High FLT3 Levels May Predict Sorafenib Benefit in Hepatocellular Carcinoma

tRNA-derived fragments: Unveiling new roles and molecular mechanisms in cancer progression

tRNA-derived fragments (tRFs) are novel small noncoding RNAs (sncRNAs) that range from approximately 14 to 50 nt. They are generated by the cleavage of mature tRNAs or precursor tRNAs (pre-tRNAs) at specific sites. Based on their origin and length, tRFs can be classified into three categories: (1) tRF-1 s; (2) tRF-3 s, tRF-5 s, and internal tRFs (i-tRFs); and (3) tRNA halves. They play important roles in stress response, signal transduction, and gene expression processes. Recent studies have identified differential expression of tRFs in various tumors. Aberrantly expressed tRFs have critical clinical value and show promise as new biomarkers for tumor diagnosis and prognosis and as therapeutic targets. tRFs regulate the malignant progression of tumors via various mechanisms, primarily including modulation of noncoding RNA biogenesis, global chromatin organization, gene expression regulation, modulation of protein translation, regulation of epigenetic modification, and alternative splicing regulation. In conclusion, tRF-mediated regulatory pathways could present new avenues for tumor treatment, and tRFs could serve as promising therapeutic targets for cancer therapy.

Efficacy and safety of FLT3 inhibitors in monotherapy of hematological and solid malignancies: a systemic analysis of clinical trials

Introduction: FLT3 mutations are closely associated with the occurrence of hematological and solid malignancies, especially with acute myeloid leukemia. Currently, several FLT3 inhibitors are in clinical trials, and some have been applied in clinic. However, the safety, efficacy and pharmacodynamics of these FLT3 inhibitors have not been systemically analyzed before. Methods: We searched and reviewed clinical trial reports on the monotherapy of 13 FLT3 inhibitors, including sorafenib, lestaurtinib, midostaurin, gilteritinib, quizartinib, sunitinib, crenolanib, tandutinib, cabozantinib, pexidartinib, pacritinib, famitinib, and TAK-659 in patients with hematological and solid malignancies before May 31, 2023. Results: Our results showed the most common adverse events (AEs) were gastrointestinal adverse reactions, including diarrhea, hand-foot syndrome and nausea, while the most common hematological AEs were febrile neutropenia, anemia, and thrombocytopenia. Based on the published data, the mean overall survival (OS) and the mean progression-free survival (PFS) were 9.639 and 5.905 months, respectively. The incidence of overall response rate (ORR), complete remission (CR), partial response (PR), and stable disease (SD) for all these FLT3 inhibitors was 29.0%, 8.7%, 16.0%, and 42.3%, respectively. The ORRs of FLT3 inhibitors in hematologic malignancies and solid tumors were 40.8% and 18.8%, respectively, indicating FLT3 inhibitors were more effective for hematologic malignancies than for solid tumors. In addition, time to maximum plasma concentration (Tmax) in these FLT3 inhibitors ranged from 0.7-12.0 hours, but the elimination half-life (T1/2) range was highly variable, from 6.8 to 151.8 h. Discussion: FLT3 inhibitors monotherapy has shown significant anti-tumor effect in clinic, and the effectiveness may be further improved through combination medication.

Integrated clinical and prognostic analyses of mTOR/Hippo pathway core genes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most aggressive and dismal cancers globally. Emerging evidence has established that mTOR and Hippo pathways are oncogenic drivers of HCC. However, the prognostic value of these pathways in HCC remains unclear. In this study, we aimed to develop a gene signature utilizing the mTOR/Hippo genes for HCC prognostication. A multiple stage strategy was employed to screen, and a 12-gene signature based on mTOR/Hippo pathways was constructed to predict the prognosis of HCC patients. The risk scores calculated by the signature were inversely correlated with patient prognosis. Validation of the signature in independent cohort confirmed its predictive power. Further analysis revealed molecular differences between high and low-risk groups at genomic, transcriptomic, and protein-interactive levels. Moreover, immune infiltration analysis revealed an immunosuppressive state in the high-risk group. Finally, the gene signature could predict the sensitivity to current chemotherapeutic drugs. This study demonstrated that combinatorial mTOR/Hippo gene signature was a robust and independent prognostic tool for survival prediction of HCC. Our findings not only provide novel insights for the molecular understandings of mTOR/Hippo pathways in HCC, but also have important clinical implications for guiding therapeutic strategies.

