Expression, Prognosis, and Immune Infiltrates Analyses of E2fs in Human Brain and CNS Cancer

Hindawi BioMed Research International Volume 2020, Article ID 6281635, 17 pages https://doi.org/10.1155/2020/6281635

Research Article Expression, Prognosis, and Immune Infiltrates Analyses of E2Fs in Human Brain and CNS Cancer

Pan Liao,1 Shuzhen Han ,2 and Honglan Qu 3

1Inner Mongolia University for the Nationalities, Tongliao, China 2Department of Neurology, Inner Mongolia Forestry General Hospital, Yakeshi, Inner Mongolia, China 3Department of Oncology, Inner Mongolia Forestry General Hospital, Yakeshi, Inner Mongolia, China

Correspondence should be addressed to Shuzhen Han; [email protected] and Honglan Qu; [email protected]

Received 23 April 2020; Accepted 6 August 2020; Published 15 December 2020

Academic Editor: Bilal Alatas

Copyright © 2020 Pan Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Objective. We investigated the expression patterns, potential functions, unique prognostic value, and potential therapeutic targets of E2Fs in brain and CNS cancer and tumor-infiltrating immune cell microenvironments. Methods. We analyzed E2F mRNA expression levels in diverse cancer types via Oncomine and GEPIA databases, respectively. Moreover, we evaluated the prognostic values using GEPIA database and TCGAportal database and the correlation of E2F expression with immune infiltration and the correlation between immune cell infiltration and GBM and LGG prognosis via TIMER database. Then, cBioPortal, GeneMANIA, and DAVID databases were used for mutation analysis, PPI network analysis of coexpressed gene, and functional enrichment analysis. Results. E2F1-8 expression increased in most cancers, including brain and CNS cancer. Higher expression in E2F1, 2, 4, 6, 7, and 8 indicated poor OS of LGG. Higher E2F3–6 and E2F1–8 expressions correlated with poor prognosis and increased immune infiltration levels in CD8+ T cells, macrophages, neutrophils, and DCs in GBM and CD8+ T cells, B cells, CD4+ T cells, neutrophils, macrophages, and DCs in LGG, respectively. Conclusion. E2F1–8 and E2F2–8 could be hopeful prognostic biomarkers of GBM and LGG, respectively. E2F3–6 and E2F1–8 could be likely therapeutic targets in patients with immune cell infiltration of GBM and LGG, respectively.

1. Introduction therapy, which is far from sufficient in combating cancer development. Tumor-infiltrating lymphocytes are an inde- E2Fs, as a set of genes encoding transcription factor family pendent predictor of sentinel lymph node status, and sur- (TFs) in higher eukaryotes, play an essential role in cell cycle vival in cancers [7] and immunotherapy has been regulation and DNA synthesis [1]. In some human malig- considered a promising direction because of its ability to nancies, E2F activator expression is deactivated and is penetrate the blood-brain barrier to treat these tumors deregulated. A report demonstrating that increased expres- since the first discovery of lymphatic in CNS [8]. How- sion in E2F3a played a significant role in the development ever, current immunotherapies, for example, anti-CTLA4, of glioma. This study suggests that E2Fs could promote demonstrated poor clinical efficacy in brain tumors [9]. cancer development [2]. CAR T cells also still face substantial obstacles in treating Worldwide, brain and CNS cancer are commonly diag- brain tumors [10]. Besides, after the diagnosis of malig- nosed as cancers and the causes of tumor death [3]. nant brain and CNS tumors, the overall 5-year relative Almost 80% of malignant brain cancers are gliomas [4]. survival rate was 32.1%, of which the survival rate was In 2016, based on data from groundbreaking research only 4.9% after the diagnosis of GBM (glioblastoma multi- [5], the WHO improved the correct classification of forme) [4], and metastasis often leads to a poor prognosis. glioma subtypes by integrating tumor morphology and Due to the heterogeneity of tumors, currently, there are molecular genetic information [6]. The clinical therapy of some limitations in the biomarkers that can predict prog- these cancers includes surgery, radiotherapy, and chemo- nosis, so it is necessary to search for new biomarkers in 2 BioMed Research International this field as prognostic indicators, to improve prognosis. sets [25]. We used cBioPortal to analyze E2F alterations in Also, there is an urgent need to identify new therapeutic the glioblastoma multiforme (TCGA, Firehose Legacy) data- targets in the brain and CNS cancer so as to effectively set, including data from 604 cases with pathology reports, improve the accuracy of treatment. and the brain lower-grade glioma (TCGA, PanCancer Atlas) E2F plays a complex and unique role in human brain dataset, including data from 514 cases with pathology and CNS tumors. E2F1/DP1 complex was reported to inhibit reports. The search parameters included mutations, putative the mismatch repair proteins MSH2, MSH6, and EXO1, as copy number alterations (CNAs) from genomic identifica- well as the homologous recombinant protein RAD51, lead- tion of significant targets in cancer (GISTIC), mRNA expres- ing to cell apoptosis [11]. Overexpression of E2F1 blocked sion Z scores (RNA-seq v.2 RSEM), and protein expression Z the proliferation repression caused by miR-342-3p or miR- scores (reverse phase protein array (RPPA)). Additionally, 377 in glioma cells [12], and E2F1 overexpression conferred Kaplan–Meier survival curves were drawn in cBioPortal to resistance to cisplatin in glioma cells [13]. Studies have evaluate the influence of gene alterations of E2Fs on the shown that downregulation of E2F2 inhibits glioma cell overall survival of GBM and LGG patients. growth [14]. Overexpression of E2F2 promoted the progression of NSCLC cells [15]. Increased expression in E2F3a 2.4. TCGAportal Database Analysis. TCGAportal was used to played a significant function in glioma development [2]. further verify the prognostic value of mRNA level of E2F Change in human GBM cell cycle is related to the decrease factors in GBM and LGG patients. of E2F4 level [16]. The silencing of E2F5 inhibited the prolif- 2.5. TIMER Database Analysis. TIMER database includes erative ability of GBM cells [17]. Moreover, the combination 10,897 samples across 32 cancer types from The Cancer of E2F6 and MATN1-AS1, which negatively targeted RELA, Genome Atlas (TCGA) to estimate the abundance of inhibited the MAPK signaling pathway, thus inhibiting the immune infiltrates [26]. We analyzed the correlation of the proliferation and invasion of GBM cells [18]. E2F7 could E2F expression with the abundance of immune infiltrates, induce autophagy of glioma [19]. Targeting E2F8 can also including B cells, CD4+ T cells, CD8+ T cells, neutrophils, regulate the development in glioma [20]. However, the macrophages, and dendritic cells, via gene modules. In addi- underlying mechanisms of E2F activation or inhibition and tion, correlations between immune cell infiltration and GBM the distinct functions of E2Fs and tumor immunology in and LGG prognosis were explored via correlation modules. brain and CNS tumor have not been fully elucidated. Lastly, we assessed how the E2F expression correlated with As far as we know, bioinformatics analysis and immune the expression of particular immune infiltrating cell subset infiltrate analysis have not been used to study the function markers. of E2Fs from tumors of the brain and CNS. As an important part of biological and biomedical research, RNA and DNA 2.6. GeneMANIA Database Analysis. GeneMANIA is a flexi- research has undergone revolutionary changes due to micro- ble web to construct protein-protein interaction networks, array technology [21]. In addition, immunotherapy, a revolu- generating hypotheses on gene role, exploring gene list, while tion in cancer treatment, has become a promising strategy prioritizing genes [27]. We visualized the gene network and [22]. Based on thousands of gene expression or copy number predicted the functions of E2F coexpression genes via variations published online, we analyzed the expression pat- GeneMANIA. terns, potential functions, and prognostic value of E2Fs in brain and CNS cancer. Furthermore, we analyzed the interre- 3. Results lationship between E2Fs and immune cell in different cancer microenvironments to identify underlying therapeutic 3.1. Expression Levels of E2Fs of Brain and CNS Tumor. targets of brain and CNS tumor. Oncomine differential expression analysis revealed that the E2F5 expression was remarkably upregulated in brain and 2. Materials and Methods CNS tumor in five datasets (Figure 1). In the French Brain Statistics [28], E2F5 was overex- 2.1. GEPIA Dataset Analysis. GEPIA was used to analyze the pressed in anaplastic oligodendroglioma versus normal RNA sequencing expression data from 9,736 tumors and tissues with a fold change of 2.425 (Table 1). In the Sun Brain 8,587 normal samples from TCGA and the Genotype- Statistics (Table 1) [29], E2F5 was also overexpressed in ana- Tissue Expression (GTEx) projects. GEPIA has many func- plastic astrocytoma with a fold change of 2.545, in oligoden- tional modules, including differential expression, survival, droglioma with a fold change of 2.580, and in glioblastoma and correlation analysis [23]. with a fold change of 2.877. In the Murat Brain Statistics (Table 1) [30], E2F5 was also overexpressed in glioblastoma 2.2. Oncomine Dataset Analysis. The transcription levels of with a fold change of 2.016. The Murat Brain Statistics E2Fs of various tumors and coexpression genes of E2Fs in (Table 1) [30] showed that E2F7 was also increased in glio- brain and CNS cancer were determined through analysis in blastoma (fold change = 4:632) compared to normal samples. Oncomine cancer microarray datasets. In addition, in the Sun Brain Statistics (Table 1) [29], E2F7 was overexpressed in glioblastoma (fold change = 5:823), and 2.3. The Cancer Genome Atlas Data [24] and cBioPortal in the French Brain Statistics (Table 1) [28], the increased Datasets Analyses. cBioPortal currently contains 225 cancer E2F7 expression was found in anaplastic oligodendroglioma studies to explore multidimensional tumor genomics data compared to normal sample (fold change = 2:282). In the BioMed Research International 3

