Uniformly shaped harmonization combines human transcriptomic data from different platforms while retaining their biological properties and differential gene expression patterns

Introduction: Co-normalization of RNA profiles obtained using different experimental platforms and protocols opens avenue for comprehensive comparison of relevant features like differentially expressed genes associated with disease. Currently, most of bioinformatic tools enable normalization in a flexible format that depends on the individual datasets under analysis. Thus, the output data of such normalizations will be poorly compatible with each other. Recently we proposed a new approach to gene expression data normalization termed Shambhala which returns harmonized data in a uniform shape, where every expression profile is transformed into a pre-defined universal format. We previously showed that following shambhalization of human RNA profiles, overall tissue-specific clustering features are strongly retained while platform-specific clustering is dramatically reduced.Methods: Here, we tested Shambhala performance in retention of fold-change gene expression features and other functional characteristics of gene clusters such as pathway activation levels and predicted cancer drug activity scores.Results: Using 6,793 cancer and 11,135 normal tissue gene expression profiles from the literature and experimental datasets, we applied twelve performance criteria for different versions of Shambhala and other methods of transcriptomic harmonization with flexible output data format. Such criteria dealt with the biological type classifiers, hierarchical clustering, correlation/regression properties, stability of drug efficiency scores, and data quality for using machine learning classifiers.Discussion: Shambhala-2 harmonizer demonstrated the best results with the close to 1 correlation and linear regression coefficients for the comparison of training vs validation datasets and more than two times lesser instability for calculation of drug efficiency scores compared to other methods

Differential co‐expression network analysis elucidated genes associated with sensitivity to farnesyltransferase inhibitor and prognosis of acute myeloid leukemia

Abstract Acute myeloid leukemia (AML) is a heterogeneous disease and the most common form of acute leukemia with a poor prognosis. Due to its complexity, the disease requires the identification of biomarkers for reliable prognosis. To identify potential disease genes that regulate patient prognosis, we used differential co‐expression network analysis and transcriptomics data from relapsed, refractory, and previously untreated AML patients based on their response to treatment in the present study. In addition, we combined functional genomics and transcriptomics data to identify novel and therapeutically potential systems biomarkers for patients who do or do not respond to treatment. As a result, we constructed co‐expression networks for response and non‐response cases and identified a highly interconnected group of genes consisting of SECISBP2L, MAN1A2, PRPF31, VASP, and SNAPC1 in the response network and a group consisting of PHTF2, SLC11A2, PDLIM5, OTUB1, and KLRD1 in the non‐response network, both of which showed high prognostic performance with hazard ratios of 4.12 and 3.66, respectively. Remarkably, ETS1, GATA2, AR, YBX1, and FOXP3 were found to be important transcription factors in both networks. The prognostic indicators reported here could be considered as a resource for identifying tumorigenesis and chemoresistance to farnesyltransferase inhibitor. They could help identify important research directions for the development of new prognostic and therapeutic techniques for AML

Higher proteotoxic stress rather than mitochondrial damage is involved in higher neurotoxicity of bortezomib compared to carfilzomib

12 pages, 6 figures, 1 table.-- This is an open access article under the CC BY-NC-ND licenseProteasome inhibitors have great success for their therapeutic potential against hematologic malignancies. First generation proteasome inhibitor bortezomib induced peripheral neuropathy is considered as a limiting factor in chemotherapy and its second-generation counterpart carfilzomib is associated with lower rates of neurotoxicity. The mitochondrial toxicity (mitotoxicity) hypothesis arises from studies with animal models of bortezomib induced peripheral neuropathy. However, molecular mechanisms are not fully elucidated and the role of mitotoxicity in bortezomib and carfilzomib induced neurotoxicity has not been investigated comparatively. Herein, we characterized the neurotoxic effects of bortezomib and carfilzomib at the molecular level in human neuronal cells using LC-MS/MS analysis, flow cytometry, RT-qPCR, confocal microscopy and western blotting. We showed that bortezomib and carfilzomib affected the human neuronal proteome differently, and bortezomib caused higher proteotoxic stress via protein oxidation, protein K48-ubiquitination, heat shock protein expression upregulation and reduction of mitochondria membrane potential. Bortezomib and carfilzomib did not affect the gene expression levels related to mitochondrial dynamics (optic atrophy 1; OPA1, mitofusin 1; MFN1, mitofusin 2; MFN2, fission 1; FIS1, dynamin-related protein 1; DRP1) and overall mitophagy rate whereas, PINK1/Parkin mediated mitophagy gene expressions were altered with both drugs. Bortezomib and carfilzomib caused downregulation of the contents of mitochondrial oxidative phosphorylation complexes, voltage-dependent anion channel 1 (VDAC1) and uncoupling protein 2 (UCP2) similarly. Our findings suggest that, both drugs induce mitotoxicity besides proteotoxic stress in human neuronal cells and the higher incidence of neurotoxicity with bortezomib than carfilzomib is not directly related to mitochondrial pathwaysThis study was supported by The Scientific and Technological Research Council of Turkey - TUBITAK (216S838) and Istanbul University Research Fund (TDK-2017-24221 and TSA-2017-25380). Financial support from the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept for SysMedOS project is gratefully acknowledged. Xunta de Galicia is thankfully acknowledged for the postdoctoral scholarship provided L.MPeer reviewe

