Prognostic Immune Biomarkers Research Articles

MRNA-seq-based analysis predicts: AEG-1 is a therapeutic target and immunotherapy biomarker for pan-cancer, including OSCC

BackgroundThe aberrant expression of AEG-1 is significantly correlated with tumorigenesis, development, neurodegeneration and inflammation. However, the relationship between AEG-1 expression and immune infiltration in OSCC, as well as other tumor types, has yet to be comprehensively analyzed.MethodsThe expression levels, prognostic and clinicopathological characteristics, mutation patterns and methylation landscapes of AEG-1 in various tumors were obtained from multiple databases, including TIMER, GEPIA, HPA, TCGA, UALCAN, cBioPortal, SMART and TISIDB, in addition to single-cell RNA-seq data. The integration of these datasets facilitated the elucidation of the relationships among pan-cancer cellular heterogeneity, immune infiltration and AEG-1 expression levels. In vitro experiments created AEG-1 overexpressing cell lines, and mRNA-seq analyzed AEG-1-related differential genes in OSCC. RT-PCR validated these findings in vivo using xenograft tumors. Tumor cell lines were developed to study AEG-1’s effects through H&E, Masson, and PAS staining. Immunohistochemistry examined AEG-1-related gene expression patterns.ResultsOur analysis demonstrated that AEG-1 is highly expressed across various cancer types and is associated with tumor grade and patient prognosis. Additionally, AEG-1 amplification was observed in multiple cancers. Notably, we identified a significant elevation of AEG-1 expression in OSCC, which strongly correlated with patient prognosis and immune infiltration. Through mRNA-seq analysis of differentially expressed genes and immune-related gene sets, we identified a strong correlation between AEG-1 and immune infiltration markers such as LCP2, CD247, HLA-DPA1, HLA-DRA, HLA-DRB1, CIITA and CD74 in OSCC. Additionally, AEG-1 was found to regulate Th1/Th2 immune homeostasis, promote glycogen accumulation, and contribute to tumor fibrosis.ConclusionIn conclusion, AEG-1 significantly correlates with prognosis and immune infiltration across various cancer types and holds potential as a novel prognostic immune biomarker for OSCC. This finding may facilitate the identification of patients who are most likely to benefit from adjuvant immunotherapy.

Day 100 Recovery of Absolute Number of Inhibitory KIR2DL2 and Activating NKp30 Natural Killer Cells Predicts Survival Post-Autologous Stem Cell Transplantation in Lymphomas.

The infusion autograft absolute number of inhibitory killer immunoglobulin-like receptor (KIR) 2DL2 and activating natural killer (NK)p30 cells are predictors of clinical outcomes in lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). To assess if the long-term recovery of these NK cell subsets still holds clinical relevance, we set up to investigate their prognostic ability at day 100 post-APBHSCT. This was a retrospective single-institution study including 107 patients from our prior phase III trial who had a clinical assessment at day 100 post-APBHSCT. The median follow-up from day 100 was 168.19 months (interquartile range: 156.85-181.28 months). Patients with day 100 inhibitory KIR2DL2 < 0.08 cells/µL and activating NKp30 ≥ 0.19 cells/µL experienced superior overall survival (OS) and progression-free survival (PFS). A multivariate analysis revealed both the day 100 inhibitory KIR2DL2 [OS: HR = 1.449, 95%CI, 1.231-1.895, p < 0.013; and PFS: HR = 2.069, 95%CI, 1.134-3.775, p < 0.021] and activating NKp30 [OS: HR = 4.985, 95%CI, 2.614-9.506, p < 0.0001; and PFS: HR = 4.661, 95%CI, 2.598-8.393, p < 0.0001] were independent predictors for OS and PFS. Inhibitory KIR2DL2 and activating NKp30 NK cells at day 100 are prognostic immune biomarkers in lymphoma patients treated with APBHSCT.

Th2 Cells Are Associated with Tumor Recurrence Following Radiation.

