carcinoma

Purpose

Due to the limitations of currently available biomarkers, new biomarkers are needed to accurately predict the prognosis of patients with hepatocellular carcinoma (HCC) patients.

Methods

In this study, we screened for differentially expressed genes (DEGs) in the tumor and the adjacent tissues using the four gene expression array (GSE14520, GSE45267, GSE121248, GSE62232) of the Gene Express Omnibus (GEO) database.

Results

Subsequently, 47 overlapping DEGs were identified in four GEO datasets, which were mostly located on chromosomes 5q and 6q, distributed in the liver and CD105-positive endothelial cells, and closely related to HCC. Function enrichment revealed 47 DEGs were related to HCC, and involved in steroid /lipid /retinol metabolism, bile secretion and p53 signalling pathway. The Kaplan–Meier plotter analysis (http://www.kmplot.com/) identified 26 and 40 genes associated with the 5-year overall survival (OS) and relapse-free survival (RFS). We found that CD5L and SRD5A2 were independent prognostic factors for 5-year OS (P=0.036) and RFS (P=0.044) in HCC patients from GSE14520, respectively. Clinicopathological features including BCLC stage, cirrhosis, and risk signature for predicted metastasis were used to construct and validate a nomogram for 5-year OS with C-index of 0.732 and 0.717 in the training and validation cohort, respectively. SRD5A2, BCLC stage and gender was independent prognostic factors for RFS which were used to build a nomogram with the C-index of 0.666 and 0.682 in the training and validation cohort, respectively.

Conclusion

CD5L can facilitate individualized, targeted therapy for HCC patients.

Establishment and Validation of an MTORC1 Signaling-Related Gene Signature to Predict Overall Survival in Patients with Hepatocellular Carcinoma

Background

Accurate and effective biomarkers for the prognosis of patients with hepatocellular carcinoma (HCC) are poorly identified. A network-based gene signature may serve as a valuable biomarker to improve the accuracy of risk discrimination in patients.

Methods

The expression levels of cancer hallmarks were determined by Cox regression analysis. Various bioinformatic methods, such as GSEA, WGCNA, and LASSO, and statistical approaches were applied to generate an MTORC1 signaling-related gene signature (MSRS). Moreover, a decision tree and nomogram were constructed to aid in the quantification of risk levels for each HCC patient.

Results

Active MTORC1 signaling was found to be the most vital predictor of overall survival in HCC patients in the training cohort. MSRS was established and proved to hold the capacity to stratify HCC patients with poor outcomes in two validated datasets. Analysis of the patient MSRS levels and patient survival data suggested that the MSRS can be a valuable risk factor in two validated datasets and the integrated cohort. Finally, we constructed a decision tree which allowed to distinguish subclasses of patients at high risk and a nomogram which could accurately predict the survival of individuals.

Conclusions

The present study may contribute to the improvement of current prognostic systems for patients with HCC.

Hippo signaling suppresses tumor cell metastasis via a Yki-Src42A positive feedback loop

Metastasis is an important cause of death from malignant tumors. It is of great significance to explore the molecular mechanism of metastasis for the development of anti-cancer drugs. Here, we find that the Hippo pathway hampers tumor cell metastasis in vivo. Silence of hpo or its downstream wts promotes tumor cell migration in a Yki-dependent manner. Furthermore, we identify that inhibition of the Hippo pathway promotes tumor cell migration through transcriptional activating src42A, a Drosophila homolog of the SRC oncogene. Yki activates src42A transcription through direct binding its intron region. Intriguingly, Src42A further increases Yki transcriptional activity to form a positive feedback loop. Finally, we show that SRC is also a target of YAP and important for YAP to promote the migration of human hepatocellular carcinoma cells. Together, our findings uncover a conserved Yki/YAP-Src42A/SRC positive feedback loop promoting tumor cell migration and provide SRC as a potential therapeutic target for YAP-driven metastatic tumors.

