PD-L1 Expression Patterns Research Articles

SIGLEC15, negatively correlated with PD-L1 in HCC, could induce CD8+ T cell apoptosis to promote immune evasion

ABSTRACT Functional roles of SIGLEC15 in hepatocellular carcinoma (HCC) were not clear, which was recently found to be an immune inhibitor with similar structure of inhibitory B7 family members. SIGLEC15 expression in HCC was explored in public databases and further examined by PCR analysis. SIGLEC15 and PD-L1 expression patterns were examined in HCC samples through immunohistochemistry. SIGLEC15 expression was knocked-down or over-expressed in HCC cell lines, and CCK8 tests were used to examine cell proliferative ability in vitro. Influences of SIGLEC15 expression on tumor growth were examined in immune deficient and immunocompetent mice respectively. Co-culture system of HCC cell lines and Jurkat cells, flow cytometry analysis of tumor infiltrated immune cells and further sequencing analyses were performed to investigate how SIGLEC15 could affect T cells in vitro and in vivo. We found SIGLEC15 was increased in HCC tumor tissues and was negatively correlated with PD-L1 in HCC samples. In vitro and in vivo models demonstrated inhibition of SIGLEC15 did not directly influence tumor proliferation. However, SIGLEC15 could promoted HCC immune evasion in immune competent mouse models. Knock-out of Siglec15 could inhibit tumor growth and reinvigorate CD8+ T cell cytotoxicity. Anti-SIGLEC15 treatment could effectively inhibit tumor growth in mouse models with or without mononuclear phagocyte deletion. Bulk and single-cell RNA sequencing data of treated mouse tumors demonstrated SIGLEC15 could interfere CD8+ T cell viability and induce cell apoptosis. In all, SIGLEC15 was negatively correlated with PD-L1 in HCC and mainly promote HCC immune evasion through inhibition of CD8+ T cell viability and cytotoxicity.

Exploration of different immunogenomic TMEs in gastric cancer based on HER2 and PD-L1 expression.

e16073 Background: Recent results from the KEYNOTE-811 study showed that first-line pembrolizumab was superior to placebo with respect to progression-free survival (PFS) in combination with trastuzumab and chemotherapy in patients with HER2 positive metastatic gastric cancer (GC). Interestingly, In the subgroup analysis, the PFS benefit with pembrolizumab was significant in patients with tumors with PD-L1 CPS ≥1, whereas there was no benefit in the small subgroup of patients with tumors with CPS < 1. Therefore, this study is to investigate immune-genomic differences in the tumor microenvironment according to the composition of surrounding cells and the expression status of HER2 and PD-L1. Methods: Utilizing single cell RNA sequencing (scRNA seq) and TCR sequencing, we examined 14 HER2 positive and 18 negative primary GC samples with CPS score based on PD-L1 IHC 22C3 pharmDx. Among the HER2-positive group, there were 4 samples in the CPS < 1 (negative) and 10 samples in the CPS ≥1 (positive) group. In the HER2 negative group, there were 6 samples in the CPS < 1 and 12 samples in the CPS ≥1. Results: First, when analyzing the distribution of total cells according to HER2 status, in the HER2 positive group, more endothelial cells ( p= 0.034) and fibroblasts ( p= 0.054) appeared in the PD-L1 negative group compared to the PD-L1 positive group, while there was no difference in the HER2 negative group. Furthermore, Through TCR analysis, the exhausted and cytotoxic score exhibit contrasting trends between HER2 negative and positive groups. In HER2-positive patients, the exhausted and cytotoxic score appear significantly higher in the CPS negative group. Next, we evaluated the proportion of immune cells according to HER2 status. The observed of CD4 Treg ( p= 0.084) and CD8 exhausted T (Tex), ( p= 0.036) cells was increased in the HER2 positive compared to the negative. When regrouped according to PD-L1 expression, only the HER2 positive group showed a tendency to increase the observation of CD4 Treg and CD8 Tex cells compared to positive in PD-L1 negative. In addition, we investigated whether the expression pattern of other immune checkpoint molecules differed depending on the PD-L1 expression pattern in both HER2 positive and negative patients. In the HER2 negative group, the expression of immune checkpoint proteins was similar regardless of the CPS expression group, or the expression of some proteins was higher in the CPS positive group. In other hands, in HER2 positive, CPS < 1 group had higher expression of immune checkpoint proteins, such as PDCD1, LAG2, BTLA, VISTA and TIGHT. Conclusions: The high proportion of CD4 Tregs, CD8 Tex and the elevated exhausted score in the subgroup with CPS < 1 in HER2 positive GCs suggesting immune exclusive environment compared to her-2 and PD-L1 coexpressing group. Considering increased expression of immune checkpoint proteins other than PD-1/PD-L1, for patients with HER2-positive and CPS < 1, combination therapy with other immune checkpoint inhibitors rather than anti-PD-1/PD-L1 may be suggested.

Comprehensive analysis of TROP2, PD-L1, stromal (s)TILs, and HER2 expression patterns in patients (pts) with metastatic HR+HER2- breast cancer.

