A Proteogenomic Approach to Understanding MYC Function in Metastatic Medulloblastoma Tumors

HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods—ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences.

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Here the authors present “HarmonizR”, a tool for missing data tolerant experimental variance reduction in large, integrated but independently generated datasets without data imputation, adjustable for individual dataset modalities, correction algorithm, and user preferences.

Current Challenges and Implications of Proteogenomic Approaches in Prostate Cancer

In the recent past, next-generation sequencing (NGS) approaches have heralded the omics era. With NGS data burgeoning, there arose a need to disseminate the omic data better. Proteogenomics has been vividly used for characterising the functions of candidate genes and is applied in ascertaining various diseased phenotypes, including cancers. However, not much is known about the role and application of proteogenomics, especially Prostate Cancer (PCa). In this review, we outline the need for proteogenomic approaches, their applications and their role in PCa.

Role of MYC-miR-29-B7-H3 in Medulloblastoma Growth and Angiogenesis

Medulloblastoma (MB) is the most common embryonal neuroepithelial tumor, with poor patient outcomes and secondary complications. In this study, we investigated the role of the B7 family of immune checkpoint homolog 3 (B7-H3) expression in MB angiogenesis. B7-H3, a co-inhibitory immune checkpoint, is highly expressed and is associated with lower overall survival in MYC⁺ MB's. Evidence for a direct transcriptional role of MYC on the B7-H3 gene promoter was confirmed by MYC inhibition and anti-MYC antibody ChIP analysis. Interestingly, MYC inhibition not only downregulated the B7-H3 protein expression, but also rescued miR-29 expression, thus indicating a triangular regulatory relationship between MYC, miR-29, and B7-H3 in Group 3 MB cells. From RNA seq and IPAD assay, we observed a negative feedback loop between miR-29 and MYC that may control B7-H3 expression levels in MB cells. Our studies show that B7-H3 expression levels play a crucial role in promoting MB angiogenesis which can be inhibited by miR-29 overexpression via miR-29-mediated B7-H3 downregulation. The tumor suppressor role of miR-29 is mediated by the activation of JAK/STAT1 signaling that further plays a role in MYC-B7-H3 downregulation in MB. This study highlights B7-H3 as a viable target in MB angiogenesis, and that the expression of miR-29 can inhibit B7-H3 and sensitize MB cells to treatment with MYC-inhibiting drugs.

Improved therapy for medulloblastoma: targeting hedgehog and PI3K-mTOR signaling pathways in combination with chemotherapy

Aberrant activation and interactions of hedgehog (HH) and PI3K/AKT/mTOR signaling pathways are frequently associated with high-risk medulloblastoma (MB). Thus, combined targeting of the HH and PI3K/AKT/mTOR pathways could be a viable therapeutic strategy to treat high-risk patients. Therefore, we investigated the anti-MB efficacies of combined HH inhibitor Vismodegib and PI3K-mTOR dual-inhibitor BEZ235 together or combined individually with cisplatin against high-risk MB. Using non-MYC- and MYC-amplified cell lines, and a xenograft mouse model, the in vitro and in vivo efficacies of these therapies on cell growth/survival and associated molecular mechanism(s) were investigated. Results showed that combined treatment of Vismodegib and BEZ235 together, or with cisplatin, significantly decreased MB cell growth/survival in a dose-dependent-fashion. Corresponding changes in the expression of targeted molecules following therapy were observed. Results demonstrated that inhibitors not only suppressed MB cell growth/survival when combined, but also significantly enhanced cisplatin-mediated cytotoxicity. Of these combinations, BEZ235 exhibited a significantly greater efficacy in enhancing cisplatin-mediated MB cytotoxicity. Results also demonstrated that the MYC-amplified MB lines showed a higher sensitivity to combined therapies compared to non-MYC-amplified cell lines. Therefore, we tested the efficacy of combined approaches against MYC-amplified MB growing in NSG mice. In vivo results showed that combination of Vismodegib and BEZ235 or their combination with cisplatin, significantly delayed MB tumor growth and increased survival of xenografted mice by targeting HH and mTOR pathways. Thus, our studies lay a foundation for translating these combined therapeutic strategies to the clinical setting to determine their efficacies in high-risk MB patients.

Identification of key genes and pathways in meningioma by bioinformatics analysis

Meningioma is the most frequently occurring type of brain tumor. The present study aimed to conduct a comprehensive bioinformatics analysis of key genes and relevant pathways involved in meningioma, and acquire further insight into the underlying molecular mechanisms. Initially, differentially expressed genes (DEGs) in 47 meningioma samples as compared with 4 normal meninges were identified. Subsequently, these DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. In addition, a protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes and visualized using Cytoscape. In total, 1,683 DEGs were identified, including 66 upregulated and 1,617 downregulated genes. The GO analysis results revealed that the DEGs were significantly associated with the ‘protein binding’, ‘cytoplasm’, ‘extracellular matrix (ECM) organization’ and ‘cell adhesion’ terms. The KEGG analysis results demonstrated the significant pathways included ‘AGE-RAGE signaling pathway in diabetic complications’, ‘PI3K-Akt signaling pathway’, ‘ECM-receptor interaction’ and ‘cell adhesion molecules’. The top five hub genes obtained from the PPI network were JUN, PIK3R1, FOS, AGT and MYC, and the most enriched KEGG pathways associated with the four obtained modules were ‘chemokine signaling pathway’, ‘cytokine-cytokine receptor interaction’, ‘allograft rejection’, and ‘complement and coagulation cascades’. In conclusion, bioinformatics analysis identified a number of potential biomarkers and relevant pathways that may represent key mechanisms involved in the development and progression of meningioma. However, these findings require verification in future experimental studies.

Pediatric brain tumors: Update of proteome-based studies

Pediatric brain tumors (PBTs) are the most common solid malignancies in childhood and continue to pose a serious burden to modern societies. Existing treatments impose debilitating effects on the developing child, highlighting the need for molecularly targeted treatments with reduced toxicity, as well as the necessity of markers that reliably assess efficacy of, and tumor response to targeted-therapies of PBTs. On this regard advances in technologies of protein identification and quantification, the large-scale, high-throughput investigation of the proteome, as well the newly-emerging field of "proteogenomics" aim to further our knowledge towards understanding the molecular pathophysiology of PBTs. This mini review article presents all updates on knowledge produced and published during the last years on PBT research derived from "omics" technologies, mainly involving protein research and proteomics.

Do the complementarities of electrokinetic and chromatographic procedures represent the "Swiss knife" in proteomic investigation? An overview of the literature in the past decade

This report reviews the literature of the past decade dealing with the combination of electrokinetic and chromatographic strategies in the proteomic field. Aim of this article is to highlight how the application of complementary techniques may contribute to substantially improve protein identification. Several studies here considered demonstrate that exploring the combination of these approaches can be a strategy to enrich the extent of proteomic information achieved from a sample. The coupling of "top-down" and "bottom-up" proteomics may result in the generation of a hybrid analytical tool, very efficient not only for large-scale profiling of complex proteomes but also for studying specific subproteomes. The range of applications described, while evidencing a continuous boost in the imagination of researchers for developing new combinations of methods for protein separation, also underlines the adaptability of these techniques to a wide variety of samples. This report points out the general usefulness of combining different procedures for proteomic analysis, an approach that allows researchers to go deeper in the proteome of samples under investigation.