E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8 Cancer Cancer Cancer Cancer Cancer Cancer Cancer Cancer vs. vs. vs. vs. vs. vs. vs. vs. Analysis type by cancer normal normal normal normal normal normal normal normal

Bladder cancer 2 1 1 3 Brain and CNS cancer 1 1 1 51 3 1 3 Breast cancer 4 9 1 2 2 4 4 Cervical cancer 1 1 3 1 2 Colorectal cancer 3 3 2 11 13 1 Esophageal cancer 1 Gastric cancer 1 2 1 Head and Neck cancer 6 1 1 Kidney cancer 1 Leukemia 1 3 2 2 1 2 3 4 Liver cancer 113 2 Lung cancer 2 2 4 2 2 5 Lymphoma 1 1 2 1 1 1 3 Melanoma 1 2 Myeloma Other cancer 1 2 4 3 2 Ovarian cancer 1 2 1 1 Pancreatic cancer 1 11 Prostate cancer 2 Sarcoma 12 1 1 Signifcant unique analyses 1848 18 37 331 27 6530 1 27 4 Total unique analyses 449 403 438 455 457 206 256 376

115510 10

Figure 1: The transcription levels of E2F factors in diﬀerent types of cancers (Oncomine).

Sun Brain Statistics (Table 1) [29], E2F8 was also overex- indicated that mRNA upregulation occupied the overwhelm- pressed in anaplastic astrocytoma (fold change = 4:196), ing majority of alteration types (Figure 4(a)). E2Fs were glioblastoma (fold change = 7:097), and oligodendroglioma altered in 324 (43%) of all the 514 sequenced cases with (fold change = 3:341) compared to normal samples. LGG, which included 1 mutation, 6 cases of amplification, 3 GEPIA differential expression analysis indicated that the cases of deep deletion, 10 cases of mRNA downregulation, E2F1-8 expressions were higher in GBM tissue compared 103 cases of mRNA upregulation, and 4 cases of multiple with normal tissue and that E2F2-8 was higher in LGG alterations. Among the LGG cases with gene alteration of (Figure 2). E2Fs, mRNA upregulation occupied the overwhelming majority of alteration types (Figure 4(b)). Kaplan–Meier 3.2. The Correlations between Different E2Fs in Brain and overall survival curves showed that gene alterations of CNS Cancer. The cBioPortal online tool calculated Pearson E2F1, E2F2, E2F4, and E2F6-8 were remarkably related to correlations. The results showed that the following E2Fs overall survival (OS) (P <0:05) among LGG (Figure 4(d)). showed significantly positive correlations: E2F1 with E2F2, No significant correlation was identified between gene E2F3, E2F7, and E2F8; E2F2 with E2F1, E2F3, E2F7, and alteration of E2Fs and OS in GBM patients (Figure 4(c)). E2F8; E2F3 with E2F1 and E2F2; E2F7 with E2F1, E2F2, and E2F8; and E2F8 with E2F1, E2F2, and E2F7 (Figure 3). 3.4. The Prognostic Value of E2Fs in GBM and LGG Patients. GEPIA and TCGAportal survival analysis both revealed that 3.3. Gene Alteration of E2Fs in Brain and CNS Cancer Tissue decreased E2F1, E2F2, E2F4, and E2F6-8 mRNA levels were from cBioPortal. cBioPortal analyses revealed that E2Fs were remarkably related to overall survival (OS) (P <0:05) among altered in 197 (33·8%) of all the 591 sequenced cases with LGG. No significant correlation was identified between E2F GBM, which included 3 mutation, 8 cases of amplification, mRNA levels and OS in GBM patients (Figure 5). 3 cases of deep deletion, 29 cases of mRNA downregulation, 97 cases of mRNA upregulation, and 5 cases of multiple alter- 3.5. Prognostic Relevance of Immune Cell Infiltration in GBM ations. Statistical results of the gene alteration frequency and LGG. TIMER analysis showed that the survival time of 4 BioMed Research International

Table 1: The signiﬁcant changes of the E2F expression in transcription level between diﬀerent types of brain and CNS cancer and normal brain and CNS tissues (Oncomine database).

Type of breast cancer versus normal breast tissue Fold change P value t-test Source and/or reference E2F1 NA NA NA NA NA E2F2 NA NA NA NA NA E2F3 NA NA NA NA NA E2F4 NA NA NA NA NA Anaplastic oligodendroglioma 2.425 3.64e−10 9.420 French Brain Statistics [28] Anaplastic astrocytoma 2.545 1.45e−7 6.181 Sun Brain Statistics [29] E2F5 Oligodendroglioma 2.580 1.99e−7 5.707 Sun Brain Statistics [29] Glioblastoma 2.877 1.78e−9 7.518 Sun Brain Statistics [29] Glioblastoma 2.016 1.59e−7 10.319 Murat Brain Statistics [30] E2F6 NA NA NA NA NA Glioblastoma 4.632 1.08e−28 17.833 Murat Brain Statistics [30] E2F7 Glioblastoma 5.823 1.31e−21 13.696 Sun Brain Statistics [29] Anaplastic oligodendroglioma 2.282 4.46e−5 4.698 French Brain Statistics [28] Anaplastic astrocytoma 4.196 8.33e−6 4.893 Sun Brain Statistics [29] E2F8 Glioblastoma 7.097 1.25e−9 8.349 Sun Brain Statistics [29] Oligodendroglioma 3.341 9.18e−6 5.003 Sun Brain Statistics [29] NA: not available; TCGA: The Cancer Genome Atlas.

