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6. Incidence and risk factors for adalimumab and infliximab anti-drug antibodies in rheumatoid arthritis: A European retrospective multicohort analysis

Author

Quistrebert, Jocelyn, Hässler, Signe, Bachelet, Delphine, Mbogning, Cyprien, Musters, Anne, Tak, Paul Peter, Wijbrandts, Carla Ann, Herenius, Marieke, Bergstra, Sytske Anne, Akdemir, Gülşah, Johannesson, Martina, Combe, Bernard, Fautrel, Bruno, Chollet-Martin, Sylvie, Gleizes, Aude, Donnellan, Naoimh, Deisenhammer, Florian, Davidson, Julie, Hincelin-Mery, Agnès, Dönnes, Pierre, Fogdell-Hahn, Anna, De Vries, Niek, Huizinga, Tom, Abugessaisa, Imad, Saevarsdottir, Saedis, Hacein-Bey-Abina, Salima, Pallardy, Marc, Broët, Philippe, and Mariette, Xavier

Published
2019
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7. Detection and kinetics of persistent neutralizing anti-interferon-beta antibodies in patients with multiple sclerosis. Results from the ABIRISK prospective cohort study

Author

Jensen, Poul Erik H., Warnke, Clemens, Ingenhoven, Kathleen, Piccoli, Luca, Gasis, Marcia, Hermanrud, Christina, Fernandez-Rodriguez, Blanca M., Ryner, Malin, Kramer, Daniel, Link, Jenny, Ramanujam, Ryan, Auer, Michael, Buck, Dorothea, Grummel, Verena, Bertotti, Elisa, Fissolo, Nicolas, Oliver-Martos, Begoña, Nytrova, Petra, Khalil, Michael, Guger, Michael, Rathmaier, Sandra, Sievers-Stober, Claudia, Lindberg, Raija L.P., Hässler, Signe, Bachelet, Delphine, Aktas, Orhan, Donnellan, Naoimh, Lawton, Andy, Hemmer, Bernhard, Havrdova, Eva Kubala, Kieseier, Bernd, Hartung, Hans-Peter, Comabella, Manuel, Montalban, Xavier, Derfuss, Tobias, Sellebjerg, Finn, Dönnes, Pierre, Pallardy, Marc, Spindeldreher, Sebastian, Broët, Philippe, Deisenhammer, Florian, Fogdell-Hahn, Anna, and Sorensen, Per Soelberg

Published
2019
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8. Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Author

Asselain, Bernard, Barlow, William, Bartlett, John, Bergh, Jonas, Bergsten-Nordström, Elizabeth, Bliss, Judith, Boccardo, Francesco, Boddington, Clare, Bogaerts, Jan, Bonadonna, Gianni, Bradley, Rosie, Brain, Etienne, Braybrooke, Jeremy, Broet, Philippe, Bryant, John, Burrett, Julie, Cameron, David, Clarke, Mike, Coates, Alan, Coleman, Robert, Coombes, Raoul Charles, Correa, Candace, Costantino, Joe, Cuzick, Jack, Danforth, David, Davidson, Nancy, Davies, Christina, Davies, Lucy, Di Leo, Angelo, Dodwell, David, Dowsett, Mitch, Duane, Fran, Evans, Vaughan, Ewertz, Marianne, Fisher, Bernard, Forbes, John, Ford, Leslie, Gazet, Jean-Claude, Gelber, Richard, Gettins, Lucy, Gianni, Luca, Gnant, Michael, Godwin, Jon, Goldhirsch, Aron, Goodwin, Pamela, Gray, Richard, Hayes, Daniel, Hill, Catherine, Ingle, James, Jagsi, Reshma, Jakesz, Raimund, James, Sam, Janni, Wolfgang, Liu, Hui, Liu, Zulian, Lohrisch, Caroline, Loibl, Sibylle, MacKinnon, Liz, Makris, Andreas, Mamounas, Eleftherios, Mannu, Gurdeep, Martín, Miguel, Mathoulin, Simone, Mauriac, Louis, McGale, Paul, McHugh, Theresa, Morris, Philip, Mukai, Hirofumi, Norton, Larry, Ohashi, Yasuo, Olivotto, Ivo, Paik, Soon, Pan, Hongchao, Peto, Richard, Piccart, Martine, Pierce, Lori, Poortmans, Philip, Powles, Trevor, Pritchard, Kathy, Ragaz, Joseph, Raina, Vinod, Ravdin, Peter, Read, Simon, Regan, Meredith, Robertson, John, Rutgers, Emiel, Scholl, Suzy, Slamon, Dennis, Sölkner, Lidija, Sparano, Joseph, Steinberg, Seth, Sutcliffe, Rosemary, Swain, Sandra, Taylor, Carolyn, Tutt, Andrew, Valagussa, Pinuccia, van de Velde, Cornelis, van der Hage, Jos, Viale, Giuseppe, von Minckwitz, Gunter, Wang, Yaochen, Wang, Zhe, Wang, Xiang, Whelan, Tim, Wilcken, Nicholas, Winer, Eric, Wolmark, Norman, Wood, William, Zambetti, Milvia, and Zujewski, Jo Anne

