PATH-01. SMALL RNASEQ ANALYSIS OF MICRORNAS IN BRAIN METASTASIS

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi115-vi115
Author(s):  
Radim Jancalek ◽  
Frantisek Siegl ◽  
Jiri Sana ◽  
Marek Vecera ◽  
Karolina Trachtova ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Expression Patterns ◽  
Predictive Biomarkers ◽  
Unknown Origin ◽  
Bioinformatic Analysis ◽  
Cdna Libraries ◽  
Sequencing Data ◽  
Aberrant Expression ◽  
Mirna Profiling ◽  
Small Rnaseq

Abstract MicroRNAs (miRNAs) are a well-known subclass of short non-coding RNAs responsible for posttranscriptional gene silencing and have been described as dysregulated in many cancers. They have also been shown to be both specific diagnostic, prognostic, and predictive biomarkers as well as therapeutic targets. Therefore, specific miRNA expression patterns of BMs of various origins could serve as a promising diagnostic tool for determining both the original tumor and the prognosis in patients with BMs of unknown origin. For identifying significantly dysregulated miRNAs among BMs (n=90) with various origin and non-tumor brain tissues (n=12), small RNAseq analyses were used. cDNA libraries were prepared using QIAseq miRNA Library Kit and purified by Qiaseq beads. The final sequencing analyses were performed by Next 500/550 High Output v2 Kit-75 cycles using the NextSeq 500 instrument. For miRNA mapping and analysis, Miraligner and MirBase were used. Bioinformatic analysis of obtained sequencing data identified 472 significantly dysregulated miRNAs (logFc >2, adj.p-value< 0.05) between BM and non-tumor samples. The comparison of BMs origin from lung BMs (n = 26) with other BMs revealed 132 significantly dysregulated miRNAs, mainly miR-4662a-5p, miR-1179, miR-211-5p, miR-146a-5p, and miR-194-5p. The most significantly dysregulated miRNAs in breast BMs were miR-4728-3p, miR-211-5p, miR-184, miR-365b-5p, and miR-2115-3p. In BMs originating from melanoma, miR-200c-3p, miR-141-5p, miR-200b-5p, miR-514a-3p, and miR-200b-3p showed the most aberrant expression. We have demonstrated that miRNA profiling could be a potent tool for the partition of brain metastases based on their origin. We found that miRNA signatures corresponding to particular origins are rather distinct from the profiles of the rest of BMs. Our results suggest that after validation, miRNA profiling can be used to identify the origin of brain metastases and potentially for the refinement of the diagnosis. Supported by the Ministry of Health of the Czech Republic, grant nr. NV18-03-00398.

scholarly journals BSCI-01. Small RNAseq analysis of microRNAs in brain metastasis

2021 ◽  
Vol 3 (Supplement_3) ◽  
pp. iii1-iii1
Author(s):  
Radim Jancalek ◽  
Frantisek Siegl ◽  
Jiri Sana ◽  
Simona Sidorova ◽  
Marek Vecera ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Expression Patterns ◽  
Predictive Biomarkers ◽  
Unknown Origin ◽  
Bioinformatic Analysis ◽  
Cdna Libraries ◽  
Sequencing Data ◽  
Aberrant Expression ◽  
Mirna Profiling ◽  
Small Rnaseq

