Silencing AML1-ETO gene expression leads to simultaneous activation of both pro-apoptotic and proliferation signaling

Acute myeloid leukemia with t(8;21) translocation: Molecular pathogenesis, potential therapeutics and future directions

Acute myeloid leukemia (AML) is a highly heterogeneous and aggressive blood cancer. Genetic abnormalities, such as the t(8;21) rearrangement, play a significant role in AML onset. This rearrangement leads to the formation of the RUNX1/RUNX1T1 fusion protein, disrupting gene regulation and genomic stability, ultimately causing full-blown leukemia. Despite a generally favorable prognosis, t(8;21) patients face relapse and chemotherapy resistance, particularly when harboring cooperating mutations. While advances in cellular genetics and molecular biology have improved AML treatment, there are currently no specific targeted therapies against RUNX1/RUNX1T1. Therefore, investigating targeted therapies for this AML subtype holds promise for patients. This review explores the complex landscape of t(8;21) AML, unravels the molecular mechanisms of RUNX1/RUNX1T1-driven leukemogenesis, and discusses recent advancements in target therapies including small molecule drugs and PROTAC. Our goal is to develop more effective and less toxic strategies for managing t(8;21) AML patients.

Cancer fusion transcripts with human non-coding RNAs

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

Human Blood Serum Can Diminish EGFR-Targeted Inhibition of Squamous Carcinoma Cell Growth through Reactivation of MAPK and EGFR Pathways

Regardless of the presence or absence of specific diagnostic mutations, many cancer patients fail to respond to EGFR-targeted therapeutics, and a personalized approach is needed to identify putative (non)responders. We found previously that human peripheral blood and EGF can modulate the activities of EGFR-specific drugs on inhibiting clonogenity in model EGFR-positive A431 squamous carcinoma cells. Here, we report that human serum can dramatically abolish the cell growth rate inhibition by EGFR-specific drugs cetuximab and erlotinib. We show that this phenomenon is linked with derepression of drug-induced G1S cell cycle transition arrest. Furthermore, A431 cell growth inhibition by cetuximab, erlotinib, and EGF correlates with a decreased activity of ERK1/2 proteins. In turn, the EGF- and human serum-mediated rescue of drug-treated A431 cells restores ERK1/2 activity in functional tests. RNA sequencing revealed 1271 and 1566 differentially expressed genes (DEGs) in the presence of cetuximab and erlotinib, respectively. Erlotinib- and cetuximab-specific DEGs significantly overlapped. Interestingly, the expression of 100% and 75% of these DEGs restores to the no-drug level when EGF or a mixed human serum sample, respectively, is added along with cetuximab. In the case of erlotinib, EGF and human serum restore the expression of 39% and 83% of DEGs, respectively. We further assessed differential molecular pathway activation levels and propose that EGF/human serum-mediated A431 resistance to EGFR drugs can be largely explained by reactivation of the MAPK signaling cascade.

Experimental Validation and Prediction of Super-Enhancers: Advances and Challenges

Super-enhancers (SEs) are cis-regulatory elements of the human genome that have been widely discussed since the discovery and origin of the term. Super-enhancers have been shown to be strongly associated with the expression of genes crucial for cell differentiation, cell stability maintenance, and tumorigenesis. Our goal was to systematize research studies dedicated to the investigation of structure and functions of super-enhancers as well as to define further perspectives of the field in various applications, such as drug development and clinical use. We overviewed the fundamental studies which provided experimental data on various pathologies and their associations with particular super-enhancers. The analysis of mainstream approaches for SE search and prediction allowed us to accumulate existing data and propose directions for further algorithmic improvements of SEs' reliability levels and efficiency. Thus, here we provide the description of the most robust algorithms such as ROSE, imPROSE, and DEEPSEN and suggest their further use for various research and development tasks. The most promising research direction, which is based on topic and number of published studies, are cancer-associated super-enhancers and prospective SE-targeted therapy strategies, most of which are discussed in this review.

Clinically relevant fusion oncogenes: detection and practical implications

Mechanistically, chimeric genes result from DNA rearrangements and include parts of preexisting normal genes combined at the genomic junction site. Some rearranged genes encode pathological proteins with altered molecular functions. Those which can aberrantly promote carcinogenesis are called fusion oncogenes. Their formation is not a rare event in human cancers, and many of them were documented in numerous study reports and in specific databases. They may have various molecular peculiarities like increased stability of an oncogenic part, self-activation of tyrosine kinase receptor moiety, and altered transcriptional regulation activities. Currently, tens of low molecular mass inhibitors are approved in cancers as the drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins, that is, including ALK, ABL, EGFR, FGFR1-3, NTRK1-3, MET, RET, ROS1 moieties. Therein, the presence of the respective RTK fusion in the cancer genome is the diagnostic biomarker for drug prescription. However, identification of such fusion oncogenes is challenging as the breakpoint may arise in multiple sites within the gene, and the exact fusion partner is generally unknown. There is no gold standard method for RTK fusion detection, and many alternative experimental techniques are employed nowadays to solve this issue. Among them, RNA-seq-based methods offer an advantage of unbiased high-throughput analysis of only transcribed RTK fusion genes, and of simultaneous finding both fusion partners in a single RNA-seq read. Here we focus on current knowledge of biology and clinical aspects of RTK fusion genes, related databases, and laboratory detection methods.

Subtype of Neuroblastoma Cells with High KIT Expression Are Dependent on KIT and Its Knockdown Induces Compensatory Activation of Pro-Survival Signaling

Neuroblastoma (NB) is a pediatric cancer with high clinical and molecular heterogeneity, and patients with high-risk tumors have limited treatment options. Receptor tyrosine kinase KIT has been identified as a potential marker of high-risk NB and a promising target for NB treatment. We investigated 19,145 tumor RNA expression and molecular pathway activation profiles for 20 cancer types and detected relatively high levels of KIT expression in NB. Increased KIT expression was associated with activation of cell survival pathways, downregulated apoptosis induction, and cell cycle checkpoint control pathways. KIT knockdown with shRNA encoded by lentiviral vectors in SH-SY5Y cells led to reduced cell proliferation and apoptosis induction up to 50%. Our data suggest that apoptosis induction was caused by mitotic catastrophe, and there was a 2-fold decrease in percentage of G2-M cell cycle phase after KIT knockdown. We found that KIT knockdown in NB cells leads to strong upregulation of other pro-survival growth factor signaling cascades such as EPO, NGF, IL-6, and IGF-1 pathways. NGF, IGF-1 and EPO were able to increase cell proliferation in KIT-depleted cells in an ERK1/2-dependent manner. Overall, we show that KIT is a promising therapeutic target in NB, although such therapy efficiency could be impeded by growth factor signaling activation.

