Using 40 known human-specific LTR sequences, we have derived a consensus sequence for an evolutionary young HERV-K (HML-2) LTR family, which was named the HS family. In the human genome the HS family is represented by approximately 150-160 LTR sequences, 90% of them being human-specific (hs). The family can be subdivided into two subfamilies differing in five linked nucleotide substitutions: HS-a and HS-b of 5.8 and 10.3 Myr evolutionary ages, respectively. The HS-b subfamily members were transpositionally active both before the divergence of the human and chimpanzee ancestor lineages and after it in both lineages. The HS-a subfamily comprises only hs LTRs. These and other data strongly suggest that at least three "master genes" of HERV-K (HML-2) LTRs were active in the human ancestor lineage after the human-chimpanzee divergence. We also found hs HERV-K (HML-2) LTRs integrations in introns of 12 human genes and identified 13 new hs HERV-K (HML-2) LTRs.

Age-related macular degeneration (AMD) is a major cause of blindness in older people and is caused by loss of the central region of the retinal pigment epithelium (RPE). Conventional methods of gene expression analysis have yielded important insights into AMD pathogenesis, but the precise molecular pathway alterations are still poorly understood. Therefore we developed a new software program, "AMD Medicine", and discovered differential pathway activation profiles in samples of human RPE/choroid from AMD patients and controls. We identified 29 pathways in RPE-choroid AMD phenotypes: 27 pathways were activated in AMD compared to controls, and 2 pathways were activated in controls compared to AMD. In AMD, we identified a graded activation of pathways related to wound response, complement cascade, and cell survival. Also, there was downregulation of two pathways responsible for apoptosis. Furthermore, significant activation of pro-mitotic pathways is consistent with dedifferentiation and cell proliferation events, which occur early in the pathogenesis of AMD. Significantly, we discovered new global pathway activation signatures of AMD involved in the cell-based inflammatory response: IL-2, STAT3, and ERK. The ultimate aim of our research is to achieve a better understanding of signaling pathways involved in AMD pathology, which will eventually lead to better treatments.

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

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.

Interferons (IFNs) are critical determinants in immune-competence and autoimmunity, and are endogenously regulated by a low-level constitutive feedback loop. However, little is known about the functions and origins of constitutive IFN. Recently, lipopolysaccharide (LPS)-induced IFN was implicated as a driver of necroptosis, a necrotic form of cell death downstream of receptor-interacting protein (RIP) kinase activation and executed by mixed lineage kinase like-domain (MLKL) protein. We found that the pre-established IFN status of the cell, instead of LPS-induced IFN, is critical for the early initiation of necroptosis in macrophages. This pre-established IFN signature stems from cytosolic DNA sensing via cGAS/STING, and maintains the expression of MLKL and one or more unknown effectors above a critical threshold to allow for MLKL oligomerization and cell death. Finally, we found that elevated IFN-signaling in systemic lupus erythematosus (SLE) augments necroptosis, providing a link between pathological IFN and tissue damage during autoimmunity.

Over the last few years, incidental thyroid nodules are being diagnosed with increasing frequency with the use of highly sensitive imaging techniques. The ultrasound thyroid gland examination, followed by the fine-needle aspiration cytology is the standard diagnostic approach. However, in cases of the follicular nature of nodules, cytological diagnosis is not enough. Analysis of miRNAs in the biopsy presents a promising approach. Increasing our knowledge of miRNA's role in follicular carcinogenesis, and development of the appropriate the miRNA analytical technologies are required to implement miRNA-based tests in clinical practice. We used material from follicular thyroid nodes (n.84), grouped in accordance with their invasive properties. The invasion-associated miRNAs expression alterations were assayed. Expression data were confirmed by highly sensitive two-tailed RT-qPCR. Reciprocally dysregulated miRNAs pair concentration ratios were explored as a diagnostic parameter using receiver operation curve (ROC) analysis. A new bioinformatics method (MiRImpact) was applied to evaluate the biological significance of the observed expression alterations. Coupled experimental and computational approaches identified reciprocal dysregulation of miR-146b and miR-451 as important attributes of follicular cell malignant transformation and follicular thyroid cancer progression. Thus, evaluation of combined dysregulation of miRNAs relevant to invasion and metastasis can help to distinguish truly malignant follicular thyroid cancer from indolent follicular adenoma.

