Proteomic and metabolomic features in patients with HCC responding to lenvatinib and anti-PD1 therapy.

Combination therapy (lenvatinib/programmed death-1 inhibitor) is effective for treating unresectable hepatocellular carcinoma (uHCC). We reveal that responders have better overall and progression-free survival, as well as high tumor mutation burden and special somatic variants. We analyze the proteome and metabolome of 82 plasma samples from patients with hepatocellular carcinoma (HCC; n = 51) and normal controls (n = 15), revealing that individual differences outweigh treatment differences. Responders exhibit enhanced activity in the alternative/lectin complement pathway and higher levels of lysophosphatidylcholines (LysoPCs), predicting a favorable prognosis. Non-responders are enriched for immunoglobulins, predicting worse outcomes. Compared to normal controls, HCC plasma proteins show acute inflammatory response and platelet activation, while LysoPCs decrease. Combination therapy increases LysoPCs/phosphocholines in responders. Logistic regression/random forest models using metabolomic features achieve good performance in the prediction of responders. Proteomic analysis of cancer tissues unveils molecular features that are associated with side effects in responders receiving combination therapy. In conclusion, our analysis identifies plasma features associated with uHCC responders to combination therapy.

WDR4/TRIM28 is a novel molecular target linked to lenvatinib resistance that helps retain the stem characteristics in hepatocellular carcinomas.

Hepatocellular carcinoma (HCC) is an aggressive malignancy with few effective treatment options. Lenvatinib is the first-line therapy for HCC but has only limited clinical benefit. Here, we explored the role and mechanism of the WD repeat domain 4 (WDR4) in lenvatinib resistance to improve clinical benefit. We found that lenvatinib-resistant HCC tissues/cells exhibited increased the N7-methylguanosine (m7G) modification and WDR4 expression. By a gain/loss of function experiment, we showed that WDR4 promoted HCC lenvatinib resistance and tumor progress both in vitro and in vivo. By proteomics analysis and RNA immunoprecipitation PCR, we found that tripartite motif protein 28 (trim28) was an important WDR4 target gene. WDR4 promoted TRIM28 expression, further affected target genes expression, and thus increased cell-acquired stemness and lenvatinib resistance. Clinical tissue data showed that TRIM28 expression was correlated with WDR4 levels, and the expression of both was positively correlated with poor prognosis. Our study provides new insight into the role of WDR4, suggesting a potential therapeutic target to enhance the lenvatinib sensitivity of HCC.

Intratumor microbiome features reveal antitumor potentials of intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is a rare malignancy with a high prevalence in China. This study aimed to characterize the ICC tissues' bacterial metagenomics signature and explore its antitumor potential for cancer. In this study, 16S rRNA sequencing was carried out on 99 tissues to characterize the features of intratumoral microbiota, followed by single-cell RNA sequencing (scRNA-seq) and multilevel validation. The presence of microbial DNA in tissues was determined using staining, fluorescence in situ hybridization (FISH), and transmission electron microscopy (TEM). A Gram-positive aerobic bacterium, identified as Staphylococcus capitis, was cultured from fresh tissues. Meanwhile, scRNA-seq showed that intratumoral bacteria could be present in multiple cell types. Using 16S rRNA sequencing, we identified a total of 2,320,287 high-quality reads corresponding to 4,594 OTU (operational taxonomic units) sequences. The most abundant bacterial orders include Burkholderiales, Pseudomonadales, Xanthomonadales, Bacillales and Clostridiales. Alpha and Beta diversity analysis revealed specific features in different tissues. In addition, the content of Paraburkholderia fungorum was significantly higher in the paracancerous tissues and negatively correlated with CA199 (Carbohydrate antigen199) levels. The results of in vitro and in vivo experiments suggest that P. fungorum possesses an antitumor activity against tumors. Metabolomics and transcriptomics showed that P. fungorum could inhibit tumor growth through alanine, aspartate and glutamate metabolism. We determined the characteristic profile of the intratumoral microbiota and the antitumor effect of P. fungorum in ICC.