Identification of hepatocellular carcinoma-related genes associated with macrophage differentiation based on bioinformatics analyses

Macrophage differentiation is associated with tumorigenesis, including the tumorigenesis of hepatocellular carcinoma (HCC). Herein, we explored the value of macrophage differentiation-associated genes (MDGs) in the prognosis of HCC using data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. We performed multivariate Cox regression analyses to identify the hub genes affecting HCC patient prognoses. The correlations between hub genes and macrophage differentiation and immune checkpoint inhibitors (PD-1, PD-L1, and CTLA4) were investigated. Finally, the potential mechanism was examined with gene set enrichment analysis (GSEA). In total, seventeen differentially expressed MDGs were obtained after intersecting data from the two databases. Multivariate analysis indicated that CDC42 expression was an independent prognostic indicator in both databases. Furthermore, CDC42 showed a strong correlation with the tumor infiltration levels of immune cells in HCC tissue. Correlation analysis revealed that CDC42 expression was positively associated with M2 macrophage markers and immune checkpoint inhibitors, which indicated that CDC42 expression might be related to M2 macrophage differentiation and HCC cell immune tolerance. Finally, GSEA showed that CDC42 expression was most significantly related to the Wnt signaling pathway. In conclusion, this study showed that CDC42 expression might be an important MDG in HCC and may prove to be a new gene for studying macrophage differentiation in HCC. Abbreviations: HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; ICGC: International Cancer Genome Consortium; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; TNM: Tumor size/lymph nodes/distance metastasis.

Pan-cancer analysis of clinical significance and associated molecular features of glycolysis

Tumor glycolysis is a major promoter of carcinogenesis and cancer progression. Given its complex mechanisms and interactions, comprehensive analysis is needed to reveal its clinical significance and molecular features. On the basis of a well-established glycolysis gene expression signature, we quantified 8633 patients with different cancer types from the Cancer Genome Atlas (TCGA) and evaluated their prognostic associations. High tumor glycolytic activity correlated with inferior overall survival in the pan-cancer patients (hazard ratio: 1.70, 95% confidence interval: 1.20-2.40, P = 0.003). The prognostic value of glycolysis correlated with the molecular subtypes and was stable regardless of clinical parameters. The prognostic significance of glycolysis was validated using three independent datasets. In addition, genome, transcriptome, and proteome profiles were utilized to characterize the distinctive molecular features associated with glycolysis. Mechanistically, glycolysis fulfilled the fundamental needs of tumor proliferation in multiple ways. Exploration of the relationships between glycolysis and tumor-infiltrating immune cells showed that glycolysis enabled the immune evasion of tumor cells. Mammalian target of rapamycin (mTOR) inhibitors and dopamine receptor antagonists can effectively reverse the glycolytic status of cancers. Overall, our study provides an in-depth molecular understanding of tumor glycolysis and may have practical implications for clinical cancer therapy.

YAP-induced Ccl2 expression is associated with a switch in hepatic macrophage identity and vascular remodelling in liver cancer

BACKGROUND & AIM

The development of hepatocellular carcinoma (HCC) is associated with the formation of communication networks leading to the recruitment of disease-modifying macrophages. However, how oncogenes in tumour cells control paracrine communication is not fully understood.

METHODS

Transgenic mice with liver-specific expression of the constitutively active yes-associated protein (YAP^S127A ) or an orthotopic implantation model served as tumour models. FACS-sorted F4/80⁺ /CD11b^dim /CD146^- /retinoid^- macrophages from healthy and tumour-bearing livers were used for transcriptomic profiling. Expression data of 242 human HCCs and a tissue microarray consisting of 91 HCCs and seven liver tissues were analyzed.

RESULTS

Screening of primary tumour cells expressing YAP^S127A identified CC chemokine ligand 2 (Ccl2) as a macrophage chemoattractant, whose expression was regulated in a YAP/TEA domain family member 4 (TEAD4)-dependent manner. Ccl2 expression was associated with a loss of Kupffer cells (KCs) and an increase in immature macrophages (Mɸ^imm ) in hepatocarcinogenesis. Recruited Mɸ^imm were characterized by a lack of functional polarization (M0 signature) and high expression of the Ccl2 receptors C-C motif chemokine receptor 2 (Ccr2), C-X3-C motif chemokine receptor 1 (Cx3cr1) and pro-angiogenic platelet-derived growth factors (Pdgfa/Pdgfb). Mɸ^imm formed cellular clusters in the perivascular space, which correlated with vascular morphometric changes indicative for angiogenesis. In human HCCs, the M0 signature served as an identifier for poor clinical outcome and CCL2 correlated with YAP expression and vascular network formation.

CONCLUSIONS

In conclusion, YAP/TEAD4-regulated Ccl2 associates with perivascular recruitment of unpolarized Mɸ^imm and may contribute to a proangiogenic microenvironment in liver cancer.

