Sleeping Beauty insertional mutagenesis screen identifies the pro-metastatic roles of CNPY2 and ACTN2 in hepatocellular carcinoma tumor progression

Sorafenib Resistance Contributed by IL7 and MAL2 in Hepatocellular Carcinoma Can Be Overcome by Autophagy-Inducing Stapled Peptides

Drug resistance poses a great challenge in systemic therapy for hepatocellular carcinoma (HCC). However, the underlying molecular mechanisms associated with resistance to anti-cancer drugs, such as Sorafenib, remain unclear. In this study, we use transposon insertional mutagenesis to generate Sorafenib-resistant HCC cell lines in order to identify potential drug resistant causative genes. Interleukin 7 (IL7) and mal, T cell differentiation protein 2 (MAL2) were identified as candidate genes that promote survival by activating JAK/STAT and PI3K/AKT signaling pathways. Sorafenib-resistant cells exhibited higher clonogenic survival and lower drug sensitivity due to IL7 and MAL2 upregulation. Higher anti-apoptotic effect, clonogenic survival and increased PI3K/AKT/STAT3 activities were observed in IL7 and MAL2 co-overexpressing cells compared with controls or cells overexpressing IL7 or MAL2 individually. Given the critical role of MAL2 in endocytosis, we propose that MAL2 might facilitate the endocytic trafficking of IL7 and its cognate receptors to the plasma membrane, which leads to upregulated JAK/STAT and PI3K/AKT signaling pathways and Sorafenib resistance. Additionally, our previous studies showed that an autophagy-inducing stapled peptide promoted the endolysosomal degradation of c-MET oncogene and overcame adaptive Sorafenib resistance in c-MET+ HCC cells. In this study, we demonstrate that these stapled peptides readily induced autophagy and inhibited the proliferation of both wild-type and Sorafenib-resistant HCC cells co-overexpressing both IL7 and MAL2. Furthermore, these peptides showed synergistic cytotoxicity with Sorafenib in drug-resistant HCC cells co-overexpressing both IL7 and MAL2. Our studies suggest that targeting autophagy may be a novel strategy to overcome IL7/MAL2-mediated Sorafenib resistance in HCC.

Recent Insights into the Biomarkers, Molecular Targets and Mechanisms of Non-Alcoholic Steatohepatitis-Driven Hepatocarcinogenesis

Non-alcoholic fatty liver disease (NAFLD) or metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (NASH) are chronic hepatic conditions leading to hepatocellular carcinoma (HCC) development. According to the recent "multiple-parallel-hits hypothesis", NASH could be caused by abnormal metabolism, accumulation of lipids, mitochondrial dysfunction, and oxidative and endoplasmic reticulum stresses and is found in obese and non-obese patients. Recent translational research studies have discovered new proteins and signaling pathways that are involved not only in the development of NAFLD but also in its progression to NASH, cirrhosis, and HCC. Nevertheless, the mechanisms of HCC developing from precancerous lesions have not yet been fully elucidated. Now, it is of particular importance to start research focusing on the discovery of novel molecular pathways that mediate alterations in glucose and lipid metabolism, which leads to the development of liver steatosis. The role of mTOR signaling in NASH progression to HCC has recently attracted attention. The goals of this review are (1) to highlight recent research on novel genetic and protein contributions to NAFLD/NASH; (2) to investigate how recent scientific findings might outline the process that causes NASH-associated HCC; and (3) to explore the reliable biomarkers/targets of NAFLD/NASH-associated hepatocarcinogenesis.

Induction of filopodia formation by α-Actinin-2 via RelA with a feedforward activation loop promoting overt bone marrow metastasis of gastric cancer

BACKGROUND

Bone marrow metastasis (BMM) is underestimated in gastric cancer (GC). GC with BMM frequently complicate critical hematological abnormalities like diffused intravascular coagulation and microangiopathic hemolytic anemia, which constitute a highly aggressive GC (HAGC) subtype. HAGC present a very poor prognosis with peculiar clinical and pathological features when compared with not otherwise specified advanced GC (NAGC). But the molecular mechanisms underlying BMM from GC remain rudimentary.