The Intratumoral Bacterial Metataxonomic Signature of Hepatocellular Carcinoma.

Microbiota is implicated in hepatocellular carcinoma (HCC). The spectrum of intratumoral microbiota associated with HCC progression remains elusive. Fluorescence in situ hybridization revealed that microbial DNAs were distributed in the cytosol of liver hepatocytes and erythrocytes. Viable anaerobic or aerobic bacteria were recovered in HCC tissues by fresh tissue culture. We performed a comprehensive DNA sequencing of bacterial 16S rRNA genes in 156 samples from 28 normal liver, 64 peritumoral, and 64 HCC tissues, and the DNA sequencing yielded 4.2 million high-quality reads. Both alpha and beta diversity in peritumor and HCC microbiota were increased compared to normal controls. The most predominant phyla in HCC were Patescibacteria, Proteobacteria, Bacteroidota, Firmicutes, and Actinobacteriota. phyla of Proteobacteria, Firmicutes, and Actinobacteriota, and classes of Bacilli and Actinobacteria, were consistently enriched in peritumor and HCC tissues, while Gammaproteobacteria was especially abundant in HCC tissues compared to normal controls. Streptococcaceae and Lactococcus were the marker taxa of HCC cirrhosis. The Staphylococcus branch and Caulobacter branch were selectively enriched in HBV-negative HCCs. The abundance of Proteobacteria, Gammaproteobacteria, Firmicutes, Actinobacteriota, and Saccharimonadia were associated with the clinicopathological features of HCC patients. The inferred functions of different taxa were changed between the microbiota of normal liver and peritumor/HCC. Random forest machine learning achieved great discriminative performance in HCC prediction (area under the curve [AUC] = 1.00 in the training cohort, AUC = 0.950 for top five class signature, and AUC = 0.943 for the top 50 operational taxonomy units [OTUs] in the validation cohort). Our analysis highlights the complexity and diversity of the liver and HCC microbiota and established a specific intratumoral microbial signature for the potential prediction of HCC. IMPORTANCE Gut microbiome is an important regulator of hepatic inflammation, detoxification, and immunity, and contributes to the carcinogenesis of liver cancer. Intratumoral bacteria are supposed to be closer to the tumor cells, forming a microenvironment that may be relevant to the pathological process of hepatocellular carcinoma (HCC). However, the presence of viable intratumoral bacteria remains unclear. It is worth exploring whether the metataxonomic characteristics of intratumoral bacteria can be used as a potential marker for HCC prediction. Here, we present the first evidence of the existence of viable intratumoral bacteria in HCC using the tissue culture method. We revealed that microbial DNAs were distributed in the cytosol of liver hepatocytes and erythrocytes. We analyzed the diversity, structure, and abundance of normal liver and HCC microbiota. We built a machine learning model for HCC prediction using intratumoral bacterial features. We show that specific taxa represent potential targets for both therapeutic and diagnostic interventions.

KSR2-14-3-3ζ complex serves as a biomarker and potential therapeutic target in sorafenib-resistant hepatocellular carcinoma.

