Integrated tumor stromal features of hepatocellular carcinoma reveals two distinct subtypes with prognostic/predictive significance

Establishment and Clinical Application of the Nomogram Related to Risk or Prognosis of Hepatocellular Carcinoma: A Review

Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, accounting for approximately 90% of all primary liver cancers, with high mortality and a poor prognosis. A large number of predictive models have been applied that integrate multiple clinical factors and biomarkers to predict the prognosis of HCC. Nomograms, as easy-to-use prognostic predictive models, are widely used to predict the probability of clinical outcomes. We searched PubMed with the keywords "hepatocellular carcinoma" and "nomogram", and 974 relative literatures were retrieved. According to the construction methodology and the real validity of the nomograms, in this study, 97 nomograms for HCC were selected in 77 publications. These 97 nomograms were established based on more than 100,000 patients, covering seven main prognostic outcomes. The research data of 56 articles are from hospital-based HCC patients, and 13 articles provided external validation results of the nomogram. In addition to AFP, tumor size, tumor number, stage, vascular invasion, age, and other common prognostic risk factors are included in the HCC-related nomogram, more and more biomarkers, including gene mRNA expression, gene polymorphisms, and gene signature, etc. were also included in the nomograms. The establishment, assessment and validation of these nomograms are also discussed in depth. This study would help clinicians construct and select appropriate nomograms to guide precise judgment and appropriate treatments.

The Combined Signatures of Hypoxia and Cellular Landscape Provides a Prognostic and Therapeutic Biomarker in HBV-Related Hepatocellular Carcinoma

Prognosis and treatment options of hepatitis B virus‐related hepatocellular carcinoma (HBV‐HCC) are generally based on tumor burden and liver function. Yet, tumor growth and therapeutic resistance of HBV‐HCC are strongly influenced by intratumoral hypoxia and cells infiltrating the tumor microenvironment (TME). We, therefore, studied whether linking parameters associated with hypoxia and TME cells could have a better prediction of prognosis and therapeutic responses. Quantification of 109 hypoxia‐related genes and 64 TME cells was performed in 452 HBV‐HCC tumors. Prognostic hypoxia and TME cells signatures were determined based on Cox regression and meta‐analysis for generating the Hypoxia‐TME classifier. Thereafter, the prognosis, tumor, and immune characteristics as well as the benefit of therapies in Hypoxia‐TME defined subgroups were analyzed. Patients in the Hypoxia^low/TME^high subgroup showed a better prognosis and therapeutic responses than any other subgroups, which can be well elucidated based on the differences in terms of immune‐related molecules, tumor somatic mutations, and cancer cellular signaling pathways. Notably, our analysis furthermore demonstrated the synergistic influence of hypoxia and TME on tumor metabolism and proliferation. Besides, the classifier allowed a further subdivision of patients with early‐ and late‐HCC stages. In addition, the Hypoxia‐TME classifier was validated in another independent HBV‐HCC cohort (n = 144) and several pan‐cancer cohorts. Overall, the Hypoxia‐TME classifier showed a pretreatment predictive value for prognosis and therapeutic responses, which might provide new directions for strategizing patients with optimal therapies.

Identification of Gene-Set Signature in Early-Stage Hepatocellular Carcinoma and Relevant Immune Characteristics

Background

The incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene set-based signature for early-stage HCC (eHCC) patients and further explored specific marker dysregulation mechanisms as well as immune characteristics.

Methods

We performed an integrated bioinformatics analysis of genomic, transcriptomic, and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics, and biological function in the different pathological stage samples. Univariate and multivariate survival analyses were performed in The Cancer Genome Atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in Wistar rats was employed to verify the reliability of the predictions.

Results

We identified a Cluster gene that potentially segregates patients with eHCC from non-tumor, through integrated analysis of expression, overall survival, immune cell characteristics, and biology function landscapes. Immune infiltration analysis showed that lower infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (hazard ratio, 1.691; 95% CI: 1.171–2.441; p = 0.012), such as CD8 Tem and cytotoxic T cells (CTLs) in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTL immune cells (receiver operating characteristic (ROC) = 0.647) and cancerization (ROC = 0.946) in liver. As a central member of Cluster C1, overexpressed PRKDC was associated with the higher genetic alteration in eHCC than advanced-stage HCC (aHCC), which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rats was also confirmed.

Conclusions

As a tumor prognosis-relevant gene set-based signature, Cluster C1 showed an effective approach to predict cancerization of eHCC and its related immune characteristics with considerable clinical value.

ARHGEF11 promotes proliferation and epithelial-mesenchymal transition of hepatocellular carcinoma through activation of β-catenin pathway

Rho guanine nucleotide exchange factor 11 (ARHGEF11) has been proved to promote tumor metastasis in glioblastoma and ovarian carcinoma. However, the role of ARHGEF11 in hepatocellular carcinoma (HCC) progression is largely unknown. Here, we found that ARHGEF11 was upregulated in HCC samples and highly metastatic hepatoma cell lines. Knockdown of ARHGEFF11 inhibited the cell proliferation and invasion in both HCCLM3 and SKHEP1 cell lines. Subsequent mechanistic investigation showed that downregulation of ARHGEF11 significantly attenuated β-catenin nuclear translocation, thereafter repressed the expression of ZEB1 and cyclinD1, finally contributing to inhibition of epithelial-mesenchymal transition (EMT) and cell cycle arrest. Moreover, high levels of ARHGEF11 were found to be associated with shorter disease free and overall survival. A prognostic nomogram model that integrated ARHGEF11, tumor size and BCLC classification showed good performance in predicting clinical outcomes of HCC patients. Overall, this study demonstrated that ARHGEF11 could promote proliferation and metastasis of HCC via activating β-catenin pathway, suggesting that ARHGEF11 might serve as a potential prognostic biomarker for HCC.

Existence of intratumoral tertiary lymphoid structures is associated with immune cells infiltration and predicts better prognosis in early-stage hepatocellular carcinoma

Tumor-associated tertiary lymphoid structures (TLS) play a critical role in the progression of various tumors. However, the dynamics of lymphocyte recruitment during hepatocellular carcinoma (HCC) clinical progression have not been fully elucidated. In the present study, tissue microarrays and hematoxylin-eosin staining were used to evaluate the existence and degree of TLS in HCC patients. Nine immune biomarkers in intratumoral tissues were examined by immunohistochemical staining. A total of 462 patients were recruited for the study. Kaplan-Meier analysis showed that TLS was inversely correlated with the risk of early tumor recurrence (P=0.014), whereas no association was found between TLS and overall survival. Cox regression analysis identified TLS as an independent prognostic factor for early HCC recurrence (P=0.005). In addition, TLS was associated with increased intratumoral CD3+, CD8+, CD20+, and decreased infiltration of Foxp3+ and CD68+ cells. A lower density of PD1+, TIM3+, and LAG3+ were found in TLS+ cases. Sub-analysis revealed the prognostic value of TLS on early-stage HCC (BCLC 0-A, TNM stage I-II) and HCC with solitary nodule. The validation cohort verified the prognostic value of TLS in early-stage HCC patients. These results suggest that TLS-targeted immune-modulating therapies may be a potential strategy for effective immune-mediated tumor suppression.