Published
2018
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12. Supplementary Figure S1 from Neurotensin Receptor 1 Determines the Outcome of Non–Small Cell Lung Cancer

Author

Alifano, Marco, primary, Souazé, Frédérique, primary, Dupouy, Sandra, primary, Camilleri-Broët, Sophie, primary, Younes, Mohamad, primary, Ahmed-Zaïd, Sadi-Menad, primary, Takahashi, Takashi, primary, Cancellieri, Alessandra, primary, Damiani, Stefania, primary, Boaron, Maurizio, primary, Broët, Philippe, primary, Miller, Lance D., primary, Gespach, Christian, primary, Regnard, Jean François, primary, and Forgez, Patricia, primary

Published
2023
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13. Supplementary Methods from Prediction of Clinical Outcome in Multiple Lung Cancer Cohorts by Integrative Genomics: Implications for Chemotherapy Selection

Author

Broët, Philippe, primary, Camilleri-Broët, Sophie, primary, Zhang, Shenli, primary, Alifano, Marco, primary, Bangarusamy, Dhinoth, primary, Battistella, Maxime, primary, Wu, Yonghui, primary, Tuefferd, Marianne, primary, Régnard, Jean-François, primary, Lim, Elaine, primary, Tan, Patrick, primary, and Miller, Lance D., primary

Published
2023
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14. Supplementary Figure Legends 1-6 from Prediction of Clinical Outcome in Multiple Lung Cancer Cohorts by Integrative Genomics: Implications for Chemotherapy Selection

Author

Broët, Philippe, primary, Camilleri-Broët, Sophie, primary, Zhang, Shenli, primary, Alifano, Marco, primary, Bangarusamy, Dhinoth, primary, Battistella, Maxime, primary, Wu, Yonghui, primary, Tuefferd, Marianne, primary, Régnard, Jean-François, primary, Lim, Elaine, primary, Tan, Patrick, primary, and Miller, Lance D., primary

Published
2023
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15. Supplementary Tables 1-4 from Prediction of Clinical Outcome in Multiple Lung Cancer Cohorts by Integrative Genomics: Implications for Chemotherapy Selection

Author

Broët, Philippe, primary, Camilleri-Broët, Sophie, primary, Zhang, Shenli, primary, Alifano, Marco, primary, Bangarusamy, Dhinoth, primary, Battistella, Maxime, primary, Wu, Yonghui, primary, Tuefferd, Marianne, primary, Régnard, Jean-François, primary, Lim, Elaine, primary, Tan, Patrick, primary, and Miller, Lance D., primary

Published
2023
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16. Data from Prediction of Clinical Outcome in Multiple Lung Cancer Cohorts by Integrative Genomics: Implications for Chemotherapy Selection

Author

Broët, Philippe, primary, Camilleri-Broët, Sophie, primary, Zhang, Shenli, primary, Alifano, Marco, primary, Bangarusamy, Dhinoth, primary, Battistella, Maxime, primary, Wu, Yonghui, primary, Tuefferd, Marianne, primary, Régnard, Jean-François, primary, Lim, Elaine, primary, Tan, Patrick, primary, and Miller, Lance D., primary