Abstract MicroRNAs (miRNAs) are a well-known subclass of short non-coding RNAs responsible for posttranscriptional gene silencing and have been described as dysregulated in many cancers. They have also been shown to be both specific diagnostic, prognostic, and predictive biomarkers as well as therapeutic targets. Therefore, specific miRNA expression patterns of BMs of various origins could serve as a promising diagnostic tool for determining both the original tumor and the prognosis in patients with BMs of unknown origin. For identifying significantly dysregulated miRNAs among BMs (n = 90) with various origin and non-tumor brain tissues (n = 12), small RNAseq analyses were used. cDNA libraries were prepared using QIAseq miRNA Library Kit and purified by Qiaseq beads. The final sequencing analyses were performed by Next 500/550 High Output v2 Kit-75 cycles using the NextSeq 500 instrument. For miRNA mapping and analysis, Miraligner and MirBase were used. Bioinformatic analysis of obtained sequencing data identified 472 significantly dysregulated miRNAs (logFc>2, adj.p-value<0.05) between BM and non-tumor samples. The comparison of BMs origin from lung BMs (n = 26) with other BMs revealed 132 significantly dysregulated miRNAs, mainly miR-4662a-5p, miR-1179, miR-211-5p, miR-146a-5p, and miR-194-5p. The most significantly dysregulated miRNAs in breast BMs were miR-4728-3p, miR-211-5p, miR-184, miR-365b-5p, and miR-2115-3p. In BMs originating from melanoma, miR-200c-3p, miR-141-5p, miR-200b-5p, miR-514a-3p, and miR-200b-3p showed the most aberrant expression. We have demonstrated that miRNA profiling could be a potent tool for the partition of brain metastases based on their origin. We found that miRNA signatures corresponding to particular origins are rather distinct from the profiles of the rest of BMs. Our results suggest that after validation, miRNA profiling can be used to identify the origin of brain metastases and potentially for the refinement of the diagnosis. Supported by the Ministry of Health of the Czech Republic, grant nr. NV18-03-00398.

Kallikrein-related peptidases (KLKs) in gastrointestinal cancer: Mechanistic and clinical aspects

2013 ◽  
Vol 110 (09) ◽  
pp. 450-457 ◽  
Author(s):  
Christos K. Kontos ◽  
Konstantinos Mavridis ◽  
Maroulio Talieri ◽  
Andreas Scorilas
Keyword(s):  
Esophageal Cancer ◽  
Gastrointestinal Cancer ◽  
Growth Regulation ◽  
Clinical Decision Making ◽  
Expression Patterns ◽  
Predictive Biomarkers ◽  
Current Status ◽  
Clinical Aspects ◽  
Aberrant Expression ◽  
Gastrointestinal Malignancies

SummaryThe human tissue kallikrein (KLK1) and kallikrein-related peptidases (KLKs) are secreted serine proteases with diverse expression patterns and physiological roles in different systems, including the digestive system. The aberrant expression of KLKs in gastrointestinal malignancies as well as their implication in carcinogenesis including cell growth regulation, angiogenesis, invasion, and metastasis, has prompted scientists to investigate their potential as cancer biomarkers. Expression of distinct KLKs is associated with various clinic-pathological parameters of patients with gastric, colorectal, pancreatic, hepatic, and esophageal cancer. Moreover, several KLKs possess significant favourable or unfavourable prognostic value in these human malignancies. Identification of novel diagnostic, prognostic and predictive biomarkers will contribute utmost to clinical decision-making, since early diagnosis of gastrointestinal cancer and early detection of recurrence following surgery are critical for the effective treatment of patients and for a positive clinical outcome. The current review provides a brief overview of the functional role of KLKs in gastric, colorectal, pancreatic, hepatic, and esophageal cancer, and describes the current status of KLKs as potential tumour biomarkers in these human malignancies.

scholarly journals Integrative analysis of mRNA and miRNA sequencing data for gliomas of various grades

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Dmitry Y. Gvaldin ◽  
Anton A. Pushkin ◽  
Nataliya N. Timoshkina ◽  
Eduard E. Rostorguev ◽  
Arbi M. Nalgiev ◽  
...  
Keyword(s):  
Overall Survival ◽  
Mirna Expression ◽  
Interaction Analysis ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differential Analysis ◽  
Sequencing Data ◽  
Aberrant Expression

