Retinoids and EZH2 inhibitors cooperate to orchestrate anti-oncogenic effects on bladder cancer cells.

The highly mutated nature of bladder cancers harboring mutations in chromatin regulatory genes opposing Polycomb-mediated repression highlights the importance of targeting EZH2 in bladder cancer. Furthermore, the critical role of the retinoic acid signaling pathway in the development and homeostasis of the urothelium, and the anti-oncogenic effects of retinoids are well established. Therefore, our aim is to simultaneously target EZH2 and retinoic acid signaling in bladder cancer to potentiate the therapeutic response. Here we report that this coordinated targeting strategy stimulates an anti-oncogenic profile, as reflected by inducing a synergistic reduction in cell viability that was associated with increased apoptosis and cell cycle arrest in a cooperative and orchestrated manner. This study characterized anti-oncogenic transcriptional reprogramming centered on the transcriptional regulator CHOP by stimulating the endoplasmic reticulum stress response. We further portrayed a molecular mechanism whereby EZH2 maintains H3K27me3-mediated repression of a subset of genes involved in unfolded protein responses, reflecting the molecular mechanism underlying this co-targeting strategy. These findings highlight the importance of co-targeting the EZH2 and retinoic acid pathway in bladder cancers and encourage the design of novel treatments employing retinoids coupled with EZH2 inhibitors in bladder carcinoma.

TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype and is associated with increased survival in cancer patients with high tumor macrophage content.

Background: TNF-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily that can either induce cell death or activate survival pathways after binding to death receptors (DRs) DR4 or DR5. TRAIL is investigated as a therapeutic agent in clinical trials due to its selective toxicity to transformed cells. Macrophages can be polarized into pro-inflammatory/tumor-fighting M1 macrophages or anti-inflammatory/tumor-supportive M2 macrophages and an imbalance between M1 and M2 macrophages can promote diseases. Therefore, identifying modulators that regulate macrophage polarization is important to design effective macrophage-targeted immunotherapies. The impact of TRAIL on macrophage polarization is not known. Methods: Primary human monocyte-derived macrophages were pre-treated with either TRAIL or with DR4 or DR5-specific ligands and then polarized into M1, M2a, or M2c phenotypes in vitro. The expression of M1 and M2 markers in macrophage subtypes was analyzed by RNA sequencing, qPCR, ELISA, and flow cytometry. Furthermore, the cytotoxicity of the macrophages against U937 AML tumor targets was assessed by flow cytometry. TCGA datasets were also analyzed to correlate TRAIL with M1/M2 markers, and the overall survival of cancer patients. Results: TRAIL increased the expression of M1 markers at both mRNA and protein levels while decreasing the expression of M2 markers at the mRNA level in human macrophages. TRAIL also shifted M2 macrophages towards an M1 phenotype. Our data showed that both DR4 and DR5 death receptors play a role in macrophage polarization. Furthermore, TRAIL enhanced the cytotoxicity of macrophages against the AML cancer cells in vitro. Finally, TRAIL expression was positively correlated with increased expression of M1 markers in the tumors from ovarian and sarcoma cancer patients and longer overall survival in cases with high, but not low, tumor macrophage content. Conclusions: TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype via both DR4 and DR5. Our study defines TRAIL as a new regulator of macrophage polarization and suggests that targeting DRs can enhance the anti-tumorigenic response of macrophages in the tumor microenvironment by increasing M1 polarization.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas.

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

Differential Occupancy and Regulatory Interactions of KDM6A in Bladder Cell Lines.

