Proteomic Analysis Identifies GSN as a Noninvasive Circulating Serum Biomarker for Predicting Early Recurrence of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is susceptible to early recurrence, but it lacks effective predictive biomarkers. In this study, we retrospectively selected 179 individuals as a discovery cohort (126 HCC patients and 53 liver cirrhosis (LC) patients) for screening candidate serum biomarkers of early recurrence based on data independent acquisition-mass spectrometry strategy. And then, the candidate biomarkers were validated in an additional independent cohort with 192 individuals (142 HCC patients and 50 LC patients) using parallel reaction monitoring targeted quantitative techniques (PXD047852). Eventually, we validated that gelsolin (GSN) concentrations were significantly lower in HCC than in LC (p < 0.0001), patients with low GSN concentrations had a poor prognosis (p < 0.0001), and GSN concentrations were significantly lower in early recurrence HCC than in late recurrence HCC (p < 0.0001). These trends were also observed in alpha-fetoprotein (AFP)-negative HCC patients. The area under the curve of machine-learning-based predictive model (GSN and microvascular invasion) for predicting early recurrence risk reached 0.803 (95% confidence interval (CI): 0.786-0.820) and maintained the same efficacy in AFP-negative patients. In conclusion, GSN is a novel serum biomarker for early recurrence of HCC. The model could provide timely warning to HCC patients at high risk of recurrence.

Integrated omics landscape of hepatocellular carcinoma suggests proteomic subtypes for precision therapy.

Patients with hepatocellular carcinoma (HCC) at the same clinical stage can have extremely different prognoses, and molecular subtyping provides an opportunity for individualized precision treatment. In this study, genomic, transcriptomic, proteomic, and phosphoproteomic profiling of primary tumor tissues and paired para-tumor tissues from HCC patients (N = 160) are integrated. Proteomic profiling identifies three HCC subtypes with different clinical prognosis, which are validated in three publicly available external validation sets. A simplified panel of nine proteins associated with metabolic reprogramming is further identified as a potential subtype-specific biomarker for clinical application. Multi-omics analysis further reveals that three proteomic subtypes have significant differences in genetic alterations, microenvironment dysregulation, kinase-substrate regulatory networks, and therapeutic responses. Patient-derived cell-based drug tests (N = 26) show personalized responses for sorafenib in three proteomic subtypes, which can be predicted by a machine-learning response prediction model. Overall, this study provides a valuable resource for better understanding of HCC subtypes for precision clinical therapy.

Proteomics-driven noninvasive screening of circulating serum protein panels for the early diagnosis of hepatocellular carcinoma.

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.

Alcohol reshapes a liver premetastatic niche for cancer by extra- and intrahepatic crosstalk-mediated immune evasion.

Cancer metastatic organotropism is still a mystery. The liver is known to be susceptible to cancer metastasis and alcoholic injury. However, it is unclear whether and how alcohol facilitates liver metastasis and how to intervene. Here, we show that alcohol preferentially promotes liver metastasis in colon-cancer-bearing mice and post-surgery pancreatic cancer patients. The mechanism is that alcohol triggers an extra- and intrahepatic crosstalk to reshape an immunosuppressive liver microenvironment. In detail, alcohol upregulates extrahepatic IL-6 and hepatocellular IL-6 receptor expression, resulting in hepatocyte STAT3 signaling activation and downstream lipocalin-2 (Lcn2) upregulation. Furthermore, LCN2 promotes T cell-exhaustion neutrophil recruitment and cancer cell epithelial plasticity. In contrast, knocking out hepatocellular Stat3 or systemic Il6 in alcohol-treated mice preserves the liver microenvironment and suppresses liver metastasis. This mechanism is reflected in hepatocellular carcinoma patients, in that alcohol-associated signaling elevation in noncancerous liver tissue indicates adverse prognosis. Accordingly, we discover a novel application for BBI608, a small molecular STAT3 inhibitor that can prevent liver metastasis. BBI608 pretreatment protects the liver and suppresses alcohol-triggered premetastatic niche formation. In conclusion, under extra- and intrahepatic crosstalk, the alcoholic injured liver forms a favorable niche for cancer cell metastasis, while BBI608 is a promising anti-metastatic agent targeting such microenvironments.

Personalized neoantigen vaccine combined with PD-1 blockade increases CD8+ tissue-resident memory T-cell infiltration in preclinical hepatocellular carcinoma models.

BACKGROUND: Personalized neoantigen vaccine could induce a robust antitumor immune response in multiple cancers, whose efficacy could be further enhanced by combining with programmed cell death 1 blockade (α-PD-1). However, the corresponding immune response and synergistic mechanisms remain largely unclear. Here, we aimed to develop clinically available combinational therapeutic strategy and further explore its potential antitumor mechanisms in hepatocellular carcinoma (HCC). METHODS: Neoantigen peptide vaccine (NeoVAC) for murine HCC cell line Hepa1-6 was developed and optimized by neoantigen screening and adjuvant optimization. Then the synergistic efficacy and related molecular mechanisms of NeoVAC combined with α-PD-1 in HCC were evaluated by orthotopic HCC mouse model, single-cell RNA sequencing, tetramer flow cytometry, immunofluorescence, etc. The tumor-killing capacity of CD8+ tissue-resident memory T cells (CD8+ TRMs) was assessed by orthotopic HCC mouse model, and autologous patient-derived cells. RESULTS: NeoVAC, which consisted of seven high immunogenic neoantigen peptides and clinical-grade Poly(I:C), could generate a strong antitumor immune response in HCC mouse models. Significantly, its efficacy could be further improved by combining with α-PD-1, with 80% of durable tumor regression and long-term immune memory in orthotopic HCC models. Moreover, in-depth analysis of the tumor immune microenvironment showed that the percentage of CD8+ TRMs was remarkedly increased in NeoVAC plus α-PD-1 treatment group, and positively associated with the antitumor efficacy. In vitro and in vivo T-cell cytotoxicity assay further confirmed the strong tumor-killing capacity of CD8+ TRMs sorting from orthotopic mouse HCC or patient's HCC tissue. CONCLUSIONS: This study showed that NeoVAC plus α-PD-1 could induce a strong antitumor response and long-term tumor-specific immune memory in HCC by increasing CD8+ TRMs infiltration, which might serve as a potential immune-therapeutic target for HCC.