LGG patients with low B cells, macrophage, CD4+ T cells, very weak interrelation with dendritic cell (r =0:135, P = neutrophil, and DCs infiltrations was significantly higher 5:75e − 03)infiltration levels in GBM (r =0:126, P =5:76e − than that of LGG patients with high infiltration. However, 03). The E2F4 expression was remarkably positively related there were no meaningful findings about GBM (Figure 6). to infiltrating levels of B cells (r =0:326, P =2:91e − 13), CD4+ T cells (r =0:327, P =2:65e − 13), macrophages 3.6. Correlations of E2F Expression with Immune Infiltration (r =0:317, P =1:58e − 12), neutrophils (r =0:306, P =8:88e − Levels in GBM and LGG. TIMER analysis revealed that the 12), and dendritic cells (r =0:134 , P =2:14e − 14)inLGG E2F1 expression is remarkably positively related to tumor (Figure 7(d)). The E2F5 expression was remarkably positively purity (r =0:347, P =2:46e − 13) in GBM (Figure 7(a)). related to tumor purity (r =0:34, P =8:99e − 13) and neutro- And the E2F1 expression demonstrated a very weak interre- phils (r =0:172, P =3:99e − 04) in GBM (Figure 7(e)). The lation with CD8+ T cell infiltration levels in LGG (r =0:126, E2F5 expression was remarkably positively related to tumor P =5:76e − 03). Also, the E2F2 expression was significantly purity (r =0:382, P =3:93e − 18), B cells (r =0:19, P =2:80 positively related to cancer purity (r =0:172, P =4:09e − 04) e − 05), CD8+ T cells (r =0:156, P =6:42e − 04), and DCs and remarkably negatively related to macrophages (r =0:182, P =6:74e − 05)butnosignificant correlation with (r = −0:183, P =1:65e − 04), neutrophils (r = −0:305, P = macrophages (r =0:138, P =2:54e − 03) in LGG (Figure 7(e)). 1:88e − 10), and dendritic cells (r = −0:264, P =4:23e − 08) The E2F6 expression was remarkably positively related to but no significant correlation with CD4+ T cells in GBM tumor purity (r =0:316, P =3:66e − 11), CD8+ T cells (Figure 7(b)). E2F2 expression level was remarkably posi- (r =0:187, P =1:25e − 04), and macrophages (r =0:192, P = tively related to infiltrating levels of B cells (r =0:359, P = 8:08e − 05) but no significant correlation with neutrophils 5:53e − 16), CD4+ T cells (r =0:339, P =3:13e − 14), macro- (r =0:145, P =2:90e − 03) in GBM (Figure 7(f)). The phages (r =0:285, P =2:63e − 10), neutrophils (r =0:293, E2F6 expression was remarkably positively related to tumor P =7:29e − 11), and dendritic cells (r =0:371, P =6:15e − purity (r =0:309, P =5:08e − 12), B cells (r =0:23, P =3:92 17) but no significant correlation with tumor purity e − 07), macrophages (r =0:264, P =5:74e − 09), CD8+ T (r =0:119, P =8:88e − 03) in LGG (Figure 7(b)). The cells (r =0:269, P =2:40e − 09), neutrophils (r =0:168, P = E2F3 expression was remarkably positively related to 2:33e − 04), and DCs (r =0:224, P =7:93e − 07) but no tumor purity (r =0:219, P =5:81e − 06) and neutrophils significant correlation with CD4+ T cells in LGG (r =0:293, P =7:29e − 11) in GBM (Figure 7(c)). The (Figure 7(f)). The E2F7 expression was remarkably positively E2F3 expression was remarkably positively related to related to tumor purity (r =0:344, P =3:54e − 05)inGBM tumor purity (r =0:157, P =5:67e − 04) and infiltrating (Figure 7(g)). The E2F7 expression was remarkably positively levels of B cells (r =0:242, P =8:88e − 08), CD8+ T cells related to tumor purity (r =0:151, P =9:03e − 04), B cells (r =0:26, P =7:74e − 09), and DCs (r =0:2, P =1:09e − 05) (r =0:222, P =9:06e − 07), CD8+ T cells (r =0:279, P = but no significant correlation with macrophages (r =0:136, 5: 13e − 10), macrophages (r =0:199, P =1:29e − 05), and P =2:98e − 03) or neutrophils (r =0:15, P =1:04e − 03)in DCs (r =0:175, P =1:22e − 04)inLGG(Figure7(g)).The LGG (Figure 7(c)). The E2F4 expression demonstrated a E2F8 expression was remarkably positively related to tumor BioMed Research International 5

E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8

GBM LGG GBM LGG GBM LGG GBM LGG GBM LGG 42 GBM LGG GBM LGG GBM LGG 80 1 21 70 80 1 70 16 1 9

8 70 18 60 70 60 14 35 7 60 60 12 15 50 50 28 6 50 50 10 12 40 40 5 40 40 21 8 9 30 30 4 30 30 6 14 3 6 20 20 Transcripts per million (TPM) per million Transcripts 20 (TPM) per million Transcripts (TPM) per million Transcripts (TPM) per million Transcripts 20 (TPM) per million Transcripts (TPM) per million Transcripts (TPM) per million Transcripts 4 (TPM) per million Transcripts 2 7 3 10 10 10 10 2 1

0 0 0 0 0 0 0 0 ( n =207) T ( n =162) T ( n =518) T ( n =163) T ( n =518) T ( n =163) T ( n =518) T ( n =162) T ( n =518) T ( n =163) T ( n =518) T ( n =163) T ( n =518) T ( n =163) T ( n =518) T ( n =163) T ( n =518) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N ( n =207) N N ( n =207) (a) E2F1 E2F2 E2F3 E2F4 7 ⁎ 7 ⁎ 6 6 4 6 5 5 5 3 4 4 4 3 3 2 3 2 2 2 1 1 1 1 0 0 0 0 GBM LCG GBM LCG GBM LCG GBM LCG (num(T)=163; (num(T)=518; (num(T)=163; (num(T)=518; (num(T)=163; (num(T)=518; (num(T)=163; (num(T)=518; num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207)

E2F5 E2F6 E2F7 E2F8 ⁎ ⁎ ⁎ 5 3.5 ⁎ 6 ⁎ 5 ⁎ 3.0 5 4 4 2.5 4 3 3 2.0 3 2 1.5 2 2 1.0 1 1 1 0.5 0 0 0 0.0 GBM LCG GBM LCG GBM LCG GBM LCG (num(T)=163; (num(T)=518; (num(T)=163; (num(T)=518; (num(T)=163; (num(T)=518; (num(T)=163; (num(T)=518; num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) num(N)=207) (b)

Figure 2: The expression of E2Fs in GBM and LGG (GEPIA): (a) scatter diagram; (b) box plot.

1 0.67 0.39 0.12 0.09 –0.01 0.48 0.54 E2F1 P =4:48e − 07), CD4+ T cells (r =0:218, P =1:57e − 06), 0.67 1 0.53 0.02 0.11 0.01 0.31 0.56 E2F2 macrophages (r =0:323, P =6:23e − 13), neutrophils 0.39 0.53 1 0.03 0.04 –0.05 0.19 0.26 E2F3 r : P : e − r : P – ( =0228, =500 07), and dendritic cells ( =0288, = 0.12 0.02 0.03 1 0.07 0.02 0.02 0.06 E2F4 : e − 0.09 0.11 0.04 0.07 1 0.5 –0.07 0 E2F5 1 64 10) in LGG (Figure 7(h)). –0.01 0.01 –0.05 0.02 0.5 1 –0.09 –0.03 E2F6 0.48 0.31 0.19 –0.02 –0.07 –0.09 1 0.69 E2F7 3.7. Assessment of the Correlation between E2Fs and Immune 0.54 0.56 0.26 0.06 0 –0.03 0.69 1 E2F8 Marker Expression. In particular, TIMER analysis revealed E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8 that E2F1 was significantly correlated with monocyte Figure 3: The correction between different E2Fs in brain and CNS markers (CD86), TAM markers (CCL2, IL10), and M2 mac- P : cancer (cBioPortal). rophage markers (VSIG4, MS4A4A) in GBM ( <00001; Table 2). E2F2 was significantly correlated with monocyte markers (CD86), TAM markers (CCL2, IL10), and M2 mac- purity (r =0:335, P =2:00e − 12) in GBM. The E2F8 expres- rophage markers (VSIG4) in GBM (P <0:0001; Table 2). sion was remarkably positively related to infiltrating levels of E2F5 was significantly correlated with monocyte markers Bcells(r =0:283, P =2:85e − 10), CD8+ T cells (r =0:228, (CD115) and M1 macrophage markers (IRF5) in GBM 6 BioMed Research International

Case set: all samples (591 patients/604 samples) 25% Altered in 197 (33.8%) of 591 sequenced cases/patients (591 total) E2F1 5% 20% Mutation E2F2 15% Amplifcation 4% Deep deletion

GBM mRNA high 10% E2F3 6% mRNA low Multiple alterations E2F4 4% Alteration frequency Alteration 5% E2F5 3% Mutation + CNA data + E2F6 5% mRNA data + Protein data + E2F7 0.8% E2F8 6% Difuse glioma (a) Case set: all samples (514 patients/samples)

25% Altered in 324 (43%) of 514 sequenced cases/patients (514 total) E2F1 6% 20% Mutation Amplifcation E2F2 4% 15% Deep deletion mRNA high E2F3 5% LGG mRNA low 10% Multiple alterations E2F4

Alteration frequency Alteration 5% 5% E2F5 6% E2F6 8% Mutation + CNA data + E2F7 4% mRNA data + E2F8 7%

Generic alteration Missense mutation (unknown signifcance) mRNA high Difuse glioma Amplication mRNA low Deep deletion No alterations (b) GBM LGG P 100% 100% Overall Logrank Test value: Overall Logrank Test P value: 90% 90% Unaltered group Unaltered group 80% E2F1 0.184 80% e E2F1 3.1915 -3 E2F2 0.911 e 70% 70% E2F2 7.862 -3 E2F3 0.143 E2F3 0.545 60% 60% E2F4 0.783 E2F4 0.0240 E2F5 0.610 50% 50% E2F5 0.394 Overall Overall E2F6 0.729 e 40% 40% E2F6 3.787 -5 E2F7 0.420 E2F7 3.527e-4 30% E2F8 0.191 30% E2F8 4.818e-6 20% 20% 10% 10% 0% 0% 0 0 10 20 30 40 50 60 70 80 90 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 Months overall 100 110 120 Months overall (c) (d)

Figure 4: E2F gene expression, mutation analysis, and survival analysis in brain and CNS cancer (cBioPortal): (a) E2F gene expression and mutation analysis in GBM; (b) E2F gene expression and mutation analysis in LGG; (c) overall survival analysis for gene alteration of E2Fs in GBM patients; (d) overall survival analysis for gene alteration of E2Fs in LGG patients.

