Elevated expression of the MYB proto-oncogene like 2 (MYBL2)-encoding gene as a prognostic and predictive biomarker in human cancers

1.   Introduction

MYBL2 (alias B-myb), a highly conserved member of the Myb transcription factor family, is ubiquitously expressed in proliferating cells, particularly in embryonic stem cells and adult haematopoietic precursors ^[1,2,3]. Previous studies have shown that the DREAM complex (DP, RB-like, E2F, and MuvB), which is critical for coordinating cell cycle-dependent gene expression, represses most cell cycle genes expression during quiescence ^[4]. Recently, it has been shown that the MuvB core dissociates from P107/P130, sequentially recruits MYBL2 and FoxM1 to coordinate the expression of the late cell cycle G2/M genes. The expression of MYBL2 involved in cell cycle regulation and performed essential functions in proliferating cells, is hardly detectable at G0 phase and induced at the G1/S transition of the cell cycle ^[5,6]. Taking those considerations together, these data indicate that MYBL2 is involved in cell proliferation and carcinogenesis.

So far, MYBL2 is frequently found to be overexpressed and associated with poor patient outcome in breast cancer, colorectal cancer, bladder carcinoma, hepatocellular carcinoma, neuroblastoma and acute myeloid leukemia ^{[7,8,9,10,11,12]}. In view of the fact that there is an association between MYBL2 expression and the clinicopathological features of human cancers, most studies reported so far are limited in their sample size, tissue type and discrete outcomes. Furthermore, which additional cancer entities are also affected by MYBL2 deregulation and which patients could specifically benefit from using MYBL2 as a biomarker or therapeutic target? In the present study, we have investigated whether elevated expression of MYBL2 could be used as a prognostic and predictive factor in a variety of human cancers. To this end, we used publicly available clinical information to generate a comprehensive molecular profile of MYBL2 in human cancers at the genomic and transcriptomic levels. Our findings indicate that elevated MYBL2 expression represents a prognostic biomarker for a large number of cancers. What's more, patients with both P53 mutation and elevated MYBL2 expression showed a worse survival in PRAD and BRCA.

2.   Material and methods

2.1.   Catalogue of somatic mutations in cancer (COSMIC) database analysis

The COSMIC database is an online resource for exploring the impact of somatic mutations ^[13], gene fusions, genomic rearrangements, and copy number variations in human cancers. Based on this authoritative database, we performed a summary of alterations affecting MYBL2. All data were extracted on November 19, 2021 (COSMIC v95 version).

2.2.   Oncomine database analysis

Oncomine is a cancer transcriptomic database and online discovery platform with genome-wide expression analyses of 715 datasets including 86,733 samples (Oncomine v4.5 version) ^[14]. Gene expression analysis for a single gene or a set of genes can be conducted across various types of cancer and include comparisons relative to normal tissues, other cancer subtypes and various clinicopathological features.

2.3.   Xena database analysis

The gene expression of MYBL2 in human cancer was downloaded from TOIL (scalable and efficient workflow engine) in Xena public data hubs (https://xena.ucsc.edu/public-hubs/) ^[15]. We used the RSEM tpm normalized expression to perform further analysis. The clinical traits and survival data was also downloaded.

2.4.   cBio cancer genomics portal (cBioPortal) analysis

The cBioPortal is an open-access resource for interactive exploration of multidimensional cancer genomics data sets. Among these datasets ^[16,17], we used TCGA provisional data about prostate, breast and lung carcinoma, including clinical traits and TP53 signalling pathway alteration. We also downloaded the genes correlated with MYBL2 in prostate, breast and lung cancer for further analysis. The annotation of the TCGA cancer type is summarized in Table S1.

2.5.   PrognoScan database analysis

PrognoScan is a database for meta-analysis of the prognostic value of genes ^[18]. We used the database to assess the biological relationship between MYBL2 gene expression and prognosis. The meta-analysis was also downloaded.

2.6.   Kaplan-Meier plotter analysis

The Kaplan-Meier plotter is a database that can be used to assess the effect of 54,675 genes on survival using 18,647 cancer samples (breast, ovarian, lung and gastric cancer) ^[19]. Data were obtained before November 19, 2021. Patients with higher and lower expression divided by median of MYBL2 (Probe ID: 201710_at, Jetset best probe) were analyzed the 5-years survival using the log-rank test. The hazard ratio with 95% confidence intervals and log-rank p values were noted. In this database, there is only 201710_at linked to MYBL2. The database has not affy U95 platform associated probes. Indeed, there are a lot of RNA-seq data for AML/COAD, but we have not found RNA-seq data for both normal samples and tumor samples.

