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Randomized Controlled Trial
. 2024 Nov 1;30(21):4900-4909.
doi: 10.1158/1078-0432.CCR-24-0149.

The Immune-Related 27-Gene Signature DetermaIO Predicts Response to Neoadjuvant Atezolizumab plus Chemotherapy in Triple-Negative Breast Cancer

Matteo Dugo  1 , Chiun-Sheng Huang  2 , Daniel Egle  3 , Begoña Bermejo  4 , Claudio Zamagni  5 , Robert S Seitz  6 , Tyler J Nielsen  6 , Marc Thill  7 , Antonio Antón-Torres  8 , Stefania Russo  9 , Eva Maria Ciruelos  10 , Brock L Schweitzer  6 , Douglas T Ross  6 , Barbara Galbardi  1 , Richard Greil  11 , Vladimir Semiglazov  12 , Balázs Gyorffy  13   14   15 , Marco Colleoni  16 , Catherine M Kelly  17 , Gabriella Mariani  18 , Lucia Del Mastro  19 , Olivia Blasi  16 , Maurizio Callari  20 , Lajos Pusztai  21 , Pinuccia Valagussa  20 , Giuseppe Viale  16 , Luca Gianni #  20 , Giampaolo Bianchini #  1   22
Affiliations
Randomized Controlled Trial

The Immune-Related 27-Gene Signature DetermaIO Predicts Response to Neoadjuvant Atezolizumab plus Chemotherapy in Triple-Negative Breast Cancer

Matteo Dugo et al. Clin Cancer Res. .

Abstract

Purpose: We assessed the 27-gene RT-qPCR-based DetermaIO assay and the same score calculated from RNA sequencing (RNA-seq) data as predictors of sensitivity to immune checkpoint therapy in the neoTRIPaPDL1 randomized trial that compared neoadjuvant carboplatin/nab-paclitaxel chemotherapy (CT) plus atezolizumab with CT alone in stage II/III triple-negative breast cancer. We also assessed the predictive function of the immuno-oncology (IO) score in expression data of patients treated with pembrolizumab plus paclitaxel (N = 29) or CT alone (N = 56) in the I-SPY2 trial.

Experimental design: RNA-seq data were obtained from pretreatment core biopsies from 242 (93.8%) of the 258 patients in the per-protocol-population. The DetermaIO RT-qPCR test, performed in the CAP/CLIA-accredited laboratory of Oncocyte Corp., was available for 220 patients (85.3%). A previously established threshold was used to assign DetermaIO-positive versus DetermaIO-negative status. Publicly available microarray data were used from I-SPY2.

Results: IO scores calculated from RNA-seq and RT-qPCR data were highly concordant. In neoTRIPaPDL1, DetermaIO-positive cancers (N = 92, 41.8%) had pathologic complete response (pCR) rates of 69.8% and 46.9% in the CT + atezolizumab and CT arms, respectively. In DetermaIO-negative cases, pCR rates were similar in both arms (44.6% vs. 49.2%; interaction test P = 0.04). PDL1 protein expression and stromal tumor-infiltrating lymphocyte count were not predictive of differential benefit from atezolizumab. In I-SPY2, IO-positive cancers (45.9%) had pCR rates of 85.7% and 16%, with and without immunotherapy, respectively. In IO-negative cancers, pCR rates were 46.7% versus 16.1%.

Conclusions: DetermaIO identified patients who benefited from neoadjuvant immunotherapy resulting in improved pCR rate, independently of PDL1.

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Conflict of interest statement