Abstract Background The purpose of this study was to characterize subtype-specific patterns of mRNA and miRNA expression of gliomas using The Cancer Genome Atlas (TCGA) data to search for genetic determinants that predict prognosis in terms of overall survival and to create interaction networks for grade 2 and 3 (G2 and G3) astrocytomas, oligodendrogliomas and grade 4 (G4) glioblastoma multiforme. Based on open-access TCGA data, 5 groups were formed: astrocytoma G2 (n = 58), astrocytoma G3 (n = 128), oligodendroglioma G2 (n = 102), oligodendroglioma G3 (n = 72) and glioblastoma G4 (n = 564); normal samples of brain tissue were also analysed (n = 15). Data of patient age, sex, survival and expression patterns of mRNA and miRNA were extracted for each sample. After stratification of the data into groups, a differential analysis of expression was carried out, genes and miRNAs that affect overall survival were identified and gene set enrichment analysis (GSEA) and interaction analysis were performed. Results A total of 939 samples of glial tumours were analysed, for which subtype-specific expression profiles of genes and miRNAs were identified and networks of mRNA-miRNA interactions were constructed. Genes whose aberrant expression level was associated with survival were determined, and pairwise correlations between differential gene expression (DEG) and differential miRNA expression (DE miRNA) were calculated. Conclusions The developed panel of genes and miRNAs allowed us to differentiate glioma subtypes and evaluate prognosis in terms of the overall survival of patients. The regulatory miRNA-mRNA pairs unique to the five glioma subtypes identified in this study can stimulate the development of new therapeutic approaches based on subtype-specific mechanisms of oncogenesis.

scholarly journals Transcriptome Analysis in Vulvar Squamous Cell Cancer

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6372
Author(s):  
Katharina Prieske ◽  
Malik Alawi ◽  
Anna Jaeger ◽  
Maximilian Christian Wankner ◽  
Kathrin Eylmann ◽  
...  
Keyword(s):  
Squamous Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Cell Cancer ◽  
Rna Expression ◽  
Sequencing Data ◽  
Aberrant Expression ◽  
Distinct Cluster ◽  
Whole Exome Sequencing Data ◽  
Chronic Skin

To date, therapeutic strategies in vulvar squamous cell carcinoma (VSCC) are lacking molecular pathological information and targeted therapy hasn’t been approved in the treatment of VSCC, yet. Two etiological pathways are widely accepted: HPV induced vs. HPV independent, associated with chronic skin disease, often harboring TP53 mutations (mut). The aim of this analysis was to analyze the RNA expression patterns for subtype stratification on VSCC samples that can be integrated into the previously performed whole exome sequencing data for the detection of prognostic markers and potential therapeutic targets. We performed multiplex gene expression analysis (NanoString) with 770 genes in 24 prior next generation sequenced samples. An integrative data analysis was performed. Here, 98 genes were differentially expressed in TP53mut vs. HPV+ VSCC, in the TP53mut cohort, where 56 genes were upregulated and 42 were downregulated in comparison to the HPV+ tumors. Aberrant expression was primarily observed in cell cycle regulation, especially in HPV+ disease. Within the TP53mut group, a distinct cluster was identified that was correlated to a significantly worse overall survival (p = 0.017). The RNA expression profiles showed distinct patterns with regard to the known VSCC subtypes and could potentially enable further subclassification in the TP53mut groups

Identification of biomarkers and functional modules from genomic data in stage-wise breast cancer

2020 ◽  
Vol 15 ◽  
Author(s):  
Athira K ◽  
Vrinda C ◽  
Sunil Kumar P V ◽  
Gopakumar G
Keyword(s):  
Breast Cancer ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Predictive Biomarkers ◽  
Stage I ◽  
Stage Ii ◽  
Stage Iii ◽  
Functional Modules ◽  
Incidence And Mortality ◽  
Multiple Stages

Background: Breast cancer is the most common cancer in women across the world, with high incidence and mortality rates. Being a heterogeneous disease, gene expression profiling based analysis plays a significant role in understanding breast cancer. Since expression patterns of patients belonging to the same stage of breast cancer vary considerably, an integrated stage-wise analysis involving multiple samples is expected to give more comprehensive results and understanding of breast cancer. Objective: The objective of this study is to detect functionally significant modules from gene co-expression network of cancerous tissues and to extract prognostic genes related to multiple stages of breast cancer. Methods: To achieve this, a multiplex framework is modelled to map the multiple stages of breast cancer, which is followed by a modularity optimization method to identify functional modules from it. These functional modules are found to enrich many Gene Ontology terms significantly that are associated with cancer. Result and Discussion: predictive biomarkers are identified based on differential expression analysis of multiple stages of breast cancer. Conclusion: Our analysis identified 13 stage-I specific genes, 12 stage-II specific genes, and 42 stage-III specific genes that are significantly regulated and could be promising targets of breast cancer therapy. That apart, we could identify 29, 18 and 26 lncRNAs specific to stage I, stage II and stage III respectively.

