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The complement cascade plays a "complementing" role in human immunity. However, the potential roles of complement system in impacting molecular and clinical features of hepatocellular carcinoma (HCC) remain unclear. In this study, eleven public datasets are analyzed to compare the complement status between normal and cancerous samples based on 18 classical complement-associated genes. The complement scores are constructed to quantify complement signatures of individual tumors. HCC patients in the The Cancer Genome Atlas (TCGA) cohort are focused to perform systematical analyses between complement status and immune infiltration, miRNA expression, DNA methylation, clinicopathological features, and drug response. The results show that the complement scores in normal tissues are dramatically higher than those of tumor tissues. Tumor samples in the TCGA cohort are classified into complement score-low and score-high groups. Pathway analysis reveals that tumor-promoting pathways are typically inhibited in complement score-high group. This study also shows that tumor-killing immune cells, such as CD8

Intrahepatic cholangiocarcinoma (ICC) remains a highly heterogeneous disease with poor prognosis. Tumor‐infiltrating lymphocytes were predictive in various cancers, but their prognostic value in ICC is less clear. A total of 168 ICC patients who had received liver resection were enrolled and assigned to the derivation cohort. Sixteen immune markers in tumor and peritumor regions were examined by immunohistochemistry. A least absolute shrinkage and selection operator model was used to identify prognostic markers and to establish an immune signature for ICC (ISICC). An ISICC‐applied prediction model was built and validated in another independent dataset. Five immune features, including CD3peritumor (P), CD57P, CD45RAP, CD66bintratumoral (T) and PD‐L1P, were identified and integrated into an individualized ISICC for each patient. Seven prognostic predictors, including total bilirubin, tumor numbers, CEA, CA19‐9, GGT, HBsAg and ISICC, were integrated into the final model. The C‐index of the ISICC‐applied prediction model was 0.719 (95% CI, 0.660‐0.777) in the derivation cohort and 0.667 (95% CI, 0.581‐0.732) in the validation cohort. Compared with the conventional staging systems, the new model presented better homogeneity and a lower Akaike information criteria value in ICC. The ISICC‐applied prediction model may provide a better prediction performance for the overall survival of patients with resectable ICC in clinical practice., Using tissue microarray, we examined the density of 16 immune biomarkers in 280 ICC patients who underwent hepatectomy, and established a novel ISICC‐based prediction model (IPM) to predict patients’ overall survival with bilirubin, tumor numbers, CEA, CA19‐9, γ‐glutamyl transferase (GGT), HBsAg and ISICC. The new model may provide a better prediction performance for the overall survival of patients with resectable ICC in clinical practice.

Lysyl oxidase like 4 (LOXL4), a member of the secreted copper-dependent amine oxidases that contribute to the assemble and maintenance of the extracellular matrix (ECM), was found to be up-regulated or down-regulated in different cancer types, suggesting its paradoxical roles in cancer. The specific role of LOXL4 in hepatocellular carcinoma (HCC), however, is still yet to be defined. Twenty-eight pairs of HCC specimens were used for LOXL4 mRNA expression analysis. The mRNA expression in HCC cell lines was examined, and HepG2 was selected for LOXL4 small interfering RNA (siRNA) interference to investigate the biological function of LOXL4, LOXL4 immunohistochemical staining was performed using a tissue microarray containing 298 HCC patients. The prognostic and diagnostic value of LOXL4 was evaluated using Cox regression and Kaplan-Meier analysis. LOXL4 mRNA or protein expression was significantly lower in HCC tissues than peritumoral tissues (LOXL4 mRNA expression, P = 0.018; LOXL4 protein expression, P < 0.001). Low LOXL4 expression was associated with lower overall survival (OS) rates and higher cumulative recurrence rates. Multivariate analysis indicated that LOXL4 was an independent prognostic indicator for OS and time to recurrence (TTR). Our results revealed that LOXL4 was down-regulated in HCC and correlated with aggressive tumors and a worse clinical outcome. LOXL4 may be a potential biomarker to identify the HCC patients with a higher risk of recurrence.