Quantitative Secretome Analysis Reveals Clinical Values of Carbonic Anhydrase II in Hepatocellular Carcinoma.

Early detection and intervention are key strategies to reduce mortality, increase long-term survival, and improve the therapeutic effects of hepatocellular carcinoma (HCC) patients. Herein, the isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomic strategy was used to study the secretomes in conditioned media from HCC cancerous tissues, surrounding noncancerous tissues, and distal noncancerous tissues to identify diagnostic and prognostic biomarkers for HCC. In total, 22 and 49 dysregulated secretory proteins were identified in the cancerous and surrounding noncancerous tissues, respectively, compared with the distal noncancerous tissues. Among these proteins, carbonic anhydrase II (CA2) was identified to be significantly upregulated in the secretome of cancerous tissues; correspondingly, the serum concentrations of CA2 were remarkably increased in HCC patients compared with that in normal populations. Interestingly, a significant increase of serum CA2 in recurrent HCC patients after radical resection was also confirmed compared with HCC patients without recurrence, and the serum level of CA2 could act as an independent prognostic factor for time to recurrence and overall survival. Regarding the mechanism, the secreted CA2 enhances the migration and invasion of HCC cells by activating the epithelial mesenchymal transition pathway. Taken together, this study identified a novel biomarker for HCC diagnosis and prognosis, and provided a valuable resource of HCC secretome for investigating serological biomarkers.

Proteomic analyses reveal divergent ubiquitylation patterns in hepatocellula carcinoma cell lines with different metastasis potential.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours, metastasis and recurrence remain the primary reasons for poor prognosis. Ubiquitination serves as a degradation mechanism of proteins, but it is involved in additional cellular processes including metastasis. Here, by using label-free quantification, double-glycine (di-Gly) antibody affinity purification and high-resolution liquid chromatography tandem mass spectrometry (LC-MS/MS), we investigated quantitative proteome, ubiquitylome, and the crosstalk between the two datasets in HCC cell lines with different metastasis potential to identify biomarkers associated with HCC metastasis. In total, 83 ubiquitinated proteins significantly and steadily changed their abundance according to their metastatic potential, and the participated biological processes of these ubiquitinated proteins were tightly associated with tumour metastasis. Further signaling pathway analysis revealed that the ribosome and proteasome were significantly over-activated in the highly metastatic cells. Furthermore, we analyzed the crosstalk between the whole proteome and the ubiquitylome, and further discussed the mechanism that how ubiquitination events affect HCC metastasis. Eventually, the ubiquitination of Ku80 was validated to be significantly down-regulated in the high-metastatic cells comparing with the low-metastatic cells. We believe that these findings will help us better understand the underlying molecular mechanisms of the metastasis of HCC. SIGNIFICANCE: In this manuscript, we used label free based proteomics combined with diglycine antibody (di-Gly) affinity purification approach to identify biomarkers associated with HCC recurrence/metastasis in in a serial HCC cell lines with increasing invasion and metastasis potential. And then, we analyzed the crosstalk between the whole proteome and the ubiquitylome. Eventually, the ubiquitination of Ku80 was confirm to be closely associated with invasion and migration of HCC cells. As far as we know, this is the first time to use quantitative proteomic approach to study the ubiquitylomics in HCC cell lines with increasing metastasis ability.

4E-BP1Thr46 Phosphorylation Association with Poor Prognosis in Quantitative Phosphoproteomics of Portal Vein Tumor Thrombus Revealed that 4E-BP1Thr46 Phosphorylation is Associated with Poor Prognosis in HCC.

PURPOSE: Early formation of portal vein tumor thrombosis (PVTT) is a key characteristic of hepatocellular carcinoma (HCC) metastasis, but to date, the aetiology of PVTT in HCC metastasis is largely unknown. We aim to find highly sensitive and specific biomarkers for the prediction of HCC prognosis. PATIENTS AND METHODS: We used isobaric tags for relative and absolute quantitation (iTRAQ) based quantitative phosphoproteomics approach to investigate the molecular signatures of the HCC with PVTT in primary HCC tissues, surrounding non-cancerous tissues and PVTT tissues. The different proteome profiles in three groups were investigated and might reveal different underlying molecular mechanisms. RESULTS: In total, we identified 1745 phosphoproteins with 2724 phosphopeptides and 4594 phosphorylation sites in three groups. Among these phosphoproteins, 80 phosphoproteins were dysregulated in PVTT/Pan group, 51 phosphoproteins were dysregulated in HCC/Pan group, and 10 phosphoproteins were dysregulated in PVTT/HCC group. Furthermore, the phosphorylation of 4E-BP1 was elevated in HCC tissues and PVTT tissues in comparison with surrounding non-cancerous tissues,  and the elevated fold change of phosphorylation level was higher than that in expression level of 4E-BP1. The further IHC analysis in acohort of 20 HCC tissues showed that the phosphorylation of 4E-BP1 on Thr46 might be closely related to HCC prognosis. CONCLUSION: The high phosphorylation level of 4E-BP1Thr46 might serve as a biomarker for the diagnosis of early recurrence and metastasis of HCC.