Predicting the prognosis of hepatocellular carcinoma based on the interaction between pyroptosis, apoptosis, and necroptosis

Multiple programmed cell death pathways (pyroptosis, apoptosis, and necroptosis) are closely related to the progression of hepatocellular carcinoma (HCC). Furthermore, molecular interactions among pyroptotic, apoptotic, and necroptotic components may be new targets for cancer therapy. However, the signature of the genes involved in the interaction between pyroptosis, apoptosis, and necroptosis (PANRGs), and their prognostic value, is still unclear in HCC. In this study, we used HCC clinical and expression data from TCGA and GEO to explore the relationship between PANRGs and HCC. First, we determined the copy number variation incidence of 41 PANRGs genes and explored the prognostic correlation of these genes in HCC. Based on PANRGs, two molecular subgroups of HCC associated with prognosis were identified. We also found significant differences in the overall survival time and the immune infiltration of HCC patients between the two subgroups. Finally, based on the nine PANRGs (CDC25B, EZH2, HMOX1, PLK1, SQSTM1, WEE1, TREM2, MYCN, and FLT3), we constructed a prognostic model using LASSO-Cox regression analysis. The prognostic model could predict OS of HCC patients in TCGA and GEO cohorts with high accuracy. Significant correlations were found between prognosis-related PANRGs and the tumor immune microenvironment (TIME), tumor mutational burden (TMB), and drug sensitivity. In conclusion, we explored the role of PANRGs in HCC and the association of these genes with TIME, TMB, and drug sensitivity.

Active compounds and potential targets of Shuganning injection in the treatment of hepatocellular carcinoma by network pharmacology and in vitro validation

Shuganning injection (SGNI), a TCM (traditional Chinese medicine) injection with good hepatoprotective effects, exerted therapeutic effects on hepatocellular carcinoma (HCC). However, the active compounds and effects of SGNI on HCC remain unclear. The objective of this study was to investigate the active compounds and potential targets of SGNI in the treatment of HCC, and explore the molecular mechanisms of main compounds. Network pharmacology was applied to predict the active compounds and targets of SGNI on cancer. The interactions between active compounds and target proteins were validated by drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), and pull-down assay. The in vitro test of the effects and mechanism of vanillin and baicalein was elucidated by MTT, western blot, immunofluorescence, and apoptosis analysis. According to compound characteristics, targets, etc., two typical active ingredients (vanillin and baicalein) were selected as representatives to explore the effects on HCC. Vanillin (an important food additive) bound to NF-κB1 and baicalein (a bioactive flavonoid) bound to FLT3 (FMS-like tyrosine kinase 3) were confirmed in this study. Vanillin and baicalein both inhibited cell viability and promoted apoptosis of Hep3B and Huh7 cells. In addition, both vanillin and baicalein could enhance the activation of the p38/MAPK (mitogen-activated protein kinase) signaling pathway, which may partially explain the anti-apoptosis effects of the two compounds. In conclusion, two active compounds of SGNI, vanillin and baicalein, promoted apoptosis of HCC cells via binding with NF-κB1 or FLT3, and regulating the p38/MAPK pathway. Baicalein and vanillin may be good candidates for HCC treatment on drug development.

High Expression of F-Box Protein 43 Is Associated With Poor Prognosis and Adjuvant Chemotherapy Resistance in Colorectal Cancer

BACKGROUND

The F-box protein 43 (FBXO43), also referred to as endogenous meiotic inhibitor 2 (EMI2), has been linked to the advancement of various types of cancer, such as hepatocellular carcinoma, breast cancer, cholangiocarcinoma, and gastric cancer. Nevertheless, the precise function of FBXO43 in colorectal cancer (CRC) remains unclear. This study employed data from The Cancer Genome Atlas (TCGA) and clinical specimens to analyze the expression, prognostic value, and chemotherapeutic advantages of FBXO43 in CRC.