Development of an Autophagy-Based and Stemness-Correlated Prognostic Model for Hepatocellular Carcinoma Using Bulk and Single-Cell RNA-Sequencing

Accumulating evidence has proved that autophagy serves as a tumor promoter in formed malignancies, and the autophagy-related prognostic signatures have been constructed as clinical tools to predict prognosis in many high-mortality cancers. Autophagy-related genes have participated in the development and metastasis of hepatocellular carcinoma (HCC), but the understanding of their prognostic value is limited. Thereafter, LIMMA and survival analysis were conducted in both ICGC and TCGA databases and a total of 10 hub autophagy-related genes, namely, NPC1, CDKN2A, RPTOR, SPHK1, HGS, BIRC5, SPNS1, BAK1, ATIC, and MAPK3, were collected. Then, GO, KEGG, correlation, consensus, and PCA analyses were utilized to reveal their potential targeted role in HCC treatment. Single-cell RNA-seq of cancer stem cells also indicated that there was a positive correlation between these genes and stemness. In parallel, we applied univariate, LASSO, and multivariate regression analyses to study the autophagy-related genes and finally proposed that ATIC and BIRC5 were the valuable prognostic indicators of HCC. The signature based on ATIC and BIRC5 exhibited moderate power for predicting the survival of HCC in the ICGC cohort, and its efficacy was further validated in the TCGA cohort. Taken together, we suggested that 10 aforementioned hub genes are promising therapeutic targets of HCC and the ATIC/BIRC5 prognostic signature is a practical prognostic indicator for HCC patients.

Survivin-positive circulating tumor cells as a marker for metastasis of hepatocellular carcinoma

BACKGROUND

Circulating tumor cells (CTCs) and survivin are indicators for tumor stage and metastasis, as well as epitheliomesenchymal transition, in various cancers, including hepatocellular cancer (HCC).

AIM

To explore the potential of survivin-positive CTCs, specifically, as a marker for tumor progression in HCC patients.

METHODS

We examined the survivin expression pattern in CTCs obtained from 179 HCC patients, and investigated the in vitro effects of survivin silencing and overexpression on the proliferation and invasion of HCC cells. CTC count and survivin expression in patient samples were examined using RNA in situ hybridization.

RESULTS

All 179 patients were positive for CTC markers, and 94.41% of the CTCs were positive for survivin. The CTC and survivin-positive CTC counts were significantly higher in the HCC patients than in the normal controls, and were significantly associated with tumor stage and degree of differentiation. Further, survivin overexpression was found to induce HepG2 cell proliferation, reduce apoptosis, and improve invasive ability.

CONCLUSION

Survivin shows upregulated expression (indicative of anti-apoptotic effects) in HCC. Thus, survivin-positive CTCs are promising as a predictor of HCC prognosis and metastasis, and their accurate measurement may be useful for the management of this cancer.

Bioinformatics Analysis Identifies Precision Treatment with Paclitaxel for Hepatocellular Carcinoma Patients Harboring Mutant TP53 or Wild-Type CTNNB1 Gene

Hepatocellular carcinoma (HCC) is an aggressive and chemoresistant cancer type. The development of novel therapeutic strategies is still urgently needed. Personalized or precision medicine is a new trend in cancer therapy, which treats cancer patients with specific genetic alterations. In this study, a gene signature was identified from the transcriptome of HCC patients, which was correlated with the patients’ poorer prognoses. This gene signature is functionally related to mitotic cell cycle regulation, and its higher or lower expression is linked to the mutation in tumor protein p53 (TP53) or catenin beta 1 (CTNNB1), respectively. Gene–drug association analysis indicated that the taxanes, such as the clinically approved anticancer drug paclitaxel, are potential drugs targeting this mitotic gene signature. Accordingly, HCC cell lines harboring mutant TP53 or wild-type CTNNB1 genes are more sensitive to paclitaxel treatment. Therefore, our results imply that HCC patients with mutant TP53 or wild-type CTNNB1 genes may benefit from the paclitaxel therapy.

