Contribution of PD-L1-expressing tumor and immune cells to the Combined Positive Score (CPS) using PD-L1 IHC 22C3 pharmDx

Contribution of PD-L1-expressing tumor and immune cells to the Combined Positive Score (CPS) using PD-L1 IHC 22C3 pharmDx | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Contribution of PD-L1-expressing tumor and immune cells to the Combined Positive Score (CPS) using PD-L1 IHC 22C3 pharmDx Tiffany Evans, Epiphani Simmons, Jay Milo, Jim Ruvalcaba-Rodarte, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7077026/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract PD-L1 IHC 22C3 pharmDx (SK006) is currently FDA-approved for use with pembrolizumab (KEYTRUDA) for non-small cell lung cancer, esophageal squamous cell cancer, cervical cancer, head and neck squamous cell carcinoma (HNSCC), triple-negative breast cancer (TNBC), and gastric and gastroesophageal junction (GC/GEJ) adenocarcinoma. This study evaluates the contribution of PD-L1 staining tumor cells (TCs) and mononuclear inflammatory cells (MICs) when determining the Combined Positive Score (CPS) with SK006. We retrospectively analyzed TNBC, urothelial carcinoma (UC), HNSCC, esophageal cancer (EC), and GC/GEJ specimens. Specimens were stained and scored using CPS (PD-L1 staining TCs and MICs) and Tumor Proportion Score (TPS; PD-L1 staining TCs only). We then determined a specimen’s calculated immune cell density (CID), and TC/MIC PD-L1 expression ratio. Analysis revealed PD-L1-expressing TCs and MICs were both present in 36% of all specimens. PD-L1-expressing TCs contributed significantly more than MICs in specimens above CPS ≥ 10 and CPS ≥ 20 cutoffs. Collectively, these results demonstrate that while the CPS for some tumor types is driven by PD-L1-expressing MICs, PD-L1-expressing TCs may drive the CPS above a cutoff for other tumor types. As such, both TCs and MICs remain important contributors to the CPS. These findings highlight CPS as a comprehensive scoring algorithm when using SK006. Biological sciences/Cancer Biological sciences/Immunology Health sciences/Oncology or Phrases PD-L1 IHC 22C3 pharmDx Combined Positive Score (CPS) Tumor Cell (TCs) Mononuclear Inflammatory Cells (MICs) Pembrolizumab (KEYTRUDA®) Figures Figure 1 Figure 2 Figure 3 Introduction Programmed death-ligand 1 (PD-L1) overexpression in tumor cells (TCs) has been a focal point in the development of cancer immunotherapy and corresponding immunohistochemical (IHC) assays intended for companion diagnostic (CDx) use. PD-L1 is expressed in several cell types including TCs, lymphocytes, macrophage-lineage cells, and endothelial cells. 1 – 4 Higher levels of PD-L1 expression have been associated with greater therapeutic efficacy from anti-PD-(L)-1 agents, although patients with lower PD-L1 expression levels can derive clinical benefit in certain tumor types. 5 Research shows that both TCs and mononuclear inflammatory cells (MICs) express PD-L1 and contribute to disease progression. 6 , 7 These findings highlight the importance of TC and MIC evaluation when determining PD-L1 expression levels. 6 , 7 PD-1 interaction with its ligands (PD-L1 and PD-L2) protects TCs from cytotoxic T-cell attack by deactivating the antitumor immune response. PD-(L)-1 inhibitors are used in immunotherapy to restore the antitumor immune response through blockade of the PD-1/PD-L1 axis. Multiple immunotherapeutic agents, including the anti-PD-1 pembrolizumab (KEYTRUDA®), are FDA-approved. 6 , 7 Qualitative CDx IHC assays are codeveloped with corresponding anti-PD(L)-1 therapies in clinical trials to identify patients who may be likely to respond to anti-PD-(L)1 treatment. PD-L1 IHC 22C3 pharmDx (SK006) is a CDx assay developed by Agilent Technologies, Inc., intended for use in identifying patients for treatment with KEYTRUDA, and was the first PD-L1 CDx approved in the United States. 9 PD-L1 IHC 22C3 pharmDx is analytically validated for multiple tumor types using the Combined Positive Score (CPS) and/or the Tumor Proportion Score (TPS) algorithm(s). CPS includes PD-L1 staining TCs and MICs, whereas TPS includes TCs only. Depending on local regulatory status, CPS is used to determine PD-L1 expression for triple-negative breast cancer (TNBC), urothelial carcinoma (UC), head and neck squamous cell carcinoma (HNSCC), esophageal cancer (EC) and/or esophageal squamous cell carcinoma (ESCC), and gastric/gastroesophageal junction adenocarcinoma (GC/GEJ), 4,6,8,10–17 with cutoff values of CPS ≥ 1 and CPS ≥ 10 for TNBC, CPS ≥ 10 for UC, CPS ≥ 1 and CPS ≥ 20 for HNSCC, CPS ≥ 10 for EC, and CPS ≥ 1 for GC/GEJ. 10–17 The purpose of this work was to assess PD-L1 expression on TCs and MICs and determine which cell types drive the CPS in TNBC, UC, HNSCC, EC, and GC/GEJ. Four parameters were used for this evaluation: (i) CPS as a measure of PD-L1 staining TCs and tumor-associated MICs (ii) TPS as a measure of PD-L1 staining TCs, (iii) calculated immune cell density (CID) as an indirect estimate of the contribution of PD-L1 staining MICs (or lack of staining TCs) to the CPS by subtracting the numerical value of TPS from CPS (CID = CPS - TPS), and (iv) classification of PD-L1 expression patterns with respect to the proportion of TCs and MICs per specimen. These parameters were evaluated for specimens from Agilent’s internal tumor bank. 18 Results from this study highlight the significance of PD-L1 staining TC and MIC inclusion in the CPS algorithm across five tumor types. Materials and Methods Agilent’s Internal Tumor Bank Unique specimens with scores spanning the dynamic range of PD-L1 expression (CPS 1–100) from Agilent’s internal tumor bank were analyzed for TNBC (n = 281), UC (n = 411), HNSCC (n = 457), EC (n = 716), and GC/GEJ (n = 290). All specimens were deidentified and commercially procured from licensed tissue vendors. Specimen Preparation A specimen is defined as a tumor tissue block that was formalin-fixed and paraffin-embedded (FFPE). Sections were cut at 4 µm thickness and placed on either a Dako FLEX IHC Microscope Slide (Code K8020; Dako North America, Inc., Carpinteria, CA) or a Superfrost Plus glass slide, and oven-dried at 58 ± 2°C for one hour. Sections were stored in the dark at 2– 8°C before immunostaining with PD-L1 IHC 22C3 pharmDx (Code SK006; Agilent Technologies, Inc., Santa Clara, CA). Further specimen preparation and storage condition details can be found in the PD-L1 IHC 22C3 pharmDx Instructions for Use (IFU). 10 , 16 This retrospective study evaluates the CPS, TPS, CID, and the PD-L1 expression pattern for the five tumor types included in this study. PD-L1 IHC 22C3 pharmDx Staining Protocol Specimens were pretreated using a 3- in-1 procedure that included deparaffinization, rehydration, and target retrieval using a PT Link (Code PT100/PT101/PT200) with a low pH TRS (Code K8005; Dako North America, Inc., Carpinteria, CA). Specimens were then stained using the Autostainer Link 48 platform with PD-L1 IHC 22C3 pharmDx according to the staining protocol described in the IFU. 16 The stained specimens were counterstained with hematoxylin (Code K8008; Agilent Technologies, Inc., Santa Clara, CA) and coverslipped. Specimen Scoring All specimens were scored using TPS and CPS according to tumor type-specific scoring criteria. 