Abstract

Background

   Nicotinamide (NAM+) regulates redox and metabolic activities in the
   mitochondria. The intention of the research was to identify key genes
   that relate to nicotinamide in hepatocellular carcinoma (HCC).

Methods

   Relevant clinical information were collected as well as RNA-seq data
   using the Cancer Genome Atlas (TCGA) database. Differential analysis
   was used to discover the genes that were differently expressed. On the
   key genes associated with NAM, functional enrichment analysis was
   carried out. Next, receiver operating characteristic (ROC) and
   prognosis Kaplan-Meier (K-M) curve analyses were used to evaluate the
   importance of important gene expression, respectively. The immune cell
   signatures were estimated using the CIBERSORT algorithm. Finally, the
   anticancer impact of NAM on HCC was experimentally confirmed, and
   important genes NADSYN1 and NT5C were validated at the protein level in
   clinical specimens.

Results

   Six prognostic key genes (NAXE, NADSYN1, NT5C, NT5C3A, PNP and NT5E)
   were identified. There is an association between the level of key gene
   expression and the clinical prognosis. Four key genes (NAXE, NADSYN1,
   NT5C and NT5C3A) have statistical significance of survival prognosis.
   Finally, the expression of NAM-related genes and the inhibitory effect
   of NAM on HCC were verified by experiments.

Conclusion

   The study first found some Nicotinamide metabolism-related
   differentially expressed genes (NMRDEGs) that are related to HCC can
   contribute to predicting survival and monitoring the treatment.

   Keywords: hepatocellular carcinoma, nicotinamide, bioinformatics
   analysis, diagnostic, prognostic

Introduction

   The most frequent primary liver cancer is HCC, which also happens to be
   the sixth most common tumor. This malignancy has been gradually on the
   rise in terms of incidence and mortality in recent years. Numerous
   people continue to receive diagnoses of advanced-stage cancer with a
   wide range of symptoms, despite the significant improvements in cancer
   screening techniques.[40]^1 However, there are not many HCC patients
   who can benefit from successful therapy options. In order to improve
   all therapy approaches, it is vital that we explore more diagnostic
   biomarkers and potential therapeutic targets.

   The water-soluble vitamin B3 (niacin) has an amide form called NAM,
   which is more frequently found in foods like meat, fish, beans,
   mushrooms, nuts, and cereals. By use of the enzyme nicotinamide
   phosphate ribosyl transferase (NAMPT), NAM is directly transformed in
   living cells into nicotinamide mononucleotide (NMN), which subsequently
   binds to ATP to create nicotinamide adenine dinucleotide (NAD^+). NAM,
   the fundamental component of cellular energy metabolism, is crucial for
   the formation of NAD^+.[41]^2 Cancer is characterized by metabolic
   dysregulation, which promotes unregulated cancer growth.[42]^3 NAM is
   therefore thought to impact tumor growth through modifying cell
   metabolism.

   Based on the TCGA and GeneCards datasets, this study intended to locate
   nicotinamide-related genes in HCC and then confirmed the expression of
   these genes in multiple datasets acquired from the GEO database. Using
   the CIBERSORT approach, the link between niacinamide expression level
   and immune cell infiltration was investigated. The drug sensitivity
   investigation of NAM major genes related with HCC used the Genomics of
   Cancer Cell Line Encyclopedia (CCLE), Drug Sensitivity in Cancer
   (GDSC), and CellMiner databases. Our research identifies a trustworthy
   and feasible treatment target for HCC.

Materials and Methods

Data Acquisition

   The Liver Hepatocellular Carcinoma (LIHC) dataset was downloaded from
   TCGA database ([43]https://portal.gdc.cancer.gov/).[44]^4 374 cases of
   liver cancer samples (grouping: LIHC) and 50 cases of paracancerous
   samples (grouping: Normal) were got from the UCSC Xena database
   ([45]http://genome.ucsc.edu).[46]^5 The limma package was performed to
   normalize the count sequencing data of the TCGA-LIHC data set.[47]^6
   Using tool GEOquery, the LIHC-related datasets [48]GSE25097,
   [49]GSE46408 and [50]GSE84402[51]^7 were obtained.[52]^7–11 The probe
   names of the datasets were annotated using the pertinent GPL platform
   files ([53]supplementary Table S1).

Identification of Nicotinamide Metabolism-Related Genes (NMRGs)

   Forty-two NMRGs were acquired from related references, and eight NMRGs