Identification of chloride intracellular channels as prognostic factors correlated with immune infiltration in hepatocellular carcinoma using bioinformatics analysis

ABSTRACT

Chloride intracellular channel (CLIC) proteins are novel Cl-channels with 6 family members (CLIC1-6) that are known to play crucial roles in multiple physiological functions, such as neurological, cardiovascular, pulmonary, and auditory functions, and in various malignancies, including hepatocellular carcinoma (HCC). However, considerable challenges exist in identifying appropriate CLICs as therapeutic target molecules and prognostic biomarkers for HCC because the transformation of soluble or integral membrane protein forms, and specific pharmacological agents (agonists and antagonists) for distinct CLICs remains enigmatic.To address this issue and the possible molecular basis and the signaling networks activated by CLICs in HCC, we examined the transcriptional, promoter methylation, DNA mutation, survival, and immune infiltration data of CLICs in patients with HCC using the ONCOMINE, UALCAN, GEPIA, cBioPortal, and TIMER databases.The data showed that the expression levels of CLIC family members were differed between tumor and normal tissues. High expression levels of CLIC1 and CLIC3 were associated with advanced cancer stage in HCC patients. Low CLIC1 expression was associated with a better overall survival (OS). The DNA methylation levels of the CLIC1-3 and CLIC5-6 promoters in tumor tissue with HCC were significantly lower in HCC tissues than in normal tissues. Patients with CLIC1 alterations had a shorter OS than patients with unaltered CLIC1. Moreover, the expression levels of CLICs correlated with the infiltration of 6 different immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells).These results indicate that the increased mRNA expression and decreased promoter DNA methylation level of CLICs may play crucial roles in HCC tumorigenesis. The expression of CLIC family members was significantly correlated with the tumor immune status. High CLIC1 and CLIC3 expression levels could serve as biomarkers for identifying advanced-stage HCC. Moreover, a CLIC1 mutation rate of 18% was also observed and CLIC1 genetic alterations were significantly associated with lower OS in HCC patients.

Multi-Modal Imaging Probe for Glypican-3 Overexpressed in Orthotopic Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is rising steadily in incidence, and more effective methods are needed for early detection and image-guided surgery. Glypican-3 (GPC3) is a cell surface biomarker that is overexpressed in early-stage cancer but not in cirrhosis. An IRDye800-labeled 12-mer amino acid sequence was identified, and specific binding to GPC3 was validated in vitro and in orthotopically implanted HCC tumors in vivo. Over 4-fold greater binding affinity and 2-fold faster kinetics were measured by comparison with previous GPC3 peptides. Photoacoustic images showed peak tumor uptake at 1.5 h post-injection and clearance within ∼24 h. Laparoscopic and whole-body fluorescence images showed strong intensity from tumor versus adjacent liver with about a 2-fold increase. Immunofluorescence staining of human liver specimens demonstrated specific binding to HCC versus cirrhosis with 79% sensitivity and 79% specificity, and normal liver with 81% sensitivity and 84% specificity. The near-infrared peptide is promising for early HCC detection in clinical trials.

Role of Hepatocyte-Derived Osteopontin in Liver Carcinogenesis

Osteopontin (OPN) expression correlates with tumor progression in many cancers, including hepatocellular carcinoma (HCC); however, its role in the onset of HCC remains unclear. We hypothesized that increased hepatocyte‐derived OPN is a driver of hepatocarcinogenesis. Analysis of a tissue microarray of 366 human samples revealed a continuous increase in OPN expression during hepatocarcinogenesis. In patients with cirrhosis, a transcriptome‐based OPN correlation network was associated with HCC incidence along 10 years of follow‐up, together with messenger RNA (mRNA) signatures of carcinogenesis. After diethylnitrosamine (DEN) injection, mice with conditional overexpression of Opn in hepatocytes (Opn^Hep transgenic [Tg]) showed increased tumor burden. Surprisingly, mice with conditional ablation of Opn in hepatocytes (Opn^ΔHep) expressed a similar phenotype. The acute response to DEN was reduced in Opn^ΔHep, which also showed more cancer stem/progenitor cells (CSCs, CD44⁺AFP⁺) at 5 months. CSCs from Opn^Hep Tg mice expressed several mRNA signatures known to promote carcinogenesis, and mRNA signatures from Opn^Hep Tg mice were associated with poor outcome in human HCC patients. Treatment with rOPN had little effect on CSCs, and their progression to HCC was similar in Opn^−/− compared with wild‐type mice. Finally, ablation of Cd44, an OPN receptor, did not reduce tumor burden in Cd44^−/−Opn^Hep Tg mice. Conclusions: Hepatocyte‐derived OPN acts as a tumor suppressor at physiological levels by controlling the acute response to DEN and the presence of CSCs, while induction of OPN is pro‐tumorigenic. This is primarily due to intracellular events rather that by the secretion of the protein and receptor activation.

