Articles publicats en revistes (Institut de Recerca Biomèdica (IRB Barcelona))

URI permanent per a aquesta col·leccióhttps://hdl.handle.net/2445/98743

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Experimental assessment of AI-based interactome mapping
(2026-04-04) Lambourne, Luke; Yadav, Anupama; Wang, Yang; Desbuleux, Alice; Kim, Dae-Kyum; Laval, Florent; Spirohn-Fitzgerald, Kerstin; Cafarelli, Tiziana; Pons, Carles; Kovács, István A.; Jailkhani, Noor; Schlabach, Sadie; De Ridder, David; Luck, Katja; Botchkarev, Vladimir V.; Debnath, Olivia; Bian, Wenting; Shen, Yun; Yang, Zhipeng; Mee, Miles W.; Helmy, Mohamed; Jacob, Yves; Lemmens, Irma; Rolland, Thomas; McClain, Gregory G.; Coté, Atina G.; Gebbia, Marinella; Kishore, Nishka; Knapp, Jennifer J.; Mellor, Joseph C.; Memisoglu, Gonen; Reimand, Jüri; Tavernier, Jan; Cusick, Michael E.; Zhong, Quan; Aloy Calaf, Patrick; Hao, Tong; Charloteaux, Benoit; Roth, Frederick P.; Rivas, Javier de las
Genotype-phenotype relationships are mediated through intricate networks of physical and functional interactions among macromolecules. Knowledge of the interactome is vital to understand and model genetics and cellular biology. Recent advances in accurately predicting tertiary protein structures using artificial intelligence (AI) approaches such as AlphaFold1 have revived the vision that the proteinprotein interactome might be fully predictable through computational modeling of quaternary structures. Here we present a comprehensive experimental framework to systematically assess the impact of AIdriven interactome predictions for yeast2 and human3. We find that the quality of high-confidence predictions is on par with established experimental approaches. However, in proteome-wide screening, the tested AI approaches underperform in the discovery of strictly novel protein-protein interactions (PPIs) compared to experimental reference interactome maps. In particular, the yeast interactome map describe here identifies >40-fold more novel PPIs than its AI counterpart. Strikingly, AlphaFold provides structural models for a substantial number of experimentally identified PPIs miss by the virtual screens. Our results suggest that, at this stage, the main contribution of AI predictions is to provide quaternary structure models for experimentally identified PPIs.
A Plastic EMP1+ to LGR5+ Cell State Conversion as a Bypass to KRASG12D Pharmacologic Inhibition in Metastatic Colorectal Cancer
(American Association for Cancer Research, 2026-02-06) Centonze, Alessia; Roura Canalda, Adrià Jaume; Novillo Font, Meritxell; Giordano, Cristina; Hernando Momblona, Javier; Llanses Martínez, Montserrat; Prats Martínez, Paula; Sevillano Rosa, Marta; Cabot, Débora; Novell, Mireia; Pabst, Gabriel; Andersch, Florian; Cañellas Socias, Adrià; Zhang, Chong ; Giakoumakis, Nikolaos Nikiforos ; Sparks, Hugh; Dunsby, Chris; Colombelli, Julien; Fernández Barral, Asunción; Sancho Suils, Elena; Stephan-Otto Attolini, Camille; Muñoz, Alberto; Barbachano, Antonio; Martínez Quintanilla, Jordi; Palmer, Héctor G.; Zuber, Johannes; Blaj, Cristina; Sancho, Elena; Quintana, Elsa ; Cortina, Carme; Martí Renom, Marc A.; Batlle Gómez, Eduard
Inhibitors of the oncogene KRAS hold promise for treating metastatic colorectal cancer (mCRC). In this study, we show that a selective, covalent small-molecule inhibitor of the active (ON) conformation of RAS-G12D, RMC-9945, exerts durable disease control in preclinical colorectal cancer models of early liver metastasis, but its therapeutic activity was diminished in the advanced metastatic disease. RMC-9945-treated metastases underwent a transition from a poor prognosis-associated Emp1+ transcriptional state to a WNT-driven Lgr5+ stem cell-like state that withstands the absence of RAS-G12D activity. This cell state change occurred within hours of RAS(ON) inhibitor treatment through a shift in transcription factor usage that involved limited chromatin remodeling. Forced conversion of metastatic cells to the Lgr5+ state through RAS-G12D inhibition, followed by genetic ablation of this population, reduced metastatic burden and prolonged survival in a mouse mCRC model. Overall, these preclinical findings demonstrate a central role for oncogenic KRAS in governing cellular plasticity in mCRC.Significance: We show that inhibition of oncogenic KRAS in preclinical models of advanced mCRC exerts a limited benefit, primarily due to the reversion of tumor cells to a stem cell-like state. Our findings highlight the context-dependent effects of oncogenic KRAS mutations and underscore cell plasticity as a therapeutic opportunity. See related commentary by Eng and Yilmaz et al., p. 201Significance: We show that inhibition of oncogenic KRAS in preclinical models of advanced mCRC exerts a limited benefit, primarily due to the reversion of tumor cells to a stem cell-like state. Our findings highlight the context-dependent effects of oncogenic KRAS mutations and underscore cell plasticity as a therapeutic opportunity. See related commentary by Eng and Yilmaz et al., p. 201