Epigenetic deregulation is a critical theme which needs further investigation in bladder cancer research. One of the most highly mutated genes in bladder cancer is KDM6A, which functions as an H3K27 demethylase and is one of the MLL3/4 complexes. To decipher the role of KDM6A in normal versus tumor settings, we identified the genomic landscape of KDM6A in normal, immortalized, and cancerous bladder cells. Our results showed differential KDM6A occupancy in the genes involved in cell differentiation, chromatin organization, and Notch signaling depending on the cell type and the mutation status of KDM6A. Transcription factor motif analysis revealed HES1 to be enriched at KDM6A peaks identified in the T24 bladder cancer cell line; moreover, it has a truncating mutation in KDM6A and lacks a demethylase domain. Our co-immunoprecipitation experiments revealed TLE co-repressors and HES1 as potential truncated and wild-type KDM6A interactors. With the aid of structural modeling, we explored how truncated KDM6A could interact with TLE and HES1, as well as RUNX and HHEX transcription factors. These structures provide a solid means of studying the functions of KDM6A independently of its demethylase activity. Collectively, our work provides important contributions to the understanding of KDM6A malfunction in bladder cancer.

"In the light of evolution:" keratins as exceptional tumor biomarkers.

Keratins (KRTs) are the intermediate filament-forming proteins of epithelial cells, classified, according to their physicochemical properties, into "soft" and "hard" keratins. They have a key role in several aspects of cancer pathophysiology, including cancer cell invasion and metastasis, and several members of the KRT family serve as diagnostic or prognostic markers. The human genome contains both, functional KRT genes and non-functional KRT pseudogenes, arranged in two uninterrupted clusters on chromosomes 12 and 17. This characteristic renders KRTs ideal for evolutionary studies. Herein, comprehensive phylogenetic analyses of KRT homologous proteins in the genomes of major taxonomic divisions were performed, so as to fill a gap in knowledge regarding the functional implications of keratins in cancer biology among tumor-bearing species. The differential expression profiles of KRTs in diverse types of cancers were investigated by analyzing high-throughput data, as well. Several KRT genes, including the phylogenetically conserved ones, were found to be deregulated across several cancer types and to participate in a common protein-protein interaction network. This indicates that, at least in cancer-bearing species, these genes might have been under similar evolutionary pressure, perhaps to support the same important function(s). In addition, semantic relations between KRTs and cancer were detected through extensive text mining. Therefore, by applying an integrative in silico pipeline, the evolutionary history of KRTs was reconstructed in the context of cancer, and the potential of using non-mammalian species as model organisms in functional studies on human cancer-associated KRT genes was uncovered.

FLI1 and FRA1 transcription factors drive the transcriptional regulatory networks characterizing muscle invasive bladder cancer.

Bladder cancer is mostly present in the form of urothelium carcinoma, causing over 150,000 deaths each year. Its histopathological classification as muscle invasive (MIBC) and non-muscle invasive (NMIBC) is the most prominent aspect, affecting the prognosis and progression of this disease. In this study, we defined the active regulatory landscape of MIBC and NMIBC cell lines using H3K27ac ChIP-seq and used an integrative approach to combine our findings with existing data. Our analysis revealed FRA1 and FLI1 as two critical transcription factors differentially regulating MIBC regulatory landscape. We show that FRA1 and FLI1 regulate the genes involved in epithelial cell migration and cell junction organization. Knock-down of FRA1 and FLI1 in MIBC revealed the downregulation of several EMT-related genes such as MAP4K4 and FLOT1. Further, ChIP-SICAP performed for FRA1 and FLI1 enabled us to infer chromatin binding partners of these transcription factors and link this information with their target genes. Finally, we show that knock-down of FRA1 and FLI1 result in significant reduction of invasion capacity of MIBC cells towards muscle microenvironment using IC-CHIP assays. Our results collectively highlight the role of these transcription factors in selection and design of targeted options for treatment of MIBC.

StemnesScoRe: an R package to estimate the stemness of glioma cancer cells at single-cell resolution.

