Estimativa do intervalo de tempo entre as paradas de decoking em fornos de pirólise

Tubes operating in the pyrolysis of organic substances suffer structural degradation resulting from carburizing mechanisms that, in general, take the failures of the tubes. The lifetime of the tubes that operate in the process ranges from 10,000 hours to 40,000 hours depending on the degree of carburizing suffered during pyrolysis. This work had as objective to estimate the time interval between stops of decoking, relating the following variables: carbon diffusion, temperature, ferromagnetism and microstructure formed. There was a correlation between the thickness of carburized and its magnetic field generated by the new intermetallic components. The results indicated that for pipes operating at a temperature of 1050 degrees Celsius, and operating time up to 10.000h, the average time suggested stops is 435 hours. As for a tube that runs between 10,000 hours and 20,000 hours, the average time suggested is 370 hours. The estimated time between decoking the charts should be used as a complementary tool to the operator control, and not as the sole measure of the process.Key words: carburization, pyrolysis, life of equipments.Os tubos que operam na pirólise de substâncias orgânicas sofrem degradação estrutural resultante dos mecanismos de carburização que, em geral, levam a falhas dos tubos. O tempo de vida dos tubos que operam no processo varia desde 10.000 horas até 40.000 horas, dependendo do grau de carburização sofrido durante a pirólise. Este trabalho teve como objetivo estimar o intervalo de tempo entre as paradas de decoking, relacionando as seguintes variáveis: difusão do carbono, temperatura, ferromagnetismo e a microestrutura formada. Foi realizada uma correlação entre a espessura carburizada e o respectivo campo magnético gerado pelos novos componentes intermetálicos. Os resultados indicaram que, para tubos que operam numa temperatura de 1050 graus Celsius, e tempo de operação até 10.000h, o tempo médio sugerido de paradas é de 435 horas. Já para um tubo que opera entre 10.000 horas e 20.000 horas, o tempo médio sugerido é de 370 horas. A estimativa do intervalo de tempo entre as paradas de decoking deve ser utilizada como uma ferramenta complementar ao controle do operador, e não como única medida do processo.Palavras-chave: carburização, pirólise, vida útil de equipamentos

Intermediate Molecular Phenotypes to Identify Genetic Markers of Anthracycline-Induced Cardiotoxicity Risk.

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex trait with a polygenic component that is mainly unidentified. We propose that levels of intermediate molecular phenotypes (IMPs) in the myocardium associated with histopathological damage could explain CDA susceptibility, so variants of genes encoding these IMPs could identify patients susceptible to this complication. Thus, a genetically heterogeneous cohort of mice (n = 165) generated by backcrossing were treated with doxorubicin and docetaxel. We quantified heart fibrosis using an Ariol slide scanner and intramyocardial levels of IMPs using multiplex bead arrays and QPCR. We identified quantitative trait loci linked to IMPs (ipQTLs) and cdaQTLs via linkage analysis. In three cancer patient cohorts, CDA was quantified using echocardiography or Cardiac Magnetic Resonance. CDA behaves as a complex trait in the mouse cohort. IMP levels in the myocardium were associated with CDA. ipQTLs integrated into genetic models with cdaQTLs account for more CDA phenotypic variation than that explained by cda-QTLs alone. Allelic forms of genes encoding IMPs associated with CDA in mice, including AKT1, MAPK14, MAPK8, STAT3, CAS3, and TP53, are genetic determinants of CDA in patients. Two genetic risk scores for pediatric patients (n = 71) and women with breast cancer (n = 420) were generated using machine-learning Least Absolute Shrinkage and Selection Operator (LASSO) regression. Thus, IMPs associated with heart damage identify genetic markers of CDA risk, thereby allowing more personalized patient management.J.P.L.’s lab is sponsored by Grant PID2020-118527RB-I00 funded by MCIN/AEI/10.13039/ 501100011039; Grant PDC2021-121735-I00 funded by MCIN/AEI/10.13039/501100011039 and by the “European Union Next Generation EU/PRTR”, the Regional Government of Castile and León (CSI144P20). J.P.L. and P.L.S. are supported by the Carlos III Health Institute (PIE14/00066). AGN laboratory and human patients’ studies are supported by an ISCIII project grant (PI18/01242). The Human Genotyping unit is a member of CeGen, PRB3, and is supported by grant PT17/0019 of the PE I + D + i 2013–2016, funded by ISCIII and ERDF. SCLl is supported by MINECO/FEDER research grants (RTI2018-094130-B-100). CH was supported by the Department of Defense (DoD) BCRP, No. BC190820; and the National Cancer Institute (NCI) at the National Institutes of Health (NIH), No. R01CA184476. Lawrence Berkeley National Laboratory (LBNL) is a multi-program national laboratory operated by the University of California for the DOE under contract DE AC02-05CH11231. The Proteomics Unit belongs to ProteoRed, PRB3-ISCIII, supported by grant PT17/0019/0023 of the PE I + D +i, 2017–2020, funded by ISCIII and FEDER. RCC is funded by fellowships from the Spanish Regional Government of Castile and León. NGS is a recipient of an FPU fellowship (MINECO/FEDER). hiPSC-CM studies were funded in part by the “la Caixa” Banking Foundation under the project code HR18-00304 and a Severo Ochoa CNIC Intramural Project (Exp. 12-2016 IGP) to J.J.S