Mitochondria and Their Relationship with Common Genetic Abnormalities in Hematologic Malignancies

Hematologic malignancies are known to be associated with numerous cytogenetic and molecular genetic changes. In addition to morphology, immunophenotype, cytochemistry and clinical characteristics, these genetic alterations are typically required to diagnose myeloid, lymphoid, and plasma cell neoplasms. According to the current World Health Organization (WHO) Classification of Tumors of Hematopoietic and Lymphoid Tissues, numerous genetic changes are highlighted, often defining a distinct subtype of a disease, or providing prognostic information. This review highlights how these molecular changes can alter mitochondrial bioenergetics, cell death pathways, mitochondrial dynamics and potentially be related to mitochondrial genetic changes. A better understanding of these processes emphasizes potential novel therapies.

Growth factor signaling predicts therapy resistance mechanisms and defines neuroblastoma subtypes

Neuroblastoma (NB) has a low frequency of recurrent mutations compared to other cancers, which hinders the development of targeted therapies and novel risk stratification strategies. Multikinase inhibitors have shown potential in treating high-risk NB, but their efficacy is likely impaired by the cancer cells' ability to adapt to these drugs through the employment of alternative signaling pathways. Based on the expression of 48 growth factor-related genes in 1189 NB tumors, we have developed a model for NB patient survival prediction. This model discriminates between stage 4 NB tumors with favorable outcomes (>80% overall survival) and very poor outcomes (<10%) independently from MYCN-amplification status. Using signaling pathway analysis and gene set enrichment methods in 60 NB patients with known therapy response, we identified signaling pathways, including EPO, NGF, and HGF, upregulated in patients with no or partial response. In a therapeutic setting, we showed that among six selected growth factors, EPO, and NGF showed the most pronounced protective effects in vitro against several promising anti-NB multikinase inhibitors: imatinib, dasatinib, crizotinib, cabozantinib, and axitinib. Mechanistically kinase inhibitors potentiated NB cells to stronger ERK activation by EPO and NGF. The protective action of these growth factors strongly correlated with ERK activation and was ERK-dependent. ERK inhibitors combined with anticancer drugs, especially with dasatinib, showed a synergistic effect on NB cell death. Consideration of growth factor signaling activity benefits NB outcome prediction and tailoring therapy regimens to treat NB.

Gene Transcription as a Therapeutic Target in Leukemia

Blood malignancies often arise from undifferentiated hematopoietic stem cells or partially differentiated stem-like cells. A tight balance of multipotency and differentiation, cell division, and quiescence underlying normal hematopoiesis requires a special program governed by the transcriptional machinery. Acquisition of drug resistance by tumor cells also involves reprogramming of their transcriptional landscape. Limiting tumor cell plasticity by disabling reprogramming of the gene transcription is a promising strategy for improvement of treatment outcomes. Herein, we review the molecular mechanisms of action of transcription-targeted drugs in hematological malignancies (largely in leukemia) with particular respect to the results of clinical trials.

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.

The Role of the MCTS1 and DENR Proteins in Regulating the Mechanisms Associated with Malignant Cell Transformation

The mutations associated with malignant cell transformation are believed to disrupt the expression of a significant number of normal, non-mutant genes. The proteins encoded by these genes are involved in the regulation of many signaling pathways that are responsible for differentiation and proliferation, as well as sensitivity to apoptotic signals, growth factors, and cytokines. Abnormalities in the balance of signaling pathways can lead to the transformation of a normal cell, which results in tumor formation. Detection of the target genes and the proteins they encode and that are involved in the malignant transformation is one of the major evolutions in anti-cancer biomedicine. Currently, there is an accumulation of data that shed light on the role of the MCTS1 and DENR proteins in oncogenesis.

OGP46 Induces Differentiation of Acute Myeloid Leukemia Cells via Different Optimal Signaling Pathways

Acute myelogenous leukemia (AML) is characterized by blockage of cell differentiation leading to the accumulation of immature cells, which is the most prevalent form of acute leukemia in adults. It is well known that all-trans retinoic acid (ATRA) and arsenic trioxide (ATO) are the preferred drugs for acute promyelocytic leukemia (APL). However, they can lead to irreversible resistance which may be responsible for clinical failure after complete remission (CR). Moreover, the differentiation therapy of ATRA-based treatment has not been effective against AML with t(8;21) translocation. Here we aimed to identify the differentiation effect of OGP46 on AML cell lines (HL-60, NB4, and Kasumi-1) and explore its possible mechanisms. We found that OGP46 has significant inhibitory activity against these cells by triggering cell differentiation with cell-cycle exit at G1/G0 and inhibited the colony-formation capacity of the AML cells. It was shown that OGP46 induced the differentiation of NB4 cells via the transcriptional misregulation in cancer signaling pathway by PML-RARα depletion, while it was attributed to the hematopoietic cell lineage and phagosome pathway in Kasumi-1 cells, which are all critical pathways in cell differentiation. These results highlight that OGP46 is an active agent not only in the APL cell line NB4 but also in AML-M2 cell lines, especially Kasumi-1 with t(8;21) translocation. Therefore, OGP46 may be a potential compound for surmounting the differentiation blockage in AML.

MicroRNA let-7b downregulates AML1-ETO oncogene expression in t(8;21) AML by targeting its 3'UTR

Background

Acute myeloid leukemia (AML) with the t(8;21)(q22;q22) chromosomal translocation is among the most common subtypes of AML and produces the AML1-ETO (RUNX1-ETO, RUNX1-RUNX1T1) oncogenic fusion gene. AML1-ETO functions as an aberrant transcription factor which plays a key role in blocking normal hematopoiesis. Thus, the expression of AML1-ETO is critical to t(8;21) AML leukemogenesis and maintenance. Post-transcriptional regulation of gene expression is often mediated through interactions between trans-factors and cis-elements within transcript 3′-untranslated regions (UTR). AML1-ETO uses the 3′UTR of the ETO gene, which is not normally expressed in hematopoietic cells. Therefore, the mechanisms regulating AML1-ETO expression via the 3’UTR are attractive therapeutic targets.