METHODS

The transcriptomic difference between HAGC and NAGC were analyzed. Genes that were specifically upregulated in HAGC were identified, and their effect on cell migration and invasion was studied. The function of ACTN2 gene were confirmed by GC cell lines, bone-metastatic animal model and patients' tissues. Furthermore, the molecular mechanism of ACTN2 derived-BMM was explored by multiple immunofluorescence staining, western blot, chromatin immunoprecipitation, and luciferase reporter assays.

RESULTS

We elucidated the key mechanisms of BMM depending on the transcriptomic difference between HAGC and NAGC. Five genes specifically upregulated in HAGC were assessed their effect on cell migration and invasion. The ACTN2 gene encoding protein α-Actinin-2 was detected enhanced the metastatic capability and induced BMM of GC cells in mouse models. Mechanically, α-Actinin-2 was involved in filopodia formation where it promoted the Actin filament cross-linking by replacing α-Actinin-1 to form α-Actinin-2:α-Actinin-4 complexes in GC cells. Moreover, NF-κB subunit RelA and α-Actinin-2 formed heterotrimers in the nuclei of GC cells. As a direct target of RelA:α-Actinin-2 heterotrimers, the ACTN2 gene was a positive auto-regulatory loop for α-Actinin-2 expression.

CONCLUSIONS

We demonstrated a link between filopodia, BMM and ACTN2 activation, where a feedforward activation loop between ACTN2 and RelA is established via actin in response to distant metastasis. Given the novel filopodia formation function and the new mechanism of BMM in GC, we propose ACTN2 as a druggable molecular vulnerability that may provide potential therapeutic benefit against BMM of GC.

Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks

Cancer is a heterogeneous disease that is driven by the accumulation of both genetic and nongenetic alterations, so integrating multiomics data and extracting effective information from them is expected to be an effective way to predict cancer driver genes. In this paper, we first generate comprehensive instructive features for each gene from genomic, epigenomic, transcriptomic levels together with protein–protein interaction (PPI)-networks-derived attributes and then propose a novel semisupervised deep graph learning framework GGraphSAGE to predict cancer driver genes according to the impact of the alterations on a biological system. When applied to eight tumor types, experimental results suggest that GGraphSAGE outperforms several state-of-the-art computational methods for driver genes identification. Moreover, it broadens our current understanding of cancer driver genes from multiomics level and identifies driver genes specific to the tumor type rather than pan-cancer. We expect GGraphSAGE to open new avenues in precision medicine and even further predict drivers for other complex diseases.

Comparative RNA-Sequencing Analysis Reveals High Complexity and Heterogeneity of Transcriptomic and Immune Profiles in Hepatocellular Carcinoma Tumors of Viral (HBV, HCV) and Non-Viral Etiology

Background and Objectives: Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is the leading cause of cancer-related mortality. It arises and progresses against fibrotic or cirrhotic backgrounds mainly due to infection with hepatitis viruses B (HBV) or C (HCV) or non-viral causes that lead to chronic inflammation and genomic changes. A better understanding of molecular and immune mechanisms in HCC subtypes is needed. Materials and Methods: To identify transcriptional changes in primary HCC tumors with or without hepatitis viral etiology, we analyzed the transcriptomes of 24 patients by next-generation sequencing. Results: We identified common and unique differentially expressed genes for each etiological tumor group and analyzed the expression of SLC, ATP binding cassette, cytochrome 450, cancer testis, and heat shock protein genes. Metascape functional enrichment analysis showed mainly upregulated cell-cycle pathways in HBV and HCV and upregulated cell response to stress in non-viral infection. GeneWalk analysis identified regulator, hub, and moonlighting genes and highlighted CCNB1, ACTN2, BRCA1, IGF1, CDK1, AURKA, AURKB, and TOP2A in the HCV group and HSF1, HSPA1A, HSP90AA1, HSPB1, HSPA5, PTK2, and AURKB in the group without viral infection as hub genes. Immune infiltrate analysis showed that T cell, cytotoxic, and natural killer cell markers were significantly more highly expressed in HCV than in non-viral tumors. Genes associated with monocyte activation had the highest expression levels in HBV, while high expression of genes involved in primary adaptive immune response and complement receptor activity characterized tumors without viral infection. Conclusions: Our comprehensive study underlines the high degree of complexity of immune profiles in the analyzed groups, which adds to the heterogeneous HCC genomic landscape. The biomarkers identified in each HCC group might serve as therapeutic targets.