2.7.   GO and KEGG analysis

GOstats is a bioconductor package written in R ^[20], that allows users to test GO terms for over or under-representation using either a classical hypergeometric test or a conditional hypergeometric that uses the relationships among GO terms to decorrelate the results. We overlapped the genes correlated with MYBL2 among prostate, breast and lung cancer from cBioportal, and the overlapped genes conducted GO and KEGG analysis used the GOstats packages. The cutoff p-value below 0.05 was selected.

2.8.   Candidate transcription factors analysis

We first get 154 genes that are co-expressed with MYBL2. Then we obtain the transcription factor list from HumanTFDB ^[21], and take the intersection with the co-expressed genes. After that, we get the position frequency matrix of the relevant transcription factor through the R package Motifdb ^[22]. Lastly, we use the matchPWM function from the R Biostrings package ^[23] to get the relevant binding site on the promoter region of MYBL2. The more detail method can refer to gene regulation workflow (https://www.bioconductor.org/help/workflows/generegulation/).

2.9.   Statistical analysis

For Oncomine analysis, we used the parameter of FC > 1.5, pvalue < 0.01 and gene rank (all) for two class differential expression analyses (e.g., cancer tissues versus normal tissues). For the RNA-seq analysis in TCGA and GTEx samples, the Mann-Whitney U test was used for two class differential expression analyses. With the Kaplan-Meier plotter and TCGA survival data, the log-rank test and uni-variable COX analysis was used to analyze the data. With the PrognoScan analysis, the data was filtered by pvalue below 0.05. For the correlated genes with MYBL2, the data was filter by absolute Spearman correlation upper 0.5 and the pvalue below 0.05. In the GO and KEGG analysis, the pvalue below 0.05 was considered significant. For the relationship between MYBL2 and TP53 signialling pathway, the permutation test and Mann-Whitney U test was used.

3.   Result

3.1.   MYBL2 DNA mutations

The MYBL2 gene in cancers of patients was assessed for mutations using the COSMIC database (COSMIC v95 version) ^[13], a comprehensive resource for exploring somatic mutations in human cancer. Before November 19, 2021, the MYBL2 gene was tested in 36,635 patient specimens in 38 different types of cancer. There were no mutations in 18 of these cancer types and 263 point mutations were found (overall frequency = 0.72%) in the 20 remaining types of cancer; 1040 copy number variations (CNV) were found (overall frequency = 2.84%) in 22 of the cancer types (Table 1). Out of the 263 point mutations in the MYBL2 gene, 8 were nonsense and 178 were missense; 76 mutations were coding silent (synonymous mutation) and the other 4 were frame shift (Table 1). The frequency of point mutations was not high in most of the cancer types, with the highest mutation frequency being 3.8%, found in cancer of small intestine (Table S2). As shown in that table, the highest CNVs were found in upper pancreas cancer, breast cancer and large intestine cancer, account for 1.5% of all samples, CNVs of other cancer account were much little. Taken together, the results indicate that there were no major alterations in the sequence or copy number of the MYBL2 gene that could account for the development of the malignancies.

3.2.   Elevated MYBL2 expression in human cancers

Using Oncomine analysis, 8 we investigated whether expression of the MYBL2 gene was altered in human cancers. It was found that MYBL2 was elevated in 91 studies and down-regulated in 10 studies (Figure 1A; fold change > 2, p < 0.01). Furthermore, 5 of the down-regulated studies clustered in leukemia and pancreatic cancer. The most common cancer types showing elevated MYBL2 expression in these studies were cancers of the lung, colorectal, breast, sarcoma and brain cancer. For further validate whether MYBL2 expression was elevated in other cancer, we used the TCGA tumor and GTEx normal sample to perform the differential expression analysis between normal and tumor tissue using Mann-Whitney U test (Figure 1B, C and Table S3) ^[15]. The study involved 15408 samples, with logFC range from 0.76 to 9.6, and the pvalue range from 1.80E-02 to 1.74E-158. Together, the results indicate that elevated MYBL2 expression is a diagnosis marker between normal and tumor tissue for most of human cancers.

