In silico drug prescription for targeting cancer patient heterogeneity and prediction of clinical outcome

In silico drug prescription tools for precision cancer medicine can match molecular alterations with tailored candidate treatments. These methodologies require large and well-annotated datasets to systematically evaluate their performance, but this is currently constrained by the lack of complete patient clinicopathological data. Moreover, in silico drug prescription performance could be improved by integrating additional tumour information layers like intra-tumour heterogeneity (ITH) which has been related to drug response and tumour progression. PanDrugs is an in silico drug prescription method which prioritizes anticancer drugs combining both biological and clinical evidence. We have systematically evaluated PanDrugs in the Genomic Data Commons repository (GDC). Our results showed that PanDrugs is able to establish an a priori stratification of cancer patients treated with Epidermal Growth Factor Receptor (EGFR) inhibitors. Patients labelled as responders according to PanDrugs predictions showed a significantly increased overall survival (OS) compared to non-responders. PanDrugs was also able to suggest alternative tailored treatments for non-responder patients. Additionally, PanDrugs usefulness was assessed considering spatial and temporal ITH in cancer patients and showed that ITH can be approached therapeutically proposing drugs or combinations potentially capable of targeting the clonal diversity. In summary, this study is a proof of concept where PanDrugs predictions have been correlated to OS and can be useful to manage ITH in patients while increasing therapeutic options and demonstrating its clinical utilityThis work was supported by the Instituto de Salud Carlos III (ISCIII); Marie-Curie Career Integration Grant (CIG334361); and Paradifference Foundatio

Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma

Adrenal gland diseases; Cancer genomics; Prognostic markersMalalties de les glàndules suprarenals; Genòmica del càncer; Marcadors pronòsticsEnfermedades de las glándulas suprarrenales; Genómica del cáncer; Marcadores pronósticosThe 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.This work was supported by Project PI17/01796 and PI20/01169 to M.R. [Instituto de Salud Carlos III (ISCIII), Acción Estratégica en Salud, cofinanciado a través del Fondo Europeo de Desarrollo Regional (FEDER)], Paradifference Foundation [no grant number applicable to M.R.], Pheipas Association [no grant number applicable to M.R.], the Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE to F.B., the Deutsche Forschungsgemeinschaft (DFG) within the CRC/Transregio 205/1 (Project No. 314061271-TRR205 to to F.B., M.F., N.B., and G.E.) and the Instituto de Salud Carlos III (ISCIII), Spanish Ministry of Science and Innovation (Project No. PID2019-111356RA-I00 to G.M.). B.C. was supported by the Rafael del Pino Foundation (Becas de Excelencia Rafael del Pino 2017). A.M.M.-M. was supported by CAM (S2017/BMD-3724; TIRONET2-CM). A.F.-S. and J.L. received the support of a fellowship from La Caixa Foundation (ID 100010434; LCF/BQ/DR21/11880009 and LCF/BQ/DR19/11740015, respectively). M.M., S.M., and M.S. were supported by the Spanish Ministry of Science, Innovation and Universities “Formación del Profesorado Universitario— FPU” fellowship with ID number FPU18/00064, FPU19/04940 and FPU16/05527. A.D.-T. is supported by the Centro de Investigacion Biomédica en Red de Enfermedades Raras (CIBERER). L.J.L.-G. was supported both by the Banco Santander Foundation and La Caixa Postdoctoral Junior Leader Fellowship (LCF/BQ/PI20/11760011). C.M.-C. was supported by a grant from the AECC Foundation (AIO15152858 MONT). We thank the Spanish National Tumor Bank Network (RD09/0076/00047) for the support in obtaining tumorsamples and all patients, physicians and tumor biobanks involved in the study

PanDrugs2: prioritizing cancer therapies using integrated individual multi-omics data

Genomics studies routinely confront researchers with long lists of tumor alterations detected in patients. Such lists are difficult to interpret since only a minority of the alterations are relevant biomarkers for diagnosis and for designing therapeutic strategies. PanDrugs is a methodology that facilitates the interpretation of tumor molecular alterations and guides the selection of personalized treatments. To do so, PanDrugs scores gene actionability and drug feasibility to provide a prioritized evidence-based list of drugs. Here, we introduce PanDrugs2, a major upgrade of PanDrugs that, in addition to somatic variant analysis, supports a new integrated multi-omics analysis which simultaneously combines somatic and germline variants, copy number variation and gene expression data. Moreover, PanDrugs2 now considers cancer genetic dependencies to extend tumor vulnerabilities providing therapeutic options for untargetable genes. Importantly, a novel intuitive report to support clinical decision-making is generated. PanDrugs database has been updated, integrating 23 primary sources that support >74K drug–gene associations obtained from 4642 genes and 14 659 unique compounds. The database has also been reimplemented to allow semi-automatic updates to facilitate maintenance and release of future versions. PanDrugs2 does not require login and is freely available at https://www.pandrugs.org/.Instituto de Salud Carlos III | Ref. IMP/00019Agencia Estatal de Investigacion | Ref. PID2021-124188NB-I00Xunta de Galicia | Ref. | Ref. ED431C2018/55Xunta de Galicia | Ref. | Ref. ED431C2022/0