(P <0:0001; Table 2). E2F6 was significantly correlated with (P <0:0001; Table 2). Meanwhile, E2F1 was significantly monocyte markers (CD86, CD115), TAM markers (CD68, correlated with monocyte markers (CD86, CD115), TAM IL10), M1 macrophage markers (IRF5), and M2 macrophage markers (CCL2), M1 macrophage markers (INOS), and M2 markers (VSIG4, MS4A4A) in GBM (P <0:0001; Table 2). macrophage markers (VSIG4) in LGG (P <0:0001; E2F7 was significantly correlated with TAM markers (IL10) Table 2). E2F2 was significantly correlated with monocyte in GBM (P <0:0001; Table 2). E2F8 was significantly corre- markers (CD86, CD115), TAM markers (CD68, IL10), M1 lated with M2 macrophage markers (VSIG4) in GBM macrophage markers (IRF5), and M2 macrophage markers BioMed Research International 7

E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8 Overall survival Overall survival Overall survival Overall survival Overall survival Overall survival Overall survival Overall survival 1.0 Logrankg P=0.=0.4141 1.0 LogranLogrankg k P=0.3=0.399 1.0 LogranLogrankg k P==0.90.9 1.0 LogranLogrankg k P=0.34 1.0 LogranLogrankg k P=0.=0.2626 1.0 Logrankg P=0.85 1.0 Logrankg P==0.060.06 1.0 LogranLogrankg k P=0.36 HR(high)=1.2 HR(higHR(high)=1.2h)=1.2 HR(high)=1 HR(higHR(high)=1.2h)=1.2 HR(high)=0.82 HR(high)=0.97 HR(high)=1.4 HR(high)=1.2 0.8 P(HR)=0(HR)=0.4.4 0.8 P((HR)=0.4HR)=0.4 0.8 P((HR)=0.88HR)=0.88 0.8 P((HR)=0.34HR)=0.34 0.8 P((HR)=0.27HR)=0.27 0.8 P((HR)=0.89HR)=0.89 0.8 P((HR)=0.058HR)=0.058 0.8 P(HR)=0(HR)=0.35.35 n(hi(high)=81gh)=81 n(hi(high)=81gh)=81 n((high)=81high)=81 n(hi(high)=81gh)=81 n(hi(high)=79gh)=79 n(hi(high)=81gh)=81 n(hi(high)=80gh)=80 n(hi(high)=81gh)=81 0.6 n((low)=81low)=81 0.6 n(low)=(low)=8181 0.6 n((low)=81low)=81 0.6 n((low)=81low)=81 0.6 n((low)=81low)=81 0.6 n((low)=81low)=81 0.6 n((low)=81low)=81 0.6 n((low)=81low)=81

SO 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 GBM

Percent survival 0.2 80 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 020406080 020406080 020406080 020406080 020406080 020406080 020406080 020406080 Months Months Months Months Months Months Months Months Overall survival Overall survival Overall survival Overall survival Overall survival Overall survival Overall survival Overall survival 1.0 Logrank P=0.0012=0.0012 1.0 Logrank P=4.7=4.7e-06 1.0 Logrankg P=0.22=0.22 1.0 Logrankg P=0.0012=0.0012 1.0 Logrankg P=0.96=0.96 1.0 Logrank P=0.0083 1.0 Logrankg P=4e-08 1.0 Logrank P==2.62.6e-07 HR(high)=1.8HR(high)=1.8 HR(high)=2.3 HR(high)=1.3 HR(high)=0.18HR(high)=0.18 HR(high)=0.99 HR(high)=1.6 HR(high)=2.9 HR(higHR(high)=2.6h)=2.6 0.8 P(HR)=0.0014(HR)=0.0014 0.8 P(HR)=8.6(HR)=8( .6e-06 0.8 P(HR)=0.22(HR)=0.22 0.8 P(HR)=0.0014(HR)=0.0014 0.8 P(HR)=0.96(HR)=0.96 0.8 P(HR)=0.0089(HR)=0.0089 0.8 P(HR)=1(HR)=1.5.5e-07 0.8 P(HR)=6(HR)=6.7.7e-07 n(high)=257(high)=257 n(high)=254(high)(hi(hihi =254 n(high)=257(high)g =257 n(high)=257(high)=257 n(high)=257(high)=257 n(high)=257(high)=257 n(high)(high)=253=253 n(hi(high)=255gh)=255 0.6 n(low)=257(low)=( 257 0.6 n(low)=254(low)=oow)ow) 254 0.6 n(low)=257(low)=(lo(loo 257 0.6 n(low)=257(low)=( 257 0.6 n(low)=257(low)=( 257 0.6 n(low)=257(low)=( 257 0.6 n(low)=(lo((low)=251lo 251 0.6 n(low)=(l((low)=252l 252

SO 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 LGG

Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2 Percent survival 0.2

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 Months Months Months Months Months Months Months Months (a)

E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

0.5 LogrankLogrank P==0.20.2 0.5 LLogrankogrank P==0.350.35 0.5 LoLogrankgrank P==0.690.69 0.5 LoLogrankgrank P==0.730.73 0.5 LoLogrankgrank P=0.1 0.5 LoLogrankgrank P=0.63 0.5 LLogrankogrank P=0.=0.4343 0.5 LoLogrankgrank P=0.7 GBM SO Survival probability Survival probability Survival probability Survival probability Survival probability 0 0 0 0 0 Survival probability 0 Survival probability 0 Survival probability 0 020406080 020406080 020406080 020406080 020406080 020406080 020406080 020406080 Months Months Months Months Months Months Months Months High 78 Low 78 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 SO LGG

Survival probability Logrank P==0.00660 0066 Survival probability P e Survival probability P Survival probability P e Survival probability P Survival probability P Survival probability P e Survival probability P e 0 0 Logrank =9=9.1 1 -06 0 LogranLogrankk =0.39 0 LogranLogrankk =2=2.7 7 -050505 0 LogranLogrankk =0.59 0 LkLogrank =0.00890 00889 0 LogranLogrankk =9=9.1 1 -0606 0 LoLogrankgrank ==4.34.3 -0-077 0 50 100 200 0 50 100 200 0 50 100 200 0 50 100 200 0 50 100 200 0 50 100 200 0 50 100 200 0 50 100 200 Months Months Months Months Months Months Months Months High 255 Low 256 (b)

Figure 5: The prognostic value of mRNA level of E2F factors in GBM and LGG patients: (a) the prognostic value of mRNA level of E2F factors in GBM and LGG patients (GEPIA); (b) the prognostic value of mRNA level of E2F factors in GBM and LGG patients (TCGAportal).

B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell 1.00 Logrank P = 0.105 Logrank P = 0.805 Logrank P = 0.629 Logrank P = 0.755 Logrank P = 0.741 Logrank P = 0.002

0.75

0.50 GBM

0.25

0.00 1.00 Logrank P = 0 Logrank P = 0.01 Logrank P = 0 Logrank P = 0 Logrank P = 0 Logrank P = 0.001

0.75 Cumulative survival

0.50 LGG

0.25

0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 Time to follow-up (months) Level High (top 50%) Low (bottom 50%)

Figure 6: Immune cell infiltration survival curve of GBM and LGG patients (TIMER). Red indicates a high degree of infiltration, and blue indicates a low degree of infiltration. P <0:05 was considered significant, and P <0:0001 was represented by 0.