BACKGROUND: Kinase suppressor of Ras 2 (KSR2) is a regulator of MAPK signaling that is overactivated in most hepatocellular carcinoma (HCC). We sought to determine the role of KSR2 in HCC pathogenesis. METHODS: We tested the level of KSR2 in HCC tissues and cell lines by tissue microarray, qPCR, and western blotting. Functionally, we determined the effects of KSR2 on the proliferation, migration, and invasion of HCC cells through colony formation assays, scratch assays, transwell migration assays, and xenograft tumor models. Co-immunoprecipitation (co-IP) experiments were used to assess the interaction of phospho-serine binding protein 14-3-3ζ and KSR2, and the effects of this interaction on growth and proliferation of human HCC cells were tested by co-overexpression and knockdown experiments. Additionally, we used flow cytometry to examine whether the KSR2 and 14-3-3ζ interaction conveys HCC resistance to sorafenib. RESULTS: KSR2 was significantly upregulated in HCC tissues and cell lines, and high KSR2 expression associated with poor prognosis in HCC patients. KSR2 knockdown significantly suppressed HCC cell proliferation, migration, and invasion in vitro and in vivo. Mechanistically, co-IP experiments identified that 14-3-3ζ complexed with KSR2, and elevated 14-3-3ζ increased KSR2 protein levels in HCC cells. Importantly, Kaplan-Meier survival analysis showed that patients with both high KSR2 and high 14-3-3ζ expression levels had the shortest survival times and poorest prognoses. Interestingly, HCC cells overexpressing both KSR2 and 14-3-3ζ, rather than either protein alone, showed hyperactivated MAPK signaling and resistance to sorafenib. CONCLUSIONS: Our results provide new insights into the pro-tumorigenic role of KSR2 and its regulation of the MAPK pathway in HCC. The KSR2-14-3-3ζ interaction may be a therapeutic target to enhance the sorafenib sensitivity of HCC.

PKCα/ZFP64/CSF1 axis resets the tumor microenvironment and fuels anti-PD1 resistance in hepatocellular carcinoma.

BACKGROUND & AIMS: Despite remarkable advances in treatment, most patients with hepatocellular carcinoma (HCC) respond poorly to anti-programmed cell death 1 (anti-PD1) therapy. A deeper insight into the tolerance mechanism of HCC against this therapy is urgently needed. METHODS: We performed next-generation sequencing, multiplex immunofluorescence, and dual-color immunohistochemistry and constructed an orthotopic HCC xenograft tumor model to identify the key gene associated with anti-PD1 tolerance. A spontaneously tumorigenic transgenic mouse model, an in vitro coculture system, mass cytometry, and multiplex immunofluorescence were used to explore the biological function of zinc finger protein 64 (ZFP64) on tumor progression and immune escape. Molecular and biochemical strategies like RNA-sequencing, chromatin immunoprecipitation-sequencing and mass spectrometry were used to gain insight into the underlying mechanisms of ZFP64. RESULTS: We showed that ZFP64 is frequently upregulated in tumor tissues from patients with anti-PD1-resistant HCC. Elevated ZFP64 drives anti-PD1 resistance by shifting macrophage polarization toward an alternative activation phenotype (M2) and fostering an inhibitory tumor microenvironment. Mechanistically, we primarily demonstrated that protein kinase C alpha (PKCα) directly phosphorylates ZFP64 at S226, leading to its nuclear translocation and the transcriptional activation of macrophage colony-stimulating factor (CSF1). HCC-derived CSF1 transforms macrophages to the M2 phenotype to drive immune escape and anti-PD1 tolerance. Notably, Gö6976, a protein kinase inhibitor, and lenvatinib, a multi-kinase inhibitor, reset the tumor microenvironment and restore sensitivity to anti-PD1 by blocking the PKCα/ZFP64/CSF1 axis. CONCLUSIONS: We propose that the PKCα/ZFP64/CSF1 axis is critical for triggering immune evasion and anti-PD1 tolerance. Inhibiting this axis with Gö6976 or lenvatinib overcomes anti-PD1 resistance in HCC. LAY SUMMARY: Despite remarkable treatment progress, most patients with hepatocellular carcinoma respond poorly to anti-PD1 therapy (a type of immunotherapy). A deeper insight into the tolerance mechanisms to this therapy is urgently needed. Herein, we unravel a previously unexplored mechanism linking tumor progression, macrophage polarization, and anti-PD1 resistance, and offer an attractive novel target for anti-PD1 combination therapy, which may benefit patients with hepatocellular carcinoma.

Acetylproteomics analyses reveal critical features of lysine-ε-acetylation in Arabidopsis and a role of 14-3-3 protein acetylation in alkaline response.

