Análisis de interacciones de letalidad sintética (SL) en cáncer y predicción de tratamientos

Trabajo fin de máster en Bioinformática y Biología ComputacionalEl tratamiento de tumores de forma dirigida todavía supone un desafío en la investigación contra el cáncer. Con el descubrimiento del fenómeno conocido como adicción oncogénica, basado en el concepto de que existen tumores cuya supervivencia depende de (o son adictos a) ciertos genes o rutas biológicas, se produjo un cambio de paradigma en el campo del desarrollo de fármacos antineoplásicos, ahora más dirigido hacia lo que conocemos como medicina personalizada. La idea de medicina personalizada surge de la dependencia que existe entre la eficacia de una terapia y la presencia de determinadas alteraciones genéticas, y busca desarrollar fármacos que actúen sobre dianas específicas del tumor. Pero pese a ser una de las líneas de investigación más importantes para el tratamiento de la enfermedad, de momento sólo ha demostrado ser efectiva en tumores muy determinados y la mayoría de pacientes tienen que recurrir a terapias tradicionales. Una de las estrategias más prometedoras para la mejora y el desarrollo de terapias anticáncer está basada en la explotación de dependencias secundarias, no necesariamente oncogénicas, conocidas como interacciones de letalidad sintética (SL). Se sabe que las células cancerígenas tienen mecanismos de compensación que les ayudan a sobrevivir en el caso de acumular mutaciones en genes críticos, desarrollando dependencias para con dichos genes en muchos de estos casos. El concepto de letalidad sintética surge con la finalidad de aprovechar estas compensaciones y así afectar la viabilidad de la célula tumoral. Utilizando pruebas de detección masivas a lo largo de paneles de líneas celulares tumorales, algunos grupos de investigación han explorado los efectos del silenciamiento de genes y su relación con el comportamiento fenotípico de la célula, detectando dependencias en células cancerígenas. En este proyecto, hemos integrado la información recogida en diversas bases de datos dedicadas a la recolección de interacciones de letalidad sintética, con información de mutaciones puntuales, alteraciones en número de copia y silenciamiento génico. 9 A partir de este análisis se han podido identificar nuevas dianas terapéuticas y biomarcadores predictivos de respuesta en cáncer. En concreto, hemos partido de más de 16 mil interacciones de letalidad sintética y analizado aquellas con opciones terapéuticas disponibles (un 34% del total). La exploración de estas interacciones nos ha llevado a la obtención de nuevas estrategias terapéuticas que involucran a oncogenes sin disponibilidad de tratamientos dirigidos como KRAS o genes supresores de tumores como BRCA. Además, nos ha ayudado a profundizar en los mecanismos biológicos que se encuentran detrás de estos eventos. Para completar ese análisis será necesario integrar más fuentes de información como datos de expresión, metilación, así como explorar los efectos de la inhibición farmacológica de estas dianas. Añadiendo la estrategia de letalidad sintética a las ya existentes, podemos avanzar en la definición de los subtipos de cáncer y su tratamiento mediante terapias dirigida

Avances en medicina personalizada: una aproximación basada en secuenciación de células únicas para tratar la heterogeneidad tumoral

