Predictive Biomarker For Immunotherapy Research Articles

Analysis of proliferating Treg cells as a predictor for immunotherapy response using systemic longitudinal immune profiling: Biomarker analysis of the phase 3 CONTINUUM trial.

140 Background: The discovery of predictive biomarkers for immunotherapy is hindered by the lack of control groups in most translational studies, making it impossible to discern whether the identified biomarkers are merely prognostic or truly predictive for treatment outcomes. This study reported on prospectively designed biomarker analyses of the phase 3 CONTINNUUM trial (NCT03700476), the first trial that demonstrated prolonged event-free survival (EFS) with the addition of anti-PD-1 (aPD1) to chemoradiotherapy (CRT) in locoregionally-advanced nasopharyngeal carcinoma (LA-NPC). Methods: Mass cytometry was performed to generate a dynamic single-cell atlas on longitudinal peripheral blood mononuclear cell (PBMC) samples from 12 pairs of matched patients with or without relapse in the aPD1-CRT arm. The machine-learning algorithm CellCnn was applied to identify a cell subset that was most strongly associated with disease relapse, which was further confirmed by flow cytometry (n = 120). Single-cell RNA sequencing data from matched PBMC and tumor samples were analyzed and multiplex immunohistochemistry was performed on baseline tumor samples (n = 249) to verify the predictive value of the cell subset within tumors. Results: Baseline circulating regulatory T cells (Tregs), with a Ki67+ proliferating phenotype, were found to display a higher frequency in LA-NPC patients who developed posttreatment relapse ( P < 0.001), which was further validated by flow cytometry. The intratumoral Ki67+ Tregs were also identified and correlated with an immunosuppressive tumor microenvironment. In patients with a low baseline level of Ki67+ Tregs, additional aPD1 significantly improved EFS compared with CRT alone (log-rank P = 0.011, HR = 0.22, 95% CI: 0.06−0.79), while EFS was almost identical in both treatment arms in patients with high Ki67+ Treg levels (log-rank P = 0.995, HR = 1.00, 95% CI: 0.49−2.05; interaction P = 0.047). This predictive value was further validated in datasets from two independent randomized trials in renal cancer. Conclusions: The frequency of Ki67+ Tregs can serve as a reliable predictive tool in selecting patients who are more likely to benefit from immunotherapy, potentially informing individualized immunotherapy strategies.

Circulating tumor cells enumeration and characterization in patients with lung cancer treated with immunotherapy.

e15030 Background: Programmed death-ligand 1 (PD-L1) is a predictive biomarker for immunotherapy in the treatment of non-small cell lung cancer (NSCLC). Assessing PD-L1 expression from the tumor specimen can be challenging because of tissue accessibility, heterogeneity, and dynamic changes in PD-L1 expression that may impact the status of PD-L1 during disease evolution and treatment. Hence, assessing PD-L1 status from archival tumor might not reflect its actual state on the tumor and having a real-time assessment of its expression with the use of non-invasive techniques such circulating tumor cells (CTCs) is useful. Methods: We conducted a single centre prospective study to detect CTCs in the blood of patients with stage III-IV NSCLC treated with immunotherapy using the standard CellSearch technology for CTC enumeration and the Epic Sciences technology for CTCs enumeration and assessment of PD-L1 protein expression on CTCs. CTCs were detected at baseline before treatment initiation and after 2 cycles of treatment. Study endpoints included CTCs detection and concordance between the 2 technologies, PD-L1 expression assessment on CTCs with the Epic Sciences technology, and concordance with tissue-based expression. Comparisons were made using Pearson correlation coefficient (PCC) and intraclass correlation coefficient (ICC) for count data and percentage of perfect agreement. Results: Between 2019 and 2022, 48 patients treated with immunotherapy were enrolled in the study. The mean ± standard deviation (SD) age was 66.8 ± 10.3 years, 63% were females, 42% received combination chemotherapy and immunotherapy, and 44% had adenocarcinoma histology. The tissue PD-L1 expression was high (≥50%), intermediate (1-49%), and low (<1%) in 36%, 31% and 33% of patients respectively. The mean ± SD baseline CTCs count per 7.5ml was 1.97 ± 4 with CellSearch and 1.38 ± 2.72 per ml with Epic Sciences. After 2 treatment cycles, 22% and 41% of patients had an increase in their CTCs count with CellSearch and Epic Sciences, respectively and 30% and 29% had a decrease in their CTCs. The PCC and ICC for baseline CTCs detected by CellSearch and Epic Sciences were 0.72 and 0.61, respectively and for CTCs detected after 2 cycles of treatment by the 2 technologies were -0.16 and 0.45 respectively. One patient had PD-L1 expression on their CTCs with the Epic Sciences technology and there was no association between the PD-L1 expression on CTCs and on matched tissue samples. Conclusions: This study showed a moderate to strong correlation between the 2 technologies for baseline CTCs detection and moderate to poor correlation for CTCs detection after 2 cycles of therapy. No association was found between CTCs and tissue PD-L1 expression. Future work needs to further investigate the role of PD-L1 expression on CTCs.

