Immune Checkpoint Biomarkers Research Articles

Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer

Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencing, an autophagy-related risk model was identified. The model was capable of distinguishing the worse prognosis of patients with gastric cancer (GC), which was validated in TCGA and two independent Gene Expression Omnibus cohorts utilizing the survival analysis, and was also independent of other clinical covariates evaluated by multivariable Cox regression. The clinical value of this model was further assessed using a receiver operating characteristic (ROC) and nomogram analysis. Investigation of single-cell RNA sequencing uncovered that this model might act as an indicator of the dysfunctional characteristics of T cells in the high-risk group. Moreover, the high-risk group exhibited the lower expression of immune checkpoint markers (PDCD1 and CTLA4) than the low-risk group, which indicated the potential predictive power to the current immunotherapy response in patients with GC. In conclusion, this autophagy-associated risk model may be a useful tool for prognostic evaluation and will facilitate the potential application of this model as an indicator of the predictive immune checkpoint biomarkers.

Comprehensive analysis of tumor necrosis factor-α-inducible protein 8-like 2 (TIPE2): A potential novel pan-cancer immune checkpoint

Tumor necrosis factor-α-inducible protein 8-like 2 (TIPE2) is encoded by TNFAIP8L2 and is a newly identified negative regulator of natural and acquired immunity that plays a critical function in maintaining immune homeostasis. Recently, CAR-NK immune cell therapy has been a focus of major research efforts as a novel cancer therapeutic strategy. TIPE2 is a potential checkpoint molecule for immune cell maturation and antitumor immunity that could be used as a novel NK cell-based immunotherapeutic approach. In this study, we explored the expression of TNFAIP8L2 across various tumor types and found that TNFAIP8L2 was highly expressed in most tumor types and correlated with prognosis. Survival analysis showed that TNFAIP8L2 expression was predictive of improved survival in cervical-squamous-cell-carcinoma (CESC), sarcoma (SARC) and skin-cutaneous-melanoma (SKCM). Conversely, TNFAIP8L2 expression predicted poorer survival in acute myeloid leukemia (LAML), lower-grade-glioma (LGG), kidney-renal-clear-cell-carcinoma (KIRC) and uveal-melanoma (UVM). Analysis of stemness features and immune cell infiltration indicated that TNFAIP8L2 was significantly associated with cancer stem cell index and increased macrophage and dendritic cell infiltration. Our data suggest that TNFAIP8L2 may be a novel immune checkpoint biomarker across different tumor types, particularly in LAML, LGG, KIRC and UVM, and may have further utility as a potential target for immunotherapy.

Combination Biomarker of Immune Checkpoints Predict Prognosis of Urothelial Carcinoma.

In contrast to Western counties, the incidence of urothelial carcinoma (UC) remains mar-edly elevated in Taiwan. Regulatory T cells (Tregs) play a crucial role in limiting immune responses within the tumor microenvironment. To elucidate the relationship between immune checkpoints in the tumor immune microenvironment and UC progression, we utilize the Gene Expression Omnibus (GEO) to analyze a microarray obtained from 308 patients with UC. We observed that the expression level of CD276 or TIM-3 was positively correlated with late-stage UC and poor prognosis. Patients with simultaneously high CD276 and TIM-3 expression in tumors have significantly reduced both univariate and multivariate survival, indicating that mRNA levels of these immune checkpoints could be independent prognostic biomarkers for UC overall survival and recurrence. Our cohort study showed rare CD8+ cytotoxic T-cells and Tregs infiltration during early-stage UC-known as cold tumors. Approximately 30% of late-stage tumors exhibited highly infiltrated cytotoxic T cells with high PD-1 and FOXP3 expression, which implied that cytotoxic T cells were inhibited in the advanced UC microenvironment. Collectively, our findings provide a better prognosis prediction by combined immune checkpoint biomarkers and a basis for early-stage UC standard treatment to convert cold tumors into hot tumors, followed by immune checkpoint therapy.

15P Serum immune checkpoint biomarkers as predictors of response to anti-PD-1/PD-L1 treatment in non-small cell lung cancer (NSCLC) patients

There is limited data on the predictive biomarkers of response to immune checkpoint blockade (ICB) treatment of non-small cell lung cancer (NSCLC) patients. The main aim of this prospective study is to understand the utility of pre-treatment soluble immune checkpoint and tumor markers as early predictors of response in locally advanced/metastatic NSCLC patients treated with ICBs.

Prognostic Significance of CSF-1R Expression in Early Invasive Breast Cancer.

