Chen et al. Cancer Cell Int (2021) 21:291 https://doi.org/10.1186/s12935-021-01928-6 Cancer Cell International PRIMARY RESEARCH Open Access Construction of a prognostic model with histone modifcation-related genes and identifcation of potential drugs in pancreatic cancer Yuan Chen† , Ruiyuan Xu†, Rexiati Ruze, Jinshou Yang, Huanyu Wang, Jianlu Song, Lei You, Chengcheng Wang* and Yupei Zhao* Abstract Background: Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. An efective prediction model is urgently needed for the accurate assessment of patients’ prognosis to assist clinical decision-making. Methods: Gene expression data and clinicopathological data of the samples were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Dif- ferential expressed genes (DEGs) analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, random forest screening and multivariate Cox regression analysis were applied to construct the risk signature. The efectiveness and independence of the model were validated by time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier (KM) survival analysis and survival point graph in training set, test set, TCGA entire set and GSE57495 set. The validity of the core gene was verifed by immunohistochemistry and our own independent cohort. Meanwhile, functional enrichment analysis of DEGs between the high and low risk groups revealed the potential biological pathways. Finally, CMap database and drug sensitivity assay were utilized to identify potential small molecular drugs as the risk model-related treatments for PC patients. Results: Four histone modifcation-related genes were identifed to establish the risk signature, including CBX8, CENPT, DPY30 and PADI1. The predictive performance of risk signature was validated in training set, test set, TCGA entire set and GSE57495 set, with the areas under ROC curve (AUCs) for 3-year survival were 0.773, 0.729, 0.775 and 0.770 respectively. Furthermore, KM survival analysis, univariate and multivariate Cox regression analysis proved it as an independent prognostic factor. Mechanically, functional enrichment analysis showed that the poor prognosis of high-risk population was related to the metabolic disorders caused by inadequate insulin secretion, which was fueled by neuroendocrine aberration. Lastly, a cluster of small molecule drugs were identifed with signifcant potentiality in treating PC patients. *Correspondence: [email protected]; [email protected] †Yuan Chen and Ruiyuan Xu contributed equally to this work Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100023, People’s Republic of China © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://crea- tivecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdo- main/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Chen et al. Cancer Cell Int (2021) 21:291 Page 2 of 22 Conclusions: Based on a histone modifcation-related gene signature, our model can serve as a reliable prognosis assessment tool and help to optimize the treatment for PC patients. Meanwhile, a cluster of small molecule drugs were also identifed with signifcant potentiality in treating PC patients. Keywords: Histone modifcation, Prognostic model, CBX8, CENPT, DPY30, PADI1, Potential drugs, Pancreatic cancer Background histone modifcations of cancer-related genes may lead Pancreatic cancer is one of the most lethal malignan- to abnormal activation or silencing of these genes, lead- cies, with a 5-year survival rate of only 10% in the United ing to the occurrence and progression of PC. Moreover, States [1]. According to the latest epidemiological data, it the changes of histone modifers tend to regulate the his- is reported that there are 495,773 new cases worldwide tone modifcation of a list of genes rather than targeting in 2020, and approximately 466,003 will die of this dis- a specifc gene. Terefore, it may lead to a series of gene ease, ranking 14th and 7th among all cancers respectively expression changes and produce a large-scale genetic [2]. In addition to the malignant characteristics of the PC remodeling in cells, which further demonstrates the piv- itself and the lack of early screening methods, the disap- otal role of histone modifcation in the development of pointing prognosis of this disease is largely attributable PC. For example, the transcription factor FOXA1 pro- to the lack of efective risk prediction models. Although motes PC progression by driving large-scale enhancer advanced surgical techniques, targeted drugs, radio- reprogramming through H3K27ac (acetylation of lysine therapy and chemotherapy drugs have been applied, the 27 of histone 3) modulation [18]. Histone lysine meth- survival benefts of these treatments are questionable and yltransferases enhancer of zeste homolog 2 (EZH2) has side efects occur to varying degrees for each individual been found to act as both an oncogene and a tumor sup- [3, 4]. Te treatment of PC should be individualized and pressor, since it maintains, rather than specifes, the tran- systematic, which can ensure a maximum gain and mini- scriptional repression state of thousands of target genes mum risk. Terefore, an efective prediction model is [19]. In view of the proposed concept of histone code and urgently needed for the accurate assessment of patients’ the critical role of histone modifcation in the progres- prognosis to assist clinical decision-making. In this con- sion of PC [20], we consider a prognosis signature based text, doctors can decide whether a more aggressive treat- on histone modifcation-related genes to better predict ment regimen is needed, and an efcacious treatment the prognosis of PC patients and optimize the clinical with balanced benefts and side efects can be selected. decision-making. Traditional risk stratifcation systems, such as AJCC In this study, we reported a risk signature model based TNM staging, has been proved to have nondiscrimina- on genes associated with histone modifcation to predict tory predictive efcacy for PC [5, 6]. However, more pre- the prognosis of PC patients. Four histone modifcation- dictive models are required to evaluate the prognosis of related genes were identifed to construct the risk signa- PC in multiple dimensions. With the large-scale appli- ture, which was proved to be an independent risk factor cation of next-generation sequencing and microarray and was validated in the training set, testing set, entire technology in disease research, the use of specifc gene set and GSE57495 set. Furthermore, functional enrich- expression levels and mutation status to assess disease ment analysis showed that the poor prognosis of high- prognosis has become increasingly accessible [7, 8]. Actu- risk population was related to the metabolic disorders ally, a number of studies have demonstrated that specifc caused by inadequate insulin secretion, which was fueled gene expression or mutant characteristics can efectively by neuroendocrine abnormality. Finally, CMap database predict the prognosis of tumors [9, 10]. Concomitantly, and drug sensitivity assay were utilized to identify poten- the establishment of prognostic models for PC has also tial drugs as the risk model-related treatments for PC been extensively reported, including whole-gene predic- patients. tion model [11–13], lncRNA-related prediction model [14], immune gene-related prediction model [15], and Methods ceRNA-related model [16], etc. At the same time, the Datasets sources and processing pivotal role of histone modifcation in the progression of Histone modifcation-related genes were extracted from PC is gradually revealed in recent years. Histone modif- the in Gene Set Enrichment Analysis (GSEA) website cations, mainly involving acetylation, methylation, phos- (https:// www. gsea- msigdb. org/ gsea/ index. jsp; ≤ Sep phorylation and ubiquitylation, represent a versatile set 1, 2020). Gene expression data was downloaded from of epigenetic marks that regulate multiple dynamic cel- UCSC XENA website (https:// xenab rowser. net/ datap lular processes [17]. Under certain conditions, aberrant ages/; ≤ Sep 1, 2020), which included 167 normal tissues Chen et al. Cancer Cell Int (2021) 21:291 Page 3 of 22 and 179 tumor tissues of pancreas. For all tumor sam- nlm. nih. gov/ geo/) for external validation. It was per- ples in subsequent analysis gene