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]

Benchmarking the transcriptomic predictive biomarkers for immunotherapy plus chemotherapy: Results from phase III RATIONALE-309 and ORIENT-11 randomized trials.

e14624 Background: The combination of PD-(L)1 inhibitors and chemotherapy (IO+Chemo) has become the standard first-line treatment for multiple types of cancer. In contrast to PD-(L)1 monotherapy, there is a lack of established biomarkers to distinguish the outcomes of IO+Chemo. The paucity of high-quality omics data in this setting has not allowed for deep biomarker exploration. We utilized RNA-seq data from two in-house randomized controlled trials (RCTs), RATIONALE-309 and ORIENT-11, with the goal to find transcriptomic biomarkers to identify patients who may not derive benefit from IO+Chemo. Methods: RATIONALE-309 (NCT03924986) was a phase 3 study conducted at 42 sites in Asia. Treatment-naive recurrent/metastatic nasopharyngeal cancer patients were randomly allocated to either PD-1 inhibitor tislelizumab or placebo plus gemcitabine and cisplatin. ORIENT-11 (NCT03607539) was a phase 3 study that enrolled patients from 47 centers in China who had previously untreated locally advanced/metastatic nonsquamous non-small cell lung cancer. Patients were randomized to PD-1 inhibitor sintilimab or placebo plus pemetrexed and platinum. We compared several immune-related biomarkers, including IFN-γ signature, PD-L1, cytolytic score (CYT), T-cell inflamed gene expression profile, B cell infiltration, and ESTIMATE immune score, and explored the optimal predictive threshold. Results: In the RATIONALE-309 and ORIENT-11 trials, 247 and 171 patients with RNA-seq data were analyzed, respectively. Although the addition of Chemo to IO could theoretically benefit tumors with low immune activation, we hypothesized that patients might not benefit from IO+Chemo if their activation level is extremely low. We first tested the predictiveness of several thresholds (20-50th quantiles) for each selected biomarker in the two RCTs. We found that low CYT and B cell are the two best indicators for identifying a lack of survival benefits from IO+Chemo versus Chemo, especially when using 20-30th quantile as threshold. To incorporate their distinct biological information and predictive value, we combined their genes into a single gene signature to represent immune activation. We found that patients in the lower quantile (<20th) showed no benefit of IO+Chemo over Chemo in terms of overall survival (OS) (RATIONALE-309: HR=1.01, P=0.99; ORIENT-11: HR=1.54, P=0.31) and progression-free survival (PFS) (RATIONALE-309: HR=0.76, P=0.42; ORIENT-11: HR=1.30, P=0.52). Moreover, this lack of advantage was maintained in key subgroups such as PD-L1-positive patients and former/current smokers across the two RCTs. Conclusions: Based on the two large-scale RCTs, our findings have implications for the selection of biomarkers when identifying suitable candidates for IO+Chemo treatment. B cells and CYT are crucial components required for the efficacy of IO+Chemo.