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de Lectura: 23-06-202

Kras oncogene ablation prevents resistance in advanced lung adenocarcinomas

KRASG12C inhibitors have revolutionized the clinical management of patients with KRASG12C-mutant lung adenocarcinoma. However, patient exposure to these inhibitors leads to the rapid onset of resistance. In this study, we have used genetically engineered mice to compare the therapeutic efficacy and the emergence of tumor resistance between genetic ablation of mutant Kras expression and pharmacological inhibition of oncogenic KRAS activity. Whereas Kras ablation induces massive tumor regression and prevents the appearance of resistant cells in vivo, treatment of KrasG12C/Trp53-driven lung adenocarcinomas with sotorasib, a selective KRASG12C inhibitor, caused a limited antitumor response similar to that observed in the clinic, including the rapid onset of resistance. Unlike in human tumors, we did not observe mutations in components of the RAS-signaling pathways. Instead, sotorasib-resistant tumors displayed amplification of the mutant Kras allele and activation of xenobiotic metabolism pathways, suggesting that reduction of the on-target activity of KRASG12C inhibitors is the main mechanism responsible for the onset of resistance. In sum, our results suggest that resistance to KRAS inhibitors could be prevented by achieving a more robust inhibition of KRAS signaling mimicking the results obtained upon Kras ablation.This work was supported by grants from the European Research Council (ERC-GA 695566, THERACAN); the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033) (grant RTC2017-6576-1), cofunded by ERDF “A way of making Europe”; the Autonomous Community of Madrid (B2017/BMD-3884 iLung-CM), cofunded by FSE and ERDF “A way of making Europe”; the CRIS Cancer Foundation, the Scientific Foundation of the Spanish Association Against Cancer (GC166173694BARB); an ERA PerMed grant, funded by the Instituto de Salud Carlos III (AC20/00114), the Scientific Foundation of the Spanish Association Against Cancer (PERME20707BARB) and the European Union’s Horizon 2020 program (779282) to MB; and the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (grant RTI2018-094664-B-I00), cofunded by ERDF “A way of making Europe” to MM and MB. Additional funding included grants from the Spanish National Research and Development Plan, Instituto de Salud Carlos III, ERDF “A way of making Europe” (PI20/01837 and DTS19/00111); the Scientific Foundation of the Spanish Association Against Cancer (LABAE20049RODR) to SRP; the Instituto de Salud Carlos III (PI19/00514), cofunded by ERDF “A way of making Europe” to CG; the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación (grant PID2020-116705RB-I00); and the Scientific Foundation of the Spanish Association Against Cancer (LABAE211678DROS) to MD. MB is a recipient of an endowed chair from the AXA Research Fund. M Salmón was supported by a predoctoral contract “Severo Ochoa” (BES-2016-079096) from the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación. OB is a recipient of a fellowship from the Formación de Personal Investigador (FPI) program of the Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación. FFG was supported by a Formación de Profesorado Universitario (FPU) fellowship from the Ministerio de Universidades

Immunophenotype and Transcriptome Profile of Patients With Multiple Sclerosis Treated With Fingolimod: Setting Up a Model for Prediction of Response in a 2-Year Translational Study

BackgroundFingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug. In MS patients, we aimed to clarify the differential effects of fingolimod on T, B, and natural killer (NK) cell subsets and to identify differentially expressed genes in responders and non-responders (NRs) to treatment.Materials and methodsSamples were obtained from relapsing–remitting multiple sclerosis patients before and 6 months after starting fingolimod. Forty-eight lymphocyte subpopulations were measured by flow cytometry based on surface and intracellular marker analysis. Transcriptome sequencing by next-generation technologies was used to define the gene expression profiling in lymphocytes at the same time points. NEDA-3 (no evidence of disease activity) and NEDA-4 scores were measured for all patients at 1 and 2 years after beginning fingolimod treatment to investigate an association with cellular and molecular characteristics.ResultsFingolimod affects practically all lymphocyte subpopulations and exerts a strong effect on genetic transcription switching toward an anti-inflammatory and antioxidant response. Fingolimod induces a differential effect in lymphocyte subpopulations after 6 months of treatment in responder and NR patients. Patients who achieved a good response to the drug compared to NR patients exhibited higher percentages of NK bright cells and plasmablasts, higher levels of FOXP3, glucose phosphate isomerase, lower levels of FCRL1, and lower Expanded Disability Status Scale at baseline. The combination of these possible markers enabled us to build a probabilistic linear model to predict the clinical response to fingolimod.ConclusionMS patients responsive to fingolimod exhibit a recognizable distribution of lymphocyte subpopulations and a different pretreatment gene expression signature that might be useful as a biomarker

Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma

The mechanisms triggering metastasis in pheochromocytoma/paraganglioma are unknown, hindering therapeutic options for patients with metastatic tumors (mPPGL). Herein we show by genomic profiling of a large cohort of mPPGLs that high mutational load, microsatellite instability and somatic copy-number alteration burden are associated with ATRX/TERT alterations and are suitable prognostic markers. Transcriptomic analysis defines the signaling networks involved in the acquisition of metastatic competence and establishes a gene signature related to mPPGLs, highlighting CDK1 as an additional mPPGL marker. Immunogenomics accompanied by immunohistochemistry identifies a heterogeneous ecosystem at the tumor microenvironment level, linked to the genomic subtype and tumor behavior. Specifically, we define a general immunosuppressive microenvironment in mPPGLs, the exception being PD-L1 expressing MAML3-related tumors. Our study reveals canonical markers for risk of metastasis, and suggests the usefulness of including immune parameters in clinical management for PPGL prognostication and identification of patients who might benefit from immunotherapy

Stratification of radiosensitive brain metastases based on an actionable S100A9/RAGE resistance mechanism