Proteostasis failure and mitochondrial dysfunction contribute to chromosomal instability-induced microcephaly
(Springer Nature, 2026-03-12) Gonzalez Blanco, Amanda; Acuna Higaki, Adrian Ricardo; Boettger, David; Joy, Jery; Milán Kalbfleisch, Marco
Oligomerization enables the selective targeting of an intrinsically disordered region by a small molecule
(Elsevier, 2026-02-27) Bielskutė, Stasė ; Mateos López, Borja; Awawdy, Muhammad ; Garcia Cabau, Carla; Niskanen, Henri ; Sánchez Zarzalejo, Carolina; Bracaglia, Lorenzo ; Pierattelli, Roberta ; Felli, Isabella C. ; Frigolé Vivas, Marta ; García Arroyo, Jesús; Riera Escale, Antoni; Hnisz, Denes ; Salvatella Giralt, Xavier
Intrinsically disordered regions (IDRs) in proteins are increasingly recognized as attractive targets for therapeutic intervention. A number of small molecules interacting with IDRs have been identified, but the lack of persistent secondary and tertiary structure of these regions has led to the prevailing view that they cannot be targeted selectively. Here, we show that a small molecule targeting an IDR evaluated in a clinical trial interacts selectively with an oligomeric form of its target, which is more structured than the monomer and is stabilized by interactions involving aromatic residues in partially α- helical regions. The interaction reshapes the conformational ensemble of the target, alters the biophysical properties of its phase- separated condensates in vitro, and attenuates RNA polymerase II recruitment in cells. Our findings provide mechanistic insights into how small molecules can selectively recognize IDRs.
Recurrent Immunogenic Neoantigens and Their Cognate T-cell Receptors in Treatment-Resistant Metastatic Prostate Cancer
(American Association for Cancer Research, 2026-02-06) Gumpert, Nofar; Sagie, Shira ; Arnedo Pac, Claudia; Babu, Tomer ; Weller, Chen ; Gonzalez Perez, Abel David; Wang, Yuan ; Todó, Lucas Michel; Levy, Ronen ; Chen, Xi ; Greenberg, Polina ; Dayan-Rubinov, Maria ; Yakubovich, Elizabeta ; Wasserman-Bartov, Talya ; Zerbib, Mirie ; Gong, Jianhui ; Rebernick, Ryan J. ; Oliveira Tercero, Anna ; Agundez Muriel, Laura ; Benedek, Gil ; Kedmi, Merav ; Oren, Roni ; Ben-Dor, Shifra ; Levin, Yishai ; Troyanskaya, Olga G. ; Munzur, Aslı D. ; Wyatt, Alexander W.; Cieslik, Marcin P. ; Quigley, David A. ; Van Allen, Eliezer M. ; Anandasabapathy, Niroshana ; Mateo, Joaquin ; Yang, Xinbo ; Martínez Jiménez, Francisco ; López Bigas, Núria ; Samuels, Yardena
New approaches that generate long-lasting therapeutic responses in patients with therapy-resistant metastatic cancer are urgently needed. To address this challenge, we developed Spot Neoantigens in Metastases (SpotNeoMet), a novel data-driven pipeline that systematically identifies recurrently presented neopeptides in treatment-resistant patients. We identified seven therapy resistance mutations predicted to produce neopeptides presented by common HLAs. Using HLA immunopeptidomics, we discovered three novel neopeptides derived from androgen receptor (AR) H875Y, a common metastatic castration-resistant prostate cancer (mCRPC) mutation. We validated these neoantigens as highly immunogenic and then isolated and characterized cognate T-cell receptors (TCR) from healthy donor peripheral blood mononuclear cells. We demonstrated that AR H875Y-specific TCRs are highly specific and kill prostate cancer cells presenting AR neopeptides in vitro and in vivo. Our new pipeline identifies novel immunotherapy targets and potential treatment options for patients with mCRPC. Moreover, SpotNeoMet offers a systematic route to identify "HLA-peptide" pairs and their cognate TCRs across treatment-resistant cancers.Significance: As the emergence of resistance to targeted treatments in patients with metastatic cancer, there is an urgent need for innovative therapeutic approaches for this population. Our study provides a new analytic framework to identify neoantigens from treatment-resistant mutations and a proof-of-concept T cell-based immunotherapy treatment for mCRPC.