High serum sodium predicts immunotherapy response in metastatic renal cell and urothelial carcinoma

ObjectivesThe development of reliable biomarkers for the prediction of immune checkpoint inhibition (ICI) response in patients with metastatic renal cell carcinoma (mRCC) and urothelial carcinoma (mUC) remains an unresolved challenge. Conventional ICI biomarkers typically focus on tumor-related factors such as PD-L1 expression. However, a comprehensive evaluation of the predictive value of serum electrolyte levels, a so far widely unexplored area, is still pending. MethodsWe conducted a post-hoc analysis of baseline sodium, potassium, chloride, magnesium and calcium levels in two independent phase 3 clinical trials: IMvigor211 for mUC comparing atezolizumab to chemotherapy, and IMmotion151 for mRCC comparing atezolizumab+bevacizumab to sunitinib. This analysis aimed to evaluate the prognostic and predictive value of these electrolyte levels in these clinical settings. A total of 1787 patients (IMvigor211 n = 901; IMmotion151 n = 886) were analyzed. ResultsWe found a linear correlation of baseline serum sodium and chloride with prognosis across both trials, which was not found for potassium, magnesium and calcium. In multivariate analysis, the prognostic capacity of sodium was limited to patients receiving ICI as compared to the control group. Interestingly, in both studies, the chance of achieving an objective response was highest in the patient subgroup with high baseline serum sodium levels of > 140 mmol/L (IMmotion151: Complete response in 17.9% versus 2.0% in patients with mRCC with baseline sodium < 135 mmol/L). Serum sodium outperformed tumor PD-L1 expression as a predictor for immunotherapy efficacy. ConclusionsPatients exhibiting elevated serum sodium levels derive the greatest benefit from immunotherapy, suggesting that baseline serum concentration could serve as a valuable and cost-effective predictive biomarker for immunotherapy across entities.

Abstract 5150: An immunohistochemical survey of predictive biomarkers for immunotherapy in ampullary carcinoma identifies strata with unique prognostic signatures

Abstract Introduction: Carcinomas located in the ampulla of Vater are a low incidence malignancy. Therapeutic options for early stage disease largely consist of pancreaticoduodenectomy followed by adjuvant chemotherapy with or without radiation. We explored the localization of CD8 and CD3 positive cells in addition to PDL-1 staining and mismatch repair deficiency markers to gain insight into the potential applicability of immunotherapy for patients with this disease. Methods: Excess material from clinically diagnosed cases collected between 1997 - 2013 were used to construct a duplicate 0.6mm core tissue microarray (TMA). All cases were derived from the Vancouver Coastal Health Region. Immunohistochemical staining was performed with the following markers: CD8, CD3, PD-L1, and the mismatch repair (MMR) markers: MSH2, MSH6, MLH1 and PMS2. CD3 and CD8 were quantified using localization within the tissue. PD-L1 was considered positive with &amp;gt;1% of cells stating positive. MMR markers were confirmed using full section and cases with convincing loss of any MMR marker were considered MMR deficient. Univariable disease specific survival analysis was performed to identify unique prognostic signatures and contingency analysis was performed to identify co-expression of the aforementioned biomarkers. Results: Ninety-eight cases were evaluable for all markers. The median age of the cohort was 69 [41 - 84] years. Forty-two percent were female. Adjuvant chemotherapy was provided to 15% of patients with the remainder undergoing post-surgical observation. Almost 90% were pT3 or pT4 and 48% had regional lymph node metastasis. CD3+ T-cells were either localized in the tumor stroma only (59%) or in both the stroma and epithelial compartments (41%). CD8+ T-cells were principally located in the stroma (66%) and both the epithelial and stroma (24%). Ten percent of cases had no CD8+ T-cells. PD-L1 staining was found in 10% of cases. MMR deficiency was found in 5% of cases. Improved prognostic signatures were found for cases with CD3+ and CD8+ T-cells in both the epithelial and stromal compartments (p &amp;lt;= 0.02). A trend towards a negative prognostic signature was observed for MMR deficient cases and for PD-L1 positive cases. The only significant positive association between biomarkers was found for CD3+ and CD8+ in both the epithelial and stromal compartments. Conclusions: The results of this analysis suggest that enhancement of an immune response yielding an increase CD3+ and CD8+ T-cells in the epithelial compartment may have a beneficial effect on prognosis. The relative scarcity of MMR deficiency in this disease is within the expected prevalence supported by other studies. Further exploration of the potential role of immunotherapy in immune enhanced subgroups of ampullary cancers is warranted. Citation Format: Steve E. Kalloger, Joanna Karasinska, James Topham, Daniel J. Renouf, David F. Schaeffer. An immunohistochemical survey of predictive biomarkers for immunotherapy in ampullary carcinoma identifies strata with unique prognostic signatures [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 5150.