1062 Background: Immune checkpoint inhibitors (ICI) have shown limited efficacy in hormone receptor positive (HR+) metastatic breast cancer (mBC) and the optimal ICI-based combination is unknown. The TROP2 antibody-drug conjugate sacituzumab govitecan (SG) demonstrated antitumor activity with a 5.5-month median PFS in endocrine refractory HR+ mBC. Given SG's potential for anticancer immunity, we sought to evaluate expression patterns of biomarkers of interest in HR+ mBC. Methods: This retrospective study included pts with HR+HER2- mBC identified at DFCI between 10/2020 and 12/2021 who received 0-1 prior lines of chemotherapy in the metastatic setting and consented to analysis of archival FFPE tissue samples. We aimed to 1) characterize expression patterns of TROP2 (SP295 H-score), PD-L1 (22C3 CPS), sTILs and HER2 (per central pathology review) in the most recent available sample; 2) assess the prognostic value of selected biomarker combinations for overall survival (OS) defined as the time from consent to either death due to any cause or last follow-up (Cox proportional hazard models; p-value <0.05 considered significant). Results: Among 142 pts included, median age at diagnosis was 46 yrs (IQR: 40–56). Baseline characteristics are shown (Table). At least one biomarker was available for 123 subjects (86.6%). TROP2 expression (n=61) was Medium/High (M-H: 101-300) in 43 pts (70.5%) and Low (L: 0-100) in 18 (29.5%). PD-L1 central assessment (n=120) revealed CPS ≥1 (PD-L1+) in 32 pts (26.7%) and <1 (PD-L1-) in 88 (73.3%); only 7 (5.8%) pts had CPS ≥10. sTILs (n=87) were ≥10% in 14 pts (16.1%) and <10% in 73 (83.9%). When analyzing TROP2 and PD-L1 (n=61), 15 pts (24.6%) were TROP2-M-H/PD-L1+, 28 (45.9%) were TROP2-M-H/PD-L1-, 5 (8.2%) were TROP2-L/PD-L1+, and 13 (21.3%) were TROP2-L/PD-L1-. When analyzing TROP2 and sTILs (n=54), 6 pts (11.1%) were TROP2-M-H/sTILs ≥10%, 32 (59.3%) were TROP2-M-H/sTILs <10%, 2 (3.7%) were TROP2-L/sTILs ≥10% and 14 (25.9%) were TROP2-L/sTILs <10%. For TROP2 and HER2 (n=46), 26 pts (56.5%) had TROP2-M-H/HER2-low tumors, 7 (15.2%) TROP2-M-H/HER2-0, 3 (6.5%) TROP2-L/HER2-low, and 10 (21.7%) TROP2-Low/HER2-0. Median OS (n=138) was 43.8 months; stratification for selected biomarker combinations will be presented although no statistical significance was found. Correlations with NGS data and HER2DX are ongoing and will be presented. Conclusions: Analyzing biomarkers of interest in pts with HR+ mBC unveiled diverse patterns, without associations with OS. Patient characteristics. [Table: see text]

PD-L1 and alternative immune checkpoints (AICs) in non-small cell lung cancer (NSCLC): Insights into the tumor immune microenvironment (TIME) and immunotherapy (IO) outcomes.

8531 Background: PD-L1 and recently identified AICs (B7x, B7-H3, and HHLA2) may function as key immune evasion mechanisms in NSCLC and influence IO efficacy. This study explores the expression patterns of PD-L1 and AICs within the TIME and their impact on IO outcomes in NSCLC, including key molecular subtypes. Methods: NSCLC samples (n=27,629) were analyzed (Caris Life Sciences) with NextGen Sequencing on DNA (592 genes or whole exome)/RNA (whole transcriptome). Tumor cell PD-L1 expression (22c3) was assessed by IHC. Gene expression profiles were analyzed for IFN-γ score and QuantiSEQ was used to assess immune cell infiltration in the TIME. Real-world overall survival (rwOS: from time of biopsy to last contact), time on treatment [TOT: from the first pembrolizumab (pembro) treatment to the last], and OS on pembro (OSpem: from pembro start to last contact) were calculated. Mann-Whitney U, X2/Fisher-Exact, and log-rank tests were applied where appropriate. Results: PD-L1 IHC+ NSCLC and cases with high PD-L1 RNA expression had higher IFN-γ score and immune cell fractions (p<0.0001 for both) vs PD-L1 IHC- and low expression, respectively. Additionally, PD-L1 IHC+ NSCLC was associated with (a/w) higher median transcript levels (TPM) of PD-L1 and B7-H3, while PD-L1 IHC- NSCLC was a/w higher TPM of HHLA2 and B7x (p<0.0001 for all). AICs expression varied by molecular subtype, e.g., higher HHLA2/B7x RNA in EGFR mutant vs wild-type (WT) NSCLC. Moreover, PD-L1 IHC+ NSCLC and cases with high PD-L1 RNA and low B7H3 RNA were a/w longer rwOS, OSpem, and TOT; high HHLA2 RNA was a/w longer rwOS and OSpem with similar TOT; and low B7x RNA expression was a/w longer OSpem and TOT with similar rwOS (Table). Conclusions: Both PD-L1 IHC+ NSCLC and cases with high PD-L1 RNA expression are a/w a more inflammatory TIME, and superior survival and IO outcomes. Moreover, consistent with our prior HHLA2 IHC work (PMIDs: 27553831, 29374053), HHLA2 RNA expression was significantly higher in PD-L1 IHC- and EGFR mutant cases. These findings support the potential utility of transcriptomics along with protein expression for assessing novel predictive biomarkers for IO. Furthermore, the distinct expression profiles of AICs identified in our study may represent key subtypes mediating IO response in WT and EGFR mutant NSCLC. [Table: see text]

Abstract PO3-13-05: PD-L1 and PD-L2 Protein Expression is Frequently Discordant in Breast Cancer