Published
2023
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17. Supplementary Figures 1-6 from Prediction of Clinical Outcome in Multiple Lung Cancer Cohorts by Integrative Genomics: Implications for Chemotherapy Selection

Author

Broët, Philippe, primary, Camilleri-Broët, Sophie, primary, Zhang, Shenli, primary, Alifano, Marco, primary, Bangarusamy, Dhinoth, primary, Battistella, Maxime, primary, Wu, Yonghui, primary, Tuefferd, Marianne, primary, Régnard, Jean-François, primary, Lim, Elaine, primary, Tan, Patrick, primary, and Miller, Lance D., primary

Published
2023
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19. Clinicogenomic factors of biotherapy immunogenicity in autoimmune disease: A prospective multicohort study of the ABIRISK consortium

Author

Hässler, Signe, Bachelet, Delphine, Duhaze, Julianne, Szely, Natacha, Gleizes, Aude, Hacein-Bey Abina, Salima, Aktas, Orhan, Auer, Michael, Avouac, Jerôme, Birchler, Mary, Bouhnik, Yoram, Brocq, Olivier, Buck-Martin, Dorothea, Cadiot, Guillaume, Carbonnel, Franck, Chowers, Yehuda, Comabella, Manuel, Derfuss, Tobias, De Vries, Niek, Donnellan, Naoimh, Doukani, Abiba, Guger, Michael, Hartung, Hans-Peter, Kubala Havrdova, Eva, Hemmer, Bernhard, Huizinga, Tom, Ingenhoven, Kathleen, Hyldgaard-Jensen, Poul Erik, Jury, Elizabeth C., Khalil, Michael, Kieseier, Bernd, Laurén, Anna, Lindberg, Raija, Loercher, Amy, Maggi, Enrico, Manson, Jessica, Mauri, Claudia, Mohand Oumoussa, Badreddine, Montalban, Xavier, Nachury, Maria, Nytrova, Petra, Richez, Christophe, Ryner, Malin, Sellebjerg, Finn, Sievers, Claudia, Sikkema, Dan, Soubrier, Martin, Tourdot, Sophie, Trang, Caroline, Vultaggio, Alessandra, Warnke, Clemens, Spindeldreher, Sebastian, Dönnes, Pierre, Hickling, Timothy P., Hincelin Mery, Agnès, Allez, Matthieu, Deisenhammer, Florian, Fogdell-Hahn, Anna, Mariette, Xavier, Pallardy, Marc, and Broët, Philippe

Subjects
Drug therapy, Usage, Complications and side effects, Genetic aspects, Health aspects, Autoimmune diseases -- Drug therapy -- Genetic aspects, Biopharmaceuticals -- Usage -- Complications and side effects, Immune response -- Genetic aspects -- Health aspects
Abstract

