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

Ethyl Acetate Fraction of Hedyotis diffusa Willd Induces Apoptosis via JNK/Nur77 Pathway in Hepatocellular Carcinoma Cells

Background

Hepatocellular carcinoma (HCC) is characterized by poor diagnosis and high mortality. Novel and efficient therapeutic agents are urgently needed for the treatment. Hedyotis diffusa Willd (HDW) is used to treat cancers, especially HCC in China.

Purpose

The study aimed to identify the main anti-HCC extract in HDW and to explore the mechanism of the active extract.

Materials and Methods

The high-performance liquid chromatography-quadrupole-time of flight mass spectrometry (HPLC-QTOF-MS) method was used for the simultaneous determination of main compounds in the ethyl acetate fraction of HDW (EHDW). The toxicity test of different HDW fractions was carried out on larvae at 2 day-post-fertilization (dpf) for 72 h. The in vivo anti-HCC effect of different HDW fractions was evaluated on a zebrafish tumor model by immersion administration. The antiproliferative effect of HDW fractions was determined with MTT assay, as well as hematoxylin and eosin (HE) staining assay. Hoechst 33258 staining was used to observe changes in nucleus morphology. Flow cytometry analysis was used to investigate apoptosis induction. Western blot analysis was used to examine apoptosis-related proteins, and key proteins in JNK/Nur77 signaling pathway. SP600125 was served to validate the apoptotic mechanism.

Results

EHDW showed the strongest tumor cell growth inhibitory effect on zebrafish tumor model. Further study revealed that EHDW induced apoptosis in zebrafish tumor model and in cultured Hep3B cells. Meanwhile, it has been shown that the levels of BCL2-associated X (Bax), cytochrome c (cyto c), cleaved-caspase 3, and poly-ADP-ribose polymerase (PARP) cells were upregulated. In contrast, the level of antiapoptotic B cell lymphoma-2 (Bcl-2) was downregulated in Hep3B cells. Additionally, EHDW activated JNK/Nur77 pathway by increasing the levels of p-JNK(Thr183/Tyr185) and p-Nur77(Ser351). Further study showed that blockage of JNK by SP600125 reversed EHDW-induced JNK/Nur77 pathway and the downstream apoptotic proteins.

Conclusion

In conclusion, EHDW exerted the anti-HCC effect, which may be attributed to the activation of JNK/Nur77 pathway. This study supported the rationale of HDW as an HCC therapeutic agent.

The Prognostic Value of AT-Rich Interaction Domain (ARID) Family Members in Patients with Hepatocellular Carcinoma

Objective

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies with a poor prognosis. The AT-rich interaction domain (ARID) family plays an essential regulatory role in the pathogenesis and progression of cancers. This study aims to evaluate the prognostic value and clinical significance of human ARID family genes in HCC.

Methods

ONCOMINE and The Cancer Genome Atlas (TCGA) databases were employed to retrieve ARIDs expression profile and clinicopathological information of HCC. Kaplan–Meier plotter and MethSurv were applied to the survival analysis of patients with HCC. CBioPortal was used to analyze genetic mutations of ARIDs. Gene Expression Profiling Interactive Analysis (GEPIA) and Metascape were used to perform hub gene identification and functional enrichment.

Results

Expression levels of 11 ARIDs were upregulated in HCC, and 2 ARIDs were downregulated. Also, 4 ARIDs and 5 ARIDs were correlated with pathologic stages and histologic grades, respectively. Furthermore, higher expression of ARID1A, ARID1B, ARID2, ARID3A, ARID3B, ARID5B, KDM5A, KDM5B, KDM5C, and JARID2 was remarkably correlated with worse overall survival of patients with HCC, and the high ARID3C/KDM5D expression was related to longer overall survival. Multivariate Cox analysis indicated that ARID3A, KDM5C, and KDM5D were independent risk factors for HCC prognosis. Moreover, ARIDs mutations and 127 CpGs methylation in all ARIDs were observed to be significantly associated with the prognosis of HCC patients. Besides, our data showed that ARIDs could regulate tumor-related pathways and distinct immune cells in the HCC microenvironment.

Conclusions

ARIDs present the potential prognostic value for HCC. Our findings suggest that ARID3A, KDM5C, and KDM5D may be the prognostic biomarkers for patients with HCC.

Prognostic Values of BolA Family Member Expression in Hepatocellular Carcinoma

The BolA gene family member (BOLA1-3) plays an important role in regulating normal and pathological biological processes including liver tumorigenesis. However, their expression patterns as prognostic factors in hepatocellular carcinoma (HCC) patients have not to be elucidated. We examined the transcriptional expressions and survival data of BolA family member in patients with HCC from online databases including ONCOMINE, TCGA, UALCAN, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, SurvExpress, cBioPortal, and Exobase. Network molecular interaction views of BolA family members and their neighborhoods were constructed by the IntAct web server. In our research, we had found that the expression levels of BolA /2/3 mRNA were higher in HCC tissue than in normal liver tissues from TGCA databases. Moreover, the BolA family gene expression level is significantly associated with distinct tumor pathological grade, TMN stage, and overall survival (OS). The BolA family can be considered as prognostic risk biomarkers of HCC. A small number of BolA gene-mutated samples were detected in the HCC tissue. IntAct analysis revealed that BolA1/2/3 was closely associated with the GLRX3 expression in HCC, which is implicated in the regulation of the cellular iron homeostasis and tumor growth. Furthermore, prognostic values of altered BolAs and their neighbor GLRX3 gene in HCC patients were validated by SurvExpress analysis. In conclusion, the membrane BolA family identified in this study provides very useful information for the mechanism of hepatic tumorigenesis.

Metabolism-Related Gene Pairs to Predict the Clinical Outcome and Molecular Characteristics of Early Hepatocellular Carcinoma

Recurrence is the main factor affecting the prognosis of early hepatocellular carcinoma (HCC), which is not accurately evaluated by clinical indicators. The metabolic heterogeneity of HCC hints at the possibility of constructing a stratification model to predict the clinical outcome. On the basis of the relative expression orderings of 2939 metabolism-related genes, an individualized signature with 10 metabolism-related gene pairs (10-GPS) was developed from 250 early HCC samples in the discovery datasets, which stratified HCC patients into the high- and low-risk subgroups with significantly different survival rates. The 10-GPS was validated in 311 public transcriptomic samples from two independent validation datasets. A nomogram that included the 10-GPS, age, gender, and stage was constructed for eventual clinical evaluation. The low-risk group was characterized by lower proliferation, higher metabolism, increased activated immune microenvironment, and lower TIDE scores, suggesting a better response to immunotherapy. The high-risk group displayed hypomethylation, higher copy number alterations, mutations, and more overexpression of immune-checkpoint genes, which might jointly lead to poor outcomes. The prognostic accuracy of the 10-GPS was further validated in 47 institutional transcriptomic samples and 101 public proteomic samples. In conclusion, the 10-GPS is a robust predictor of the clinical outcome for early HCC patients and could help evaluate prognosis and characterize molecular heterogeneity.

A single-cell atlas of the multicellular ecosystem of primary and metastatic hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents a paradigm of the relation between tumor microenvironment (TME) and tumor development. Here, we generate a single-cell atlas of the multicellular ecosystem of HCC from four tissue sites. We show the enrichment of central memory T cells (T_CM) in the early tertiary lymphoid structures (E-TLSs) in HCC and assess the relationships between chronic HBV/HCV infection and T cell infiltration and exhaustion. We find the MMP9⁺ macrophages to be terminally differentiated tumor-associated macrophages (TAMs) and PPARγ to be the pivotal transcription factor driving their differentiation. We also characterize the heterogeneous subpopulations of malignant hepatocytes and their multifaceted functions in shaping the immune microenvironment of HCC. Finally, we identify seven microenvironment-based subtypes that can predict prognosis of HCC patients. Collectively, this large-scale atlas deepens our understanding of the HCC microenvironment, which might facilitate the development of new immune therapy strategies for this malignancy.

The immune cell constituents and localisation within human hepatocellular carcinoma is not fully understood. Here the authors use single cell RNA sequencing of HCC from four different tissue sites and show differences between primary and metastatic tumours, tumour associated macrophages and immune cell populations.

IL27 Signaling Serves as an Immunologic Checkpoint for Innate Cytotoxic Cells to Promote Hepatocellular Carcinoma

Although inflammatory mechanisms driving hepatocellular carcinoma (HCC) have been proposed, the regulators of anticancer immunity in HCC remain poorly understood. We found that IL27 receptor (IL27R) signaling promotes HCC development in vivo. High IL27EBI3 cytokine or IL27RA expression correlated with poor prognosis for patients with HCC. Loss of IL27R suppressed HCC in vivo in two different models of hepatocarcinogenesis. Mechanistically, IL27R sig-naling within the tumor microenvironment restrains the cytotoxicity of innate cytotoxic lymphocytes. IL27R ablation enhanced their accumulation and activation, whereas depletion or functional impairment of innate cytotoxic cells abrogated the effect of IL27R disruption. Pharmacologic neutralization of IL27 signaling increased infiltration of innate cytotoxic lymphocytes with upregulated cytotoxic molecules and reduced HCC development. Our data reveal an unexpected role of IL27R signaling as an immunologic checkpoint regulating innate cytotoxic lymphocytes and promoting HCC of different etiologies, thus indicating a therapeutic potential for IL27 pathway blockade in HCC.