Methods

We used RNA-sequencing of t(8;21) patients and cell lines to examine the 3′UTR isoforms used by AML1-ETO transcripts. Using luciferase assay approaches, we test the relative contribution of 3′UTR cis elements to AML1-ETO expression. We further use let-7b microRNA mimics and anti-let-7b sponges for functional studies of t(8;21) AML cell lines.

Results

In this study, we examine the regulation of AML1-ETO via the 3’UTR. We demonstrate that AML1-ETO transcripts primarily use a 3.7 kb isoform of the ETO 3′UTR in both t(8;21) patients and cell lines. We identify a negative regulatory element within the AML1-ETO 3′UTR. We further demonstrate that the let-7b microRNA directly represses AML1-ETO through this site. Finally, we find that let-7b inhibits the proliferation of t(8;21) AML cell lines, rescues expression of AML1-ETO target genes, and promotes differentiation.

Conclusions

AML1-ETO is post-transcriptionally regulated by let-7b, which contributes to the leukemic phenotype of t(8;21) AML and may be important for t(8;21) leukemogenesis and maintenance.

RUNX1/RUNX1T1 mediates alternative splicing and reorganises the transcriptional landscape in leukemia

The fusion oncogene RUNX1/RUNX1T1 encodes an aberrant transcription factor, which plays a key role in the initiation and maintenance of acute myeloid leukemia. Here we show that the RUNX1/RUNX1T1 oncogene is a regulator of alternative RNA splicing in leukemic cells. The comprehensive analysis of RUNX1/RUNX1T1-associated splicing events identifies two principal mechanisms that underlie the differential production of RNA isoforms: (i) RUNX1/RUNX1T1-mediated regulation of alternative transcription start site selection, and (ii) direct or indirect control of the expression of genes encoding splicing factors. The first mechanism leads to the expression of RNA isoforms with alternative structure of the 5'-UTR regions. The second mechanism generates alternative transcripts with new junctions between internal cassettes and constitutive exons. We also show that RUNX1/RUNX1T1-mediated differential splicing affects several functional groups of genes and produces proteins with unique conserved domain structures. In summary, this study reveals alternative splicing as an important component of transcriptome re-organization in leukemia by an aberrant transcriptional regulator.

Definition of a small core transcriptional circuit regulated by AML1-ETO

Transcription factors regulate gene networks controlling normal hematopoiesis and are frequently deregulated in acute myeloid leukemia (AML). Critical to our understanding of the mechanism of cellular transformation by oncogenic transcription factors is the ability to define their direct gene targets. However, gene network cascades can change within minutes to hours, making it difficult to distinguish direct from secondary or compensatory transcriptional changes by traditional methodologies. To overcome this limitation, we devised cell models in which the AML1-ETO protein could be quickly degraded upon addition of a small molecule. The rapid kinetics of AML1-ETO removal, when combined with analysis of transcriptional output by nascent transcript analysis and genome-wide AML1-ETO binding by CUT&RUN, enabled the identification of direct gene targets that constitute a core AML1-ETO regulatory network. Moreover, derepression of this gene network was associated with RUNX1 DNA binding and triggered a transcription cascade ultimately resulting in myeloid differentiation.

Molecular heterogeneity in breast carcinoma cells with increased invasive capacities

Background Metastatic progression of breast cancer is still a challenge in clinical oncology. Therefore, an elucidation how carcinoma cells belonging to different breast cancer subtypes realize their metastatic capacities is needed. The aim of this study was to elucidate a similarity of activated molecular pathways underlying an enhancement of invasiveness of carcinoma cells belonging to different breast carcinoma subtypes. Materials and methods In order to reach this aim, parental and invasive (INV) MDA-MB-231 (triple-negative), T47D (hormone receptor-positive), and Au565 (Her2-positive) breast carcinoma cells were used and their molecular phenotypes were compared using a proteomic approach. Results Independently from breast cancer subtypes, INV cells have demonstrated fibroblast-like morphology accompanied by enhancement of invasive and migratory capacities, increased expression of cancer stem cell markers, and delayed tumor growth in in vivo animal models. However, the global proteomic analysis has highlighted that INV cells were different in protein expressions from the parental cells, and Her2-positive Au565-INV cells showed the most pronounced molecular differences compared to the triple-negative MDA-MB-231-INV and hormone receptor-positive T47D-INV cells. Although Au565-INV breast carcinoma cells possessed the highest number of deregulated proteins, they had the lowest overlapping in proteins commonly expressed in MDA-MB-231-INV and T47D-INV cells. Conclusions We can conclude that hormone receptor-positive cells with increased invasiveness acquire the molecular characteristics of triple-negative breast cancer cells, whereas Her2-positive INV cells specifically changed their own molecular phenotype with very limited partaking in the involved pathways found in the MDA-MB-231-INV and T47D-INV cells. Since hormone receptor-positive invasive cells share their molecular properties with triple-negative breast cancer cells, we assume that these types of metastatic disease can be treated rather equally with an option to add anti-hormonal agents. In contrast, Her2-positive metastasis should be carefully evaluated for more effective therapeutic approaches which are distinct from the triple-negative and hormone-positive metastatic breast cancers.

Quantitation of Molecular Pathway Activation Using RNA Sequencing Data

Intracellular molecular pathways (IMPs) control all major events in the living cell. IMPs are considered hotspots in biomedical sciences and thousands of IMPs have been discovered for humans and model organisms. Knowledge of IMPs activation is essential for understanding biological functions and differences between the biological objects at the molecular level. Here we describe the Oncobox system for accurate quantitative scoring activities of up to several thousand molecular pathways based on high throughput molecular data. Although initially designed for gene expression and mainly RNA sequencing data, Oncobox is now also applicable for quantitative proteomics, microRNA and transcription factor binding sites mapping data. The Oncobox system includes modules of gene expression data harmonization, aggregation and comparison and a recursive algorithm for automatic annotation of molecular pathways. The universal rationale of Oncobox enables scoring of signaling, metabolic, cytoskeleton, immunity, DNA repair, and other pathways in a multitude of biological objects. The Oncobox system can be helpful to all those working in the fields of genetics, biochemistry, interactomics, and big data analytics in molecular biomedicine.

