Methylation of the Phospholipase A2 Receptor 1 Promoter Region in Childhood B Cell Acute Lymphoblastic Leukaemia

Blood-Based DNA Methylation Analysis by Multiplexed OBBPA-ddPCR to Verify Indications for Prostate Biopsies in Suspected Prostate Cancer Patients

Current prostate carcinoma (PCa) biomarkers, including total prostate-specific antigen (tPSA), have unsatisfactory diagnostic sensitivity and specificity resulting in overdiagnosis and overtreatment. Previously, we described an optimised bias-based preamplification-digital droplet PCR (OBBPA-ddPCR) technique, which detects tumour DNA in blood-derived cell-free DNA (cfDNA) of cancer patients. The current study investigated the performance of newly developed OBBPA-ddPCR-based biomarkers. Blood plasma samples from healthy individuals (n = 90, controls) and PCa (n = 39) and benign prostatic hyperplasia patients (BPH, n = 40) were analysed. PCa and BPH patients had tPSA values within a diagnostic grey area of 2-15 ng/mL, for whom further diagnostic validation is most crucial. Methylation levels of biomarkers RASSF1A, MIR129-2, NRIP3, and SOX8 were found significantly increased in PCa patients compared to controls. By combining classical PCa risk factors (percentage of free PSA compared to tPSA (QfPSA) and patient's age) with cfDNA-based biomarkers, we developed PCa risk scores with improved sensitivity and specificity compared to established tPSA and QfPSA single-marker analyses. The diagnostic specificity was increased to 70% with 100% sensitivity for clinically significant PCa patients. Thus, prostate biopsies could be avoided for 28 out of 40 BPH patients. In conclusion, the newly developed risk scores may help to confirm the clinical decision and prevent unnecessary prostate biopsy.

CENPA knockdown restrains cell progression and tumor growth in breast cancer by reducing PLA2R1 promoter methylation and modulating PLA2R1/HHEX axis

BACKGROUND

Breast cancer is a lethal malignancy affecting females worldwide. It has been reported that upregulated centromere protein A (CENPA) expression might indicate unfortunate prognosis and can function as a prognostic biomarker in breast cancer. This study aimed to investigate the accurate roles and downstream mechanisms of CENPA in breast cancer progression.

METHODS

CENPA protein levels in breast cancer tissues and cell lines were analyzed by Western blot and immunohistochemistry assays. We used gain/loss-of-function experiments to determine the potential effects of CENPA and phospholipase A2 receptor (PLA2R1) on breast cancer cell proliferation, migration, and apoptosis. Co-IP assay was employed to validate the possible interaction between CENPA and DNA methyltransferase 1 (DNMT1), as well as PLA2R1 and hematopoietically expressed homeobox (HHEX). PLA2R1 promoter methylation was determined using methylation-specific PCR assay. The biological capabilities of CENPA/PLA2R1/HHEX axis in breast cancer cells was determined by rescue experiments. In addition, CENPA-silenced MCF-7 cells were injected into mice, followed by measurement of tumor growth.

RESULTS

CENPA level was prominently elevated in breast cancer tissues and cell lines. Interestingly, CENPA knockdown and PLA2R1 overexpression both restrained breast cancer cell proliferation and migration, and enhanced apoptosis. On the contrary, CENPA overexpression displayed the opposite results. Moreover, CENPA reduced PLA2R1 expression through promoting DNMT1-mediated PLA2R1 promoter methylation. PLA2R1 overexpression could effectively abrogate CENPA overexpression-mediated augment of breast cancer cell progression. Furthermore, PLA2R1 interacted with HHEX and promoted HHEX expression. PLA2R1 knockdown increased the rate of breast cancer cell proliferation and migration but restrained apoptosis, which was abrogated by HHEX overexpression. In addition, CENPA silencing suppressed tumor growth in vivo.

CONCLUSION

CENPA knockdown restrained breast cancer cell proliferation and migration and attenuated tumor growth in vivo through reducing PLA2R1 promoter methylation and increasing PLA2R1 and HHEX expression. We may provide a promising prognostic biomarker and novel therapeutic target for breast cancer.

