Biology subjects

Boldina, G.

Publications and source records attributed to Boldina, G..

3 recordsLinked to original sources

bioRxiv2023

MET functions in tumour progression and therapy resistance are repressed by intronic polyadenylation

Intronic polyadenylation (IPA) leads to the production of transcript isoforms with alternative last exons in thousands of mammalian genes. Widespread regulation of IPA isoforms was observed during oncogenic transformation and in tumours versus healthy tissues, and several IPA isoforms were involved in oncogenesis. However, little is known about the potential involvement of IPA in tumour progression, such as cancer cell invasiveness and metastasis, and in resistance to anticancer therapies. Here, we show that an IPA isoform of MET (short MET) whose production is inhibited by U1 snRNP (U1), an essential ribonucleoprotein complex that recognizes the 5 exon-intron junction of pre-mRNA, is associated with better prognosis in breast cancer. Induction of the short MET isoform, using a steric-blocking antisense oligonucleotide targeting the U1 binding site in the vicinity of the short MET alternative polyadenylation site, antagonizes cell invasiveness. U1 blockade with an antisense oligonucleotide targeting the U1 snRNA also decreases breast cancer cell invasiveness, in both human and mouse cancer cell models, and this effect involves IPA induction in MET and several genes belonging to the RAS/RAF/MAPK signalling pathway. Finally, short MET relieves melanoma cell resistance to MAPK cascade-targeted therapy in vitro and in vivo. IPA isoform levels of MET and a few other genes (mTOR, EGFR and CTNNA1) help predict such resistance in patients. Altogether, our findings provide evidence for a role of IPA in both cancer cell invasiveness and resistance to therapy. This suggests that IPA isoforms can be exploited as biomarkers and therapeutic targets to combat tumour progression.

molecular biology↗

bioRxiv2022

Uncoupling from transcription protects polyadenylation site cleavage from inhibition by DNA damage

Pre-mRNA 3-end processing by cleavage and polyadenylation (CPA) is a nuclear process in which RNA polymerase II (Pol II) transcripts are cleaved at the polyadenylation site (PAS cleavage) before addition of a poly(A) tail. While PAS cleavage is usually coupled to transcription termination, for some pre-mRNAs it occurs post-transcriptionally, i.e. after pre-mRNA release from chromatin to nucleoplasm through a downstream co-transcriptional cleavage (CoTC) event. DNA-damaging agents such as ultraviolet-C (UV) irradiation trigger rapid shutdown of pre-mRNA 3-end processing. However, specific compensatory mechanisms exist to ensure efficient 3-end processing for some pre-mRNAs encoding proteins involved in the DNA damage response (DDR), such as the p53 tumor suppressor protein. Here, we show that PAS cleavage of the p53 pre-mRNA occurs in part post-transcriptionally, in a PCF11-independent manner, in the nucleoplasm, following a CoTC-type event. Upon UV-irradiation, cells with an engineered deletion of the p53 CoTC site exhibit impaired 3-end processing of the p53 pre-mRNA, decreased mRNA and protein levels of p53 and its transcriptional target, p21, and altered cell cycle progression. Finally, using a transcriptome-wide analysis of PAS cleavage, we identified additional-including DDR related-pre-mRNAs whose PAS cleavage is maintained in response to UV and occurs post-transcriptionally. These findings indicate that CoTC-type cleavage of pre-mRNAs, followed by PAS cleavage in the nucleoplasm, allows specific pre-mRNAs to escape 3-end processing inhibition in response to UV-induced DNA damage.

molecular biology↗

bioRxiv2021

ASIGNTF: AGNOSTIC SIGNATURE USING NTF: A UNIVERSAL AGNOSTIC STRATEGY TO ESTIMATE CELL-TYPES ABUNDANCE FROM TRANSCRIPTOMIC DATASETS

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSMolecular signatures for deconvolution of immune cell types have been proposed, based on a methodology that relies on the biological classification of the cell types being studied. When working with less known biological material, a data-driven approach is needed to uncover the underlying classes and construct ad hoc signatures. ResultsWe introduce a new approach, ASigNTF: Agnostic Signature using Non-negative Tensor Factorization, to perform the deconvolution of cell types from transcriptomics data (RNAseq and microarray). ASigNTF, which is based on two complementary statistical/mathematical tools: non-negative tensor factorization (for dimensionality reduction) and the Herfindahl-Hirschman index (for signature selection), can be applied to any type of tissue as long as transcriptomic data on isolated cells is available. As a direct result of the new method, we propose two new signatures for the deconvolution of immune cell types, one consisting of a relatively small set of 415 genes, which is more compatible with microarray platforms, and a larger set of 915 genes. Using external datasets, our two signatures outperform the CIBERSORT LM22 signature in deconvolution of RNA-seq data. Our signature with 415 genes allows to recognize a larger number of cell types compared to the ABIS microarray signature. ConclusionsThe paper proposes a new method, ASigNTF; applies the method, and also provides a software implementation that allows to identify molecular signatures for deconvolution of complex tissues and specifically up to 16 immune cell types from micro-array or RNA-seq data. HO_SCPLOWIGHLIGHTSC_SCPLOWO_LISeveral signatures of immune cell types have been proposed, which follow a methodology deeply rooted in the known biological classification of the investigated cell types. C_LIO_LIWhen working with less known biological material, a more agnostic, data-driven approach is required to uncover the underlying classes and construct ad hoc signatures. C_LIO_LIWe present ASigNTF, a new agnostic approach to cell type classification and signature selection supported by an application software. C_LIO_LIWe discuss the results of benchmarking our proposed signatures, ABIS-seq and CIBERSORT on external datasets. C_LI

bioinformatics↗