10 , 16 The CPS and TPS results were then leveraged to calculate CID post-hoc. Specimens were evaluated using a light microscope by trained pathologists. Each specimen was evaluated by one pathologist. CPS equation : CPS is the number of PD-L1 staining cells (TCs, lymphocytes, and macrophages) divided by the total number of viable TCs, multiplied by 100. Although the result of the calculation can exceed 100, the maximum score is defined as CPS 100. $$\:\varvec{C}\varvec{P}\varvec{S}=\frac{ \:\varvec{P}\varvec{D}-\varvec{L}1\:\varvec{s}\varvec{t}\varvec{a}\varvec{i}\varvec{n}\varvec{i}\varvec{n}\varvec{g}\:\varvec{c}\varvec{e}\varvec{l}\varvec{l}\varvec{s}\:(\varvec{t}\varvec{u}\varvec{m}\varvec{o}\varvec{r}\:\varvec{c}\varvec{e}\varvec{l}\varvec{l}\varvec{s},\:\varvec{l}\varvec{y}\varvec{m}\varvec{p}\varvec{h}\varvec{o}\varvec{c}\varvec{y}\varvec{t}\varvec{e}\varvec{s},\:\varvec{m}\varvec{a}\varvec{c}\varvec{r}\varvec{o}\varvec{p}\varvec{h}\varvec{a}\varvec{g}\varvec{e}\varvec{s})}{\varvec{T}\varvec{o}\varvec{t}\varvec{a}\varvec{l}\: \:\varvec{o}\varvec{f}\:\varvec{v}\varvec{i}\varvec{a}\varvec{b}\varvec{l}\varvec{e}\:\varvec{t}\varvec{u}\varvec{m}\varvec{o}\varvec{r}\:\varvec{c}\varvec{e}\varvec{l}\varvec{l}\varvec{s}}\:\varvec{X}\:100$$ TPS equation : TPS is the percentage of viable tumor cells showing partial or complete membrane staining at any intensity. $$\:\varvec{T}\varvec{P}\varvec{S}\:\left(\varvec{\%}\right)=\frac{\:\varvec{P}\varvec{D}-\varvec{L}1\:\varvec{s}\varvec{t}\varvec{a}\varvec{i}\varvec{n}\varvec{i}\varvec{n}\varvec{g}\:\varvec{t}\varvec{u}\varvec{m}\varvec{o}\varvec{r}\:\varvec{c}\varvec{e}\varvec{l}\varvec{l}\varvec{s}}{\varvec{T}\varvec{o}\varvec{t}\varvec{a}\varvec{l}\: \:\varvec{o}\varvec{f}\:\varvec{v}\varvec{i}\varvec{a}\varvec{b}\varvec{l}\varvec{e}\:\varvec{t}\varvec{u}\varvec{m}\varvec{o}\varvec{r}\:\varvec{c}\varvec{e}\varvec{l}\varvec{l}\varvec{s}\:}\:\varvec{x}\:100\:$$ CID equation : CID is calculated by subtracting the TPS value from CPS. CID was calculated post-hoc to provide an estimate of PD-L1 staining MIC (or lack of TC staining) contribution to CPS. $$\:\varvec{C}\varvec{I}\varvec{D}=\varvec{C}\varvec{P}\varvec{S}-\varvec{T}\varvec{P}\varvec{S}$$ Statistical Analysis Although the CID score is an indirect measurement, CID still provides an estimate of PD-L1 staining MIC contribution to CPS. The CPS algorithm has a maximum score of 100 and does not capture cases where staining MICs exceed the number of total TCs. As such, in cases where CPS = 100, specimens were removed from the stratification analysis. The distribution of CPS values for specimens that were PD-L1-expressing (CPS ≥ 1) with corresponding representation of TPS and CID was plotted for each tumor type. For each tumor type, specimens were rank ordered based on CPS value. For visual interpretation, specimens were plotted against the square root of the CPS value. The CPS for each specimen was further broken into TPS and CID components to understand trends in TC and MIC staining patterns across tumor types. Unique specimens from Agilent’s internal tumor bank that were PD-L1-expressing (CPS ≥ 1) were stratified into five categories based on the PD-L1 staining in TCs and MICs: Tumor Only (TPS = CPS, CID = 0); Majority Tumor (TPS > CID); Equal Tumor and Immune (TPS = CID); Majority Immune (TPS < CID); and Immune Only (CID = CPS, TPS = 0). Once the expression patterns were determined for each specimen, the distribution of specimens that fell into each of these categories for each tumor type was calculated. The proportion of PD-L1 staining that was contributed by TCs for each specimen was calculated as (TPS/CPS)*100. The distributions of the TC proportions were then plotted separately for specimens that were above and below the respective cutoffs for each tumor type. For each tumor type within each cutoff, the Wilcoxon Rank-Sum Test was applied to test whether a statistical difference in distributions of TC proportions existed between specimens that fell above and below the cutoff. Since only CPS ≥ 1 specimens were included in this analysis, the Wilcoxon Rank-Sum Test was not performed for the CPS ≥ 1 cutoff. Therefore, this statistical test was only applied to the CPS ≥ 10 and CPS ≥ 20 cutoffs. All data generated to support the findings of this study are included in this published article. Results To evaluate how PD-L1 staining TC and MIC contribution to the CPS may shift across the range of PD-L1 expression (CPS 1-100), we plotted the TPS and CID by tumor type (Fig. 1 ) . At a high level, these results demonstrate that MICs contribute more to the CPS than TCs in EC, GC and TNBC (Fig. 1 ; A, B, and D ). In contrast, TCs contribute more to the CPS than MICs in HNSCC (Fig. 1 C). In UC, there is a shift from greater MIC contribution to greater TC contribution to the CPS as CPS increases across the dynamic range of PD-L1 expression ( Fig. 1 E ) . These results demonstrate how PD-L1 expression patterns of TCs and MICs may vary throughout the dynamic range of PD-L1 expression and across different tumor types. To further characterize the contribution of TCs and MICs to the CPS, specimens were grouped by tumor type and then categorized based on the PD-L1 expression patterns in TCs and MICs (Fig. 2 , Supplemental Table 1 ). Across all tumor types, at least 41% of specimens demonstrated PD-L1 staining TCs, and at least 69% of specimens demonstrated PD-L1 staining MICs. Notably, UC had nearly equal representation of specimens with PD-L1 staining TCs and MICs; 70% and 69%, respectively. In EC, the proportion of specimens expressing the Tumor Only, Majority Immune, and Immune Only patterns were 2.9%, 30.9%, and 52.9%, respectively ( Fig. 2 A ) . The same pattern was present in GC/GEJ, with only 5.6% of specimens expressing Tumor Only staining, while 21.7% expressed Majority Immune staining and 58.7% expressed Immune Only staining ( Fig. 2 B ) . In HNSCC, 12.2% of specimens expressed Tumor Only staining, 40.5% expressed Majority Tumor staining, and only 14.2% of specimens expressed Immune Only staining ( Fig. 2 C ) . TNBC expression patterns were similar to those of GC/GEJ and EC, with only 4.1% of specimens expressing Tumor Only staining, while 30.3% expressed Majority Immune staining and 48.4% expressed Immune Only staining ( Fig. 2 D ) . Lastly, UC PD-L1 expression was more balanced between TCs and MICs, with 31.2% of specimens expressing Tumor Only staining, 17.5% expressing Majority Tumor staining, 4.4% expressing Equal Tumor and Immune staining, 17.1% expressing Majority Immune staining, and 29.8% expressing Immune Only staining ( Fig. 2 D ) . Both TCs and MICs contributed meaningfully to the CPS across all tumor types: 44% of EC, 36% of GC/GEJ, 74% of HNSCC, 48% of TNBC, and 39% of UC specimens had PD-L1 expression in both cell types. These results demonstrate the PD-L1 expression patterns of TCs and MICs in these tumor types and reveal that both PD-L1 staining MICs and TCs are important drivers of the CPS. The PD-L1 expression patterns of TCs and MICs can vary across tumor types, showing that both cell types are important to consider when determining PD-L1 expression levels for multiple tumor types. Furthermore, these data highlight the value in using CPS, an algorithm which captures both PD-L1 staining TCs and MICs. Next, we evaluated differences in PD-L1-expressing TCs and MICs relative to CPS cutoffs. The percent contribution