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Book Chapter
Haibe-Kains B, Desmedt C, Loi S, Delorenzi M, Sotiriou C, Bontempi G. Computational Intelligence in Clinical Oncology : Lessons Learned from an Analysis of a Clinical Study. In: Applications of Computational Intelligence in Biology. Vol. 122. Applications of Computational Intelligence in Biology. ; 2008. p. 237-268.
Conference Paper
Sotiriou C, Wirapati P, Loi S, Desmedt C, Durbecq V, Harris A, Bergh J, Smeds J, Haibe-Kains B, Larsimont D, et al. Better characterization of estrogen receptor (ER) positive luminal subtypes using genomic grade. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S19.
Sotiriou C, Wirapati P, Loi S, Haibe-Kains B, Desmedt C, Tutt A, Ellis P, Buyse M, Delorenzi M, Piccart M, et al. Comprehensive analysis integrating both clinicopathological and gene expression data in more than 1500 samples: Proliferation captured by gene expression grade index appears to be the strongest prognostic factor in breast cancer (BC).
Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, et al. Gene Expression Profiling in Breast Cancer Challenges the Existence of Intermediate Histological Grade.
Sotiriou C, Wirapati P, Loi S, Haibe-Kains B, Piette F, Buyse M, Bontempi G, Delorenzi M, Piccart M. Is genomic grading killing histological grading ?. In: Journal of European Breast Cancer. Vol. 4. Journal of European Breast Cancer. ; 2006. p. 177.
Loi S, Sotiriou C, Haibe-Kains B, Lallemand F, Conus N, Piccart MJ, Speed T, McArthur GA. Overcoming tamoxifen resistance in the luminal B subtype by targeting activated HER2 (ERBB2) signaling in the absence of HER2 overexpression: tailoring treatment in hormone responsive breast cancer.
Loi S, Desmedt C, Haibe-Kains B, Lallemand F, Gillett C, Tutt A, Ryder K, Ellis P, Harris A, Smeds J, et al. Predicting relapse in estrogen receptor (ER) positive breast cancer (luminal) subgroups treated with adjuvant tamoxifen. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S129.
Loi S, Piccart M, Haibe-Kains B, Desmedt C, A.Harris, Bergh J, Ellis P, Miller L, Liu E, Sotiriou C, et al. Prediction of early distant relapses on tamoxifen in early- stage breast cancer (BC): a potential tool for adjuvant aromatase inhibitor (AI) tailoring.
Desmedt C, Piette F, Cardoso F, Wang Y, Loi S, Lallemand F, Klijn J, Haibe-Kains B, Viale G, Delorenzi M, et al. TRANSBIG multi-centre independent validation of the Rotterdam 76-gene prognostic signature for patients with node-negative breast cancer.
Journal Article
Loi S, Haibe-Kains B, Lallemand F, Pusztai L, Bardelli A, Gillett C, Ellis P, Piccart-Gebhart MJ, Phillips WA, McArthur GA, et al. Correlation of PIK3CA mutation-associated gene expression signature (PIK3CA-GS) with deactivation of the PI3K pathway and with prognosis within the luminal-B ER+ breast cancers. J Clin Oncol (Meeting Abstracts). 2009:533-.
Loi S, Haibe-Kains B, Desmedt C, Lallemand F, Tutt A, Gillett C, Harris A, Bergh J, Foekens J, Klijn J, et al. Definition of clinically distinct molecular subtypes in estrogen receptor positive breast carcinomas through use of genomic grade. Journal of Clinical Oncology. 2007.
Loi S, Haibe-Kains B, Desmedt C, Sotiriou C. Expression Profiling in Breast Carcinoma: New Insights on Old Prognostic Factors?. Journal of Clinical Oncology. 2007:4317-4318.
Loi S, Haibe-Kains B, Majjaj S, Lallemand F, Durbecq V, Larsimont D, Gonzalez-Angulo AM, Pusztai L, Symmans FW, Bardelli A, et al. PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor positive breast cancer. PNAS. 2010.
Loi S, Haibe-Kains B, Desmedt C, Wirapati P, Lallemand F, Tutt A, Gillet C, Ellis P, Ryder K, Reid J, et al. Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen. BMC Genomics [Internet]. 2008:239.
Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, Viale G, Delorenzi M, Zhang Y, Saghatchian d'Assignies M, et al. Strong time-dependency of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multi-centre independent validation series. Clinical Cancer Research. 2007:3207-14.
Haibe-Kains B, Desmedt C, Loi S, Culhane AC, Bontempi G, Quackenbush J, Sotiriou C. A three-gene model to robustly identify breast cancer molecular subtypes. Journal of the National Cancer Institute. 2012:311–325.

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