Lysine-ε-acetylation (Kac) is a post-translational modification (PTM) that is critical for metabolic regulation and cell signaling in mammals. However, its prevalence and importance in plants remain to be determined. Employing high-resolution tandem mass spectrometry, we analyzed protein lysine acetylation in five representative Arabidopsis organs with 2 ~ 3 biological replicates per organ. A total of 2887 Kac proteins and 5929 Kac sites were identified. This comprehensive catalog allows us to analyze proteome-wide features of lysine acetylation. We found that Kac proteins tend to be more uniformly expressed in different organs, and the acetylation status exhibits little correlation with the gene expression level, indicating that acetylation is unlikely caused by stochastic processes. Kac preferentially targets evolutionarily conserved proteins and lysine residues, but only a small percentage of Kac proteins are orthologous between rat and Arabidopsis. A large portion of Kac proteins overlap with proteins modified by other PTMs including ubiquitination, SUMOylation and phosphorylation. Although acetylation, ubiquitination and SUMOylation all modify lysine residues, our analyses show that they rarely target the same sites. In addition, we found that "reader" proteins for acetylation and phosphorylation, i.e., bromodomain-containing proteins and GRF (General Regulatory Factor)/14-3-3 proteins, are intensively modified by the two PTMs, suggesting that they are main crosstalk nodes between acetylation and phosphorylation signaling. Analyses of GRF6/14-3-3λ reveal that the Kac level of GRF6 is decreased under alkaline stress, suggesting that acetylation represses plant alkaline response. Indeed, K56ac of GRF6 inhibits its binding to and subsequent activation of the plasma membrane H+-ATPase AHA2, leading to hypersensitivity to alkaline stress. These results provide valuable resources for protein acetylation studies in plants and reveal that protein acetylation suppresses phosphorylation output by acetylating GRF/14-3-3 proteins.

Identification of HIV-1-specific cascaded microRNA-mRNA regulatory relationships by parallel mRNA and microRNA expression profiling with AIDS patients after antiviral treatment.

BACKGROUND: The pathogenesis of human immunodeficiency virus 1 (HIV-1) infection is so complex that have not been clearly defined, despite intensive efforts have been made by many researchers. MicroRNA (miRNA) as regulation factor in various human diseases may influence the course of HIV-1 infection by targeting mRNAs. Thus, studies combining transcription of posttranscriptional miRNA regulation are required. METHODS: With the purpose of identifying cascaded miRNA-mRNA regulatory relationships related to HIV infection in gene level, the parallel miRNA, and mRNA expression profiles were analyzed to select differential expressed miRNAs and mRNAs. Then, miRNA-mRNA interactions were predicted using 3 data sources and Pearson correlation coefficient was calculated based on the gene expression level for accuracy improvement. Furthermore, the calculation of the regulatory impact factors was conducted to reveal crucial regulators in HIV-1 infection. To give further insight into these transcription factor (TF) regulators, the differentially co-expression analysis was conducted to identify differentially co-expressed links and differential co-expressed genes and the co-expression gene modules were identified using a threshold-based hierarchical clustering method, then modules were combined into a miRNA-TF-mRNA network. RESULTS: A total of 69,126 differentially co-expressed links and 626 differential co-expressed genes were identified. Functional enrichment analysis indicated that these co-expressed genes were significantly involved in immune response and apoptosis. Moreover, according to regulatory impact factors, 5 most influential TFs and miRNA in HIV-1 infection were identified and miRNA-TF-mRNA regulatory networks were built during the computing process. CONCLUSIONS: In our study, a set of integrated methods was generated to identify important regulators and miRNA-TF-mRNA interactions. Parallel profiling analysis of the miRNAs and mRNAs expression of HIV/acquired immunodeficiency syndrome (AIDS) patients after antiretroviral therapy indicated that some regulators have wide impact on gene regulation and that these regulatory elements may bear significant implications on the underlying molecular mechanism and pathogenesis of AIDS occurrence.

Comparative physiological and transcriptomic analysis reveals salinity tolerance mechanisms in Sorghum bicolor (L.) Moench.