Author(s): Signe Hässler 1,2,3,*, Delphine Bachelet 1,4, Julianne Duhaze 1,5, Natacha Szely 6, Aude Gleizes 6,7, Salima Hacein-Bey Abina 7,8, Orhan Aktas 9, Michael Auer 10, Jerôme Avouac 11,12, Mary [...], Background Biopharmaceutical products (BPs) are widely used to treat autoimmune diseases, but immunogenicity limits their efficacy for an important proportion of patients. Our knowledge of patient-related factors influencing the occurrence of antidrug antibodies (ADAs) is still limited. Methods and findings The European consortium ABIRISK (Anti-Biopharmaceutical Immunization: prediction and analysis of clinical relevance to minimize the RISK) conducted a clinical and genomic multicohort prospective study of 560 patients with multiple sclerosis (MS, n = 147), rheumatoid arthritis (RA, n = 229), Crohn&apos;s disease (n = 148), or ulcerative colitis (n = 36) treated with 8 different biopharmaceuticals (etanercept, n = 84; infliximab, n = 101; adalimumab, n = 153; interferon [IFN]-beta-1a intramuscularly [IM], n = 38; IFN-beta-1a subcutaneously [SC], n = 68; IFN-beta-1b SC, n = 41; rituximab, n = 31; tocilizumab, n = 44) and followed during the first 12 months of therapy for time to ADA development. From the bioclinical data collected, we explored the relationships between patient-related factors and the occurrence of ADAs. Both baseline and time-dependent factors such as concomitant medications were analyzed using Cox proportional hazard regression models. Mean age and disease duration were 35.1 and 0.85 years, respectively, for MS; 54.2 and 3.17 years for RA; and 36.9 and 3.69 years for inflammatory bowel diseases (IBDs). In a multivariate Cox regression model including each of the clinical and genetic factors mentioned hereafter, among the clinical factors, immunosuppressants (adjusted hazard ratio [aHR] = 0.408 [95% confidence interval (CI) 0.253-0.657], p < 0.001) and antibiotics (aHR = 0.121 [0.0437-0.333], p < 0.0001) were independently negatively associated with time to ADA development, whereas infections during the study (aHR = 2.757 [1.616-4.704], p < 0.001) and tobacco smoking (aHR = 2.150 [1.319-3.503], p < 0.01) were positively associated. 351,824 Single-Nucleotide Polymorphisms (SNPs) and 38 imputed Human Leukocyte Antigen (HLA) alleles were analyzed through a genome-wide association study. We found that the HLA-DQA1*05 allele significantly increased the rate of immunogenicity (aHR = 3.9 [1.923-5.976], p < 0.0001 for the homozygotes). Among the 6 genetic variants selected at a 20% false discovery rate (FDR) threshold, the minor allele of rs10508884, which is situated in an intron of the CXCL12 gene, increased the rate of immunogenicity (aHR = 3.804 [2.139-6.764], p < 1 x 10.sup.-5 for patients homozygous for the minor allele) and was chosen for validation through a CXCL12 protein enzyme-linked immunosorbent assay (ELISA) on patient serum at baseline before therapy start. CXCL12 protein levels were higher for patients homozygous for the minor allele carrying higher ADA risk (mean: 2,693 pg/ml) than for the other genotypes (mean: 2,317 pg/ml; p = 0.014), and patients with CXCL12 levels above the median in serum were more prone to develop ADAs (aHR = 2.329 [1.106-4.90], p = 0.026). A limitation of the study is the lack of replication; therefore, other studies are required to confirm our findings. Conclusion In our study, we found that immunosuppressants and antibiotics were associated with decreased risk of ADA development, whereas tobacco smoking and infections during the study were associated with increased risk. We found that the HLA-DQA1*05 allele was associated with an increased rate of immunogenicity. Moreover, our results suggest a relationship between CXCL12 production and ADA development independent of the disease, which is consistent with its known function in affinity maturation of antibodies and plasma cell survival. Our findings may help physicians in the management of patients receiving biotherapies.

Published
2020
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22. IL28B polymorphism is associated with treatment response in patients with genotype 4 chronic hepatitis C

Author

Asselah, Tarik, De Muynck, Simon, Broët, Philippe, Masliah-Planchon, Julien, Blanluet, Maud, Bièche, Ivan, Lapalus, Martine, Martinot-Peignoux, Michelle, Lada, Olivier, Estrabaud, Emilie, Zhang, Qian, El Ray, Ahmed, Vidaud, Dominique, Ripault, Marie-Pierre, Boyer, Nathalie, Bedossa, Pierre, Valla, Dominique, Vidaud, Michel, and Marcellin, Patrick

Published
2012
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40. A Machine Learning Approach for High-Dimensional Time-to-Event Prediction With Application to Immunogenicity of Biotherapies in the ABIRISK Cohort

Author

Duhazé, Julianne, primary, Hässler, Signe, additional, Bachelet, Delphine, additional, Gleizes, Aude, additional, Hacein-Bey-Abina, Salima, additional, Allez, Matthieu, additional, Deisenhammer, Florian, additional, Fogdell-Hahn, Anna, additional, Mariette, Xavier, additional, Pallardy, Marc, additional, and Broët, Philippe, additional

Published
2020
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42. The Establishment of the Household Air Pollution Consortium (HAPCO)