(CD163, VSIG4, MS4A4A) in LGG (P <0:0001; Table 2). 3.8. Functional Enrichment Analysis of Coexpressed Genes E2F4 was signiﬁcantly correlated with monocyte markers Correlated with E2Fs in Brain and CNS Cancer. Oncomine (CD86), TAM markers (CD68), M1 macrophage markers analyses revealed that E2F1 was positively related to CDK2, (IRF5), and M2 macrophage markers (CD163, VSIG4, RAB3B, FANCI, NUP88, CKS1B, TMEM194A, UBE2S, MS4A4A) in LGG (P <0:0001; Table 2). E2F8 was signiﬁ- GINS1, SMC1A, TOPBP1, and USP1. E2F2 was positively cantly correlated with monocyte markers (CD68), TAM corrected with ASAP3, TCEA3, ID3, RPL11, TCEB3, markers (CCL2, IL10), M1 macrophage markers (IRF5), C1orf128, LYPLA2, GALE, HMGCL, SFRS13A, and PNRC2. and M2 macrophage markers (CD163, MS4A4A) in LGG E2F3 was positively corrected with ARHGAP11A, MYB, (P <0:0001; Table 2). BLM, WEE1, CDC7, EXOSC8, HIST1H4C, HIST1H4I, 8 BioMed Research International

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell 7 cor = 0.847 partial.cor = 0.109 partial.cor = 0.085 partial.cor = 0.024 partial.cor = –0.082 partial.cor = –0.051 partial.cor = –0.032 P = 2.46e-13 P = 2.53e-02 P = 8.29e-02 P = 6.18e-01 P = 9.24e-02 P = 2.96e-01 P = 5.14e-01

6 GBM

partial.cor = 0.079 partial.cor = 0.099 partial.cor = –0.126 partial.cor = –0.09 partial.cor = –0.05 partial.cor = –0.043 partial.cor = 0.004 P = 8.23e-02 P = 3.05e-02 P = 5.76e-03 P = 4.98e-02 P = 2.77e-01 P = 3.53e-01 P = 9.25e-01 75

50 LGG E2F1 expression level (log2 TPM) level E2F1 expression 25

0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 0.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (a)

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell partial.cor = –0.172 partial.cor = –0.011 partial.cor = –0.008 partial.cor = –0.129 partial.cor = –0.183 partial.cor = –0.305 partial.cor = –0.264 P = 4.09e-04 P = 8.19e-01 P = 8.69e-01 P = 8.13e-03 P = 1.65e-04 P = 1.88e-10 P = 4.23e-08 4.4

4.0 GBM 3.6

3.2 cor = 0.119 partil.cor = 0.359 partil.cor = 0.102 partil.cor = 0.339 partil.cor = 0.285 partil.cor = 0.293 partil.cor = 0.371 P = 8.88e-03 P = 5.53e-16 P = 2.54e-02 P = 3.13e-14 P = 2.63e-10 P = 7.29e-11 P = 6.15e-17 20

E2F2 expression level (log2 TPM) level E2F2 expression 10 LGG

0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.000.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (b)

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell 10 cor = 0.219 partil.cor = –0.078 partil.cor = 0.025 partil.cor = 0.082 partil.cor = 0.088 partil.cor = 0.169 partil.cor = 0.053 P = 5.18e-06 P = 1.13e-01 P = 6.15e-01 P = 9.52e-02 P = 7.36e-02 P = 5.08e-04 P = 2.78e-01 9

7 GBM

80 cor = 0.157 partil.cor = 0.242 partil.cor = 0.26 partil.cor = 0.096 partil.cor = 0.136 partil.cor = 0.15 partil.cor = 0.2 P = 5.67e-04 P = 8.88e-08 P = 7.74e-09 P = 3.55e-02 P = 2.98e-03 P = 1.04e-03 P = 1.09e-05 60

40 LGG E2F3 expression level (log2 TPM) level E2F3 expression 20

0 0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.000.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (c)

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell 7.0 cor = 0.041 partil.cor = –0.035 partil.cor = –0.016 partil.cor = 0.082 partil.cor = 0.017 partil.cor = 0.105 partil.cor = 0.135 P = 3.98e-01 P = 4.72e-01 P = 7.37e-01 P = 9.55e-02 P = 7.28e-01 P = 3.14e-02 P = 5.75e-03

6.5

6.0 GBM

5.5

cor = 0.089 partil.cor = 0.326 partil.cor = 0.068 partil.cor = 0.327 partil.cor = 0.317 partil.cor = 0.306 partil.cor = 0.341 P = 5.23e-02 P = 2.91e-13 P = 1.36e-13 P = 2.65e-13 P = 1.58e-12 P = 8.88e-12 P = 2.14e-14 70

50 E2F4 expression level (log2 TPM) level E2F4 expression LGG

0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 0.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (d)

Figure 7: Continued. BioMed Research International 9

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell cor = 0.34 partil.cor = 0.031 partil.cor = 0.049 P e P e P e partil.cor = 0.048 partil.corP = 0.049e partil.cor = 0.172 partil.cor = 0.05 6.0 = 8.99 -13 = 5.23 -01 = 3.49 -01 P = 3.27e-01 = 3.18 -01 P = 3.99e-04 P = 3.09e-01

5.5

5.0 GBM

4.5

4.0 80 cor = 0.382 partil.cor = 0.19 partil.cor = 0.156 partil.cor = 0.112 partil.cor = 0.138 partil.cor = 0.082 partil.cor = 0.182 P = 3.93e-18 P = 2.80e-05 P = 6.42e-04 P = 1.44e-02 P = 2.54e-03 P = 7.56e-02 P = 6.74e-05 60

E2F5 expression level (log2 TPM) level E2F5 expression 40 LGG 20

0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 0.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (e)

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell cor = 0.316 partil.cor = 0.028 partil.cor = 0.017 partil.cor = 0.192 partil.cor = 0.145 partil.cor = 0.116 P e P e partil.corP = 0.187e P e P e P e P e 9 = 3.66 -11 = 5.73 -01 = 1.25 -04 = 7.26 -01 = 8.08 -05 = 2.90 -03 = 1.74 -02

7 GBM

5 25 cor = 0.309 partil.cor = 0.23 partil.cor = 0.269 partil.cor = 0.146 partil.cor = 0.264 partil.cor = 0.168 partil.cor = 0.224 P = 5.08e-12 P = 3.92e-07 P = 2.40e-09 P = 1.42e-03 P = 5.74e-09 P = 2.23e-04 P = 7.93e-07 20

15 E2F6 expression level (log2 TPM) level E2F6 expression LGG 10

5 0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 0.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (f)

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell cor = 0.344 partil.cor = –0.059 partil.cor = –0.004 partil.cor = –0.034 partil.cor = –0.049 partil.cor = –0.108 partil.cor = 0.067 20 P = 3.54e-05 P = 5.15e-01 P = 9.66e-01 P = 6.95e-01 P = 5.78e-01 P = 2.20e-01 P = 4.45e-01

10 GBM

cor = 0.151 partil.cor = 0.222 partil.cor = 0.279 partil.cor = 0.056 partil.cor = 0.199 partil.cor = 0.116 partil.cor = 0.175 30 P = 9.03e-04 P = 9.06e-07 P = 5.13e-10 P = 2.26e-01 P = 1.29e-05 P = 1.17e-02 P = 1.22e-04

20 E2F7 expression level (log2 TPM) level E2F7 expression 10 LGG

0.25 0.50 0.75 1.00 0.0 0.1 0.2 0.3 0.4 0.5 0.0 0.2 0.4 0.6 0.0 0.1 0.2 0.3 0.4 0.5 0.0 0.1 0.2 0.3 0.4 0.0 0.1 0.2 0.2 0.0 0.4 0.8 1.2 Infltration level (g)

Purity B cell CD8+ T cell CD4+ T cell Macrophage Neutrophil Dendritic cell cor = 0.835 partil.cor = –0.011 partil.cor = –0.066 partil.cor = –0.036 partil.cor = 0.008 partil.cor = –0.068 partil.cor = 0.077 P = 2.00e-12 P = 8.18e-01 P = 1.80e-01 P = 4.64e-01 P = 8.66e-01 P = 1.65e-01 P = 1.16e-01 8

6 GBM

cor = 0.107 partil.cor = 0.283 partil.cor = 0.228 partil.cor = 0.218 partil.cor = 0.323 partil.cor = 0.228 partil.cor = 0.288 P = 1.94e-02 P = 2.85e-10 P = 4.48e-07 P = 1.57e-06 P = 6.23e-13 P = 5.00e-07 P = 1.64e-10 5.0

2.5 E2F8 expression level (log2 TPM) level E2F8 expression LGG

0.0

0.25 0.50 0.75 1.00 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 0.00 0.25 0.50 0.75 0.00 0.25 0.50 0.75 1.00 0.0 0.3 0.6 0.9 1.2 0 1 2 Infltration level (h)

Figure 7: Correlation of the E2F expression with immune infiltration level in GBM and LGG: (a) correlation of the E2F1 expression with immune infiltration level in GBM and LGG; (b) correlation of the E2F2 expression with immune infiltration level in GBM and LGG; (c) correlation of the E2F3 expression with immune infiltration level in GBM and LGG; (d) correlation of the E2F4 expression with immune infiltration level in GBM and LGG; (e) correlation of the E2F5 expression with immune infiltration level in GBM and LGG; (f) correlation of the E2F6 expression with immune infiltration level in GBM and LGG; (g) correlation of the E2F7 expression with immune infiltration level in GBM and LGG; (h) correlation of the E2F8 expression with immune infiltration level in GBM and LGG. 10

Table 2: Correlation analysis between E2F and relate genes and markers of monocyte, TAM, and macrophages in TIMER.