METHODS

Level 3 RNA sequencing data pertaining to 631 cases of colon and rectal adenocarcinomas (COAD-READ) were downloaded from TCGA. The data were utilized to analyze the expression, prognosis, and related signal pathways of FBXO43. The expression of FBXO43 in clinical samples was subsequently confirmed through the use of real-time quantitative polymerase chain reaction (qPCR) and immunohistochemistry (IHC). Lastly, a tissue microarray (TMA) consisting of 120 cases of CRC and corresponding normal tissues was established to investigate the relationship between FBXO43 and survival outcomes.

RESULTS

Results from both the TCGA analysis and clinical samples indicated that FBXO43 was significantly upregulated in CRC tissues in comparison to normal tissues. Moreover, high level of FBXO43 was found to be relevant to malignant clinical features, such as differentiation, lymph node metastasis, and pathological stage, as well as unfavorable prognosis in CRC patients. Subgroup analysis further demonstrated that FBXO43 could be an effective parameter for stratifying low-risk CRC patients. Notably, survival analysis showed that patients with high level of FBXO43 had worse overall survival (OS) and disease-free survival (DFS) following adjuvant chemotherapy, and FBXO43 was distinctly upregulated in chemotherapy-resistant patients' primary CRC tissues.

CONCLUSIONS

FBXO43 was upregulated and associated with poor prognosis of CRC; patients with high expression of FBXO43 may not be benefit from adjuvant chemotherapy.

A novel signature incorporating lipid metabolism- and immune-related genes to predict the prognosis and immune landscape in hepatocellular carcinoma

Background

Liver hepatocellular carcinoma (LIHC) is a highly malignant tumor with high metastasis and recurrence rates. Due to the relation between lipid metabolism and the tumor immune microenvironment is constantly being elucidated, this work is carried out to produce a new prognostic gene signature that incorporates immune profiles and lipid metabolism of LIHC patients.

Methods

We used the "DEseq2" R package and the "Venn" R package to identify differentially expressed genes related to lipid metabolism (LRDGs) in LIHC. Additionally, we performed unsupervised clustering of LIHC patients based on LRDGs to identify their subgroups and immuno-infiltration and Gene Ontology (GO) enrichment analysis on the subgroups. Next, we employed multivariate, LASSO and univariate Cox regression analyses to determine variables and to create a prognostic profile on the basis of immune- and lipid metabolism-related differential genes (IRDGs and LRDGs). We separated patients into low- and high-risk groups in accordance with the best cut-off value of risk score. We conducted Decision Curve Analysis (DCA), Receiver Operating Characteristic curve analysis as a function of time as well as Survival Analysis to evaluate this signature's prognostic value. We incorporated the clinical characteristics of patients into the risk model to obtain a nomogram prognostic model. GEO14520 and ICGC-LIRI JP datasets were employed to externally confirm the accuracy and robustness of signature. The gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were applied for investigating the underlying mechanisms. Immune infiltration analysis was implemented to examine the differences in immune between both risk groups. Single-cell RNA sequencing (scRNA-SEQ) was utilized to characterize the genes that were involved in the distribution of signature and expression characteristics of different LIHC cell types. The patients' sensitivity in both risk groups to commonly used chemotherapeutic agents and semi-inhibitory concentrations (IC50) of the drugs was assessed using the GDSC database. On the basis of the differentially expressed genes (DEGs) in the two groups, the CMAP database was adopted for the prediction of potential small-molecule compounds. Small-molecule compounds were molecularly docked with prognostic markers. Lastly, we investigated the prognostic gene expression levels in normal and LIHC tissues with immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction(qRT-PCR).

Results

We built and verified a prognostic signature with seven genes that incorporated immune profiles and lipid metabolism. Patients were classified as low- and high-risk groups depending on their prognostic profiles. The overall survival (OS) was markedly lower in the high-risk group as compared to low-risk group. Time-dependent ROC curves more precisely predicted patients' survival at 1, 3 and 5 years; the area under the ROC curve was 0.81 (1 year), 0.75 (3 years) and 0.77 (5 years). The DCA curves showed the value of the prognostic genes in this signature for clinical applications. We included the patients' clinical characteristics in the risk model for both multivariate and univariate Cox regression analyses, and the findings revealed that the risk model represents an independent factor that influences OS in LIHC patients. With immune analysis, GSVA and GSEA, we identified that there are remarkable differences between the two risk groups in immune pathways, lipid metabolism, tumor development, immune cell infiltration and immune microenvironment, response to immunotherapy, and sensitivity to chemotherapy. Moreover, those with higher risk scores presented greater sensitivity to the chemotherapeutic agents. Experiments in vitro further elucidated the roles of SPP1 and FLT3 in the LIHC immune microenvironment. Furthermore, four small-molecule drugs that could target LIHC were screened. In vitro qRT-PCR , IHC revealed that the SPP1,KIF18A expressions were raised in LIHC in tumor samples, whereas FLT3,SOCS2 showed the opposite trend.