Profound cell wall remodeling in Candida parapsilosis during systemic infection confers simultaneous tolerance to echinocandins and host immunity.
(2026-02-13) Daneshnia, Farnaz; Arastehfar, Amir; Cai, Liuyang ; Gunasekaran, Deepika ; Gautam, Isha ; Perry, Austin M. ; Ghahfarokhy, Pegah Mosharaf ; Ebadati, Arefeh ; Muñoz, Julieta ; Padilla, Dorian ; Hilmioglu-Polat, Süleyha ; Mei, Shenglin ; Floyd, Daniel J. ; Schikora Tamarit, Miquel Àngel ; Fuentes Palacios, Diego; Artigues Lleixà, Maria; Walker, Louise A. ; Gonçalves, Samuel M. ; Salehi, Mostafa ; Carvalho, Agostinho ; Desai, Jigar V. ; Perlin, David S. ; Munro, Carol A. ; Hopke, Alex ; Wang, Tuo ; Gabaldón Esteban, Toni ; Fang, Wenjie ; Nobile, Clarissa J. ; Mansour, Michael K.
Antifungal tolerance can promote the emergence of resistance yet often incurs fitness costs for fungal pathogens. How tolerant populations compensate for these deficits and how they may be therapeutically targeted remain poorly under stood. Here, we investigate four sequential Candida parapsilosis isolates recovered from a patient with persistent candidemia and failure of micafungin therapy. The infection was ultimately cleared with liposomal amphotericin B (LAMB). Whole-genome sequencing (WGS) confirmed clonal relatedness and the absence of known resistance mutations. Later isolates displayed marked cell wall remodeling (CWR), characterized by increased mannan and reduced β-glucan content, as revealed by microscopy and solid-state nuclear magnetic resonance. These isolates formed thicker biofilms and displayed enhanced echinocandin tolerance but paradoxically showed increased susceptibility to amphotericin B (AMB) in vitro and during systemic infection in mice. Despite a complex mutational landscape, transcriptomic profiling across planktonic and biofilm growth showed minimal divergence from the earliest isolate. Functionally, evolved isolates suppressed M1 macrophage polarization, dampened proinflammatory cytokine production, survived better during neutrophil interactions, and transiently increased fungal burden in vivo. These findings show that host-driven CWR could promote echinocandin tolerance while simultaneously sensitizing C. parapsilosis to AMB. Our results suggest that alternating echinocandin and LAMB therapy may effectively eliminate echinocandin-tolerant fungal populations.
Molecular dynamics modelling of the interaction of a synthetic zinc-finger miniprotein with DNA
(Royal Society of Chemistry, 2023) Rodriguez, Jessica; Battistini, Federica; Learte-Aymamí, Soraya; Orozco López, Modesto; Mascareñas, José L.
We report the modelling of the DNA complex of an artificial miniprotein composed of two zinc finger modules and an AT-hook linking peptide. The computational study provides for the first time a structural view of these types of complexes, dissecting interactions that are key to modulate their stability. The relevance of these interactions was validated experimentally. These results confirm the potential of this type of computational approach for studying peptide–DNA complexes and suggest that they could be very useful for the rational design of non-natural, DNA binding miniproteins.