Machine learning (ML) methods still have limited applicability in personalized oncology due to low numbers of available clinically annotated molecular profiles. This doesn't allow sufficient training of ML classifiers that could be used for improving molecular diagnostics.

Background: Inevitable recurrence after radiochemotherapy is the major problem in the treatment of glioblastoma, the most prevalent type of adult brain malignancy. Glioblastomas are notorious for a high degree of intratumor heterogeneity manifest through a diversity of cell types and molecular patterns. The current paradigm of understanding glioblastoma recurrence is that cytotoxic therapy fails to target effectively glioma stem cells. Recent advances indicate that therapy-driven molecular evolution is a fundamental trait associated with glioblastoma recurrence. There is a growing body of evidence indicating that intratumor heterogeneity, longitudinal changes in molecular biomarkers and specific impacts of glioma stem cells need to be taken into consideration in order to increase the accuracy of molecular diagnostics still relying on readouts obtained from a single tumor specimen. Methods: This study integrates a multisampling strategy, longitudinal approach and complementary transcriptomic investigations in order to identify transcriptomic traits of recurrent glioblastoma in whole-tissue specimens of glioblastoma or glioblastoma stem cells. In this study, 128 tissue samples of 44 tumors including 23 first diagnosed, 19 recurrent and 2 secondary recurrent glioblastomas were analyzed along with 27 primary cultures of glioblastoma stem cells by RNA sequencing. A novel algorithm was used to quantify longitudinal changes in pathway activities and model efficacy of anti-cancer drugs based on gene expression data. Results: Our study reveals that intratumor heterogeneity of gene expression patterns is a fundamental characteristic of not only newly diagnosed but also recurrent glioblastomas. Evidence is provided that glioblastoma stem cells recapitulate intratumor heterogeneity, longitudinal transcriptomic changes and drug sensitivity patterns associated with the state of recurrence. Conclusions: Our results provide a transcriptional rationale for the lack of significant therapeutic benefit from temozolomide in patients with recurrent glioblastoma. Our findings imply that the spectrum of potentially effective drugs is likely to differ between newly diagnosed and recurrent glioblastomas and underscore the merits of glioblastoma stem cells as prognostic models for identifying alternative drugs and predicting drug response in recurrent glioblastoma. With the majority of recurrent glioblastomas being inoperable, glioblastoma stem cell models provide the means of compensating for the limited availability of recurrent glioblastoma specimens.

The tumor-associated ganglioside GD2 represents an attractive target for cancer immunotherapy. GD2-positive tumors are more responsive to such targeted therapy, and new methods are needed for the screening of GD2 molecular tumor phenotypes. In this work, we built a gene expression-based binary classifier predicting the GD2-positive tumor phenotypes. To this end, we compared RNA sequencing data from human tumor biopsy material from experimental samples and public databases as well as from GD2-positive and GD2-negative cancer cell lines, for expression levels of genes encoding enzymes involved in ganglioside biosynthesis. We identified a 2-gene expression signature combining ganglioside synthase genes ST8SIA1 and B4GALNT1 that serves as a more efficient predictor of GD2-positive phenotype (Matthews Correlation Coefficient (MCC) 0.32, 0.88, and 0.98 in three independent comparisons) compared to the individual ganglioside biosynthesis genes (MCC 0.02-0.32, 0.1-0.75, and 0.04-1 for the same independent comparisons). No individual gene showed a higher MCC score than the expression signature MCC score in two or more comparisons. Our diagnostic approach can hopefully be applied for pan-cancer prediction of GD2 phenotypes using gene expression data.