High Expression Levels of SLC38A1 Are Correlated with Poor Prognosis and Defective Immune Infiltration in Hepatocellular Carcinoma

Solute Carrier Family 38 Member 1 (SLC38A1) is a principal transporter of glutamine and plays a crucial role in the transformation of neoplastic cells. However, the correlation between SLC38A1 expression, prognosis, and immune infiltration in hepatocellular carcinoma (HCC) has yet to be elucidated. We used two independent patient cohorts, namely, a Cancer Genome Atlas (TCGA) cohort and a Clinical Proteomic Tumor Analysis Consortium (CPTAC) cohort, to analyze the role of SLC38A1 in HCC at the mRNA and protein levels, respectively. In these two cohorts, SLC38A1 mRNA and protein expression levels were higher in HCC tissues than in adjacent nontumor tissues. Both SLC38A1 mRNA and protein expression were positively associated with clinicopathological characteristics (clinical stage, T stage, pathological grade, tumor size, and tumor thrombus), were negatively associated with survival, and were independent prognostic factors in HCC patients. Functional enrichment analyses further indicated that SLC38A1 was involved in multiple pathways related to amino acid metabolism, tumors, and immunity. High expression levels of SLC38A1 were inversely proportional to CD8+ T cells and directly proportional to macrophages M0, neutrophils, programmed cell death-1/programmed cell death ligand 1 (PD-1/PD-L1), and cytotoxic T lymphocyte-associated protein 4 (CTLA-4). Moreover, we used immunohistochemical analysis of tissue samples and other online databases to further validate the expression levels and prognostic significance of SLC38A1 in HCC. Collectively, our study demonstrated that the upregulated expression of SLC38A1 was related to an unfavorable prognosis and defective immune infiltration in HCC.

GJA1 promotes hepatocellular carcinoma progression by mediating TGF-β-induced activation and the epithelial-mesenchymal transition of hepatic stellate cells

Introduction

Gap junction protein, alpha 1 (GJA1), which is correlated with recurrences and unfavorable prognoses in hepatocellular carcinomas (HCCs), is one of the specific proteins expressed by activated hepatic stellate cells (HSCs).

Methods

Expression of GJA1 was compared between HCCs and nontumor tissues (NTs), between hepatic cirrhosis and NTs, and between primary and metastatic HCCs using transcriptomic datasets from the Gene Expression Omnibus and the Integrative Molecular Database of Hepatocellular Carcinoma. The in vitro activities of GJA1 were investigated in cultured HSCs and HCC cells. The underlying mechanism was characterized using Gene Set Enrichment Analysis and validated by western blotting.

Results

The expression of GJA1 was significantly increased in HCCs and hepatic cirrhosis compared to that in NTs. GJA1 was also overexpressed in pulmonary metastases from HCCs when compared with HCCs without metastasis. Overexpression of GJA1 promoted while knockdown of GJA1 inhibited proliferation and transforming growth factor (TGF)-β-mediated activation and migration of cultured HSCs. Overexpression of GJA1 by lentivirus infection promoted proliferation and migration, while conditioned medium from HSCs overexpressing GJA1 promoted migration but inhibited proliferation of Hep3B and PLC-PRF-5 cells. Lentivirus infection with shGJA1 or conditioned medium from shGJA1-infected HSCs inhibited the proliferation and migration of HCCLM3 cells that had a high propensity toward lung metastasis. Mechanistically, GJA1 induced the epithelial–mesenchymal transition (EMT) in HSCs and HCCLM3 cells.

Conclusion

GJA1 promoted HCC progression by inducing HSC activation and the EMT in HSCs. GJA1 is potentially regulated by TGF-β and thus may be a therapeutic target to inhibit HCC progression.

Bioinformatics screening of biomarkers related to liver cancer

Background

Liver cancer is a common malignant tumor in China, with high mortality. Its occurrence and development were thoroughly studied by high-throughput expression microarray, which produced abundant data on gene expression, mRNA quantification and the clinical data of liver cancer. However, the hub genes, which can be served as biomarkers for diagnosis and treatment of early liver cancer, are not well screened.