SIGNIFICANCE

HCC, the most common form of liver cancer, is characterized by a poor survival rate and limited treatment options. The discovery of a novel IL27-dependent mechanism controlling anticancer cytotoxic immune response will pave the road for new treatment options for this devastating disease. This article is highlighted in the In This Issue feature, p. 1825.

Integrated multi-omics analysis identifies ENY2 as a predictor of recurrence and a regulator of telomere maintenance in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and has a high recurrence rate. Accurate prediction of recurrence risk is urgently required for tailoring personalized treatment programs for individual HCC patients in advance. In this study, we analyzed a gene expression dataset from an HCC cohort with 247 samples and identified five genes including ENY2, GPAA1, NDUFA4L2, NEDD9, and NRP1 as the variables for the prediction of HCC recurrence, especially the early recurrence. The Cox model and risks score were validated in two public HCC cohorts (GSE76427 and The Cancer Genome Atlas (TCGA)) and one cohort from Huashan Hospital, which included a total of 641 samples. Moreover, the multivariate Cox regression analysis revealed that the risk score could serve as an independent prognostic factor in the prediction of HCC recurrence. In addition, we found that ENY2, GPAA1, and NDUFA4L2 were significantly upregulated in HCC of the two validation cohorts, and ENY2 had significantly higher expression levels than another four genes in malignant cells, suggesting that ENY2 might play key roles in malignant cells. The cell line analysis revealed that ENY2 could promote cell cycle progression, cell proliferation, migration, and invasion. The functional analysis of the genes correlated with ENY2 revealed that ENY2 might be involved in telomere maintenance, one of the fundamental hallmarks of cancer. In conclusion, our data indicate that ENY2 may regulate the malignant phenotypes of HCC via activating telomere maintenance.

Calcium/calmodulin-dependent protein kinase kinase 2 regulates hepatic fuel metabolism

OBJECTIVE

The liver is the primary internal metabolic organ that coordinates whole body energy homeostasis in response to feeding and fasting. Genetic ablation or pharmacological inhibition of calcium/calmodulin-dependent protein kinase kinase 2 (CaMKK2) has been shown to significantly improve hepatic health and peripheral insulin sensitivity upon overnutrition with high fat diet. However, the precise molecular underpinnings that explain this metabolic protection have remained largely undefined.

METHODS

To characterize the role of CaMKK2 in hepatic metabolism, we developed and challenged liver-specific CaMKK2 knockout (CaMKK2LKO) mice with high fat diet and performed glucose and insulin tolerance tests to evaluate peripheral insulin sensitivity. We used a combination of RNA-Sequencing, glucose and fatty acid istotopic tracer studies, a newly developed Seahorse assay for measuring the oxidative capacity of purified peroxisomes, and a degenerate peptide libarary to identify putative CaMKK2 substrates that mechanistically explain the protective effects of hepatic CaMKK2 ablation.

RESULTS

Consistent with previous findings, we show that hepatic CaMKK2 ablation significantly improves indices of peripheral insulin sensitivity. Mechanistically, we found that CaMKK2 phosphorylates and regulates GAPDH to promote glucose metabolism and PEX3 to blunt peroxisomal fatty acid catabolism in the liver.

CONCLUSION

CaMKK2 is a central metabolic fuel sensor in the liver that significantly contributes to whole body systems metabolism.

Oncogenic signaling pathway mediated by Notch pathway-related genes induces immunosuppression and immunotherapy resistance in hepatocellular carcinoma

The Notch pathway is a highly conserved signaling pathway involved in the regulation of cell proliferation and differentiation. However, the relationships between Notch pathway-related genes (NPRGs), immunosuppression, and immunotherapy resistance of hepatocellular carcinoma (HCC) remain unclear. Gene expression data and clinical information were extracted from GSE14520, GSE36376, GSE76427, LIRI-JP, TCGA-LIHC, GSE20140, GSE27150, and IMvigor210 datasets. A consensus clustering analysis based on 10 NPRGs was performed to determine the molecular subtypes, and then a notchScore was constructed based on differentially expressed and prognostic genes between molecular subtypes. Two molecular subgroups with significantly distinct survival and immune cell infiltration were identified. Then, a notchScore was constructed to quantify the Notch index of each patient with HCC. Next, we investigated the correlations between the clinical characteristics and the notchScore using logistic regression. Furthermore, multivariate Cox analysis showed that a high notchScore was an independent predictor of poor overall survival (OS) in the TCGA and LIRI-JP datasets and was associated with higher pathological stages. Additionally, a high notchScore was associated with higher immune cells, higher ESTIMATE score, higher immune score, higher stromal score, higher immune checkpoint, and lower tumor purity, which was consistent with the "immunity tidal model theory." Importantly, a high notchScore was sensitive to immunotherapy. Additionally, GSEA indicated that several GO and KEGG items associated with apoptosis, immune-related pathways, and cell cycle signal pathways were significantly enriched in the high notchScore phenotype pathway. Our findings propose that a high notchScore is a prognostic biomarker and correlates with immune infiltration and sensitivity to immunotherapy in HCC.

Stemness Analysis Uncovers That The Peroxisome Proliferator-Activated Receptor Signaling Pathway Can Mediate Fatty Acid Homeostasis In Sorafenib-Resistant Hepatocellular Carcinoma Cells

Hepatocellular carcinoma (HCC) stem cells are regarded as an important part of individualized HCC treatment and sorafenib resistance. However, there is lacking systematic assessment of stem-like indices and associations with a response of sorafenib in HCC. Our study thus aimed to evaluate the status of tumor dedifferentiation for HCC and further identify the regulatory mechanisms under the condition of resistance to sorafenib. Datasets of HCC, including messenger RNAs (mRNAs) expression, somatic mutation, and clinical information were collected. The mRNA expression-based stemness index (mRNAsi), which can represent degrees of dedifferentiation of HCC samples, was calculated to predict drug response of sorafenib therapy and prognosis. Next, unsupervised cluster analysis was conducted to distinguish mRNAsi-based subgroups, and gene/geneset functional enrichment analysis was employed to identify key sorafenib resistance-related pathways. In addition, we analyzed and confirmed the regulation of key genes discovered in this study by combining other omics data. Finally, Luciferase reporter assays were performed to validate their regulation. Our study demonstrated that the stemness index obtained from transcriptomic is a promising biomarker to predict the response of sorafenib therapy and the prognosis in HCC. We revealed the peroxisome proliferator-activated receptor signaling pathway (the PPAR signaling pathway), related to fatty acid biosynthesis, that was a potential sorafenib resistance pathway that had not been reported before. By analyzing the core regulatory genes of the PPAR signaling pathway, we identified four candidate target genes, retinoid X receptor beta (RXRB), nuclear receptor subfamily 1 group H member 3 (NR1H3), cytochrome P450 family 8 subfamily B member 1 (CYP8B1) and stearoyl-CoA desaturase (SCD), as a signature to distinguish the response of sorafenib. We proposed and validated that the RXRB and NR1H3 could directly regulate NR1H3 and SCD, respectively. Our results suggest that the combined use of SCD inhibitors and sorafenib may be a promising therapeutic approach.

NCAPG promotes the proliferation of hepatocellular carcinoma through the CKII-dependent regulation of PTEN

BACKGROUND

NCAPG, non-SMC subunit in the concentrate I complex, might promote the proliferation of hepatocellular carcinoma (HCC), but the mechanism is unclear. The aim of this study was to explore how NCAPG affects PTEN to influence the proliferation of HCC.

METHODS

Western blotting, qRT-PCR and immunohistochemistry were used to detect NCAPG expression in HCC tissues. The effect of NCAPG on the proliferation of HCC cell lines was evaluated using an EdU incorporation assay, a Cell Counting Kit-8 assay and Fluorescence in situ hybridization (FISH). BALB/c-nu/nu mice were used for the in vivo proliferation experiment. Transcriptome sequencing was used to determine the relationship between NCAPG and PTEN. Immunocoprecipitation-mass spectrometry (IP-MS), proteomic sequencing and Co-immunoprecipitation (CO-IP) were used to identify and examine the interaction between the NCAPG and CKII proteins.

RESULTS

We confirmed that NCAPG was abnormally overexpressed in HCC and promoted the proliferation of HCC cells. Transcriptome sequencing revealed that NCAPG inhibited the transcription of PTEN and promoted the activation of the PI3K-AKT pathway. We found a close association between NCAPG and CKII through proteomic sequencing; their interaction was confirmed by Co-IP. There was a positive correlation between NCAPG and CKII that promoted the phosphorylation of PTEN and thus inhibited its transcription and functions. We also proved that CKII was the key factor in the induction of proliferation by NCAPG.

CONCLUSION

We revealed the mechanism by which NCAPG regulates the proliferation of HCC: NCAPG inhibits PTEN through its interaction with CKII, and then activates the PI3K-AKT pathway to promote the proliferation of HCC.