scholarly journals Integrated molecular characterisation of endometrioid ovarian carcinoma identifies opportunities for stratification

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Robert L. Hollis ◽  
Barbara Stanley ◽  
John P. Thomson ◽  
Michael Churchman ◽  
Ian Croy ◽  
...  
Keyword(s):  
High Risk ◽  
Ovarian Carcinoma ◽  
Expression Patterns ◽  
Parp Inhibitors ◽  
Receptor Expression ◽  
Cancer Type ◽  
Sequencing Data ◽  
Molecular Features ◽  
Endometrioid Ovarian Carcinoma ◽  
Molecular Landscape

AbstractEndometrioid ovarian carcinoma (EnOC) is an under-investigated ovarian cancer type. Recent studies have described disease subtypes defined by genomics and hormone receptor expression patterns; here, we determine the relationship between these subtyping layers to define the molecular landscape of EnOC with high granularity and identify therapeutic vulnerabilities in high-risk cases. Whole exome sequencing data were integrated with progesterone and oestrogen receptor (PR and ER) expression-defined subtypes in 90 EnOC cases following robust pathological assessment, revealing dominant clinical and molecular features in the resulting integrated subtypes. We demonstrate significant correlation between subtyping approaches: PR-high (PR + /ER + , PR + /ER−) cases were predominantly CTNNB1-mutant (73.2% vs 18.4%, P < 0.001), while PR-low (PR−/ER + , PR−/ER−) cases displayed higher TP53 mutation frequency (38.8% vs 7.3%, P = 0.001), greater genomic complexity (P = 0.007) and more frequent copy number alterations (P = 0.001). PR-high EnOC patients experience favourable disease-specific survival independent of clinicopathological and genomic features (HR = 0.16, 95% CI 0.04–0.71). TP53 mutation further delineates the outcome of patients with PR-low tumours (HR = 2.56, 95% CI 1.14–5.75). A simple, routinely applicable, classification algorithm utilising immunohistochemistry for PR and p53 recapitulated these subtypes and their survival profiles. The genomic profile of high-risk EnOC subtypes suggests that inhibitors of the MAPK and PI3K-AKT pathways, alongside PARP inhibitors, represent promising candidate agents for improving patient survival. Patients with PR-low TP53-mutant EnOC have the greatest unmet clinical need, while PR-high tumours—which are typically CTNNB1-mutant and TP53 wild-type—experience excellent survival and may represent candidates for trials investigating de-escalation of adjuvant chemotherapy to agents such as endocrine therapy.

scholarly journals Histone deacetylase (HDAC) 9: versatile biological functions and emerging roles in human cancer

2021 ◽  
Author(s):  
Chun Yang ◽  
Stéphane Croteau ◽  
Pierre Hardy
Keyword(s):  
Histone Deacetylase ◽  
Posttranslational Modifications ◽  
Histone Deacetylases ◽  
Muscle Development ◽  
Target Genes ◽  
Human Cancer ◽  
Expression Patterns ◽  
Aberrant Expression ◽  
Physiological Processes ◽  
Cancer Pathogenesis

Abstract Background HDAC9 (histone deacetylase 9) belongs to the class IIa family of histone deacetylases. This enzyme can shuttle freely between the nucleus and cytoplasm and promotes tissue-specific transcriptional regulation by interacting with histone and non-histone substrates. HDAC9 plays an essential role in diverse physiological processes including cardiac muscle development, bone formation, adipocyte differentiation and innate immunity. HDAC9 inhibition or activation is therefore a promising avenue for therapeutic intervention in several diseases. HDAC9 overexpression is also common in cancer cells, where HDAC9 alters the expression and activity of numerous relevant proteins involved in carcinogenesis. Conclusions This review summarizes the most recent discoveries regarding HDAC9 as a crucial regulator of specific physiological systems and, more importantly, highlights the diverse spectrum of HDAC9-mediated posttranslational modifications and their contributions to cancer pathogenesis. HDAC9 is a potential novel therapeutic target, and the restoration of aberrant expression patterns observed among HDAC9 target genes and their related signaling pathways may provide opportunities to the design of novel anticancer therapeutic strategies.