of TCs (represented by the TPS) relative to the CPS was calculated for each cutoff and tumor type ( Fig. 3 ) . For the CPS ≥ 1 cutoff, the median percent contribution of TCs in GC/GEJ, TNBC, and HNSCC was 0%, 2.1%, and 66.7%, respectively ( Fig. 3 A ). Analysis of EC, TNBC, and UC specimens evaluated at CPS ≥ 10 revealed that specimens above the cutoff demonstrated significantly increased TC contributions compared to specimens below the cutoff (Wilcoxon Rank-Sum Test p-values < 0.005). Specimens above the CPS ≥ 10 cutoff demonstrated 10%, 5%, and 91% increased median TC contribution when compared to specimens below the cutoff for EC, TNBC, and UC, respectively ( Fig. 3 B ) . In HNSCC, TC contribution for specimens above the CPS ≥ 20 was also significantly increased by 56% when compared to specimens below the cutoff (Wilcoxon Rank-Sum Test p-value < 0.001) ( Fig. 3 C ) . These results highlight the critical role of PD-L1 staining TCs when evaluating specimens at CPS ≥ 10 and CPS ≥ 20 using PD-L1 IHC 22C3 pharmDx. Discussion Previous reports document both TCs and MICs express PD-L1 and influence the progression of disease. 6 , 7 Higher levels of PD-L1 expression are associated with therapeutic response from anti-PD-(L)-1 agents. 5 As such, PD-L1 serves as a predictive biomarker for patient response to immune checkpoint inhibitors. PD-L1 IHC 22C3 pharmDx evaluates PD-L1 expression using CPS, and contributors to this algorithm include PD-L1 staining TCs and MICs. When characterizing the contribution of TCs and MICs to the CPS, this study reports that approximately half of all specimens demonstrate PD-L1 staining TCs and PD-L1 staining MICs across the investigated tumor types. Not only did the PD-L1 expression in TCs and MICs vary across tumor types, but also across the dynamic range of PD-L1 expression. The contribution of PD-L1-expressing TCs and MICs was relatively balanced in UC. The CPS for EC, GC/GEJ, and TNBC was heavily driven by PD-L1-expressing MICs. In contrast, the CPS for HNSCC was driven by PD-L1-expressing TCs. These results highlight differences in PD-L1 expression patterns across tumor types while also confirming that both PD-L1 staining MICs and TCs are important drivers of the CPS across the dynamic range of PD-L1 expression. Literature suggests that there may be organ- or tumor type-specific physiological and histological profiles that are reflected in the prevalence of PD-L1 staining TCs and MICs. 19 Previous studies show that PD-L1 expression in TNBC is highly driven by PD-L1 staining MICs, 20 , 21 consistent with our reports. To date, there is limited literature on PD-L1 expression patterns in the tumor microenvironment of EC and GC/GEJ specimens. 22 , 23 We then narrowed our focus to understand if differences in PD-L1-expressing TCs and MICs exist around specific CPS cutoffs. Specimens above the CPS ≥ 10 and CPS ≥ 20 cutoff demonstrate significantly increased TC contribution to the CPS compared to specimens below the cutoff. Although the CPS for EC and TNBC is driven by MICs when evaluated across the dynamic range of PD-L1 expression, TC contribution to the CPS is significantly higher in specimens above the cutoff. Collectively, these results demonstrate that while the CPS for some tumor types is driven by PD-L1-expressing MICs, PD-L1-expressing TCs specifically may drive the CPS above a respective cutoff. Ward et al. evaluated both the TPS and CPS of UC specimens, reporting that while 29.7% of UC specimens are positive at TPS ≥ 1, 86.5% of specimens were positive at CPS ≥ 1. 24 Taken together, these results and our data demonstrate how CPS is a comprehensive algorithm for determining PD-L1 expression in the tumor microenvironment. Both prior literature and findings from this study further highlight the value of using an algorithm such as CPS, which captures both PD-L1 staining TCs and MICs. While we acknowledge that the clinical impact of scoring both TCs and MICs is critical to the utility of CPS in practice, the goal of this work was to explore the analytical impact of PD-L1 staining TCs and MICs contributing to the CPS across multiple tumor types using PD-L1 IHC 22C3 pharmDx. Clinical outcomes of patient stratification using PD-L1 IHC 22C3 pharmDx with CPS may be explored in a future manuscript. Conclusion These data underscore that both PD-L1 staining TCs and MICs are critical contributors to the CPS across multiple tumor types. This work is given further significance by the clinical utility of PD-L1 IHC 22C3 pharmDx testing and CPS scoring to identify patients who may benefit from treatment with KEYTRUDA. 16 These results provide insight on PD-L1 expression patterns to pathologists who use CPS for scoring various tumor types stained with PD-L1 IHC 22C3 pharmDx. Declarations Conflicts of Interest The authors have indicated the following conflicts of interest that relate to the content of this manuscript: Tiffany Evans M.S., Epiphani Simmons Ph.D., Jay Milo M.A.S., Jim Ruvalcaba-Rodarte, M.S., Stephanie Hund, B.S., Julia Hand MSBME, Brittany Watts B.S., Darlene Krohn Ph.D., Siena Tabuena-Frolli B.S., Karina Kulangara Ph.D., Kelly Martyniuk Ph. D. are employees of Agilent Technologies and own Agilent stock. Competing Interests The authors have indicated the following conflicts of interest that relate to the content of this manuscript: Tiffany Evans M.S., Epiphani Simmons Ph.D., Jay Milo M.A.S., Jim Ruvalcaba-Rodarte, M.S., Stephanie Hund, B.S., Julia Hand MSBME, Brittany Watts B.S., Darlene Krohn Ph.D., Siena Tabuena-Frolli B.S., Karina Kulangara Ph.D., Kelly Martyniuk Ph. D. are employees of Agilent Technologies and own Agilent stock. Author Contribution TE, JR, CL, JH, BW, performed the research.TE, ES, JM, SH, CL, JH, STF, KM designed the research study.TE, ES, STF, KM analyzed the data.TE, ES, SH, JH, DK, STF, KK, KM wrote the paper. Acknowledgement Studies were supported by Agilent Technologies and Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA. Tissue samples were supplied by BioIVT Asterand®. Data Availability All data generated to support the findings of this study are included in this published article. References Cheung, C. C. et al. 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Gastric Cancer . 23 (1), 95–104 (2020). PD-L1 IHC 22C3. pharmDx [Instructions for Use] (Agilent Technologies, Inc., 2023). de Ruiter, E. J. et al. Comparison of three PD-L1 immunohistochemical assays in head and neck squamous cell carcinoma (HNSCC). Mod. Pathol. 34 (6), 1125–1132 (2021). Keytruda (pembrolizumab) for injection, for intravenous use [package insert] (Merk Sharpe & Dohme Corp, 2023). Kluger, H. M. et al. PD-L1 Studies Across Tumor Types, Its Differential Expression and Predictive Value in Patients Treated with Immune Checkpoint Inhibitors. Clin. Cancer Res. 23 (15), 4270–4279. 10.1158/1078-0432.CCR-16-3146 (2017). Emens, L. A. Breast Cancer Immunotherapy: Facts and Hopes. Clin. cancer research: official J. Am. Association Cancer Res. 24 (3), 511–520. https://doi.org/10.1158/1078-0432.CCR-16-3001 (2018). Loi, S. et al. The journey of tumor-infiltrating lymphocytes as a biomarker in breast cancer: clinical utility in an era of checkpoint inhibition. 