The areas selected to be tumor-relevant by the pathologist were used for staining and analysis. The staining was per-formed using a single 4uM FFPE slide. Slides were prepared and stained using MultiOmyx optimized protocols by Neogeneomics. For each round of staining, conjugated ﬂuorescent antibodies are applied to each slide, followed by image acquisition of stained slides. The dye is then quenched allowing for subsequent rounds of staining with other antibodies. Proprietary deep learning-basedworkﬂows were applied to identify individual cells and perform cell classiﬁcation for all individual markers, as well as to identify tissueand tumor regions for analysis. Individual cell and region classiﬁcation results were combined to generate co-expression summaries for phenotypes of interest. Antibodies used for staining include CD3, CD4, CD8, Pan CK, DAPI. Analysis was performed according to NeoGeonomics Laboratories’ optimized protocols ( Gerdes et al., 2013 ;Xu-Monette et al., 2019 ). Multiplex IHC staining protocol Multiplex immunoﬂuorescence (mIF) staining was performed on 4 mm FFPE tumor sections using the OPAL mIHC kit (Akoya Biosci- ences). Brieﬂy, sections were deparafﬁnized and rehydrated. Antigen retrieval was performed in a using an antigen unmasking solution (citrate-based and tris-based). Protein blocking was performed for 10 min using Antibody Diluent/Block solution (Akoya Bio- sciences). Primary antibodies were incubated for 30 min at RT. Slides were then incubated with Polymer-HRP(Vector Labs) diluted1:1 with TBS for 30 min. For visualization with OPAL ﬂuors, slides were incubated for 10 min with OPAL colors. Another heat stepconsisting of boiling the slides in antigen unmasking solution was performed to remove the antibody complexes. The same sequence of blocking, primary antibody incubation, Polymer-HRP application and heating was repeated for each antibody in the multiplex sequence. Finally, the slides were counterstained with DAPI, mounted with prolong gold and coverslipped. Some antibodies usedin staining panels include CD3, CD4, HLA DP/DQ/DR, and Pan Ck. Multispectral analysis The multiplex slides were scanned with a Vectra 3.0 microscope system (Perkin Elmer). Whole slide scans were performed using the 103objective lens. Up to ten individual ﬁelds were selected in the Phenochart program (Phenochart 1.0.9, Perkin Elmer) for higher resolution scanning at 20x (669 3500mm). Multispectral images were unmixed and analyzed using inForm software (inForm 2.4.2, Perkin Elmer) and analyzed with tissue component segmentation based on tumor cell staining: tumor = Pan Ck + regions and stroma = Pan Ck-regions. Individual cells (deﬁned by DAPI positive nuclei) were then phenotyped to characterize various cell populations. Density of cells in each ROI was calculated by combining the cell counts from all images and normalizingby the total area (cells/mm 2). Statistical analysis Statistical analyses of clinical data were performed using SAS (version 9.2). All other analyses were performed in either the R lan-guage and environment for statistical computing (version 4.0.0) or GraphPad Prism (version 7.01). Likewise, all ﬁgures were created using an R script on the ‘‘ggplot2 00package ( Wickham 2016 ) or GraphPad Prism. Unless otherwise speciﬁed, p values were derived from a two-tailed Student’s ttest. ADDITIONAL RESOURCES All data presented in this manuscript is from the multicenter phase I clinical trial NCT03380871. The study’s protocol is provided in Data S1 .ll Article Cancer Cell 40, 1010–1026.e1–e11, September 12, 2022 e11