Comprehensive transcriptomic and co-expression analysis of ABL1 gene and molecularly targeted drugs in hepatocellular carcinoma based on multi-database mining

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. Consequently, it is essential to identify biomarkers for treatment response and the prognosis prediction. We investigated whether ABL1 can function as a biomarker or a drug target for HCC. We assessed the ABL1 expression, genetic alterations and patients' survival from LinkedOmics, GEO, TCGA and Human Protein Atlas. We analyzed PPI, GO and KEGG pathways. GSEA was analyzed for functional comparison. The current drugs targeting ABL1 were statistically analyzed using DRUGSURV and DGIdb database. We found ABL1 is overexpressed in HCC and its higher expression reduces survival probability. Genetic changes of ABL1 are not frequent. We screened out 25 differentially expressed genes correlated with ABL1. The top functions of ABL1 are biological regulation, metabolic process, protein-containing, and protein binding. KEGG pathways showed that ABL1 and correlated with ABL1 significantly genes markedly enriched in the ErbB signaling pathway, and pathways in cancer. We counted the existing drugs targeting ABL1, which indicates that inhibiting ABL1 expression may improve the survival probability of HCC. In conclusion, ABL1 plays a crucial role in the development and progression of this cancerization and is a potential drug target.

Necroptosis-Related Genes Signatures Identified Molecular Subtypes and Underlying Mechanisms in Hepatocellular Carcinoma

Background

Although emerging evidence supports the relationship between necroptosis (NEC) related genes and hepatocellular carcinoma (HCC), the contribution of these necroptosis-related genes to the development, prognosis, and immunotherapy of HCC is unclear.

Methods

The expression of genes and relevant clinical information were downloaded from TCGA-LIHC, LIRI-JP, GSE14520/NCI, GSE36376, GSE76427, GSE20140, GSE27150, and IMvigor210 datasets. Next, we used an unsupervised clustering method to assign the samples into phenotype clusters base on 15 necroptosis-related genes. Subsequently, we constructed a NEC score based on NEC phenotype-related prognostic genes to quantify the necroptosis related subtypes of individual patients.

Results

We divided the samples into the high and low NEC score groups, and the high NEC score showed a poor prognosis. Simultaneously, NEC score is an effective and stable model and had a good performance in predicting the prognosis of HCC patients. A high NEC score was characterized by activation of the stroma and increased levels of immune infiltration. A high NEC score was also related to low expression of immune checkpoint molecules (PD-1/PD-L1). Importantly, the established NEC score would contribute to predicting the response to anti-PD-1/L1 immunotherapy.

Conclusions

Our study provide a comprehensive analysis of necroptosis-related genes in HCC. Stratification based on the NEC score may enable HCC patients to benefit more from immunotherapy and help identify new cancer treatment strategies.

Prognostic Value of Stem Cell Index-Related Characteristics in Primary Hepatocellular Carcinoma

The objective of this study is to form a cancer stem cell index-based model to stratify HCC risk and predict survival. After screening the Tumor Genome Atlas (TCGA) of liver and normal liver tissue samples, we obtained differentially expressed genes (DEGs). We employed a weighted correlation network analysis (WGCNA) and differentially expressed genes were studied in HCC to find the modules most associated with cancer stem cells (mRNAsi). At the same time, gene ontology and Kyoto Genome Encyclopedia (KEGG) were used for functional annotation and combined with LASSO, univariate, and multivariate COX regression analyses, a prediction model of key module genes of cancer stem cells was developed. The model's clinical efficacy was measured using the C index, calibration curve, multiindex ROC curve, and clinical decision curve. WGCNA found that black modules were most correlated with tumour stem cell index. Seven genes (CSDC2, GNA14, LGI2, MMRN1, PDE2A, SELP, and STK32B) were filtered by univariate, LASSO, and multivariate Cox regression analyses to establish the primary HCC model. The survival analysis and ROC curve in the TCGA training and validation cohort showed good performance. The independent prognostic factor of primary HCC was risk score, according to univariate and multivariate Cox regression analyses. It is found that the stem cell index model of 7 genes could predict factors independently, indicating that signatures of the stem cell will play a significant role in liver cancer survival prediction and risk stratification.

Tumor suppressor LHPP suppresses cell proliferation and epithelial-mesenchymal transition in hepatocellular carcinoma cell lines

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer in the world with high mortality due to its high potential of metastasis. Epithelial-mesenchymal transition (EMT) plays a key role in the pathogenesis of HCC occurrence and metastasis. Phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) is a novel tumor suppressor. There is little study about LHPP in human HCC development. In the present study, we aimed to investigate the role of LHPP in human HCC cell metastasis. We analyzed the LHPP expression level in human HCC tissues compared with normal tissues in the public database. We detected the mRNA level and protein level of LHPP in transformed liver cell line (LO2) and human HCC cell lines (MHCC-97 H, MHCC-97L, and HepG2). We performed genetic gain and loss of function experiments with LHPP using small interfering RNA (siRNA) and lentivirus infection. Then, we detected that LHPP suppressed proliferation and promoted apoptosis in hepatocellular carcinoma cell lines. Also, we investigated the role of LHPP in the EMT process. Finally, we examined the effect of LHPP on TGF-β-induced EMT. Interestingly, we also found that LHPP expression is positively regulated tumor suppressor p53. Our data showed that LHPP is significantly decreased in the human HCC tissues and human HCC cell lines compared with normal liver tissues and transformed liver cells. Knockdown of LHPP promotes HCC cell proliferation and metastasis, and LHPP expression levels negatively correlate with EMT-related genes. Furthermore, LHPP inhibits TGF-β-induced EMT in HCC cell lines. These studies validate LHPP as a tumor suppressor in liver cancer and provide a new genetic target for HCC diagnosis and treatment.

Novel dual inhibitor for targeting PIM1 and FGFR1 kinases inhibits colorectal cancer growth in vitro and patient-derived xenografts in vivo

Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world. The pro-viral integration site for Moloney murine leukemia virus 1 (PIM1) is a proto-oncogene and belongs to the serine/threonine kinase family, which are involved in cell proliferation, migration, and apoptosis. Fibroblast growth factor receptor 1 (FGFR1) is a tyrosine kinase that has been implicated in cell proliferation, differentiation and migration. Small molecule HCI-48 is a derivative of chalcone, a class of compounds known to possess anti-tumor, anti-inflammatory and antibacterial effects. However, the underlying mechanism of chalcones against colorectal cancer remains unclear. This study reports that HCI-48 mainly targets PIM1 and FGFR1 kinases, thereby eliciting antitumor effects on colorectal cancer growth in vitro and in vivo. HCI-48 inhibited the activity of both PIM1 and FGFR1 kinases in an ATP-dependent manner, as revealed by computational docking models. Cell-based assays showed that HCI-48 inhibited cell proliferation in CRC cells (HCT-15, DLD1, HCT-116 and SW620), and induced cell cycle arrest in the G2/M phase through modulation of cyclin A2. HCI-48 also induced cellular apoptosis, as evidenced by an increase in the expression of apoptosis biomarkers such as cleaved PARP, cleaved caspase 3 and cleaved caspase 7. Moreover, HCI-48 attenuated the activation of downstream components of the PIM1 and FGFR1 signaling pathways. Using patient-derived xenograft (PDX) murine tumor models, we found that treatment with HCI-48 diminished the PDX tumor growth of implanted CRC tissue expressing high protein levels of PIM1 and FGFR1. This study suggests that the inhibitory effect of HCI-48 on colorectal tumor growth is mainly mediated through the dual-targeting of PIM1 and FGFR1 kinases. This work provides a theoretical basis for the future application of HCI-48 in the treatment of clinical CRC.

Prognostic and immunological significance of peroxisome proliferator-activated receptor gamma in hepatocellular carcinoma based on multiple databases

BACKGROUND

Peroxisome proliferator-activated receptor gamma (PPARG) plays some roles in preventing liver disease progression to hepatocellular carcinoma. However, there is limited information about the function of PPARG of in hepatocellular carcinoma. This study aimed to determine the significance of PPARG in immunological response and as a biomarker for hepatocellular carcinoma survival.

METHODS

We investigated the expression, prognosis, Kyoto Encyclopedia of Genes and Genomes/Gene Ontology biological process enrichment, and immune significance of PPARG using data from three databases-The Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus-through bioinformatics analysis as well as experimental verification in proliferation function of PPARG in HepG2 cell.

RESULTS

High PPARG expression in hepatocellular carcinoma tissues positively correlated with TP53 mutation, and predicted poor prognosis. The results of enrichment and immune infiltration showed that PPARG negatively correlated with the complement system and macrophage infiltration, and laboratory results support that PPARG regulate proliferation of HepG2 cell.

CONCLUSIONS

PPARG is upregulated in hepatocellular carcinoma and it correlates with a worse prognosis. Moreover, PPARG may play an important role in the cell proliferation, complement system and immune cell infiltration in hepatocellular carcinoma.

Identification of two immune-related risk score signatures through integrated analysis of multi-omics data in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Immunotherapy has become a major treatment for advanced HCC, but the therapeutic effects remain unsatisfactory. In this study, we constructed an immune cell risk score (ICS) and an immune cell-related gene risk score (ICRGS) for the prognosis prediction of HCC through integrated analysis of bulk and single-cell RNA (scRNA) sequencing data. These two risk score signatures both showed good predictive values in the training and validation cohorts. The potential interactions among these prognostic immune cell types were elucidated by cell-cell communication analysis. The results of enrichment analysis and gene set enrichment analysis (GSEA) of the prognostic genes showed that metabolic-related processes were involved in the immune response of HCC. Furthermore, the results of correlation analyses further confirmed the hub genes that were strongly correlated with immune cells. Finally, potential therapeutic drugs targeting these hub genes were screened by CellMiner based on NCI-60 cell line set. Taken together, two useful models for the prognosis prediction of HCC patients were constructed in this study. The functional differences between the two groups of HCC patients separated by ICS or ICRGS provide fundamental knowledge for finding synergistic therapeutic targets for HCC immunotherapy.