Current methods of high-throughput molecular and genomic analyses enabled to reconstruct thousands of human molecular pathways. Knowledge of molecular pathways structure and architecture taken along with the gene expression data can help interrogating the pathway activation levels (PALs) using different bioinformatic algorithms. In turn, the pathway activation profiles can characterize molecular processes, which are differentially regulated and give numeric characteristics of the extent of their activation or inhibition. However, different pathway nodes may have different functions toward overall pathway regulation, and calculation of PAL requires knowledge of molecular function of every node in the pathway in terms of its activator or inhibitory role. Thus, high-throughput annotation of functional roles of pathway nodes is required for the comprehensive analysis of the pathway activation profiles. We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. The resulting knowledgebase can be applied for the direct calculation of the PALs and establishing large scale profiles of the signaling, metabolic, and DNA repair pathway regulation using high throughput gene expression data. We also provide a bioinformatic tool for PAL data calculations using the current pathway knowledgebase.

DNA repair can prevent mutations and cancer development, but it can also restore damaged tumor cells after chemo and radiation therapy. We performed RNA sequencing on 95 human pathological thyroid biosamples including 17 follicular adenomas, 23 follicular cancers, 3 medullar cancers, 51 papillary cancers and 1 poorly differentiated cancer. The gene expression profiles are annotated here with the clinical and histological diagnoses and, for papillary cancers, with BRAF gene V600E mutation status. DNA repair molecular pathway analysis showed strongly upregulated pathway activation levels for most of the differential pathways in the papillary cancer and moderately upregulated pattern in the follicular cancer, when compared to the follicular adenomas. This was observed for the BRCA1, ATM, p53, excision repair, and mismatch repair pathways. This finding was validated using independent thyroid tumor expression dataset PRJEB11591. We also analyzed gene expression patterns linked with the radioiodine resistant thyroid tumors (n = 13) and identified 871 differential genes that according to Gene Ontology analysis formed two functional groups: (i) response to topologically incorrect protein and (ii) aldo-keto reductase (NADP) activity. We also found RNA sequencing reads for two hybrid transcripts: one in-frame fusion for well-known NCOA4-RET translocation, and another frameshift fusion of ALK oncogene with a new partner ARHGAP12. The latter could probably support increased expression of truncated ALK downstream from 4th exon out of 28. Both fusions were found in papillary thyroid cancers of follicular histologic subtype with node metastases, one of them (NCOA4-RET) for the radioactive iodine resistant tumor. The differences in DNA repair activation patterns may help to improve therapy of different thyroid cancer types under investigation and the data communicated may serve for finding additional markers of radioiodine resistance.

Trastuzumab, a HER2-targeted antibody, is widely used for targeted therapy of HER2-positive breast cancer (BC) patients; yet, not all of them respond to this treatment. We investigated here whether trastuzumab activity on the growth of HER2-overexpressing BT474 cells may interfere with human peripheral blood endogenous factors. Among 33 individual BC patient blood samples supplemented to the media, BT474 sensitivity to trastuzumab varied up to 14 times. In the absence of trastuzumab, human peripheral blood serum samples could inhibit growth of BT474, and this effect varied ~10 times for 50 individual samples. In turn, the epidermal growth factor (EGF) suppressed the trastuzumab effect on BT474 cell growth. Trastuzumab treatment increased the proportion of BT474 cells in the G0/G1 phases of cell cycle, while simultaneous addition of EGF decreased it, yet not to the control level. We used RNA sequencing profiling of gene expression to elucidate the molecular mechanisms involved in EGF- and human-sera-mediated attenuation of the trastuzumab effect on BT474 cell growth. Bioinformatic analysis of the molecular profiles suggested that trastuzumab acts similarly to the inhibition of PI3K/Akt/mTOR signaling axis, and the mechanism of EGF suppression of trastuzumab activity may be associated with parallel activation of PKC and transcriptional factors ETV1-ETV5.

Tissue specific promoters may be utilized for a variety of applications, including programmed gene expression in cell types, tissues and organs of interest, for developing different cell culture models or for use in gene therapy. We report a novel, tissue-specific promoter that was identified and engineered from the native upstream regulatory region of the human gene NDUFV1 containing an endogenous retroviral sequence.

Harmonization techniques make different gene expression profiles and their sets compatible and ready for comparisons. Here we present a new bioinformatic tool termed Shambhala for harmonization of multiple human gene expression datasets obtained using different experimental methods and platforms of microarray hybridization and RNA sequencing.

