Abstract 2000P
Background
A minority of pts obtain clinical benefit (CB) of ICI in mUC. We previously demonstrated that longitudinal assessment of WB-RNA and ctDNA are promising standalone biomarkers for early response prediction in mUC [1,2]. In the current study, we combined ctDNA and WB-RNA data in a multi-modal model (MMM) to assess the synergy between both measurements and improve the identification of non-CB.
Methods
Within a multicenter trial, blood samples of 92 pts were collected at baseline and after 3-6 weeks of ICI (79 WB-RNA/88 ctDNA). ctDNA was quantified using a custom targeted next-generation sequencing (tNGS) panel. On-treatment changes were dichotomized into increase or no increase, the latter including pts with undetectable ctDNA at both timepoints. WB-RNA data were analyzed through Novigenix's Liquid Immuno-TranscriptOmics platform (LITOSeekTM). The cohort was split in a training (n=29), validation (n=29) and independent test set (n=21). Finally, the WB-RNA and ctDNA prediction readouts of the pts in the test set were integrated in a combined MMM. tNGS by TSO500 and PD-L1 immunohistochemistry were performed on archival tumor tissue to determine tumor mutation burden (TMB) and combined positivity score (CPS). Sensitivities (SN) and specificities (SP) for predicting non-CB, defined as progression within 6 months, were compared between the standalone biomarkers, TMB, CPS and the MMM.
Results
In the total cohort, 41/92 pts had CB (45%). ctDNA was detected in 77/88 tested pts (88%). SN and SP of a ctDNA increase for predicting non-CB were 60% and 92% in the full cohort, respectively. A WB-RNA 10-gene model achieved a SN and SP of 73% and 79% in the validation set and 67% and 67% in the test set. Both standalone tests outperformed TMB and CPS. WB-RNA and ctDNA showed strong synergy. In the subset of pts in the test set with both WB-RNA and ctDNA data (n=5 CB, n=14 non-CB), the MMM reached a SN of 79% and SP of 100%. In the same subset, SN and SP of ctDNA alone were 64% and 100%.
Conclusions
The combination of WB-RNA and ctDNA in a MMM shows promise as a non-invasive blood-based biomarker test for early identification of non-CB to ICIs in mUC.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Eurostars.
Disclosure
D. Croci, S. Costa, L. Ciarloni, P. Romero, S. Pavan, S. Hosseinian Ehrensberger: Financial Interests, Personal, Full or part-time Employment: Novigenix. M. Franken: Financial Interests, Institutional, Invited Speaker: Servier; Financial Interests, Institutional, Other, Congres: Ipsen; Financial Interests, Institutional, Advisory Board: Astellas. M. Ligtenberg: Financial Interests, Institutional, Advisory Board: AstraZeneca, GSK, Janssen Pharmaceuticals ; Financial Interests, Institutional, Other, educational activities: Roye Congressen; Financial Interests, Institutional, Other, educational: Uitgeverij Jaap. N. Mehra: Financial Interests, Personal, Advisory Board: Pfizer, MSD, AstraZeneca, Astellas, JNJ, Bayer; Financial Interests, Institutional, Advisory Board: Janssen; Financial Interests, Institutional, Other, An predictive biomarker IP is being validated / no income / no royalties: EUROSTAR grant for predictive biomarker in urothelial cancer; Financial Interests, Institutional, Funding: Astellas, Pfizer; Financial Interests, Personal and Institutional, Funding: Janssen; Financial Interests, Institutional, Coordinating PI: BMS, Janssen, BMS; Financial Interests, Institutional, Research Grant: AstraZeneca, BMS; Non-Financial Interests, Leadership Role, Head of the Prostate Cancer Working group: Dutch Uro-Oncology Study Group; Non-Financial Interests, Principal Investigator, co-PI / multi-dharma sponsored: Prospective Bladder Cancer Infrastructure (Netherlands); Non-Financial Interests, Leadership Role: Castration-resistant Prostate Cancer Registry; Non-Financial Interests, Principal Investigator, RWD registry de novo mHSPC: TripleAIM1 / Janssen. All other authors have declared no conflicts of interest.
Resources from the same session
252P - Evolution of breast cancer biological subtypes between pre-treatment biopsy and residual disease after neoadjuvant therapy
Presenter: Katarzyna Pogoda
Session: Poster session 13
253P - Single-cell RNA sequencing reveals tumor heterogeneity and potential mechanisms of response/resistance in breast cancer treated with neoadjuvant therapy
Presenter: Marcela Carausu
Session: Poster session 13
254P - IHC and GEX biomarkers and their prognostic and treatment predictive role in the neoadjuvant treatment of breast cancer
Presenter: Hani Saghir
Session: Poster session 13
255P - Predicting early recurrence in breast cancer patients undergoing neo-adjuvant chemotherapy through MRI-radiomics analysis
Presenter: Anna D'Angelo
Session: Poster session 13
256P - Protein signature of tertiary lymphoid structure predicts efficacy of neoadjuvant chemotherapy in triple-negative breast cancer
Presenter: Shuling Zhou
Session: Poster session 13
257P - Spatial predictors of pathologic complete response to neoadjuvant chemotherapy using imaging mass cytometry in the IMMUcan TNBC cohort
Presenter: Andrea Joaquin Garcia
Session: Poster session 13
258P - Correlation between pathological complete response (pCR) following neoadjuvant docetaxel, carboplatin and trastuzumab (TCH) with or without pertuzumab (TCHP) and PAM50 subtypes in HER2(+) early breast cancer (eBC)
Presenter: Coralia Bueno Muiño
Session: Poster session 13
1954P - 5-methylthioadenosine phosphorylase (MTAP) loss in clinically advanced uveal melanoma (CAUM): A comprehensive genomic profiling (CGP) study
Presenter: Nimisha Srivastava
Session: Poster session 13
1955P - Glycan-programmed T cell immunity: Effective adoptive T cell transfer in a CRC preclinical model
Presenter: Yong Miao
Session: Poster session 13