Simple SummaryExperimental evidence suggests that CSF-1/CSF-1R signaling attracts immune cells called macrophages into the tumor microenvironment which promote the capacity of cancer cells to spread. In this study, we investigated CSF-1R protein expression on breast cancer cells and macrophages and their relationship with other immune cells and breast cancer survival. Our results show that cases with high CSF-1R expression on cancer cells, but not macrophages, are associated with inferior survival, particularly in the common hormone receptor-positive breast cancer group, which persists even in the presence of an active anti-tumor host immune response.Colony-stimulating factor-1 receptor (CSF-1R) signaling promotes an immune suppressive microenvironment enriched in M2 macrophages. Given that CSF-1R inhibitors are under investigation in clinical trials, including in breast cancer, CSF-1R expression and association with immune biomarkers could identify patients who derive greater benefit from combination with immunotherapies. TIMER2.0 and bc-GenExMiner v4.7 were used to assess the correlation of CSF1R mRNA with immune infiltrates and prognosis. Following a prespecified training–validation approach, an optimized immunohistochemistry assay was applied to assess CSF-1R on carcinoma cells and macrophages on breast cancer tissue microarray series representing 2384 patients, coupled to comprehensive clinicopathological, biomarker, and outcome data. Significant positive correlations were observed between CSF1R mRNA and immune infiltrates. High carcinoma CSF-1R correlated with grade 3 tumors >2 cm, hormone receptor negativity, high Ki67, immune checkpoint biomarkers, and macrophages expressing CSF-1R and CD163. High carcinoma CSF-1R was significantly associated with poor survival in univariate and multivariate analyses. Adverse prognostic associations were retained in ER+ cases regardless of the presence of CD8+ T cells. CSF-1R+ macrophages were not prognostic. High carcinoma CSF-1R is associated with aggressive breast cancer biology and poor prognosis, particularly in ER+ cases, and identifies patients in whom biomarker-directed CSF-1R therapies may yield superior therapeutic responses.

Abstract 1616: Characterizing differences in checkpoint inhibitor biomarkers in a real-world cohort of stage III and IV non-small cell lung cancer patients

Abstract Immune checkpoint blockade (ICB) therapies have emerged as an essential treatment modality in lung cancer. While ICB therapies are approved in several indications for stage IV and metastatic non-small cell lung cancers (NSCLC), approvals for early but invasive tumors have been limited. To investigate the molecular landscape potentially underlying this difference, we assessed levels of known ICB biomarkers and transcriptome-wide pathway activity between stage III and IV NSCLC primary tumors across a real-world cohort. Following exome-capture bulk RNA sequencing of tumors with non-squamous NSCLC histology, data underwent quality control and normalization. We employed a linear regression approach adjusted for age, sex, and tumor purity to identify hundreds of differentially expressed (DE) genes by stage (false discovery rate=5%). Correlations were evaluated by Pearson's coefficient, and differences in means were assessed by Mann-Whitney U test and Student's t-test, as appropriate. From KEGG gene set enrichment analysis of the DE genes, we found metabolic pathways were significantly enriched in stage IV tumors. In contrast, several immune-related pathways were relatively depleted in stage IV tumors, including pathways associated with NF-κB signaling, IL-17 signaling, TNF signaling, Th1 and Th2 differentiation, and Th17 differentiation. Consistent with this depletion of immune signaling pathways in stage IV tumors, several important ICB biomarkers including CTLA4 and PDCD1 (PD-1) had increased expression in stage III tumors relative to stage IV. Notably, CD274 (PD-L1) expression did not differ by stage, nor did tumor cell PD-L1 protein levels, as measured by IHC. In addition, PD-L1 gene expression and protein levels were concordant across both stages (P<2.2e-16). Based on these results, we next examined differences in overall level of immune infiltration using estimated immune proportions derived from gene expression data. While overall immune proportion did not differ significantly between stage III and IV tumors, stage III tumors had a significantly higher estimated proportion of CD4+ T cells relative to stage IV, and stage IV tumors had a significantly higher proportion of macrophages relative to stage III. These results demonstrate enrichment of immune activation gene expression pathways and paradoxically, increased expression of immune checkpoint biomarkers in stage III tumors relative to stage IV tumors, suggesting that evolution of metastasis in NSCLC tumors is accompanied by consequential changes in the tumor-immune microenvironment. This comprehensive assessment of the expression of immune checkpoint genes, and the transcriptome more broadly, may help to inform the development of anti-cancer immune modulating agents or use of existing ICB in early-stage NSCLC. Citation Format: Yinjie Gao, Michelle M. Stein, Prerna Jain, Denise Lau, Kimberly L. Blackwell, Aly A. Khan. Characterizing differences in checkpoint inhibitor biomarkers in a real-world cohort of stage III and IV non-small cell lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1616.

Profiling of immune checkpoint biomarkers by multiplex immunofluorescence in breast cancer brain metastases.