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The authors have indicated the following conflicts of interest that relate to the content of this manuscript: Tiffany Evans M.S., Epiphani Simmons Ph.D., Jay Milo M.A.S., Jim Ruvalcaba-Rodarte, M.S., Stephanie Hund, B.S., Julia Hand MSBME, Brittany Watts B.S., Darlene Krohn Ph.D., Siena Tabuena-Frolli B.S., Karina Kulangara Ph.D., Kelly Martyniuk Ph. D. are employees of Agilent Technologies and own Agilent stock. Supplementary Files EvansSimmonsCPSContributionTableSubmission.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 Dec, 2025 Reviewers agreed at journal 17 Dec, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers invited by journal 11 Nov, 2025 Editor assigned by journal 11 Nov, 2025 Editor invited by journal 15 Jul, 2025 Submission checks completed at journal 11 Jul, 2025 First submitted to journal 11 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7077026","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":544779640,"identity":"7c5d7a6d-de6d-4c2f-abc9-16b9fe0e2c56","order_by":0,"name":"Tiffany Evans","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Tiffany","middleName":"","lastName":"Evans","suffix":""},{"id":544779641,"identity":"48ec6a1a-12f5-4690-896a-2232a2585858","order_by":1,"name":"Epiphani Simmons","email":"data:image/png;base64,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","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":true,"prefix":"","firstName":"Epiphani","middleName":"","lastName":"Simmons","suffix":""},{"id":544779642,"identity":"2074ad7e-d942-4c1d-9b44-0bbc43f22e14","order_by":2,"name":"Jay Milo","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Jay","middleName":"","lastName":"Milo","suffix":""},{"id":544779643,"identity":"764a1d39-f02d-4b4b-bbdd-36060306f13d","order_by":3,"name":"Jim Ruvalcaba-Rodarte","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Jim","middleName":"","lastName":"Ruvalcaba-Rodarte","suffix":""},{"id":544779644,"identity":"82efa093-4d86-45dc-a225-760b58c188a0","order_by":4,"name":"Stephanie Hund","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Stephanie","middleName":"","lastName":"Hund","suffix":""},{"id":544779645,"identity":"b9a9aba7-6b99-4f99-9eff-a7751b8c81d1","order_by":5,"name":"Chris LaPlaca","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Chris","middleName":"","lastName":"LaPlaca","suffix":""},{"id":544779649,"identity":"f1147b5d-3d36-4d7f-9029-ca806160f2b8","order_by":6,"name":"Julia Hand","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Hand","suffix":""},{"id":544779651,"identity":"a7d38313-2fd8-4312-a6fd-19aed373ee77","order_by":7,"name":"Brittany Watts","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Brittany","middleName":"","lastName":"Watts","suffix":""},{"id":544779654,"identity":"d21d418f-4d63-4608-8408-954a00baa8c8","order_by":8,"name":"Darlene Krohn","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Darlene","middleName":"","lastName":"Krohn","suffix":""},{"id":544779657,"identity":"e66ed983-e50b-40bb-b9cf-166bbe3c9947","order_by":9,"name":"Siena Tabuena-Frolli","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Siena","middleName":"","lastName":"Tabuena-Frolli","suffix":""},{"id":544779658,"identity":"cc63b4a5-55a8-45b3-bb6c-e1913f8fb035","order_by":10,"name":"Karina Kulangara","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Karina","middleName":"","lastName":"Kulangara","suffix":""},{"id":544779659,"identity":"f21eb64a-504e-4c37-9526-8058b7cf2b7a","order_by":11,"name":"Kelly Martyniuk","email":"","orcid":"","institution":"Agilent Technologies, Inc","correspondingAuthor":false,"prefix":"","firstName":"Kelly","middleName":"","lastName":"Martyniuk","suffix":""}],"badges":[],"createdAt":"2025-07-08 17:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7077026/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7077026/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96502531,"identity":"58d51ab5-3e16-420b-b3ae-609925fd89a4","added_by":"auto","created_at":"2025-11-22 00:52:38","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":421937,"visible":true,"origin":"","legend":"","description":"","filename":"EvansSimmonsCPSContributionFiguresSubmission.docx","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/93ade02001f3631682d45cb5.docx"},{"id":96604116,"identity":"c53f0816-cb82-4ff2-86d0-b929badd3b70","added_by":"auto","created_at":"2025-11-24 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00:52:38","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79383,"visible":true,"origin":"","legend":"","description":"","filename":"4f40806a29494de2987c22a8e03243381structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/42132dd9d767d55c1c052014.xml"},{"id":96502538,"identity":"018145b0-e87b-4f09-bead-4ab21619afa0","added_by":"auto","created_at":"2025-11-22 00:52:38","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":93574,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/ee9ff435507d58b3cb03e9f0.html"},{"id":96502530,"identity":"e2f6603f-7bbb-411f-bfe4-f861fe03dc4e","added_by":"auto","created_at":"2025-11-22 00:52:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73393,"visible":true,"origin":"","legend":"\u003cp\u003eContribution of CID and TPS to the CPS in individual specimens. Specimens were stained with PD-L1 IHC 22C3 pharmDx and scored using the Combined Positive Score (CPS) and the Tumor Proportion Score (TPS). \u0026nbsp;CID was then calculated by subtracting the TPS value from CPS post-hoc to provide an estimate of each specimen’s PD-L1 staining MIC contribution to CPS. Tumor types include \u003cstrong\u003e(A)\u003c/strong\u003e esophageal cancer (EC), \u003cstrong\u003e(B)\u003c/strong\u003egastric/gastroesophageal junction adenocarcinoma (GC/GEJ), \u003cstrong\u003e(C)\u003c/strong\u003e Head and Neck Squamous Cell Carcinoma (HNSCC), \u003cstrong\u003e(D)\u003c/strong\u003e Triple Negative Breast Cancer (TNBC), and \u003cstrong\u003e(E)\u003c/strong\u003e urothelial carcinoma (UC) specimens. The square root of the cutoff(s) per tumor type is represented by the horizontal black lines where CPS ≥ 1, CPS ≥ 10, and CPS ≥ 20 are represented by y = 1, y = 2.16, and y = 4.47, respectively [EC (CPS ≥ 10), and GC/GEJ (CPS ≥ 1), HNSCC (CPS ≥ 1, CPS ≥ 20), TNBC (CPS ≥ 1, CPS ≥ 10), UC (CPS ≥ 10)].\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/2f266038686f781216724769.png"},{"id":96502540,"identity":"1f56d8c6-22f1-449b-b43a-5f36719c5568","added_by":"auto","created_at":"2025-11-22 00:52:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":101011,"visible":true,"origin":"","legend":"\u003cp\u003ePD-L1 expression patterns in each tumor type. Specimens were stained with PD-L1 IHC 22C3 pharmDx and scored using the Combined Positive Score (CPS) and the Tumor Proportion Score (TPS). CID was then calculated by subtracting the TPS value from CPS post-hoc to provide an estimate of each specimen’s PD-L1 staining MIC contribution to CPS. Specimens were categorized by their tumor cell (TC) and immune cell expression pattern. Tumor types include \u003cstrong\u003e(A)\u003c/strong\u003e esophageal cancer (EC), \u003cstrong\u003e(B)\u003c/strong\u003egastric/gastroesophageal junction adenocarcinoma (GC/GEJ), \u003cstrong\u003e(C)\u003c/strong\u003e Head and Neck Squamous Cell Carcinoma (HNSCC), \u003cstrong\u003e(D)\u003c/strong\u003e Triple Negative Breast Cancer (TNBC), and \u003cstrong\u003e(E)\u003c/strong\u003e urothelial carcinoma (UC) specimens.