Background/aim: Glioblastoma is the most heterogeneous and the most difficult-to-treat type of brain tumor and one of the deadliest among all cancers. The high plasticity of glioma cancer stem cells and the resistance they develop against multiple modalities of therapy, along with their high heterogeneity, are the main challenges faced during treatment of glioblastoma. Therefore, a better understanding of the stemness characteristics of glioblastoma cells is needed. With the development of various single-cell technologies and increasing applications of machine learning, indices based on transcriptomic and/or epigenomic data have been developed to quantitatively measure cellular states and stemness. In this study, we aimed to develop a glioma-specific stemness score model using scATAC-seq data for the first time. Materials and methods: We first applied three powerful machine-learning algorithms, i.e. random forest, gradient boosting, and extreme gradient boosting, to glioblastoma scRNA-seq data to discover the most important genes associated with cellular states. We then identified promoter and enhancer regions associated with these genes. After downloading the scATAC-seq peaks and their read counts for each patient, we identified the overlapping regions between the single-cell peaks and the peaks of genes obtained through machine-learning algorithms. Then we calculated read counts that were mapped to these overlapping regions. We finally developed a model capable of estimating the stemness score for each glioma cell using overlapping regions and the importance of genes predictive of glioblastoma cellular states. We also created an R package, accessible to all researchers regardless of their coding proficiency. Results: Our results showed that mesenchymal-like stem cells display higher stemness scores compared to neural-progenitor-, oligodendrocyte-progenitor-, and astrocyte-like cells. Conclusion: scATAC-seq can be used to assess heterogeneity in glioblastoma and identify cells with high stemness characteristics. The package is publicly available at https://github.com/Necla/StemnesScoRe and includes documentation with implementation of a real-data experiment.

Identification of neoplasm-specific signatures of miRNA interactions by employing a systems biology approach.

MicroRNAs represent major regulatory components of the disease epigenome and they constitute powerful biomarkers for the accurate diagnosis and prognosis of various diseases, including cancers. The advent of high-throughput technologies facilitated the generation of a vast amount of miRNA-cancer association data. Computational approaches have been utilized widely to effectively analyze and interpret these data towards the identification of miRNA signatures for diverse types of cancers. Herein, a novel computational workflow was applied to discover core sets of miRNA interactions for the major groups of neoplastic diseases by employing network-based methods. To this end, miRNA-cancer association data from four comprehensive publicly available resources were utilized for constructing miRNA-centered networks for each major group of neoplasms. The corresponding miRNA-miRNA interactions were inferred based on shared functionally related target genes. The topological attributes of the generated networks were investigated in order to detect clusters of highly interconnected miRNAs that form core modules in each network. Those modules that exhibited the highest degree of mutual exclusivity were selected from each graph. In this way, neoplasm-specific miRNA modules were identified that could represent potential signatures for the corresponding diseases.

Repeat expression is linked to patient survival and exhibits single nucleotide variation in pancreatic cancer revealing LTR70:r.879A>G.

Despite an overwhelming number of cancer literature reporting the links between patient survival and the expression levels of genes or mutations/single nucleotide variations (SNVs) on them, there is only limited information on repeat elements, which make at least half the human genome. Here, we analysed RNA-seq data obtained from primary pancreatic cancer tissues of 51 patients and revealed that two transposons, HERVI-int and X6A_LINE, showed an upregulation trend in the patients who lived shorter, along with 56 other potential repeats which were linked to survival. We also detected expressed single nucleotide variations (SNVs) on repeats, among which LTR70:r.879A>G stands out with the effect of its presence on this particular repeat's expression levels and a significant link to overall patient survival. Interestingly, the expression of LTR70:r.879A>G correlated with different cancer genes in comparison to its reference version highlighting the involvement of BRAF and Fumerate Hydratase with this expressed SNV. This is one of the first studies revealing possible links between repeat expression and survival in cancer and it warrants further research in this avenue.

Evaluation of ATAD2 as a Potential Target in Hepatocellular Carcinoma.