2021 Background: Despite potential clinical implications, the complexity of immune microenvironment in breast cancer (BC) brain metastases (BM) is still poorly understood. Multiplex immunofluorescence (mIF) allows simultaneous visualization of several IF labeled proteins while maintaining spatial information. This novel technique can be used to comprehensively describe BCBM immune microenvironment, potentially providing useful information to guide novel therapeutic approaches. Methods: Clinical data and archival BM samples from 60 BC patients undergoing neurosurgery (2003-2018) at three institutions were collected. BCBMs were characterized using a custom mIF panel, including immune checkpoint and co-inhibitory molecules (CD3, PD1, PD-L1, TIM3, LAG3, CD163) and localization (keratin for tumor recognition) markers. Mean marker density was determined by digital image analysis (positive cells/mm2) and classified in tumor and stroma areas. Associations between immune marker densities, BC subtype and overall survival from BM diagnosis (OS) were studied. Results: Sixty BCBM samples were analyzed; 32% HR+/HER2-, 38% HER2+, 30% HR-/HER2-. At a median follow-up of 43 months, the only clinical variable associated with OS was BC subtype (shortest for HR-/HER2- and longest for HER2+, p=0.02). In the total sample area and tumor area, no significant difference in marker density was observed according to BC subtype. In the stroma area, a significant difference in TIM3+ cell density was observed according to BC subtype (highest density in HR+/HER2- and lowest density in HER2+ tumors, Kruskal-Wallis p=0.017). Higher CD163 density (a marker of M2 macrophage polarization), both in the tumor and in the stroma area, was significantly associated with worse OS, even after correction by BC subtype. In the subgroup of patients with HR+/HER2- BCBM, high TIM3+ cell density in the stroma area was significantly associated with longer OS (median OS 54.1 versus 23 months respectively for TIM3+ density above and below median value; p=0.01). Conclusions: In BCBM, stromal TIM3+ immune infiltrate differs according to BC subtype. M2 macrophage polarization is consistently associated with worse OS across all BC subtypes and might represent a potential therapeutic target for these patients.[Table: see text]

Systematic Assessment of Transcriptomic Biomarkers for Immune Checkpoint Blockade Response in Cancer Immunotherapy.

Simple SummaryThe aim of our study was to evaluate the predictive performance of transcriptomic biomarkers to immune response. The study collected 22 transcriptomic biomarkers and constructed multiple benchmark datasets to evaluate their predictive performance of immune checkpoint blockade (ICB) response in pre-treatment patients with distinct ICB agents in diverse cancers. We found “Immune-checkpoint molecule” biomarkers PD-L1, PD-L2, CTLA-4 and IMPRES and the “Effector molecule” biomarker CYT showed significant associations with ICB response and clinical outcomes. These immune-checkpoint biomarkers and another immune effector IFN-gamma presented predictive ability in melanoma, urothelial cancer and clear cell renal-cell cancer. Interestingly, for anti-PD-1 therapy and anti-CTLA-4 therapy, the top-performing response biomarkers were usually mutually exclusive even though in the same biomarker category and most of biomarkers with outstanding predictive power were observed in patients with combined anti-PD-1 and anti-CTLA-4 therapy.Background: Immune checkpoint blockade (ICB) therapy has yielded successful clinical responses in treatment of a minority of patients in certain cancer types. Substantial efforts were made to establish biomarkers for predicting responsiveness to ICB. However, the systematic assessment of these ICB response biomarkers remains insufficient. Methods: We collected 22 transcriptome-based biomarkers for ICB response and constructed multiple benchmark datasets to evaluate the associations with clinical response, predictive performance, and clinical efficacy of them in pre-treatment patients with distinct ICB agents in diverse cancers. Results: Overall, “Immune-checkpoint molecule” biomarkers PD-L1, PD-L2, CTLA-4 and IMPRES and the “Effector molecule” biomarker CYT showed significant associations with ICB response and clinical outcomes. These immune-checkpoint biomarkers and another immune effector IFN-gamma presented predictive ability in melanoma, urothelial cancer (UC) and clear cell renal-cell cancer (ccRCC). In non-small cell lung cancer (NSCLC), only PD-L2 and CTLA-4 showed preferable correlation with clinical response. Under different ICB therapies, the top-performing biomarkers were usually mutually exclusive in patients with anti-PD-1 and anti-CTLA-4 therapy, and most of biomarkers presented outstanding predictive power in patients with combined anti-PD-1 and anti-CTLA-4 therapy. Conclusions: Our results show these biomarkers had different performance in predicting ICB response across distinct ICB agents in diverse cancers.

Granulocyte Colony Stimulating Factor Expression in Breast Cancer and Its Association with Carbonic Anhydrase IX and Immune Checkpoints.