Abstract Background: In neoadjuvant setting, PD-1 inhibitors have shown significantly higher pathological responses in patients (pts) with early-stage triple-negative breast cancer (TNBC) irrespective of PD-L1 status. However, durable responses are less common in estrogen receptor-positive (ER+) pts. Most breast cancer (BC) clinical trials of PD-1 inhibitors have thus far focused on PD-L1 expression for patient eligibility. The alternative PD-1 ligand, PD-L2, with reported ~4-fold greater affinity for PD-1, has been largely understudied. We recently reported that high cancer cell protein levels of PD-L2 in pts with treatment-naïve ER+ BC was an independent predictor of shorter progression-free survival. PD-L2 expression was significantly high in ER- group as well, however, given the low numbers of ER- pts, the study was not powered enough to determine the correlation of PD-L2 with PFS in the ER- subgroup. These findings suggest that PD-L2 has an important role in BC and combined PD-L1/PD-L2 status may help improve BC pt selection for PD-1 inhibitors. We therefore initiated efforts to determine baseline expression patterns of PD-L1 and PD-L2 in BC. Methods: PD-L1 and PD-L2 protein levels in cancer cells and tumor-infiltrating immune cells were prospectively analyzed by immunohistochemistry (IHC) using validated antibodies in diagnostic core biopsies of 31 consecutive pts diagnosed with localized or locoregional ER+/HER2- BC or TNBC. Percent positivity of PD-L1 and PD-L2 in cancer cells and immune cells was determined by our breast pathologist. Detectable PD-L1 or PD-L2 expression in ≥1% of cancer cells or stromal immune cells was considered positive. Spearman correlation and Wilcoxon paired analyses were used to measure and correlate PD-L1 and PD-L2 protein expression in cancer and immune cells. Results: There was no significant correlation between PD-L1 and PD-L2 expression, neither across all cases (N=31), nor within ER+ (N=22) or TNBC (N=9) cases. However, PD-L1 and PD-L2 expression patterns in BC differed in several ways. PD-L1-positivity in immune cells was higher than in cancer cells (median=5.0% vs. 0.0%; p=0.001), whereas PD-L2-positivity was higher in cancer cells than in immune cells (median=30% vs. 5.0%; p< 0.001). PD-L1 positivity in cancer cells and immune cells were positively correlated in TNBC (rho=0.69, p=0.04) but not in ER+ BC. Conversely, PD-L2 positivity in cancer cells and immune cells were positively correlated in ER+ BC (rho=0.68, p=0.001) but not in TNBC. TNBC diverged from ER+ BC by displaying higher PD-L1 positivity in immune cells (median=20.0% vs. 1.0%; p=0.004). By the conventional cut point for positivity of ≥1% for PD-L1 and PD-L2 in cancer cells or immune cells, all TNBC tumors were PD-L1-positive (9/9), with 8 also being PD-L2-positive. Of the 22 ER+ cases, 16 were PD-L2-positive, of which only 9 were also PD-L1-positive. Table 1. shows cross tabulation data for PD-L1 and PD-L2 status by BC subtype. Conclusions: PD-L1 and PD-L2 proteins show divergent expression and are not correlated in BC. Discordant PD-L2 and PD-L1 expression may be more common in ER+ BC than in TNBC. This finding justifies efforts to explore PD-L2 as a complementary marker to PD-L1 for improved prediction of response to PD-1 inhibitors, which may benefit patients with aggressive ER+ BC that are eligible for chemotherapy. Table 1. PD-L1 vs. PD-L2 Status by Breast Cancer Subtype Citation Format: Lubna Chaudhary, Julie Jorns, Yunguang Sun, Sailaja Kamaraju, Yee Chung Cheng, Amanda Kong, Tina Yen, Caitlin Patten, Chandler Cortina, Inna Chervoneva, Christopher Chitambar, Hallgeir Rui. PD-L1 and PD-L2 Protein Expression is Frequently Discordant in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-13-05.

Divergent Cellular Expression Patterns of PD-L1 and PD-L2 Proteins in Breast Cancer.

PD-L1 immunohistochemistry (IHC) has become an established method for predicting cancer response to targeted anti-PD1 immunotherapies, including breast cancer (BC). The alternative PD-1 ligand, PD-L2, remains understudied but may be a complementary predictive marker. Prospective analysis of 32 breast cancers revealed divergent expression patterns of PD-L1 and PD-L2. PD-L1-positivity was higher in immune cells than in cancer cells (median = 5.0% vs. 0.0%; p = 0.001), whereas PD-L2-positivity was higher in cancer cells than immune cells (median = 30% vs. 5.0%; p = 0.001). Percent positivity of PD-L1 and PD-L2 were not correlated, neither in cancer cells nor immune cells. Based on a cut-point of ≥1% positivity, ER+ tumors (n = 23) were frequently PD-L2-positive (73.9%), whereas only 40.9% were PD-L1-positive. These data suggest differential control of cellular PD-L1 and PD-L2 expression in BC and a potential role for PD-L2 IHC as a complementary marker to PD-L1 to improve selection of aggressive ER+ BC that may benefit from anti-PD-1 therapy.

Abstract 6189: Deep-learning model trained on multiplex immunofluorescence-stained tissue samples predicts the survival of patients with non-small cell lung cancer better than PD-L1 TPS alone