PURPOSE: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide with lack of effective systemic chemotherapy. In this study, we aimed to evaluate the value of ATPase family AAA domain-containing protein 2 (ATAD2) as a biomarker and potential therapeutic target for HCC. METHODS: The expression of ATAD2 was tested in different HCC patient cohorts by immunohistochemistry and comparative transcriptional analysis. The co-expression of ATAD2 and proliferation markers was compared during liver regeneration and malignancy with different bioinformatics tools. The cellular effects of ATAD2 inactivation in liver malignancy was tested on cell cycle, apoptosis, and colony formation ability as well as tumor formation using RNA interference. The genes affected by ATAD2 inactivation in three different HCC cell lines were identified by global gene expression profiling and bioinformatics tools. RESULTS: ATAD2 overexpression is closely correlated with HCC tumor stage. There was gradual increase from dysplasia, well-differentiated and poorly-differentiated HCC, respectively. We also observed transient upregulation of ATAD2 expression during rat liver regeneration in parallel to changes in Ki-67 expression. ATAD2 knockdown resulted in apoptosis and decreased cell survival in vitro and decreased tumor formation in some HCC cell lines. However, three other HCC cell lines tested were not affected. Similarly, gene expression response to ATAD2 inactivation in different HCC cell lines was highly heterogeneous. CONCLUSIONS: ATAD2 is a potential proliferation marker for liver regeneration and HCC. It may also serve as a therapeutic target despite heterogeneous response of malignant cells.

Identification of differentially expressed genomic repeats in primary hepatocellular carcinoma and their potential links to biological processes and survival.

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. Research on HCC so far primarily focused on genes and provided limited information on genomic repeats, which constitute more than half of the human genome and contribute to genomic stability. In line with this, repeat dysregulation was significantly shown to be pathological in various cancers and other diseases. In this study, we aimed to determine the full repeat expression profile of HCC for the first time. We utilised two independent RNA-seq datasets obtained from primary HCC tumours with matched normal tissues of 20 and 17 HCC patients, respectively. We quantified repeat expressions and analysed their differential expression. We also identified repeats that are cooperatively expressed with genes by constructing a gene coexpression network. Our results indicated that HCC tumours in both datasets harbour 24 differentially expressed repeats and even more elements were coexpressed with genes involved in various metabolic pathways. We discovered that two L1 elements (L1M3b, L1M3de) were downregulated and a handful of HERV subfamily repeats (HERV-Fc1-int, HERV3-int, HERVE_a-int, HERVK11D-int, HERVK14C-int, HERVL18-int) were upregulated with the exception of HERV1_LTRc, which was downregulated. Various LTR elements (LTR32, LTR9, LTR4, LTR52-int, LTR70) and MER elements (MER11C, MER11D, MER57C1, MER9a1, MER74C) were implicated along with few other subtypes including Charlie12, MLT2A2, Tigger15a, Tigger 17b. The only satellite repeat differentially expressed in both datasets was GSATII, whose expression was upregulated in 33 (>90%) out of 37 patients. Notably, GSATII expression correlated with HCC survival genes. Elements discovered here promise future studies to be considered for biomarker and HCC therapy research. The coexpression pattern of the GSATII satellite with HCC survival genes and the fact that it has been upregulated in the vast majority of patients make this repeat particularly stand out for HCC.

In Silico Methods for the Identification of Diagnostic and Favorable Prognostic Markers in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML), the most common type of acute leukemia in adults, is mainly asymptomatic at early stages and progresses/recurs rapidly and frequently. These attributes necessitate the identification of biomarkers for timely diagnosis and accurate prognosis. In this study, differential gene expression analysis was performed on large-scale transcriptomics data of AML patients versus corresponding normal tissue. Weighted gene co-expression network analysis was conducted to construct networks of co-expressed genes, and detect gene modules. Finally, hub genes were identified from selected modules by applying network-based methods. This robust and integrative bioinformatics approach revealed a set of twenty-four genes, mainly related to cell cycle and immune response, the diagnostic significance of which was subsequently compared against two independent gene expression datasets. Furthermore, based on a recent notion suggesting that molecular characteristics of a few, unusual patients with exceptionally favorable survival can provide insights for improving the outcome of individuals with more typical disease trajectories, we defined groups of long-term survivors in AML patient cohorts and compared their transcriptomes versus the general population to infer favorable prognostic signatures. These findings could have potential applications in the clinical setting, in particular, in diagnosis and prognosis of AML.

