Epigenetic silencing of MEIS2 in prostate cancer recurrence

MEIS2 suppresses breast cancer development by downregulating IL10

BACKGROUND

Breast cancer (BC) is the most commonly diagnosed female cancer. Homeobox protein MEIS2, a key transcription factor, is involved in the regulation of many developmental and cellular processes. However, the role of MEIS2 in the development of breast cancer is still unclear.

AIMS

We aimed to examine the role of myeloid ecotropic insertion site (MEIS2) in breast cancer and the association of MEIS2 with breast cancer clinical stages and pathological grades. We revealed the underlying mechanism by which MEIS2 affected breast cancer cell growth and tumor development.

METHODS AND RESULTS

Using human BC cell lines, clinical samples and animal xenograft model, we reveal that MEIS2 functions as a tumor suppressor in breast cancer. The expression of MEIS2 is inversely correlated with BC clinical stages and pathological grades. MEIS2 knockdown (MEIS2-KD) promotes while MEIS2 overexpression suppresses breast cancer cell proliferation and tumor development in vitro and in animal xenograft models, respectively. To determine the biological function of MEIS2, we screen the expression of a group of MEIS2 potential targeting genes in stable-established cell lines. Results show that the knockdown of MEIS2 in breast cancer cells up-regulates the IL10 expression, but MEIS2 overexpression opposed the effect on IL10 expression. Furthermore, the suppressive role of MEIS2 in breast cancer cell proliferation is associated with the IL10 expression and myeloid cells infiltration.

CONCLUSION

Our study demonstrates that the tumor suppressor of MEIS2 in breast cancer progression is partially via down regulating the expression of IL10 and promoting myeloid cells infiltration. Targeting MEIS2 would be a potentially therapeutic avenue for BC.

Transcription Factor ELF1 Modulates Cisplatin Sensitivity in Prostate Cancer by Targeting MEIS Homeobox 2

As a widely used first-line agent for prostate cancer treatment, cisplatin is facing drug resistance which has resulted in chemotherapy failure in many prostate cancer patients, while the related molecular mechanisms remain unclear. In this study, we discovered that MEIS homeobox 2 (MEIS2) was lowly expressed in prostate cancer tissues by bioinformatics analysis, which had a close connection with the T stage and N stage of the tumor. Cell function experiments demonstrated that MEIS2 overexpression was capable of significantly suppressing proliferation of tumor cells, arresting prostate cancer cells in G0/G1 phase, and promoting DNA damage, thereby enhancing the sensitivity of prostate cancer to cisplatin. Dual-luciferase assay and chromatin co-immunoprecipitation (ChIP) assays confirmed the binding relationship between MEIS2 and ELF1. The results of rescue assay showed that ELF1 could promote DNA damage and enhance the sensitivity of tumor cells to cisplatin by activating MEIS2. In conclusion, the results of this study demonstrated that ELF1 could modulate DNA damage through activating MEIS2 and thus enhance cisplatin sensitivity in prostate cancer. This study suggested that the ELF1/MEIS2 axis may be a therapeutic target to strengthen cisplatin sensitivity in prostate cancer.

EpCAM as a Novel Biomarker for Survivals in Prostate Cancer Patients

Background: Due to the insufficient understanding of the biological mechanisms, the improvement of therapeutic effects of prostate cancer (PCa) is limited. There is an urgent need to find the molecular mechanisms and underlying PCa to improve its early diagnosis, treatment, and prognosis.

Methods: The mRNA expression profiles, survival and methylation data of PRAD were downloaded from The Cancer Genome Atlas (TCGA) database. The identification of differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed by R software. Subsequently, we identified the key gene and validated its prognostic role from the Human Protein Atlas (HPA) database, UALCAN and the LinkedOmics database. We performd correlation analysis and constructed the ceRNA network based on the data obtained from miRbase and starBase. Finally, we performed methylation analysis and evaluated the immune cell infiltration by Tumor Immune Estimation Resource (TIMER).