Conclusions

We developed and verified a new signature comprising immune- and lipid metabolism-associated markers and to assess the prognosis and the immune status of LIHC patients. This signature can be applied to survival prediction, individualized chemotherapy, and immunotherapeutic guidance for patients with liver cancer. This study also provides potential targeted therapeutics and novel ideas for the immune evasion and progression of LIHC.

Identification and Validation of Prognosis-Related Necroptosis Genes for Prognostic Prediction in Hepatocellular Carcinoma

Background

The prediction of hepatocellular carcinoma (HCC) survival is challenging because of its rapid progression. In recent years, necroptosis was found to be involved in the progression of multiple cancer types. However, the role of necroptosis in HCC remains unclear.

Methods

Clinicopathological parameters and transcriptomic data of 370 HCC patients were obtained from TCGA-LIHC dataset. Prognosis-related necroptosis genes (PRNGs) were identified and utilized to construct a LASSO risk model. The GEO cohorts (GSE54236 and GSE14520) were used for external validation. We evaluated the distribution of HCC patients, the difference in prognosis, and the accuracy of the prognostic prediction of the LASSO risk model. The immune microenvironment and functional enrichment of different risk groups were further clarified. Finally, we performed a drug sensitivity analysis on the PRNGs that constructed the LASSO model and verified their mRNA expression levels in vitro. Results: A total of 48 differentially expressed genes were identified, 23 of which were PRNGs. We constructed the LASSO risk model using nine genes: SQSTM1, FLT3, HAT1, PLK1, MYCN, KLF9, HSP90AA1, TARDBP, and TNFRSF21. The outcomes of low-risk patients were considerably better than those of high-risk patients in both the training and validation cohorts. In addition, stronger bile acid metabolism, xenobiotic metabolism, and more active immune cells and immune functions were observed in low-risk patients, and high expressions of TARDBP, PLK1, and FLT3 were associated with greater drug sensitivity. With the exception of FLT3, the mRNA expression of the other eight genes was verified in Huh7 and 97H cells. Conclusions. The PRNG signature provides a novel and effective method for predicting the outcome of HCC as well as potential targets for further research.

MBP-11901 Inhibits Tumor Growth of Hepatocellular Carcinoma through Multitargeted Inhibition of Receptor Tyrosine Kinases

Simple Summary

Although various treatments such as surgery and chemotherapy exist for advanced or unresectable HCC, most patients suffer from intractable diseases, having a poor prognosis. While immunotherapy using immune checkpoint inhibitors was recently proposed for HCC, only a small percentage of patients respond. Thus, there remains an unmet need for the development of therapeutic agents for the treatment of liver cancer. Here, we presented multi-RTKi MBP-11901, an innovative targeted anticancer agent for HCC, suggesting it as a new therapeutic strategy for the treatment of liver cancer.

Abstract

Hepatocellular carcinomas (HCCs) are aggressive tumors with a poor prognosis. Approved first-line treatments include sorafenib, lenvatinib, and a combination of atezolizumab and bevacizumab; however, they do not cure HCC. We investigated MBP-11901 as a drug candidate for HCC. Cell proliferation and cytotoxicity were evaluated using normal and cancer human liver cell lines, while Western blotting and flow cytometry evaluated apoptosis. The anticancer effect of MBP-11901 was verified in vitro through migration, invasion, colony formation, and JC-1 MMP assays. In mouse models, the tumor volume, tumor weight, and bodyweight were measured, and cancer cell proliferation and apoptosis were analyzed. The toxicity of MBP-11901 was investigated through GOT/GPT and histological analyses in the liver and kidney. The signaling mechanism of MBP-11901 was investigated through kinase assays, phosphorylation analysis, and in silico docking simulations. Results. MBP-11901 was effective against various human HCC cell lines, leading to the disappearance of most tumors when administered orally in animal models. This effect was dose-dependent, with no differences in efficacy according to administration intervals. MBP-11901 induced anticancer effects by targeting the signaling mechanisms of FLT3, VEGFR2, c-KIT, and PDGFRβ. MBP-11901 is suggested as a novel therapeutic agent for the treatment of advanced or unresectable liver cancer.