INK4 cyclin-dependent kinase inhibitors as potential prognostic biomarkers and therapeutic targets in hepatocellular carcinoma

The INK4 family is an important family of cyclin-dependent kinase inhibitors (CDKIs) and consists of CDKN2A, CDKN2B, CDKN2, and CDKN2D. Abnormal expression of CDKN2A has been reported in hepatocellular carcinoma (HCC) and is associated with the prognosis of patients and infiltration of immune cells. However, there is a lack of systematic research on the roles of the other INK4 family members in the diagnosis, prognosis, and immune regulation of HCC. Using online public databases and clinical samples, we comprehensively analyzed the INK4 family in HCC. All four INK4 proteins were overexpressed in HCC and correlated with advanced cancer stage and poor prognosis. INK4 expression accurately distinguished tumor from normal tissue, particularly CDKN2A and CDKN2C. The INK4 family participated in cell-cycle regulation and the DNA damage repair pathway, which inhibited genotoxic-induced apoptosis in tumorigenesis. INK4 proteins were positively correlated with the infiltration of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) and immune checkpoints (CTLA-4, PD1, and PD-L1). CDKN2D had the highest correlation (correlation coefficient >0.3) with all the above-mentioned infiltrating immune cells and immune checkpoints, indicating that it may be useful as an immunotherapy target. The INK4 family was valuable for diagnosis and predicting the prognosis of HCC and participated in the occurrence, progression, and immune regulation of HCC, demonstrating its potential as a diagnostic and prognostic biomarker and therapeutic target in HCC.

Molecular subtypes, prognostic and immunotherapeutic relevant gene signatures mediated by DNA methylation regulators in hepatocellular carcinoma

Growing evidence has revealed the crucial role of epigenetics in tumor progression and immune response. However, the molecular subtypes and their microenvironment characterization mediated by DNA methylation regulators in hepatocellular carcinoma remain little known. In this study, we comprehensively integrated the transcriptome profiling of twenty DNA methylation regulators in hepatocellular carcinoma. Consensus clustering was used to identify distinct methylation regulator-related molecular subtypes. The prognostic DMS signature was constructed using principal components analysis. Most regulators experienced a low genomic variation, but we found a remarkably difference in mRNA expression of these regulators between normal and tumor tissues. Three distinct methylation regulator-related molecular subtypes were successfully identified according to the expression of 20 regulators, which had substantially different biological characteristics and prognosis. The classic carcinogenic pathways and stromal activity including TGF-beta, p53 and WNT signaling pathway were significantly activated in subtype B, leading to a survival inferiority in subtype B compared to other two subtypes. Further analysis demonstrated the constructed DMS signature was an independent predictive biomarker in patient prognosis. Two anti-checkpoint immunotherapy cohorts demonstrated patients with high DMS presented significantly improved treatment advantages and enhanced responses especially the survival prolonged. Generally, the high DMS groups improved more than 15% clinical response to immunotherapy than low DMS groups. In conclusion, this study identified three DNA methylation regulator-related subtypes with distinct clinical, molecular and biological characteristics, and constructed a prognostic and immunotherapeutic relevant gene signature. It might help to promote individualized immunotherapy for hepatocellular carcinoma from the perspective DNA methylation regulators.

Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma

BACKGROUND

At present, the diagnostic ability of hepatocellular carcinoma (HCC) based on serum alpha-fetoprotein level is limited. Finding markers that can effectively distinguish cancer and non-cancerous tissues is important for improving the diagnostic efficiency of HCC.

RESULTS

In this study, we developed a predictive model for HCC diagnosis using personalized biological pathways combined with a machine learning algorithm based on regularized regression and carry out relevant examinations. In two training sets, the overall cross-study-validated area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve and the Brier score of the diagnostic model were 0.987 [95%confidence interval (CI): 0.979-0.996], 0.981 and 0.091, respectively. Besides, the model showed good transferability in external validation set. In TCGA-LIHC cohort, the AUROC, AURPC and Brier score were 0.992 (95%CI: 0.985-0.998), 0.967 and 0.112, respectively. The diagnostic model has accomplished very impressive performance in distinguishing HCC from non-cancerous liver tissues. Moreover, we further analyzed the extracted biological pathways to explore molecular features and prognostic factors. The risk score generated from a 12-gene signature extracted from the characteristic pathways was correlated with some immune related pathways and served as an independent prognostic factor for HCC.

CONCLUSION

We used personalized biological pathways analysis and machine learning algorithm to construct a highly accurate HCC diagnostic model. The excellent interpretable performance and good transferability of this model enables it with great potential for personalized medicine, which can assist clinicians in diagnosis for HCC patients.

Molecular signatures of long-term hepatocellular carcinoma risk in nonalcoholic fatty liver disease

Prediction of hepatocellular carcinoma (HCC) risk is an urgent unmet need in patients with nonalcoholic fatty liver disease (NAFLD). In cohorts of 409 patients with NAFLD from multiple global regions, we defined and validated hepatic transcriptome and serum secretome signatures predictive of long-term HCC risk in patients with NAFLD. A 133-gene signature, prognostic liver signature (PLS)-NAFLD, predicted incident HCC over up to 15 years of longitudinal observation. High-risk PLS-NAFLD was associated with IDO1+ dendritic cells and dysfunctional CD8+ T cells in fibrotic portal tracts along with impaired metabolic regulators. PLS-NAFLD was validated in independent cohorts of patients with NAFLD who were HCC naïve (HCC incidence rates at 15 years were 22.7 and 0% in high- and low-risk patients, respectively) or HCC experienced (de novo HCC recurrence rates at 5 years were 71.8 and 42.9% in high- and low-risk patients, respectively). PLS-NAFLD was bioinformatically translated into a four-protein secretome signature, PLSec-NAFLD, which was validated in an independent cohort of HCC-naïve patients with NAFLD and cirrhosis (HCC incidence rates at 15 years were 37.6 and 0% in high- and low-risk patients, respectively). Combination of PLSec-NAFLD with our previously defined etiology-agnostic PLSec-AFP yielded improved HCC risk stratification. PLS-NAFLD was modified by bariatric surgery, lipophilic statin, and IDO1 inhibitor, suggesting that the signature can be used for drug discovery and as a surrogate end point in HCC chemoprevention clinical trials. Collectively, PLS/PLSec-NAFLD may enable NAFLD-specific HCC risk prediction and facilitate clinical translation of NAFLD-directed HCC chemoprevention.

A risk score model based on TGF-β pathway-related genes predicts survival, tumor microenvironment and immunotherapy for liver hepatocellular carcinoma

BACKGROUND

Transforming growth factor-beta (TGF-β) signal is an important pathway involved in all stages of liver hepatocellular carcinoma (LIHC) initiation and progression. Therefore, targeting TGF- β pathway may be a potential therapeutic strategy for LIHC. Prediction of patients' tumor cells response requires effective biomarkers.

METHODS

From 54 TGF-β-related genes, this research determined the genes showing the greatest relation to LIHC prognosis, and developed a risk score model with 8 TGF-β-related genes. The model divided LIHC patients from different datasets and platforms into low- and high-risk groups. Multivariate Cox regression analysis confirmed that the model was an independent prognostic factor for LIHC. The differences in genetic mutation, immune cell infiltration, biological pathway, response to immunotherapy or chemotherapy, and tumor microenvironment in LIHC samples showing different risks were analyzed.

RESULTS

Compared with low-risk group, in the training set and test set, high-risk group showed shorter survival, lower stromal score and higher M0 macrophages scores, regulatory T cells (Tregs), helper follicular T cells. Moreover, high-risk samples showed higher sensitivity to cisplatin, imatinib, sorafenib and salubrinal and pyrimethamine. High-risk group demonstrated a significantly higher Tumor Immune Dysfunction and Exclusion (TIDE) score, but would significantly benefit less from taking immunotherapy and was less likely to respond to immune checkpoint inhibitors.

CONCLUSIONS

In general, this work provided a risk scoring model based on 8 TGF-β pathway-related genes, which might be a new potential tool for predicting LIHC.

Integrative Analysis Identifies Cell-Type-Specific Genes Within Tumor Microenvironment as Prognostic Indicators in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, but effective early detection and prognostication methods are lacking.

Methods

The Cox regression model was built to stratify the HCC patients. The single-cell RNA sequencing data analysis and gene set enrichment analysis were employed to investigate the biological function of identified markers. PLCB1 gain- or loss-of-function experiments were performed, and obtained HCC samples were analyzed using quantitative real-time PCR and immunohistochemistry assay to validate the biological function of identified markers.

Results

In this study, we developed a model using optimized markers for HCC recurrence prediction. Specifically, we screened out 8 genes through a series of data analyses, and built a multivariable Cox model based on their expression. The risk stratifications using the Eight-Gene Cox (EGC) model were closely associated with the recurrence-free survivals (RFS) in both training and three validation cohorts. We further demonstrated that this risk stratification could serve as an independent predictor in predicting HCC recurrence, and that the EGC model could outperform other models. Moreover, we also investigated the cell-type-specific expression patterns of the eight recurrence-related genes in tumor microenvironment using single-cell RNA sequencing data, and interpreted their functional roles from correlation and gene set enrichment analyses, in vitro and in vivo experiments. Particularly, PLCB1 and SLC22A7 were predominantly expressed in malignant cells, and they were predicted to promote angiogenesis and to help maintain normal metabolism in liver, respectively. In contrast, both FASLG and IL2RB were specifically expressed in T cells, and were highly correlated with T cell marker genes, suggesting that these two genes might assist in maintaining normal function of T cell-mediated immune response in tumor tissues.