Expansion of the neocortex and protection from neurodegeneration by in vivo transient reprogramming
(Elsevier B.V., 2024-12-05) Shen, Yi Ru; Zaballa Larrinaga, Sofía; Bech, Xavier; Sancho Balsells, Anna; Rodriguez Navarro, Irene; Cifuentes Díaz, Carmen; Seyit Bremer, Gönül; Chun, Seung Hee; Straub, Tobias; Abante Llenas, Jordi; Merino Valverde, Iñaki; Richart, Laia; Gupta, Vipul; Li, Hao Yi; Ballasch, Iván; Alcazar, Noelia; Alberch i Vié, Jordi, 1959-; Canals i Coll, Josep M.; Abad, María; Serrano, Manuel; Klein, Rüdiger; Giralt Torroella, Albert; Toro Ruiz, Daniel del
Yamanaka factors (YFs) can reverse some aging features in mammalian tissues, but their effects on the brain remain largely unexplored. Here, we induced YFs in the mouse brain in a controlled spatiotemporal manner in two different scenarios: brain development and adult stages in the context of neurodegeneration. Embryonic induction of YFs perturbed cell identity of both progenitors and neurons, but transient and low-level expression is tolerated by these cells. Under these conditions, YF induction led to progenitor expansion, an increased number of upper cortical neurons and glia, and enhanced motor and social behavior in adult mice. Additionally, controlled YF induction is tolerated by principal neurons in the adult dorsal hippocampus and prevented the development of several hallmarks of Alzheimer’s disease, including cognitive decline and altered molecular signatures, in the 5xFAD mouse model. These results highlight the powerful impact of YFs on neural proliferation and their potential use in brain disorders.
Characterisation of the gut-lung axis microbiome in clinically stable patients with chronic obstructive pulmonary disease.
(Elsevier, 2026-01-07) Viglino, Julieta; Perea Soriano, Lídia; García Nuñez, Marian; Rodrigo-Troyano, Ana; Torrego, Alfons; Domínguez Álvarez, Marisol; Villar, Judith; Carrizosa Gueri, Xènia; Quero Blanca, Sara; Gabaldón Estevan, Juan Antonio, 1973-; Willis, Jesse R.; Saus, Ester; Gea Guiral, Joaquim; Santos Pérez, Salud; Camps Massa, Paula; Agustí García-Navarro, Àlvar; Monsó, Eduard; Sibila Vidal, Oriol; Faner, Rosa
Background Airway and gut dysbiosis have been reported in Chronic Obstructive Pulmonary Disease (COPD); however, their relationship and association with clinical features remain poorly understood. We aimed to characterise the lung and gut microbiome in patients with stable COPD and controls. Methods Prospective, multicentre, longitudinal and controlled study of n = 60 stable patients with COPD and n = 30 controls. In them, we analysed 16S rRNA-seq in oropharyngeal (OP) swabs, sputum, bronchoalveolar lavage fluid (BALF) and stool. Weighted gene co-expression network analysis (WGCNA) was employed in each sample type to identify modules of co-abundant bacteria associated with clinical traits. Findings We found that the microbiome in airway and stool samples was highly dissimilar both in patients and controls, with 0.37% of this diversity associated to COPD. The microbiome taxa associated with COPD in OP swabs and sputum were highly similar, but different from BALF, suggesting that OP swabs can be a surrogate sample of sputum. Finally, using WGCNA, we identified: (a) 5 modules in OP swabs and 3 in sputum associated with FEV1, but some of them were also associated with exacerbations, dyspnoea and inhaled steroid (ICS) use; (b) In BALF 4 modules associated with FEV1 and dyspnoea, and 2 modules with ICS; and, finally, (c) in stool, 1 module related to FEV1, 1 to exacerbations and 3 with ICS. Interpretation The gut and lung microbiomes in patients with COPD are distinct, but both clinically relevant as both present bacterial associations with airflow limitation, exacerbation history, and ICS use.