Estimativa do intervalo de tempo entre as paradas de decoking em fornos de pirólise

Os tubos que operam na pirólise de substâncias orgânicas sofrem degradação estrutural resultante dos mecanismos de carburização que, em geral, levam a falhas dos tubos. O tempo de vida dos tubos que operam no processo varia desde 10.000 horas até 40.000 horas, dependendo do grau de carburização sofrido durante a pirólise. Este trabalho teve como objetivo estimar o intervalo de tempo entre as paradas de decoking, relacionando as seguintes variáveis: difusão do carbono, temperatura, ferromagnetismo e a microestrutura formada. Foi realizada uma correlação entre a espessura carburizada e o respectivo campo magnético gerado pelos novos componentes intermetálicos. Os resultados indicaram que, para tubos que operam numa temperatura de 1050 graus Celsius, e tempo de operação até 10.000h, o tempo médio sugerido de paradas é de 435 horas. Já para um tubo que opera entre 10.000 horas e 20.000 horas, o tempo médio sugerido é de 370 horas. A estimativa do intervalo de tempo entre as paradas de decoking deve ser utilizada como uma ferramenta complementar ao controle do operador, e não como única medida do processo.Tubes operating in the pyrolysis of organic substances suffer structural degradation resulting from carburizing mechanisms that, in general, take the failures of the tubes. The lifetime of the tubes that operate in the process ranges from 10,000 hours to 40,000 hours depending on the degree of carburizing suffered during pyrolysis. This work had as objective to estimate the time interval between stops of decoking, relating the following variables: carbon diffusion, temperature, ferromagnetism and microstructure formed. There was a correlation between the thickness of carburized and its magnetic field generated by the new intermetallic components. The results indicated that for pipes operating at a temperature of 1050 degrees Celsius, and operating time up to 10.000h, the average time suggested stops is 435 hours. As for a tube that runs between 10,000 hours and 20,000 hours, the average time suggested is 370 hours. The estimated time between decoking the charts should be used as a complementary tool to the operator control, and not as the sole measure of the process

Analysis of genetic and phenotypic interactions between DNA damage / genotoxicity pathways in heart tissue and heart damage caused by anthracyclines and taxanes