MAIN CONCLUSION: Mota Maradi is a sorghum line that exhibits holistic salinity tolerance mechanisms, making it a viable potential donor in breeding efforts for improved sorghum lines. High soil salinity is one of the global challenges for crop growth and productivity. Understanding the salinity tolerance mechanisms in crops is necessary for genetic breeding of salinity-tolerant crops. In this study, physiological and molecular mechanisms in sorghum were identified through a comparative analysis between a Nigerien salinity-tolerant sorghum landrace, Mota Maradi, and the reference sorghum line, BTx623. Significant differences on physiological performances were observed, particularly on growth and biomass gain, photosynthetic rate, and the accumulation of Na+, K+, proline, and sucrose. Transcriptome profiling of the leaves, leaf sheaths, stems, and roots revealed contrasting differentially expressed genes (DEGs) in Mota Maradi and BTx623 which supports the physiological observations from both lines. Among the DEGs, ion transporters such as HKT, NHX, AKT, HAK5, and KUP3 were likely responsible for the differences in Na+ and K+ accumulation. Meanwhile, DEGs involved in photosynthesis, cellular growth, signaling, and ROS scavenging were also identified between these two genotypes. Functional and pathway analysis of the DEGs has revealed that these processes work in concert and are crucial in elevated salinity tolerance in Mota Maradi. Our findings indicate how different complex processes work synergistically for salinity stress tolerance in sorghum. This study also highlights the unique adaptation of landraces toward their respective ecosystems, and their strong potential as genetic resources for future plant breeding endeavors.

Quantitative acetylome analysis reveals histone modifications that may predict prognosis in hepatitis B-related hepatocellular carcinoma.

Lysine acetylation (Kac) as an important posttranslational modification of histones is essential for the regulation of gene expression in hepatocellular carcinoma (HCC). However, the atlas of whole acetylated proteins in HCC tissues and the difference in protein acetylation between normal human tissues and HCC tissues are unknown. In this report, we characterized the proteome and acetyl proteome (acetylome) profile of normal, paracancerous, and HCC liver tissues in human clinical samples by quantitative proteomics techniques. We identified 6781 acetylation sites of 2582 proteins and quantified 2492 acetylation sites of 1190 proteins in normal, paracancerous, and HCC liver tissues. Among them, 15 proteins were multiacetylated with more than 10 lysine residues. The histone acetyltransferases p300 and CBP were found to be hyperacetylated in hepatitis B virus pathway. Moreover, we found that 250 Kac sites of 214 proteins were upregulated and 662 Kac sites of 451 proteins were downregulated in HCC compared with normal liver tissues. Additionally, the acetylation levels of lysine 120 in histone H2B (H2BK120ac), lysine 18 in histone H3.3 (H3.3K18ac), and lysine 77 in histone H4 (H4K77ac) were increased in HCC. Interestingly, the higher levels of H2BK120ac, H3.3K18ac, and H4K77ac were significantly associated with worse prognosis, such as poorer survival and higher recurrence in an independent clinical cohort of HCC patients. Overall, this study lays a foundation for understanding the functions of acetylation in HCC and provides potential prognostic factors for the diagnosis and therapy of HCC.

[3D organization profiling of human hepatocellular carcinoma cell line PLC/PRF/5 in comparison with normal human liver cell line L02 by in situ Hi-C].

Genetic and epigenetic alterations accumulate in the process of hepatocellular carcinogenesis, but the role of genomic spatial organization in HCC is still unknown. Here, we performed in situ Hi-C in HCC cell line PLC/PRF/5 compared with normal liver cell line L02, together with RNA-seq and ChIP-seq of SMC3/CTCF/H3K27ac. The results indicate that there were significant compartment switching, TAD shifting and loop pattern altering in PLC/PRF/5. These spatial changes are correlated with abnormal gene expression and more opening promoter regions of the HCC cell line. Thus, the 3D genome organization alterations in PLC/PRF/5 are important in epigenetic mechanisms of HCC tumorigenesis.

Histone acetylation recruits the SWR1 complex to regulate active DNA demethylation in Arabidopsis.