Novel FLT3/AURK multikinase inhibitor is efficacious against sorafenib-refractory and sorafenib-resistant hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the sixth most common type of cancer and has a high mortality rate worldwide. Sorafenib is the only systemic treatment demonstrating a statistically significant but modest overall survival benefit. We previously have identified the aurora kinases (AURKs) and FMS-like tyrosine kinase 3 (FLT3) multikinase inhibitor DBPR114 exhibiting broad spectrum anti-tumor effects in both leukemia and solid tumors. The purpose of this study was to evaluate the therapeutic potential of DBPR114 in the treatment of advanced HCC.

Methods

Human HCC cell lines with histopathology/genetic background similar to human HCC tumors were used for in vitro and in vivo studies. Human umbilical vein endothelial cells (HUVEC) were used to evaluate the drug effect on endothelial tube formation. Western blotting, immunohistochemical staining, and mRNA sequencing were employed to investigate the mechanisms of drug action. Xenograft models of sorafenib-refractory and sorafenib-acquired resistant HCC were used to evaluate the tumor response to DBPR114.

Results

DBPR114 was active against HCC tumor cell proliferation independent of p53 alteration status and tumor grade in vitro. DBPR114-mediated growth inhibition in HCC cells was associated with apoptosis induction, cell cycle arrest, and polyploidy formation. Further analysis indicated that DBPR114 reduced the phosphorylation levels of AURKs and its substrate histone H3. Moreover, the levels of several active-state receptor tyrosine kinases were downregulated by DBPR114, verifying the mechanisms of DBPR114 action as a multikinase inhibitor in HCC cells. DBPR114 also exhibited anti-angiogenic effect, as demonstrated by inhibiting tumor formation in HUVEC cells. In vivo, DBPR114 induced statistically significant tumor growth inhibition compared with the vehicle control in multiple HCC tumor xenograft models. Histologic analysis revealed that the DBPR114 treatment reduced cell proliferation, and induced apoptotic cell death and multinucleated cell formation. Consistent with the histological findings, gene expression analysis revealed that DBPR114-modulated genes were mostly related to the G2/M checkpoint and mitotic spindle assembly. DBPR114 was efficacious against sorafenib-intrinsic and -acquired resistant HCC tumors. Notably, DBPR114 significantly delayed posttreatment tumor regrowth and prolonged survival compared with the regorafenib group.

Conclusion

Our results indicated that targeting AURK signaling could be a new effective molecular-targeted agent in the treatment of patients with HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12929-022-00788-0.

MAPK-RAP1A Signaling Enriched in Hepatocellular Carcinoma Is Associated With Favorable Tumor-Infiltrating Immune Cells and Clinical Prognosis

Background

MAPK-RAP1A signaling, which is involved in cancer progression, remains to be defined. Upregulation of MAPK-RAP1A signaling accounts for most cancers that harbor high incident rate, such as non-small cell lung cancer (NSCLC) and pancreatic cancer, especially in hepatocellular carcinoma (HCC). MAPK-RAP1A signaling plays an important function as clinical diagnosis and prognostic value in cancers, and the role of MAPK-RAP1A signaling related with immune infiltration for HCC should be elucidated.

Methods

Microarray data and patient cohort information from The Cancer Genome Atlas (TCGA; n = 425) and International Cancer Genome Consortium (ICGC; n = 405) were selected for validation. The Cox regression and least absolute shrinkage and selection operator (LASSO) were used to construct a clinical prognostic model in this analysis and validation study. We also tested the area under the curve (AUC) of the risk signature that could reflect the status of predictive power by determining model. MAPK-RAP1A signaling is also associated with tumor-infiltrating immune cells (TICs) as well as clinical parameters in HCC. The GSEA and CIBERSORT were used to calculate the proportion of TICs, which should be beneficial for the clinical characteristics (clinical stage, distant metastasis) and positively correlated with the survival of HCC patients.

