Abstract

NF-Y is a pioneer trimeric transcription factor formed by the Histone Fold Domain (HFD) NF-YB/NF-YC subunits and NF-YA. Three subunits are required for DNA binding. CCAAT-specificity resides in NF-YA and transactivation resides in Q-rich domains of NF-YA and NF-YC. They are involved in alternative splicing (AS). We recently showed that NF-YA is overexpressed in breast and lung carcinomas. We report here on the overexpression of all subunits in the liver hepatocellular carcinoma (HCC) TCGA database, specifically the short NF-YAs and NF-YC2 (37 kDa) isoforms. This is observed at all tumor stages, in viral-infected samples and independently from the inflammatory status. Up-regulation of NF-YAs and NF-YC, but not NF-YB, is associated to tumors with mutant p53. We used a deep-learning-based method (DeepCC) to extend the partitioning of the three molecular clusters to all HCC TCGA tumors. In iCluster3, CCAAT is a primary matrix found in promoters of up-regulated genes, and cell-cycle pathways are enriched. Finally, clinical data indicate that, globally, only NF-YAs, but not HFD subunits, correlate with the worst prognosis; in iCluster1 patients, however, all subunits correlate. The data show a difference with other epithelial cancers, in that global overexpression of the three subunits is reported and clinically relevant in a subset of patients; yet, they further reinstate the regulatory role of the sequence-specific subunit.

Highlights

  • Liver cancer is one of the most widespread types of cancer worldwide

  • Histone Fold Domain (HFD) subunits appear to be in excess with respect to NF-YA inside nuclei; in keeping with this, HFD levels are higher Transcript per Million (TPM)-wise, as we found previously in Breast Carcinomas (BRCA), Lung Squamous Cells Carcinomas (LUSC) and LUAD

  • The available TCGA classification of hepatocellular carcinoma (HCC) in the three molecular iClusters comprises 183 tumors; we extended it to all HCC tumors by using the deep cancer subtype classification tool (DeepCC) version 0.1, which is based on the deep learning of functional spectra-quantifying activities [45]

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Summary

Introduction

Its major form is Hepatocellular Carcinoma (HCC) [1,2]. There are several risk factors in developing HCC, such as chronic viral infections (HBV and HCV), alcohol abuse, autoimmune hepatitis and metabolic diseases [3,4]. These conditions are believed to cause chronic inflammation, which entails continuous necrosis and tissue regeneration. This process causes the fixation of cumulative genetic and epigenetic changes, resulting in cancer [5]. In addition to the identification of mutated genes, alterations of DEG (Differentially Expressed Genes) have been determined in many studies: RNA-seq analysis allowed TCGA to classify HCC in three subtypes, iCluster1/2/3 [6]; these clusters correspond well to the classes previously identified based on analysis of large databases of microarray profiling [7]

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