Biology subjects

Perera-Bel, J.

Publications and source records attributed to Perera-Bel, J..

10 recordsLinked to original sources

bioRxiv2026

RERE and the Mediator complex cooperate with EWSR1::FLI1 in the reprogramming of Translation and Alternative Splicing, the latter being a therapeutically targetable vulnerability in Ewing sarcoma

Ewing Sarcoma (ES) is an aggressive neoplasm arising in bones and soft tissues driven by the oncogenic fusion EWSR1::FLI1. Through epigenetic deregulation, EWSR1::FLI1 generates de novo super-enhancers that control the expression of key genes for tumor cell maintenance. By an integrative in silico analysis, we identified the subunit of the Mediator complex MED13L and RERE, a member of the atrophin family of arginine-glutamic acid dipeptide repeat-containing proteins, as genes regulated by EWSR1::FLI1-bound super-enhancers. We confirmed that EWSR1::FLI1 regulates MED13L and RERE expression in ES cell lines and showed that these proteins are highly expressed in Ewing primary tumors. Besides the well-established role of the Mediator complex in transcriptional regulation given its association with the RNA polymerase II, in ES cells the DNA binding sites of MED13L overlap with those of RERE and EWSR1::FLI1 in genes that control protein translation and alternative splicing (AS). Accordingly, the expression of various spliceosome components is co-regulated by MED13L, RERE and the oncogene, leading to AS in ES cells. We identified RBM39, a splicing factor downregulated after MED13L and RERE depletion, as a direct transcriptional target of EWSR1::FLI1. Consistently, in vitro viability experiments using indisulam, which induces selective DCAF15-dependent proteosome degradation of RBM39, demonstrate ES cells highly and specifically sensitive to RBM39 inhibition. In vivo experiments with mice xenografted with ES cells show complete tumor regression with indisulam, highlighting the potential of this approach as a novel and promising therapeutic strategy for Ewing sarcoma. STATEMENT OF SIGNIFICANCEEwing sarcoma (ES) is characterized by FET::ETS oncoproteins that act as pioneer transcription factors. Here, we identified two genes controlled by EWSR1::FLI1-bound super-enhancers, MED13L and RERE, and characterized the mechanism by which these proteins cooperate with the oncogene to regulate RNA metabolism and ribosomal processes in ES cells. These findings have led to the identification of the splicing factor RBM39 as a vulnerability in ES, as supported by the extraordinary sensitivity of these tumors to monotherapy with RBM39 degrader indisulam.

cancer biology↗

bioRxiv2026

Identification of a large class of cancer-germline microproteins as a source of immunotherapeutic targets

Classical cancer germline-antigens (CGAs) are proteins that are expressed in the male germinal line but not in somatic tissues, and that can also become expressed in tumors. However, the vast majority of testis-specific transcripts are long non-coding RNAs (lncRNAs) rather than protein-coding genes. Since recent studies have shown that many lncRNAs contain non-canonical open reading frames (ncORFs) that are translated into small proteins, or microproteins, there could be a large class of non-canonical cancer-germline antigens (ncCGAs) that remains to be discovered. Here, we integrate ribosome profiling from human testis and cancer cell lines with paired tumor/normal transcriptomes from 917 patients across eight common cancer types to define a comprehensive catalog of ncCGAs. This set comprises 235 ncCGAs encoded by lncRNAs or mRNA untranslated regions (5UTRs and 3UTRs), compared to 192 canonical CGAs (cCGAs) with similar expression patterns. We show that ncCGAs are evolutionary young, consistent with recent de novo emergence in the rapidly evolving male germline. Moreover, a large fraction is expressed across multiple patients and cancer types, indicating recurrent reactivation mechanisms in tumors. We further find that ncCGAs are frequently located in cancer-amplified regions or associated with MYC or E2F-regulated pathways, which may explain their expression in cancer. Finally, we provide strong evidence that a subset of ncCGAs give rise to potentially immunogenic HLA class I bound peptides. Together, our results describe a previously unexplored class of tumor-restricted antigens with potential applications in cancer immunotherapy.

cancer biology↗

bioRxiv2026

Oncogenes and tumor suppressor genes are enriched in stop-loss mutations generating protein extensions