Abstract In non-small cell lung cancer (NSCLC), the composition and structure of the tumor immune microenvironment (TME) critically impact patient outcomes, necessitating improved computational approaches to characterize the TME beyond traditional metrics like the PD-L1 tumor proportion score (TPS). Here, we developed an interpretable deep-learning model that robustly predicts patient overall survival (OS) and identifies unique PD-L1 enriched neighborhoods linked to patient prognosis. We utilized a dataset of 507 NSCLC patient biopsy samples prospectively acquired as part of the DFCI ImmunoPROFILE project. Each sample was stained for Cytokeratin as tumor marker, PD-L1, PD-1, CD8, and FOXP3 using a targeted multiplex immunofluorescence assay. Inner tumor regions of interest were automatically processed for spatially resolved identification and quantification of marker expression at the single-cell level. The dataset was divided into 380 patients for model development and 127 for testing. The deep-learning model, a graph neural network (GNN), was trained to predict OS based on local cell neighborhoods using a weakly supervised training paradigm. The GNN models neighborhoods as a graph, with cells and their corresponding marker expression representing nodes and edges connecting adjacent cells, for an average of 42 cells per neighborhood. Survival predictions were obtained by averaging predictions over all neighborhoods from one sample. The GNN model demonstrated robust performance with a concordance index (c-index) of 0.79 on the test data, surpassing traditional metrics such as TPS and immune marker density-based models (c-index: 0.50 and 0.74, respectively). Beyond assessing performance, we investigated the features learned by the GNN using k-means clustering in the model’s feature space. We identified three clusters that were notably enriched in PD-L1 positive tumor cells. The first cluster shows an especially “high TPS” phenotype, where the GNN predicted such neighborhoods to be generally poor for survival. The other two clusters were additionally enriched with PD-L1 positive immune cells (ICs) and associated with favorable survival predictions. Notably, one cluster was also enriched with other types of ICs (”PD-L1 IC mixed”), which the GNN predicted as especially favorable for survival compared to exclusive enrichment of PD-L1 ICs (”PD-L1 IC dominant”). A score summarizing these three PD-L1 expression patterns was significantly associated with OS (p-value: 0.01; HR: 0.72, 95% CI: 0.16-1.27), validating the features learned by the GNN. In sum, we developed a highly interpretable deep-learning model leveraging cellular neighborhood graphs, which effectively identifies expression patterns correlating with NSCLC prognosis, offering promise for developing personalized treatment strategies. Citation Format: Katharina Viktoria Hoebel, James R. Lindsay, Joao V. Alessi, Jason L. Weirather, Ian D. Dryg, Jennifer Altreuter, Mark M. Awad, Scott J. Rodig, William E. Lotter. Deep-learning model trained on multiplex immunofluorescence-stained tissue samples predicts the survival of patients with non-small cell lung cancer better than PD-L1 TPS alone [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6189.

Epstein-Barr Virus BRLF1 Induces PD-L1 Expression in Nasopharyngeal Carcinoma Cells.

Nasopharyngeal carcinoma (NPC) is a specific human malignancy with unique geographic distribution and genetic backgrounds. Although early treatment with radio-chemotherapy has been proven effective for NPC therapy, its therapeutic efficacy substantially diminishes in the late stages of this malignancy. In the tumor microenvironment of NPC, PD-L1 has been demonstrated as a critical factor in impairing T cell activation. As an etiological role for NPC development, it is found that Epstein-Barr virus (EBV) latent proteins upregulated PD-L1 expression. However, whether EBV lytic protein affects PD-L1 expression remains unclear. In this study, through monitoring the mRNA expression pattern of lytic genes and PD-L1 in EBV-positive NPC cell line NA, EBV immediately-early gene BRLF1(Rta) was found to have the potential for PD-L1 activation. Furthermore, we identified that Rta expression enhanced PD-L1 expression in mRNA and protein levels through quantitative real-time polymerase chain reaction and western blotting analysis. The luciferase reporter assay revealed that Rta expression enhanced PD-L1 promoter activity. We also demonstrated that Rta-induced PD-L1 expressions could impair interleukin 2 secretion of T cells, and this mechanism may be through ERK activation. These results displayed the importance of EBV Rta in PD-L1 expression in NPC and may give an alternative target for NPC therapy.

M1 macrophages induce PD-L1hi cell-led collective invasion in HPV-positive head and neck squamous cell carcinoma via TNF-α/CDK4/UPS14

BackgroundAlthough the roles of PD-L1 in promoting tumor escape from immunosurveillance have been extensively addressed, its non-immune effects on tumor cells remain unclear.MethodsThe spatial heterogeneity of PD-L1 staining in human...

The expression changes of PD-L1 and immune response mediators are related to the severity of primary bone tumors

The expression pattern, diagnostic value, and association of PD-L1, IFN-γ and TGF-β with bone tumor type, severity, and relapse are determined in this study. 300 human samples from patients with osteosarcoma, Ewing sarcoma, and GCT were enrolled. The PD-L1 gene and protein expression were assessed by qRT-PCR and immunohistochemistry, respectively. ELISA and flow cytometry was used to detect cytokines and CD4/CD8 T cell percentages, respectively. A considerable increase in PD-L1 level was detected in bone tumor tissues at both gene and protein levels that was considerable in osteosarcoma and Ewing sarcoma. A positive correlation was detected regarding the PD-L1 and tumor metastasis and recurrence in osteosarcoma and Ewing sarcoma. The increased IFN-γ level was detected in patients with metastatic, and recurrent osteosarcoma tumors that were in accordance with the level of TGF-β in these samples. The simultaneous elevation of IFN-γ and TGF-β was detected in Ewing sarcoma and GCT, also the CD4 + /CD8 + ratio was decreased significantly in patients with osteosarcoma compared to GCT tumors. The elevated levels of PD-L1, TGF- β, and IFN-γ were associated with bone tumor severity that can provide insights into the possible role of this axis in promoting immune system escape, suppression, and tumor invasion.

Immune microenvironment of intimal sarcomas: Adaptive immune resistance with potential therapeutic implications.