3.3.   Elevated MYBL2 expression effect on clinical outcome

Next, we wondered whether elevated MYBL2 expression had an effect on clinical outcome. Using the Prognoscan database ^[18], we noticed that elevated MYBL2 expression was associated with higher hazard ratio in 35 studies, which indicated patients with higher MYBL2 expression had poor prognosis (Figure 2A, B and Table S4). While in two studies elevated MYBL2 expression was associated with lower hazard ratio, considering the duplicated probe (216421_at, 201710_at) and the cox-pvalue, the probe (216421_at) made these studies less definitive. Then, we focused on the relationship between elevated MYBL2 expression and overall survival in 5-years using a Kaplan-Meier plotter ^[19]. Elevated MYBL2 expression significantly correlated with lower 5-years overall survival of breast, lung, gastric and ovarian cancer (Figure 2C-F and Table S5). We also validated the relationship between elevated MYBL2 expression and clinical outcome using 5-years OS (overall survival), 5-years DSS (disease-specific survival) and 5-years PFI (progressive-free interval) of TCGA data ^[15]. We found elevated MYBL2 expression significantly correlated with lower 5-years OS of ACC, KIRC, KIRP, LGG, MESO, LIHC, BRCA, SKCM, SARC, PAAD, THYM, KICH (Figure 3 and Table S6). Furthermore, elevated MYBL2 expression was significantly correlated with lower 5-years DSS of ACC, KIRC, KIRP, LGG, MESO, BRCA, LIHC, SKCM, KICH, PAAD, LUAD, UVM and SARC (Figure 4 and Table S7). Lastly, we found elevated MYBL2 expression was significantly correlated with lower 5-years PFI of ACC, KIRC, KIRP, PRAD, MESO, LGG, LIHC, UVM, KICH, THCA, PAAD, BRCA, SARC, PCPG and TGCT (Figure 5 and Table S8). Noticeably, while the log-rank p value of some cancer types was no significant, elevated MYBL2 expression may still have effect on 5-years OS, 5-years DSS, 5-years PFI (Figures 3−5 and Tables S6−S8). Together, the results indicate that elevated MYBL2 expression is prognostic of poor clinical outcome for a large variety of human cancers. In Figures 1−5, high MYBL2 expression means that the gene expression of MYBL2 is high, which is significantly correlated with poor patient outcome in numerous cancer entities. Low MYBL2 expression denotes that the gene expression amount of MYBL2 is low. Generally, MYBL2 expression is higher than other normal tissues in almost all cancers. Therefore, MYBL2 may become a potential diagnostic and prognostic marker in the cancer.

3.4.   Genes co-expressed with MYBL2 and potential MYBL2 regulatory mechanisms

According to the newest incidence of cancer ^[24], we selected breast, prostate and lung cancer to perform further investigating. To identify the potential function of elevated MYBL2 expression, we searched for genes co-expressed with MYBL2 in breast, prostate and lung cancer (TCGA provisional) from cBioportal database ^[16,17]. We identified 441,380 and 164 genes with a co-expression score ≥ 0.5 or ≤ −0.5 and got 154 gene common in the three data-sets (Figure 6A). Using GOstats R package to perform GO and KEGG analysis, the GO terms primarily related to cell process and cell cycle (Table 2) ^[20] and the KEGG terms primarily related to the cell cycle, p53 signaling pathway and some types of cancer pathway (Table 3). Furthermore, we investigated the potential relationship between the elevated MYBL2 expression and p53 signaling pathway. The mutation and copy number variant data of TP53 signaling pathway were downloaded from cBioportal database. We plotted the oncoprint according the rank of MYBL2 expression and observed that most of the TP53 mutant patients are accompanied by elevated MYBL2 expression (Figure 6E-G). There are 29.22% of the PRAD samples in MYBL2 high expression group had TP53 signaling pathway altered, compared with 18.29% of the PRAD samples in low group (Figure 6E). The similar results of BRCA and LUAD were 77.45% in high group and 28.6% in low group, 79.82% in high group and 56.52% in low group (Figure 6F-G and Table S9). Simultaneously, the box-plot showed that the TP53 altered group had higher MYBL2 expression (Figure 6B-D). We concluded that TP53 mutation or TP53 signaling altered may lead to elevated expression of MYBL2. Lastly, we divided the samples into four groups based on the presence or absence of TP53 mutations and the median expression of MYBL2. We found low and no-altered group had the better prognosis compared with high and altered group in PRAD and BRCA (Figure 7).