Simple SummaryPreclinical studies suggest that interactions between granulocyte colony-stimulating factor (G-CSF) and hypoxia-induced carbonic anhydrase IX regulate the trafficking and function of immune cells in the tumour microenvironment. We investigated the clinical significance of this crosstalk by analyzing the protein expression of G-CSF and macrophage markers by immunohistochemistry on a well-characterized tissue microarray series of invasive breast cancers. We report that high expression of G-CSF on breast carcinoma cells is linked with significantly improved survival in an important group of breast cancers that do not respond to hormonal therapy. These tumours were infiltrated by immune cells expressing biomarkers that can be targeted with immune checkpoint inhibitor drugs. In contrast, carbonic anhydrase IX expression was associated with unfavourable outcomes.Purpose: Granulocyte colony-stimulating factor (G-CSF) and hypoxia modulate the tumour immune microenvironment. In model systems, hypoxia-induced carbonic anhydrase IX (CAIX) has been associated with G-CSF and immune responses, including M2 polarization of macrophages. We investigated whether these associations exist in human breast cancer specimens, their relation to breast cancer subtypes, and clinical outcome. Methods: Using validated protocols and prespecified scoring methodology, G-CSF expression on carcinoma cells and CD163 expression on tumour-associated macrophages were assayed by immunohistochemistry and applied to a tissue microarray series of 2960 primary excision specimens linked to clinicopathologic, biomarker, and outcome data. Results: G-CSFhigh expression showed a significant positive association with ER negativity, HER2 positivity, presence of CD163+ M2 macrophages, and CAIX expression. In univariate analysis, G-CSFhigh phenotype was associated with improved survival in non-luminal cases, although the CAIX+ subset had a significantly adverse prognosis. A significant positive association was observed between immune checkpoint biomarkers on tumour-infiltrating lymphocytes and both G-CSF- and CAIX-expressing carcinoma cells. Immune checkpoint biomarkers correlated significantly with favourable prognosis in G-CSFhigh/non-luminal cases independent of standard clinicopathological features. Conclusions: The prognostic associations linking G-CSF to immune biomarkers and CAIX strongly support their immunomodulatory roles in the tumour microenvironment.

EPCO-23. COMPARATIVE TRANSCRIPTOMICS TO IDENTIFY TARGETED THERAPY CANDIDATES IN HIGH GRADE GLIOMA

Abstract Genomic characterization is often used for the identification of therapeutic targets in tumors. Recently, comparative transcriptomics has begun to be utilized for this purpose. In this pilot, we compare the transcriptome of a patient with recurrent high grade glioma (HGG) to our cohort to identify potential therapies. We reviewed transcriptomic profiles from patients who had resection of HGG at our institution over the past year as well as the UCSC cancer compendium. Briefly, tumor RNA was extracted from embedded tumor tissue sections with tumor cellularity higher than 20%. RNA libraries were sequenced to obtain approximately 65 million reads on an Illumina HiSeq 4000 System utilizing patterned flow cell technology. The RNA profile of a 24 male with Li-Fraumeni syndrome and recurrent HGG with leptomeningeal spread underwent comparative transcriptomics to identify targets. A Bayesian statistical framework for gene expression outlier detection was used. These comparisons allowed for the identification of genes and pathways that are significantly overexpressed. Our internal HGG cohort consisted of 44 adult patients and was evenly distributed among the 4 HGG Verhaak subtypes. Our patient of interest had druggable outlier expression in HDAC1, STAT1 and STAT2 in comparison to our internal cohort indicating vorinostat and ruxolitinib as potential therapies, respectively. We then compared our patient of interest to 12,747 patients in the cancer compendium and STAT2 expression was high but not an outlier. In comparison to 738 glioma samples, STAT1 and STAT2 were outliers but not HDAC1 again indicating ruxolitinib as a potential targeted therapy. The patient did not have outlier expression in notch transcriptional targets or immune checkpoint biomarkers when compared to all cohorts. In conclusion, comparative Transcriptomics can identify therapeutic targets in a patient with recurrent HGG even in small cohorts. In our pilot, we identified ruxolitinib as a potential candidate to treat leptomeningeal recurrence.

Abstract CT234: Phase I study of epacadostat added to preoperative chemoradiation in patients with locally advanced rectal cancer