Conclusion

In conclusion, the EGC model and eight identified marker genes could not only facilitate the accurate prediction of HCC recurrence, but also improve our understanding of the mechanisms behind HCC recurrence.

Overexpressed SNRPB/D1/D3/E/F/G correlate with poor survival and immune infiltration in hepatocellular carcinoma

BACKGROUND

Prior reports have indicated that the abnormal expression of small nuclear ribonucleoproteins (snRNPs) genes is related to malignant tumors. However, in hepatocellular carcinoma (HCC), the precise role of snRNPs is not well understood. Therefore, the purpose of this study was to evaluate the prognostic roles of SNRPB/D1/D2/D3/E/F/G and their correlation to immune infiltration in HCC.

METHODS

The study was carried out via the following databases, software, and experimental validation: ONCOMINE, GEPIA2, UALCAN, The Cancer Genome Atlas, Gene Expression Omnibus, ArrayExpress, Kaplan-Meier plotter, cBioPortal, STRING, DAVID 6.8, TIMER, Cytoscape software, and immunohistochemistry experiments.

RESULTS

Overexpressed SNRPB/D1/D2/D3/E/F/G proteins were found in HCC tissues. The transcription levels of 7 snRNPs genes were related to the TP53 mutation and tumor grades. SNRPB/D1/D2/D3/F/G expression was significantly correlated with cancer staging, whereas SNRPE was not. Moreover, Kaplan-Meier survival analysis showed that upregulation of SNRPB/D1/D2/E/G was relevant to worse OS in HCC patients, especially in patients with alcohol consumption and those without viral hepatitis. Multivariate Cox regression analysis indicated that expression of SNRPB/D1/D3/E/F/G were independent prognostic factors for unfavorable OS in HCC. In addition, a high mutation rate of snRNPs genes (44%) was also found in HCC. The mRNA expression levels of snRNPs were meaningfully and positively related to six types of infiltrating immune cells (B cells, CD4⁺ T cells, CD8⁺ T cells, neutrophil, macrophage, and dendritic cells). Also, SNRPB/D1/G genes were significantly associated with molecular markers of various immune cells in HCC.

CONCLUSIONS

SNRPB/D1/D3/E/F/G are potential prognostic biomarkers for a short OS in HCC, and SNRPB/D1/G were novel immune therapy targets in HCC patients.

Evaluation of tumoral glypican 3 mRNA level as a diagnostic and prognostic biomarker for hepatitis-b virus-associated hepatocellular carcinoma by an integrative transcriptomic meta-analysis and bioinformatics

Aim: The aim of this study is to evaluate the potential of GPC3 mRNA level as a diagnostic and prognostic biomarker for HBV-associated HCC. Materials and Methods: GPC3 mRNA expression in HBV-associated HCC tumor tissues compared to matched adjacent tissues was evaluated by integrative transcriptomic meta-analysis. The results were validated in a different patient cohort and the possible associations between GPC3 mRNA level and the clinical variables were evaluated. Results: Transcriptomic data of HBV-associated HCC tissues (n=61) and matched adjacent tissues (n=61) from four datasets (GSE19665;GSE84402;GSE121248;GSE55092) were included in the meta-analysis. GPC3 mRNA level was found to be higher in tumors than adjacent tissues (fold change=12.88; p= 0;FDR=0). The result was validated in GSE14520, (HBV-associated HCC(n)=203; matched adjacent tissue(n)=203), (log-fold-change= 4.82; adj.p=1.43E-79). It was found that GPC3 mRNA level could distinguish HCC from adjacent tissues with high specificity and sensitivity (AUC=0.9108;95%CI=0.08792-0.9424;p

Identification of the Immune Subtype of Hepatocellular Carcinoma for the Prediction of Disease-Free Survival Time and Prevention of Recurrence by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data

Background

The main factors affecting the long-term prognosis of hepatocellular carcinoma (HCC) patients undergoing radical surgery are recurrence and metastasis. However, the methods for predicting disease-free survival (DFS) time and preventing postoperative recurrence of HCC are still very limited.

Methods

In this study, immune cell abundances in HCC samples were analyzed by single-sample gene set enrichment analysis (ssGSEA), while the prognostic values of immune cells for DFS time prediction were evaluated by the least absolute shrinkage and selection operator (LASSO) and subsequent univariate and multivariate Cox analyses. Next, a risk score was constructed based on the most prognostic immune cells and their corresponding coefficients. Interactions among prognostic immune cells and the specific targets for the prevention of recurrence were further identified by single-cell RNA (scRNA) sequencing data and CellMiner.

Results

A novel efficient T cell risk score (TCRS) was constructed based on data from the three most prognostic immune cell types (effector memory CD8 T cells, regulatory T cells and follicular helper T cells) for identifying an immune subtype of HCC patients with longer DFS times and inflammatory immune characteristics. Functional differences between the high- and low-score groups separated by TCRS were clarified, and the cell-cell communication among these immune cells was elucidated. Finally, fifteen hub genes that may be potential therapeutic targets for the prevention of recurrence were identified.

Conclusions

We constructed and verified a useful model for the prediction of DFS time of HCC after surgery. In addition, fifteen hub genes were identified as candidates for the prevention of recurrence, and a preliminarily investigation of potential drugs targeting these hub genes was carried out.

miR-579-3p Controls Hepatocellular Carcinoma Formation by Regulating the Phosphoinositide 3-Kinase-Protein Kinase B Pathway in Chronically Inflamed Liver

Chronic liver inflammation causes continuous liver damage with progressive liver fibrosis and cirrhosis, which may eventually lead to hepatocellular carcinoma (HCC). Whereas the 10-year incidence for HCC in patients with cirrhosis is approximately 20%, many of these patients remain tumor free for their entire lives. Clarifying the mechanisms that define the various outcomes of chronic liver inflammation is a key aspect in HCC research. In addition to a wide variety of contributing factors, microRNAs (miRNAs) have also been shown to be engaged in promoting liver cancer. Therefore, we wanted to characterize miRNAs that are involved in the development of HCC, and we designed a longitudinal study with formalin-fixed and paraffin-embedded liver biopsy samples from several pathology institutes from Switzerland. We examined the miRNA expression by nCounterNanostring technology in matched nontumoral liver tissue from patients developing HCC (n = 23) before and after HCC formation in the same patient. Patients with cirrhosis (n = 26) remaining tumor free within a similar time frame served as a control cohort. Comparison of the two cohorts revealed that liver tissue from patients developing HCC displayed a down-regulation of miR-579-3p as an early step in HCC development, which was further confirmed in a validation cohort. Correlation with messenger RNA expression profiles further revealed that miR-579-3p directly attenuated phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) expression and consequently protein kinase B (AKT) and phosphorylated AKT. In vitro experiments and the use of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology confirmed that miR-579-3p controlled cell proliferation and cell migration of liver cancer cell lines. Conclusion: Liver tissues from patients developing HCC revealed changes in miRNA expression. miR-579-3p was identified as a novel tumor suppressor regulating phosphoinositide 3-kinase-AKT signaling at the early stages of HCC development.

E2F1 promotes Warburg effect and cancer progression via upregulating ENO2 expression in Ewing sarcoma

Altered glucose metabolism is an important characteristic of cancer cells, which is referred to as Warburg effect or aerobic glycolysis. Ewing sarcoma (EWS) is a highly malignant tumor that occurs in children and adolescents. However, the functions of aerobic glycolysis in EWS remain to be elucidated. The present study identified a transcription factor, E2F transcription factor 1 (E2F1), as a new regulator of cancer the aerobic glycolysis and progression in EWS. The present study showed that E2F1 modulated aerobic glycolysis in EWS cells by effecting glucose uptake, lactate production and ATP generation. Altered E2F1 expression increased or decreased cell viability and invasion in EWS. Mechanistically, the results demonstrated that E2F1 may promote the Warburg effect and cancer progression in EWS via upregulating enolase 2 expression. Generally, these findings indicated that E2F1 involvement in the progression of EWS and could serve as a clinical therapeutic target in EWS.

Comprehensive Molecular Analyses of a Macrophage-Related Gene Signature With Regard to Prognosis, Immune Features, and Biomarkers for Immunotherapy in Hepatocellular Carcinoma Based on WGCNA and the LASSO Algorithm

Macrophages have been reported to exert a crucial role in hepatocellular carcinoma (HCC). This study aimed to explore the macrophage-related genes and establish a macrophage-related signature (MRS) model to predict the overall survival (OS) of patients with HCC based on these genes’ expression. We screened the macrophage-related gene module by weighted gene coexpression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO) Cox regression analysis was utilized for further selection, and the selected genes were entered into stepwise regression to develop the MRS model, which was further validated in the Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC) datasets. We analyzed the biological phenotypes associated with macrophages in terms of functional enrichment, tumor immune signature, and tumor mutational signature. The patient’s response to immunotherapy was inferred by the tumor immune dysfunction and exclusion (TIDE) score, the immunophenotype score (IPS), and the IMvigor210 dataset. A novel MRS model was established based on the LASSO regression coefficients of the genes PON1, IL15RA, NEIL3, HILPDA, PFN2, HAVCR1, ANXA10, CDCA8, EPO, S100A9, TTK, KLRB1, SPP1, STC2, CYP26B1, GPC1, G6PD, and CBX2. In either dataset, MRS was identified as an independent risk factor for OS in HCC patients. Additionally, our research indicated that a high-risk score in the MRS model was significantly correlated with tumor staging, pathological grade, tumor–node–metastasis (TNM) stage, and survival. Several genes of the human leukocyte antigen (HLA) family and immune checkpoints were highly expressed in the high-risk group. In addition, the frequency of tumor mutations was also higher in the high-risk group. According to our analyses, a higher risk score in the MRS model may predict a better response to immunotherapy.