Predicting programmed death-ligand 1 (PD-L1) expression with fluorine-18 fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters in resectable non-small cell lung cancer

BackgroundProgrammed death-ligand 1 (PD-L1) expression is a predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). PD-L1 and glucose transporter 1 expression are closely associated, and studies demonstrate correlation of PD-L1 with glucose metabolism.AimThe aim of this study was to investigate the association of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters with PD-L1 expression in primary lung tumour and lymph node metastases in resected NSCLC.MethodsWe conducted a retrospective analysis of 210 patients with node-positive resectable stage IIB–IIIB NSCLC. PD-L1 tumour proportion score (TPS) was determined using the DAKO 22C3 immunohistochemical assay. Semi-automated techniques were used to analyse pre-operative [18F]FDG-PET/CT images to determine primary and nodal metabolic parameter scores (including max, mean, peak and peak adjusted for lean body mass standardised uptake values (SUV), metabolic tumour volume (MTV), total lesional glycolysis (TLG) and SUV heterogeneity index (HISUV)).ResultsPatients were predominantly male (57%), median age 70 years with non-squamous NSCLC (68%). A majority had negative primary tumour PD-L1 (TPS < 1%; 53%). Mean SUVmax, SUVmean, SUVpeak and SULpeak values were significantly higher (p < 0.05) in those with TPS ≥ 1% in primary tumour (n = 210) or lymph nodes (n = 91). However, ROC analysis demonstrated only moderate separability at the 1% PD-L1 TPS threshold (AUCs 0.58–0.73). There was no association of MTV, TLG and HISUV with PD-L1 TPS.ConclusionThis study demonstrated the association of SUV-based [18F]FDG-PET/CT metabolic parameters with PD-L1 expression in primary tumour or lymph node metastasis in resectable NSCLC, but with poor sensitivity and specificity for predicting PD-L1 positivity ≥ 1%.Clinical relevance statementWhilst SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography metabolic parameters may not predict programmed death-ligand 1 positivity ≥ 1% in the primary tumour and lymph nodes of resectable non-small cell lung cancer independently, there is a clear association which warrants further investigation in prospective studies.Trial registrationNon-applicableKey Points• Programmed death-ligand 1 immunohistochemistry has a predictive role in non-small cell lung cancer immunotherapy; however, it is both heterogenous and dynamic.• SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters were significantly higher in primary tumour or lymph node metastases with positive programmed death-ligand 1 expression.• These SUV-based parameters could potentially play an additive role along with other multi-modal biomarkers in selecting patients within a predictive nomogram.

PD-L1 mRNA and protein expression in canine mammary carcinomas: Correlation with histopathological grade and molecular markers.

Programmed death ligand 1 (PD-L1) is an immune checkpoint molecule that plays a crucial role in regulating antitumor immune responses. Canine mammary carcinomas (CMCs) are common tumors of dogs. Despite extensive studies on the heterogeneity of CMCs, there is still a lack of effective precision therapies for the treatment of CMCs. In this study, we aimed to investigate the correlation between PD-L1 mRNA and protein expression in CMCs and explore its association with histopathological grade and molecular markers, including the estrogen receptor, epidermal growth factor receptor 2, and cytokeratin 5/6 (CK5/6). Formalin-fixed paraffin-embedded samples were evaluated for PD-L1 mRNA expression using RNA in situ hybridization and PD-L1 protein expression using immunohistochemistry. We observed no substantial correlation between PD-L1 mRNA and protein expression in CMCs; however, PD-L1 mRNA levels were significantly higher in grade 3 than in grade 1 tumors (P = .001). In addition, we observed a positive correlation between PD-L1 protein expression and CK5/6 expression in CMCs (P = .032). These findings suggest that PD-L1 expression in CMCs is heterogeneous and may be regulated post-transcriptionally. Further studies are needed to explore the prognostic and therapeutic implications of PD-L1 expression in different molecular subtypes of CMCs and their potential as predictive biomarkers for immunotherapy.