Resumen del póster presentado al XXXIX Congreso de la Sociedad Española de Bioquímica y Biología Molecular, celebrado en Salamanca del 5 al 8 de septiembre de 2016.[Introduction]: Anthracyclines are among the most widely used chemotherapeutic agents in the treatment of a variety of tumors. The identification of genetic and molecular factors responsible for the increased risk of CDA (cardiotoxicity due to anthracyclines) will contribute to a better understanding of their pathophysiology, which could lead to new approaches to predict, prevent and treat this serious complication of chemotherapy. [Working hypothesis]: Based on two premises: (i) anthracyclines have a pro-genotoxicity effect. Differences in anti-genotoxicity pathways and genetic variants could contribute to different susceptibility to CDA. (ii) The usefulness of a simplified model system to identify genetic determinants involved in the quantitative inheritance of complex traits. [Materials and methods]: We treated a cohort of mice carrying ERBB2 breast cancer with doxorubicin alone (N = 85) or in combination with docetaxel (N = 77). The cohort was generated by a backcross between two genetically homogeneous strains, C57BL/6 and FVB, with the latter carrying the MMTV- ErbB2 / Neu transgene. Histopathologic heart damage was assessed by quantification of histologic parameters using Ariol automated system. Cardiac level of some key anti-genotoxicity proteins: ATR total, pp53 (Ser15), P21 Total, Total MDM2, pHistone H2AX (Ser139), pCHK1 (Ser345) and pCHK2 (Thr68) were quantified. [Results]: We identified: (i) differences dependent on the genetic background in both cardiotoxicity and the levels of proteins implicated in the pathways protecting against genotoxicity; (ii) activation of anti-genotoxicity pathways were associated with chemotherapy cardiotoxicity; (iii) quantitative trait loci (QTLs) specific and common to cardiotoxicity and the levels of the pathways studied. [Conclusion]: We identified genetic determinants associated with anthracycline cardiotoxicity using components of the anti-genotoxic pathways as subphenotypes. Crosses of syngeneic mouse strains are useful in these studies, but require further validation in the human population.Peer reviewe

Identification of genetic and molecular determinants associated with cardiotoxicity by anthracyclines and taxanes according to age

Resumen del trabajo presentado al 5th Symposium on Biomedical Research: "Advances and Perspectives In Pharmacology, Drug Toxicity and Pharmacogenetics", celebrado en Madrid del 15 al 16 de marzo de 2018.[Introduction]: Cardiotoxicity due to anthracyclines (CDA) is a very common problem in cancer patients, with great repercussion on their quality of life, which limits chemotherapy treatment and has consequences in the final prognosis of the oncologic disease itself. The susceptibility and degree of cardiotoxicity by anthracyclines is very heterogeneous among patients, and who will suffer this complication is unknown. CDA is a complex trait, thus follows a model of quantitative genetics, whose polygenic component is mostly unidentified. In addition, as a complex trait, CDA heterogeneity is explained by the variability among subphenotypes that would participate in its pathogenesis. Thus, anthracyclines exert their toxicity through DNA damage, so that among these subphenotypes would be the molecular pathways involved in the response to it, and a series of signaling pathways that promote and others that protect from that heart damage anthracyclines have a pro-genotoxicity effect. Differences in these pathways with the genetic variants linked with them could contribute to different susceptibility to CDA among individuals.[Material and Methods]: we identified the genetic and molecular determinants of cardiotoxicity in a simplified model of controlled genetic and phenotypic heterogeneity, generated by a backcross of two mouse strains of divergent phenotypic behavior, FVB and C57BL/6. We evaluated cardiac damage at histopathological level and also quantified different subphenotypes such as signaling pathways associated with cardiac damage and protection, genotoxicity pathways, TGFβ levels, telomere length, and expression of miRNAs in the myocardium.[Results]: We quantified anthracycline cardiotoxicity in a heterogeneous cohort of mice with breast cancer generated by a backcross. Cardiotoxicity was higher in old mice, was higher in the combined treatment with taxanes, was higher in the subendocardial zone and was influenced by the genetic background. We have identified multiple QTL associated with CDA in these different conditions studied. Differences in the grade of anthracycline cardiotoxicity at the histopathological level were accompanied by differences in the molecular levels in the myocardium of different molecular components of the pathways of response to damage at DNA, signaling pathways, miRNAs and telomere length. QTLs associated with these subphenotypes help to define CDA variability. Lastly, we have also defined CDA by multivariate models.[Conclusion]: The identification of genetic and molecular factors responsible for the increased risk of CDA will contribute to a better understanding of their pathophysiology, which could lead to new approaches to predict, prevent and treat this serious complication of chemotherapy.JPL was partially supported by FEDER and the MICINN (SAF2014-56989-R, SAF2017-88854R), the Instituto de Salud Carlos III (PIE14/00066), “Proyectos Integrados IBSAL 2015” (IBY15/00003), the Sandra Ibarra Foundation “de Solidaridad Frente al Cáncer” Foundation and “We can be heroes” Foundation.Peer reviewe

