TY - JOUR
T1 - Pan-cancer analysis of antibody-drug conjugate targets and putative predictors of treatment response
AU - Bosi, Carlo
AU - Bartha, Áron
AU - Galbardi, Barbara
AU - Notini, Giulia
AU - Naldini, Matteo M.
AU - Licata, Luca
AU - Viale, Giulia
AU - Mariani, Marco
AU - Pistilli, Barbara
AU - Ali, H. Raza
AU - André, Fabrice
AU - Piras, Marta
AU - Callari, Maurizio
AU - Barreca, Marco
AU - Locatelli, Alberta
AU - Viganò, Lucia
AU - Criscitiello, Carmen
AU - Pusztai, Lajos
AU - Curigliano, Giuseppe
AU - Győrffy, Balázs
AU - Dugo, Matteo
AU - Bianchini, Giampaolo
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Background: Antibody-drug conjugates (ADCs) are a rapidly expanding class of compounds in oncology. Our goal was to assess the expression of ADC targets and potential downstream determining factors of activity across pan-cancer and normal tissues. Materials and methods: ADCs in clinical trials (n = 121) were identified through ClinicalTrials.gov, corresponding to 54 targets. Genes potentially implicated in treatment response were identified in the literature. Gene expression from The Cancer Genome Atlas (9000+ cancers of 31 cancer types), the Genotype-Tissue Expression database (n = 19,000 samples from 31 normal tissue types), and the TNMplot.com (n = 12,494 unmatched primary and metastatic samples) were used in this analysis. To compare relative expression across and within tumour types we used pooled normal tissues as reference. Results: For most ADC targets, mRNA levels correlated with protein expression. Pan-cancer target expression distributions identified appealing cancer types for each ADC development. Co-expression of multiple targets was common and suggested opportunities for ADC combinations. Expression levels of genes potentially implicated in ADC response downstream of the target might provide additional information (e.g. TOP1 was highly expressed in many tumour types, including breast and lung cancers). Metastatic compared to primary tissues overexpressed some ADCs targets. Single sample “targetgram” plots were generated to visualise the expression of potentially competing ADC targets and resistance/sensitivity markers highlighting high inter-patient heterogeneity. Off-cancer target expression only partially explains adverse events, while expression of determinants of payload activity explained more of the observed toxicities. Conclusion: Our findings draw attention to new therapeutic opportunities for ADCs that can be tested in the clinic and our web platform (https://tnmplot.com) can assist in prioritising upcoming ADC targets for clinical development.
AB - Background: Antibody-drug conjugates (ADCs) are a rapidly expanding class of compounds in oncology. Our goal was to assess the expression of ADC targets and potential downstream determining factors of activity across pan-cancer and normal tissues. Materials and methods: ADCs in clinical trials (n = 121) were identified through ClinicalTrials.gov, corresponding to 54 targets. Genes potentially implicated in treatment response were identified in the literature. Gene expression from The Cancer Genome Atlas (9000+ cancers of 31 cancer types), the Genotype-Tissue Expression database (n = 19,000 samples from 31 normal tissue types), and the TNMplot.com (n = 12,494 unmatched primary and metastatic samples) were used in this analysis. To compare relative expression across and within tumour types we used pooled normal tissues as reference. Results: For most ADC targets, mRNA levels correlated with protein expression. Pan-cancer target expression distributions identified appealing cancer types for each ADC development. Co-expression of multiple targets was common and suggested opportunities for ADC combinations. Expression levels of genes potentially implicated in ADC response downstream of the target might provide additional information (e.g. TOP1 was highly expressed in many tumour types, including breast and lung cancers). Metastatic compared to primary tissues overexpressed some ADCs targets. Single sample “targetgram” plots were generated to visualise the expression of potentially competing ADC targets and resistance/sensitivity markers highlighting high inter-patient heterogeneity. Off-cancer target expression only partially explains adverse events, while expression of determinants of payload activity explained more of the observed toxicities. Conclusion: Our findings draw attention to new therapeutic opportunities for ADCs that can be tested in the clinic and our web platform (https://tnmplot.com) can assist in prioritising upcoming ADC targets for clinical development.
KW - ADC targets
KW - ADCs
KW - Agnostic drug
KW - Antibody-drug conjugates
KW - Precision medicine
KW - RNA-seq
KW - Sacituzumab govitecan
KW - Trastuzumab deruxtecan
UR - http://www.scopus.com/inward/record.url?scp=85175169586&partnerID=8YFLogxK
U2 - 10.1016/j.ejca.2023.113379
DO - 10.1016/j.ejca.2023.113379
M3 - Article
AN - SCOPUS:85175169586
SN - 0959-8049
VL - 195
JO - European Journal of Cancer
JF - European Journal of Cancer
M1 - 113379
ER -