Tumor mutation load better predicts the prognosis of patients treated with immune checkpoint inhibitors in upper gastrointestinal cancers: A systematic review and meta-analysis.

Tumor mutational load (TML) has emerged as a potential biomarker for multiple solid tumors. However, data on its prognostic impact on upper gastrointestinal (UGI) cancer are limited. Therefore, the aim of this systematic review and meta-analysis was to assess the prognostic value of TML for the survival of patients with UGI cancer. A comprehensive search of the PubMed, Embase, Cochrane Library, and Web of Science databases was conducted up to February 13, 2023. Eleven studies met our inclusion criteria. Hazard ratios (HRs) for progression-free survival and overall survival and their 95% confidence intervals (CIs) were calculated. Subsequently, the combined HR and its 95% CI were calculated for UGI tract cancers in the high and low TML groups. I2 statistics and p-values were used to evaluate heterogeneity. Publication bias, sensitivity, and subgroup analyses were performed to determine sources of heterogeneity. In total, 932 patients with UGI tract cancer from 11 publications were included. The high TML group treated with immunotherapy showed significantly improved overall survival (HR = 0.68; 95% CI: 0.53, 0.86; p = .001) and progression-free survival (HR = 0.74; 95% CI: 0.58, 0.95; p = .020) compared with the low TML group. Our study demonstrated that patients with UGI tumors and higher TML have a better prognosis with immunotherapy, suggesting that TML is a promising predictive biomarker for immunotherapy. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO Registration No: CRD42023405596).

Multimodality treatment in recurrent/metastatic squamous cell carcinoma of head and neck: current therapy, challenges, and future perspectives.

Squamous cell carcinoma of the head and neck is a complex group of diseases that presents a challenge to the clinician. The prognosis in the recurrent/metastatic disease is particularly dismal, with a median survival of approximately 12 months. Recently, the personalized and multimodal approach has increased prognosis by integrating locoregional strategies (salvage surgery and stereotactic radiotherapy) and systemic treatments (chemotherapy, immunotherapy, and target therapy). Malnutrition is a significant clinical problem that interferes with dose intensity, and thus, feeding supplementation is critical not only to increase the quality of life but also to improve overall survival. With this review, we want to emphasize the importance of the multidisciplinary approach, quality of life, and nutritional supportive care and to integrate the latest updates of predictive biomarkers for immunotherapy and future therapeutic strategies.

Immunohistochemical study of Programmed Cell Death Ligand 1 (PDL1) expression by combined positive score using 22C3 clone in head and neck squamous cell carcinomas, its correlation with clinicopathological features and outcome.

Programmed cell death ligand 1 (PD L1) is a transmembrane protein that is highly expressed in neoplastic cells. Therapy with immune checkpoint inhibitors target PD-1/PD-L1 blockade-inducing tumour regression. Immunohistochemistry (IHC) for PD-L1 expression enables patient selection for immunotherapy and can be considered as a potential predictive biomarker for immunotherapy in head and neck squamous cell carcinoma (HNSCC). To determine the PDL1 expression in HNSCC, to correlate with clinicopathological features and outcome. We retrospectively analysed 59 cases of HNSCC at our Tertiary Hospital between January 2017 and November 2018 and followed up until death/Nov 2022 for Overall survival. IHC analysis of PD-L1 using Combined Positive Score (CPS) with antibody clone 22C3 in 59 cases of HNSCC was performed. PD-L1 expression was correlated with clinicopathological features and outcomes. Pearson Chi-square test was used to analyse the correlation between PD-L1 expression and clinicopathological parameters using SPSS20.0. Survival curves were calculated by Kaplan-Meier method, and differences were analysed by log-rank test. A total of 25 cases (42.4%) had positive PDL expression (CPS ≥1). 16/25 cases (27.1%) belonged to CPS (≥1, <10). An almost-perfect interobserver agreement was noted by two pathologists for PD-L1 IHC expression. No statistically significant correlation was noted between PD-L1 score and clinicopathologic features. Detection of PD-L1 status gives further insight into frequency of PD-L1 expression in Indian HNSCC patients to possibly improve clinical treatment strategies, ensuring that our patients get the maximum therapeutic benefit of immunotherapy.