Cancer genomes tend to accumulate a large number of mutations, and even rare mutations such as those causing the loss of a stop codon can be observed in a significant fraction of the tumors. Stop-loss mutations extend protein translation into the 3 untranslated region (3 UTR), generating altered proteins carrying extra amino acid sequences. These C-terminal extensions can potentially have consequences for tumorigenesis and immune recognition. To investigate the prevalence of stop-loss mutations in cancer, and to identify recurrent mutations with a possible tumor-promoting effect, we have interrogated mutation data from the tumor samples of 20,801 patients. This search has resulted in the annotation of 3,757 stop-loss mutations in 3,249 different protein-coding genes. Around 11% of the mutated genes contain recurrent stop-loss mutations, occurring in more than one patient. The protein extensions created by the mutations tend to be hydrophobic and/or positively charged, and these features are associated with an increased propensity to generate MHC I-bound peptides. We have also found that cancer-related genes contain 37% more stop-loss mutations than non-cancer-related genes, with both oncogenes and tumor suppressor genes showing similar enrichments. Furthermore, three out of the four genes with the highest number of stop-loss recurrences, PTMA, PCDH9 and SOX9, are cancer-related. In PTMA, the gene with the largest number of stop-loss mutations (14 patients), the mutation results in an extension of 9 amino acids. We provide experimental evidence that the mutation is associated with impaired cleavage of thymosin alpha 1, a peptide with immunostimulatory functions that is generated from the N-terminal part of the PTMA protein. The study provides evidence that stop-loss mutations are enriched in cancer-associated genes and constitutes a valuable resource for further studies on the effects of stop-loss mutations in cancer.

genomics↗

bioRxiv2025

Tumor B cell infiltration in platinum-treated advanced urothelial carcinoma

Platinum-based chemotherapy combined with immunotherapy provides durable disease control in advanced urothelial cancer. However, cisplatin and carboplatin differently impact the tumor immune microenvironment, affecting chemo-immunotherapy response. Here, we evaluate immune cell populations and ecosystems associated with overall survival in patients treated with platinum-based chemotherapy. Our transcriptomic analysis of pretreatment tumor samples from three cohorts (189 patients) of advanced urothelial cancer showed that lymphoid cell infiltration was significantly associated with prolonged overall survival. In cisplatin-treated patients, high memory B cell infiltration provided a significant overall survival improvement, but no such association was found in carboplatin-treated patients. Additionally, gene expression signatures implicated in B cell memory lineage and associated cytokines were associated with better overall survival in independent cancer patient cohorts. Our findings highlight memory B cell infiltration as a potential prognostic biomarker in urothelial cancer and emphasize the role of the tumor immune microenvironment in chemotherapy response.

cancer biology↗

bioRxiv2025

EWS-FLI1 Expression in Human Embryonic MSCs Leads to Transcriptional Reprograming, Defective DNA Damage Repair and Ewing Sarcoma

Ewing sarcoma (ES) is an aggressive bone and soft tissue neoplasm characterized by EWSR1/ETS rearrangements and whose cellular origin remains unclear. EWS-FLI1 expression in human pediatric mesenchymal stem cells (hpMSCs) induces a quantitatively and qualitatively different transcriptional response than its expression in human adult MSCs (haMSCs), but fails to form tumors in vivo. ES cells have early developmental lineage signatures distinct from postnatal MSCs. Here, we have generated MSCs from experimental teratomas out of human embryonic stem cells (heSCs). Transduction of these human embryonic mesenchymal stem cells (heMSCs) with EWS-FLI1 results in the acquisition of an ES transcriptome, although the oncogene does not preferentially bind to promoters, but to intronic and intergenic microsatellites with >10 CA dinucleotides and GGAA repeats, respectively. In heMSCs, EWS-FLI1 directly regulates BRCA1 expression, although EWS-FLI1-expressing cells show defects in DNA damage repair. Xenografting of EWS-FLI1-transduced heMSCs resulted in the formation of tumors expressing characteristic ES markers. In summary, EWS-FLI1 enforces an aberrant transcriptome and endows in vivo transforming capacity when expressed in an undifferentiated early heMSC. Our approach represents an innovative experimental method for understanding critical aspects of the biology of developmental tumors, from leukemia to sarcomas, in which few (even single) genetic alterations are able to transform a fetal stem cell.

cancer biology↗

bioRxiv2024

Predicting immunotherapy response in advanced bladder cancer: a meta-analysis of six independent cohorts

Advanced bladder cancer patients show very variable responses to immune checkpoint inhibitors (ICIs) and effective strategies to predict response are still lacking. Here we integrate mutation and gene expression data from 707 advanced bladder cancer patients treated with anti-PD-1/anti-PD-L1 to build highly accurate predictive models. We find that, in addition to tumor mutational burden (TMB), enrichment in the APOBEC mutational signature, and the abundance of pro-inflammatory macrophages, are major factors associated with the response. Paradoxically, patients with high immune infiltration do not show an overall better response. We show that this can be explained by the activation of immune suppressive mechanisms in a large portion of these patients. In the case of non-immune-infiltrated cancer subtypes, we uncover specific variables likely to be involved in the response. Our findings provide novel information for advancing precision medicine in patients with advanced bladder cancer treated with immunotherapy.

cancer biology↗

bioRxiv2023

Non-canonical ORFs are an important source of tumor-specific antigens in a liver cancer meta-cohort

