Guillaume Assié1,2, Anne Jouinot1,2,3, Martin Fassnacht4,5, Rossella Libé1,2, Simon Garinet1, Louis Jacob1, Nadim Hamzaoui6, Mario Neou1, Julien Sakat1, Bruno de La Villéon1, Karine Perlemoine1, Bruno Ragazzon1, Mathilde Sibony1,7, Frédérique Tissier1,8, Sébastien Gaujoux9, Bertrand Dousset9, Silviu Sbiera4, Cristina L Ronchi4,10, Matthias Kroiss5, Esther Korpershoek11, Ronald De Krijger11,12, Jens Waldmann13, Marcus Quinkler14, Magalie Haissaguerre15, Antoine Tabarin15, Olivier Chabre16, Michaela Luconi17, Massimo Mannelli17, Lionel Groussin1,2, Xavier Bertagna1,2, Eric Baudin18, Laurence Amar19, Joel Coste20, Felix Beuschlein21,22, Jérôme Bertherat1,2. 1. Institut Cochin, INSERM U1016, CNRS UMR8104, Paris Descartes University, Paris, France. 2. Endocrinology, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France. 3. Medical Oncology, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France. 4. Division of Endocrinology and Diabetes, Department of Internal Medicine I, University Hospital, University of Würzburg, Würzburg, Germany. 5. Comprehensive Cancer Center Mainfranken, University of Würzburg, Würzburg, Germany. 6. Department of Oncogenetics, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France. 7. Department of Pathology, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France. 8. Department of Pathology, Assistance Publique Hôpitaux de Paris, Hôpital Pitié Salpétrière, Paris, France. 9. Department of Digestive and Endocrine Surgery, Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France. 10. Institute of Metabolism and System Research, University of Birmingham, Birmingham, United Kingdom. 11. Department of Pathology, Erasmus MC University Medical Center, Rotterdam, the Netherlands. 12. Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands. 13. Department of Surgery, University Hospital Giessen and Marburg, Campus Marburg, Marburg, Germany. 14. Endocrinology in Charlottenburg, Berlin, Germany. 15. Department of Endocrinology, Diabetes and Metabolic Diseases, University Hospital of Bordeaux, Bordeaux, France. 16. Department of Endocrinology, University Hospital of Grenoble, Grenoble, France. 17. Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy. 18. Department of Nuclear Medicine and Endocrine Oncology, Institut Gustave Roussy, Villejuif, France. 19. Hypertension Unit, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France. 20. Biostatistics and Epidemiology Unit, Hôtel Dieu, Assistance Publique-Hôpitaux de Paris, Paris, France. 21. Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-Universität München, Munich, Germany. 22. Klinik für Endokrinologie, Diabetologie und Klinische Ernährung, Universitätsspital Zürich, Zurich, Switzerland.
Abstract
IMPORTANCE: The risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome. OBJECTIVE: To compare the molecular classification for prognostic assessment of ACC with other known prognostic factors. DESIGN, SETTING, AND PARTICIPANTS: In this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018. EXPOSURES: Meta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts. MAIN OUTCOMES AND MEASURES: Disease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model. RESULTS: Of the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC. CONCLUSIONS AND RELEVANCE: The findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.
IMPORTANCE: The risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome. OBJECTIVE: To compare the molecular classification for prognostic assessment of ACC with other known prognostic factors. DESIGN, SETTING, AND PARTICIPANTS: In this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018. EXPOSURES: Meta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts. MAIN OUTCOMES AND MEASURES: Disease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model. RESULTS: Of the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC. CONCLUSIONS AND RELEVANCE: The findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.
Authors: Rui Caetano Oliveira; Maria João Martins; Carolina Moreno; Rui Almeida; João Carvalho; Paulo Teixeira; Miguel Teixeira; Edgar Tavares Silva; Isabel Paiva; Arnaldo Figueiredo; Maria Augusta Cipriano Journal: Rare Tumors Date: 2021-06-27
Authors: Tito Fojo; Lyn Huff; Thomas Litman; Kate Im; Maureen Edgerly; Jaydira Del Rivero; Stefania Pittaluga; Maria Merino; Susan E Bates; Michael Dean Journal: BMC Med Genomics Date: 2020-11-04 Impact factor: 3.063