Abstract B052: Single-cell analysis of multiple cancers in the upper gastrointestinal tract uncovers immune characteristics of tumor microenvironments linked to the predictive biomarkers for immunotherapy in esophageal cancers

Abstract Esophageal cancer is mainly composed of two subtypes – esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) – with distinct risk factors and cancer phenotypes despite arising from the same organ. The recent study by the Cancer Genome Atlas (TCGA) has revealed their distinct genomic characteristics and similarities to subsets of other nearby cancers such as head and neck squamous neck carcinoma (HNSCC) and gastric adenocarcinoma (GAC) for ESCC and EAC, respectively. Furthermore, recent clinical trials with anti-PD-1 monotherapy and combination treatment with anti-PD-1 and anti-CTLA-4 reported varying degrees of responses to immunotherapy for those cancers. Here we performed single-cell RNA sequencing of patients with ESCC, EAC, and HNSCC, and collected additional public datasets for comparative analysis of four cancer types in the upper gastrointestinal tract, especially in connection to responses to immunotherapy. In total, we integrated 35 patient samples from 4 different cohorts to comprehensively analyze malignant cells, stromal/endothelial cells, and immune cells. With the integrative analysis, we confirmed the similarities and differences among those cancer types in the upper gastrointestinal tract and expanded understanding of immune mechanisms at single-cell resolution. For malignant cells, we utilized matrix factorization analysis to identify underlying malignant cell programs related to each cancer type. We confirmed clear separation between malignant cells of squamous epithelial cell origins and glandular epithelial cell origins. We further identified the malignant cell programs related to both cancer cell origins and molecular mechanisms of cancer cells. For stromal and endothelial cells, we identified compositional differences in their cellular subtypes. With biological pathway and signature analyses, we revealed that their distinct cellular subtypes might be connected to distinct immune mechanisms in tumor microenvironments. For immune cells, despite having less compositional difference in cellular subtypes, we identified their underlying immune mechanisms that could explain key differences in responses to immunotherapy. With comprehensive analyses of various immune cell-types and their interactions, we identified several T cell populations and related tumor-associated macrophages that could serve as predictive markers of responses to cancer immunotherapy. In order to validate our findings, we utilized both bulk and single-cell sequencing datasets of various cancer types with treatments of immune checkpoint inhibitors (ICI) from previous studies and confirmed significance of those immune signatures and cellular compositions in responses to the ICI treatment. Citation Format: Seungbyn Baek, Gamin Kim, Sang Jun Ha, Hye Ryun Kim, Seong Yong Park, Insuk Lee. Single-cell analysis of multiple cancers in the upper gastrointestinal tract uncovers immune characteristics of tumor microenvironments linked to the predictive biomarkers for immunotherapy in esophageal cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B052.

The Efficacy of Immunotherapy and Clinical Utility of Comprehensive Genomic Profiling in Adenoid Cystic Carcinoma of Head and Neck.

Background and Objectives: Adenoid cystic carcinoma (ACC) of the head and neck is generally slow-growing but has a high potential for local recurrence and metastasis to distant organs. There is currently no standard pharmacological treatment for recurrent/metastatic (R/M) ACC, and there are cases in which immune checkpoint inhibitors (ICIs) are administered for ACC according to head and neck squamous cell carcinoma (HNSCC). However, the efficacy of ICIs for ACC remains unclear, and the predictive biomarkers need to be elucidated. Materials and Methods: The Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database enabled the retrospective but nationwide analysis of 263 cases of ACC of the head and neck. Then, we examined and reported four cases of ACC that received ICIs and comprehensive genomic profiling (CGP) in our institution. Results: The C-CAT database revealed that 59 cases out of 263 received ICIs, and the best response was 8% of objective response rate (ORR) and 53% of disease control rate (DCR) (complete response, CR 3%, partial response, PR 5%, stable disease, SD 44%, progressive disease, PD 19%, not evaluated, NE 29%). The tumor mutational burden (TMB) in ACC was lower overall compared to HNSCC and could not be useful in predicting the efficacy of ICIs. Some cases with MYB structural variants showed the response to ICIs in the C-CAT database. A patient with MYB fusion/rearrangement variants in our institution showed long-term stable disease. Conclusions: ICI therapy is a potential treatment option, and the MYB structural variant might be a candidate for predictive biomarkers for immunotherapy in patients with R/M ACC.