Nuclear stiffness through lamin A/C overexpression differentially modulates chromosomal instability biomarkers
(Wiley, 2025-02-25) Bosch Calvet, Mireia; Pérez Venteo, Alejandro; Cebria Xart, Alex; Garcia Cajide, Marta; Mauvezin, Caroline
Background Information Mitosis is crucial for the faithful transmission of genetic material, and disruptions can result in chromosomal instability (CIN), a hallmark of cancer. CIN is a known driver of tumor heterogeneity and anti-cancer drug resistance, thus highlighting the need to assess CIN levels in cancer cells to design effective targeted therapy. While micronuclei are widely recognized as CIN markers, we have recently identified the toroidal nucleus, a novel ring-shaped nuclear phenotype arising as well from chromosome mis-segregation. Results Here, we examined whether increasing nuclear envelope stiffness through lamin A/C overexpression could affect the formation of toroidal nuclei and micronuclei. Interestingly, lamin A/C overexpression led to an increase in toroidal nuclei while reducing micronuclei prevalence. We demonstrated that chromatin compaction and nuclear stiffness drive the formation of toroidal nuclei. Furthermore, inhibition of autophagy and lysosomal function elevated the frequency of toroidal nuclei without affecting the number of micronuclei in the whole cell population. We demonstrated that this divergence between the two CIN biomarkers is independent of defects in lamin A processing. Conclusions and Significance These findings uncover a complex interplay between nuclear architecture and levels of CIN, advancing our understanding of the mechanisms supporting genomic stability and further contributing to cancer biology.
Harnessing dendritic cell metabolism for healthy ageing: reducing the risk of cardiovascular disease?
(2024-06-06) Wculek, Stefanie Kristin
Success and Limitations of Current Force Fields for the Description of RNA–Ligand Complexes
(American Chemical Society, 2025-10-31) Fernández Migens, Paula; Serrano Chacón, Israel; Orozco López, Modesto; Battistini, Federica
We present a systematic assessment of the last generation of RNA force fields to reproduce the structures and dynamics of ligand−RNA complexes. Our comprehensive analysis helped not only to define the more reliable force field to represent complex structures but also suggests details that can be improved and provide a critical analysis of the quality of experimental structures in complex systems that are expected to be very flexible and environment dependent.
Variable efficiency of nonsense-mediated mRNA decay across human tissues, tumors and individuals
(BMC, 2025-09-29) Palou Márquez, Guillermo; Supek, Fran
BackgroundNonsense-mediated mRNA decay (NMD) is a quality-control pathway that degrades mRNA bearing premature termination codons (PTCs) resulting from mutation or mis-splicing, and that additionally participates in gene regulation of unmutated transcripts. While NMD activity is known to differ between examples of PTCs, it is less well studied if human tissues differ in NMD activity, or if individuals differ.ResultsWe analyzed exomes and matched transcriptomes from Human tumors and healthy tissues to quantify individual-level NMD efficiency, and assess its variability between tissues, tumors, and individuals. This was done by monitoring mRNA levels of endogenous NMD target transcripts, and additionally supported by allele-specific expression of germline PTCs. Nervous system and reproductive system tissues have lower NMD efficiency than other tissues, such as the digestive tract. Next, there is systematic inter-individual variability in NMD efficiency, and we identify two underlying mechanisms. First, somatic copy number alterations can robustly associate with NMD efficiency, prominently the commonly-occurring gain at chromosome 1q that encompasses two core NMD genes: SMG5 and SMG7 and additional functionally interacting genes such as PMF1 and GON4L. Second, deleterious germline variants in genes such as the KDM6B chromatin modifier can associate with higher or lower NMD efficiency in individuals. Variable NMD efficiency modulates positive selection upon somatic nonsense mutations in tumor suppressor genes, and is associated with cancer patient survival and immunotherapy responses. ConclusionsNMD efficiency is variable across human tissues, and it is additionally variable across individuals and tumors thereof due to germline and somatic genetic alterations.