Intimal sarcomas are rare, aggressive neoplasms that arise from large blood vessels. Characterization of the tumor immune microenvironment may suggest new treatment strategies. Seventeen specimens from 7 patients were labeled by immunohistochemistry for programmed cell death 1 ligand 1 (PD-L1), CD45, CD8, CD4, FOXP3, CD20, CD68, and LAG3. The immune cell density was scored as a percentage of the tumor area (1+ [<5%], 2+ [5%-50%], 3+ [>50%]); PD-L1 expression was scored on tumor cells and on intratumoral immune cells. Immune marker density was quantified using image analysis software. All intimal sarcomas showed immune cell infiltration (41% were 1+, 53% were 2+, 6% were 3+). Tumor and immune cell PD-L1 labeling was seen in 35% and 76% of cases, respectively; PD-L1+ intimal sarcomas had higher CD45+, CD8+, FOXP3+, CD68+, and leukocyte activation gene 3 (LAG3)+ cell densities (P ≤ .01). Similarly, PD-L1 expression on immune cells correlated with higher densities of CD8+ and FOXP3+ cells (P < .04). Higher LAG3+ cell density correlated with higher CD68+ cell density and necrosis (P < .05). One patient with prolonged survival had the highest immune cell density and PD-L1 expression. These data show that intimal sarcomas have an active tumor microenvironment with an adaptive pattern of PD-L1 expression. Our results suggest that immunotherapy may be an effective treatment option.

Genomic alterations affecting tumor-infiltrating lymphocytes and PD-L1 expression patterns in triple-negative breast cancer.

Tumor-infiltrating lymphocytes (TILs) and programmed cell death 1 ligand 1 (PD-L1) remain imperfect in predicting clinical outcomes of triple-negative breast cancer because outcomes do not always correlate with the expression of these biomarkers. Genomic and transcriptomic alterations that may contribute to the expression of these biomarkers remain incompletely uncovered. We evaluated PD-L1 immunohistochemistry scores (SP142 and 28-8 assays) and TILs in our triple-negative breast cancer multiomics dataset and 2 immunotherapy clinical trial cohorts. Then, we analyzed genomic and transcriptomic alterations correlated with TILs, PD-L1 expression, and patient outcomes. Despite TILs serving as a decent predictor for triple-negative breast cancer clinical outcomes, exceptions remained. Our study revealed that several genomic alterations were correlated with unexpected events. In particular, PD-L1 expression may cause a paradoxical relationship between TILs and prognosis in certain patients. Consequently, we classified triple-negative breast cancers into 4 groups based on PD-L1 and TIL levels. The TIL-negative PD-L1-positive and TIL-positive PD-L1-negative groups were not typical "hot" tumors; both were associated with worse prognoses and lower immunotherapy efficacy than TIL-positive PD-L1-positive tumors. Copy number variation of PD-L1 and oncogenic signaling activation were correlated with PD-L1 expression in the TIL-negative PD-L1-positive group, whereas GSK3B-induced degradation may cause undetectable PD-L1 expression in the TIL-positive PD-L1-negative group. These factors have the potential to affect the predictive function of both PD-L1 and TILs. Several genomic and transcriptomic alterations may cause paradoxical effects among TILs, PD-L1 expression, and prognosis in triple-negative breast cancer. Investigating and targeting these factors will advance precision immunotherapy for patients with this disease.

Expression pattern of PD-1/PD-L1 in primary liver cancer with clinical correlation.

Immunotherapy, including ICIs, has emerged as an invaluable treatment option for advanced PLC. Nevertheless, the expression patterns of PD-L1 and PD-1 in PLC remain incompletely understood. In this study, the expression pattern and clinical correlation of PD-L1 and PD-1 were analysed in 5245 PLC patients. The positivity rates of PD-L1 and PD-1 were very low in the patient PLCs, but the positivity rates of PD-L1 and PD-1 were higher in the ICC and cHCC-ICC than in HCC. The expression of PD-L1 and PD-1 correlated with the malignant phenotypes and clinicopathological characteristics of PLC. Interestingly, PD-1 positivity might serve as an independent prognostic factor. Based on a systematic analysis of a large amount of PLC tissues, we proposed a novel classification of PD-1/PD-L1 expression in HCC and ICC. In light of this stratification, we observed a close correlation between PD-L1 levels and PD-1 expression in HCC and ICC.

Subsets of interferon signaling and response to immune checkpoint blockade.

9522 Background: Interferon (IFN) signaling in tumors is critical for both response and resistance to immune checkpoint inhibitors (ICI). While PD-L1 is an approved biomarker for ICI response in some cancers, most have no approved biomarkers for ICI response. Further, there are no clinical strategies to predict IFN sensitive vs resistant states. We hypothesized that distinct patterns of IFN signaling in melanoma, including STAT1 (precursor to IFN signaling), phosphorylated STAT1 (pSTAT1, marker of active IFN signaling), and PD-L1 (canonical inhibitory output), are associated with response or resistance to ICI. Methods: Samples from 2 tissue microarrays of 97 patients total with metastatic melanoma who received ICI from 2011-2017 were randomized into discovery [D] or validation [V] cohorts. Multiplexed immunofluorescent microscopy was used to assess STAT1, pSTAT1, and PD-L1. 54 tumors were assessed for CD3. Signals were quantified via AQUA (Automated Quantitative Analysis). High vs low signals were defined around the discovery cohort median AQUA scores. Treatment response was assessed using RECIST, and 3-year survival was analyzed. For in vitro studies, 4 human melanoma cell lines were stimulated with IFNγ/β, and Western blots were performed for STAT1, pSTAT1, and PD-L1. Results: Median follow up time was 20.2 mos (range 0.9-95.4 mos). Higher overall histospot, tumor, and nuclear STAT1 were in responders (CR/PR/SD &gt; 6 mos) compared to non-responders (SD &lt; 6 mos/PD, histospot p = 0.029 [D] and 0.040 [V]) and were associated with improved survival (histospot HR 0.25 [95% CI 0.08-0.76] p = 0.015 [D]; HR 0.32 [95% CI 0.12-0.84] p = 0.021 [V]). PD-L1 and pSTAT1 did not validate as associated with ICI response/survival. While many tumors had concordant high/low STAT1, pSTAT1, and PD-L1, many also had a discordant STAT1 or PD-L1 predominance. To assess the basis of this discordance, we performed IFN stimulation and Western blots of melanoma cell lines. IFNβ upregulated STAT1 greater than PD-L1 in both acute and chronic settings (p &lt; 0.001 and &lt; 0.001), while chronic IFNγ upregulated PD-L1 compared to the acute setting (p = 0.039) but not STAT1 (p = 0.105). Therefore, we hypothesized patients with discordant STAT1 and PD-L1 expression may have differential responses to ICI. In the overall cohort, STAT1highPD-L1high tumors (IFN engaged) were associated with improved survival compared to STAT1lowPD-L1low tumors (IFN low, HR 0.28 [95% CI 0.11-0.70] p = 0.007). Interestingly, STAT1highPD-L1low tumors were associated with improved survival compared to STAT1lowPD-L1high tumors (HR 0.28 [95% CI 0.08-0.94] p = 0.04). Accordingly, STAT1highPD-L1high and STAT1highPD-L1low tumors had greater CD3 AQUA scores compared to STAT1lowPD-L1low tumors (p &lt; 0.001 and p = 0.018 respectively). Conclusions: Combined STAT1 and PD-L1 expression patterns may better predict melanoma response to ICI and provide insight into IFN sensitive versus resistant states.