The expression of tumor-specific antigens during cancer progression can trigger an immune response against the tumor. Antigens that have been used as cancer vaccines are those originated by non- synonymous mutations and those derived from cancer/testis antigens. However, the first class is predominantly patient-specific, preventing the development of therapies than can benefit multiple patients, and the second one offers a limited set of actionable targets. A possible alternative is the use of peptides derived from non-canonical ORFs (ncORFs). While many ncORFs have been shown to be translated in cancer cells, their tumor-specificity and patient distribution remains to be determined. Here we analyze RNA sequencing data 117 hepatocellular carcinoma (HCC) tumors and matched healthy tissue, together with ribosome profiling data from an additional 10 HCC tumors, to answer these open questions. Combining HLA-epitope binding predictions and experimental validation experiments we conclude that around 40% of the tumor-specific antigens in HCC are likely to be derived from ncORFs in lncRNAs, including two peptides that can trigger an immune response in mice. We identify a subset of 33 tumor-specific lncRNAs expressing novel cancer antigens shared by more than 10% of the HCC analyzed, which could be combined to target a large proportion of the patients. The results of the study open new avenues for extending the range of anti-cancer vaccines.

genomics↗

bioRxiv2023

Atypical memory B cells form a pre-plasmacellular reservoir for steady-state IgD responses to common nasopharyngeal antigens

The human nasopharyngeal mucosa includes organized lymphoepithelial structures continually engaged in frontline immune responses to aerodigestive antigens. Advancing our understanding of these responses might lead to the development of new strategies for the prevention and treatment of common immune disorders such as allergies. Here we identified a hitherto elusive tonsillar subset of atypical IgD class-switched IgD+IgM- memory (IgD-ME) B cells that were clonally related to IgD+IgM- germinal center (IgD-GC) B cells and IgD-secreting IgD+IgM- plasma cells (IgD-PCs) but not anergic IgD+IgM- B cells. Consistent with their pre-plasmacellular properties, IgD-ME B cells served as preferential precursors of IgD-PCs over IgD-GC B cells. IgD antibodies from IgD+IgM- cells acquired reactivity to multiple oral, airborne and commensal antigens through a mutation-dependent pathway involving both innate and adaptive signals. Thus, IgD-ME B cells may form a ready-to-use pre-plasmacellular reservoir for steady-state IgD responses likely aimed at enhancing nasopharyngeal homeostasis. One Sentence SummaryTonsillar atypical memory B cells form a ready-to-use pre-plasmacellular repertoire for IgD responses to common aerodigestive antigens.

immunology↗

bioRxiv2022

Reproducible data integration and visualization of biological networks in R

MotivationCollaborative workflows in network biology not only require the documentation of the performed analysis steps but also of the network data on which the decisions were based. However, replication of the entire workflow or tracking of the intermediate networks used for a particular visualization remains an intricate task. Also, the amount and heterogeneity of the integrated data requires instruments to explore and thus comprehend the results. ResultsHere we demonstrate a collection of software tools and libraries for network data integration, exploration, and visualization to document the different stages of the workflow. The integrative steps are performed in R, and the entire process is accompanied by an interchangeable toolset for data exploration and network visualization. AvailabilityThe source code of the performed workflow is available as R markdown scripts at https://github.com/frankkramer-lab/reproducible-network-visualization. A compiled HTML version is also hosted on Github pages at https://frankkramer-lab.github.io/reproducible-network-visualization. Contactflorian.auer@informatik.uni-augsburg.de

bioinformatics↗

bioRxiv2020

Explaining decisions of Graph Convolutional Neural Networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

MotivationContemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as non-interpretable black-box models. Layer-wise Relevance Propagation (LRP) is a technique to explain decisions of deep learning methods. It is widely used to interpret Convolutional Neural Networks (CNNs) applied on image data. Recently, CNNs started to extend towards non-euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Graph-CNNs can be applied to structured gene expression data, for example, to predict metastatic events in breast cancer. Therefore, there is a need for explanations showing which part of a molecular network is relevant for predicting an event, e.g. distant metastasis in cancer, for each individual patient. ResultsWe extended the procedure of LRP to make it available for Graph-CNN and tested its applicability on a large breast cancer dataset. We present Graph Layer-wise Relevance Propagation (GLRP) as a new method to explain the decisions made by Graph-CNNs. We demonstrate a sanity check of the developed GLRP on a hand-written digits dataset, and then applied the method on gene expression data. We show that GLRP provides patient-specific molecular subnetworks that largely agree with clinical knowledge and identify common as well as novel, and potentially druggable, drivers of tumor progression. As a result this method could be potentially highly useful on interpreting classification results on the individual patient level, as for example in precision medicine approaches or a molecular tumor board. Availabilityhttps://gitlab.gwdg.de/UKEBpublic/graph-lrp https://frankkramer-lab.github.io/MetaRelSubNetVis/ Contacttim.beissbarth@bioinf.med.uni-goettingen.de

bioinformatics↗