For the past several decades, research in understanding the molecular basis of human aging has progressed significantly with the analysis of premature aging syndromes. Progerin, an altered form of lamin A, has been identified as the cause of premature aging in Hutchinson-Gilford Progeria Syndrome (HGPS), and may be a contributing causative factor in normal aging. However, the question of whether HGPS actually recapitulates the normal aging process at the cellular and organismal level, or simply mimics the aging phenotype is widely debated. In the present study we analyzed publicly available microarray datasets for fibroblasts undergoing cellular aging in culture, as well as fibroblasts derived from young, middle-age, and old-age individuals, and patients with HGPS. Using GeroScope pathway analysis and drug discovery platform we analyzed the activation states of 65 major cellular signaling pathways. Our analysis reveals that signaling pathway activation states in cells derived from chronologically young patients with HGPS strongly resemble cells taken from normal middle-aged and old individuals. This clearly indicates that HGPS may truly represent accelerated aging, rather than being just a simulacrum. Our data also points to potential pathways that could be targeted to develop drugs and drug combinations for both HGPS and normal aging.

Concomitant hepatocyte apoptosis and regeneration is a hallmark of chronic liver diseases (CLDs) predisposing to hepatocellular carcinoma (HCC). Here, we mechanistically link caspase-8-dependent apoptosis to HCC development via proliferation- and replication-associated DNA damage. Proliferation-associated replication stress, DNA damage, and genetic instability are detectable in CLDs before any neoplastic changes occur. Accumulated levels of hepatocyte apoptosis determine and predict subsequent hepatocarcinogenesis. Proliferation-associated DNA damage is sensed by a complex comprising caspase-8, FADD, c-FLIP, and a kinase-dependent function of RIPK1. This platform requires a non-apoptotic function of caspase-8, but no caspase-3 or caspase-8 cleavage. It may represent a DNA damage-sensing mechanism in hepatocytes that can act via JNK and subsequent phosphorylation of the histone variant H2AX.

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.

We developed a technique called GREM (Genomic Repeat Expression Monitor) that can be applied to genome-wide isolation and quantitative analysis of any kind of transcriptionally active repetitive elements. Briefly, the technique includes three major stages: (i) generation of a transcriptome wide library of cDNA 5' terminal fragments, (ii) selective amplification of repeat-flanking genomic loci and (iii) hybridization of the cDNA library (i) to the amplicon (ii) with subsequent selective amplification and cloning of the cDNA-genome hybrids. The sequences obtained serve as 'tags' for promoter active repetitive elements. The advantage of GREM is an unambiguous mapping of individual promoter active repeats at a genome-wide level. We applied GREM for genome-wide experimental identification of human-specific endogenous retroviruses and their solitary long terminal repeats (LTRs) acting in vivo as promoters. Importantly, GREM tag frequencies linearly correlated with the corresponding LTR-driven transcript levels found using RT-PCR. The GREM technique enabled us to identify 54 new functional human promoters created by retroviral LTRs.

Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94-1 for the experimental CRCs and 0.94-1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91-0.97, whereas the third signature showed a significantly lower AUC of 0.69-0.88. Software for calculating these MSI signatures using RNAseq data is included.

Hypofractionated radiotherapy is the mainstay of the current treatment for glioblastoma. However, the efficacy of radiotherapy is hindered by the high degree of radioresistance associated with glioma stem cells comprising a heterogeneous compartment of cell lineages differing in their phenotypic characteristics, molecular signatures, and biological responses to external signals. Reconstruction of radiation responses in glioma stem cells is necessary for understanding the biological and molecular determinants of glioblastoma radioresistance. To date, there is a paucity of information on the longitudinal outcomes of hypofractionated radiation in glioma stem cells. This study addresses long-term outcomes of hypofractionated radiation in human glioma stem cells by using a combinatorial approach integrating parallel assessments of the tumor-propagating capacity, stemness-associated properties, and array-based profiling of gene expression. The study reveals a broad spectrum of changes in the tumor-propagating capacity of glioma stem cells after radiation and finds association with proliferative changes at the onset of differentiation. Evidence is provided that parallel transcriptomic patterns and a cumulative impact of pathways involved in the regulation of apoptosis, neural differentiation, and cell proliferation underly similarities in tumorigenicity changes after radiation.