GBM Description Gene markers E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8 cor P cor P cor P cor P cor P cor P cor P cor P ∗∗∗ ∗∗∗ ∗∗ ∗ ∗∗∗ ∗ CD86 -0.359 -0.328 -0.242 -0.140 0.084 -0.261 -0.312 -0.193 0.016 -0.224 Monocyte ∗ ∗ ∗∗∗ ∗∗∗ CD115 (CSF1R) -0.239 -0.227 -0.097 0.229 -0.006 0.933 -0.349 -0.352 -0.150 0.062 -0.143 0.076 ∗∗∗ ∗∗∗ ∗∗ ∗ CCL2 -0.383 -0.415 -0.309 -0.111 0.17 -0.203 0.011 -0.228 -0.170 0.035 -0.167 0.038 ∗ ∗ ∗∗ ∗∗∗ TAM CD68 -0.246 -0.210 -0.097 0.228 0.010 0.901 -0.306 -0.380 -0.180 0.025 -0.164 0.042 ∗∗∗ ∗∗∗ ∗∗ ∗ ∗∗∗ ∗∗∗ ∗∗ IL10 -0.392 -0.357 -0.289 -0.141 0.081 -0.259 -0.398 -0.326 -0.302 INOS (NOS2) 0.006 0.936 -0.082 0.308 -0.106 0.19 0.164 0.042 -0.114 0.159 0.041 0.61 0.129 0.11 0.116 0.153 ∗ ∗ ∗∗∗ ∗∗∗ M1 macrophage IRF5 -0.246 -0.262 -0.149 0.065 0.064 0.429 -0.362 -0.395 -0.084 0.296 -0.134 0.098 COX2 (PTGS2) -0.182 0.023 -0.140 0.082 0.064 0.431 0.035 0.661 -0.091 0.259 -0.087 0.279 -0.032 0.691 0.005 0.944 ∗ ∗ CD163 -0.205 0.010 -0.234 -0.126 0.118 -0.070 0.386 -0.192 0.017 -0.243 -0.060 0.458 -0.103 0.203 ∗∗∗ ∗∗∗ ∗∗ ∗ ∗∗∗ ∗∗ ∗∗∗ M2 macrophage VSIG4 -0.389 -0.346 -0.282 -0.156 0.052 -0.249 -0.373 -0.276 -0.332 ∗∗∗ ∗∗ ∗ ∗ ∗∗∗ ∗ ∗ MS4A4A -0.319 -0.295 -0.231 -0.173 0.031 -0.253 -0.313 -0.241 -0.233 LGG Description Gene markers E2F1 E2F2 E2F3 E2F4 E2F5 E2F6 E2F7 E2F8 cor P cor P cor P cor P cor P cor P cor P cor P ∗∗∗ ∗∗∗ ∗∗∗ ∗∗ CD86 -0.203 0.228 0.061 0.166 0.185 0.004 0.910 0.074 0.089 -0.004 0.921 0.157 Monocyte ∗∗∗ ∗∗∗ ∗ ∗∗ CD115 (CSF1R) -0.285 0.209 0.048 0.269 0.114 -0.029 0.510 -0.041 0.343 -0.147 0.055 0.208 ∗∗∗ CCL2 -0.19 0.065 0.137 -0.027 0.532 0.096 0.028 -0.057 0.188 -0.004 0.922 0.01 0.818 0.062 0.153 ∗ ∗∗∗ ∗∗∗ ∗∗∗ TAM CD68 -0.124 0.28 0.076 0.084 0.267 0.057 0.192 0.103 0.018 0.098 0.025 0.224 ∗∗ ∗∗∗ ∗∗ ∗∗ IL10 -0.152 0.183 0.043 0.321 0.168 0.002 0.954 0.035 0.421 0.049 0.257 0.145 iMdRsac International Research BioMed ∗∗∗ INOS (NOS2) 0.197 -0.005 0.905 0.011 0.801 0.012 0.771 -0.059 0.178 0.014 0.738 0.093 0.034 0.073 0.093 ∗ ∗∗∗ ∗∗∗ ∗∗∗ M1 macrophage IRF5 -0.117 0.226 0.008 0.842 0.285 -0.076 0.081 0.038 0.386 0.05 0.250 0.183 COX2 (PTGS2) 0.009 0.830 0.008 0.849 0.077 0.079 -0.038 0.386 -0.109 0.012 -0.072 0.100 0.047 0.286 0.051 0.242 ∗∗∗ ∗ ∗∗∗ ∗∗ ∗ ∗∗∗ CD163 -0.077 0.077 0.224 0.131 0.193 0.023 0.597 0.153 0.142 0.203 ∗∗∗ ∗∗∗ ∗∗∗ M2 macrophage VSIG4 -0.255 0.256 0.098 0.024 0.183 0.041 0.349 0.08 0.067 -0.079 0.072 0.107 0.014 ∗∗ ∗∗∗ ∗ ∗∗∗ ∗∗ ∗∗∗ MS4A4A -0.157 0.28 0.134 0.193 0.104 0.017 0.145 0.07 0.107 0.212 Cor: R value of Spearman’s correlation; TAM: tumor-associated macrophages. ∗P <0:01; ∗∗P <0:001; ∗∗∗P <0:0001. BioMed Research International 11

E2F1 E2F2 E2F3 E2F4

E2F6 E2F7

E2F8

Figure 8: Coexpressed genes of E2Fs in brain and CNS cancer (Oncomine).

HIST1H4B, IGF2BP, and RRP1B. E2F4 was positively cor- of E2Fs and E2F-correlated coexpressed genes. Based on rected with ELMO3, LRRC29, EXOC3L, KIAA0895L, biological processes, cell components, and molecular func- NOL3, HSF4, FBXL8, TRADD, B3GNT9, FHOD1, and tions, GO enrichment analyses predicted the functions of TMEM208. E2F5 was positively corrected with CCDC85B, target host genes. We found that cell cycle phase, mitotic NDN, SMAD2, TFPI2, DNALI1, CDH11, FGF2, SLC39A6, cell cycle, DNA replication, cell cycle checkpoint, and MBD2, SMAD2, and TGFA. E2F6 was positively corrected mRNA transport were remarkably regulated by E2F alter- with POLA1, STOML2, RPA2, RPA1, JMJD6, CCT7, ations in brain and CNS cancer (Figure 10(a)). Chromo- THOC4, SF3B3, CSTF2, CIAO1, and EIF2B1. E2F7 was pos- some, replication, transcription factor complex, and itively corrected with CDKN3, CEP55, KIF4A, SHCBP1, protein serine/threonine kinase activity were also signiﬁ- CCNB1, CENPK, ECT2, DEPDC1B, NEK2, NCAPG, and cantly controlled by these E2F alterations (Figures 10(b) KIF14. E2F8 was positively corrected with KIFC1, CENPM, and 10(c)). The corresponding genes are known to be MYBL2, ERCC6L, AURKB, TK1, MCM10, CDCA3, associated with cell cycle. NCAPH, NUSAP1, and MKI67 (Figure 8). KEGG analysis can deﬁne the pathways related to the Next, we constructed a network of E2Fs and E2F- functions of E2F alterations and coexpressed genes corre- correlated coexpressed genes via GeneMANIA. The results lated with E2Fs. Nine pathways related to the functions of showed that the biological functions of the enriched gene E2F alterations in brain and CNS cancer were found via set, including DNA replication, chromosome segregation, KEGG analysis (Figure 10(d)). Among these pathways, mitosis, regulation of cell division, cell cycle phase, and regu- cfa04110: cell cycle, cfa04350: TGF-beta signaling path- lation of DNA metabolic process, were intimately associated way, ptr05200: pathways in cancer, and cfa04115: p53 sig- with E2F alterations (Figure 9). naling pathway were involved in the tumorigenesis and The GO (gene ontology) and KEGG pathways in the pathogenesis about brain and CNS cancer (Figures 11(a) DAVID database were analyzed to predict the functions and 11(b)). 12 BioMed Research International

