Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Sapino A.;Perez E.;Floris G.;Singh R.;Chen W.;
2020-01-01

Abstract

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.
2020
6
1
15
N/A
Biomarkers; Breast cancer; Tumour biomarkers; Tumour immunology
Hudecek J.; Voorwerk L.; van Seijen M.; Nederlof I.; de Maaker M.; van den Berg J.; van de Vijver K.K.; Sikorska K.; Adams S.; Demaria S.; Viale G.; Nielsen T.O.; Badve S.S.; Michiels S.; Symmans W.F.; Sotiriou C.; Rimm D.L.; Hewitt S.M.; Denkert C.; Loibl S.; Loi S.; Bartlett J.M.S.; Pruneri G.; Dillon D.A.; Cheang M.C.U.; Tutt A.; Hall J.A.; Kos Z.; Salgado R.; Kok M.; Horlings H.M.; Hyytiainen A.; Hida A.I.; Thompson A.; Lefevre A.; Lazar A.J.; Gown A.; Lo A.; Sapino A.; Madabhushi A.; Moreira A.; Richardson A.; Vingiani A.; Beck A.H.; Bellizzi A.M.; Guerrero A.; Grigoriadis A.; Ehinger A.; Garrido-Castro A.; Vincent-Salomon A.; Laenkholm A.-V.; Sharma A.; Cimino-Mathews A.; Srinivasan A.; Acs B.; Singh B.; Calhoun B.; Haibe-Kans B.; Solomon B.; Thapa B.; Nelson B.H.; Gallas B.D.; Castaneda C.; Ballesteros-Merino C.; Criscitiello C.; Boeckx C.; Colpaert C.; Quinn C.; Chennubhotla C.S.; Swanton C.; Solinas C.; Hiley C.; Drubay D.; Bethmann D.; Moore D.A.; Larsimont D.; Sabanathan D.; Peeters D.; Zardavas D.; Hoflmayer D.; Johnson D.B.; Thompson E.A.; Brogi E.; Perez E.; ElGabry E.A.; Stovgaard E.S.; Blackley E.F.; Roblin E.; Reisenbichler E.; Bellolio E.; Balslev E.; Chmielik E.; Gaire F.; Andre F.; Lu F.-I.; Azmoudeh-Ardalan F.; Rojo F.; Gruosso T.; Ciompi F.; Peale F.; Hirsch F.R.; Klauschen F.; Penault-Llorca F.; Acosta Haab G.; Farshid G.; van den Eynden G.; Curigliano G.; Floris G.; Broeckx G.; Gonzalez-Ericsson; Koeppen H.; Haynes H.R.; McArthur H.; Joensuu H.; Olofsson H.; Lien H.-C.; Chen I.-C.; Cree I.; Frahm I.; Brcic I.; Chan J.; Ziai J.; Brock J.; Wesseling J.; Giltnane J.; Kerner J.K.; Thagaard J.; Braybrooke J.P.; van der Laak J.A.W.M.; Lemonnier J.; Zha J.; Ribeiro J.; Lennerz J.K.; Carter J.M.; Saltz J.; Hartman J.; Hainfellner J.; Quesne J.L.; Juco J.W.; Reis-Filho J.; Sanchez J.; Sparano J.; Cucherousset J.; Araya J.C.; Adam J.; Balko J.M.; Saeger K.; Siziopikou K.; Willard-Gallo K.; Weber K.; Pogue-Geile K.L.; Steele K.E.; Emancipator K.; AbdulJabbar K.; El Bairi K.; Blenman K.R.M.; Allison K.H.; Korski K.; Pusztai L.; Comerma L.; Buisseret L.; Cooper L.A.D.; Shi L.; Kooreman L.F.S.; Molinero L.; Estrada M.V.; Lacroix-Triki M.; Al Bakir M.; Sebastian M.M.; van de Vijver M.; Balancin M.L.; Dieci M.V.; Mathieu M.-C.; Rebelatto M.C.; Piccart M.; Hanna M.G.; Goetz M.P.; Preusser M.; Khojasteh M.; Sanders M.E.; Regan M.M.; Barnes M.; Christie M.; Misialek M.; Ignatiadis M.; van Bockstal M.; Castillo M.; Amgad M.; Harbeck N.; Tung N.; Laudus N.; Sirtaine N.; Burchardi N.; Ternes N.; Radosevic-Robin N.; Gluz O.; Grimm O.; Nuciforo P.; Jank P.; Gonzalez-Ericsson P.; Kirtani P.; Jelinic P.; Watson P.H.; Savas P.; Francis P.A.; Russell P.A.; Singh R.; Kim R.S.; Pierce R.H.; Hills R.; Leon-Ferre R.; de Wind R.; Shui R.; De Clercq S.; Leung S.; Tabbarah S.; Souza S.C.; O'Toole S.; Swain S.; Dudgeon S.; Willis S.; Ely S.; Kim S.-R.; Bedri S.; Irshad S.; Liu S.-W.; Goel S.; Hendry S.; Bianchi S.; Braganca S.; Paik S.; Wienert S.; Fox S.B.; Luen S.J.; Naber S.; Schnitt S.J.; Sua L.F.; Lakhani S.R.; Fineberg S.; Soler T.; Gevaert T.; D'Alfonso T.; John T.; Sugie T.; Kurkure U.; Bossuyt V.; Manem V.; Camara V.P.; Tong W.; Chen W.; Yang W.; Tran W.T.; Wang Y.; Yuan Y.; Allory Y.; Husain Z.; Bago-Horvath Z.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1768068
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