TAF1 plays a critical role in AML1-ETO driven leukemogenesis

AML1-ETO (AE) is a fusion transcription factor, generated by the t(8;21) translocation, that functions as a leukemia promoting oncogene. Here, we demonstrate that TATA-Box Binding Protein Associated Factor 1 (TAF1) associates with K43 acetylated AE and this association plays a pivotal role in the proliferation of AE-expressing acute myeloid leukemia (AML) cells. ChIP-sequencing indicates significant overlap of the TAF1 and AE binding sites. Knockdown of TAF1 alters the association of AE with chromatin, affecting of the expression of genes that are activated or repressed by AE. Furthermore, TAF1 is required for leukemic cell self-renewal and its reduction promotes the differentiation and apoptosis of AE+ AML cells, thereby impairing AE driven leukemogenesis. Together, our findings reveal a role of TAF1 in leukemogenesis and identify TAF1 as a potential therapeutic target for AE-expressing leukemia.

TAF1 plays a critical role in AML1-ETO driven leukemogenesis

AML1-ETO (AE) is a fusion transcription factor, generated by the t(8;21) translocation, that functions as a leukemia promoting oncogene. Here, we demonstrate that TATA-Box Binding Protein Associated Factor 1 (TAF1) associates with K43 acetylated AE and this association plays a pivotal role in the proliferation of AE-expressing acute myeloid leukemia (AML) cells. ChIP-sequencing indicates significant overlap of the TAF1 and AE binding sites. Knockdown of TAF1 alters the association of AE with chromatin, affecting of the expression of genes that are activated or repressed by AE. Furthermore, TAF1 is required for leukemic cell self-renewal and its reduction promotes the differentiation and apoptosis of AE+ AML cells, thereby impairing AE driven leukemogenesis. Together, our findings reveal a role of TAF1 in leukemogenesis and identify TAF1 as a potential therapeutic target for AE-expressing leukemia.

AML1-ETO is a fusion protein in which acetylation of lysine-43 is critical to leukemogenesis. Here, they show that TAF1 is required for AML1-ETO mediated gene expression such that it binds to acetylated AML1-ETO to facilitate the association of AML1-ETO with chromatin, and consequently, promotes leukemic self-renewal.

Two Receptors, Two Isoforms, Two Cancers: Comprehensive Analysis of KIT and TrkA Expression in Neuroblastoma and Acute Myeloid Leukemia

Pediatric cancers represent a wide variety of different tumors, though they have unique features that distinguish them from adult cancers. Receptor tyrosine kinases KIT and TrkA functions in AML and NB, respectively, are well-characterized. Though expression of these receptors is found in both tumors, little is known about KIT function in NB and TrkA in AML. By combining gene enrichment analysis with multidimensional scaling we showed that pediatric AMLs with t(8;21) or inv16 and high KIT expression levels stand out from other AML subtypes as they share prominent transcriptomic features exclusively with KIT-overexpressing NBs. We showed that AML cell lines had a predominant expression of an alternative TrkAIII isoform, which reportedly has oncogenic features, while NB cell lines had dominating TrkAI-II isoforms. NB cells, on the other hand, had an abnormal ratio of KIT isoforms as opposed to AML cells. Both SCF and NGF exerted protective action against doxorubicin and cytarabine for t(8;21) AML and NB cells. We identified several gene sets both unique and common for pediatric AML and NB, and this expression is associated with KIT or TrkA levels. NMU, DUSP4, RET, SUSD5, NOS1, and GABRA5 genes are differentially expressed in NBs with high KIT expression and are associated with poor survival in NB. We identified HOXA10, BAG3, and MARCKS genes that are connected with TrkA expression and are marker genes of poor outcome in AML. We also report that SLC18A2, PLXNC1, and MRPL33 gene expression is associated with TrkA or KIT expression levels in both AML and NB, and these genes have a prognostic value for both cancers. Thus, we have provided a comprehensive characterization of TrkA and KIT expression along with the oncogenic signatures of these genes across two pediatric tumors.

RNA sequencing for research and diagnostics in clinical oncology

Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted therapies. The analysis of RNA expression (transcriptomic) profiles presents a reasonable solution because transcriptomics stands a few steps closer to tumor phenotype than the genome analysis. Several recent studies pioneered using transcriptomics for practical oncology and showed truly encouraging clinical results. The possibility of directly measuring of expression levels of molecular drugs' targets and profiling activation of the relevant molecular pathways enables personalized prioritizing for all types of molecular-targeted therapies. RNA sequencing is the most robust tool for the high throughput quantitative transcriptomics. Its use, potentials, and limitations for the clinical oncology will be reviewed here along with the technical aspects such as optimal types of biosamples, RNA sequencing profile normalization, quality controls and several levels of data analysis.

Selective inhibition of Aurora A and B kinases effectively induces cell cycle arrest in t(8;21) acute myeloid leukemia

The fusion gene AML1-ETO initially dysregulates various cell cycle molecules in t(8;21) acute myeloid leukemia. Aurora kinases have shown great promise in treating tumors. However, the efficacy of Aurora kinase (AURK) A and B inhibition in t(8;21) AML remains unclear. We found that AURK-A inhibitor Alisertib and AURK-B inhibitor Barasertib strongly inhibited the growth and proliferation of t(8;21) AML cells. The quantity and size of cell colonies were markedly decreased after a 14-d drug exposure. The cell cycle distribution was blocked at the G2/M phase in both dose- and time-dependent manner. The expression of p53 family and cdc2-p34 significantly changed as well. Notably, we found that t(8;21) AML cells are more sensitive to Aurora B inhibition. In each set of experiments, Barasertib took less time or a lower concentration to achieve similar efficacy. Taken together, our data highlighted the potential role of Aurora kinases as promising cell cycle targets for the treatment of t(8;21) AML and hereby provided a theoretical basis to guide relevant clinical trials.