Results

Here we present a new method for getting 6 key genes, aiming to diagnose and treat the early liver cancer. We firstly analyzed the different expression microarrays based on TCGA database, and a total of 1564 differentially expressed genes were obtained, of which 1400 were up-regulated and 164 were down-regulated. Furthermore, these differentially expressed genes were studied by using GO and KEGG enrichment analysis, a PPI network was constructed based on the STRING database, and 15 hub genes were obtained. Finally, 15 hub genes were verified by applying the survival analysis method on Oncomine database, and 6 key genes were ultimately identified, including PLK1, CDC20, CCNB2, BUB1, MAD2L1 and CCNA2. The robustness analysis of four independent data sets verifies the accuracy of the key gene’s classification of the data set.

Conclusions

Although there are complicated differences between cancer and normal cells in gene functions, cancer cells could be differentiated in case that a group of special genes expresses abnormally. Here we presented a new method to identify the 6 key genes for diagnosis and treatment of early liver cancer, and these key genes can help us understand the pathogenesis of liver cancer more deeply.

Exploring the Expression and Prognostic Value of the TCP1 Ring Complex in Hepatocellular Carcinoma and Overexpressing Its Subunit 5 Promotes HCC Tumorigenesis

T-complex protein-1 ring complex (TRiC), also known as Chaperonin Containing T-complex protein-1 (CCT), is a multisubunit chaperonin required for the folding of nascent proteins. Mounting evidence suggests that TRiC also contributes to the development and progression of tumors, but there are limited studies on pathogenic functions in hepatocellular carcinoma (HCC). We comprehensively evaluated the expression pattern and biological functions of TRiC subunits using The Cancer Genome Atlas and The Human Protein Atlas. Expression levels of TRiC subunits TCP1, CCT2/3/4/5/6A/7/8 were significantly upregulated in HCC tissues at both transcript and protein levels, which predicted shorter overall survival (OS). Moreover, high mutation rates were found in several CCT subunits, and patients with altered CCT genes exhibited poorer clinical outcomes. Functional enrichment analysis showed that co-regulated genes were preferentially involved in 'protein folding' and 'microtubule-based process', while genes co-expressed with CCT subunits were primarily involved in 'ribosome' and 'spliceosome'. Knockout of CCT5 in a HCC cell line reduced while overexpression enhanced proliferation rate, cycle transition, migration, and invasion. In conclusion, these findings suggest that subunits of the TRiC may be potential biomarkers for the diagnosis of HCC and play an important role in the occurrence and development of HCC.

Systematic Construction and Validation of a Prognostic Model for Hepatocellular Carcinoma Based on Immune-Related Genes

Hepatocellular carcinoma (HCC), a highly aggressive tumor, has high incidence and mortality rates. Recently, immunotherapies have been shown to be a promising treatment in HCC. The results of either the CheckMate-040 or IMbrave 150 trials demonstrate the importance of immunotherapy in the systemic treatment of liver cancer. Thus, in this study, we tried to establish a reliable prognostic model for liver cancer based on immune-related genes (IRGs) and to provide a new insight for immunotherapy of HCC. In this study, we used four datasets that incorporated 851 HCC samples, including 340 samples with complete clinical information from the cancer genome atlas (TCGA) database, to establish an effective model for predicting the prognosis of HCC patients based on the differential expression of IRGs and validated the prognostic model using the data from International Cancer Genome Consortium (ICGC). The top 6 characteristic IRGs identified by protein-protein interaction (PPI) network analysis, MMP9, FOS, CAT, ESR1, ANGPTL3, and KLKB1, were selected for further study. In addition, we assessed the correlations of the six characteristic IRGs with the tumor immune microenvironment, clinical stage, and sensitivity to anti-cancer drugs. We also explored whether the differential expression of the characteristic IRGs was specific to HCC or present in pan-cancer. The expression levels of the six characteristic IRGs were significantly different between most tumor tissues and adjacent normal tissues. In addition, these characteristic IRGs showed a strong association with immune cell infiltration in HCC patients. We found that MMP9 and ESR1 were independent prognostic factors for HCC, while CAT, ESR1, and KLKB1 were associated with the clinical stage. We collected HCC paraffin sections from 24 patients from Xijing hospital to identify the differential expression of the five genes (MMP9, ESR1, CAT, FOS, and KLKB1). Finally, the results of decision curve analysis (DCA) and nomogram revealed that our models provided a prognostic benefit for most HCC patients and the predicted overall survival (OS) was consistent with the actual OS. In conclusion, we systemically constructed a novel prognostic model that provides new insights into HCC.