Mining Natural Products with Anticancer Biological Activity through a Systems Biology Approach.

Natural products, like turmeric, are considered powerful antioxidants which exhibit tumor-inhibiting activity and chemoradioprotective properties. Nowadays, there is a great demand for developing novel, affordable, efficacious, and effective anticancer drugs from natural resources. In the present study, we have employed a stringent in silico methodology to mine and finally propose a number of natural products, retrieved from the biomedical literature. Our main target was the systematic search of anticancer products as anticancer agents compatible to the human organism for future use. In this case and due to the great plethora of such products, we have followed stringent bioinformatics methodologies. Our results taken together suggest that natural products of a great diverse may exert cytotoxic effects in a maximum of the studied cancer cell lines. These natural compounds and active ingredients could possibly be combined to exert potential chemopreventive effects. Furthermore, in order to substantiate our findings and their application potency at a systems biology level, we have developed a representative, user-friendly, publicly accessible biodatabase, NaturaProDB, containing the retrieved natural resources, their active ingredients/fractional mixtures, the types of cancers that they affect, and the corresponding experimentally verified target genes.

Investigating Molecular Determinants of Cancer Cell Resistance to Ionizing Radiation Through an Integrative Bioinformatics Approach.

Eradication of cancer cells through exposure to high doses of ionizing radiation (IR) is a widely used therapeutic strategy in the clinical setting. However, in many cases, cancer cells can develop remarkable resistance to radiation. Radioresistance represents a prominent obstacle in the effective treatment of cancer. Therefore, elucidation of the molecular mechanisms and pathways related to radioresistance in cancer cells is of paramount importance. In the present study, an integrative bioinformatics approach was applied to three publicly available RNA sequencing and microarray transcriptome datasets of human cancer cells of different tissue origins treated with ionizing radiation. These data were investigated in order to identify genes with a significantly altered expression between radioresistant and corresponding radiosensitive cancer cells. Through rigorous statistical and biological analyses, 36 genes were identified as potential biomarkers of radioresistance. These genes, which are primarily implicated in DNA damage repair, oxidative stress, cell pro-survival, and apoptotic pathways, could serve as potential diagnostic/prognostic markers cancer cell resistance to radiation treatment, as well as for therapy outcome and cancer patient survival. In addition, our findings could be potentially utilized in the laboratory and clinical setting for enhancing cancer cell susceptibility to radiation therapy protocols.

TAp73ß Can Promote Hepatocellular Carcinoma Dedifferentiation.

Hepatocyte dedifferentiation is a major source of hepatocellular carcinoma (HCC), but its mechanisms are unknown. We explored the p73 expression in HCC tumors and studied the effects of transcriptionally active p73ß (TAp73ß) in HCC cells. Expression profiles of p73 and patient clinical data were collected from the Genomic Data Commons (GDC) data portal and the TSVdb database, respectively. Global gene expression profiles were determined by pan-genomic 54K microarrays. The Gene Set Enrichment Analysis method was used to identify TAp73ß-regulated gene sets. The effects of TAp73 isoforms were analyzed in monolayer cell culture, 3D-cell culture and xenograft models in zebrafish using western blot, flow cytometry, fluorescence imaging, real-time polymerase chain reaction (RT-PCR), immunohistochemistry and morphological examination. TAp73 isoforms were significantly upregulated in HCC, and high p73 expression correlated with poor patient survival. The induced expression of TAp73ß caused landscape expression changes in genes involved in growth signaling, cell cycle, stress response, immunity, metabolism and development. Hep3B cells overexpressing TAp73ß had lost hepatocyte lineage biomarkers including ALB, CYP3A4, AFP, HNF4α. In contrast, TAp73ß upregulated genes promoting cholangiocyte lineage such as YAP, JAG1 and ZO-1, accompanied with an increase in metastatic ability. Our findings suggest that TAp73ß may promote malignant dedifferentiation of HCC cells.