Author

Hosgood, H. Dean, Klugman, Madelyn, Matsuo, Keitaro, White, Alexandra J., Sadakane, Atsuko, Shu, Xiao-Ou, Lopez-Ridaura, Ruy, Shin, Aesun, Tsuji, Ichiro, Malekzadeh, Reza, Noisel, Nolwenn, Bhatti, Parveen, Yang, Gong, Saito, Eiko, Rahman, Shafiur, Hu, Wei, Bassig, Bryan, Downward, George, Vermeulen, Roel, Xue, Xiaonan, Rohan, Thomas, Abe, Sarah K., Broët, Philippe, Grant, Eric J., Dummer, Trevor J. B., Rothman, Nat, Inoue, Manami, Lajous, Martin, Yoo, Keun-Young, Ito, Hidemi, Sandler, Dale P., Ashan, Habib, Zheng, Wei, Boffetta, Paolo, Lan, Qing, One Health Chemisch, dIRAS RA-2, One Health Chemisch, dIRAS RA-2, Hosgood H.D., Klugman M., Matsuo K., White A.J., Sadakane A., Shu X.-O., Lopez-Ridaura R., Shin A., Tsuji I., Malekzadeh R., Noisel N., Bhatti P., Yang G., Saito E., Rahman S., Hu W., Bassig B., Downward G., Vermeulen R., Xue X., Rohan T., Abe S.K., Broet P., Grant E.J., Dummer T.J.B., Rothman N., Inoue M., Lajous M., Yoo K.-Y., Ito H., Sandler D.P., Ashan H., Zheng W., Boffetta P., and Lan Q.

Subjects
Pollution, Atmospheric Science, medicine.medical_specialty, media_common.quotation_subject, Air pollution, consortium, Environmental Science (miscellaneous), lcsh:QC851-999, medicine.disease_cause, Article, Human lung, 03 medical and health sciences, Bioma, 0302 clinical medicine, stomatognathic system, cohort studies, Environmental health, Epidemiology, medicine, pollution, cancer, 030212 general & internal medicine, Prospective cohort study, Lung cancer, media_common, 0303 health sciences, biomass, business.industry, Public health, 030311 toxicology, Environmental exposure, medicine.disease, 3. Good health, medicine.anatomical_structure, 13. Climate action, lcsh:Meteorology. Climatology, environmental exposures, business, Cohort studie, Cohort study
Abstract

Household air pollution (HAP) is of public health concern, with ~3 billion people worldwide (including >15 million in the US) exposed. HAP from coal use is a human lung carcinogen, yet the epidemiological evidence on carcinogenicity of HAP from biomass use, primarily wood, is not conclusive. To robustly assess biomass’s carcinogenic potential, prospective studies of individuals experiencing a variety of HAP exposures are needed. We have built a global consortium of 13 prospective cohorts (HAPCO: Household Air Pollution Consortium) that have site- and disease-specific mortality and solid fuel use data, for a combined sample size of 587,257 participants and 57,483 deaths. HAPCO provides a novel opportunity to assess the association of HAP with lung cancer death while controlling for important confounders such as tobacco and outdoor air pollution exposures. HAPCO is also uniquely positioned to determine the risks associated with cancers other than lung as well as nonmalignant respiratory and cardiometabolic outcomes, for which prospective epidemiologic research is limited. HAPCO will facilitate research to address public health concerns associated with HAP-attributed exposures by enabling investigators to evaluate sex-specific and smoking status-specific effects under various exposure scenarios.

Published
2019

48. Pooled Analysis of Prognostic Impact of Urokinase-Type Plasminogen Activator and Its Inhibitor PAI-1 in 8377 Breast Cancer Patients

Author

Look, Maxime P., van Putten, Wim L. J., Duffy, Michael J., Harbeck, Nadia, Christensen, Ib Jarle, Thomssen, Christoph, Kates, Ronald, Spyratos, Frédérique, Fernö, Mårten, Eppenberger-Castori, Serenella, Sweep, C. G. J. Fred, Ulm, Kurt, Peyrat, Jean-Philippe, Martin, Pierre-Marie, Magdelenat, Henri, Brünner, Nils, Duggan, Catherine, Lisboa, Björn W., Bendahl, Pär-Ola, Quillien, Véronique, Daver, Alain, Ricolleau, Gabriel, Meijer-van Gelder, Marion E., Manders, Peggy, Fiets, W. Edward, Blankenstein, Marinus A., Broët, Philippe, Romain, Sylvie, Daxenbichler, Günter, Windbichler, Gudrun, Cufer, Tanja, Borstnar, Simona, Kueng, Willy, Beex, Louk V. A. M., Klijn, Jan G. M., OʼHiggins, Niall, Eppenberger, Urs, Jänicke, Fritz, Schmitt, Manfred, and Foekens, John A.