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Whole-brain radiotherapy (WBRT) is the treatment backbone for many patients with brain metastasis; however, its efficacy in preventing disease progression and the associated toxicity have questioned the clinical impact of this approach and emphasized the need for alternative treatments. Given the limited therapeutic options available for these patients and the poor understanding of the molecular mechanisms underlying the resistance of metastatic lesions to WBRT, we sought to uncover actionable targets and biomarkers that could help to refine patient selection. Through an unbiased analysis of experimental in vivo models of brain metastasis resistant to WBRT, we identified activation of the S100A9-RAGE-NF-κB-JunB pathway in brain metastases as a potential mediator of resistance in this organ. Targeting this pathway genetically or pharmacologically was sufficient to revert the WBRT resistance and increase therapeutic benefits in vivo at lower doses of radiation. In patients with primary melanoma, lung or breast adenocarcinoma developing brain metastasis, endogenous S100A9 levels in brain lesions correlated with clinical response to WBRT and underscored the potential of S100A9 levels in the blood as a noninvasive biomarker. Collectively, we provide a molecular framework to personalize WBRT and improve its efficacy through combination with a radiosensitizer that balances therapeutic benefit and toxicity.info:eu-repo/semantics/publishedVersio

Reactive Astrocytes in Brain Metastasis

Brain metastasis, the secondary growth of malignant cells within the central nervous system (CNS), exceeds the incidence of primary brain tumors (i.e., gliomas) by tenfold and are seemingly on the rise owing to the emergence of novel targeted therapies that are more effective in controlling extracranial disease relatively to intracranial lesions. Despite the fact that metastasis to the brain poses a unmet clinical problem, with afflicted patients carrying significant morbidity and a fatal prognosis, our knowledge as to how metastatic cells manage to adapt to the tissue environment of the CNS remains limited. Answering this question could pave the way for novel and more specific therapeutic modalities in brain metastasis by targeting the specific makeup of the brain metastatic niche. In regard to this, astrocytes have emerged as the major host cell type that cancer cells encounter and interact with during brain metastasis formation. Similarly to other CNS disorders, astrocytes become reactive and respond to the presence of cancer cells by changing their phenotype and significantly influencing the outcome of disseminated cancer cells within the CNS. Here, we summarize the current knowledge on the contribution of reactive astrocytes in brain metastasis by focusing on the signaling pathways and types of interactions that play a crucial part in the communication with cancer cells and how these could be translated into innovative therapies

Lipoxin A 4 prevents tight junction disruption and delays the colonization of cystic fibrosis bronchial epithelial cells by Pseudomonas aeruginosa

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PD-L1ATTAC mice reveal the potential of depleting PD-L1 expressing cells in cancer therapy.

Antibodies targeting the PD-1 receptor and its ligand PD-L1 have shown impressive responses in some tumors of bad prognosis. We hypothesized that, since immunosuppressive cells might present several immune checkpoints on their surface, the selective elimination of PD-L1 expressing cells could be efficacious in enabling the activation of antitumoral immune responses. To address this question, we developed an inducible suicidal knock-in mouse allele of Pd-l1 (PD-L1ATTAC) which allows for the tracking and specific elimination of PD-L1-expressing cells in adult tissues. Consistent with our hypothesis, elimination of PD-L1 expressing cells from the mouse peritoneum increased the septic response to lipopolysaccharide (LPS), due to an exacerbated inflammatory response to the endotoxin. In addition, mice depleted of PD-L1+ cells were resistant to colon cancer peritoneal allografts, which was associated with a loss of immunosuppressive B cells and macrophages, concomitant with an increase in activated cytotoxic CD8 T cells. Collectively, these results illustrate the usefulness of PD-L1ATTAC mice for research in immunotherapy and provide genetic support to the concept of targeting PD-L1 expressing cells in cancer.O.F-C. is supported by grants from the Spanish Ministry of Science, Innovation and Universities (PID2021- 128722OB-I00, co-financed with European FEDER funds) and the Spanish Association Against Cancer (AECC; PROYE20101FERN) to O.F-C. and by a Ph.D. fellowship from Mar?a Oliva-Amigos/as del CNIO to E.F-M. The CNIO Bioinformatics Unit (BU) is a member of the Spanish National Bioinformatics Institute (INB) , ISCIII- Bioinformatics platform and is supported by grant PT17/0009/0011, of the Accion Estrategica en Salud 2013-2016 of the Programa Estatal de Investigacion Orientada a los Retos de la Sociedad, funded by the ISCIII and European Regional Development Fund (ERDF-EU) and project RETOS RTI2018-097596-B-I00 funded by AEI-MCIU and cofounded by the ERDF-EU. The authors declare no competing financial interests.S