Datasets related to a study aimed to identify genetic markers of CDA by subphenotypes associated with cardiotoxicity

Who produced the data? The data has been created by the authors listed above. Is the title specific enough? "Datasets related to a study aimed to identify genetic markers of CDA by subphenotypes associated with cardiotoxicity." Why has the data been created? These datasets are supplementary material with which the principal and supplementary figures and tables of our indicated work were generated. What limitations do the data have (for example, sensitive data has been deleted)? All confidential patient information is not present. We have not had access to that information, following current legal regulations. How should the data be interpreted? These data sets should not be separated from the main article in which they were utilized. Thus, to better understand their context, researchers should see them in the global scenario of our work. Are there gaps in the data, or do they give a complete picture of the topic studied? As indicated above, data should be considered and interpreted in the global context of our study. What processes have generated the data? The processes that generated the data are indicated in the summary of the data above and individually for each of them. Thus, each dataset is accompanied by a legend within the document. What does the data measure in the columns of the files? As indicated, each dataset individually shows the information contained in the legend of each dataset. What software is required to be able to read the data? The datasets are in Excel format. How should the data be quoted? Researchers should cite the data in the context of the work they belong to once it is published and free of the embargo. Can the data be reused? What use licenses are assigned to you? In principle, yes. If additional clinical information is required, these data were previously published by some of us, and the references are included in our manuscript. These data are available from the principal investigators of the references listed in our work upon reasonable request. Are there more versions of the data? Where? I do not think so beyond our files and copies. Have the technical terms and acronyms referenced by the data been defined? A legend with the appropriate descriptions accompanies each dataset. Have the geographic and chronological parameters of the data been qualified? The authors of the work have generated the data. Elsewhere, we indicate the authors of the work, their contributions, and affiliations. Are keywords sufficiently data-specific? Are they based on any thesaurus? Keywords are based on our study. We include cardiotoxicity due to anthracyclines, missing heritability, subphenotype, pathophenotype, complex trait. What is the name of the research project in which the data are framed? The main research project in which the data is prepared is: Títle: "Chemotherapy cardiotoxicity in the elderly: a translational and personnel approach." Ref.: PIE14/00066 Who has financed data production and management? Each of the authors of the study has its funding. The grants are included in the acknowledgments section of our manuscript.Here we present a series of supplemental datasets that complement our study entitled "A Systems Genetics approach to identify genetic markers of cardiotoxicity due to anthracyclines in cancer patients." The datasets presented here were used to generate the main and supplementary figures and tables of the indicated study. The study consists of the identification of genetic markers of cardiotoxicity due to anthracyclines (CDA). CDA is a complex genesis disease or complex trait, and because of this, there is a component of missing heritability. Therefore, it is not possible to identify genetic markers associated with CDA risk. Here, we propose that molecular subphenotypes associated with the CDA may be a strategy for identifying some of this missing heritability and risk markers associated with it. A similar strategy could be applied to identify markers of other diseases of complex genesis. This study is done using a genetically heterogeneous cohort of mice that developed breast cancer and was treated with doxorubicin or a combined treatment of doxorubicin and docetaxel. The mouse cohort was generated by backcrossing, so each mouse is genetically unique. Post-chemotherapy heart damage was assessed by quantifying fibrosis's cardiac area and the thickness of myocardial fibers. The genetic regions associated with CDA were assessed by massive genotyping and genetic linkage analysis. Several molecular subphenotypes were quantified in the myocardium, and their association with the CDA was evaluated. Subsequently, we identified which of them were most statistically associated with CDA in multivariate models. Moreover, which complex trait loci (QTLs) associated with molecular subphenotypes best explained CDA. This strategy served to identify in the cohort of mice genes whose allelic forms could be candidates for the risk of CDA. Allelic variants of these genes were evaluated in four cohorts of cancer patients treated with anthracyclines and whose CDA was evaluated by echocardiography or cardiac magnetic resonance imaging (CMR).JPL laboratory was partially supported by the European Regional Development Fund (ERDF) and the Ministry of Science, Innovation, and Universities (SAF2014-56989-R, SAF2017-88854R), the Carlos III Health Institute (PIE14/00066), "Proyectos Integrados IBSAL 2015" (IBY15/00003), the Regional Government of Castile and Leon (CSI234P18), and "We can be heroes" Foundation. AGN laboratory and human patients' study are supported by funds from the ISCIII project grant (PI18/01242). The Human Genotyping unit is a member of CeGen, PRB3, and is supported by grant PT17/0019, of the PE I+D+i 2013-2016, funded by ISCIII and ERDF. SCLL was the recipient of a Ramón y Cajal research contract from the Spanish Ministry of Economy and Competitiveness, and the work was supported by MINECO/FEDER research grants (RTI2018-094130-B-100). The Proteomics Unit belongs to ProteoRed, PRB3-ISCIII, supported by grant PT17/0019/0023, of the PE I + D + I 2017-2020, funded by ISCIII and FEDER. RCC is funded by fellowships from the Spanish Regional Government of Castile and León. NGS is a recipient of an FPU fellowship (MINECO/FEDER). hiPSC-CM studies were funded in part by the "la Caixa" Banking Foundation under the project code HR18-00304" and Severo Ochoa CNIC Intramural Project (Expediente 12-2016 IGP) to JJ.Supplemental Dataset 1: CDA pathophenotypes after doxorubicin treatment. We treated 71 mice carrying breast cancer with doxorubicin. Each mouse was generated by backcrossing; thus, each one is genetically unique. Cardiotoxicity due to anthracyclines (CDA) was evaluated by automatically quantifying the heart fibrosis area and the average area of myocardial fibers as pathophenotypes of cardiotoxicity using the Ariol slide scanner. The histopathological damage was evaluated in the subendocardium and subepicardium from five randomly chosen regions of each sample (averages in μm2 are shown).