Regulation of the PD-1/PD-L1 axis in relapsing-remitting Multiple Sclerosis (P2-3.001)

<h3>Objective:</h3> The PD-1/PD-L1 (programmed cell death protein 1/programmed cell death ligand 1) axis plays an important role in the adaptive immune system and has influence on neoplastic and inflammatory diseases. The role of the PD-1/PD-L1 axis in multiple sclerosis (MS) has not yet been investigated in detail. We aimed to delineate distinct expression patterns in peripheral blood mononuclear cell (PBMC) subsets and to evaluate the role of soluble PD-1/PD-L1 in the context of MS. <h3>Background:</h3> PD-L1/PD-1 also exist in soluble forms (sPD-L1/sPD-1) shedded from cellular surfaces. In systemic autoimmune diseases, sPD-1/sPD-L1 serum levels and membrane-bound PD-1/PD-L1 on T and antigen-presenting cells are linked to disease activity and treatment response. In MS, the PD-1/PD-L1 axis and in particular the role of soluble PD-1/PD-L1 is poorly understood but may offer relevance as disease marker and potential target for therapeutic intervention. <h3>Design/Methods:</h3> In depth immunophenotyping by flow cytometry was performed on PBMCs of 49 patients with relapsing-remitting MS (RRMS) and 27 controls. sPD-1/sPD-L1 serum levels were analyzed in a cohort of 84 patients with RRMS and 36 controls. To evaluate the therapeutic potential of soluble PD-L1, 600 μg/kg recombinant protein was systemically administered in Experimental Autoimmune Encephalomyelitis (EAE), an animal model of MS. <h3>Results:</h3> Patients with RRMS displayed distinct cellular PD-1/PD-L1 expression patterns in PBMCs and an association of sPD-L1 with MS subtype and disease severity. Systemic administration of recombinant PD-L1 in EAE resulted in ameliorated disease severity and reduced infiltration of peripheral immune cells into the CNS. <h3>Conclusions:</h3> The marked expression of PD-1/PD-L1 in immune cell subsets of patients with RRMS, and the correlation of sPD-L1 with disease-severity offers promising potential for the use as a serum marker in the context of MS. Furthermore, enhancement of coregulatory PD-1/PD-L1 signaling by exogenous supplementation of sPD-L1 may serve as a novel therapeutic strategy for severe stages of acute neuroinflammation. <b>Disclosure:</b> Dr. Tsaktanis has nothing to disclose. Mr. Linnerbauer has nothing to disclose. Mrs. Loesslein has nothing to disclose. Prof. Hemmer has received personal compensation in the range of $0-$499 for serving as a Consultant for Vaccitech. Prof. Hemmer has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Prof. Hemmer has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Polpharma. Prof. Hemmer has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for TG Therapeutics. Prof. Hemmer has received personal compensation in the range of $0-$499 for serving on a Scientific Advisory or Data Safety Monitoring board for Allergy Care. The institution of Prof. Hemmer has received research support from Regeneron. The institution of Prof. Hemmer has received research support from German Research Foundation. The institution of Prof. Hemmer has received research support from German Ministry for Education and Research. The institution of Prof. Hemmer has received research support from European Commission. Prof. Hemmer has received intellectual property interests from a discovery or technology relating to health care. Prof. Hemmer has received intellectual property interests from a discovery or technology relating to health care. Mark Mühlau has nothing to disclose. Dr. Quintana has nothing to disclose. Prof. Rothhammer has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Prof. Rothhammer has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Merck. The institution of Prof. Rothhammer has received research support from German Research Foundation. The institution of Prof. Rothhammer has received research support from European Research Council.

