HN1 as a diagnostic and prognostic biomarker for liver cancer

Abstract Background: The present study aimed to examine the diagnostic and prognostic value of HN1 in terms of overall survival (OS) and recurrence-free survival (RFS) in liver cancer and its potential regulatory signaling pathway. Methods: We obtained clinical data and HN1 RNA-seq expression data of liver cancer patients from The Cancer Genome Atlas database, and analyzed the differences and clinical association of HN1 expression in different clinical features. We uesd receiver-operating characteristic curve to evaluate the diagnosis capability of HN1. We analyzed and evaluated the prognostic significance of HN1 by Kaplan–Meier curves and Cox analysis. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to HN1 expression. Results: HN1 mRNA was up-regulated in liver cancer, and was associated with age, histologic grade, stage, T classification, M classification, and vital status. HN1 mRNA had ideal specificity and sensitivity for the diagnosis (AUC = 0.855). Besides, the analysis of Kaplan–Meier curves and Cox model showed that HN1 mRNA was strongly associated with the overall survival and could be well-predicted liver cancer prognosis, as an independent prognostic variable. GSEA analysis identified three signaling pathways that were enriched in the presence of high HN1 expression. Conclusion: HN1 serves as a biomarker of diagnosis and prognosis in liver cancer.


Introduction
Liver cancer is one of the malignancies with a high mortality rate. According to the latest statistics of 2018, 782,000 died of liver cancer, and the cancer mortality rate ranks fourth in the world [1]. Despite diagnostic techniques and the treatment means to become more abundant for liver cancer [2][3][4][5], the improvement of liver cancer prognosis is still disappointing [6]. Recently, exploring specific biomarkers and integrating them into clinical prognosis evaluation have become one of the main research directions of cancer. [7] Hematological and neurological expressed 1 (HN1) also known as Jupiter microtubule-associated homolog 1 (JPT1) was first discovered in mouse embryos and is located on human chromosome 17q25.2 [8,9]. Although the functional role of HN1 is still not completely clear in human cells, current studies indicate that HN1 is involved in regulating cell cycle, growth, repair, and regeneration processes in embryo, retinal, hematopoietic and neurologic cells, and the high conservation of this gene suggests its function is important to the human [10][11][12].In the early time Huang et al. found that HN1 was up-regulated and associated with cancer metastasis in prostate cancer [13]. Then HN1 was found to be highly expressed in several cancers, such as lung cancer [14], breast cancer [15,16], melanoma [17], malignant gliomas [10], and epithelial ovarian cancer [18].
However, no studies investigated the association between HN1 expression and liver cancer up to now. In this study, we explored the relationship between HN1 mRNA and clinical features of liver cancer and evaluated the potential value of HN1 mRNA in the diagnosis and prognosis of liver cancer patients.

Data collection
The data in this study was obtained from TCGA-Liver Hepatocellular Carcinoma.
The data included RNA-seq expression of HN1 and clinical information of liver cancer patients with 50 normal liver tissue and 373 liver cancer tissue.

Statistical Analysis
Data management and analysis were performed using R version 3

Gene set enrichment analysis (GSEA)
GSEA determines whether an a priori defined set of genes has statistically significant differences in expression under two different biological conditions [23,24]. This analysis, performed using GSEA software 3.0 from the Broad Institute, was used for analysis of RNAseq data from TCGA-LIHC. The gene set of "h.all.v6.2.symbols.gmt", which summarizes and represents specific, well-defined biological states or processes, was downloaded from the Molecular Signatures Database (http://software.broadinstitute.org/gsea/msigdb/index.jsp). The normalized enrichment score (NES) was determined by analysis of 1000 permutations. A gene set was considered significantly enriched when the p-value was less than 0.05 and the false discovery rate (FDR) was less than 0.25.

Patient characteristic
Data including HN1 mRNA expression and basic clinical information had been collected from 373 liver cancer patients. The staging of TNM classification and stage was referred to AJCC [25]. Detailed data were shown in Table 1.

HN1 mRNA expression was upregulated in patients with liver carcinoma
Box-plots showed that the HN1 mRNA expression in liver cancer patients was significantly higher than that in the normal group(P=3.4e -16 )( Figure 1). In addition, HN1 expression also had significant differences in variable groups including Especially, HN1 mRNA expression was increased with the malignant degree increased according to histologic grade.

The diagnostic capability of HN1 in liver cancer
As ROC curve showed, HN1 mRNA expression has ideal specificity and sensitivity for the diagnosis of all liver cancer patients (AUC=0.855, Figure 2 Table 1).

High HN1 predicts poor prognosis of OS and RFS.
Kaplan-Meier survival curve with the log-rank test was performed to assess the prognostic value of HN1 in OS. The results showed that high HN1 expression was associated with poor OS (P<0.0001; Figure 3). Besides, survival curve with the log-rank test was performed to assess the prognostic value of HN1 in RFS. The results showed that high HN1 expression was associated with poor RFS (P=0.03; Figure 3)

Subgroup analysis identified the prognostic value of HN1 in OS.
Subgroup analysis showed that high HN1 expression was correlated with poor OS

Subgroup analysis identified the prognostic value of HN1 in RFS.
Subgroup analysis showed that high HN1 expression was correlated with poor OS of cases with grade G1/G2 (P=0.044) and male (P=0.017) ( Figure 5). However, stage I/II, stage III/IV, younger and older showed no significance in the prognostic value of

GSEA identifies HN1-related signaling pathway
We compared the data sets for low and high HN1 expression using GSEA to identify signaling pathways activated during liver cancer. The results indicated significant differences (FDR < 0.25, NOM p-value < 0.05) in the enrichment of the MSigDB collection (h.all.v6.2.symbols.gmt; Table 2). We selected the most significantly enriched signaling pathways, based on normalized enrichment score (NES) (Figure 7, Table 2). The results indicated the data set with high HN1 expression was enriched for DNA repair, G2M checkpoint, E2F targets.
Consistent with these results, we found HN1 mRNA overexpression in liver cancer. This finding also makes it possible for HN1 to act as target molecules of liver cancer.
HN1 can enhance oncogenic factor MYC [15], and the LEPR-STAT3 pathway, which manages the BCSC path and maintains CSC self-renewal [38][39][40][41][42][43]. MYC [15], LEPR, STAT3 [16] [15]pointed out that the HN1 overexpression promoted self-renewal of CSCs in breast. Another latest research reports that HN1 is identified as a critical regulatory gene for breast CSC maintenance and promotes breast cancer progression by LEPR-STAT3 pathway [16], which regularize CSC self-renewal [38][39][40][41][42][43]. In the study of melanoma and glioma, HN1 is also involved in the process of differentiation or dedifferentiation in cancer cells [10,17]. These suggest that HN1 may regulate the growth and differentiation of CSCs, promote the metastasis and recurrence of liver cancer, and lead to the poor prognosis of liver cancer patients finally. Consistent with these findings, we found that high HN1 could predict poor prognosis in liver cancer, which may involve in DNA repair, G2M checkpoint, E2F targets.
In summary, we found HN1 mRNA over-expressed in liver cancer, explore the diagnostic value of HN1, and revealed that HN1 can independently predict and assess the prognosis of liver cancer patients. HN1 serves as a biomarker of diagnosis and prognosis in liver cancer. However, our study focuses on the clinical significance and do not explore the molecular mechanism. In future work, we will do some in vivo and in vitro experiments to explore the underlying mechanism in liver cancer. Laughlin          Cutoff value determined by ROC curve.