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Abstract
Background Identifying biomarkers that predict patient response to immunotherapy is critical for optimizing treatment strategies and improving clinical outcomes. Despite the success of immunotherapy, a significant proportion of patients do not respond to treatment. Thus, there is an urgent need for more robust methods to differentiate responders from non-responders. In this study, we present a novel multiplex imaging-based immunotherapy panel and a comprehensive analysis pipeline to characterize the spatial distribution and function of immune cells and its application for spatial biomarkers detection in a cohort of immunotherapy and targeted therapy-treated melanoma patients.
Methods We designed a 28-plex panel to perform sequential immunofluorescence (seqIF™) on the COMET™ platform1 to target key biomarkers associated with tumor microenvironment composition (TME), immune cell infiltration, and immune checkpoint pathways (figure 1). Utilizing Nucleai’s deep-learning-based multiplex imaging analysis pipeline,2 we were able to identify 13 cell types, including 9 different immune cell populations, in addition to 10 cell state markers. Cells were assigned to the tumor area or TME and spatial features were calculated based on cell type, marker positivity, and area assignments (figure 2). We obtained pre-treatment biopsies from patients with known long-term response or rapid progression to immunotherapy combination treatment (Ipilimumab+Nivolumab) from the SECOMBIT Phase II Trial (NCT02631447)3 4 and profiled these samples using the aforementioned panel and analysis solution. We aimed to identify spatial biomarkers that can differentiate between long-term responders and non-responders to immunotherapy.
Results Our novel multiplex imaging panel and analysis pipeline demonstrated high balanced accuracy (> 0.8) and F1 scores (> 0.8) in cell typing and protein quantification for the majority of cell types and markers. This analysis pipeline enables the quantification of known biomarkers such as T cell activation states, T cell infiltration patterns, and TLS maturation. In addition, we explored several additional biomarkers such as receptor-ligand interactions of PD-1 and PD-L1, interactions between T cells and other immune populations, and stromal cells or tumor cells as additional biomarkers for their association with patient outcomes.
Conclusions Enabling the precise identification of cells and cellular states in immunotherapy-treated patients is critical for guiding personalized treatment strategies. The development of this multiplex imaging panel and deep learning pipeline highlights the potential of integrating multiplex imaging with AI analysis to enhance our understanding of treatment efficacy and resistance mechanisms, ultimately aiming to improve patient outcomes in clinical practice.
Acknowledgements The authors thank the patients and families who made this trial possible. Additionally, the authors acknowledge the clinical study teams and CRO who participated in the trial and in particular Paola Schiavo e Mariarita Arenella from CRT (Clinical Research Technology - Salerno). We thank Bristol-Myers Squibb (Princeton, NJ) and Array Biopharma Inc/Pfizer (Boulder, CO) for support. Moreover, the authors thank the participating investigators who did not enroll any patients and thus are not included as authors on the paper, Koelblinger P, Hafner C, Hoeller C (Austria), Weide B (Germany), Larkin J, Lorigan P (UK).
References
Rivest F, et al. Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics. Sci Rep 2023;13(1):16994.
Markovits E, et al. A novel deep learning pipeline for cell typing and phenotypic marker quantification in multiplex imaging. BioRxiv 2022.
Ascierto PA, et al. Sequencing of ipilimumab plus nivolumab and encorafenib plus binimetinib for untreated BRAF-mutated metastatic melanoma (SECOMBIT): a randomized, three-arm, open-label phase II trial. J Clin Oncol 2023 Jan 10;41(2):212-221.
Ascierto PA, et al. Sequential immunotherapy and targeted therapy for metastatic BRAF V600 mutated melanoma: 4-year survival and biomarkers evaluation from the phase II SECOMBIT trial. Nat Commun 2024,15(1):146.
Ethics Approval This study was designed in 2015 as a phase II, open-label randomized trial with no formal comparative test and a single-stage design for each arm. Patients were enrolled at 37 academic medical centers in 9 countries. The trial protocol was approved by the appropriate ethics body at each participating institution and is available in the Supplementary Information file. An independent data monitoring committee oversaw the trial. SECOMBIT is registered at ClinicalTrials.gov (NCT02631447). The study design and conduct complied with all current regulations regarding the use of human study participants and was conducted in accordance with the criteria set by the Declaration of Helsinki.
A novel immunotherapy-focused multiplex imaging panel
Spatially resolved multiplex imaging analysis pipeline for biomarker identification
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