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology

IntroductionCombination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. ObjectiveTo overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. MethodsWe proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. ResultsThe entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm−1 showed a positive linear correlation with PD-L1 expression level. ConclusionsThis study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

309P Expression of estrogen receptor is a negative predictive biomarker for immunotherapy with lenvatinib plus pembrolizumab for advanced endometrial cancer with pMMR

309P Expression of estrogen receptor is a negative predictive biomarker for immunotherapy with lenvatinib plus pembrolizumab for advanced endometrial cancer with pMMR

EP03.03-07 T-Cell Receptor Repertoire Profiling as a Predictive Biomarker for Immunotherapy in Unresectable Stage III Non-small Cell Lung (NSCLC)

EP03.03-07 T-Cell Receptor Repertoire Profiling as a Predictive Biomarker for Immunotherapy in Unresectable Stage III Non-small Cell Lung (NSCLC)

Development and Preclinical Evaluation of [68Ga]BMSH as a New Potent Positron Emission Tomography Tracer for Imaging Programmed Death-Ligand 1 Expression.

Immunotherapy targeting the programmed death-ligand 1 (PD-L1)/programmed cell death protein 1 (PD-1) pathway has shown remarkable efficacy against various cancers, but the overall response rate (ORR) is still low. PD-L1 expression in tumors may predict treatment response to immunotherapy. Indeed, ongoing clinical studies utilize a few PD-L1 radiotracers to assess PD-L1 expression as a predictive biomarker for immunotherapy. Here, we present a novel positron emission tomography (PET) radiotracer called [68Ga]BMSH, which is derived from a small molecule inhibitor specifically targeting the binding site of PD-L1. The inhibitor was modified to optimize its in vivo pharmacokinetic properties and enable chelation of 68Ga. In vitro evaluation revealed [68Ga]BMSH possessed a strong binding affinity, high specificity, and rapid internalization in PD-L1 overexpressing cells. Biodistribution studies showed that PD-L1 overexpressing tumors had an uptake of [68Ga]BMSH at 4.22 ± 0.65%ID/g in mice, while the number was 2.23 ± 0.41%ID/g in PD-L1 low-expressing tumors. Micro-PET/CT imaging of tumor-bearing mice further confirmed that, compared to [18F]FDG, [68Ga]BMSH can specifically identify tumors with varying levels of PD-L1 expression. Our findings suggest that the [68Ga]BMSH is a PD-L1 radioligand with ideal imaging properties, and its further application in the clinical screening of PD-L1 overexpressing tumors may improve ORR for immunotherapy.

Predictive Biomarkers for Immunotherapy in Gastric Cancer: Current Status and Emerging Prospects.

Gastric cancer presents substantial management challenges, and the advent of immunotherapy has ignited renewed hope among patients. Nevertheless, a significant proportion of patients do not respond to immunotherapy, and adverse events associated with immunotherapy also occur on occasion, underscoring the imperative to identify suitable candidates for treatment. Several biomarkers, including programmed death ligand-1 expression, tumor mutation burden, mismatch repair status, Epstein-Barr Virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes, have demonstrated potential in predicting the effectiveness of immunotherapy in gastric cancer. However, the quest for the optimal predictive biomarker for gastric cancer immunotherapy remains challenging, as each biomarker carries its own limitations. Recently, multi-omics technologies have emerged as promising platforms for discovering novel biomarkers that may help in selecting gastric cancer patients likely to respond to immunotherapy. The identification of reliable predictive biomarkers for immunotherapy in gastric cancer holds the promise of enhancing patient selection and improving treatment outcomes. In this review, we aim to provide an overview of clinically established biomarkers of immunotherapy in gastric cancer. Additionally, we introduce newly reported biomarkers based on multi-omics studies in the context of gastric cancer immunotherapy, thereby contributing to the ongoing efforts to refine patient stratification and treatment strategies.