C.-S. Huang reports grants, personal fees, and non-financial support from AstraZeneca, Novartis, OBI Pharma, Pfizer, Daiichi Sankyo, EirGenix, Eli Lilly, and from Roche during the conduct of the study; grants from Aston Sci. and Seagen; grants and personal fees from Gilead; and grants and non-financial support from MSD outside the submitted work. D. Egle reports personal fees from AstraZeneca, Gilead, Lilly, MSD, Novartis, Pfizer, Roche, Menarini, and Seagen; personal fees and non-financial support from Daiichi Sankyo; and grants and personal fees from Sirius Medical during the conduct of the study. B. Bermejo reports personal fees from MSD, Roche, Lilly, and Novartis, and other support from Pfizer and Gilead outside the submitted work. C. Zamagni reports grants from Michelangelo Tech during the conduct of the study and from AbbVie, Array BioPharma, and Synthon outside the submitted work; grants, personal fees, and non-financial support from AstraZeneca, Daiichi Sankyo, Gilead, GSK, MSD, Novartis, Pfizer, and Roche; and personal fees and non-financial support from Eisai, Exact Sciences, Lilly, and Seagen. R.S. Seitz reports personal fees from Insight Genetics Inc. during the conduct of the study and from Gene Capture and BioGenerator Ventures outside the submitted work; in addition, R.S. Seitz reports a patent for WO2022031630A1 pending. T.J. Nielsen reports personal fees from Oncocyte Corporation during the conduct of the study as well as a patent for Classifying Tumors and Predicting Responsiveness pending to Oncocyte Corporation. M. Thill reports personal fees and non-financial support from Roche during the conduct of the study; personal fees from Agendia, Amgen, AstraZeneca, ClearCut, Daiichi Sankyo, Eisai, Gilead, Hexal, MSD, Grünengthal, GSK, Onkowissen, Jörg Eickeler, Organon, Pfizer, Seagen, Pierre Fabre, Sirius Medical, Sysmex, Stemline, Vifor, ZP Therapeutics, and StreamedUp; grants and personal fees from Exact Science, NeoDynamics, and Novartis; and grants, personal fees, and non-financial support from PFM Medical outside the submitted work. A. Antón-Torres reports personal fees from Lilly, Pfizer, Seagen, Novartis, Roche, and Daiichi Sankyo outside the submitted work. B.L. Schweitzer reports personal fees from Oncocyte Corporation during the conduct of the study and outside the submitted work, as well as a patent for WO2022031630A1 pending to Oncocyte Corporation. D.T. Ross reports personal fees from Oncocyte Inc. during the conduct of the study as well from TwinStrand Biosciences Inc. outside the submitted work. R. Greil reports other support from Celgene, Roche, Merck, Takeda, AstraZeneca, Novartis, Amgen, BMS, MSD, Sandoz, AbbVie, Gilead, Daiichi Sankyo, Sanofi, Novo Nordisk, and Lilly outside the submitted work. M. Colleoni reports grants from Roche outside the submitted work. L. Del Mastro reports grants and personal fees from Eli Lilly, Novartis, GSK, and Seagen; grants, personal fees, and non-financial support from Roche, Daiichi Sankyo, AstraZeneca, and Gilead; personal fees from Pierre Fabre, Pfizer, MSD, Eisai, Agendia, Menarini/Stemline, Ipsen, Olema, and Exact Sciences; and grants from AIRC outside the submitted work. L. Pusztai reports personal fees and other support from Merck, AstraZeneca, and Pfizer, as well as personal fees from Oncocyte outside the submitted work. G. Viale reports personal fees from Roche, AstraZeneca, Daiichi Sankyo, Gilead, Pfizer, and Agilent outside the submitted work. L. Gianni reports grants from the Breast Cancer Research Foundation during the conduct of the study, as well as personal fees from AstraZeneca, Roche, Pfizer, Zymeworks, Artemida Pharma Ltd, Daiichi Sankyo, BeiGene, Revolution Medicines, Synaffix, Menarini Ricerche, Amgen, Biomedical Insights Inc., and Denali Therapeutics Inc. outside the submitted work; L. Gianni also reports a patent for European Patent Application Nos. 12195182.6 and 12196177.5 issued. G. Bianchini reports grants from Fondazione AIRC per la Ricerca sul Cancro during the conduct of the study; personal fees from Roche, Eli Lilly, Pfizer, AstraZeneca, MSD, Daiichi Sankyo, EISAI, Menarini/Stemline, Exact Science, Seagen, Agendia, and Novartis; and grants and personal fees from Gilead outside the submitted work. No disclosures were reported by the other authors.

Figures

Figure 1.
Figure 1.
Baseline RT-qPCR DetermaIO score. A, Frequency of DetermaIO+ and IO− patients in the overall NeoTRIP population (left) and by treatment arm (right). P value by χ2 test. B, Association between IO classes and PDL1 status (left) or sTILs (right). P values by Fisher’s exact test. C, pCR rate by IO classification and treatment arm. P values by logistic regression.
Figure 2.
Figure 2.
Baseline TNBC subtypes. A, Frequency of TNBC subtypes in the overall NeoTRIP population (left) and by treatment arm (right). P values by χ2 test. B, Association between TNBC subtypes and PDL1 status (left) or sTILs (right). P values by Fisher’s exact test. C, pCR rate by TNBC subtypes and treatment arm. ND, not able to designate a molecular class.
Figure 3.
Figure 3.
IO score evaluation in TNBC from the I-SPY2 trial. A, Frequency of IO+ and IO− patients in the overall I-SPY2 TNBC population (top) and by treatment arm (bottom). P values by χ2 test. B, pCR rate by IO classification and treatment arm. P values by logistic regression analysis. C, Distribution of IO score by treatment arm and pCR status. P values by logistic regression analysis.
See this image and copyright information in PMC

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