HSP70 Inhibition Leads to the Activation of Proteasomal System under Mild Hyperthermia Conditions in Young and Senescent Fibroblasts

Aging has been characterized with the accumulation of oxidized proteins, as a consequence of progressive decline in proteostasis capacity. Among others, proteasomal system is an efficient protein turnover complex to avoid aggregation of oxidized proteins. Heat shock protein 70 (HSP70) is another critical player that is involved in some key processes including the correct folding of misfolded proteins and targeting aggregated proteins to the proteasome for rapid degradation. The aim of this study was to determine the role of proteasomal system and heat shock proteins to maintain proteome balance during replicative senescence in mild hyperthermia conditions. Our results demonstrated that HSP40/70 machinery is induced by mild hyperthermia conditions independent from senescence conditions. Since HSP70 is largely responsible for the rapidly inducible cell protection following hyperthermia, the activation of "heat shock response" resulted in the elevation of HSP40/70 expressions as well as the proteasome activity. Interestingly, when HSP70 expression was inhibited, increased proteasomal activation was shown to be responsive to mild hyperthermia. Since HSP70 is involved in various stress-related pathways such as oxidative and endoplasmic reticulum stress, depletion of HSP70 expression may induce proteasomal degradation to maintain proteome balance of the cell. Thus, our data suggests that in mild heat stress conditions, molecular chaperone HSP70 plays an important role to avoid protein oxidation and aggregation; however, activities of proteasomal system are induced when HSP70 expression is depleted

Exploring the Anticancer Effects of Brominated Plastoquinone Analogs with Promising Cytotoxic Activity in MCF-7 Breast Cancer Cells via Cell Cycle Arrest and Oxidative Stress Induction

Plastoquinone analogs are privileged structures among the known antiproliferative natural product-based compound families. Exploiting one of these analogs as a lead structure, we report the investigation of the brominated PQ analogs (BrPQ) in collaboration with the National Cancer Institute of Bethesda within the Developmental Therapeutics Program (DTP). These analogs exhibited growth inhibition in the micromolar range across leukemia, non-small cell lung cancer (EKVX, HOP-92, and NCI-H522), colon cancer (HCT-116, HOP-92), melanoma (LOX IMVI), and ovarian cancer (OVCAR-4) cell lines. One brominated PQ analog (BrPQ5) was selected for a full panel five-dose in vitro assay by the NCI’s Development Therapeutic Program (DTP) division to determine GI50, TGI, and LC50 parameters. The brominated PQ analog (BrPQ5) displayed remarkable activity against most tested cell lines, with GI50 values ranging from 1.55 to 4.41 µM. The designed molecules (BrPQ analogs) obeyed drug-likeness rules, displayed a favorable predictive Absorption, Distribution, Metabolism, and Excretion (ADME) profile, and an in silico simulation predicted a possible BrPQ5 interaction with proteasome catalytic subunits. Furthermore, the in vitro cytotoxic activity of BrPQ5 was assessed, and IC50 values for U-251 glioma, MCF-7 and MDA-MB-231 breast cancers, DU145 prostate cancer, HCT-116 colon cancer, and VHF93 fibroblast cell lines were evaluated using an MTT assay. MCF-7 was the most affected cell line, and the effects of BrPQ5 on cell proliferation, cell cycle, oxidative stress, apoptosis/necrosis induction, and proteasome activity were further investigated in MCF-7 cells. The in vitro assay results showed that BrPQ5 caused cytotoxicity in MCF-7 breast cancer cells via cell cycle arrest and oxidative stress induction. However, BrPQ5 did not inhibit the catalytic activity of the proteasome. These results provide valuable insights for further discovery of novel antiproliferative agents

Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas

Interactome analysis of Bag-1 isoforms reveals novel interaction partners in endoplasmic reticulum-associated degradation

Bag-1 is a multifunctional protein that regulates Hsp70 chaperone activity, apoptosis, and proliferation. The three major Bag-1 isoforms have different subcellular localizations and partly non-overlapping functions. To identify the detailed interaction network of each isoform, we utilized mass spectrometry-based proteomics and found that interactomes of Bag-1 isoforms contained many common proteins, with variations in their abundances. Bag-1 interactomes were enriched with proteins involved in protein processing and degradation pathways. Novel interaction partners included VCP/p97; a transitional ER ATPase, Rad23B; a shuttling factor for ubiquitinated proteins, proteasome components, and ER-resident proteins, suggesting a role for Bag-1 also in ER-associated protein degradation (ERAD). Bag-1 pull-down from cells and tissues from breast cancer patients validated these interactions and showed cancer-related prominence. Using in silico predictions we detected hotspot residues of Bag-1. Mutations of these residues caused loss of binding to protein quality control elements and impaired proteasomal activity in MCF-7 cells. Following CD147 glycosylation pattern, we showed that Bag-1 downregulated VCP/p97-dependent ERAD. Overall, our data extends the interaction map of Bag-1, and broadens its role in protein homeostasis. Targeting the interaction surfaces revealed in this study might be an effective strategy in the treatment of cancer