Observations in the Spanish Mediterranean Waters: A Review and Update of Results of 30-Year Monitoring

The Instituto Español de Oceanografía (IEO, Spanish Institute of Oceanography) has maintained different monitoring programs in the Spanish Mediterranean waters (Western Mediterranean) since 1992. All these monitoring programs were unified in 2007 under the current program RADMED (series temporales de datos oceanográficos en el Mediterráneo), which is devoted to the in situ multidisciplinary sampling of the water column of coastal and open-sea waters by means of periodic oceanographic campaigns. These campaigns, together with a network of tide-gauges, are part of the IEO Observing system (IEOOS). In some cases, the temperature and salinity time series collected in the frame of these monitoring programs are now more than 30 years long, whereas sea level time series date to the beginning of the 1940s. This information has been complemented with international databases and has been analyzed in numerous works by the Grupo mediterráneo de Cambio Climático (GCC; Mediterranean Climate Change Group) for more than 20 years. These works have been devoted to the detection and quantification of the changes that climate change is producing on the physical, chemical, and biological properties of the Spanish Mediterranean waters. In this work, we review the results obtained by the GCC since 2005 in relation to the changes in the physical properties of the sea: water column temperature, salinity, and density, heat content, mixed layer depth, and sea level. Time series and results are updated from the last works, and the reliability of the existing time series for the detection of climatologies and long-term trends are analyzed. Furthermore, the different sources of uncertainty in the estimation of linear trends are considered in the present work. Besides this review and update of the results obtained from the data collected in the frame of the IEOOS, we conduct a review of the existing monitoring capabilities from other institutions in the Spanish Mediterranean waters and a review of results dealing with climate change in the Spanish Mediterranean obtained by such institutions. In particular, we include a review of the results obtained by SOCIB (Servicio de Observación y Predicción Costero de las Islas Baleares; Balearic Islands costal observing and forecasting system) in relation to the study of marine heat waves and the warming of the sea surface, and the results corresponding to the intense warming of the Catalan continental shelf at L’Estartit oceanographic station. All these results evidence that the surface Spanish Mediterranean waters are warming up at a rate higher than that affecting the global ocean (>2 °C/100 years). This warming and a salinity increase are also observed along the whole water column. Marine heat waves are increasing their intensity, frequency, and duration since 1982, and coastal sea level is increasing at a rate of 2.5 mm/yr. The salinity increase seems to have compensated for the warming, at least at surface and intermediate waters where no significant trends have been detected for the density. This could also be the reason for the lack of significant trends in the evolution of the mixed layer depth. All these results highlight the importance of monitoring the water column and the necessity of maintaining in situ sampling programs, which are essential for the study of changes that are occurring throughout the Spanish Mediterranean waters

PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data

BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. RESULTS: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. CONCLUSIONS: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org .The authors thank Joaquín Dopazo, Patricia León, and José Carbonell for kindly providing the modelled pathways employed in PanDrugs implementation; and Michael Tress for his helpful comments and suggestions in the earlier version of the manuscript.S

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

Oncogenic Rag GTPase signalling enhances B cell activation and drives follicular lymphoma sensitive to pharmacological inhibition of mTOR