Genome-wide expression profiling reveals novel biomarkers in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the most aggressive and frequent malignancy detected among women worldwide. The pathophysiology of OC should, therefore be better understood to identify diagnostic, prognostic, and predictive novel biomarkers necessary for early detection, management, and prognostication. In this study, we aimed to investigate transcriptomic landscape and biomarker through RNA-seq data analysis. Further analysis by Protein Protein network identified top 10 Differentially Expressed Genes (DEGs). KEGG pathway enrichment analysis revealed the significant enrichment of DEGs in basal cell carcinoma, cell cycle and FoxO signalling pathway. The RNA-seq results of 10 DEGs were validated by QRT-PCR and TCGA database. Correlation studies were also performed between gene expression and clinical characteristics followed by survival analysis. Finally, 8 DEGs (CDKN1A, BCL6, CDC45, WNT2, TLR5, AQP5) including two novel DEGs (CSN1S1 and NKILA) were identified showing significant correlations with EOC characteristics. These may serve as interesting biomarkers and novel treatment targets and warrant further investigation into the functional outcome of EOC.

Clinical importance of PLA2R1 and RASSF9 in thyroid cancer and their inhibitory roles on the Wnt/β-catenin pathway and thyroid cancer cell malignant behaviors

Thyroid cancer is a common malignant tumor with rising incidence worldwide. The purpose of this study was to explore key genes in thyroid cancer. The differentially expressed genes were analyzed according to GEO datasets. PLA2R1 and RASSF9 levels were confirmed by UALCAN and the Human Protein Atlas databases. The disease free survival and linear correlation were analyzed by GEPIA. ROC curve was generated according to The Cancer Genome Atlas (TCGA) database. The methylation level and immune infiltration were analyzed using GSCA platform. PLA2R1, RASSF9 and Wnt/β-catenin-related protein levels were detected by western blotting. Cell proliferation was assessed by 5-ethynyl-2'-deoxyuridine assay. Cell invasion and migration were evaluated by Transwell assay. There were 2 common differentially expressed genes (PLA2R1 and RASSF9) in thyroid cancer from GSE104005, GSE65144 and GSE53157 datasets. Decreased PLA2R1 and RASSF9 were associated with advanced stages and lower disease free survival. PLA2R1 and RASSF9 methylation levels were enhanced in thyroid cancer samples compared with normal samples. PLA2R1 methylation level was negatively correlated to its mRNA level. PLA2R1 and RASSF9 were related to immune infiltration in thyroid cancer. PLA2R1 and RASSF9 expression was associated with radioiodine resistance, and positively correlated to expression of iodide uptake-related factors. Multiple signaling pathways were involved in the action mechanisms of PLA2R1 and RASSF9, including the Wnt/β-catenin signaling. Overexpression of PLA2R1 and RASSF9 inhibited the activation of the Wnt/β-catenin pathway, proliferation, invasion, and migration in thyroid cancer cells. Collectively, PLA2R1 and RASSF9 are two key genes in thyroid cancer, which have potential diagnostic, prognostic, and anti-tumor effects in thyroid cancer.

Increased Sensitivity of Detection of RASSF1A and GSTP1 DNA Fragments in Serum of Prostate Cancer Patients: Optimisation of Diagnostics Using OBBPA-ddPCR