DLL3 Is a Prognostic and Potentially Predictive Biomarker for Immunotherapy Linked to PD/PD-L Axis and NOTCH1 in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive neoplasm with very poor patient survival outcomes despite available treatments. There is an urgent need for new potential treatment options and novel biomarkers for these patients. Delta-like canonical Notch ligand 3 (DLL3) interacts with the Notch receptor and causes inhibition of Notch signaling, which confers a survival advantage to PDAC cells. Thus, DLL3 expression could affect cell survival, and its inhibition could increase a patient's survival. To test this hypothesis, a survival analysis was conducted using the progression-free and overall survival from two independent datasets of PDAC patients, with one using mRNA z-score levels and the other using the Hscore protein expression level; both were carried out using a log-rank test and plotted using Kaplan-Meier curves. DLL3 at the mRNA expression level showed an association between high mRNA expression and both a longer progression-free survival (PFS) and overall survival (OS) of patients. Then, we designed a retrospective study with resected PDAC samples. Our primary objective with this dataset was to assess the relationship between PFS and OS and DLL3 protein expression. The secondary assessment was to provide a rationale for the use of anti-DLL3-based treatments in combination with immunotherapy that is supported by the link between DLL3 and other factors that are involved in immune checkpoints. The survival analyses revealed a protective effect of high DLL3 protein expression levels in both PFS and OS. Interestingly, high DLL3 protein expression levels were significantly correlated with PD-L1/2 and negatively correlated with NOTCH1. Therefore, DLL3 could be considered a biomarker for better prognosis in resectable PDAC patients as well as a therapeutic biomarker for immunotherapy response. These facts set a rationale for testing anti-DLL3-based treatments either alone or combined with immunotherapy or other NOTCH1 inhibitors.

In silico targeting of colony-stimulating factor-1 receptor: delineating immunotherapy in cancer.

Delineate structure-based inhibition of colony-stimulating factor-1 receptor (CSF1R) by small molecule CSF1R inhibitors in clinical development for target identification and potential lead optimization in cancer therapeutics since CSF1R is a novel predictive biomarker for immunotherapy in cancer. Compounds were in silico modelled by induced fit docking protocol in a molecular operating environment (MOE, MOE.v.2015). The 3-dimensional (3D) X-ray crystallized structure of CSF1R kinase (Protein Databank, ID 4R7H) was obtained from Research Collaboratory for Structural Bioinformatics (RSCB) Protein Databank. The 3D conformers of edicotinib, DCC-3014, ARRY-382, BLZ-945, chiauranib, dovitinib, and sorafenib were obtained from PubChem Database. These structures were modelled in Amber10:EHT molecular force field, and quick prep application was used to correct and optimize the structures for missing residues, H-counts, termini capping, and alternates. The binding site was defined within the vicinity of the co-crystallized ligand of CSF1R kinase. The compounds were docked by the triangular matcher placement method and ranked by the London dG scoring function. The docked poses were further refined by the induced fit method. The pose with the lowest binding score (ΔG) was used to model the ligand interaction profile in Discovery Studio Visualizer v17.2. The co-crystallized ligand was docked in its apo conformation, and root-mean-square deviation was computed to validate the docking protocol. All 7 CSF1R inhibitors interact with residue Met637 exhibiting selectivity except for edicotinib. The inhibitors maintain CSF1R in an auto-inhibitory conformation by interacting with Asp797 of the Asp-Phe-Gly (DFG) motif and/or hindering the conserved salt bridge formed between Glu633 and Lys616 thus stabilizing the activation loop, or interacting with tryptophan residue (Trp550) in the juxtamembrane domain. DCC-3014, ARRY-382, BLZ-945, and sorafenib bind with the lowest binding energy with CSF1R kinase. Pyrimidines are potent inhibitors that interact with CSF1R residues. DCC-3014 and ARRY-382 exhibit exceptional pharmaceutical potential exhibiting great structural stability and affinity.