Abstract Background: Epacadostat is an orally active, potent and selective inhibitor of indoleamine 2, 3-dioxygenase 1 (IDO1). IDO1 inhibition enhances cytotoxic T cell activation by dendritic cells, and significantly decreases regulatory T cell proliferation. We developed preclinical data supporting combination of epacadostat with radiation therapy in rectal cancer. In rectal cancer samples obtained from patients who received hypofractionated radiation, IDO1 was overexpressed in tumor tissue as compensatory response after radiation in both microsatellite stable and unstable cell lines. IDO1 inhibition with epacadostat selectively reduced survival of cancer cells and enhanced radiosensitivity without impacting normal epithelial cells. Epacadostat in addition to radiation showed both increased tumor cytotoxicity and enhanced immune activation in tumor microenvironment in a syngeneic mouse model of colorectal cancer. Literature also supports the choice of high dose, hypofractionated radiation to induce a more favorable anti-tumor immune response. Therefore, we hypothesized that IDO1 expression is a mechanism of radioresistance in rectal cancer and IDO1 inhibition is a safe and well-tolerated combination therapy to enhance tumor radiosensitivity. Methods: Patients with locally advanced rectal cancer who are candidates for neoadjuvant therapy using short-course radiation and chemotherapy are included in this study. Primary objective of the study is to determine the recommended phase II dose (RP2D) of epacadostat for combination with short course radiation and chemotherapy in preoperative treatment of locally advanced rectal cancer. This study includes dose-escalation part of patients receiving epacadostat with radiation and chemotherapy (n=6-18) followed by dose-expansion (n=up to 27 including those treated at RP2D during escalation). Two dose levels of epacadostat (300mg and 600mg orally twice daily) will be explored. Epacadostat will be combined with short-course radiation (5Gy x 5 fractions) followed by 6 cycles of CAPOX chemotherapy, until the day of surgery for a total of approximately 24 weeks of therapy. Research biopsies of tumor and adjacent non-tumor tissue along with blood sample collection will be performed before and after the radiation, and at the time of surgery. Tryptophan pathway metabolites, immune checkpoint biomarkers, markers of cell death, proliferation and potentially prognostic molecular biomarkers will be measured in tumor tissues before and after radiation therapy. In addition, patient-derived organoid and xenograft models from rectal biopsy samples will be used to determine the success rate of organoid generation, to evaluate treatment response and to characterize molecular changes to identify potential predictors of response and mechanisms of resistance. Enrollment began in November 2019. NCT03516708 Citation Format: Haeseong Park, Ebunoluwa Otegbeye, Hyun Kim, Matthew Mutch, Katrina Pedersen, Manik Amin, Benjamin Tan, Nikolaos Trikalinos, Kian-Huat Lim, Olivia Aranha, Rama Suresh, Shahed Badiyan, Matthew Silviera, Lauren Henke, Paul Wise, Steven Hunt, Jonathan Mitchem, Esther Lu, Andrea Wang-Gillam, Matthew Ciorba. Phase I study of epacadostat added to preoperative chemoradiation in patients with locally advanced rectal cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT234.

Abstract 3857: Characterization of immune cell biomarkers in undifferentiated pleomorphic sarcoma

Abstract Background: Undifferentiated pleomorphic sarcoma (UPS) are genetically complex sarcomas often showing a relatively higher immune infiltration among sarcomas, and a demonstrated benefit for immunotherapy in a subset of patients. This study characterizes the immune microenvironment of UPS including tumor infiltrating lymphocytes (TILs), as well as immune checkpoint (IC) and related biomarkers. Methods: We used FFPE surgical resected UPS from 90 patients (43 primary, 28 recurrence and 19 metastasis) placed in a tissue microarray and stained with immunohistochemistry for the following biomarkers: IC (stimulatory: OX40 & ICOS; inhibitory: PD-L1, LAG3, IDO1, & PD1), TILs (CD3 & CD8), monocytes-macrophages (CD163), Adenosine Pathway (CD73 & CD39), and pSTAT3. We scored TIL and IC biomarkers as positive cell densities, and PD-L1, pSTAT3, CD73 and CD39 as percentage of expression in malignant cells. Clinicopathological data and clinical outcome were available for all patients. Spearman correlation was used to assess the correlation between two biomarkers. Cox proportional hazard regression models were used to identify the prognostic biomarkers for overall survival (OS), recurrence-free survival (RFS), and metastasis-free survival (MFS). Results: In our cohort, PD-L1, pSTAT3, CD73 and CD39 positive expression (cut-off ≥1%) was 19, 73 78 and 68% respectively. These biomarkers were positively correlated with immune infiltrates: CD3 (p=0.013, 0.009, 0.009, <.001), CD8 (p=0.004, 0.016, <.001, <.001) and ICOS (p=0.005, 0.222, 0.007, 0.022). CD73 and CD39 were also positively correlated with both CD163 (p=0.001, <.001) and PD-1 (p=0.012, <.001). In recurrent tumors, smaller tumors had higher CD3, CD8, ICOS and PD-1 (p=0.011, 0.045, 0.013, 0.045). In metastatic tumor, CD163 and OX40 were positively correlated with age (p=0.045, 0.019). OX40 was inversely correlated with tumor size (p=0.04). ICOS positively correlated with PD-1, PD-L1 and CD39 (p<.001, 0.002, 0.003) in primary tumors; with IDO1 and PD1 (p=0.012, <.001) in recurrent tumors; and with PD-L1 expression (p=0.031) in metastatic tumors. Low CD3, CD8, CD163 densities (cut-off median) were associated with inferior OS (HR: 3.19 [1.37, 7.42]; p=0.007), RFS (HR: 2.79 [1.21, 6.42], p=0.016), and MFS (HR: 2.42 [1.05, 5.56]; p=0.038) after adjusting for size, respectively. Low CD73 and PD-L1 (cut-off median) were associated with inferior OS (HR 3.03 [HR: 1.21, 7.61], p=0.018), RFS (HR: 2.59 [1.06, 6.36]; p=0.037), and MFS (HR: 2.43 [1.00, 5.89], p=0.049), respectively. Conclusions: In this study, we characterized the immune cell infiltrates and the expression of PD-L1, pSTAT3, CD73 and CD39 in UPS. These biomarkers differentially correlated with clinicopathological characteristics in primary, recurrent and metastatic tumors. Lower TILs and low CD73/PD-L1 expression were associated with inferior survival outcomes. Citation Format: Carmelia M. Barreto, Luisa M. Solis-Soto, Ruth Salazar, Swati Gite, Edwin R. Parra, Barbara Mino, Davis Ingram, Khalida M. Wani, Cheuk H. Leung, Heather Lin, Ignacio I. Wistuba, Alexander Lazar, Wei-Lien Wang. Characterization of immune cell biomarkers in undifferentiated pleomorphic sarcoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3857.