DiffInvex identifies evolutionary shifts in driver gene repertoires during tumorigenesis and chemotherapy
(Nature Communications, 2025-05-13) Khalil, Ahmed; Supek, Fran
Somatic cells can transform into tumors due to mutations, and the tumors further evolve towards increased aggressiveness and therapy resistance. We develop DiffInvex, a framework for identifying changes in selection acting on individual genes in somatic genomes, drawing on an empirical mutation rate baseline derived from non-coding DNA that accounts for shifts in neutral mutagenesis during cancer evolution. We apply DiffInvex to >11,000 somatic whole-genome sequences from similar to 30 cancer types or healthy tissues, identifying genes where point mutations are under conditional positive or negative selection during exposure to specific chemotherapeutics, suggesting drug resistance mechanisms occurring via point mutation. DiffInvex identifies 11 genes exhibiting treatment-associated selection for different classes of chemotherapies, linking selected mutations in PIK3CA, APC, MAP2K4, SMAD4, STK11 and MAP3K1 with drug exposure. Various gene-chemotherapy associations are further supported by differential functional impact of mutations pre- versus post-therapy, and are also replicated in independent studies. In addition to nominating drug resistance genes, we contrast the genomes of healthy versus cancerous cells of matched human tissues. We identify noncancerous expansion-specific drivers, including NOTCH1 and ARID1A. DiffInvex can also be applied to diverse analyses in cancer evolution to identify changes in driver gene repertoires across time or space.
The DNA dialect: a comprehensive guide to pretrained genomic language models
(EMBO Press en asociación con Springer Nature, 2026-01-19) Veiner, Marcell; Supek, Fran
Following their success in natural language processing and protein biology, pretrained large language models have started appearing in genomics in large numbers. These genomic language models (gLMs), trained on diverse DNA and RNA sequences, promise improved performance on a variety of downstream prediction and understanding tasks. In this review, we trace the rapid evolution of gLMs, analyze current trends, and offer an overview of their application in genomic research. We investigate each gLM component in detail, from training data curation to the architecture, and highlight the present trends of increasing model complexity. We review major benchmarking efforts, suggesting that no single model dominates, and that task-specific design and pretraining data often outweigh general model scale or architecture. In addition, we discuss requirements for making gLMs practically useful for genomic research. While several applications, ranging from genome annotation to DNA sequence generation, showcase the potential of gLMs, their use highlights gaps and pitfalls that remain unresolved. This guide aims to equip researchers with a grounded understanding of gLM capabilities, limitations, and best practices for their effective use in genomics.
Joint inference of mutational signatures from indels and single-nucleotide substitutions reveals prognostic impact of DNA repair deficiencies
(BMC, 2025-07-03) Ferrer Torres, Patricia; Galvan Femenia, Ivan ; Supek, Fran
BackgroundMutational signatures are increasingly used to understand the mechanisms causing cancer. However, their important applications in predicting prognosis and stratifying patients for therapy are hampered by inaccurate inference of the various featureless, dense trinucleotide mutational spectra, which are often confounded with one another. One of them is the homologous recombination deficiency (HRd)-associated signature SBS3, relevant because of its association with prognosis in ovarian and breast cancer and because of its potential as a biomarker for synthetic lethality therapies.MethodsHere, we highlight strong benefits of a multimodal approach for mutational signature extraction, applied on top of standard bioinformatic pipelines. By jointly operating on single-base substitution (SBS) and indel (ID) spectra, this method enables accurate identification of various DNA repair deficiency signatures and patient survival prediction.ResultsAcross four different cohorts of whole-genome sequenced high-grade serous ovarian cancers (HGSOC), the multimodal SBS + ID approach correctly distinguished the commonly confused signatures SBS3, SBS5, SBS8, SBS39, and SBS40. Importantly, we robustly identified two different multimodal SBS3 signatures, m-SBS3a and m-SBS3b, with distinct patterns in the indel spectrum. Multimodal SBS3b signature was strongly predictive of longer survival in ovarian cancer patients, replicating across four cohorts, with effect sizes greatly exceeding other genetic markers. Our m-SBS3 also predicted survival in platinum-treated patients with various cancer types, and moreover, the SBS + ID joint inference was successfully applied to mismatch repair-deficient colorectal cancer and immunotherapy response, supporting a general utility of the multimodal mutational signatures approach.ConclusionsOverall, combining SBS and ID mutations improves detection of HR deficiency-associated signatures and reveals distinct SBS3 subtypes with prognostic value. This multimodal approach outperforms existing markers and is readily applicable to therapy stratification.
Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations
(Nature Communications, 2024-07-20) Besedina, Elizaveta; Supek, Fran
Cancer driver genes can undergo positive selection for various types of genetic alterations, including gain-of-function or loss-of-function mutations and copy number alterations (CNA). We investigated the landscape of different types of alterations affecting driver genes in 17,644 cancer exomes and genomes. We find that oncogenes may simultaneously exhibit signatures of positive selection and also negative selection in different gene segments, suggesting a method to identify additional tumor types where an oncogene is a driver or a vulnerability. Next, we characterize the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Similarly, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed regardless of the type of CNA and may signal new therapeutic opportunities. An analysis with focus on the somatic CNA two-hit events can help identify additional driver genes relevant to a tumor type. By a global inference of point mutation and CNA selection signatures and interactions thereof across genes and tissues, we identify 9 evolutionary archetypes of driver genes, representing different mechanisms of (in)activation by genetic alterations.
Editorial: The impact of lipid metabolism on cancer progression and metastasis
(Frontiers Media, 2025-12-10) Aydemir, Duygu; Martín Pérez, Miguel; Sunami, Yoshiaki
Recent advances in oncology, immunology, and metabolic medicine have increasingly positioned lipid metabolism as a central determinant of cancer initiation, progression, and therapeutic response. Across multiple domains, lipid metabolic pathways are now understood to intersect with endocrine regulation, immune cell function, and systemic metabolic homeostasis, thereby influencing tumor behavior at both cellular and organismal levels. This expanding body of evidence highlights lipid metabolism not as an isolated biochemical process, but as an integrative axis that coordinates metabolic, immunological, and endocrine signals within the tumor microenvironment and throughout the host. Such a multidimensional perspective underscores the importance of synthesizing cross-disciplinary findings to fully elucidate the mechanistic and translational relevance of lipid metabolic regulation in contemporary cancer research.
Molecular simulations meet personalized medicine: The mechanism of action of CLC-5 antiporter and the origin of Dent's disease
(2025-11-01) Macaluso, Veronica; Pérez, Carles; Soliva, Robert; Westermaier, Yvonne; Díaz, Lucía; Wieczór, Milosz ; Orozco López, Modesto
ClC-5 is a Cl-/H+ antiporter crucial for the homeostasis of the entire organism, and whose functional deficiencies cause pathologies such as Dent's disease, a rare genetic disorder that can have lethal consequences. While the clinical aspects of the pathology are known, its molecular basis is elusive, which hampers the development of potential therapies. We present here a systematic study, where we explore the mechanism of transport of ClC-5, deciphering the choreography of structural changes required for the transport of chloride ions and protons in opposing directions. Once the mechanism is determined, we explore how the 523 Delta Val deletion linked to Dent's disease hampers the correct functioning of the transporter, despite having a very minor structural impact. Our study highlights how state-of-the-art simulation methods can shed light on the origin of rare diseases and explore targets for personalized medicine.
Phylogeny-aware Simulations Suggest a Low Impact of Unsampled Lineages in the Inference of Gene Flow During Eukaryogenesis
(2025-11-01) Bernabeu, Moises; Manzano Morales, Saioa ; Gabaldón Esteban, Toni
The topologies of gene trees are broadly used to infer horizontal gene transfer events and characterize the potential donor and acceptor partners. Additionally, ratios between branch lengths in the gene tree can inform about the timing of transfers relative to each other. Using this approach, recent studies have proposed a relative chronology of gene acquisitions in the lineage leading to the last eukaryotic common ancestor. However, a recognized caveat of the branch-length ratio method are potential biases due to incomplete taxon sampling resulting in so-called "ghost" lineages. Here, we assessed the effect of ghost lineages on the inference of the relative ordering of gene acquisition events during eukaryogenesis. For this, we used a novel simulation framework that populates a dated Tree of Life with plausible "ghost" lineages and simulates their gene transfers to the lineage leading to last eukaryotic common ancestor. Our simulations suggest that a substantial majority of gene acquisitions from distinct ghost donors are inferred with the correct relative order. However, we identify phylogenetic placements where ghost lineages would be more likely to produce misleading results. Overall, our approach offers valuable guidance for the interpretation of future work on eukaryogenesis, and can be readily adapted to other evolutionary scenarios.

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