Cyclin-dependent kinase 19 upregulation correlates with an unfavorable prognosis in hepatocellular carcinoma

Objectives

Cyclin-dependent kinase 19 (CDK19) is a component of the mediator coactivator complex, which is required for transcriptional activation. In this study, we utilized public databases and wet-bench hepatic cell line experiments to elucidate the potential roles of CDK19 in hepatocellular cancer (HCC).

Materials and methods

We studied the relationships between CDK19 expression and several clinical features related to HCC via the Oncomine and UALCAN databases. The prognostic value of CDK19 was tested using the Kaplan–Meier Plotter database. We presented the mutations of CDK19 and addressed the relation of CDK19 expression with immune cell infiltration by means of the cBioPortal, Catalogue of Somatic Mutations in Cancer (COSMIC) and Tumor IMmune Estimation Resource (TIMER) databases. Hub genes were obtained and further analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. To test the in silico findings, we knocked down CDK19 with short hairpin RNA (shRNA) technology in two hepatic cell lines and conducted several functional characterization experiments.

Results

Marked CDK19 upregulation was found in HCC tissues versus normal liver tissues, and CDK19 mRNA expression had high diagnostic value in HCC patients. Subgroup analysis showed that CDK19 overexpression was associated with sex, tumor stage and TP53 mutation status. The prognostic value of CDK19 upregulation for overall survival (OS) was significant in patients with stage 2–3, stage 3–4, and grade 2 disease. One percent of the patients had CDK19 mutations, but no relationship between CDK19 mutation and prognosis was observed. CDK19 was positively correlated with the abundances of CD4 + T cells, macrophages and dendritic cells. We identified 10 genes correlated with CDK19, 8 of which presented excellent prognostic value in HCC. These hub genes were directly involved in cell division and regulation of the G2/M cell cycle transition. Protein–protein interaction (PPI) and pathway predictions indicated that CDK19 is highly likely to be involved in several cellular functions, such as proliferation, migration, and invasion. These functions were strongly interfered from two independent hepatic cell lines after CDK19 knockdown.

Conclusions

CDK19 could be a prognostic marker in HCC, and its therapeutic potential in HCC needs further study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-01962-8.

Integrative Predictive Modeling of Metastasis in Melanoma Cancer Based on MicroRNA, mRNA, and DNA Methylation Data

Introduction: Despite the significant progress in understanding cancer biology, the deduction of metastasis is still a challenge in the clinic. Transcriptional regulation is one of the critical mechanisms underlying cancer development. Even though mRNA, microRNA, and DNA methylation mechanisms have a crucial impact on the metastatic outcome, there are no comprehensive data mining models that combine all transcriptional regulation aspects for metastasis prediction. This study focused on identifying the regulatory impact of genetic biomarkers for monitoring metastatic molecular signatures of melanoma by investigating the consolidated effect of miRNA, mRNA, and DNA methylation.

Method: We developed multiple machine learning models to distinguish the metastasis by integrating miRNA, mRNA, and DNA methylation markers. We used the TCGA melanoma dataset to differentiate between metastatic melanoma samples by assessing a set of predictive models. For this purpose, machine learning models using a support vector machine with different kernels, artificial neural networks, random forests, AdaBoost, and Naïve Bayes are compared. An iterative combination of differentially expressed miRNA, mRNA, and methylation signatures is used as a candidate marker to reveal each new biomarker category’s impact. In each iteration, the performances of the combined models are calculated. During all comparisons, the choice of the feature selection method and under and oversampling approaches are analyzed. Selected biomarkers of the highest performing models are further analyzed for the biological interpretation of functional enrichment.

Results: In the initial model, miRNA biomarkers can identify metastatic melanoma with an 81% F-score. The addition of mRNA markers upon miRNA increased the F-score to 92%. In the final integrated model, the addition of the methylation data resulted in a similar F-score of 92% but produced a stable model with low variance across multiple trials.

Conclusion: Our results support the role of miRNA regulation in metastatic melanoma as miRNA markers model metastasis outcomes with high accuracy. Moreover, the integrated evaluation of miRNA with mRNA and methylation biomarkers increases the model’s power. It populates selected biomarkers on the metastasis-associated pathways of melanoma, such as the “osteoclast”, “Rap1 signaling”, and “chemokine signaling” pathways.