Oridonin inhibits LPS-induced inflammation in human gingival fibroblasts by activating PPARγ

Oridonin, the major terpene isolated from Rabdosia rubescens, has been used as dietary supplement. Recently, it has been known to exhibit anti-inflammatory effect. This study we employed an in vitro model of LPS-stimulated human gingival fibroblasts to investigate the anti-inflammatory effects and mechanism of oridonin. Oridonin (10-30 μg/mL) was administrated 1 h before LPS treatment. The results showed that oridonin significantly inhibited inflammatory mediators PGE₂, NO, IL-6, and IL-8 production. Immunoblotting experiments revealed that oridonin reduced the expression of phosphorylation levels of NF-κB p65 and IκBα. Furthermore, the expression of PPARγ was up-regulated by the treatment of oridonin. Further studies showed that PPARγ inhibitor GW9662 could reverse the inhibition of oridonin on PGE₂, NO, IL-6, and IL-8 production. In conclusion, oridonin inhibited LPS-induced microglia activation through activating PPARγ.

Elucidation of Novel Therapeutic Targets for Acute Myeloid Leukemias with RUNX1-RUNX1T1 Fusion

The RUNX1-RUNX1T1 fusion is a frequent chromosomal alteration in acute myeloid leukemias (AMLs). Although RUNX1-RUNX1T1 fusion protein has pivotal roles in the development of AMLs with the fusion, RUNX1-RUNX1T1, fusion protein is difficult to target, as it lacks kinase activities. Here, we used bioinformatic tools to elucidate targetable signaling pathways in AMLs with RUNX1-RUNX1T1 fusion. After analysis of 93 AML cases from The Cancer Genome Atlas (TCGA) database, we found expression of 293 genes that correlated to the expression of the RUNX1-RUNX1T1 fusion gene. Based on these 293 genes, the cyclooxygenase (COX), vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), and fibroblast growth factor receptor (FGFR) pathways were predicted to be specifically activated in AMLs with RUNX1-RUNX1T1 fusion. Moreover, the in vitro proliferation of AML cells with RUNX1-RUNX1T1 fusion decreased significantly more than that of AML cells without the fusion, when the pathways were inhibited pharmacologically. The results indicate that novel targetable signaling pathways could be identified by the analysis of the gene expression features of AMLs with non-targetable genetic alterations. The elucidation of specific molecular targets for AMLs that have a specific genetic alteration would promote personalized treatment of AMLs and improve clinical outcomes.

Anticancer Activity of the Goat Antimicrobial Peptide ChMAP-28

Cytotoxic effect of the antimicrobial peptide ChMAP-28 from leucocytes of the goat Capra hircus was examined against five cancer and two normal human cell lines. ChMAP-28 has the amino acid sequence GRFKRFRKKLKRLWHKVGPFVGPILHY and is homologous to other α-helical mammalian antimicrobial peptides. ChMAP-28 shows considerably higher cytotoxicity against cultured tumor cells than toward normal cells at concentrations of <10 μM. Our findings suggest that ChMAP-28 can initiate necrotic death of cancer cells. Its cytotoxic effect is accomplished due to disruption of the plasma membrane integrity and is not abrogated by the addition of the caspase inhibitor Z-VAD-FMK. ChMAP-28 causes permeabilization of cytoplasmic membrane of human leukemia cells HL-60 already after 15 min of incubation. Here, we show that ChMAP-28 has one of the highest antitumor activity in vitro among all known antimicrobial peptides. We speculate that the observed specificity of ChMAP-28 cytotoxic effect against tumor cells is due to its relatively low hydrophobicity and high cationicity. In the meantime, this peptide has low hemolytic activity, which generates a potential for its use as a therapeutic agent.

Oncobox Bioinformatical Platform for Selecting Potentially Effective Combinations of Target Cancer Drugs Using High-Throughput Gene Expression Data

Sequential courses of anticancer target therapy lead to selection of drug-resistant cells, which results in continuous decrease of clinical response. Here we present a new approach for predicting effective combinations of target drugs, which act in a synergistic manner. Synergistic combinations of drugs may prevent or postpone acquired resistance, thus increasing treatment efficiency. We cultured human ovarian carcinoma SKOV-3 and neuroblastoma NGP-127 cancer cell lines in the presence of Tyrosine Kinase Inhibitors (Pazopanib, Sorafenib, and Sunitinib) and Rapalogues (Temsirolimus and Everolimus) for four months and obtained cell lines demonstrating increased drug resistance. We investigated gene expression profiles of intact and resistant cells by microarrays and analyzed alterations in 378 cancer-related signaling pathways using the bioinformatical platform Oncobox. This revealed numerous pathways linked with development of drug resistant phenotypes. Our approach is based on targeting proteins involved in as many as possible signaling pathways upregulated in resistant cells. We tested 13 combinations of drugs and/or selective inhibitors predicted by Oncobox and 10 random combinations. Synergy scores for Oncobox predictions were significantly higher than for randomly selected drug combinations. Thus, the proposed approach significantly outperforms random selection of drugs and can be adopted to enhance discovery of new synergistic combinations of anticancer target drugs.

Large-scale profiling of signalling pathways reveals an asthma specific signature in bronchial smooth muscle cells

Background

Bronchial smooth muscle (BSM) cells from asthmatic patients maintain in vitro a distinct hyper-reactive (“primed”) phenotype, characterized by increased release of pro-inflammatory factors and mediators, as well as hyperplasia and/or hypertrophy. This “primed” phenotype helps to understand pathogenesis of asthma, as changes in BSM function are essential for manifestation of allergic and inflammatory responses and airway wall remodelling.

Objective

To identify signalling pathways in cultured primary BSMs of asthma patients and non-asthmatic subjects by genome wide profiling of differentially expressed mRNAs and activated intracellular signalling pathways (ISPs).

Methods

Transcriptome profiling by cap-analysis-of-gene-expression (CAGE), which permits selection of preferentially capped mRNAs most likely to be translated into proteins, was performed in human BSM cells from asthmatic (n=8) and non-asthmatic (n=6) subjects and OncoFinder tool were then exploited for identification of ISP deregulations.