The curative treatment of multiple solid tumors, including head and neck squamous cell carcinoma (HNSCC), utilizes radiation. The outcomes for HPV/p16-negative HNSCC are significantly worse than HPV/p16-positive tumors, with increased radiation resistance leading to worse locoregional recurrence (LRR) and ultimately death. This study analyzed the relationship between immune function and outcomes following radiation in HPV/p16-negative tumors to identify mechanisms of radiation resistance and prognostic immune biomarkers. A discovery cohort of 94 patients with HNSCC treated uniformly with surgery and adjuvant radiation and a validation cohort of 97 similarly treated patients were utilized. Tumor immune infiltrates were derived from RNAseq gene expression. The immune cell types significantly associated with outcomes in the discovery cohort were examined in the independent validation cohort. A positive association between high Th2 infiltration and LRR was identified in the discovery cohort and validated in the validation cohort. Tumor mutations in CREBBP/EP300 and CASP8 were significantly associated with Th2 infiltration. A pathway analysis of genes correlated with Th2 cells revealed the potential repression of the antitumor immune response and the activation of BRCA1-associated DNA damage repair in multiple cohorts. The Th2 infiltrates were enriched in the HPV/p16-negative HNSCC tumors and associated with LRR and mutations in CASP8, CREBBP/EP300, and pathways previously shown to impact the response to radiation.

TRIM56: a promising prognostic immune biomarker for glioma revealed by pan-cancer and single-cell analysis.

Tripartite-motif 56 (TRIM56) is a member of the TRIM family, and was shown to be an interferon-inducible E3 ubiquitin ligase that can be overexpressed upon stimulation with double-stranded DNA to regulate stimulator of interferon genes (STING) to produce type I interferon and thus mediate innate immune responses. Its role in tumors remains unclear. In this study, we investigated the relationship between the expression of the TRIM56 gene and its prognostic value in pan-cancer, identifying TRIM56 expression as an adverse prognostic factor in glioma patients. Therefore, glioma was selected as the primary focus of our investigation. We explored the differential expression of TRIM56 in various glioma subtypes and verified its role as an independent prognostic factor in gliomas. Our research revealed that TRIM56 is associated with malignant biological behaviors in gliomas, such as proliferation, migration, and invasion. Additionally, it can mediate M2 polarization of macrophages in gliomas. The results were validated in vitro and in vivo. Furthermore, we utilized single-cell analysis to investigate the impact of TRIM56 expression on cell communication between glioma cells and non-tumor cells. We constructed a multi-gene signature based on cell markers of tumor cells with high TRIM56 expression to enhance the prediction of cancer patient prognosis. In conclusion, our study demonstrates that TRIM56 serves as a reliable immune-related prognostic biomarker in glioma.

Day 100 Natural Killer Cell/CD14+HLA-DRDIM ratio and survival in lymphoma post-autologous peripheral blood hematopoietic stem cell transplantation.

The infusion of autograft Natural Killer Cells (NKC)/CD14+ HLA-DRDIM ratio is a predictor of survival in lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). This study evaluated if the Day 100 NKC/CD14+ HLA-DRDIM ratio still functions as a prognostic immune-biomarker. This was a retrospective, single-institution, cohort analysis including 107 patients in this study that had clinical assessment at Day 100 post-APBHSCT from our prior phase III trial. We evaluated the prognostic ability of the Day 100 NKC/CD14+ HLA-DRDIM ratio to predict overall survival (OS) and progression-free survival (PFS) using Cox regression model for outcome analysis and survival by Kaplan-Meier method. The median follow-up from day 100 was 94.7 months (range 4.83-158.1 months) for the entire cohort. Patients with a Day 100 NKC/CD14+ HLA-DRDIM ratio ≥1.67 experienced better OS and PFS versus those with a Day 100 NKC/CD14+ HLA-DRDIM ratio <1.67: median OS was not reached versus 49.7 months, the 5-year OS rates were 91% (95% CI, 81%-96%) versus 40% (95% CI, 27%-55%), p<.0001, respectively; and median PFS was not reached versus 23.5 months, the 5-year PFS rates were 66% (95% CI, 55%-81%) versus 21% (95% CI, 15%-40%), p<.0001, respectively. Day 100 NKC/CD14+ HLA-DRDIM ratio was an independent predictor for OS and PFS in the multivariate analysis. Day 100 NKC/CD14+ HLA-DRDIM ratio is a prognostic immune-biomarker in lymphoma patients post- APBHSCT.