Results: A total of 567 DEGs were identified in PCa. ARHGEF38, SLPI, EpCAM, C1QTNF1, and HBB were regarded as target genes related to favorable overall survival (OS). Among them, EpCAM was considered as the most significant gene through the HPA database and receiver operating characteristic (ROC) analysis. A prognostic ceRNA network was constructed with EBLN3P, miR-204-5p, and EpCAM. EpCAM was found to be related to DNA methylation and tumor-infiltrating immune cells.

Conclusion: Our findings provide novel insights into the tumorigenesis mechanism of PCa and contribute to the development of EpCAM as a potential prognostic biomarker in PCa.

Impact of large granular lymphocyte leukemia on blood DNA methylation and epigenetic clock modeling in Fischer 344 rats

Age-dependent differences in methylation at specific cytosine-guanosine sites (CpGs) have been used in "epigenetic clock" formulas to predict age. Deviations of epigenetic age from chronological age are informative of health status and are associated with adverse health outcomes, including mortality. In most cases, epigenetic clocks are performed on methylation from DNA extracted from circulating blood cells. However, the effect of neoplastic cells in the circulation on estimation and interpretation of epigenetic clocks is not well understood. Here, we explored this using Fischer 344 (F344) rats, a strain that often develops large granular lymphocyte leukemia (LGL). We found clear histological markers of LGL pathology in the spleens and livers of 27 out of 61 rats aged 17-27 months. We assessed DNA methylation by reduced representation bisulfite sequencing with coverage of 3 million cytosine residues. Although LGL broadly increased DNA methylation variability, it did not change epigenetic aging. Despite this, inclusion of rats with LGL in clock training sets significantly altered predictor selection probability at 83 of 121 commonly utilized CpGs. Furthermore, models trained on rat samples that included individuals with LGL had greater absolute age error than those trained exclusively on LGL-free rats (39% increase; p<0.0001). We conclude that the epigenetic signals for aging and LGL are distinct, such that LGL assessment is not necessary for valid measures of epigenetic age in F344 rats. The precision and architecture of constructed epigenetic clock formulas, however, can be influenced by the presence of neoplastic hematopoietic cells in training set populations.

Identification of novel biomarkers of prostate cancer through integrated analysis

Background

The current methods adopted to screen for prostate cancer (PCa) can sometimes be misleading and inaccurate. Moreover, for advanced stages of PCa, the current effect of treatment is not satisfactory for some patients. Accordingly, we aimed to identify new biomarkers for the diagnosis and prognosis of PCa.

Methods

A series of bioinformatic tools were utilized to search for potential new biomarkers of PCa and analyze their functions, expression, clinical relevance, prognostic value, and underlying mechanisms.

Results

Although ASPN was overexpressed in PCa, EDN3, PENK, MEIS2, IGF1, and CXCL12 were downregulated. The univariate Cox regression analysis showed that abnormally high expression of ASPN and low expression of other genes predicted worse prognosis. Moreover, the multivariate Cox regression analysis showed that ASPN, PENK, and MEIS2 were independently associated with the overall survival (OS) of patients, whereas other markers were not. The outcomes of gene ontology and gene set enrichment analysis showed that the expression levels of these genes might be associated with cell proliferation and infiltration of immune cells in PCa.

Conclusions

We demonstrated that ASPN, EDN3, PENK, MEIS2, IGF1, and CXCL12 are possibly novel diagnostic indicators for PCa, whereas ASPN, PENK, and MEIS2 show appealing potential to predict the prognosis of this disease.

Oncogenic and tumor suppressor function of MEIS and associated factors

MEIS proteins are historically associated with tumorigenesis, metastasis, and invasion in cancer. MEIS and associated PBX-HOX proteins may act as tumor suppressors or oncogenes in different cellular settings. Their expressions tend to be misregulated in various cancers. Bioinformatic analyses have suggested their upregulation in leukemia/lymphoma, thymoma, pancreas, glioma, and glioblastoma, and downregulation in cervical, uterine, rectum, and colon cancers. However, every cancer type includes, at least, a subtype with high MEIS expression. In addition, studies have highlighted that MEIS proteins and associated factors may function as diagnostic or therapeutic biomarkers for various diseases. Herein, MEIS proteins and associated factors in tumorigenesis are discussed with recent discoveries in addition to how they could be modulated by noncoding RNAs or newly developed small-molecule MEIS inhibitors.