Active DNA demethylation is critical for controlling the DNA methylomes in plants and mammals. However, little is known about how DNA demethylases are recruited to target loci, and the involvement of chromatin marks in this process. Here, we identify 2 components of the SWR1 chromatin-remodeling complex, PIE1 and ARP6, as required for ROS1-mediated DNA demethylation, and discover 2 SWR1-associated bromodomain-containing proteins, AtMBD9 and nuclear protein X1 (NPX1). AtMBD9 and NPX1 recognize histone acetylation marks established by increased DNA methylation 1 (IDM1), a known regulator of DNA demethylation, redundantly facilitating H2A.Z deposition at IDM1 target loci. We show that at some genomic regions, H2A.Z and DNA methylation marks coexist, and H2A.Z physically interacts with ROS1 to regulate DNA demethylation and antisilencing. Our results unveil a mechanism through which DNA demethylases can be recruited to specific target loci exhibiting particular histone marks, providing a conceptual framework to understand how chromatin marks regulate DNA demethylation.

eIF3a mediates HIF1α-dependent glycolytic metabolism in hepatocellular carcinoma cells through translational regulation.

eIF3a is the largest subunit of eIF3 complex and is a key player in translational control. Recently eIF3a is recognized as a proto-oncogene, which is overexpressed and connected to tumorigenesis of many cancers. However, the mechanistic roles of eIF3a during the tumorigenesis remain largely elusive. Here, we report that depletion of eIF3a significantly reduced HIF1α protein level and cellular glycolysis ability. Mechanistically, we found that eIF3a regulates HIF1α protein synthesis through internal ribosomal entry site (IRES)-dependent translation. Importantly, through analyses of our own sample collection, we found that eIF3a is overexpressed in hepatocellular carcinoma (HCC) tissues, and a high level of eIF3a predicts poor prognosis of HCC patients. TCGA analyses further confirmed that eIF3a is coincident with an elevated activity of HIF1α pathway genes. Collectively, we identify eIF3a as a regulator for glycolysis through HIF1α IRES-dependent translational regulation, which may be a potential therapeutic target for HCC.

Identification of the transcriptional regulators by expression profiling infected with hepatitis B virus.

BACKGROUND: The molecular pathogenesis of infection by hepatitis B virus with human is extremely complex and heterogeneous. To date the molecular information is not clearly defined despite intensive research efforts. Thus, studies aimed at transcription and regulation during virus infection or combined researches of those already known to be beneficial are needed. AIMS: With the purpose of identifying the transcriptional regulators related to infection of hepatitis B virus in gene level, the gene expression profiles from some normal individuals and hepatitis B patients were analyzed in our study. METHODS: In this work, the differential expressed genes were selected primarily. The several genes among those were validated in an independent set by qRT-PCR. Then the differentially co-expression analysis was conducted to identify differentially co-expressed links and differential co-expressed genes. Next, the analysis of the regulatory impact factors was performed through mapping the links and regulatory data. In order to give a further insight to these regulators, the co-expression gene modules were identified using a threshold-based hierarchical clustering method. Incidentally, the construction of the regulatory network was generated using the computer software. RESULTS: A total of 137,284 differentially co-expressed links and 780 differential co-expressed genes were identified. These co-expressed genes were significantly enriched inflammatory response. The results of regulatory impact factors revealed several crucial regulators related to hepatocellular carcinoma and other high-rank regulators. Meanwhile, more than one hundred co-expression gene modules were identified using clustering method. CONCLUSIONS: In our study, some important transcriptional regulators were identified using a computational method, which may enhance the understanding of disease mechanisms and lead to an improved treatment of hepatitis B. However, further experimental studies are required to confirm these findings.

MitProNet: A knowledgebase and analysis platform of proteome, interactome and diseases for mammalian mitochondria.

Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated biological mechanisms underlying mitochondrial functions and human mitochondrial diseases. MitProNet is freely accessible at http://bio.scu.edu.cn:8085/MitProNet.