To explore the upstream regulator of MYBL2, we selected the correlated TF (transcription factors) from the 154 co-expressed genes, and used their motif sequence to match the 1500bp sequence of MYBL2 at the upstream of TSS (transcription start site). We observed that E2F1, E2F2, E2F7 and ZNF659 could interact with MYBL2 promotor directly or indirectly, indicating the four TFs may be the upstream regulator of MYBL2 (Figure 8 and Table S10). In the cancer cells from the public database Cristrome ^[25], we find the chip-seq data of E2F1 and E2F7. Then, we show the actual motif occupancy of E2F1 and E2F7 on the promoter region of MYBL2. The result is summarized in Figure S1. As observed from Figure S1, it can be found that E2F1 and E2F7 have binding sites in the MYBL2 promoter region, which further verified our analysis that E2F1 and E2F7 can regulate MYBL2.

3.5.   Elevated MYBL2 expression as a potential predictive biomarker in prostate, breast and lung cancer

To investigate whether elevated MYBL2 expression in prostate, lung and breast cancer could be used to predict the prognosis, we used Gleason score of prostate cancer, tipple negative status of breast cancer, and adenocarcinoma or not of lung cancer. The result showed that unregulated MYBL2 expression may be used as a predictive biomarker for poor clinical trait of prostate and breast cancer, and for distinguished the adenocarcinoma and squamous carcinoma of lung (Figure 9A-C). Furthermore, we performed multivariate analysis. The analysis result is summarized in Figure S2A, C. From those figures, we found MYBL2 can be a significant prognostic marker in BRCA (HR = 1.2, p < 0.01) and PRAD (HR = 1.2, p < 0.05). We also compare the prognostic value of MYBL2 expression with Gleason score in prostate cancer and hormonal receptor expression in breast cancer, which is summarized in Figure S2B, D. From those figures, we can see that in BRCA, the TNBC group and the Her2 group with high MYBL2 expression have a worse prognosis; while in PRAD, the high Gleason group with high MYBL2 expression have a worse prognosis.

4.   Discussion

While elevated levels of MYBL2 have been reported in many cancer ^{[26,27,28,29]}, the present study, based on TCGA and Oncomine analysis, shows that elevated MYBL2 expression can be found in almost 29 cancer types. The study involved 15408 samples, with logFC range from 0.76 to 9.6 and the pvalue range from 1.80E-02 to 1.74E-158. While the pvalue was no significant in Thymoma and Pheochromocytoma, the relatively low number of patients in normal tissue made this finding less definitive. Based on prognoscan and Kaplan-Meier plotter database ^[18,19], we found the unregulated MYBL2 expression is correlated poor prognosis (HR > 1) in bladder, blood, brain, breast, lung, prostate, skin, ovarian, gastric and soft tissue cancer. We further used TCGA data to analyze the OS, DSS and PFI in 33 cancer types and observed the same result. Taken together, the data showed that the unregulated MYBL2 expression not only could be used as a prognostic biomarker of poor survival outcome in breast cancer, colorectal cancer, bladder carcinoma, hepatocellular carcinoma, neuroblastoma and acute myeloid leukemia ^[30], but also in adrenocortical, kidney, lung, skin, pancreatic, thyroid, brain, mesothelioma, uveal melanoma, prostate, testicular, sarcoma, uveal melanoma and paraganglioma.

Based on the newest incidence of cancer ^[24], we selected breast, prostate and lung cancer to further investigate the mechanism (Figure S3). We used the 154 genes, which were co-expressed with MYBL2, to perform GO and KEGG analysis using the bioconductor package GOstats ^[20]. We found the major KEGG terms were p53 signaling, cell cycle and other cancer pathway, and the major GO terms were cell process and cell cycle. The GO and KEGG analysis indicated the elevated expression of MYBL2 may associate with p53 signaling and cell cycle related genes. This is in accordance with the results from Fischer et al. showing that the p53-p21-DREAM-CDE/CHR pathway represses MYBL2 expression ^[31]. We further plotted the oncoprint according the rank of MYBL2 expression and observed that most of the TP53 mutant patients are accompanied by elevated MYBL2 expression. Lastly, we divided the samples into four groups based on the presence or absence of TP53 mutations and the median expression of MYBL2. We found in low and no-altered group had the best prognosis compared with the worst prognosis of high and altered group in PRAD and BRCA. These data further elucidated the MYBL2 related mechanism and identified patients could specifically benefit from using MYBL2 as a biomarker.