Day 100 Inhibitory KIR2DL2 and Activating NKp30 Natural Killer Cell Receptors Predicts Survival Post-Autologous Stem Cell Transplantation in Lymphomas

Introduction: Our group previously published that the infusion autograft inhibitor KIR2DL2 (CD158b+CD337-) and activating NKp30 (CD158b- CD337+) Natural killer (NK) cells receptors were predictors of clinical outcomes in lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT) (Porrata et al. Leukemia Research 2019; 81: 1-9). To assess if these subsets of NK cells still hold clinical relevance, we set up to investigate their prognostic ability to predict clinical outcomes at Day 100 post-APBHSCT. Methods: 107 lymphoma patients who participated in our double-blind phase III trail (Porrata et al, Biology of Blood and Marrow Transplantation 2016; 22(6); 1017-1023) and had clinical assessment at Day 100 post-APBHSCT were included in this study. Nkp30 and KIR2DL2 at Day 100 were assessed by flow cytometry analysis. Results: With a median follow-up for the entire cohort from Day 100 was 94.7 months (range: 4.83-158.1 months). Figure 1 shows the overall survival (OS) and progression-free survival (PFS) based on the absolute numbers of KIR2DL2 and Nkp30 NK cells. At Day 100, patients with a KIR2DL2 &amp;lt; 0.08 and Nkp30 ≥0.19 experienced superior OS and PFS compared with patients with a Day 100 KIR2DLD2 ≥0.08 and NKp30 &amp;lt; 0.19. In the multivariate analysis both the KIR2DL2 [OS: HR = 1.767, 95%CI, 1.302-30.31, p &amp;lt; 0.04; and PFS: HR = 2.663, 95%CI, 1.108-6.403, p &amp;lt; 0.03] and Nkp30 [OS: HR = 2.594, 95% CI, 1.239-5.432, p &amp;lt; 0.01; and PFS: HR = 3.676, 95% CI, 1.875-7.206, p &amp;lt; 0.01] were independent predictors for OS and PFS. Conclusion: Day 100 inhibitory KIR2DL2 and activating NKp30 NK cells are prognostic immune-biomarkers in lymphoma patients undergoing APBHSCT.

Prognostic Significance of Pretreatment Immune Cell Infiltration in Muscle Invasive Bladder Cancer Treated with Definitive Chemoradiation: Analysis of NRG RTOG 0524 and 0712

Chemoradiation therapy (CRT) is an organ conserving approach in the treatment of locally advanced bladder cancer. Chemoradiation is thought to potentially result in immunogenic stimulation, and bladder cancer is often a tumor with high immune cell infiltration. Thus, we aimed to profile the tumor immune microenvironment of bladder cancer and identify prognostic immune biomarkers for CRT response by profiling tumor samples from NRG/RTOG 0524 and 0712, two prospective trials of CRT in muscle invasive bladder cancer (MIBC). Pretreatment tissue samples from both trials were profiled using Cofactor Genomics ImmunoPrism, an RNA sequencing assay that uses gene expression profiles to quantify immune cell populations in the tumor microenvironment (TME). Differential gene expression was estimated for different immune cell type proportions across samples. Kaplan-Meier survival analysis and log rank tests were performed to evaluate differences in overall survival (OS) stratified by genes influenced by immune cell proportions or genes associated with immune response signatures. A total of 70 samples (43 from RTOG 0524 and 27 from RTOG 0712) underwent analysis using the ImmunoPrism assay. Immune cell proportions were as follows: CD8 T cells: median 1.2%, CD4 T cells: median 0.8%, Treg cells: median 9.2%, CD19 B cells: median 5.1%, M2 macrophages: median 0.8%, M1 macrophages: median 0%. Unbiased clustering based on gene expression profiles driven by immune cell proportions demonstrated two groups: cluster 1 with a low percentage of immune cells and shorter OS (median 31 months) and cluster 2 with a high percentage of immune cells and longer OS (median 101 months, p = 0.036). Higher expression of genes associated with T cell infiltration (CD8A and ICOS) was associated with improved OS (104 vs 35 months, p = 0.028, HR = 0.48 (0.25 - 0.94), p = 0.031) as was higher expression of IDO1, which is associated with the interferon gamma pathway (104 vs 35 months, p = 0.042, HR = 0.49 (0.24 - 0.99), p = 0.046). Bladder tumors have a wide range of immune cell infiltration in the TME. Increased immune cell proportions are prognostic for OS following CRT, as well as a higher expression of genes associated with T cell infiltration interferon gamma signaling. These findings have implications for the integration of immunotherapy in the definitive management of MIBC; and can be explored further in the ongoing NRG/SWOG 1806 trial.

