Biology subjects

Alba, M. M.

Publications and source records attributed to Alba, M. M..

13 recordsLinked to original sources

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

An expanded reference catalog of translated open reading frames for biomedical research

Non-canonical (i.e., unannotated) open reading frames (ncORFs) have until recently been omitted from reference genome annotations, despite evidence of their translation, limiting their incorporation into biomedical research. To address this, in 2022, we initiated the TransCODE consortium and built the first community-driven consensus catalog of human ncORFs, which was openly distributed to the research community via Ensembl-GENCODE. While this catalog represented a starting point for reference ncORF annotation, major technical and scientific issues remained. In particular, this initial catalogue had no standardized framework to judge the evidence of translation for individual ncORFs. Here, we present an expanded and refined catalog of the human reference annotation of ncORFs. By incorporating more datasets and by lifting constraints on ORF length and start-codon, we define a comprehensive set of 28,359 ncORFs that is nearly four times the size of the previous catalog. Furthermore, to aid users who wish to work with ncORFs with the strongest and most reproducible signals of translation, we utilized a data-driven framework (i.e. translation signature scores) to assess the accumulated evidence for any individual ncORF. Using this approach, we derive a subset of 7,888 ncORFs with translation evidence on par with canonical protein-coding genes, which we refer to as the Primary set. This set can serve as a reliable reference for downstream analyses and validation, with a particular emphasis on high quality. Overall, this update reflects continual community-driven efforts to make ncORFs accessible and actionable to the broader research public and further iterations of the catalog will continue to expand and refine this resource.

genomics↗

bioRxiv2024

GENCODE: massively expanding the lncRNA catalog through capture long-read RNA sequencing

Accurate and complete gene annotations are indispensable for understanding how genome sequences encode biological functions. For more than twenty years, the GENCODE consortium has developed reference annotations for the human and mouse genomes, becoming a foundation for biomedical and genomics communities worldwide. Nevertheless, collections of important yet poorly-understood gene classes like long non-coding RNAs (lncRNAs) remain incomplete and scattered across multiple, uncoordinated catalogs. To address this, GENCODE has undertaken the most comprehensive lncRNA annotation effort to date. This is founded on the manually supervised computational annotation of full-length targeted long-read sequencing, on matched embryonic and adult tissues, of orthologous regions in human and mouse. Altogether 17,931 human genes (140,268 transcripts) and 22,784 mouse genes (136,169 transcripts) have been added to the GENCODE catalog representing a 2-fold and 6-fold growth in transcripts, respectively - the greatest increase in the number of annotated human genes since the sequencing of the human genome. Our targeted design assigned human-mouse orthologs at a rate beyond previous studies, tripling the number of human disease-associated lncRNAs that have mouse orthologs. Novel lncRNA genes consistently exhibit biological signals of functionality, and they greatly enhance the functional interpretability of the human genome. While poorly expressed in bulk RNA-Seq samples, many of them are highly expressed in specific cell populations, maybe even contributing to cell-type determination. The expanded GENCODE lncRNA annotations mark a critical step toward deciphering the human and mouse genomes.

genomics↗

bioRxiv2024

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

molecular 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↗

bioRxiv2021

De novo determination of mosquitocidal Cry11Aa and Cry11Ba structures from naturally-occurring nanocrystals

Cry11Aa and Cry11Ba are the two most potent toxins produced by mosquitocidal Bacillus thuringiensis subsp. israelensis and jegathesan, respectively. The toxins naturally crystallize within the host; however, the crystals are too small for structure determination at synchrotron sources. Therefore, we applied serial femtosecond crystallography at X-ray free electron lasers to in vivo-grown nanocrystals of these toxins. The structure of Cry11Aa was determined de novo using the single-wavelength anomalous dispersion method, which in turn enabled the determination of the Cry11Ba structure by molecular replacement. The two structures reveal a new pattern for in vivo crystallization of Cry toxins, whereby each of their three domains packs with a symmetrically identical domain, and a cleavable crystal packing motif is located within the protoxin rather than at the termini. The diversity of in vivo crystallization patterns suggests explanations for their varied levels of toxicity and rational approaches to improve these toxins for mosquito control.

molecular biology↗

bioRxiv2021

A community-driven roadmap to advance research on translated open reading frames detected by Ribo-seq

Ribosome profiling (Ribo-seq) has catalyzed a paradigm shift in our understanding of the translational vocabulary of the human genome, discovering thousands of translated open reading frames (ORFs) within long non-coding RNAs and presumed untranslated regions of protein-coding genes. However, reference gene annotation projects have been circumspect in their incorporation of these ORFs due to uncertainties about their experimental reproducibility and physiological roles. Yet, it is indisputable that certain Ribo-seq ORFs make stable proteins, others mediate gene regulation, and many have medical implications. Ultimately, the absence of standardized ORF annotation has created a circular problem: while Ribo-seq ORFs remain unannotated by reference biological databases, this lack of characterisation will thwart research efforts examining their roles. Here, we outline the initial stages of a community-led effort supported by GENCODE / Ensembl, HGNC and UniProt to produce a consolidated catalog of human Ribo-seq ORFs.