Differential expression of full-length and NH2 terminally truncated FAM134B isoforms in normal physiology and cancer.

Selective autophagy of the endoplasmic reticulum (ER), namely ER-phagy, is mediated by ER-localized receptors, which are recognized and sequestered by GABARAP/LC3B-decorated phagophores and transferred to lysosomes for degradation. Being one such receptor, FAM134B plays critical roles in cellular processes such as protein quality control and neuronal survival. FAM134B has also been associated with different cancers, although its exact role remains elusive. We report here that the FAM134B gene encodes not one but at least two different protein isoforms: the full-length and the NH2 terminally truncated forms. Their relative expression shows extreme variation, both within normal tissues and among cancer types. Expression of full-length FAM134B is restricted to the brain, testis, spleen, and prostate. In contrast, NH2 terminally truncated FAM134B is dominant in the heart, skeletal muscle, kidney, pancreas, and liver. We compared wild-type and knockout mice to study the role of the Fam134b gene in starvation. NH2 terminally truncated FAM134B-2 was induced in the liver, skeletal muscle, and heart but not in the pancreas and stomach following starvation. Upon starvation, Fam134b-/- mice differed from wild-type mice by less weight loss and less hyperaminoacidemic and hypocalcemic response but increased levels of serum albumin, total serum proteins, and α-amylase. Interestingly, either NH2 terminally truncated FAM134B or both isoforms were downregulated in liver, lung, and colon cancers. In contrast, upregulation was observed in stomach and chromophobe kidney cancers.NEW & NOTEWORTHY We reported tissues expressing FAM134B-2 such as the kidney, muscle, heart, and pancreas, some of which exhibit stimulated expression upon nutrient starvation. We also demonstrated the effect of Fam134b deletion during ad libitum and starvation conditions. Resistance to weight loss and hypocalcemia, accompanied by an increase in serum albumin and α-amylase levels, indicate critical roles of Fam134b in physiology. Furthermore, the differential expression of FAM134B isoforms was shown to be significantly dysregulated in human cancers.

Analysis of open chromatin regions in bladder cancer links ß-catenin mutations and Wnt signaling with neuronal subtype of bladder cancer.

Urothelial carcinoma of the bladder is the most frequent bladder cancer affecting more than 400,000 people each year. Histopathologically, it is mainly characterized as muscle invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer (NMIBC). Recently, the studies largely driven by consortiums such as TCGA identified the mutational landscape of both MIBC and NMIBC and determined the molecular subtypes of bladder cancer. Because of the exceptionally high rate of mutations in chromatin proteins, bladder cancer is thought to be a disease of chromatin, pointing out to the importance of studying epigenetic deregulation and the regulatory landscape of this cancer. In this study, we have analyzed ATAC-seq data generated for MIBC and integrated our findings with gene expression and DNA methylation data to identify subgroup specific regulatory patterns for MIBC. Our computational analysis revealed three MIBC regulatory clusters, which we named as neuronal, non-neuronal and luminal outlier. We have identified target genes of neuronal regulatory elements to be involved in WNT signaling, while target genes of non-neuronal and luminal outlier regulatory regions were enriched in epithelial differentiation and drug metabolism, respectively. Neuronal regulatory elements were determined to be ß-catenin targets (p value = 3.59e-08) consisting of genes involved in neurogenesis such as FGF9, and PROX1, and significantly enriched for TCF/LEF binding sites (p value = 1e-584). Our results showed upregulation of ß-catenin targets regulated by neuronal regulatory elements in three different cohorts, implicating ß-catenin signature in neuronal bladder cancer. Further, integration with mutation data revealed significantly higher oncogenic exon 3 ß-catenin mutations in neuronal bladder cancer compared to non-neuronal (odds ratio = 31.33, p value = 1.786e-05). Our results for the first time identify regulatory elements characterizing neuronal bladder cancer and links these neuronal regulatory elements with WNT signaling via mutations in ß-catenin and its destruction complex components.