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/b6fa85893e5c92ae769ee875.png"},{"id":96604612,"identity":"3138313c-bfe2-4aca-bdb1-0e8d66085376","added_by":"auto","created_at":"2025-11-24 09:14:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114940,"visible":true,"origin":"","legend":"\u003cp\u003ePercent contribution of PD-L1 expressing tumor cells to the CPS for each cutoff. Specimens were stained with PD-L1 IHC 22C3 pharmDx and scored using the Combined Positive Score (CPS) and the Tumor Proportion Score (TPS). \u003cstrong\u003e(A)\u003c/strong\u003e CPS ≥ 1 (GC/GEJ, HNSCC, TNBC); \u003cstrong\u003e(B)\u003c/strong\u003e CPS ≥ 10 (EC, TNBC, UC); \u003cstrong\u003e(C)\u003c/strong\u003e CPS ≥ 20 (HNSCC). Orange and blue boxes encompass the 25\u003csup\u003eth\u003c/sup\u003e through 75\u003csup\u003eth\u003c/sup\u003e percentile for specimens above or below the CPS cutoff, respectively; vertical bars reach the 95\u003csup\u003eth\u003c/sup\u003e percentile. Orange and blue dots represent individual specimens outside the 95\u003csup\u003eth\u003c/sup\u003e percentile. Black dots represent individual specimens. Horizontal orange and blue bars denote the median percent contribution of TC to the CPS for each cutoff.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/41369e3ffa5335f42aea7c4b.png"},{"id":97136016,"identity":"7d39b469-e794-4df4-9645-d334d65b2412","added_by":"auto","created_at":"2025-12-01 09:55:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":754200,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/e19ae5e8-8a9f-4102-a5b5-005be479b15d.pdf"},{"id":96502542,"identity":"584c8cd1-d836-4fa1-b564-abe01be6ce4f","added_by":"auto","created_at":"2025-11-22 00:52:39","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":134581,"visible":true,"origin":"","legend":"","description":"","filename":"EvansSimmonsCPSContributionTableSubmission.docx","url":"https://assets-eu.researchsquare.com/files/rs-7077026/v1/88a0da9bc71469736f81c9e4.docx"}],"financialInterests":"Competing interest reported. The authors have indicated the following conflicts of interest that relate to the content of this manuscript: Tiffany Evans M.S., Epiphani Simmons Ph.D., Jay Milo M.A.S., Jim Ruvalcaba-Rodarte, M.S., Stephanie Hund, B.S., Julia Hand MSBME, Brittany Watts B.S., Darlene Krohn Ph.D., Siena Tabuena-Frolli B.S., Karina Kulangara Ph.D., Kelly Martyniuk Ph. D. are employees of Agilent Technologies and own Agilent stock.","formattedTitle":"Contribution of PD-L1-expressing tumor and immune cells to the Combined Positive Score (CPS) using PD-L1 IHC 22C3 pharmDx","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProgrammed death-ligand 1 (PD-L1) overexpression in tumor cells (TCs) has been a focal point in the development of cancer immunotherapy and corresponding immunohistochemical (IHC) assays intended for companion diagnostic (CDx) use. PD-L1 is expressed in several cell types including TCs, lymphocytes, macrophage-lineage cells, and endothelial cells.\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Higher levels of PD-L1 expression have been associated with greater therapeutic efficacy from anti-PD-(L)-1 agents, although patients with lower PD-L1 expression levels can derive clinical benefit in certain tumor types.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Research shows that both TCs and mononuclear inflammatory cells (MICs) express PD-L1 and contribute to disease progression.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e These findings highlight the importance of TC and MIC evaluation when determining PD-L1 expression levels.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePD-1 interaction with its ligands (PD-L1 and PD-L2) protects TCs from cytotoxic T-cell attack by deactivating the antitumor immune response. PD-(L)-1 inhibitors are used in immunotherapy to restore the antitumor immune response through blockade of the PD-1/PD-L1 axis. Multiple immunotherapeutic agents, including the anti-PD-1 pembrolizumab (KEYTRUDA\u0026reg;), are FDA-approved.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Qualitative CDx IHC assays are codeveloped with corresponding anti-PD(L)-1 therapies in clinical trials to identify patients who may be likely to respond to anti-PD-(L)1 treatment. PD-L1 IHC 22C3 pharmDx (SK006) is a CDx assay developed by Agilent Technologies, Inc., intended for use in identifying patients for treatment with KEYTRUDA, and was the first PD-L1 CDx approved in the United States.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePD-L1 IHC 22C3 pharmDx is analytically validated for multiple tumor types using the Combined Positive Score (CPS) and/or the Tumor Proportion Score (TPS) algorithm(s). CPS includes PD-L1 staining TCs and MICs, whereas TPS includes TCs only. Depending on local regulatory status, CPS is used to determine PD-L1 expression for triple-negative breast cancer (TNBC), urothelial carcinoma (UC), head and neck squamous cell carcinoma (HNSCC), esophageal cancer (EC) and/or esophageal squamous cell carcinoma (ESCC), and gastric/gastroesophageal junction adenocarcinoma (GC/GEJ),\u003csup\u003e4,6,8,10\u0026ndash;17\u003c/sup\u003e with cutoff values of CPS\u0026thinsp;\u0026ge;\u0026thinsp;1 and CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 for TNBC, CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 for UC, CPS\u0026thinsp;\u0026ge;\u0026thinsp;1 and CPS\u0026thinsp;\u0026ge;\u0026thinsp;20 for HNSCC, CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 for EC, and CPS\u0026thinsp;\u0026ge;\u0026thinsp;1 for GC/GEJ.\u003csup\u003e10\u0026ndash;17\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe purpose of this work was to assess PD-L1 expression on TCs and MICs and determine which cell types drive the CPS in TNBC, UC, HNSCC, EC, and GC/GEJ. Four parameters were used for this evaluation: (i) CPS as a measure of PD-L1 staining TCs and tumor-associated MICs (ii) TPS as a measure of PD-L1 staining TCs, (iii) calculated immune cell density (CID) as an indirect estimate of the contribution of PD-L1 staining MICs (or lack of staining TCs) to the CPS by subtracting the numerical value of TPS from CPS (CID\u0026thinsp;=\u0026thinsp;CPS - TPS), and (iv) classification of PD-L1 expression patterns with respect to the proportion of TCs and MICs per specimen. These parameters were evaluated for specimens from Agilent\u0026rsquo;s internal tumor bank.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Results from this study highlight the significance of PD-L1 staining TC and MIC inclusion in the CPS algorithm across five tumor types.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cem\u003eAgilent\u0026rsquo;s Internal Tumor Bank\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUnique specimens with scores spanning the dynamic range of PD-L1 expression (CPS 1\u0026ndash;100) from Agilent\u0026rsquo;s internal tumor bank were analyzed for TNBC (n\u0026thinsp;=\u0026thinsp;281), UC (n\u0026thinsp;=\u0026thinsp;411), HNSCC (n\u0026thinsp;=\u0026thinsp;457), EC (n\u0026thinsp;=\u0026thinsp;716), and GC/GEJ (n\u0026thinsp;=\u0026thinsp;290). All specimens were deidentified and commercially procured from licensed tissue vendors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSpecimen Preparation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA specimen is defined as a tumor tissue block that was formalin-fixed and paraffin-embedded (FFPE). Sections were cut at 4 \u0026micro;m thickness and placed on either a Dako FLEX IHC Microscope Slide (Code K8020; Dako North America, Inc., Carpinteria, CA) or a Superfrost Plus glass slide, and oven-dried at 58\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for one hour. Sections were stored in the dark at 2\u0026ndash; 8\u0026deg;C before immunostaining with PD-L1 IHC 22C3 pharmDx (Code SK006; Agilent Technologies, Inc., Santa Clara, CA). Further specimen preparation and storage condition details can be found in the PD-L1 IHC 22C3 pharmDx Instructions for Use (IFU).