TMEM208 TCEA3 R LP 11 DNALI1

PITHD1 LYPLA2 TCEB3 ALYREF

RAB3B SF3B3 NUP88 GALE WEE 1 SMC 1A ASAP3 CSTF2 EIF2B 1 CIAO1 TGFA EXOS 8C RPA 1 TOPBP 1 HMGCL MBD2 CDH11 ELMO3 RPA2 1 BLM NEMP U PS 1 CDCA3 HIST1H4B CDC7 NUSAP 1 DEPDC1B ECT2 CDK2 CKS 1B CCT7 E2F5 TK1 CENPM PNRC2 MYBCCNB1RKB FANCI CDKN3 HIST1H4C FHOD1 E2F6 E2F 1 NE E2F4 UBE 2S CEP55 KIFC1KI67 POLA1 E2F2 E2F7 NCAPH ID3 TRADD NCAPG E2F3 GINS1 KIF14

JMJD6 SMAD2 C ENPK KIF4A TFPI2 RRP1B MCM10 ARHGAP11A E2F 8 SRSF10 HSF4 NOL3 SHCBP1 FGF 2 NDN ERCC6L FBXL8

EXOC3L1 MYB SLC 39A6

B3GNT9 LRRC29 KIAA0895L HIST1H4I CCDC85B

Networks Functions Coexpression G1/S transition of mitotic cell cycle

Physical interactions DNA replication Predicted Chromosome segregation Co-localization Cell cycle phase Pathway Regulation of DNA metabolic process Shared protein domains Mitosis Genetic interactions Regulation of cell division

Figure 9: Protein-protein interaction network of E2F coexpression genes (GeneMANIA). Diﬀerent colors of the network edge indicate the bioinformatics methods applied: coexpression, website prediction, pathway, physical interactions, and colocalization. The diﬀerent colors for the network nodes indicate the biological functions of the set of enrichment genes.

4. Discussion E2F1 blocked the proliferation repression caused by miR- 342-3p or miR-377 in glioma cells [12], and E2F1 overex- The function of E2F activators in tumorigenesis and their pression conferred resistance to cisplatin in glioma cells prognostic relevance has been partially demonstrated in sev- [13]. MicroRNA-138 inhibited the development of GBM by eral cancers [31–33]; however, further bioinformatics analy- targeting E2F1 [34]. PPARα inhibited growth of glioma cells sis and analysis of immune infiltrates in brain and CNS through the E2F1/miR-19a feedback loop [35]. miRNA-320 cancers have not been performed. This is the first study that and miRNA-329 inhibited glioma proliferation by targeting explored the mRNA expressions of different E2F factors in E2F1 [36, 37]. The ECT2/PSMD14/PTTG1 axis promoted brain and CNS cancer and investigated their prognostic glioma proliferation by stabilizing E2F1 [38]. In this study, relevance and correlation with various tumor-infiltrating analysis of Oncomine dataset and GEPIA dataset revealed immune cells. Our findings may help improve treatment of that elevated expression of E2F1 in human GBM. Analysis patients with brain and CNS cancers. of GEPIA and TCGAportal datasets revealed the prognostic E2F1 has been studied extensively in tumors of the brain value of E2F1 in patients with GBM and LGG. High E2F1 and CNS [11–13, 34–38]. E2F1/DP1 complex was reported to expression and gene alteration of E2F1 in LGG was associ- inhibit the mismatch repair proteins MSH2, MSH6, and ated with poor OS; however, the E2F1 expression and gene EXO1, as well as the homologous recombinant protein alteration of E2F1 in GBM showed no significant correlation RAD51, leading to cell apoptosis [11]. Overexpression of with OS. In TIMER datasets, the E2F1 expression in GBM BioMed Research International 13

Bioligical process Cellular component Cell cycle phase Chromosome Mitotic cell cycle Condensed chromosome Chormosome segregation Spindle DNA replication Nucleoplasm DNA metabolic process Non-membrane-bounded organelle DNA repair Kinetochore Cell cycle checkpoint Cytoskeleton Second-messenger-mediated signaling Replication fork mRNA transport Transcription factor complex

01020304050 0 5 10 15 20 25 (a) (b) Molecule function KEGG pathway Cell cycle Nucleoside binding Oocyte meiosis ATP binding Mismatch repair Pathways in cancer Nucleotide binding DNA replication Progesterone-mediated oocyte maturation Microtubule motor activity p53 signaling pathway Homologous recombination Purine ribonucleotide binding Pancreatic cancer Identical protein binding Small cell lung cancer Nucleotide excision repair DNA binding TGF-beta signaling pathway Pyrimidine metabolism Protein serin/threonine kinase activity Melanoma Non-small cell lung cancer Protein kinase activity Prostate cancer 012 3456 0 2 4 6 8 101214161820 (c) (d)

Figure 10: Significantly enriched GO annotations and KEGG pathways of E2Fs in brain and CNS cancer (DAVID). The functions of E2Fs and E2F coexpression genes were predicted by the analysis of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by DAVID (Database for Annotation, Visualization, and Integrated Discovery) tools (https://david.ncifcrf.gov/summary.jsp): (a) cellular components; (b) biological processes; (c) molecular functions; (d) KEGG pathway analysis. showed a positive association with tumor purity while the not with tumor purity. Specifically, E2F2 was significantly E2F1 expression in LGG demonstrated a very weak interrela- correlated with monocyte markers (CD86), TAM markers tion with CD8+ T cells infiltration level. Specifically, E2F1 (CCL2, IL10), and M2 macrophage markers (VSIG4) in was significantly correlated with monocyte markers GBM. E2F2 was significantly correlated with monocyte (CD86), TAM markers (CCL2, IL10), and M2 macrophage markers (CD86, CD115), TAM markers (CD68, IL10), M1 markers (VSIG4, MS4A4A) in GBM. E2F1 was significantly macrophage markers (IRF5), and M2 macrophage markers correlated with monocyte markers (CD86, CD115), TAM (CD163, VSIG4, MS4A4A) in LGG. This suggests that markers (CCL2), M1 macrophage markers (INOS), and M2 E2F2 plays a role in regulating monocyte polarization in macrophage markers (VSIG4) in LGG. This suggests that GBM and LGG. E2F1 plays a role in regulating monocyte polarization in E2F3 overexpression is a cancer suppressor event in GBM and LGG. many types of tumors, including brain and CNS cancers Downregulation of E2F2 was shown to inhibit glioma cell [32, 40, 41]. miR128-1 inhibited GBM growth by targeting growth in vitro and in vivo by inducing cell cycle arrest in E2F3 [40]. The primary factor of miR-195-mediated cell G0/G1 [14]. Overexpression of E2F2 was found to promote arrest was E2F3 [41]. Increased expression in E2F3a played invasive growth of NSCLC cells [15]. miR-125b regulated a significant role in the development of glioma [2]. Interest- glioblastoma progress via E2F2 [39]. In our study, we ingly, SNHG5 promoted the development of glioma by tar- observed overexpression of E2F2 in GBM and LGG tissues. geting E2F3 [42]. In our study, the E2F3 expression was However, while high E2F2 expression and gene alteration upregulated in GBM and LGG. The E2F3 expression and of E2F2 in LGG was related to low overall survival (consistent gene alteration of E2F3 in LGG and GBM showed no corre- with its role as an oncogene), the E2F2 expression and gene lation with survival outcomes. However, the E2F3 expression alteration of E2F1 showed no significant correlation with was positively related to tumor purity and neutrophil infiltra- OS in the context of GBM. Furthermore, the E2F2 expression tion remarkably in GBM. About LGG, the E2F3 expression was positively related to cancer purity and negatively related showed a positive correlation with tumor purity and infiltrat- to macrophages, neutrophils, and DCs of GBM; however, the ing levels of B cells, CD8+ T cells, and dendritic cells but not E2F2 expression in GBM showed no significant correlation with macrophages and neutrophils. with CD4+ T cells. The E2F2 expression in LGG showed a TFs play a vital role in inhibiting proliferation-related positive correlation with infiltrating levels of B cells, CD4+ genes. As a member of the TFs E2F family, E2F4 is rich in T cells, macrophages, neutrophils, and dendritic cells but nonproliferating and differentiated cells [43]. Decreased 14 BioMed Research International