NAP1L1 Functions as a Novel Prognostic Biomarker Associated With Macrophages and Promotes Tumor Progression by Influencing the Wnt/β-Catenin Pathway in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is regarded as one of the universal cancers in the world. Therefore, our study is based on clinical, molecular mechanism and immunological perspectives to analyze how NAP1L1 affects the progression of HCC. To begin with, the gene expression datasets and clinical data of GSE14520, GSE76427, ICGC, and TCGA are originated from GEO, ICGC, and TCGA databases. Subsequently, DEG screening was performed on data using R studio, and we finally found that 2,145 overlapping DEGs were screened from four datasets at the end. Then, we used R studio to filter the survival-related genes of the GSE76427 and ICGC datasets, and we screened out 101 survival-related genes. Finally, 33 common genes were screened out from 2,145 overlapping DEGs and 101 survival-related genes. Then, NAP1L1 was screened from 33 common genes using the CytoHubba plug-in in Cytoscape software. Furthermore, ground on GEO, ICGC, and TCGA databases, the survival analysis, clinical feature analysis, univariate/multivariate regression analysis, and multiple GSEA were used to study NAP1L1. The Conclusion claimed that HCC patients with higher expression levels of NAP1L1 had a poorer prognosis than those with lower expression levels. Thus, we believe that NAP1L1 is an independent prognostic factor for HCC. In order to shed light on NAP1L1’s molecular mechanism promoting the progression of HCC closely, the GSEA tool was applied to complete the GSEA of the four datasets. Furthermore, the results confirmed that NAP1L1 could promote HCC progression by regulating the G2/M transition of the cell cycle and Wnt signaling pathway. Western blot and flow cytometry were also performed to understand those mechanisms in this study. The result of Western blot showed that NAP1L1 silencing led to downregulation of CDK1 and β-catenin proteins; the result of flow cytometry showed that cell numbers in the G2 phase were significantly increased when NAP1L1 was silenced. Thus, we claimed that NAP1L1 might promote HCC progression by activating the Wnt signaling pathway and promoting cell cycle G2/M transition. In addition, ground on GSE14520 and GSE76427 datasets, and ICGC and TCGA databases, the correlation between NAP1L1 and immune cells was analyzed in HCC patients. At the same time, the TISIDB online database and the TIMER online database were testified to the association between NAP1L1 and immune cells. Hence, the summary shows that NAP1L1 was connected with a certain amount of immune cells. We can speculate that NAP1L1 may influence macrophages to promote HCC progression through some potential mechanisms.

Single-Cell RNA-seq Analysis Reveals Dysregulated Cell-Cell Interactions in a Tumor Microenvironment Related to HCC Development

The heterogeneity of tumor microenvironment (TME) of hepatocellular carcinoma (HCC) may relate to cell-cell interaction event (CCE) dysregulation and would affect therapeutic responses and clinical outcomes. To reveal the differentiation of CCEs in the liver tissue from healthy donors (HD) to HCC, scRNA-seq data of ~62000 cells from HD, paracancerous nontumor tissue (NT), and HCC were analyzed. The microenvironmental CCE landscape was constructed. Dysregulated cell types and changed molecular functions were identified with CCE alterations in HCC. Dysregulated CCEs which function as pivotal roles in tumorigenesis and development of HCC included SPP1-CD44, MIF-TNFRSF14, and VEGFA-NRP1. A CCE-based immune regulatory network was extracted to illustrate the mechanism of TME dysregulation. A prognostic signature based on CCE genes was identified and validated in independent datasets. Our study provided insights into the characteristics of the cross-talk between tumor cells and microenvironment in HCC and established a workflow strategy for CCE analyses based on scRNA-seq data.

Identifying common transcriptome signatures of cancer by interpreting deep learning models

Background

Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types.

Results

Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer.

Conclusions

Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13059-022-02681-3).

Human liver single nucleus and single cell RNA sequencing identify a hepatocellular carcinoma-associated cell-type affecting survival

BACKGROUND

Hepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival.

METHODS

We combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort (n = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort (n = 1 non-HCC, n = 14 HCC-tumor, and n = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort (n = 3 HCC-tumor and n = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients' tumor (n = 361) and adjacent non-tumor tissue (n = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University.

RESULTS

We discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC.

CONCLUSIONS

By integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.

NUF2 Is a Potential Immunological and Prognostic Marker for Non-Small-Cell Lung Cancer

Background

Globally, non-small-cell lung cancer (NSCLC) is one of the most prevalent tumors. Various studies have investigated its etiology, but the molecular mechanism of NSCLC has not been elucidated.

Methods

The GSE19804, GSE118370, GSE19188, GSE27262, and GSE33532 microarray datasets were obtained from the Gene Expression Omnibus (GEO) database for the identification of genes involved in NSCLC development as well as progression. Then, the identified differentially expressed genes (DEGs) were subjected to functional enrichment analyses. The protein-protein interaction (PPI) network was built after which module analysis was conducted via the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. There were 562 DEGs: 98 downregulated genes and 464 upregulated. These DEGs were established to be enriched in p53 signaling pathway, transendothelial leukocyte migration, cell adhesion molecules, contractions of vascular smooth muscles, coagulation and complement cascades, and axon guidance. Assessment of tumor immunity was performed to determine the roles of hub genes.

Results

There were 562 dysregulated genes, while 12 genes were hub genes. NUF2 was established to be a candidate immunotherapeutic target with potential clinical implications. The 12 hub genes were highly enriched in the p53 signaling pathway, the cell cycle, progesterone-associated oocyte maturation, cellular senescence, and oocyte meiosis. Survival analysis showed that NUF2 is associated with NSCLC occurrence, invasion, and recurrence.

Conclusion

The NUF2 gene discovered in this study helps us clarify the pathomechanisms of NSCLC occurrence as well as progression and provides a potential diagnostic and therapeutic target for NSCLC.

A Prognosis Marker Dynein Cytoplasmic 1 Heavy Chain 1 Correlates with EMT and Immune Signature in Liver Hepatocellular Carcinoma by Bioinformatics and Experimental Analysis

Background

Liver hepatocellular carcinoma (LIHC) has had a continuous increase in incidence and mortality rates over the last 40 years. Dynein Cytoplasmic 1 Heavy Chain 1 (DYNC1H1) is a protein coding gene which encodes the cytoplasmic dynein heavy chain family. This is the first investigation into the expression of DYNC1H1 and its mechanisms of action in LIHC patients.

Methods

Based on the DYNC1H1 expression data from the TCGA database, we performed the DYNC1H1 expression, clinicopathological data, gene enrichment, and immune infiltration analysis. TIMER and CIBERSORT were used to assess immune responses of DYNC1H1 in LIHC. GEPIA, K-M survival analysis, and immunohistochemical staining pictures from the THPA were used to validate the results. In order to evaluate the diagnostic value of DYNC1H1, GEO datasets were analyzed by using ROC analysis. And quantitative real-time polymerase chain reaction was also carried out to evaluate the expression of DYNC1H1.

Results

DYNC1H1 expression levels were associated with T classification, pathologic stage, histologic grade, and serum AFP levels. DYNC1H1 is an independent factor for a poor prognosis in patients with LIHC. Further study showed that high expression of DYNC1H1 was enriched in epithelial-mesenchymal transition (EMT) and the TGF β signaling pathway by GSEA analysis enrichment, indicating that DYNC1H1 might play a key role in the progression of CRC through EMT and immune response, which also had been validated by the experimental assays.

Conclusions

DYNC1H1 will provide a novel and important perspective for the mechanisms of LIHC by regulating EMT. This gene will be able to act as an efficacious tool for the early diagnosis and effective intervention of LIHC.

Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis

The human Six-Transmembrane Epithelial Antigen of the Prostate (STEAP) family comprises STEAP1-4. Several studies have pointed out STEAP proteins as putative biomarkers, as well as therapeutic targets in several types of human cancers, particularly in prostate cancer. However, the relationships and significance of the expression pattern of STEAP1-4 in cancer cases are barely known. Herein, the Oncomine database and cBioPortal platform were selected to predict the differential expression levels of STEAP members and clinical prognosis. The most common expression pattern observed was the combination of the over- and underexpression of distinct STEAP genes, but cervical and gastric cancer and lymphoma showed overexpression of all STEAP genes. It was also found that STEAP genes’ expression levels were already deregulated in benign lesions. Regarding the prognostic value, it was found that STEAP1 (prostate), STEAP2 (brain and central nervous system), STEAP3 (kidney, leukemia and testicular) and STEAP4 (bladder, cervical, gastric) overexpression correlate with lower patient survival rate. However, in prostate cancer, overexpression of the STEAP4 gene was correlated with a higher survival rate. Overall, this study first showed that the expression levels of STEAP genes are highly variable in human cancers, which may be related to different patients’ outcomes.