Abstract 4986: Utilizing image analysis to characterize an 8-plex immunofluorescence immune checkpoint biomarker panel within the tumor tissue microenvironment

Abstract Multiplex staining and image analysis are being increasingly deployed for immuno-oncology (I/O) evaluations to investigate and understand the complexity of immune cell / tumor cell interactions in the tumor microenvironment (TME) and in discovering novel predictive biomarkers for targeted immunotherapy. Immune checkpoint inhibitor treatment, guided by immunohistochemically labelled tissue expression of PD-L1 and PD-1, have already been shown to improve outcomes, in the metastatic setting, for non-small cell lung carcinoma (NSCLC) and colorectal cancer (CRC) patients. The purpose of the current study was to phenotype and compare checkpoint and immune cell interactions within NSCLC and CRC tumor types. The study included samples from NSCLC, CRC, and normal tonsil tissues. Sections were stained using InSituPlex® multiplex immunofluorescence (mIF), for studying PD-L1/PD-1 checkpoint expression including immune cell markers for CD3, CD4, CD8, CD68, FoxP3, and pan-CK as an epithelial tumor indicator. Slides were scanned at 20X magnification on the ZEISS Axio Scan.Z1 platform, with individual .tiff format files being generated per marker. Image analysis was performed using the Visiopharm® Oncotopix® platform. Individual marker image layers were aligned, tumor/stroma regions of interest (ROI) classified, and cell formations detected. Quantification of markers was determined across the image layers to evaluate positive cell staining within both cancer indications. Quantitative image analysis data generated included total positive and negative cell counts per marker, per mm2 ROI. Co-localization analysis provided relevant immune cell phenotypes (T-cytotoxic, T-helper, T-regs, and macrophages) and immune cell functional status. Cell spatial analysis relationships were generated, including CD8+/PD-1− and CD8+/PD-1+ to CK+/PD-L1+ tumor cells. This study highlighted the benefits of utilizing an 8-plex staining protocol and detailed image analysis approach for the comprehensive assessment of the immune cell types and interactions within the TME. The ability to carry out multiparameter cellular analysis facilitates the delivery of key phenotypic data, thereby leading to greater understanding of tumor biology. Citation Format: Alison L. Bigley, Lorcan A. Sherry, Nicole Stillie, Douglas Wood, Sean Downing. Utilizing image analysis to characterize an 8-plex immunofluorescence immune checkpoint biomarker panel within the tumor tissue microenvironment [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4986.

Association between immunotherapy biomarkers and glucose metabolism from F-18 FDG PET.

To assess associations between parameters derived from F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and mRNA expression levels of immune checkpoint biomarkers such as programmed death receptor 1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte antigen 4 (CTLA-4) as well as tumor mutation burden (TMB) in non-small cell lung cancer (NSCLC) patients. Integrated data were downloaded from Genomic Data Common Data Portal. Clinical, mRNA-seq, and whole exome-seq data of lung adenocarcinoma and squamous cell carcinoma from The Cancer Genome Atlas (TCGA) database were analyzed. TMB was defined as the total number of somatic missense mutations per megabase of the genome examined. Expression levels of PD-1, PD-L1, CTLA4 mRNA and TMB were collected. Correlations between imaging parameters of glucose metabolism and the expression levels of genomic biomarkers from cancers were evaluated. Bonferroni correction (adjusted p<0.0027) was applied to reduce type 1 error. Of 31 NSCLC cases, 11 cases were adenocarcinoma (LUAD) and 20 were squamous cell carcinoma (LUSC). In linear regression analysis, texture parameters such as low gray-level run emphasis (LGRE, R2=0.48, p<0.0001), short run low gray-level emphasis (SRLGE, R2=0.45, p<0.0001) and long run low gray-level emphasis (LRLGE, R2=0.41, p=0.0001) derived from gray-level run length matrix (GLRLM) showed remarkable correlation with PD-L1 mRNA expression. Expression of PD-1, CTLA-4, and TMB failed to show any significant correlation with parameters of the F-18 FDG PET/CT. Texture parameters derived from PET, known to indicate glucose uptake distribution, were correlated with expression of PD-L1 mRNA but not with expression of PD-1, CTLA-4 and TMB. Thus, tumoral heterogeneity could be a surrogate marker for the identification of PD-L1 level in NSCLC.

