Aglave, M. | bioRxiv Science

bioRxiv2025

NOX4 prevents the recruitment of PAX8 and NKX2.1 to chromatin in BRAF-mutated thyroid cancer cells.

Radioiodine (RAI) therapy, used for treating thyroid cancers, hinges on the expression of the Sodium Iodide Symporter (NIS). The majority of differentiated thyroid cancers (DTCs) are papillary, with a BRAFV600E mutation. This mutation correlates with an absence of RAI uptake, due to low NIS expression and a low differentiation score. NADPH oxidase 4 (NOX4)-derived ROS contribute to NIS repression in BRAFV600E-mutated thyroid cancer cells. Depleting NOX4 enhances the reactivation of NIS. This reversibility implies an epigenetic mechanisms contribution. Our findings indicate that NOX4 generates oxidative DNA damage in BRAFV600E-mutated thyroid cancer cells. DNA repair proteins such as OGG1 and MSH2/MSH6 proteins, in cooperation with DNMT1, turn these damages into transcription-blocking damages. This prevents the binding of PAX8 and NKX2.1 - two key transcription factors involved in thyroid differentiation - to the chromatin. Co-inhibition of the MAPK pathway, which regulates MSH2/MSH6 and DNMT1 expressions, and the TGF-{beta}1 pathway, which regulates NOX4 expression, fortifies the recruitment of the two transcription factors to the chromatin. Collectively, our findings present a molecular basis for NOX4s role in thyroid dedifferentiation.

cancer biology↗

bioRxiv2021

The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma

BackgroundTranscriptome analysis of cancer tissues has been instrumental in defining tumor subtypes, diagnostic signatures and cancer regulatory networks. Cancer transcriptomes are still predominantly analyzed at the level of gene expression. Few studies have addressed transcript-level variations, and most of these only looked at splice variants. Previously we introduced a k-mer based, reference-free method, DE-kupl, that performs differential analysis of RNA-seq data at the k-mer level, which enables distinguishing RNAs differing by a single nucleotide. Here we evaluate the significance of differential events discovered by this method in two independent lung adenocarcinoma RNA-seq datasets (N=583 and N=154). ResultsFocusing on differential events in a tumor vs normal setting, we found events in endogenous repeats, alternative splicing and polyadenylation sites, long non-coding RNAs, retained introns and unmapped RNAs. Replicability was highly significant for most event classes (assessed by comparing to events shared between unrelated tumors). Overall about 160,000 differential k-mer contigs were shared between datasets, including a large set of sequences from hypervariable genes such as immunoglobulins, SFTP and mucin genes. Most interestingly, we identified a set of novel tumor-specific long non-coding RNAs in intergenic and intronic regions. We found that expressed endogenous transposons defined two major groups of patients (high/low repeat expression) with distinct clinical characteristic. A number of repeats, intronic RNAs and lincRNA achieved strong patient stratification in univariate or multivariate survival models. Finally, using antigen presentation prediction, we identified 55 contigs predicted to produce recurrent tumor-specific antigens. ConclusionsK-mer based RNA-seq analysis enables description of cancer transcriptomes at nucleotide precision, independently of prior transcript annotation. Application to lung cancer data uncovered events stemming from a wide variety of transcriptional and postranscriptional mechanisms. Among those events, a significant subset was replicable between cohorts, thus constituting novel RNA hallmarks of cancer. The code is available at: https://github.com/Transipedia/dekupl-lung-cancer-inter-cohort.

bioinformatics↗