PET-Based Radiogenomics Supports mTOR Pathway Targeting for Hepatocellular Carcinoma

PURPOSE

This work aimed to explore in depth the genomic and molecular underpinnings of hepatocellular carcinoma (HCC) with increased 2[18F]fluoro-2-deoxy-d-glucose (FDG) uptake in PET and to identify therapeutic targets based on this imaging-genomic surrogate.

EXPERIMENTAL DESIGN

We used RNA sequencing and whole-exome sequencing data obtained from 117 patients with HCC who underwent hepatic resection with preoperative FDG-PET/CT imaging as a discovery cohort. The primary radiogenomic results were validated with transcriptomes from a second cohort of 81 patients with more advanced tumors. All patients were allocated to an FDG-avid or FDG-non-avid group according to the PET findings. We also screened potential drug candidates targeting FDG-avid HCCs in vitro and in vivo.

RESULTS

High FDG avidity conferred worse recurrence-free survival after HCC resection. Whole transcriptome analysis revealed upregulation of mTOR pathway signals in the FDG-avid tumors, together with higher abundance of associated mutations. These clinical and genomic findings were replicated in the validation set. A molecular signature of FDG-avid HCCs identified in the discovery set consistently predicted poor prognoses in the public-access datasets of two cohorts. Treatment with an mTOR inhibitor resulted in decreased FDG uptake followed by effective tumor control in both the hyperglycolytic HCC cell lines and xenograft mouse models.

CONCLUSIONS

Our PET-based radiogenomic analysis indicates that mTOR pathway genes are markedly activated and altered in HCCs with high FDG retention. This nuclear imaging biomarker may stimulate umbrella trials and tailored treatments in precision care of patients with HCC.

Human constitutive androstane receptor represses liver cancer development and hepatoma cell proliferation by inhibiting erythropoietin signaling

The constitutive androstane receptor (CAR) is a nuclear receptor that plays a crucial role in regulating xenobiotic metabolism and detoxification, energy homeostasis, and cell proliferation by modulating the transcription of numerous target genes. CAR activation has been established as the mode of action by which phenobarbital-like nongenotoxic carcinogens promote liver tumor formation in rodents. This paradigm, however, appears to be unrelated to the function of human CAR (hCAR) in hepatocellular carcinoma (HCC), which remains poorly understood. Here, we show that hCAR expression is significantly lower in HCC than that in adjacent nontumor tissues and, importantly, reduced hCAR expression is associated with a worse HCC prognosis. We also show overexpression of hCAR in human hepatoma cells (HepG2 and Hep3B) profoundly suppressed cell proliferation, cell cycle progression, soft-agar colony formation, and the growth of xenografts in nude mice. RNA-Seq analysis revealed that the expression of erythropoietin (EPO), a pleiotropic growth factor, was markedly repressed by hCAR in hepatoma cells. Addition of recombinant EPO in HepG2 cells partially rescued hCAR-suppressed cell viability. Mechanistically, we showed that overexpressing hCAR repressed mitogenic EPO-EPO receptor signaling through dephosphorylation of signal transducer and activator of transcription 3, AKT, and extracellular signal-regulated kinase 1/2. Furthermore, we found that hCAR downregulates EPO expression by repressing the expression and activity of hepatocyte nuclear factor 4 alpha, a key transcription factor regulating EPO expression. Collectively, our results suggest that hCAR plays a tumor suppressive role in HCC development, which differs from that of rodent CAR and offers insight into the hCAR-hepatocyte nuclear factor 4 alpha-EPO axis in human liver tumorigenesis.

A Molecular Hepatocellular Carcinoma Prognostic Score System Precisely Predicts Overall Survival of Hepatocellular Carcinoma Patients

BACKGROUND AND AIMS

With high rates of recurrence post-treatment, hepatocellular carcinoma (HCC) is one of the most common types of cancer worldwide and the major cause of cancer death. To improve the overall survival of HCC patients, identification of a reliable biomarker and precise early diagnosis of HCC remain major unsolved problems.

METHODS

We initially screened data from the Cancer Genome Atlas liver cancer cohort to identify potential prognosis-related genes. Then, a meta-analysis of five international HCC cohorts was implemented to validate such genes. Subsequently, artificial intelligence models (random forest and neural network) were trained to predict prognosis accurately, and a log-rank test was performed for validation. Finally, the correlation between the molecular hepatocellular carcinoma prognostic score (mHPS) and the stromal and immune scoring in HCC were explored.

RESULTS

A comprehensive list of 65 prognosis-related genes was obtained, most of which have been not extensively studied thus far. A universal HCC mHPS system depending on the expression pattern of only 23 genes was established. The mHPS system had general applicability to HCC patients (log-rank p<0.05) in a platform-independent manner (RNA sequencing or microarray). The mHPS was also correlated with the stromal and immune scoring in HCC, reflecting the status of the tumor immune microenvironment.

CONCLUSIONS

Overall, the mHPS is an easy and cost-effective prognosis predicting system, which can disclose previously uncovered heterogeneity among patient subpopulations. The mHPS system can further stratify patients who are at the same clinical stage and should be valuable for precise treatment. Moreover, the prognosis-related genes recognized in this study have potential in targeted and immune therapy.

Uncovering N4-Acetylcytidine-Related mRNA Modification Pattern and Landscape of Stemness and Immunity in Hepatocellular Carcinoma

N4-acetylcytidine (ac4C) is an ancient and conserved RNA modification. Previously, ac4C mRNA modification has been reported promoting proliferation and metastasis of tumor cells. However, it remains unclear whether and how ac4C-related mRNA modification patterns influencing the prognosis of hepatocellular carcinoma (HCC) patients. Hereby, we constructed an ac4Cscore model and classified patients into two groups and investigated the potential intrinsic and extrinsic characteristics of tumor. The ac4Cscore model, including COL15A1, G6PD and TP53I3, represented ac4C-related mRNA modification patterns in HCC. According to ac4Cscore, patients were stratified to high and low groups with distinct prognosis. Patients subject to high group was related to advanced tumor stage, higher TP53 mutation rate, higher tumor stemness, more activated pathways in DNA-repair system, lower stromal score, higher immune score and higher infiltrating of T cells regulatory. While patients attributed to low group were correlated with abundance of T cells CD4 memory, less aggressive immune subtype and durable therapy benefit. We also found ac4Cscore as a novel marker to predict patients’ prognosis with anti-PD1 immunotherapy and/or mTOR inhibitor treatment. Our study for the first time showed the association between ac4C-related mRNA modification patterns and tumor intrinsic and extrinsic characteristics, thus influencing the prognosis of patients.

Identification of a Tumor Immunological Phenotype-Related Gene Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the predominant subtype of primary liver cancer and represents a highly heterogeneous disease, making it hard to predict the prognosis and therapy efficacy. Here, we established a novel tumor immunological phenotype-related gene index (TIPRGPI) consisting of 11 genes by Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to predict HCC prognosis and immunotherapy response. TIPRGPI was validated in multiple datasets and exhibited outstanding performance in predicting the overall survival of HCC. Multivariate analysis verified it as an independent predictor and a TIPRGPI-integrated nomogram was constructed to provide a quantitative tool for clinical practice. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in tumor microenvironment were shown between the TIPRGPI high and low-risk groups. Notably, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade (ICB) therapy of the low-risk group. Besides, six potential drugs binding to the core target of the TIPRGPI signature were predicted via molecular docking. Taken together, our study shows that the proposed TIPRGPI was a reliable signature to predict the risk classification, immunotherapy response, and drugs candidate with potential application in the clinical decision and treatment of HCC. The novel "TIP genes"-guided strategy for predicting the survival and immunotherapy efficacy, we reported here, might be also applied to more cancers other than HCC.

B4GALT5 high expression associated with poor prognosis of hepatocellular carcinoma

BACKGROUND

B4GALT5 is postulated to be an important protein in sugar metabolism that catalyzes the synthesis of lactosylceramide (LacCer). However, its role in hepatocellular carcinoma (HCC) remains unknown.

METHOD

We characterized the expression of B4GALT5 in HCC tissue compared to normal tissue, and explored its function of B4GALT5 in HCC by enrichment analysis based on its co-expressed gene set. Next, we checked whether B4GALT5 expression is correlated to immune infiltration level and clinical prognosis in hepatocellular carcinoma. Finally, we verified the expression of B4GALT5 using clinical samples evaluated by RT-PCR, and conducted in vitro experiments with B4GALT5-knockdown HCC cells to investigate the function of B4GALT5 in the HCC cell proliferation, migration and invasion.

RESULTS

We found B4GALT5 mRNA and protein expression levels were significantly high in HCC tissue compared to normal tissue. The enrichment analysis of the gene sets that co-expressed with B4GALT5 showed specificity in HCC-related pathways and functions. Also, the expression pattern of B4GALT5 was significantly related to the immune infiltration level, especially CD4+ T cell and macrophage cells. B4GALT5 higher mRNA expression was associated with poor overall survival (OS) in HCC patients. Furthermore, In vitro experiments showed that depletion of B4GALT5 significantly inhibited HCC cell proliferation, migration and invasion. This study revealed the function and its mediated pathways of B4GALT5 in HCC, indicating that B4GALT5 may serve as a prognostic biomarker of HCC.