Identification of aberrant DNA methylation is a promising tool in prostate cancer (PCa) diagnosis and treatment. In this study, we evaluated a two-step method named optimised bias-based preamplification followed by digital PCR (OBBPA-dPCR). The method was used to identify promoter hypermethylation of 2 tumour suppressor genes RASSF1A and GSTP1 in the circulating cell-free DNA (cfDNA) from serum samples of PCa patients (n = 75), benign prostatic hyperplasia (BPH, n = 58), and healthy individuals (controls, n = 155). The PCa cohort was further subdivided into subgroups comprising (I) patients with Gleason Scores (GS) ≤ 7 (n = 55), (II) GS ≥ 8 (n = 10), and (III) patients with metastatic PCa diagnosis (n = 10). We found that RASSF1A methylation levels were significantly increased in all 3 PCa subgroups compared to the controls and BPH cohorts (p < 0.01 for all comparisons). Fractional abundances of methylated GSTP1 DNA fragments were significantly increased in subgroup III of metastatic PCa patients (p < 0.001). RASSF1A methylation analysis was found to be beneficial as a complementary biomarker where further diagnostic validation is most crucial. In combination with free PSA, RASSF1A methylation status helps to identify PCa patients with GS ≥ 8 and grey-zone total PSA values between 2-10 ng/mL. In our study, PCR biases between 80-90% were sufficient to detect minute amounts of tumour DNA with high signal-to-noise ratios as well as high analytical sensitivity and specificity. Both RASSF1A and GSTP1 exhibited strongly increased DNA methylation levels in all metastatic PCa patients. Our data indicates a superior sensitivity of epigenetic biomarker analyses in early detection of PCa metastases that should also help to improve PCa therapy.

PLA2R1 promotes DNA damage and inhibits spontaneous tumor formation during aging

Although aging is a major risk factor for most types of cancers, it is barely studied in this context. The transmembrane protein PLA2R1 (phospholipase A2 receptor) promotes cellular senescence, which can inhibit oncogene-induced tumor initiation. Functions and mechanisms of action of PLA2R1 during aging are largely unknown. In this study, we observed that old Pla2r1 knockout mice were more prone to spontaneously develop a wide spectrum of tumors compared to control littermates. Consistently, these knockout mice displayed increased Parp1, a master regulator of DNA damage repair, and decreased DNA damage, correlating with large human dataset analysis. Forced PLA2R1 expression in normal human cells decreased PARP1 expression, induced DNA damage and subsequent senescence, while the constitutive expression of PARP1 rescued cells from these PLA2R1-induced effects. Mechanistically, PARP1 expression is repressed by a ROS (reactive oxygen species)-Rb-dependent mechanism upon PLA2R1 expression. In conclusion, our results suggest that PLA2R1 suppresses aging-induced tumors by repressing PARP1, via a ROS-Rb signaling axis, and inducing DNA damage and its tumor suppressive responses.

Integrative Analysis of Multi-Omics Identified the Prognostic Biomarkers in Acute Myelogenous Leukemia

Background

Acute myelogenous leukemia (AML) is a common pediatric malignancy in children younger than 15 years old. Although the overall survival (OS) has been improved in recent years, the mechanisms of AML remain largely unknown. Hence, the purpose of this study is to explore the differentially methylated genes and to investigate the underlying mechanism in AML initiation and progression based on the bioinformatic analysis.

Methods

Methylation array data and gene expression data were obtained from TARGET Data Matrix. The consensus clustering analysis was performed using ConsensusClusterPlus R package. The global DNA methylation was analyzed using methylationArrayAnalysis R package and differentially methylated genes (DMGs), and differentially expressed genes (DEGs) were identified using Limma R package. Besides, the biological function was analyzed using clusterProfiler R package. The correlation between DMGs and DEGs was determined using psych R package. Moreover, the correlation between DMGs and AML was assessed using varElect online tool. And the overall survival and progression-free survival were analyzed using survival R package.

Results

All AML samples in this study were divided into three clusters at k = 3. Based on consensus clustering, we identified 1,146 CpGs, including 40 hypermethylated and 1,106 hypomethylated CpGs in AML. Besides, a total 529 DEGs were identified, including 270 upregulated and 259 downregulated DEGs in AML. The function analysis showed that DEGs significantly enriched in AML related biological process. Moreover, the correlation between DMGs and DEGs indicated that seven DMGs directly interacted with AML. CD34, HOXA7, and CD96 showed the strongest correlation with AML. Further, we explored three CpG sites cg03583857, cg26511321, cg04039397 of CD34, HOXA7, and CD96 which acted as the clinical prognostic biomarkers.

Conclusion

Our study identified three novel methylated genes in AML and also explored the mechanism of methylated genes in AML. Our finding may provide novel potential prognostic markers for AML.