Source Code:https://github.com/aysegul-kt/MelonomaMetastasisPrediction/

Development of a Toll-Like Receptor-Based Gene Signature That Can Predict Prognosis, Tumor Microenvironment, and Chemotherapy Response for Hepatocellular Carcinoma

Objective: Emerging evidence highlights the implications of the toll-like receptor (TLR) signaling pathway in the pathogenesis and therapeutic regimens of hepatocellular carcinoma (HCC). Herein, a prognostic TLR-based gene signature was conducted for HCC.

Methods: HCC-specific TLRs were screened in the TCGA cohort. A LASSO model was constructed based on prognosis-related HCC-specific TLRs. The predictive efficacy, sensitivity, and independency of this signature was then evaluated and externally verified in the ICGC, GSE14520, and GSE76427 cohorts. The associations between this signature and tumor microenvironment (stromal/immune score, immune checkpoint expression, and immune cell infiltrations) and chemotherapy response were assessed in HCC specimens. The expression of TLRs in this signature was verified in HCC and normal liver tissues by Western blot. Following si-MAP2K2 transfection, colony formation and apoptosis of Huh7 and HepG2 cells were examined.

Results: Herein, we identified 60 HCC-specific TLRs. A TLR-based gene signature (MAP2K2, IRAK1, RAC1, TRAF3, MAP3K7, and SPP1) was conducted for HCC prognosis. High-risk patients exhibited undesirable outcomes. ROC curves confirmed the well prediction performance of this signature. Multivariate Cox regression analysis demonstrated that the signature was an independent prognostic indicator. Also, high-risk HCC was characterized by an increased immune score, immune checkpoint expression, and immune cell infiltration. Meanwhile, high-risk patients displayed higher sensitivity to gemcitabine and cisplatin. The dysregulation of TLRs in the signature was confirmed in HCC. MAP2K2 knockdown weakened colony formation and elevated apoptosis of Huh7 and HepG2 cells.

Conclusion: Collectively, this TLR-based gene signature might assist clinicians to select personalized therapy programs for HCC patients.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

circRPS16 Promotes Proliferation and Invasion of Hepatocellular Carcinoma by Sponging miR-876-5p to Upregulate SPINK1

The roles of serine protease inhibitor Kazal type 1 (SPINK1) in multiple types of cancers have been significantly documented. However, its specific roles in hepatocellular carcinoma (HCC) remain to be investigated. This study found that SPINK1 is upregulated in HCC and its upregulation correlates with poor prognosis. Besides, functional assays revealed that SPINK1 promotes cell proliferation, cell cycle, and invasion in vitro. Through bioinformatics analysis, we speculate that circRPS16 regulates SPINK1 expression by sponging miR-876-5p. This was further verified by the dual-luciferase reporter and fluorescent in situ hybridization (FISH) assays. Subsequently, rescue assays verified that circRPS16 promotes cell proliferation, cell cycle, and invasion through miR-876-5p. Importantly, silencing circRPS16 inhibited tumor growth by downregulating SPINK1 expression in vivo. Collectively, our results confirm that SPINK1 is a downstream target of circRPS16. Besides, circRPS16 and SPINK1 are oncogenic factors in HCC progression; they provide novel diagnostic and therapeutic targets for HCC patients.

KIF2C: a novel link between Wnt/β-catenin and mTORC1 signaling in the pathogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is the fourth-leading cause of cancer-related deaths worldwide. HCC is refractory to many standard cancer treatments and the prognosis is often poor, highlighting a pressing need to identify biomarkers of aggressiveness and potential targets for future treatments. Kinesin family member 2C (KIF2C) is reported to be highly expressed in several human tumors. Nevertheless, the molecular mechanisms underlying the role of KIF2C in tumor development and progression have not been investigated. In this study, we found that KIF2C expression was significantly upregulated in HCC, and that KIF2C up-regulation was associated with a poor prognosis. Utilizing both gain and loss of function assays, we showed that KIF2C promoted HCC cell proliferation, migration, invasion, and metastasis both in vitro and in vivo. Mechanistically, we identified TBC1D7 as a binding partner of KIF2C, and this interaction disrupts the formation of the TSC complex, resulting in the enhancement of mammalian target of rapamycin complex1 (mTORC1) signal transduction. Additionally, we found that KIF2C is a direct target of the Wnt/β-catenin pathway, and acts as a key factor in mediating the crosstalk between Wnt/β-catenin and mTORC1 signaling. Thus, the results of our study establish a link between Wnt/β-catenin and mTORC1 signaling, which highlights the potential of KIF2C as a therapeutic target for the treatment of HCC.