Natural shikonin and acetyl-shikonin improve intestinal microbial and protein composition to alleviate colitis-associated colorectal cancer

BACKGROUND

Colorectal cancer (CRC) and inflammatory bowel disease (IBD) are the most common diseases of human digestive system. Nowadays, the influence of the inflammatory microenvironment on tumorigenesis has become a new direction, and the exploration of relative molecular mechanism will facilitate the discovery and identification of novel potential anti-cancer molecules.

METHODS

Natural shikonin (SK) and acetyl-shikonin (acetyl-SK) was administered to azoxymethane (AOM)/dextran sodium sulphate (DSS)-induced colitis-associated colorectal cancer (CAC) mice model by gavage to investigate their therapeutic effects. Moreover, fresh feces and colon tissues were collected for determining the function of SK and acetyl-SK on the gut microbes and protein expression, respectively.

RESULTS

Both SK and acetyl-SK decreased AOM/DSS-induced CAC, and regulated the intestinal flora structure in CAC mouse model. They, especially SK, improved species richness, evenness and diversity of intestinal flora, recovered the upregulated ratio of Firmicutes to Bacteroidota (F/B ratio) which symbolizes gut microbiota dysbiosis. SK and its derivative increased the beneficial bacteria g__norank_f__Muribaculaceae, Lactobacillus, Lachnospiraceae_NK4A136_Group, and reduced those harmful ones including Ileibacterium and Coriobacteriaceae UCG-002. Notably, AOM/DSS caused significant increase in the abundance of Ileibaterium valens and g__norank_f__norank_o__Clostridia_UCG-014, which were not previously reported in studies of colonic inflammation or cancer, and the disorder was reversed by 20 mg/kg of SK. In our current study, the action of SK and acetyl-SK is dose-dependent, and 20 mg/kg SK exhibited the most effective functions, even better than the positive drug mesalazine. Moreover, differential proteomics and ELISA results showed that SK could recover the increase of pro-inflammatory cytokines (including IL-1β, IL-6 and TNF-α), the upregulation of pyruvate kinase isozyme type M2 (PKM2) and some other proteins (mainly concentrated in transcriptional mis-regulation in cancer and IL-17 signaling pathways), and the downregulation of Aldh1b1-Acc3-Maoa and Μgt2b34-Aldh1a1-Aldh1a7 involved in Wnt/β-catenin signaling pathway.

CONCLUSION

Our study identified SK and acetyl-SK, especially SK, as potential preventive agents for CAC through regulating both gut microbes and pathways involved in inflammation and cancer such as Wnt/β-catenin signaling pathway.

Overexpressed or hyperactivated Rac1 as a target to treat hepatocellular carcinoma

Despite novel targeted and immunotherapies, the prognosis remains bleak for patients with hepatocellular carcinoma (HCC), especially for advanced and/or metastatic forms. The rapid emergence of drug resistance is a major obstacle in the success of chemo-, targeted-, immuno-therapies of HCC. Novel targets are needed. The prominent roles of the small GTPase Rac1 in the development and progression of HCC are discussed here, together with its multiple protein partners, and the targeting of Rac1 with RNA-based regulators and small molecules. We discuss the oncogenic functions of Rac1 in HCC, including the contribution of Rac1 mutants and isoform Rac1b. Rac1 is a ubiquitous target, but the protein is frequently overexpressed and hyperactivated in HCC. It contributes to the aggressivity of the disease, with key roles in cancer cell proliferation, tumor metastasis and resistance to treatment. Small molecule targeting Rac1, indirectly or directly, have shown anticancer effects in HCC experimental models. Rac1-binding agents such as EHT 1864 and analogues offer novel opportunities to combat HCC. We discuss the different modalities to repress Rac1 overactivation in HCC with small molecules and the combination with reference drugs to promote cancer cell death and to repress cell invasion. We highlight the necessity to combine Rac1-targeted approach with appropriate biomarkers to select Rac1 activated tumors. Our analysis underlines the prominent oncogenic functions of Rac1 in HCC and discuss the modalities to target this small GTPase. Rac1 shall be considered as a valid target to limit the acquired and intrinsic resistance of HCC tumors and their metastatic potential.