-- Supplemental Dataset 2: CDA pathophenotypes after the combined therapy. We treated 61 mice carrying breast cancer with the combined therapy with doxorubicin and docetaxel. Each mouse was generated by backcrossing; thus, each one is genetically unique. Cardiotoxicity due to anthracyclines (CDA) was evaluated by automatically quantifying the heart fibrosis area and the average area of myocardial fibers as pathophenotypes of cardiotoxicity using the Ariol slide scanner. The histopathological damage was evaluated in the subendocardium and subepicardium from five randomly chosen regions of each sample (averages in μm2 are shown).-- Supplemental Dataset 3: CDA subphenotypes after doxorubicin therapy. Myocardium molecular subphenotypes after doxorubicin therapy. Proteins were quantified by a multiplex bead array (Luminex). TGFβ units are shown in pg/mL. The rest of the protein levels are shown in molecular fluorescence intensity (MFI) Units. The telomeric length was quantified by QPCR (RQ units). miRNAs were quantified by QPCR (RQ units). QPCR analyses were assessed by the ΔΔCT method; we show the averages of triplicates.-- Supplemental Dataset 4: CDA subphenotypes after the combined therapy. Myocardium molecular subphenotypes after the combined therapy with doxorubicin and docetaxel. Proteins were quantified by a multiplex bead array (Luminex). TGFβ units are shown in pg/mL. The rest of the protein levels are shown in molecular fluorescence intensity (MFI) Units. The telomeric length was quantified by QPCR (RQ units). miRNAs were quantified by QPCR (RQ units). QPCR analyses were assessed by the ΔΔCT method; we show the averages of triplicates.-- Supplemental Dataset 5: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after doxorubicin therapy in all mice.-- Supplemental Dataset 6: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after doxorubicin therapy in young mice. Correlation of Spearman.-- Supplemental Dataset 7: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after doxorubicin therapy in old mice. Correlation of Spearman.-- Supplemental Dataset 8: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after the combined therapy in all mice. Correlation of Spearman.-- Supplemental Dataset 9: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after the combined therapy in young mice. Correlation of Spearman.-- Supplemental Dataset 10: Correlations identified between molecular subphenotype levels in the myocardium and pathophenotypes of cardiotoxicity due to anthracyclines (CDA) after the combined therapy in old mice. Correlation of Spearman.-- Supplemental Dataset 11: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after doxorubicin therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 12: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after doxorubicin therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 13: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after doxorubicin therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 14: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after the combined therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 15: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after the combined therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 16: Linkage analysis of molecular subphenotype levels quantified in the myocardium. Lod scores after the combined therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 17: Massive genotyping of mouse cohort treated with doxorubicin. The genome-wide scan was carried out at the Spanish National Centre of Genotyping (CeGEN) at the Spanish National Cancer Research Centre (CNIO, Madrid, Spain). The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution.-- Supplemental Dataset 18: Massive genotyping of mouse cohort treated with the combined therapy. The genome-wide scan was carried out at the Spanish National Centre of Genotyping (CeGEN) at the Spanish National Cancer Research Centre (CNIO, Madrid, Spain). The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution.-- Supplemental Dataset 19: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after doxorubicin therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 20: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after doxorubicin therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 21: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after doxorubicin therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 22: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after the combined therapy in all mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 23: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after the combined therapy in young mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 24: Linkage analysis of CDA pathophenotypes quantified in the myocardium. Lod scores after the combined therapy in old mice. The Illumina Mouse Medium Density Linkage Panel Assay was used to genotype 130 F1BX mice at 1449 single nucleotide polymorphisms (SNPs). Genotypes were classified as FVB/FVB (F/F) or FVB/C57BL/6 (F/B). Ultimately, 806 SNPs are informative from the FVB and C57BL/6 mice; the average genomic distance between these SNPs was 9.9 Mb. The genotype proportion among the F1BX mice showed a normal distribution. Linkage analysis was carried out using interval mapping with the expectation-maximization (EM) algorithm and R/QTL software. The criteria for significant and suggestive linkages for single markers were chosen based on Lander and Kruglyak (see methods section of our manuscript).-- Supplemental Dataset 25: Human breast cancer cohort-1 genotyping. The association of genetic variants with CDA was evaluated in four patient cohorts p