\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e This retrospective study evaluates the CPS, TPS, CID, and the PD-L1 expression pattern for the five tumor types included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePD-L1 IHC 22C3 pharmDx Staining Protocol\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSpecimens were pretreated using a 3- in-1 procedure that included deparaffinization, rehydration, and target retrieval using a PT Link (Code PT100/PT101/PT200) with a low pH TRS (Code K8005; Dako North America, Inc., Carpinteria, CA). Specimens were then stained using the Autostainer Link 48 platform with PD-L1 IHC 22C3 pharmDx according to the staining protocol described in the IFU.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The stained specimens were counterstained with hematoxylin (Code K8008; Agilent Technologies, Inc., Santa Clara, CA) and coverslipped.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSpecimen Scoring\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll specimens were scored using TPS and CPS according to tumor type-specific scoring criteria.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The CPS and TPS results were then leveraged to calculate CID post-hoc. Specimens were evaluated using a light microscope by trained pathologists. Each specimen was evaluated by one pathologist.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCPS equation\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eCPS is the number of PD-L1 staining cells (TCs, lymphocytes, and macrophages) divided by the total number of viable TCs, multiplied by 100. Although the result of the calculation can exceed 100, the maximum score is defined as CPS 100.\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:\\varvec{C}\\varvec{P}\\varvec{S}=\\frac{ \\:\\varvec{P}\\varvec{D}-\\varvec{L}1\\:\\varvec{s}\\varvec{t}\\varvec{a}\\varvec{i}\\varvec{n}\\varvec{i}\\varvec{n}\\varvec{g}\\:\\varvec{c}\\varvec{e}\\varvec{l}\\varvec{l}\\varvec{s}\\:(\\varvec{t}\\varvec{u}\\varvec{m}\\varvec{o}\\varvec{r}\\:\\varvec{c}\\varvec{e}\\varvec{l}\\varvec{l}\\varvec{s},\\:\\varvec{l}\\varvec{y}\\varvec{m}\\varvec{p}\\varvec{h}\\varvec{o}\\varvec{c}\\varvec{y}\\varvec{t}\\varvec{e}\\varvec{s},\\:\\varvec{m}\\varvec{a}\\varvec{c}\\varvec{r}\\varvec{o}\\varvec{p}\\varvec{h}\\varvec{a}\\varvec{g}\\varvec{e}\\varvec{s})}{\\varvec{T}\\varvec{o}\\varvec{t}\\varvec{a}\\varvec{l}\\: \\:\\varvec{o}\\varvec{f}\\:\\varvec{v}\\varvec{i}\\varvec{a}\\varvec{b}\\varvec{l}\\varvec{e}\\:\\varvec{t}\\varvec{u}\\varvec{m}\\varvec{o}\\varvec{r}\\:\\varvec{c}\\varvec{e}\\varvec{l}\\varvec{l}\\varvec{s}}\\:\\varvec{X}\\:100$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eTPS equation\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eTPS is the percentage of viable tumor cells showing partial or complete membrane staining at any intensity.\u003c/p\u003e\n\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equb\" class=\"mathdisplay\"\u003e$$\\:\\varvec{T}\\varvec{P}\\varvec{S}\\:\\left(\\varvec{\\%}\\right)=\\frac{\\:\\varvec{P}\\varvec{D}-\\varvec{L}1\\:\\varvec{s}\\varvec{t}\\varvec{a}\\varvec{i}\\varvec{n}\\varvec{i}\\varvec{n}\\varvec{g}\\:\\varvec{t}\\varvec{u}\\varvec{m}\\varvec{o}\\varvec{r}\\:\\varvec{c}\\varvec{e}\\varvec{l}\\varvec{l}\\varvec{s}}{\\varvec{T}\\varvec{o}\\varvec{t}\\varvec{a}\\varvec{l}\\: \\:\\varvec{o}\\varvec{f}\\:\\varvec{v}\\varvec{i}\\varvec{a}\\varvec{b}\\varvec{l}\\varvec{e}\\:\\varvec{t}\\varvec{u}\\varvec{m}\\varvec{o}\\varvec{r}\\:\\varvec{c}\\varvec{e}\\varvec{l}\\varvec{l}\\varvec{s}\\:}\\:\\varvec{x}\\:100\\:$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eCID equation\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eCID is calculated by subtracting the TPS value from CPS. CID was calculated post-hoc to provide an estimate of PD-L1 staining MIC (or lack of TC staining) contribution to CPS.\u003c/p\u003e\n\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equc\" class=\"mathdisplay\"\u003e$$\\:\\varvec{C}\\varvec{I}\\varvec{D}=\\varvec{C}\\varvec{P}\\varvec{S}-\\varvec{T}\\varvec{P}\\varvec{S}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eAlthough the CID score is an indirect measurement, CID still provides an estimate of PD-L1 staining MIC contribution to CPS. The CPS algorithm has a maximum score of 100 and does not capture cases where staining MICs exceed the number of total TCs. As such, in cases where CPS\u0026thinsp;=\u0026thinsp;100, specimens were removed from the stratification analysis.\u003c/p\u003e\n\u003cp\u003eThe distribution of CPS values for specimens that were PD-L1-expressing (CPS\u0026thinsp;\u0026ge;\u0026thinsp;1) with corresponding representation of TPS and CID was plotted for each tumor type. For each tumor type, specimens were rank ordered based on CPS value. For visual interpretation, specimens were plotted against the square root of the CPS value. The CPS for each specimen was further broken into TPS and CID components to understand trends in TC and MIC staining patterns across tumor types.\u003c/p\u003e\n\u003cp\u003eUnique specimens from Agilent\u0026rsquo;s internal tumor bank that were PD-L1-expressing (CPS\u0026thinsp;\u0026ge;\u0026thinsp;1) were stratified into five categories based on the PD-L1 staining in TCs and MICs: Tumor Only (TPS\u0026thinsp;=\u0026thinsp;CPS, CID\u0026thinsp;=\u0026thinsp;0); Majority Tumor (TPS\u0026thinsp;\u0026gt;\u0026thinsp;CID); Equal Tumor and Immune (TPS\u0026thinsp;=\u0026thinsp;CID); Majority Immune (TPS\u0026thinsp;\u0026lt;\u0026thinsp;CID); and Immune Only (CID\u0026thinsp;=\u0026thinsp;CPS, TPS\u0026thinsp;=\u0026thinsp;0). Once the expression patterns were determined for each specimen, the distribution of specimens that fell into each of these categories for each tumor type was calculated.\u003c/p\u003e\n\u003cp\u003eThe proportion of PD-L1 staining that was contributed by TCs for each specimen was calculated as (TPS/CPS)*100. The distributions of the TC proportions were then plotted separately for specimens that were above and below the respective cutoffs for each tumor type. For each tumor type within each cutoff, the Wilcoxon Rank-Sum Test was applied to test whether a statistical difference in distributions of TC proportions existed between specimens that fell above and below the cutoff. Since only CPS\u0026thinsp;\u0026ge;\u0026thinsp;1 specimens were included in this analysis, the Wilcoxon Rank-Sum Test was not performed for the CPS\u0026thinsp;\u0026ge;\u0026thinsp;1 cutoff. Therefore, this statistical test was only applied to the CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 and CPS\u0026thinsp;\u0026ge;\u0026thinsp;20 cutoffs. All data generated to support the findings of this study are included in this published article.