Study of PD-L1 Expression in Tumours Based on Site and Histology of Tumour – The Experience of a Tertiary Referral Laboratory

Background: PD-L1 IHC test is used as a predictive biomarker using FDA-approved assays to select patients likely to benefit from immunotherapy in several advanced-stage tumors. We aim to present our data regarding the prevalence and expression pattern of PD-L1 across various tumors based on site and histology and compare them with those of the reported literature. Material and Methods: A retrospective study of 301 cases of various tumors at different sites was done for PD-L1 IHC using the 22С3 pharmDx assay on the recommended platform.Results: Out of 237 non small cell lung carcinoma cases, 14.7% were squamous and 85.2% were of nonsquamous histotype, with adenocarcinomas comprising the majority (82.2%). Fifty-seven percent of non small cell lung carcinoma was PD-L1 positive, 28.6% showed high expression. Sixty percent of the squamous and 56.4% of the non-squamous histotypes showed positive immunoexpression. Amongst non-squamous types, 56.4% of adenocarcinomas and 66.6% of sarcomatoid carcinomas were positive. At metastatic sites, 54.3% of on small cell lung carcinoma were positive. In head and neck squamous cell carcinoma, the majority (10/11) of cases were from the oral cavity; 81.8% of total cases were positive, 27.2% were strong expressors. For other sites, the number of cases showing PD-L1 immunopositivity is as follows: oesophageal squamous cell carcinoma (2/6), gastric adenocarcinoma (2/6), triple negative breast carcinoma (0/3), urothelial carcinoma (2/5), gall bladder (2/5), pancreatico-biliary (2/11), and colorectal (2/17) adenocarcinomas. In these tumors, PD-L1 immunoexpression did not differ significantly by age or gender. Conclusion: Our study showed PD-L1 immunopositivity in 57% of non small cell lung carcinoma and 81.8% of head and neck squamous cell carcinoma, which is comparable to international studies. Further studies with larger sample sizes are needed to see their expression pattern in tumors at other sites and with different histologies.

Abstract 6634: Digital and spacial characterization of PD-L1 expression and IVD assay performance in the immune landscape of head and neck squamous cell carcinoma: A multimodal approach

Abstract The anti-PD-L1 antibody (22C3) is used as a companion diagnostic for successful checkpoint inhibitor therapy in head and neck squamous cell carcinoma. The positive predictive value of this assay, however, is less than ideal as a high PD-L1 score does not necessarily associate with a good response, and a good response may be seen with a low or negative PD-L1 score. In principle, this could be due to lack of accuracy and/or precision of the assay, as well as biological factors, such as variable expression across tumor cells and interacting immune cells. In this study, we describe a digital image analysis algorithm to address assay-related problems and improve both accuracy and precision, as well as improve identification of PD-L1 expression in differing cell populations of the tumor microenvironment. In addition, we propose a panel of assays that in aggregate might reveal inherent heterogeneity among cases with similar PD-L1 score and thus provide vital context underlying the efficacy of checkpoint inhibitors in the clinic. Here we show that applying novel machine-learning based digital image analysis to multiplex assays together with digital scoring of PD-L1 provides an accurate and precise assessment of the real-world tumor milieu that we hypothesize will help establish the immunophenotypes that inform therapeutic efficacy of checkpoint inhibitors. We have additionally interrogated whether expression of PD-L1 in these groups are consistent with known molecular patterns assayed using novel methodologies, such as high-plex digital spatial transcriptomics through the nanoString GeoMx Digital Spatial Profiler (DSP) platform and assessed the ability of the different digital platforms to provide concordant data relating to real-world expression patterns of PD-L1 and associated biomarkers. Thus, our results point to the importance of robust methodologies, used in combination, to evaluate complex tumor immune landscapes and the advantages of digital analyses to provide accurate and precise clinical contexts for better patient outcomes. Citation Format: Clara Troccoli, Lauren Matelski, Adam Beharry, Vanessa Ly, Morgan Wambaugh, Melanie Amen, Will Paces, Geoffrey Metcalf, Roberto Gianani, Tom Turi. Digital and spacial characterization of PD-L1 expression and IVD assay performance in the immune landscape of head and neck squamous cell carcinoma: A multimodal approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6634.

Spatially resolved multimarker evaluation of CD274 (PD-L1)/PDCD1 (PD-1) immune checkpoint expression and macrophage polarisation in colorectal cancer

BackgroundThe CD274 (PD-L1)/PDCD1 (PD-1) immune checkpoint interaction may promote cancer progression, but the expression patterns and prognostic significance of PD-L1 and PD-1 in the colorectal cancer microenvironment are inadequately characterised.MethodsWe used a custom 9-plex immunohistochemistry assay to quantify the expression patterns of PD-L1 and PD-1 in macrophages, T cells, and tumour cells in 910 colorectal cancer patients. We evaluated cancer-specific mortality according to immune cell subset densities using multivariable Cox regression models.ResultsCompared to PD-L1– macrophages, PD-L1+ macrophages were more likely M1-polarised than M2-polarised and located closer to tumour cells. PD-L1+ macrophage density in the invasive margin associated with longer cancer-specific survival [Ptrend = 0.0004, HR for the highest vs. lowest quartile, 0.52; 95% CI: 0.34–0.78]. T cell densities associated with longer cancer-specific survival regardless of PD-1 expression (Ptrend < 0.005 for both PD-1+ and PD-1– subsets). Higher densities of PD-1+ T cell/PD-L1+ macrophage clusters associated with longer cancer-specific survival (Ptrend < 0.005).ConclusionsPD-L1+ macrophages show distinct polarisation profiles (more M1-like), spatial features (greater co-localisation with tumour cells and PD-1+ T cells), and associations with favourable clinical outcome. Our comprehensive multimarker assessment could enhance the understanding of immune checkpoints in the tumour microenvironment and promote the development of improved immunotherapies.