TEffectR: an R package for studying the potential effects of transposable elements on gene expression with linear regression model.

INTRODUCTION: Recent studies highlight the crucial regulatory roles of transposable elements (TEs) on proximal gene expression in distinct biological contexts such as disease and development. However, computational tools extracting potential TE -proximal gene expression associations from RNA-sequencing data are still missing. IMPLEMENTATION: Herein, we developed a novel R package, using a linear regression model, for studying the potential influence of TE species on proximal gene expression from a given RNA-sequencing data set. Our R package, namely TEffectR, makes use of publicly available RepeatMasker TE and Ensembl gene annotations as well as several functions of other R-packages. It calculates total read counts of TEs from sorted and indexed genome aligned BAM files provided by the user, and determines statistically significant relations between TE expression and the transcription of nearby genes under diverse biological conditions. AVAILABILITY: TEffectR is freely available at https://github.com/karakulahg/TEffectR along with a handy tutorial as exemplified by the analysis of RNA-sequencing data including normal and tumour tissue specimens obtained from breast cancer patients.

Dysregulated expression of repetitive DNA in ER+/HER2- breast cancer.

Limited studies on breast cancer indicated pathogenic changes in the expressions of some repeat elements. A global analysis was much needed within this context to distinguish the most significant repeats from more than a thousand repeat motifs. Utilising a previously presented RNA-seq dataset, we studied expression changes of all repeats in ER+/HER2- human breast tumour samples obtained from 22 patients in comparison to matched normal tissues. Fifty six (56) repeat subtypes including satellites and transposons were found to be differentially expressed and most of them were novel for breast cancer. HERVKC4-int and HERV1_LTRc, whose expressions correlated well with that of the estrogen receptor gene ESR1, were upregulated at the highest level. REP522 and D20S16 satellites were also significantly upregulated along with insignificant increases in the expressions of other satellites including HSATI and BSR/beta. Interestingly, expressions of REP522 and D20S16 correlated with many key breast cancer pathway (e.g. BRCA1, BRCA2, AKT1, MTOR, KRAS) and survival genes; possibly highlighting their importance in the carcinogenesis of breast. Additional differentially expressed elements such as L1P and various MER transposons also exhibited a similar pattern. Finally, our repeat enrichment analysis on the promoters of differentially expressed genes revealed further links between additional repeats and nearby genes.

Inflammatory markers C-reactive protein and PLR in relation to HCC characteristics.

INTRODUCTION: Several markers of systemic inflammation, including blood C-reactive protein, platelet lymphocyte ratio (PLR) and neutrophil lymphocyte ratio (NLR) have been identified as independent prognosticators for hepatocellular carcinoma (HCC). METHODS: To attempt to understand the significance of these markers, they were examined in relation to 4 tumour parameters, namely maximum tumour diameter (MTD), tumour multifocality, portal vein thrombosis (PVT) and blood alpha-fetoprotein (AFP) levels. RESULTS: Using linear and logistic regression models, we found that C-reactive protein and PLR on single variables, were statistically significantly related to the tumour parameters. In a logistic regression final model, CRP was significantly related to MTD, AFP and PVT, and the Glasgow Index significantly related to MTD and AFP. Results of the area under the receiver operating characteristic curves (ROC), showed that the areas for PLR and CRP were statistically significant for high versus low MTD and for presence versus absence of PVT. CRP alone was significant for high versus low AFP. CONCLUSIONS: These analyses suggest that the prognostic usefulness of the inflammatory markers PLR and CRP (but not NLR) may be due to their reflection of parameter values for tumour growth and invasiveness.