Intermediate Molecular Phenotypes to Identify Genetic Markers of Anthracycline-Induced Cardiotoxicity Risk.

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex trait with a polygenic component that is mainly unidentified. We propose that levels of intermediate molecular phenotypes (IMPs) in the myocardium associated with histopathological damage could explain CDA susceptibility, so variants of genes encoding these IMPs could identify patients susceptible to this complication. Thus, a genetically heterogeneous cohort of mice (n = 165) generated by backcrossing were treated with doxorubicin and docetaxel. We quantified heart fibrosis using an Ariol slide scanner and intramyocardial levels of IMPs using multiplex bead arrays and QPCR. We identified quantitative trait loci linked to IMPs (ipQTLs) and cdaQTLs via linkage analysis. In three cancer patient cohorts, CDA was quantified using echocardiography or Cardiac Magnetic Resonance. CDA behaves as a complex trait in the mouse cohort. IMP levels in the myocardium were associated with CDA. ipQTLs integrated into genetic models with cdaQTLs account for more CDA phenotypic variation than that explained by cda-QTLs alone. Allelic forms of genes encoding IMPs associated with CDA in mice, including AKT1, MAPK14, MAPK8, STAT3, CAS3, and TP53, are genetic determinants of CDA in patients. Two genetic risk scores for pediatric patients (n = 71) and women with breast cancer (n = 420) were generated using machine-learning Least Absolute Shrinkage and Selection Operator (LASSO) regression. Thus, IMPs associated with heart damage identify genetic markers of CDA risk, thereby allowing more personalized patient management