Cell cycle

Growth factor Growth factor � DNa damage checkpoint withdrawal TGF ARF Smc1 Smc3 p107 Stag1,2 E2F4,5 p300 Rad21 Cohesin GSK3� DP-1,2 DNA-PK ATMATR ee Mdm2 Mps1 SCF Esp1 Separin Skp2 +p +p c-Myc e e +p Mad1 Rb p53 Apoptosis PTTG Securin MAPK Miz1 +p signaling e +u +u e +p +u pathway ee Mad2 p16 p15 p18 p18 p27,57 p21 Chkl, 2 BubR1 APC/C Ink4a Ink4b Ink4c Ink4d Kipl, 2 Cip1 GADD45 143-3� Bub1 Bub3 Cdc20 +p PCNA 14-3-3 +p +p Ubiquitin Cdc25A mediated Cdc25B,C proteolysis +p +p -p R-point CycD -p CycE -p CycA -p CycH -p CycA CycB +p (Start) CDK4,6 +u CDK2 CDK2 +p CDK7 +p CDK1 CDK1 Plk1 +p +p +p +p+p +p+u +p +p +p +p +p SCF APC/C Ab1 Cdc6 Cdc45 Rb Wee Myt1 +p Skp2 p107,130 Rb Cdh1 HDAC ORC MCM -p E2F4,5 E2F1,2,3 +p +p Cdc14 DP-1,2 DP-1,2 Cdc7 Bub2 MEN Dbf4 ORC (origin MCM (mini-chromosome recognition complex) maintenance complex) S-phase proteins, DNA CycE DNA biosynthesis Orc1 Orc2 Mcm2 Mcm3 DNA Orc3 Orc4 Mcm4 Mcm5 Orc5 Orc6 Mcm6 Mcm7

G1 SG2M 04110 11/15/18 (c) Kanehisa laboaratoris (a)

TGF-Beta signaling pathway

NEO1 HJV BMP2/4/6 +p BMPRI Smad1/58 Hepcidin Iron metabolism Activin B RMPRIL/ActRII DNA Smad4 RGMa/b +p BMP2/4 BMPRI RMPRIL/ActRII Osteoblast diferentiation, Id Chordin BAMBI Smad1/58 neurogenesis, Noggin DNA DNA ventral mesodem specifcation +p Smad4 DAN BMPRI +p BMP BMPRII GREM Ras/MAPK Growth factor ERK IFN� Smad6/7 Angiogenesis TNF� Transcription factors, extracellular matrix Rbx1 +p co-activators neogenesis Smurf1/2 Cul1 and co-repressors immunosuppression, THSD4 FBN1 apoptosis induction BAMB1 Skp1 LTBP1 Apoptosis THBS1 +p p107 TGF� RI Smad2/3 E2F4/5 c-Myc � Decorin TGF TGF� RII DP1 DNA SARA Smad4 FMOD +u p300 +u p15 G1 arrest Ubiquitin mediated SP1 DNA proteolysis TGIF Cell cycle TAK1, MEKK1 DAXX/JNK MAPK signaling pathway

RhoA ROCK1 -p PP2A p70S6K Lefy BAMBI +p Gonadal growth, ActivinRI Smad2/3 embryo diferentiation, Activin ActivinRII DNA placent formation, etc FST Smad6/7 Smad4 +p Pitx2 Lef-right axis determination NodalRI Smad2/3 mesodem and endodem induction, etc Nodal NodalRII DNA Smad4 04350 5/13/19 (c) Kanehisa laboaratoris (b)

Figure 11: (a) Cell cycle and (b) TGF-beta-signaling pathway regulated by the E2F alteration in brain and CNS cancer.

levels of E2F4 in human GBM cells induced G2/M cell cycle positively related to CD4+ T cells, neutrophil, B cells, macro- arrest with a concomitant 2-fold decrease with S phase cell phage, and DCs. Specifically, E2F4 was significantly corre- [16]. In our study, the expression of E2F4 in GBM and lated with monocyte markers (CD86), TAM markers LGG was higher than that in normal tissue. High E2F4 (CD68), M1 macrophage markers (IRF5), and M2 macro- expression in LGG was related to poor overall survival, while phage markers (CD163, VSIG4, MS4A4A) in LGG. This sug- the E2F4 expression and gene alteration of E2F4 of GBM gests that E2F4 plays a role in regulating monocyte showed no correlation with OS. In addition, the E2F4 expres- polarization in LGG. sion in GBM demonstrated a very weak interrelation with E2F5 was highly expressed in all kinds of tumors, such as dendritic cell infiltration. E2F4 expression level in LGG was prostate tumor [44] and glioblastoma [45]. In addition, BioMed Research International 15 silencing of E2F5 inhibited the proliferation of GBM cells and 5. Conclusions induced cell cycle arrest. More importantly, reintroduction of E2F5 into GBM cells reversed the tumor-suppressive func- In this study, we systematically analyzed the expressions of tion of miR-1179 [17]. miRNA-129-3p suppressed growth E2Fs in brain and CNS cancer tissues, assessed their prognos- of glioblastoma via targeting E2F5 [45]. Moreover, Let-7c tic value, and investigated their correlation with tumor- fi fi inhibited glioma development by targeting E2F5 [46]. In in ltrating immune cells. Our ndings characterize the our study, the expression of E2F5 in GBM and LGG was heterogeneity and complexity of the molecular biology and fi higher than that in normal tissue. The E2F5 expression and the immune in ltrates in brain and CNS cancers. Bioinfor- gene alteration of E2F5 in LGG and GBM showed no corre- matics analysis indicated that the increased expressions of – lation with OS. However, the E2F5 expression of GBM was E2F1, 2, and 5 8 in GBM tissues and those of E2F5 and 6 positively related to cancer purity and neutrophil infiltration. in LGG tissues may play a vital role in oncogenesis. High – The E2F5 expression of LGG showed a positive correlation E2F1 8 expressions may serve as molecular markers to iden- with tumor purity and infiltrating levels of B cells, CD8+ T tify high-risk subgroups of patients with GBM. Similarly, – cells, and dendritic cells but not with infiltrating level of mac- high E2F2 8 expressions may help identify high-risk patients fi – – rophages. Specifically, E2F5 was significantly correlated with in LGG. Our ndings suggest that E2F1 8 and E2F2 8 are monocyte markers (CD115) and M1 macrophage markers potential prognostic biomarkers for GBM and LGG, respec- – (IRF5) in GBM. This suggests that E2F5 plays a role in regu- tively. However, increased expressions of E2F3 6 in GBM fi lating monocyte polarization in GBM. correlated with poor prognosis and increased in ltration of The combination of E2F6 and MATN1-AS1 (which CD8+ T cells, macrophages, neutrophils, and DCs. Increased negatively targets RELA) was shown to inhibit the MAPK expressions of E2F1-8 in LGG correlated with poor prognosis fi signaling pathway, thus inhibiting the development of and increased in ltration of B cells, CD8+ T cells, CD4+ T – GBM [18]. In our study, the expression of E2F6 in GBM cells, macrophages, neutrophils, and DCs. Therefore, E2F3 – and LGG was higher than that in normal tissue. Increased 6 and E2F1 8 are potential therapeutic targets in patients fi E2F6 expression and gene alteration of E2F6 in LGG was with immune cell in ltration of GBM and LGG, respectively. related to poor OS, while the E2F6 expression of GBM showed no correlation with OS. In addition, the E2F6 Abbreviations expression of GBM was positively related to cancer purity, CD8+ T cells, and macrophages but not with neutrophils. E2Fs: E2F transcription factors The E2F6 expression in LGG showed a significant positive CNS: Central nervous system correlation with tumor purity and infiltrating levels of B GBM: Glioblastoma multiforme cells, CD8+ T cells, macrophages, neutrophils, and den- LGG: Low grade glioma dritic cells but not with CD4+ T cells. Specifically, E2F6 PPI: Protein-protein interaction was significantly correlated with monocyte markers OS: Overall survival (CD86, CD115), TAM markers (CD68, IL10), M1 macro- TAM: Tumor-associated macrophages phage markers (IRF5), and M2 macrophage markers GO: Gene ontology (VSIG4, MS4A4A) in GBM. This suggests that E2F6 plays KEGG: Kyoto Encyclopedia of Genes and Genomes. a role in regulating monocyte polarization in GBM. E2F7 and E2F8 function as transcriptional repressors Data Availability [47]. E2F7 could induce autophagy of glioma [19]. HOXD- AS1 regulated glioma progress via E2F8 [20]. In our study, The data used to support the findings of this study are the expressions of E2F7 and E2F8 in GBM and LGG were included within the article. higher than those in normal tissues. High E2F7 and E2F8 expressions and gene alteration of E2F7 and E2F8 in LGG Conflicts of Interest were associated with poor OS. Moreover, the E2F7 and E2F8 expressions were positively related to tumor purity in No conflict of interest. GBM remarkably. E2F7 expression level in LGG showed a positive correlation with tumor purity and infiltrating levels Acknowledgments of B cells, CD8+ T cells, macrophages, and dendritic cells. 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