Exploring the Multicomponent Synergy Mechanism of Yinzhihuang Granule in Inhibiting Inflammation-Cancer Transformation of Hepar Based on Integrated Bioinformatics and Network Pharmacology

Background

The Chinese patent drug Yinzhihuang granule (YZHG) is used to treat hepatitis B. This research is aimed at exploring the multicomponent synergistic mechanism of YZHG in the treatment of inflammation-cancer transformation of hepar and at providing new evidence and insights for its clinical application.

Methods

To retrieve the components and targets of Yinzhihuang granules. The differentially expressed genes (DEGs) of hepar inflammation-cancer transformation were obtained from TTD, PharmGKB, and GEO databases. Construct the compound-prediction target network and the key module network using Cytoscape 3.7.1.

Results

The results show that hepatitis B and hepatitis C shared a common target, MMP2. CDK1 and TOP2A may play an important role in the treatment with YZHG in hepatitis B inflammatory cancer transformation. KEGG pathway enrichment showed that key genes of modules 1, 2, and 4 were mainly enriched in the progesterone-mediated oocyte maturation signaling pathway and oocyte meiosis signaling pathway.

Conclusion

The multicomponent, multitarget, and multichannel pharmacological benefits of YZHG in the therapy of inflammation-cancer transition of hepar are directly demonstrated by network pharmacology, providing a scientific basis for its mechanism.

Five metastasis-related mRNAs signature predicting the survival of patients with liver hepatocellular carcinoma

Backgrounds

Liver hepatocellular carcinoma (HCC) is one of the most malignant tumors, of which prognosis is unsatisfactory in most cases and metastatic of HCC often results in poor prognosis. In this study, we aimed to construct a metastasis- related mRNAs prognostic model to increase the accuracy of prediction of HCC prognosis.

Methods

Three hundred seventy-four HCC samples and 50 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database, involving transcriptomic and clinical data. Metastatic-related genes were acquired from HCMBD website at the same time. Two hundred thirty-three samples were randomly divided into train dataset and test dataset with a proportion of 1:1 by using caret package in R. Kaplan-Meier method and univariate Cox regression analysis and lasso regression analysis were performed to obtain metastasis-related mRNAs which played significant roles in prognosis. Then, using multivariate Cox regression analysis, a prognostic prediction model was established. Transcriptome and clinical data were combined to construct a prognostic model and a nomogram for OS evaluation. Functional enrichment in high- and low-risk groups were also analyzed by GSEA. An entire set based on The International Cancer Genome Consortium(ICGC) database was also applied to verify the model. The expression levels of SLC2A1, CDCA8, ATG10 and HOXD9 are higher in tumor samples and lower in normal tissue samples. The expression of TPM1 in clinical sample tissues is just the opposite.

Results

One thousand eight hundred ninety-five metastasis-related mRNAs were screened and 6 mRNAs were associated with prognosis. The overall survival (OS)-related prognostic model based on 5 MRGs (TPM1,SLC2A1, CDCA8, ATG10 and HOXD9) was significantly stratified HCC patients into high- and low-risk groups. The AUC values of the 5-gene prognostic signature at 1 year, 2 years, and 3 years were 0.786,0.786 and 0.777. A risk score based on the signature was a significantly independent prognostic factor (HR = 1.434; 95%CI = 1.275–1.612; P < 0.001) for HCC patients. A nomogram which incorporated the 5-gene signature and clinical features was also built for prognostic prediction. GSEA results that low- and high-risk group had an obviously difference in part of pathways. The value of this model was validated in test dataset and ICGC database.

Conclusion

Metastasis-related mRNAs prognostic model was verified that it had a predictable value on the prognosis of HCC, which could be helpful for gene targeted therapy.