Results

HCC patients with enrichment of MAPK-RAP1A signaling were associated with clinical characteristics and favorable T cell gamma delta (Vδ T cells), and STMN1, RAP1A, FLT3, HSPA8, ANGPT2, and PGF were used as candidate biomarkers for risk scores of HCC. To determine the molecular mechanism of this signature gene association, Gene Set Enrichment Analysis (GSEA) was proposed. Cytokine-cytokine receptor interaction, TGF-β signaling pathway, and Intestinal immune network for IgA production gene sets were closely related in MAPK-RAP1A gene sets. Thus, we established a novel prognostic prediction of HCC to deepen learning of MAPK-RAP1A signaling pathways.

Conclusion

Our findings demonstrated that HCC patients with enrichment of MAPK-RAP1A signaling were associated with clinical characteristics and favorable T cell gamma delta (Vδ T cells), which may be a novel prognostic prediction of HCC.

Prognostic Nomogram for Sorafenib Benefit in Hepatitis B Virus-Related Hepatocellular Carcinoma After Partial Hepatectomy

Background

Predicting the long-term prognosis of individuals who experienced sorafenib treatment following partial hepatectomy due to hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is difficult. This work aims to create an effective prognostic nomogram for HBV related HCC patients who are receiving sorafenib treatment as adjuvant therapy after surgery.

Methods

A total of 233 HBV-related HCC patients treated with or without sorafenib following partial hepatectomy at the Eastern Hepatobiliary Surgery Hospital from 2008 to 2013 were matched with propensity score matching analysis. The optimal cut-off point of the overall survival (OS) factor level was determined by x-tile. The selection of indicators was based on clinical findings. The Cox regression model with an interaction term was employed for evaluating the predictive value. Using a multivariate Cox proportional hazards model, a nomogram was subsequently formulated to analyze 111 patients treated with sorafenib. The nomogram's discriminative ability and predictive accuracy were determined using the concordance index (C-index), calibration, and ROC curve.

Results

The matched sorafenib cohort of 111 patients and control cohort of 118 patients were analyzed. Subgroup analysis revealed that low GPC3, pERK, pAKT, serum AFP levels, without MVI, under 50 years old, male, TNM stage I/II and BCLC stage 0/A were significantly associated with a better OS in patients subjected to sorafenib treatment compared to those without sorafenib treatment after surgery. Multivariate analysis of the sorafenib cohort revealed GPC3, pERK, pAKT, serum AST, and BCLC stage as independent factors for OS, and all were included in the nomogram. The survival probability based on the calibration curve showed that the prediction of the nomogram was in good agreement with the actual observation. The C-index of the nomogram for predicting survival was 0.73(95% CI, 0.67-0.78). The area under the ROC curve (AUC) for the nomogram to predict the survival for 1, 3, and 5-year was 0.726, 0.816, and 0.823, respectively.

Conclusion

This proposed nomogram shows the potential to make a precise prediction regarding the prognosis of HBV-related HCC patients and may help to stratify patients for personalized therapy following partial hepatectomy.

Molecular subtyping of hepatocellular carcinoma: A step toward precision medicine

Hepatocellular carcinoma (HCC) is one of the most prevalent and fatal digestive tumors. Treatment for this disease has been constraint by heterogeneity of this group of tumors, which has greatly limited the progress in personalized therapy. Although existing studies have revealed the genetic and epigenetic blueprints that drive HCCs, many of the molecular mechanisms that lead to HCCs remain elusive. Recent advances in techniques for studying functional genomics, such as genome sequencing and transcriptomic analyses, have led to the discovery of molecular mechanisms that participate in the initiation and evolution of HCC. Integrative multi-omics analyses have identified several molecular subtypes of HCC associated with specific molecular characteristics and clinical outcomes. Deciphering similar molecular features among highly heterogeneous HCC patients is a prerequisite to implementation of personalized therapeutics. This review summarizes the current research progresses in precision therapy on the backbone of molecular subtypes of HCC.