Abstract OT2-15-01: COntinue the SaMe systemic therapy after local ablative therapy for Oligoprogression in metastatic breast cancer - the COSMO study

Abstract Background Patients with metastatic breast cancer (MBC) are usually treated with palliative systemic therapy until progression or unacceptable toxicity. When progression occurs, clinicians typically switch to the next line of systemic therapy. However, this strategy might be suboptimal in case of mixed response or oligoprogression. Oligoprogression refers to a situation in which inter-lesion heterogeneity causes one or few metastatic lesions to progress while the vast majority of the metastatic burden responds to the treatment. Locally ablative treatment of the progressive lesion(s) with radiotherapy, resection or radiofrequency ablation may enable continuation of otherwise effective systemic treatment. Solid data to support this approach, however, is lacking at this moment. Study design The COSMO study is an investigator-initiated single-arm phase 2 study. It is intended to be a multicenter study. Eligibility criteria Patients with MBC and oligoprogression, defined as 1-2 progressive lesions while the majority of the metastatic burden remains stable or in remission, are eligible. Current systemic therapy must be 1st or 2nd line and patients must have responded to this systemic therapy for at least six months prior to the occurence of oligoprogression. The aberrant lesion must be amenable to locally ablative therapy. All eligibility criteria may be found in table 1: eligibility criteria. Aim To investigate efficacy of local ablation of aberrant lesions combined with continuation of the same systemic therapy in patients with oligoprogression of MBC. Primary endpoint: Progression-free survival rate at six months (PFS-6). Secondary endpoints: - PFS - Overall survival - Time to next line of systemic therapy Primary and secondary endpoints will also be stratified by localization of progressive lesion and BC subtype (ER+/HER2- vs. HER2+ vs. TN). - Local control rate of lesion treated with LAT at 12 months - Complications due to LAT - Quality of life - Incidence of visceral crisis Exploratory endpoints: - Biomarkers, including receptor (ER/PR/HER2), PD-L1 and gene expression patterns in biopsies from progressive and responding lesions - Prognostic value of ctDNA at oligoprogression and during the course of treatment Statistical methods An A’hern design was chosen to conduct this study. As null-hypothesis (H0), PFS-6 rate ≤ 25% is set. The alternative hypothesis (H1) is PFS-6-rate ≥ 40%. Hypotheses were set to meet criteria for clinical significance, as stated by experts in the field. Setting one-sided α = 0.05 and a desirable power=95%, 107 evaluable patients are needed. To account for 10% of the patients to be unevaluable, 118 included patients are needed. An early stopping rule for safety is applicable: if out of the first 45 patients ≥4 of these patients have developed visceral crisis, the study will be closed early. Accrual Start: July 2022 Target: 118 patients Estimated accrual time: 2-3 years Further information Corresponding author: c.almekinders@nki.nl Clinicaltrials.gov identifier: NCT05301881 This study is funded by the Maarten van der Weijden foundation. This study was developed during the 21st EORTC/ESMO/AACR workshop on methods in clinical cancer research (MCCR). Table 1. Eligibility criteria. Citation Format: Cornelia AM Almekinders, Tessa G Steenbruggen, Ingrid A. Mandjes, Marta Lopez-Yurda, Monique EMM Bos, Terry G Wiersma, Gabe S. Sonke. COntinue the SaMe systemic therapy after local ablative therapy for Oligoprogression in metastatic breast cancer - the COSMO study [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr OT2-15-01.

Exploratory analysis of predictive biomarkers for immune-related adverse events (irAEs) due to checkpoint inhibitors (CPIs) in patients with genitourinary (GU) cancers.

569 Background: CPIs targeting PD-1/PD-L1 and CTLA-4 have transformed management of GU cancers. These agents are associated with a unique type of immune-mediated toxicities that may affect any organ, which may be severe or life-threatening. Development of irAEs may in part depend on type of CPI used, type of solid tumor, and individual patient factors including presence of subclinical inflammatory states. However, distinct biomarkers predictive of irAE development are poorly defined. This study aimed to examine possible associations between tumor mutation burden (TMB) and PD-L1 expression with occurrence of irAEs. Methods: A retrospective chart review was performed of all patients with urothelial carcinoma (UC) and renal cell carcinoma (RCC), who received therapy with CPIs from 1/2019 to 9/2022 at our institution and developed associated irAEs. Severe irAEs were defined as those necessitating initiation of immunosuppressive therapies or other supportive therapies. TMB and PDL-1 expression patterns were analyzed, if available. Given lack of standardized cutoffs for PD-L1 positivity across different GU cancer types, tumors were considered positive if a combined positive score of greater than 10 was present in UC or a total positive score of greater than 1% was present in RCC. Results: A total of 60 patients were included in this analysis - 33 with UC and 27 with RCC. Severe irAEs occurred in 19 patients with UC and 25 patients with RCC. Median TMB was 8.7 in patients with UC, while it was 2.5 in patients with RCC. PD-L1 positivity was seen in 39.3% (13/33) of UC patients and 40.7% (11/27) of RCC patients. In the UC cohort, 57.8% (11/19) had severe irAEs and TMB less than 10, while 36.8% (7/19) had severe irAEs and TMB greater than 10. Further, 47.3% (9/19) of UC patients had severe irAEs and positive PD-L1, while 42.1% (8/19) had severe irAEs and negative PD-L1. In the RCC cohort, 88% (22/25) had severe irAEs and TMB less than 10, while 8% (2/25) had severe irAEs and TMB greater than 10. Additionally, 40% (10/25) RCC patients had severe irAEs and positive PD-L1, while 56% (14/25) had severe irAEs and negative PD-L1. The incidence of TERT promoter mutations and TMB is noted in the table. Conclusions: Identification of predictive biomarkers of irAEs from CPIs is a major area of need in GU malignancies. Definitive conclusions from this dataset are limited by its small sample size. Interestingly, there appear to be differences in baseline expression of traditional immune biomarkers between UC and RCC, with lower prevalence of TMB greater than 10 and positive PD-L1 noted in the RCC cohort. As such, their utility when making treatment decisions in clinical practice may be of limited value. [Table: see text]