Results

CAGE revealed >600 RNAs differentially expressed in asthma vs control cells (p≤0.005), with asthma samples showing a high degree of similarity among them. Comprehensive ISP activation analysis revealed that among 269 pathways analysed, 145 (p<0.05) or 103 (p<0.01) are differentially active in asthma, with profiles that clearly characterize BSM cells of asthmatic individuals. Notably, we identified 7 clusters of coherently acting pathways functionally related to the disease, with ISPs down-regulated in asthma mostly targeting cell death-promoting pathways and up-regulated ones affecting cell growth and proliferation, inflammatory response, control of smooth muscle contraction and hypoxia-related signalization.

Conclusions

These first-time results can now be exploited toward development of novel therapeutic strategies targeting ISP signatures linked to asthma pathophysiology.

The anti-tumorigenic activity of A2M-A lesson from the naked mole-rat

Cancer resistance is a major cause for longevity of the naked mole-rat. Recent liver transcriptome analysis in this animal compared to wild-derived mice revealed higher expression of alpha2-macroglobulin (A2M) and cell adhesion molecules, which contribute to the naked mole-rat’s cancer resistance. Notably, A2M is known to dramatically decrease with age in humans. We hypothesize that this might facilitate tumour development. Here we found that A2M modulates tumour cell adhesion, migration and growth by inhibition of tumour promoting signalling pathways, e.g. PI3K / AKT, SMAD and up-regulated PTEN via down-regulation of miR-21, in vitro and in tumour xenografts. A2M increases the expression of CD29 and CD44 but did not evoke EMT. Transcriptome analysis of A2M-treated tumour cells, xenografts and mouse liver demonstrated a multifaceted regulation of tumour promoting signalling pathways indicating a less tumorigenic environment mediated by A2M. By virtue of these multiple actions the naturally occurring A2M has strong potential as a novel therapeutic agent.

Acquired resistance to tyrosine kinase inhibitors may be linked with the decreased sensitivity to X-ray irradiation

Acquired resistance to chemotherapy and radiation therapy is one of the major obstacles decreasing efficiency of treatment of the oncologic diseases. In this study, on the two cell lines (ovarian carcinoma SKOV-3 and neuroblastoma NGP-127), we modeled acquired resistance to five target anticancer drugs. The cells were grown on gradually increasing concentrations of the clinically relevant tyrosine kinase inhibitors (TKIs) Sorafenib, Pazopanib and Sunitinib, and rapalogs Everolimus and Temsirolimus, for 20 weeks. After 20 weeks of culturing, the half-inhibitory concentrations (IC₅₀) increased by 25 – 186% for the particular combinations of the drugs and cell types. We next subjected cells to 10 Gy irradiation, a dose frequently used in clinical radiation therapy. For the SKOV-3, but not NGP-127 cells, for the TKIs Sorafenib, Pazopanib and Sunitinib, we noticed statistically significant increase in capacity to repair radiation-induced DNA double strand breaks compared to naïve control cells not previously treated with TKIs. These peculiarities were linked with the increased activation of ATM DNA repair pathway in the TKI-treated SKOV-3, but not NGP-127 cells. Our results provide a new cell culture model for studying anti-cancer therapy efficiency and evidence that there may be a tissue-specific radioresistance emerging as a side effect of treatment with TKIs.

The Hematopoietic Transcription Factors RUNX1 and ERG Prevent AML1-ETO Oncogene Overexpression and Onset of the Apoptosis Program in t(8;21) AMLs

The t(8;21) acute myeloid leukemia (AML)-associated oncoprotein AML1-ETO disrupts normal hematopoietic differentiation. Here, we have investigated its effects on the transcriptome and epigenome in t(8,21) patient cells. AML1-ETO binding was found at promoter regions of active genes with high levels of histone acetylation but also at distal elements characterized by low acetylation levels and binding of the hematopoietic transcription factors LYL1 and LMO2. In contrast, ERG, FLI1, TAL1, and RUNX1 bind at all AML1-ETO-occupied regulatory regions, including those of the AML1-ETO gene itself, suggesting their involvement in regulating AML1-ETO expression levels. While expression of AML1-ETO in myeloid differentiated induced pluripotent stem cells (iPSCs) induces leukemic characteristics, overexpression increases cell death. We find that expression of wild-type transcription factors RUNX1 and ERG in AML is required to prevent this oncogene overexpression. Together our results show that the interplay of the epigenome and transcription factors prevents apoptosis in t(8;21) AML cells.

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.

Gene expression and molecular pathway activation signatures of MYCN-amplified neuroblastomas

Neuroblastoma is a pediatric cancer arising from sympathetic nervous system. Remarkable heterogeneity in outcomes is one of its widely known features. One of the traits strongly associated with the unfavorable subtype is the amplification of oncogene MYCN. Here, we performed cross-platform biomarker detection by comparing gene expression and pathway activation patterns from the two literature reports and from our experimental dataset, combining profiles for the 761 neuroblastoma patients with known MYCN amplification status. We identified 109 / 25 gene expression / pathway activation biomarkers strongly linked with the MYCN amplification. The marker genes/pathways are involved in the processes of purine nucleotide biosynthesis, ATP-binding, tetrahydrofolate metabolism, building mitochondrial matrix, biosynthesis of amino acids, tRNA aminoacylation and NADP-linked oxidation-reduction processes, as well as in the tyrosine phosphatase activity, p53 signaling, cell cycle progression and the G1/S and G2/M checkpoints. To connect molecular functions of the genes involved in MYCN-amplified phenotype, we built a new molecular pathway using known intracellular protein interaction networks. The activation of this pathway was highly selective in discriminating MYCN-amplified neuroblastomas in all three datasets. Our data also suggest that the phosphoinositide 3-kinase (PI3K) inhibitors may provide new opportunities for the treatment of the MYCN-amplified neuroblastoma subtype.

Peptide microarray profiling identifies phospholipase C gamma 1 (PLC-γ1) as a potential target for t(8;21) AML

The t(8;21) (q22;q22) chromosomal translocation is one of the most frequent genetic alterations in acute myeloid leukemia (AML) which has a need for improved therapeutic strategies. We found PLC-γ1 as one of the highest phosphorylated peptides in t(8;21) AML samples compared to NBM or CN-AML in our previous peptide microarray. PLC-γ1 is known to play a role in cancer progression, however, the impact of PLC-γ1 in AML is currently unknown. Therefore, we aimed to study the functional role of PLC-γ1 by investigating the cellular growth, survival and its underlying mechanism in t(8;21) AML.