The humoral immune response requires that B cells undergo a sudden anabolic shift and high cellular nutrient levels, which are required to sustain the subsequent proliferative burst. Follicular lymphoma (FL) originates from B cells that have participated in the humoral response, and 15% of FL samples harbour point-activating mutations in RRAGC, an essential activator of mTORC1 downstream of the sensing of cellular nutrients. The impact of recurrent RRAGC mutations in B cell function and lymphoma is unexplored. RRAGC mutations, targeted to the endogenous locus in mice, confer a partial insensitivity to nutrient deprivation, but strongly exacerbate B cell responses and accelerate lymphomagenesis, while creating a selective vulnerability to pharmacological inhibition of mTORC1. This moderate increase in nutrient signalling synergizes with paracrine cues from the supportive T cell microenvironment that activate B cells via the PI3K–Akt–mTORC1 axis. Hence, Rragc mutations sustain induced germinal centres and murine and human FL in the presence of decreased T cell help. Our results support a model in which activating mutations in the nutrient signalling pathway foster lymphomagenesis by corrupting a nutrient-dependent control over paracrine signals from the T cell microenvironment.Research was supported by the RETOS projects Programme of Spanish Ministry of Science, Innovation and Universities, Spanish State Research Agency, cofunded by the European Regional Development Fund (grant SAF2015-67538-R), EU-H2020 Programme (ERC-2014-STG-638891), Excellence Network Grant from MICIU/AEI (SAF2016-81975-REDT), a Ramon y Cajal Award from MICIU/AEI (RYC-2013-13546), Spanish Association Against Cancer Research Scientific Foundation Laboratory Grant, Beca de Investigación en Oncología Olivia Roddom, FERO Grant for Research in Oncology; Miguel Servet Fellowship and Grant Award (MS16/00112 and CP16/00112) and Project PI18/00816 within the Health Strategic Action from the ISCIII (to A.O.-M.), both cofunded by the European Regional Development Fund, Marcos Fernandez Fellowship from the Spanish Leukaemia and Lymphoma Foundation/Vistare Foundation (to A.O.-M.) and L’Oreal For Women in Science Award (to A.O.-M.). J.F. is a recipient of a Cancer Research UK Programme Award (15968) and J.O. is a recipient of a Cancer Research UK Clinician Scientist Fellowship (22742). N.M.-M. is a Ramon y Cajal Awardee MICIU/AEI (RYC-2016-20173). N.D.-S., C.C.A., A.B.P.-G. and K.T. are recipients of Ayudas de contratos predoctorales para la formacion de doctores from MICIU/AEI (BES-2016-077410, BES-2015-073776, BES-2017−081381, BES-2016-078082).Peer reviewe

A user guide for the online exploration and visualization of PCAWG data.

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: Ontario Institute for Cancer Research (Institut Ontarien de Recherche sur le Cancer); doi: https://doi.org/10.13039/100012118Funder: EMBL Member States EU FP7 Programme projects EurocanPlatform (260791) CAGEKID (241669)Funder: European Union’s Framework Programme For Research and Innovation Horizon 2020 under the Marie Sklodowska-Curie grant agreement no. 703543Funder: Michael & Susan Dell Foundation; Mary K. Chapman Foundation; CCSG Grant P30 CA016672 (Bioinformatics Shared Resource); ITCR U24 CA199461; GDAN U24 CA210949; GDAN U24 CA210950Funder: European Commission's H2020 Programme, project SOUND, Grant Agreement no 633974Funder: Spanish Government (SEV 2015-0493) BSC-Lenovo Master Collaboration Agreement (2015)The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Desarrollo de estrategias de priorización de fármacos para tratar los genomas de cáncer en la medicina de precisión

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 28-04-2021Precision oncology requires the definition of a distinctive molecular fingerprint of the patient, as well as a pharmacological arsenal with the agents capable of reversing the associated pathogenic phenotype. One of the tools for molecular characterization is massive genomic sequencing, used with different objectives, including to provide evidence to identify specific and effective treatments. However, this technology entails several difficulties in its management, for example, distinguishing between harmful and benign alterations, as well as pointing out those that may indicate treatment guidelines. On the other hand, the available pharmacological arsenal is limited, so strategies are required to maximize its utility and the integration of available experimental compounds. The methodology of in silico prescription developed in this thesis, which we have named PanDrugs, has been conceived to contribute to overcoming these difficulties. For this purpose, we have built an extensive database of drug-gene associations as a search basis and a double prioritization system: (i) of genomic events according to their oncological impact and consequent therapeutic potential, (ii) and of drugs according to their availability and suitability in the detected molecular context. In order to determine its capabilities, it has been analyzed in several scenarios using different combinations of molecular evidence. In order to characterize in general terms the potential spectrum of therapeutic action in the different types of tumors, it has been systematically applied to several cases of the TCGA (The Cancer Genome Atlas). It has also been used in individual patients at a higher resolution, dissecting the proposed therapeutic suggestions at a molecular level, where it has been able to prioritize coherent options both at the level of sensitivity and resistance. It has demonstrated its potential for proposing therapeutic alternatives to conventional treatments in a clinical study of acute lymphoblastic T-cell leukemia with previous therapeutic failure. And finally, it has shown predictive capacity in the response to EGFR inhibitors in cases with available clinical informatio