Integrative Analysis of DNA Methylation and Gene Expression to Determine Specific Diagnostic Biomarkers and Prognostic Biomarkers of Breast Cancer

Background: DNA methylation is a common event in the early development of various tumors, including breast cancer (BRCA), which has been studies as potential tumor biomarkers. Although previous studies have reported a cluster of aberrant promoter methylation changes in BRCA, none of these research groups have proved the specificity of these DNA methylation changes. Here we aimed to identify specific DNA methylation signatures in BRCA which can be used as diagnostic and prognostic markers.

Methods: Differentially methylated sites were identified using the Cancer Genome Atlas (TCGA) BRCA data set. We screened for BRCA-differential methylation by comparing methylation profiles of BRCA patients, healthy breast biopsies and blood samples. These differential methylated sites were compared to nine main cancer samples to identify BRCA specific methylated sites. A BayesNet model was built to distinguish BRCA patients from healthy donors. The model was validated using three Gene Expression Omnibus (GEO) independent data sets. In addition, we also carried out the Cox regression analysis to identify DNA methylation markers which are significantly related to the overall survival (OS) rate of BRCA patients and verified them in the validation cohort.

Results: We identified seven differentially methylated sites (DMSs) that were highly correlated with cell cycle as potential specific diagnostic biomarkers for BRCA patients. The combination of 7 DMSs achieved ~94% sensitivity in predicting BRCA, ~95% specificity comparing healthy vs. cancer samples, and ~88% specificity in excluding other cancers. The 7 DMSs were highly correlated with cell cycle. We also identified 6 methylation sites that are highly correlated with the OS of BRCA patients and can be used to accurately predict the survival of BRCA patients (training cohort: likelihood ratio = 70.25, p = 3.633 × 10⁻¹³, area under the curve (AUC) = 0.784; validation cohort: AUC = 0.734). Stratification analysis by age, clinical stage, Tumor types, and chemotherapy retained statistical significance.

Conclusion: In summary, our study demonstrated the role of methylation profiles in the diagnosis and prognosis of BRCA. This signature is superior to currently published methylation markers for diagnosis and prognosis for BRCA patients. It can be used as promising biomarkers for early diagnosis and prognosis of BRCA.

Advances in Prognostic Methylation Biomarkers for Prostate Cancer

There is a major clinical need for accurate biomarkers for prostate cancer prognosis, to better inform treatment strategies and disease monitoring. Current clinically recognised prognostic factors, including prostate-specific antigen (PSA) levels, lack sensitivity and specificity in distinguishing aggressive from indolent disease, particularly in patients with localised intermediate grade prostate cancer. There has therefore been a major focus on identifying molecular biomarkers that can add prognostic value to existing markers, including investigation of DNA methylation, which has a known role in tumorigenesis. In this review, we will provide a comprehensive overview of the current state of DNA methylation biomarker studies in prostate cancer prognosis, and highlight the advances that have been made in this field. We cover the numerous studies into well-established candidate genes, and explore the technological transition that has enabled hypothesis-free genome-wide studies and the subsequent discovery of novel prognostic genes.

MEIS-mediated suppression of human prostate cancer growth and metastasis through HOXB13-dependent regulation of proteoglycans

The molecular roles of HOX transcriptional activity in human prostate epithelial cells remain unclear, impeding the implementation of new treatment strategies for cancer prevention and therapy. MEIS proteins are transcription factors that bind and direct HOX protein activity. MEIS proteins are putative tumor suppressors that are frequently silenced in aggressive forms of prostate cancer. Here we show that MEIS1 expression is sufficient to decrease proliferation and metastasis of prostate cancer cells in vitro and in vivo murine xenograft models. HOXB13 deletion demonstrates that the tumor-suppressive activity of MEIS1 is dependent on HOXB13. Integration of ChIP-seq and RNA-seq data revealed direct and HOXB13-dependent regulation of proteoglycans including decorin (DCN) as a mechanism of MEIS1-driven tumor suppression. These results define and underscore the importance of MEIS1-HOXB13 transcriptional regulation in suppressing prostate cancer progression and provide a mechanistic framework for the investigation of HOXB13 mutants and oncogenic cofactors when MEIS1/2 are silenced.