Published
2002

49. A pseudo-R2 measure for selecting genomic markers with crossing hazards functions

Author

Moreau Thierry, Rouam Sigrid, and Broët Philippe

Subjects
Medicine (General), R5-920
Abstract

Abstract Background In genomic medical studies, one of the major objectives is to identify genomic factors with a prognostic impact on time-to-event outcomes so as to provide new insights into the disease process. Selection usually relies on statistical univariate indices based on the Cox model. Such model assumes proportional hazards (PH) which is unlikely to hold for each genomic marker. Methods In this paper, we introduce a novel pseudo-R2 measure derived from a crossing hazards model and designed for the selection of markers with crossing effects. The proposed index is related to the score statistic and quantifies the extent of a genomic factor to separate patients according to their survival times and marker measurements. We also show the importance of considering genomic markers with crossing effects as they potentially reflect the complex interplay between markers belonging to the same pathway. Results Simulations show that our index is not affected by the censoring and the sample size of the study. It also performs better than classical indices under the crossing hazards assumption. The practical use of our index is illustrated in a lung cancer study. The use of the proposed pseudo-R2 allows the identification of cell-cycle dependent genes not identified when relying on the PH assumption. Conclusions The proposed index is a novel and promising tool for selecting markers with crossing hazards effects.

Published
2011
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50. CXCL12 expression by healthy and malignant ovarian epithelial cells

Author

Emilie Dominique, Arenzana-Seisdedos Fernando, Gladieff Laurence, Alexandre Jerôme, Pujade-Lauraine Eric, Bouchet-Delbos Laurence, Nasreddine Salam, Camilleri-Broët Sophie, Gaudin Françoise, Machelon Véronique, Prévot Sophie, Broët Philippe, and Balabanian Karl

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background CXCL12 has been widely reported to play a biologically relevant role in tumor growth and spread. In epithelial ovarian cancer (EOC), CXCL12 enhances tumor angiogenesis and contributes to the immunosuppressive network. However, its prognostic significance remains unclear. We thus compared CXCL12 status in healthy and malignant ovaries, to assess its prognostic value. Methods Immunohistochemistry was used to analyze CXCL12 expression in the reproductive tracts, including the ovaries and fallopian tubes, of healthy women, in benign and borderline epithelial tumors, and in a series of 183 tumor specimens from patients with advanced primary EOC enrolled in a multicenter prospective clinical trial of paclitaxel/carboplatin/gemcitabine-based chemotherapy (GINECO study). Univariate COX model analysis was performed to assess the prognostic value of clinical and biological variables. Kaplan-Meier methods were used to generate progression-free and overall survival curves. Results Epithelial cells from the surface of the ovary and the fallopian tubes stained positive for CXCL12, whereas the follicles within the ovary did not. Epithelial cells in benign, borderline and malignant tumors also expressed CXCL12. In EOC specimens, CXCL12 immunoreactivity was observed mostly in epithelial tumor cells. The intensity of the signal obtained ranged from strong in 86 cases (47%) to absent in 18 cases ( Conclusion Our findings highlight the previously unappreciated constitutive expression of CXCL12 on healthy epithelia of the ovary surface and fallopian tubes, indicating that EOC may originate from either of these epithelia. We reveal that CXCL12 production by malignant epithelial cells precedes tumorigenesis and we confirm in a large cohort of patients with advanced EOC that CXCL12 expression level in EOC is not a valuable prognostic factor in itself. Trial Registration ClinicalTrials.gov: NCT00052468

Published
2011
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