genomics↗

bioRxiv2020

Reference-free reconstruction and quantification of transcriptomes from long-read sequencing

Nanopore sequencing enables the efficient and unbiased measurement of transcriptomes from any sample. However, current methods for transcript identification and quantification rely of mapping reads to a reference genome, which precludes the study of species with a partial or missing reference or the identification of disease-specific transcripts not readily identifiable from a reference. Here we present RATTLE, a tool to perform reference-free reconstruction and quantification of transcripts using only Nanopore reads. Using simulated data and experimental data from isoform spike-ins, human tissues, and cell lines, we show that RATTLE accurately determines transcript sequences and their abundances, and shows good scalability with the number of transcripts. RATTLE provides unprecedented access to transcriptomes from any sample and species without relying on a reference or additional technologies.

bioinformatics↗

bioRxiv2019

Frequent birth of de novo genes in the compact yeast genome

Evidence has accumulated that some genes originate directly from previously non-genic sequences, or de novo, rather than by the duplication or fusion of existing genes. However, how de novo genes emerge and eventually become functional is largely unknown. Here we perform the first study on de novo genes that uses transcriptomics data from eleven different yeast species, all grown identically in both rich media and in oxidative stress conditions. The genomes of these species are densely-packed with functional elements, leaving little room for the co-option of genomic sequences into new transcribed loci. Despite this, we find that at least 213 transcripts (~5%) have arisen de novo in the past 20 million years of evolution of bakers yeast-or approximately 10 new transcripts every million years. Nearly half of the total newly expressed sequences are generated from regions in which both DNA strands are used as templates for transcription, explaining the apparent contradiction between the limited empty genomic space and high rate of de novo gene birth. In addition, we find that 40% of these de novo transcripts are actively translated and that at least a fraction of the encoded proteins are likely to be under purifying selection. This study shows that even in very highly compact genomes, de novo transcripts are continuously generated and can give rise to new functional protein-coding genes.

evolutionary biology↗

bioRxiv2018

Using ribosome profiling to quantify differences in protein expression: a case study in Saccharomyces cerevisiae oxidative stress conditions

Cells respond to changes in the environment by modifying the concentration of specific proteins. Paradoxically, the cellular response is usually examined by measuring variations in transcript abundance by high throughput RNA sequencing (RNA-Seq), instead of directly measuring protein concentrations. This happens because RNA-Seq-based methods provide better quantitative estimates, and more extensive gene coverage, than proteomics-based ones. However, variations in transcript abundance do not necessarily reflect changes in the corresponding protein abundance. How can we close this gap? Here we explore the use of ribosome profiling (Ribo-Seq) to perform differentially gene expression analysis in a relatively well-characterized system, oxidative stress in bakers yeast. Ribo-Seq is an RNA sequencing method that specifically targets ribosome-protected RNA fragments, and thus is expected to provide a more accurate view of changes at the protein level than classical RNA-Seq. We show that gene quantification by Ribo-Seq is indeed more highly correlated with protein abundance, as measured from mass spectrometry data, than quantification by RNA-Seq. The analysis indicates that, whereas a subset of genes involved in oxidation-reduction processes is detected by both types of data, the majority of the genes that happen to be significant in the RNA-Seq-based analysis are not significant in the Ribo-Seq analysis, suggesting that they do not result in protein level changes. The results illustrate the advantages of Ribo-Seq to make inferences about changes in protein abundance in comparison with RNA-Seq.

genomics↗

bioRxiv2018

Frequent translation of small open reading frames in evolutionary conserved lncRNA regions

The mammalian transcriptome includes thousands of transcripts that do not correspond to annotated protein-coding genes. Although many of these transcripts show homology between human and mouse, only a small proportion of them have been functionally characterized. Here we use ribosome profiling data to identify translated open reading frames, as well as non-ribosomal protein-RNA interactions, in evolutionary conserved and non-conserved transcripts. We find that conserved regions are subject to significant evolutionary constraints and are enriched in translated open reading frames, as well as non-ribosomal protein-RNA interaction signatures, when compared to non-conserved regions. Translated ORFs can be divided in two classes, those encoding functional micropeptides and those that show no evidence of protein functionality. This study underscores the importance of combining evolutionary and biochemical measurements to advance in a more complete understanding of the transcriptome.

evolutionary biology↗