scholarly journals Differential expression and correlation analysis of miRNA–mRNA profiles in swine testicular cells infected with porcine epidemic diarrhea virus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoqian Zhang ◽  
Chang Li ◽  
Bingzhou Zhang ◽  
Zhonghua Li ◽  
Wei Zeng ◽  
...  
Keyword(s):  
Differential Expression ◽  
Porcine Epidemic Diarrhea Virus ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Bacterial Invasion ◽  
Sequencing Data ◽  
Diarrhea Virus ◽  
Comparison Groups ◽  
Porcine Epidemic Diarrhea

AbstractThe variant virulent porcine epidemic diarrhea virus (PEDV) strain (YN15) can cause severe porcine epidemic diarrhea (PED); however, the attenuated vaccine-like PEDV strain (YN144) can induce immunity in piglets. To investigate the differences in pathogenesis and epigenetic mechanisms between the two strains, differential expression and correlation analyses of the microRNA (miRNA) and mRNA in swine testicular (ST) cells infected with YN15, YN144, and mock were performed on three comparison groups (YN15 vs Control, YN144 vs Control, and YN15 vs YN144). The mRNA and miRNA expression profiles were obtained using next-generation sequencing (NGS), and the differentially expressed (DE) (p-value < 0.05) mRNA and miRNA were obtained using DESeq R package. mRNAs targeted by DE miRNAs were predicted using the miRanda algortithm. 8039, 8631 and 3310 DE mRNAs, and 36, 36, and 22 DE miRNAs were identified in the three comparison groups, respectively. 14,140, 15,367 and 3771 DE miRNA–mRNA (targeted by DE miRNAs) interaction pairs with negatively correlated expression patterns were identified, and interaction networks were constructed using Cytoscape. Six DE miRNAs and six DE mRNAs were randomly selected to verify the sequencing data by real-time relative quantitative reverse transcription polymerase chain reaction (qRT-PCR). Based on bioinformatics analysis, we discovered the differences were mostly involved in host immune responses and viral pathogenicity, including NF-κB signaling pathway and bacterial invasion of epithelial cells, etc. This is the first comprehensive comparison of DE miRNA–mRNA pairs in YN15 and YN144 infection in vitro, which could provide novel strategies for the prevention and control of PED.

scholarly journals Cysteine Cathepsins and Their Prognostic and Therapeutic Relevance in Leukemia

2021 ◽  
Author(s):  
Mohit Arora ◽  
Garima Pandey ◽  
Shyam S. Chauhan
Keyword(s):  
Antigen Processing ◽  
Hematological Malignancies ◽  
Expression Patterns ◽  
Aberrant Expression ◽  
Hematopoietic Stem ◽  
Cysteine Cathepsins ◽  
Expression Activity ◽  
Available Information ◽  
Antigen Processing And Presentation ◽  
Selection Of

AbstractCysteine cathepsins are lysosomal proteases that require Cys-His ion pair in their catalytic site for enzymatic activity. While their aberrant expression and oncogenic functions have been widely reported in solid tumors, recent findings suggest that these proteases also play an important role in the pathogenesis of hematological malignancies. In this review, we summarize the potential clinical implications of cysteine cathepsins as diagnostic and prognostic markers in leukemia, and present evidences which supports the utility of these proteases as potential therapeutic targets in hematological malignancies. We also highlight the available information on the expression patterns, regulation, and potential functions of cysteine cathepsins in normal hematopoiesis and hematological malignancies. In hematopoiesis, cysteine cathepsins play a variety of physiological roles including regulation of hematopoietic stem cell adhesion in the bone marrow, trafficking, and maturation. They are also involved in several functions of immune cells which include the selection of lymphocytes in the thymus, antigen processing, and presentation. However, the expression of cysteine cathepsins is dysregulated in hematological malignancies where they have been shown to play diverse functions. Interestingly, several pieces of evidence over the past few years have demonstrated overexpression of cathepsins in leukemia and their association with worst survival outcomes in patients. Strategies aimed at altering the expression, activity, and subcellular localization of these cathepsins are emerging as potential therapeutic modalaties in the management of hematological malignancies. Recent findings also suggest the involvement of these proteases in modulating the immune response in leukemia and lymphomas.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

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