In this study, PLC-γ1 expression was significantly higher in t(8;21) AML compared to other karyotypes. The PLC-γ1 protein expression was suppressed in AML1-ETO knock down cells indicating that it might induce kasumi-1 cell death. ShRNA-mediated PLC-γ1 knockdown in kasumi-1 cells significantly blocked cell growth, induced apoptosis and cell cycle arrest which was explained by the increased activation of apoptotic related and cell cycle regulatory protein expressions. Gene expression array analysis showed the up-regulation of apoptotic and DNA damage response genes together with the downregulation of cell growth, proliferation and differentiation genes in the PLC-γ1 suppressed kasumi-1 cells, consistent with the observed phenotypic effects. Importantly, PLC-γ1 suppressed kasumi-1 cells showed higher chemosensitivity to the chemotherapeutic drug treatments and lower cell proliferation upon hypoxic stress.

Taken together, these in vitro finding strongly support an important role for PLC-γ1 in the survival of t(8;21) AML mimicking kasumi-1 cells and identify PLC-γ1 as a potential therapeutic target for t(8;21) AML treatment.

Synergistic suppression of t(8;21)-positive leukemia cell growth by combining oridonin and MAPK1/ERK2 inhibitors

One of the most common chromosomal translocations in acute myeloid leukemia is t(8;21)(q22;q22), which results in the appearance of abnormal transcripts encoding for the fusion protein RUNX1-ETO. Therefore, this oncoprotein is considered to be a pertinent and promising target for treating t(8;21) leukemia. Previously, we have shown that downregulation of RUNX1-ETO leads to activation of intracellular signaling pathways enhancing cell survival and determined that the protein ERK2 can mediate activation of most of these pathways. Here we used a combination of oridonin (natural tetracycline diterpenoid), which has been shown to exhibit anti-RUNX1-ETO activity, and ERK2 kinase inhibitors. We found that treatment of leukemic t(8;21)-positive Kasumi-1 cells with oridonin cause decrease of phosphorylated ERK1/2. Treatment of these cells with ERK2 inhibitors makes them more sensitive to RUNX1-ETO inhibition with oridonin. Therefore we postulate that simultaneous inhibition of RUNX1-ETO and ERK2 cause synergistic effect on survival of leukemic cells.

Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene Expression Data

We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantitative and qualitative analyses of the intracellular molecular pathway activation. OF utilizes an algorithm that distinguishes the activator/repressor role of every gene product in a pathway. This method is applicable for the analysis of any physiological, stress, malignancy, and other conditions at the molecular level. OF showed a strong potential to neutralize background-caused differences between experimental gene expression data obtained using NGS, microarray and modern proteomics techniques. Importantly, in most cases, pathway activation signatures were better markers of cancer progression compared to the individual gene products. OF also enables correlating pathway activation with the success of anticancer therapy for individual patients. We further expanded this approach to analyze impact of micro RNAs (miRs) on the regulation of cellular interactome. Many alternative sources provide information about miRs and their targets. However, instruments elucidating higher level impact of the established total miR profiles are still largely missing. A variant of OncoFinder termed MiRImpact enables linking miR expression data with its estimated outcome on the regulation of molecular processes, such as signaling, metabolic, cytoskeleton, and DNA repair pathways. MiRImpact was used to establish cancer-specific and cytomegaloviral infection-linked interactomic signatures for hundreds of molecular pathways. Interestingly, the impact of miRs appeared orthogonal to pathway regulation at the mRNA level, which stresses the importance of combining all available levels of gene regulation to build a more objective molecular model of cell.

Mathematical Justification of Expression-Based Pathway Activation Scoring (PAS)

Although modeling of activation kinetics for various cell signaling pathways has reached a high grade of sophistication and thoroughness, most such kinetic models still remain of rather limited practical value for biomedicine. Nevertheless, recent advancements have been made in application of signaling pathway science for real needs of prescription of the most effective drugs for individual patients. The methods for such prescription evaluate the degree of pathological changes in the signaling machinery based on two types of data: first, on the results of high-throughput gene expression profiling, and second, on the molecular pathway graphs that reflect interactions between the pathway members. For example, our algorithm OncoFinder evaluates the activation of molecular pathways on the basis of gene/protein expression data in the objects of the interest.Yet, the question of assessment of the relative importance for each gene product in a molecular pathway remains unclear unless one call for the methods of parameter sensitivity /stiffness analysis in the interactomic kinetic models of signaling pathway activation in terms of total concentrations of each gene product.Here we show two principal points: 1. First, the importance coefficients for each gene in pathways that were obtained using the extremely time- and labor-consuming stiffness analysis of full-scaled kinetic models generally differ from much easier-to-calculate expression-based pathway activation score (PAS) not more than by 30%, so the concept of PAS is kinetically justified. 2. Second, the use of pathway-based approach instead of distinct gene analysis, due to the law of large numbers, allows restoring the correlation between the similar samples that were examined using different transcriptome investigation techniques.

Early stage of cytomegalovirus infection suppresses host microRNA expression regulation in human fibroblasts

Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific. We investigated molecular profiles in 2 primary cell cultures of human fibroblasts, which are highly or marginally sensitive to HCMV infection, respectively. We screened expression of genes and microRNAs (miRs) at the early (3 hours) stage of infection. To assess molecular pathway activation profiles, we applied bioinformatic algorithms OncoFinder and MiRImpact. In both cell types, pathway regulation properties at mRNA and miR levels were markedly different. Surprisingly, in the infected highly sensitive cells, we observed a "freeze" of miR expression profiles compared to uninfected controls. Our results evidence that in the sensitive cells, HCMV blocks intracellular regulation of microRNA expression already at the earliest stage of infection. These data suggest somewhat new functions for HCMV products and demonstrate dependence of miR expression arrest on the host-encoded factors.

MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways

MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs - known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets – miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.