Analysis of the expression and prognosis for leukocyte immunoglobulin-like receptor subfamily B in human liver cancer

Background

Leukocyte immunoglobulin-like receptor subfamily B (LILRB), including 5 subtypes, is a group of inhibitory receptors in the immune system. The LILRB family is known to be involved in the tumor progression of various cancer types, especially liver cancer. However, the expression patterns and prognostic values of LILRB family members in liver cancer tissues remain unclear.

Methods

We used the Oncomine database, GEPIA database, Kaplan–Meier Plotter, Timer, and TISIDB to assess the expression and prognostic value of the LILRB family in liver cancer patients. We also verified the expression of the LILRB family in tumor tissues and tumor-free liver tissues at the protein level by using immunohistochemistry. The STRING website was used to explore the interaction between the LILRB family and their related genes. The DAVID database was used to perform the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Flow cytometry was used to assess the infiltrated NK cells in liver cancer tissues.

Results

Our study revealed that the mRNA expression of LILRB1, LILRB2, LILRB3, and LILRB5 was downregulated, while compared with normal tissues, the mRNA expression of LILRB4 was upregulated in liver cancer tissues. Survival analysis revealed that LILRB2 and LILRB5 mRNA expression levels were significantly positively associated with overall survival (OS) and disease-free survival (DSS) and that the mRNA expression of all LILRB family members was significantly positively correlated with recurrence-free survival (RFS) and progression-free survival (PFS). Next, we further found that the mRNA expression of all LILRB family members was significantly associated with the infiltration of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells in liver cancer. Finally, GO and KEGG analyses found that the LILRB family and its related genes were involved in antigen processing and presentation and natural killer cell-mediated cytotoxicity pathways.

Conclusions

Our study suggested that LILRB family expression was associated with the prognosis of liver cancer patients and infiltrated immune cells. The LILRB family might be involved in antigen processing and presentation and natural killer cell-mediated cytotoxicity pathways.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02562-w.

Identification of CCL20 and LCN2 as Efficient Serological Tools for Detection of Hepatocellular Carcinoma

Objectives

To discover a more powerful diagnostic tool for the detection of hepatocellular carcinoma (HCC).

Methods

16 extracellularly located candidates were selected by analyzing the expression array datasets in GEO. 10 of them were validated in clinical samples by ELISA. Differences of each variable were compared by one-way ANOVA or Kruskal-Wallis test. CCL20 and LCN2 were determined in all samples (HCC, 167; liver cirrhosis, 106; and healthy control, 106) and finally chosen for the construction of the combination model by binary logistic regression. The models were first built using a comprehensive control, including both liver cirrhosis (LC) and healthy donors. Then, the models were rebuilt by using the LC group alone as a control. ROC analysis was performed to compare the diagnostic efficiency of each indicator.

Results

Levels of CCL20 and LCN2 in HCC sera were significantly higher than those in all controls. Using the comprehensive control, ROC curves showed that the optimum diagnostic cutoff of the CCL20 and LCN2 combination was 0.443 (area under curve (AUC) of 0.927 (95% CI 0.896-0.951), sensitivity of 0.808, specificity of 0.892, and accuracy of 0.859). For detection of HCC from LC control, the optimum diagnostic cutoff was 0.590 (AUC of 0.919 (95% CI 0.880-0.948), sensitivity of 0.814, specificity of 0.868, and accuracy of 0.834). Furthermore, the model maintained diagnostic accuracy for patients with HCC in the early stage, with the sensitivity and specificity of 0.75 and 0.77 from LC control, yet the AFP only reached 0.5 and 0.67, respectively.

Conclusion

A combination model composed of CCL20 and LCN2 may serve as a more efficient tool for distinguishing HCC from nonmalignant liver diseases.

Molecular Characterization of Differentiated-Resistance MSC Subclones by Single-Cell Transcriptomes

Background: The mechanism of tumorigenicity potentially evolved in mesenchymal stem cells (MSCs) remains elusive, resulting in inconsistent clinical application efficacy. We hypothesized that subclones in MSCs contribute to their tumorgenicity, and we approached MSC-subclones at the single-cell level. Methods: MSCs were cultured in an osteogenic differentiation medium and harvested on days 12, 19, and 25 for cell differentiation analysis using Alizarin Red and followed with the single-cell transcriptome. Results: Single-cell RNA-seq analysis reveals a discrete cluster of MSCs during osteogenesis, including differentiation-resistant MSCs (DR-MSCs), differentiated osteoblasts (DO), and precursor osteoblasts (PO). The DR-MSCs population resembled cancer initiation cells and were subjected to further analysis of the yes associated protein 1 (YAP1) network. Verteporfin was also used for YAP1 inhibition in cancer cell lines to confirm the role of YAP1 in MSC--involved tumorigenicity. Clinical data from various cancer types were analyzed to reveal relationships among YAP1, OCT4, and CDH6 in MSC--involved tumorigenicity. The expression of cadherin 6 (CDH6), octamer-binding transcription factor 4 (OCT4), and YAP1 expression was significantly upregulated in DR-MSCs compared to PO and DO. YAP1 inhibition by Verteporfin accelerated the differentiation of MSCs and suppressed the expression of YAP1, CDH6, and OCT4. A survey of 56 clinical cohorts revealed a high degree of co-expression among CDH6, YAP1, and OCT4 in various solid tumors. YAP1 inhibition also down-regulated HeLa cell viability and gradually inhibited YAP1 nuclear localization while reducing the transcription of CDH6 and OCT4. Conclusions: We used single-cell sequencing to analyze undifferentiated MSCs and to discover a carcinogenic pathway in single-cell MSCs of differentiated resistance subclones.

The role of RNA binding proteins in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of overall cancer deaths worldwide with limited therapeutic options. Due to the heterogeneity of HCC pathogenesis, the molecular mechanisms underlying HCC development are not fully understood. Emerging evidence indicates that RNA-binding proteins (RBPs) play a vital role throughout hepatocarcinogenesis. Thus, a deeper understanding of how RBPs contribute to HCC progression will provide new tools for early diagnosis and prognosis of this devastating disease. In this review, we summarize the tumor suppressive and oncogenic roles of RBPs and their roles in hepatocarcinogenesis. The diagnostic and therapeutic potential of RBPs in HCC, including their limitations, are also discussed.

Acyl-CoA Binding Domain Containing 4 Polymorphism rs4986172 and Expression Can Serve as Overall Survival Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients After Hepatectomy

Background

The aim of our study was to evaluate the potential of expression and single nucleotide polymorphism of Acyl-CoA binding domain containing 4 (ACBD4) gene as prognosis biomarkers in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after hepatectomy.

Methods

HBV-related HCC patients from the First Affiliated Hospital of Guangxi Medical University and GSE14520 were included in the current study, as well as The Cancer Genome Atlas (TCGA) HCC verification cohort. Prognostic analysis and multiple functional enrichment analysis methods were used to evaluate the prognostic value and potential biological functions of the ACBD4 gene in HBV-related HCC.

Results

We found that ACBD4 gene is highly expressed in normal liver tissues and markedly down-regulated in HBV-related HCC tissues. ACBD4 gene was significantly related to overall survival (OS) of HCC in TCGA and GSE14520 cohorts, and patients with low ACBD4 expression were markedly related to poor OS. Rs4986172 was observed as an OS biomarker after hepatectomy in the Guangxi HBV-related HCC cohort. The OS of rs4986172 GG genotype was worse than that of HCC patients with A allele (AA and AG genotypes). Multifunctional enrichment analysis suggested that ACBD4 gene is closely related to the metabolic, peroxisome proliferator-activated receptor and cytochrome P450 pathway. Through connectivity map, we also identified eight compounds that may be used as targeted therapeutic agents for ACBD4 gene in HBV-related HCC; these compounds were scopoletin, alfaxalone, bephenium hydroxynaphthoate, apramycin, 4,5-dianilinophthalimide, DL-thiorphan, aminohippuric acid and quinidine. Immune microenvironment analysis revealed that there were significant differences in immune scores of HBV-related HCC tumor tissues with different ACBD4 expression levels.

Conclusion

Our study reveals that ACBD4 expression and rs4986172 can be serve as biomarkers of OS in HBV-related HCC patients after hepatectomy.

Down-regulation of TRPV6 Is Associated With Adverse Prognosis in Hepatocellular Carcinoma Treated With Curative Resection

BACKGROUND/AIM

Transient receptor potential vanilloid 6 (TRPV6), an endothelial Ca2+-selective entry channel, is expressed in various cancer types, and a selective TRPV6 inhibitor is currently being investigated in a clinical trial. However, TRPV6 expression in hepatocellular carcinoma (HCC) has not been reported.

MATERIALS AND METHODS

We evaluated TRPV6 expression in 219 cases of HCC and analyzed its association with clinicopathological parameters and prognostic significance. TRPV6 mRNA expression was compared between HCC and non-tumor liver tissues using various public datasets, and its prognostic effect was examined in The Cancer Genome Atlas (TCGA) cohort.

RESULTS

Low TRPV6 expression was found in 37.4% of patients, which was significantly associated with adverse histologic features, and patients with low TRPV6 expression had shorter recurrence-free and disease-free survival. TRPV6 mRNA expression was consistently lower in HCC compared to non-tumor liver samples in public datasets, at the whole tissue level as well as single-cell level. Patients with low TRPV6 expression in the TCGA cohort had shorter progression-free survival.

CONCLUSION

TRPV6 expression is down-regulated in HCCs and associated with a poor prognosis. TRPV6 may be a prognostic biomarker in HCC.