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTo evaluate how PD-L1 staining TC and MIC contribution to the CPS may shift across the range of PD-L1 expression (CPS 1-100), we plotted the TPS and CID by tumor type (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. At a high level, these results demonstrate that MICs contribute more to the CPS than TCs in EC, GC and TNBC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e; \u003cb\u003eA, B, and D\u003c/b\u003e). In contrast, TCs contribute more to the CPS than MICs in HNSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). In UC, there is a shift from greater MIC contribution to greater TC contribution to the CPS as CPS increases across the dynamic range of PD-L1 expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. These results demonstrate how PD-L1 expression patterns of TCs and MICs may vary throughout the dynamic range of PD-L1 expression and across different tumor types.\u003c/p\u003e\u003cp\u003eTo further characterize the contribution of TCs and MICs to the CPS, specimens were grouped by tumor type and then categorized based on the PD-L1 expression patterns in TCs and MICs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e). Across all tumor types, at least 41% of specimens demonstrated PD-L1 staining TCs, and at least 69% of specimens demonstrated PD-L1 staining MICs. Notably, UC had nearly equal representation of specimens with PD-L1 staining TCs and MICs; 70% and 69%, respectively. In EC, the proportion of specimens expressing the Tumor Only, Majority Immune, and Immune Only patterns were 2.9%, 30.9%, and 52.9%, respectively \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The same pattern was present in GC/GEJ, with only 5.6% of specimens expressing Tumor Only staining, while 21.7% expressed Majority Immune staining and 58.7% expressed Immune Only staining \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. In HNSCC, 12.2% of specimens expressed Tumor Only staining, 40.5% expressed Majority Tumor staining, and only 14.2% of specimens expressed Immune Only staining \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. TNBC expression patterns were similar to those of GC/GEJ and EC, with only 4.1% of specimens expressing Tumor Only staining, while 30.3% expressed Majority Immune staining and 48.4% expressed Immune Only staining \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Lastly, UC PD-L1 expression was more balanced between TCs and MICs, with 31.2% of specimens expressing Tumor Only staining, 17.5% expressing Majority Tumor staining, 4.4% expressing Equal Tumor and Immune staining, 17.1% expressing Majority Immune staining, and 29.8% expressing Immune Only staining \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Both TCs and MICs contributed meaningfully to the CPS across all tumor types: 44% of EC, 36% of GC/GEJ, 74% of HNSCC, 48% of TNBC, and 39% of UC specimens had PD-L1 expression in both cell types. These results demonstrate the PD-L1 expression patterns of TCs and MICs in these tumor types and reveal that both PD-L1 staining MICs and TCs are important drivers of the CPS. The PD-L1 expression patterns of TCs and MICs can vary across tumor types, showing that both cell types are important to consider when determining PD-L1 expression levels for multiple tumor types. Furthermore, these data highlight the value in using CPS, an algorithm which captures both PD-L1 staining TCs and MICs.\u003c/p\u003e\u003cp\u003eNext, we evaluated differences in PD-L1-expressing TCs and MICs relative to CPS cutoffs. The percent contribution of TCs (represented by the TPS) relative to the CPS was calculated for each cutoff and tumor type \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. For the CPS\u0026thinsp;\u0026ge;\u0026thinsp;1 cutoff, the median percent contribution of TCs in GC/GEJ, TNBC, and HNSCC was 0%, 2.1%, and 66.7%, respectively \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e Analysis of EC, TNBC, and UC specimens evaluated at CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 revealed that specimens above the cutoff demonstrated significantly increased TC contributions compared to specimens below the cutoff (Wilcoxon Rank-Sum Test p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.005). Specimens above the CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 cutoff demonstrated 10%, 5%, and 91% increased median TC contribution when compared to specimens below the cutoff for EC, TNBC, and UC, respectively \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. In HNSCC, TC contribution for specimens above the CPS\u0026thinsp;\u0026ge;\u0026thinsp;20 was also significantly increased by 56% when compared to specimens below the cutoff (Wilcoxon Rank-Sum Test p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. These results highlight the critical role of PD-L1 staining TCs when evaluating specimens at CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 and CPS\u0026thinsp;\u0026ge;\u0026thinsp;20 using PD-L1 IHC 22C3 pharmDx.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePrevious reports document both TCs and MICs express PD-L1 and influence the progression of disease.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Higher levels of PD-L1 expression are associated with therapeutic response from anti-PD-(L)-1 agents.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e As such, PD-L1 serves as a predictive biomarker for patient response to immune checkpoint inhibitors. PD-L1 IHC 22C3 pharmDx evaluates PD-L1 expression using CPS, and contributors to this algorithm include PD-L1 staining TCs and MICs.\u003c/p\u003e\u003cp\u003eWhen characterizing the contribution of TCs and MICs to the CPS, this study reports that approximately half of all specimens demonstrate PD-L1 staining TCs and PD-L1 staining MICs across the investigated tumor types. Not only did the PD-L1 expression in TCs and MICs vary across tumor types, but also across the dynamic range of PD-L1 expression. The contribution of PD-L1-expressing TCs and MICs was relatively balanced in UC. The CPS for EC, GC/GEJ, and TNBC was heavily driven by PD-L1-expressing MICs. In contrast, the CPS for HNSCC was driven by PD-L1-expressing TCs. These results highlight differences in PD-L1 expression patterns across tumor types while also confirming that both PD-L1 staining MICs and TCs are important drivers of the CPS across the dynamic range of PD-L1 expression. Literature suggests that there may be organ- or tumor type-specific physiological and histological profiles that are reflected in the prevalence of PD-L1 staining TCs and MICs.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Previous studies show that PD-L1 expression in TNBC is highly driven by PD-L1 staining MICs,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e consistent with our reports. To date, there is limited literature on PD-L1 expression patterns in the tumor microenvironment of EC and GC/GEJ specimens.