To cite this paper use one of the standards below:
Please log in to watch the video
Log inINTRODUCTION AND OBJECTIVES: CRLF2 overexpression (CRLF2-high) has been associated with unfavourable prognosis in acute lymphoblastic leukaemia (ALL) cases. In B-cell precursor ALL (B-ALL), the presence of CRLF2 rearrangements (CRLF2-r) and CRLF2 F232C mutations can explain half of the cases with this gene overexpression. Nonetheless, the mechanism accounting for the other 50% of cases lacking CRLF2 abnormalities is still unknown. Recent studies have suggested that long non-coding RNAs (lncRNAs), including intergenic lncRNAs (lincRNAs), play a role in the development and progression of leukaemia and can interfere in the transcriptional regulation of protein-coding genes. In this scenario, we hypothesise that the dysregulation of lncRNAs might be a potential mechanism behind CRLF2-high in B-ALL patients. MATERIAL AND METHODS: We included 126 diagnostic B-ALL cases from the TARGET cohort and characterised their molecular profile based on WGS and RNA-seq data. The DESeq2 v.1.28.1 package was used for identifying the differentially expressed (DE) lincRNAs in CRLF2-high patients based on their adjusted p-value (p < 0.05). Lncpath package was used to obtain functional pathways influenced by the combinatory effect of DE lincRNAs with an FDR < 0.05. The DE lncRNA mRNA pairs experimentally validated were obtained from the LncRNA2Target v3.0 database. The interactions identified were tested in the TARGET data using correlation analysis. In addition, potential miRNAs targets were predicted by the multimiR package. All analyses were conducted based on the GRCh37-hg19 genome. RESULTS AND CONCLUSION: The DE analysis of 6,200 lincRNAs identified 293 up- and 70 down-regulated lincRNAs in CRLF2-high compared to CRLF2-low patients. These DE lincRNAs are mainly involved in pathways of processing of genetic information as well as pathways involved in different types of cancer, including acute and chronic myeloid leukemia. The expression patterns of 5 out of 11 potential DE lncRNA-target relationships identified were positively correlated among them in TARGET B-ALL cohort (R > 0.10 and p < 0.05), including RPL34-AS1-MIR3663, LINC00161-MIR21, LINC00161-MIR590, PWRN1-MIR21 and PART1-MIR149. These lincRNAs were previously reported as competing endogenous RNA (ceRNA) via sponging these target miRNAs pointed in other type cancer cells, impacting in cell proliferation, invasion, migration and apoptosis. The prediction of candidate target miRNAs revealed more than 11,000 miRNA-mRNA interactions that are under investigation. Based on this initial data, we will validate the significant correlations observed in the preliminary analyses in a series of Brazilian B-ALL cases. Our initial findings suggest a potential mechanistic role for these lincRNAs interactions on leukemogenesis which could unravel potential biomarkers. In conclusion, our data will expand the understanding of CRLF2 gene expression regulation.
Eliane Gouvêa de Oliveira-Barros
Thayana, primeiramente, parabéns pelo trabalho!
RNAs intergênicos são realmente intrigantes e podem desempenhar importantes papéis na regulação gênica e em doenças. Contudo, tanto na parte da biologia molecular quanto computacional ainda faltam métodos para sua predição... Embora já saibamos que muitos transcritos são associados a lncRNAs, ainda não se sabe muito a respeito dos papéis exercidos pelos lncRNAs, certo? Nesse trabalho vocês já identificaram 6.200 RNAs intergênicos (293 up e 70 down) em pacientes CRLF2-high em relação aos pacientes CRLF2-low. Vocês chegaram a avaliar as vias ou processos nos quais os RNAs up ou RNAs down estão envolvidos, exclusivamente?
With nearly 200,000 papers published, Galoá empowers scholars to share and discover cutting-edge research through our streamlined and accessible academic publishing platform.
Learn more about our products:
This proceedings is identified by a DOI , for use in citations or bibliographic references. Attention: this is not a DOI for the paper and as such cannot be used in Lattes to identify a particular work.
Check the link "How to cite" in the paper's page, to see how to properly cite the paper
Thayana Barbosa
Obrigada pelos comentários, Eliane! Já avaliamos as vias ou processos significativamente envolvidos sim, mas nesse momento estamos priorizando explorar as interações diretas ou indiretas desses lncRNAs diferencialmente expressos. Como estamos com um número grande de lncRNAs para explorar, pretendemos utilizar essa informação das redes como "filtro" para as abordagens futuras.
Eliane Gouvêa de Oliveira-Barros
Certo, entendo perfeitamente. Realmente é muita informação gerada para análise e por isso, é mesmo necessário estabelecer prioridades.
De qualquer forma, acredito que essa análise (separando os lncRNAs em up e down) poderá revelar se há algum “efeito redundante”, se uma mesma via é estimulada e inibida, concomitantemente. Além disso, seria possível tentar estimar o quanto as mesmas vias estão sendo estimuladas positiva ou negativamente.
Thayana Barbosa
Perfeito! Já temos essa análise. Avaliarei com esse pensamento! Obrigada! :)