Molecular pathway activation features of pediatric acute myeloid leukemia (AML) and acute lymphoblast leukemia (ALL) cells

Acute lymphoblast leukemia (ALL) is characterized by overproduction of immature white blood cells in the bone marrow. ALL is most common in the childhood and has high (>80%) cure rate. In contrast, acute myeloid leukemia (AML) has far greater mortality rate than the ALL and is most commonly affecting older adults. However, AML is a leading cause of childhood cancer mortality. In this study, we compare gene expression and molecular pathway activation patterns in three normal blood, seven pediatric ALL and seven pediatric AML bone marrow samples. We identified 172/94 and 148/31 characteristic gene expression/pathway activation signatures, clearly distinguishing pediatric ALL and AML cells, respectively, from the normal blood. The pediatric AML and ALL cells differed by 139/34 gene expression/pathway activation biomarkers. For the adult 30 AML and 17 normal blood samples, we found 132/33 gene expression/pathway AML-specific features, of which only 7/2 were common for the adult and pediatric AML and, therefore, age-independent. At the pathway level, we found more differences than similarities between the adult and pediatric forms. These findings suggest that the adult and pediatric AMLs may require different treatment strategies.

Molecular pathway activation features linked with transition from normal skin to primary and metastatic melanomas in human

Melanoma is the most aggressive and dangerous type of skin cancer, but its molecular mechanisms remain largely unclear. For transcriptomic data of 478 primary and metastatic melanoma, nevi and normal skin samples, we performed high-throughput analysis of intracellular molecular networks including 592 signaling and metabolic pathways. We showed that at the molecular pathway level, the formation of nevi largely resembles transition from normal skin to primary melanoma. Using a combination of bioinformatic machine learning algorithms, we identified 44 characteristic signaling and metabolic pathways connected with the formation of nevi, development of primary melanoma, and its metastases. We created a model describing formation and progression of melanoma at the level of molecular pathway activation. We discovered six novel associations between activation of metabolic molecular pathways and progression of melanoma: for allopregnanolone biosynthesis, L-carnitine biosynthesis, zymosterol biosynthesis (inhibited in melanoma), fructose 2, 6-bisphosphate synthesis and dephosphorylation, resolvin D biosynthesis (activated in melanoma), D-myo-inositol hexakisphosphate biosynthesis (activated in primary, inhibited in metastatic melanoma). Finally, we discovered fourteen tightly coordinated functional clusters of molecular pathways. This study helps to decode molecular mechanisms underlying the development of melanoma.

Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs

Effective choice of anticancer drugs is important problem of modern medicine. We developed a method termed OncoFinder for the analysis of new type of biomarkers reflecting activation of intracellular signaling and metabolic molecular pathways. These biomarkers may be linked with the sensitivity to anticancer drugs. In this study, we compared the experimental data obtained in our laboratory and in the Genomics of Drug Sensitivity in Cancer (GDS) project for testing response to anticancer drugs and transcriptomes of various human cell lines. The microarray-based profiling of transcriptomes was performed for the cell lines before the addition of drugs to the medium, and experimental growth inhibition curves were built for each drug, featuring characteristic IC₅₀ values. We assayed here four target drugs - Pazopanib, Sorafenib, Sunitinib and Temsirolimus, and 238 different cell lines, of which 11 were profiled in our laboratory and 227 - in GDS project. Using the OncoFinder-processed transcriptomic data on ∼600 molecular pathways, we identified pathways showing significant correlation between pathway activation strength (PAS) and IC₅₀ values for these drugs. Correlations reflect relationships between response to drug and pathway activation features. We intersected the results and found molecular pathways significantly correlated in both our assay and GDS project. For most of these pathways, we generated molecular models of their interaction with known molecular target(s) of the respective drugs. For the first time, our study uncovered mechanisms underlying cancer cell response to drugs at the high-throughput molecular interactomic level.

A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation

A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearson's correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.

Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data

Deep learning is rapidly advancing many areas of science and technology with multiple success stories in image, text, voice and video recognition, robotics, and autonomous driving. In this paper we demonstrate how deep neural networks (DNN) trained on large transcriptional response data sets can classify various drugs to therapeutic categories solely based on their transcriptional profiles. We used the perturbation samples of 678 drugs across A549, MCF-7, and PC-3 cell lines from the LINCS Project and linked those to 12 therapeutic use categories derived from MeSH. To train the DNN, we utilized both gene level transcriptomic data and transcriptomic data processed using a pathway activation scoring algorithm, for a pooled data set of samples perturbed with different concentrations of the drug for 6 and 24 hours. In both pathway and gene level classification, DNN achieved high classification accuracy and convincingly outperformed the support vector machine (SVM) model on every multiclass classification problem, however, models based on pathway level data performed significantly better. For the first time we demonstrate a deep learning neural net trained on transcriptomic data to recognize pharmacological properties of multiple drugs across different biological systems and conditions. We also propose using deep neural net confusion matrices for drug repositioning. This work is a proof of principle for applying deep learning to drug discovery and development.

Celastrol Induces Cell Apoptosis and Inhibits the Expression of the AML1-ETO/C-KIT Oncoprotein in t(8;21) Leukemia

Resistance to chemotherapy is a major challenge to improving overall survival in Acute Myeloid Leukemia (AML). Therefore, the development of innovative therapies and the identification of more novel agents for AML are urgently needed. Celastrol, a compound extracted from the Chinese herb Tripterygium wilfordii Hook, exerts anticancer activity. We investigated the effect of celastrol in the t(8;21) AML cell lines Kasumi-1 and SKNO-1. We demonstrated that inhibition of cell proliferation activated caspases and disrupted mitochondrial function. In addition, we found that celastrol downregulated the AML1-ETO fusion protein, therefore downregulating C-KIT kinases and inhibiting AKT, STAT3 and Erk1/2. These findings provide clear evidence that celastrol might provide clinical benefits to patients with t(8;21) leukemia.

Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways

We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer. Using Illumina HT12v4 microarrays, we profiled gene expression in 17 cancer and seven non-cancerous bladder tissue samples. These experiments were done in two independent laboratories located in Russia and Canada. We calculated pathway activation strength values for the investigated transcriptomes and identified signaling pathways that were regulated differently in bladder cancer (BC) tissues compared with normal controls. We found, for both experimental datasets, 44 signaling pathways that serve as excellent new biomarkers of BC, supported by high area under the curve (AUC) values. We conclude that the OncoFinder approach is highly efficient in finding new biomarkers for cancer. These markers are mathematical functions involving multiple gene products, which distinguishes them from “traditional” expression biomarkers that only assess concentrations of single genes.