A panel of epigenetically dysregulated Wnt signaling pathway genes for non-invasive diagnosis of pediatric acute lymphoblastic leukemia

Epigenetically dysregulated NOTCH-Delta-HES signaling cascade can serve as a subtype classifier for acute lymphoblastic leukemia

The NOTCH-Delta-HES signaling cascade is regarded as a double-edged sword owing to its dual tumor-suppressor and oncogenic roles, in different cellular environments. In the T-cells, it supports leukemogenesis by promoting differentiation while in B-cells, it controls leukemogenesis by inhibiting early differentiation/inducing growth arrest in the lead to apoptosis. The present study was undertaken to assess if this bi-faceted behavior of NOTCH family can be exploited as a diagnostic biomarker or subtype classifier of acute lymphoblastic leukemia (ALL). In this pursuit, expression of seven NOTCH cascade genes was analyzed in bone marrow (BM) biopsy and blood plasma (BP) of pediatric ALL patients using quantitative PCR (qPCR). Further, promoter DNA methylation status of the differentially expressed genes (DEGs) was assessed by methylation-specific qMSP and validated through bisulphite amplicon sequencing. Whereas hypermethylation of JAG1, DLL1, and HES-2, HES-4, and HES-5 was observed in all patients, NOTCH3 was found hypermethylated specifically in Pre-B ALL cases while DLL4 in Pre-T ALL cases. Aberrant DNA methylation strongly correlated with downregulated gene expression, which restored at complete remission stage as observed in "follow-up/post-treatment" subjects. The subtype-specific ROC curve analysis and Kaplan-Meier survival analysis predicted a clinically applicable diagnostic and prognostic potential of the panel. Moreover, the logistic regression model (Pre-B vs Pre-T ALL) was found to be the best-fitted model (McFadden's R2 = 0.28, F1 measure = 0.99). Whether analyzed in BM-aspirates or blood plasma, the NOTCH epigenetic signatures displayed comparable results (p < 0.001), advocating the potential of NOTCH-Delta-HES cascade, as a subtype classifier, in minimally invasive diagnosis of ALL.

Circulating Biomarkers Associated with the Diagnosis and Prognosis of B-Cell Progenitor Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is a hematological disease characterized by the dysfunction of the hematopoietic system that leads to arrest at a specific stage of stem cells development, suppressing the average production of cellular hematologic components. BCP-ALL is a neoplasm of the B-cell lineage progenitor. BCP-ALL is caused and perpetuated by several mechanisms that provide the disease with its tumor potential and genetic and cytological characteristics. These pathological features are used for diagnosis and the prognostication of BCP-ALL. However, most of these paraclinical tools can only be obtained by bone marrow aspiration, which, as it is an invasive study, can delay the diagnosis and follow-up of the disease, in addition to the anesthetic risk it entails for pediatric patients. For this reason, it is crucial to find noninvasive and accessible ways to supply information concerning diagnosis, prognosis, and the monitoring of the disease, such as circulating biomarkers. In oncology, a biomarker is any measurable indicator that demonstrates the presence of malignancy, tumoral behavior, prognosis, or responses to treatments. This review summarizes circulating molecules associated with BCP-ALL with potential diagnostic value, classificatory capacity during monitoring specific clinic features of the disease, and/or capacity to identify each BCP-ALL stage regarding its evolution and outcome of the patients with BCP-ALL. In the same way, we provide and classify biomarkers that may be used in further studies focused on clinical approaches or therapeutic target identification for BCP-ALL.

Comprehensive Analysis of DNA Methylation and Transcriptome to Identify PD-1-Negative Prognostic Methylated Signature in Endometrial Carcinoma

Background

Epigenetic mechanism plays an important role in endometrial carcinoma (EC). This study was designed to analyze the epigenetic mechanism between DNA methylation-driven genes (DEDGs) and drugs targeting DEDGs and to develop a DEDG score model for predicting the prognosis of EC.

Methods

Expression profile and methylation profile data of PD-1-negative EC samples were obtained from TCGA. To obtain intersected DEDGs, differentially expressed genes (DEGs) and differentially methylated genes from tumor tissues and normal tissues were analyzed by limma. A linear discriminant classification model was constructed using the gene expression profile of DMDGs, methylation profile of TSS1500, TSS200, and gene body regions. Principal component analysis (PCA) and ROC analysis were conducted. The protein-drug interactions analysis of DMDGs was performed using Network Analyst 3.0 tool. Lasso Cox regression analysis was used to screen prognostic DNA methylation driving gene and to build a risk score model. The ROC curve and Kaplan-Meier survival curve were plotted to evaluate the model prediction capability.

Results

A total of 96 DMDGs were screened from the three regions, distributed on 22 chromosomes, with consistent methylation patterns in different gene regions. Both the expression profile and methylation profile of the three regions can neatly distinguish tumor samples from normal ones, with a high classifying performance. A gene signature, which consisted of ELFN1-AS1 and ZNF132, could classify EC patients into a high-risk group and low-risk group. Prognosis of the high-risk group was significantly worse than that of the low-risk group. The risk model showed a high performance in predicting the prognosis of EC.

Conclusion

We successfully established a risk score system with two DMDGs, which showed a high prediction accuracy of EC prognosis.