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eWe then narrowed our focus to understand if differences in PD-L1-expressing TCs and MICs exist around specific CPS cutoffs. Specimens above the CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 and CPS\u0026thinsp;\u0026ge;\u0026thinsp;20 cutoff demonstrate significantly increased TC contribution to the CPS compared to specimens below the cutoff. Although the CPS for EC and TNBC is driven by MICs when evaluated across the dynamic range of PD-L1 expression, TC contribution to the CPS is significantly higher in specimens above the cutoff. Collectively, these results demonstrate that while the CPS for some tumor types is driven by PD-L1-expressing MICs, PD-L1-expressing TCs specifically may drive the CPS above a respective cutoff. Ward et al. evaluated both the TPS and CPS of UC specimens, reporting that while 29.7% of UC specimens are positive at TPS\u0026thinsp;\u0026ge;\u0026thinsp;1, 86.5% of specimens were positive at CPS\u0026thinsp;\u0026ge;\u0026thinsp;1.\u003csup\u003e24\u003c/sup\u003e Taken together, these results and our data demonstrate how CPS is a comprehensive algorithm for determining PD-L1 expression in the tumor microenvironment. Both prior literature and findings from this study further highlight the value of using an algorithm such as CPS, which captures both PD-L1 staining TCs and MICs.\u003c/p\u003e\u003cp\u003eWhile we acknowledge that the clinical impact of scoring both TCs and MICs is critical to the utility of CPS in practice, the goal of this work was to explore the analytical impact of PD-L1 staining TCs and MICs contributing to the CPS across multiple tumor types using PD-L1 IHC 22C3 pharmDx. Clinical outcomes of patient stratification using PD-L1 IHC 22C3 pharmDx with CPS may be explored in a future manuscript.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese data underscore that both PD-L1 staining TCs and MICs are critical contributors to the CPS across multiple tumor types. This work is given further significance by the clinical utility of PD-L1 IHC 22C3 pharmDx testing and CPS scoring to identify patients who may benefit from treatment with KEYTRUDA.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e These results provide insight on PD-L1 expression patterns to pathologists who use CPS for scoring various tumor types stained with PD-L1 IHC 22C3 pharmDx.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflicts of Interest\u003c/h2\u003e\n\u003cp\u003eThe authors have indicated the following conflicts of interest that relate to the content of this manuscript: Tiffany Evans M.S., Epiphani Simmons Ph.D., Jay Milo M.A.S., Jim Ruvalcaba-Rodarte, M.S., Stephanie Hund, B.S., Julia Hand MSBME, Brittany Watts B.S., Darlene Krohn Ph.D., Siena Tabuena-Frolli B.S., Karina Kulangara Ph.D., Kelly Martyniuk Ph. D. are employees of Agilent Technologies and own Agilent stock.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have indicated the following conflicts of interest that relate to the content of this manuscript: Tiffany Evans M.S., Epiphani Simmons Ph.D., Jay Milo M.A.S., Jim Ruvalcaba-Rodarte, M.S., Stephanie Hund, B.S., Julia Hand MSBME, Brittany Watts B.S., Darlene Krohn Ph.D., Siena Tabuena-Frolli B.S., Karina Kulangara Ph.D., Kelly Martyniuk Ph. D. are employees of Agilent Technologies and own Agilent stock.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eTE, JR, CL, JH, BW, performed the research.TE, ES, JM, SH, CL, JH, STF, KM designed the research study.TE, ES, STF, KM analyzed the data.TE, ES, SH, JH, DK, STF, KK, KM wrote the paper.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eStudies were supported by Agilent Technologies and Merck Sharp \u0026amp; Dohme LLC, a subsidiary of Merck \u0026amp; Co., Inc., Rahway, NJ, USA. Tissue samples were supplied by BioIVT Asterand\u0026reg;.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data generated to support the findings of this study are included in this published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCheung, C. C. et al. 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Mol. morphology: AIMM\u003c/em\u003e. \u003cb\u003e30\u003c/b\u003e (1), 56\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/PAI.0000000000000957\u003c/span\u003e\u003cspan address=\"10.1097/PAI.0000000000000957\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"or Phrases PD-L1 IHC 22C3 pharmDx, Combined Positive Score (CPS), Tumor Cell (TCs), Mononuclear Inflammatory Cells (MICs), Pembrolizumab (KEYTRUDA®)","lastPublishedDoi":"10.21203/rs.3.rs-7077026/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7077026/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePD-L1 IHC 22C3 pharmDx (SK006) is currently FDA-approved for use with pembrolizumab (KEYTRUDA) for non-small cell lung cancer, esophageal squamous cell cancer, cervical cancer, head and neck squamous cell carcinoma (HNSCC), triple-negative breast cancer (TNBC), and gastric and gastroesophageal junction (GC/GEJ) adenocarcinoma. This study evaluates the contribution of PD-L1 staining tumor cells (TCs) and mononuclear inflammatory cells (MICs) when determining the Combined Positive Score (CPS) with SK006. We retrospectively analyzed TNBC, urothelial carcinoma (UC), HNSCC, esophageal cancer (EC), and GC/GEJ specimens. Specimens were stained and scored using CPS (PD-L1 staining TCs and MICs) and Tumor Proportion Score (TPS; PD-L1 staining TCs only). We then determined a specimen\u0026rsquo;s calculated immune cell density (CID), and TC/MIC PD-L1 expression ratio. Analysis revealed PD-L1-expressing TCs and MICs were both present in 36% of all specimens. PD-L1-expressing TCs contributed significantly more than MICs in specimens above CPS\u0026thinsp;\u0026ge;\u0026thinsp;10 and CPS\u0026thinsp;\u0026ge;\u0026thinsp;20 cutoffs. Collectively, these results demonstrate that while the CPS for some tumor types is driven by PD-L1-expressing MICs, PD-L1-expressing TCs may drive the CPS above a cutoff for other tumor types. As such, both TCs and MICs remain important contributors to the CPS. These findings highlight CPS as a comprehensive scoring algorithm when using SK006.\u003c/p\u003e","manuscriptTitle":"Contribution of PD-L1-expressing tumor and immune cells to the Combined Positive Score (CPS) using PD-L1 IHC 22C3 pharmDx","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-22 00:52:33","doi":"10.21203/rs.3.rs-7077026/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-17T20:42:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28494874069050577001412344148439357563","date":"2025-12-17T14:58:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256732024415877453439456101378002146598","date":"2025-11-13T23:58:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-11T14:20:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-11T11:17:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-15T05:00:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-11T15:52:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-11T15:49:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cfd4b581-94d6-48ce-a7ea-5784d117d227","owner":[],"postedDate":"November 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":57962419,"name":"Biological sciences/Cancer"},{"id":57962420,"name":"Biological sciences/Immunology"},{"id":57962421,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-11-22T00:52:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-22 00:52:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7077026","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7077026","identity":"rs-7077026","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}