The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation

BackgroundLimited studies examine the immune landscape in Esophageal Adenocarcinoma (EAC). We aim to identify novel associations, which may inform immunotherapy treatment stratification.MethodsThree hundred twenty-nine EAC cases were available in Tissue Microarrays (TMA) format. A discovery cohort of 166 EAC cases were stained immunohistochemically for range of adaptive immune (CD3, CD4, CD8 and CD45RO) and immune checkpoint biomarkers (ICOS, IDO-1, PD-L1, PD-1). A validation cohort of 163 EAC cases was also accessed. A digital pathology analysis approach was used to quantify biomarker density.ResultsCD3, CD4, CD8, CD45RO, ICOS and PD-1 were individually predictive of better overall survival (OS) (Log rank p = < 0.001; p = 0.014; p = 0.001; p = < 0.001; p = 0.008 and p = 0.026 respectively). Correlation and multivariate analysis identified high CD45RO/ICOS patients with significantly improved OS which was independently prognostic (HR = 0.445, (0.223–0.886), p = 0.021). Assessment of CD45RO and ICOS high cases in the validation cohort revealed an associated with improved OS (HR = 0.601 (0.363–0.996), p = 0.048). Multiplex IHC identified cellular co-expression of high CD45RO/ICOS. High CD45RO/ICOS patients have significantly improved OS.ConclusionsMultiplexing identifies true cellular co-expression. These data demonstrate that co-expression of immune biomarkers are associated with better outcome in EAC and may provide evidence for immunotherapy treatment stratification.

Supramolecular Photothermal Nanomedicine Mediated Distant Tumor Inhibition via PD-1 and TIM-3 Blockage.

Supramolecular nanoparticles for photothermal therapy (PTT) have shown promising therapeutic efficacy in the primary tumor and great potential for turning the whole-body immune microenvironment from “cold” to “hot,” which allows for the simultaneous treatment of the primary tumor and the metastatic site. In this work, we develop a liposome-based PTT nanoparticle through the self-assembly of FDA-approved intravenous injectable lipids and a photothermal agent, indocyanine green (ICG). The obtained ICG-liposome shows long-term storage stability, high ICG encapsulation efficiency (>95%), and enhanced near-infrared (NIR) light-triggered photothermal reaction both in vitro and in vivo. The ICG-liposome efficiently eradicated the primary tumor upon laser irradiation in two colon cancer animal models (CT26 and MC38) and promoted the infiltration of CD8 T cells to distant tumors. However, PTT from ICG-liposome shows only a minimal effect on the inhibition of distant tumor growth in long-term monitoring, predicting other immunosuppressive mechanisms that exist in the distant tumor. By immune-profiling of the tumor microenvironment, we find that the distant tumor growth after PTT highly correlates to compensatory upregulation of immune checkpoint biomarkers, including program death-1 (PD-1), T-cell immunoglobulin, and mucin domain-containing protein 3 (TIM-3), in tumor-infiltrating CD8 T cells. Based on this mechanism, we combine dual PD-1 and TIM-3 blockade with PTT in an MC38 tumor model. This combo successfully clears the primary tumor, generates a systemic immune response, and inhibits the growth of the distant tumor. The ICG-liposome-combined PD-1/TIM-3 blockade strategy sheds light on the future clinical use of supramolecular PTT for cancer immunotherapy.