In order to find the potential upstream of MYBL2, we selected the 6 TF co-expressed with MYBL2 from the 154 genes and used the bioconductor packages (https://www.bioconductor.org/help/workflows/generegulation) to find the potential binding site at the 1500bp sequence of MYBL2 at the upstream of TSS ^[32]. As a result, only E2F1, E2F2, E2F7 and ZNF695 can find the matched sequence. In accordance with this, previous studies have shown that E2F1 and E2F2 could transactivate MYBL2 and thus regulated cell cycle ^[4]. All these data suggested that E2F7 and ZNF695 may be alternative upstream regulator of MYBL2.

In addition, to investigate whether the elevated MYBL2 expression in prostate, lung cancer and breast cancer could be used as predictive marker, we used Gleason score of prostate cancer, tipple negative status of breast cancer and adenocarcinoma or not of lung cancer. And the data showed that the elevated MYBL2 expression was correlated with high gleason score of prostate cancer, correlated with tipple negative status of breast cancer and correlated with squamous lung cancer.

In conclusion, the present study indicates that elevated expression of MYBL2 can be used as a biomarker of poor patient prognosis in a large variety of human cancers. Patients with low MYLB2 expression and no-TP53 altered had the best prognosis compared to the worst prognosis of patients with high MYLB2 expression and TP53 altered in PRAD and BRCA. In our future work, we will collect clinical samples from different cancers, such as prostate, breast, and lung cancer. It can be noted that artificial intelligence techniques can also be employed in the further analysis for those cancers ^{[33,34,35,36]}. Then, we employ the FFPE tissues from those cancers on the protein level to explore the effect of the protein expression by IHC in the clinic. Moreover, we will further verify the regulatory relationship between p35, E2F2, ZNF659 and MYBL2 in cancer cells using the clinical samples experimentally. The detailed mechanism that mediates the poor prognosis and the study about the downstream targets of MYBL2 can also be treated as one of the research directions.

Acknowledgments

This study is sponsored by Precision Medicine Center, Tianjin Medical University General Hospital and Departments of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University. We would like to especially thank Dr Xinhua Liu and colleagues from Tianjin Medical University for discussions and comments.

Abbreviations

TCGA    The Cancer Genome Atlas

COSMIC     Catalogue of somatic mutations in cancer

cBioPortal  cBio cancer genomics portal

OS      Overall survival

DSS     Disease-specific survival

PFI      Progressive-free interval

ACC     Adrenocortical carcinoma

BLCA    Bladder Urothelial Carcinoma

BRCA    Breast invasive carcinoma

CESC       Cervical squamous cell carcinoma and endocervical adenocarcinoma

CHOL    Cholangio carcinoma

COAD    Colon adenocarcinoma

DLBC    Lymphoid Neoplasm Diffuse Large B-cell Lymphoma

ESCA     Esophageal carcinoma

GBM     Glioblastoma multiforme

HNSC    Head and Neck squamous cell carcinoma

KICH    Kidney Chromophobe

KIRC    Kidney renal clear cell carcinoma

KIRP     Kidney renal papillary cell carcinoma

LAML    Acute Myeloid Leukemia

LGG     Brain Lower Grade Glioma

LIHC     Liver hepatocellular carcinoma

LUAD    Lung adenocarcinoma

LUSC    Lung squamous cell carcinoma

MESO    Mesothelioma

OV       Ovarian serous cystadenocarcinoma

PAAD    Pancreatic adenocarcinoma

PCPG     Pheochromocytoma and Paraganglioma

PRAD    Prostate adenocarcinoma

READ    Rectum adenocarcinoma

SARC    Sarcoma

SKCM    Skin Cutaneous Melanoma

STAD    Stomach adenocarcinoma

TGCT    Testicular Germ Cell Tumors

THCA    Thyroid carcinoma

THYM    Thymoma

UCEC    Uterine Corpus Endometrial Carcinoma

UCS     Uterine Carcinosarcoma

UVM     Uveal Melanoma

Conflict of interest

The authors declare no competing interests.