Inside the USCAP Journals

Inside the USCAP Journals

Expression of lymphocyte immunoregulatory biomarkers in bone and soft-tissue sarcomas

Despite advances in our understanding of the underlying molecular drivers of sarcomas, few treatments are available with proven benefit for advanced metastatic sarcomas. Immunotherapy has value in this setting for some types of cancers, but sarcomas, with their multiplicity of rare types, have not been characterized in detail for their expression of targetable immune biomarkers. This study provides the most systematic evaluation to date of tumor-infiltrating lymphocytes and immune checkpoint biomarker expression in sarcomas. We examined by morphology and immunohistochemistry 1072 sarcoma specimens representing 22 types, in addition to 236 benign bone and soft-tissue tumors. Genomically-complex sarcoma types—those driven by mutations and/or copy-number alterations—had much higher numbers of tumor-infiltrating lymphocytes than translocation-associated sarcomas. Prior exposure to radiotherapy was associated with increased immune infiltrates. Higher lymphocytic infiltration was associated with better overall survival among the non-translocation-associated sarcomas. Expression of PD-1 and CD56 were associated with worse overall survival. LAG-3 and TIM-3, two emerging immune checkpoints, were frequently expressed in most sarcoma types. Indeed, most cases positive for PD-(L)1 coexpressed one or both of these novel biomarkers, providing a potential rationale in support for trials targeting LAG-3 and/or TIM-3 in conjunction with PD-1 inhibition.

The type of distribution of PD-L1 positive immune cells and PD-L1 expression in tumor cells correlate with the development of non-classical differentiation in urinary bladder cancer

Background: The basic diagnostic tool of urinary bladder cancer is the histopathological assessment. However, it is insufficient to accurately predict the progression of this disease. There is a need to look for new prognostic factors that will make the therapeutic process more effective. The aim of this study is to evaluate the effect of activation of a PD1 – PD-L1 immune checkpoint in immune effector cells (IECs) and tumor cells, on the development of malignancy in the form of non-classic differentiation in urinary bladder cancer. Materials and methods: 110 patients with stage pT1-pT4 urothelial bladder carcinoma who underwent radical cystectomy/cystoprostatectomy between 2011 and 2014 were included in the study. Tumor advancement (pT stage), grade (G), as well as, non-classic differentiation frequency and number were evaluated pathologically. In each case, the area of the tumor containing PD-L1+ IECs was analyzed. The distribution of PD-L1+ immune effector cells within the tumor was also assessed as dispersed or aggregated. Results: The frequency of non-classic differentiation was significantly lower in urothelial bladder cancer tumors with a dispersed pattern of distribution of PD-L1+ IECs. A correlation between the extent of PD-L1 expression in tumor cells and the non-classic differentiation number in UBC was identified. Conclusions: The distribution of cells expressing the immune checkpoint biomarker PD-L1 constitutes a new prognostic factor and may play a key role in the selection of individualized immunotherapy. In addition, the evaluation of non-classic differentiation in the tumor may complement the assessment of PD-L1 expression due to its capacity to characterize the current malignant potential of the tumor, whereas the assessment of extent and distribution of PD-L1+ in tumor-associated immune cells indicates the functional status of the immune system.

Bioinformatics Model of Serum Biomarkers to Prognosticate the Response to Programmed Death-1/Ligand-1 Targeted Immunotherapy in Metastatic Non–Small Cell Lung Cancer

Abstract Introduction Immune-checkpoint inhibitors revolutionized the therapeutic paradigm for metastatic non–small cell lung cancer (NSCLC). The average response, however, still hovers at 20%, demonstrating the urgent need for biomarkers predictive of response. High-throughput laboratory technology promises to serve as an insightful and robust tool to recognize and select patterns of biomarkers in serum. We applied machine learning on serum immune-checkpoint biomarkers for prognostication of response to immunotherapy in advanced NSCLC. Method Pretreatment sera from 106 advanced NSCLC cases who failed frontline chemotherapy were evaluated for 16 soluble immune-checkpoint molecules using the Human Immuno-Oncology Checkpoint Protein Panel (MilliporeSigma). This panel constituted BTLA, CD27, CD28, TIM-3, HVEM, CD40, GITR, GITRL, LAG-3, TLR-2, PD-1, PD-L1, CTLA-4, CD80, CD86, and ICOS. Primary data points were collected and calculated via a Luminex FLEXMAP 3D system (xPONENT v4.0.3 Luminex Corp). The minimum follow-up after treatment was 12 months. Response patterns were categorized based on their overall survival (OS) as long-term responders (&gt;12 months) or short-term responders (&lt;12 months). Values were analyzed with the clinical outcomes using “Survminer” and “survival” R packages to determine the log-rank-based cutoff values associated with overall survival. Finally, machine learning methods were implemented using “caret” and “rpart” R packages to fit a classification model to predict the response pattern. The model was trained and tested on random fractions of the cohort. Results BTLA4, HVEM, CD40, GITRL, LAG-3, PD-1, CD80, and CD86 serum levels significantly correlated with OS (all P values ≤.02 and HR of 0.27, 0.5, 4.59, 0.17, 0.12, 0.48, 3.64, and 0.37, respectively). The algorithm composing PD-1, LAG-3, CD86, and CTLA4 predicted the response pattern with PPV of 81%, specificity of 87%, and accuracy of 75%. Conclusion The serum immune-checkpoint predictive model might assist in the tissue and gene-based profiling of immune-checkpoints to predict the benefit from immunotherapy.