Prognostic significance of pretreatment immune cell infiltration in muscle invasive bladder cancer treated with definitive chemoradiation: Analysis of NRG RTOG 0524 and 0712.

4523 Background: Chemoradiation therapy (CRT) is an organ conserving approach in the treatment of locally advanced bladder cancer. Chemoradiation is thought to potentially result in immunogenic stimulation, and bladder cancer is often a tumor with high immune cell infiltration. Thus, we aimed to profile the tumor immune microenvironment of bladder cancer and identify prognostic immune biomarkers for CRT response by profiling tumor samples from NRG/RTOG 0524 and 0712, two prospective trials of CRT in muscle invasive bladder cancer (MIBC). Methods: Pretreatment tissue samples from both trials were profiled using Cofactor Genomics ImmunoPrism, an RNA sequencing assay that uses gene expression profiles to quantify immune cell populations in the tumor microenvironment (TME). Differential gene expression was estimated for different immune cell type proportions across samples. Kaplan-Meier survival analysis and log rank tests were performed to evaluate differences in overall survival (OS) stratified by genes influenced by immune cell proportions or genes associated with immune response signatures. Results: A total of 70 samples (43 from RTOG 0524 and 27 from RTOG 0712) underwent analysis using the ImmunoPrism assay. Immune cell proportions were as follows: CD8 T cells: median 1.2%, CD4 T cells: median 0.8%, Treg cells: median 9.2%, CD19 B cells: median 5.1%, M2 macrophages: median 0.8%, M1 macrophages: median 0%. Unbiased clustering based on gene expression profiles driven by immune cell proportions demonstrated two groups: cluster 1 with a low percentage of immune cells and shorter OS (median 31 months) and cluster 2 with a high percentage of immune cells and longer OS (median 101 months, p = 0.036). Higher expression of genes associated with T cell infiltration ( CD8A and ICOS) was associated with improved OS (104 vs 35 months, p = 0.028, HR = 0.48 (0.25 – 0.94), p = 0.031) as was higher expression of IDO1, which is associated with the interferon gamma pathway (104 vs 35 months, p = 0.042, HR = 0.49 (0.24 – 0.99), p = 0.046). Conclusions: Bladder tumors have a wide range of immune cell infiltration in the TME. Increased immune cell proportions are prognostic for OS following CRT, as well as a higher expression of genes associated with T cell infiltration interferon gamma signaling. These findings have implications for the integration of immunotherapy in the definitive management of MIBC; and can be explored further in the ongoing NRG/SWOG 1806 trial.

Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation

Background and purposeTumor recurrence after liver transplantation (LT) impedes the curative chance for hepatocellular carcinoma (HCC) patients. This study aimed to develop a deep pathomics score (DPS) for predicting tumor recurrence after liver transplantation using deep learning.Patients and methodsTwo datasets of 380 HCC patients who underwent LT were enrolled. Residual convolutional neural networks were used to identify six histological structures of HCC. The individual risk score of each structure and DPS were derived by a modified DeepSurv network. Cox regression analysis and Concordance index were used to evaluate the prognostic significance. The cellular exploration of prognostic immune biomarkers was performed by quantitative and spatial proximity analysis according to three panels of 7-color immunofluorescence.ResultsThe overall classification accuracy of HCC tissue was 97%. At the structural level, immune cells were the most significant tissue category for predicting post-LT recurrence (HR 1.907, 95% CI 1.490–2.440). The C-indices of DPS achieved 0.827 and 0.794 in the training and validation cohorts, respectively. Multivariate analysis for recurrence-free survival (RFS) showed that DPS (HR 4.795, 95% CI 3.017–7.619) was an independent risk factor. Patients in the high-risk subgroup had a shorter RFS, larger tumor diameter and a lower proportion of clear tumor borders. At the cellular level, a higher infiltration of intratumoral NK cells was negatively correlated with recurrence risk.ConclusionsThis study established an effective DPS. Immune cells were the most significant histological structure related to HCC recurrence. DPS performed well in post-LT recurrence prediction and the identification of clinicopathological features.

Abstract P3-05-09: LAG3+ Tumor Infiltrating Lymphocytes Predict Outcome in Treatment Naïve Triple Negative Breast Carcinoma

Abstract Significance: Triple negative breast carcinoma (TNBC), characterized by lack of estrogen (ER) and progesterone receptors (PR) and absence of Her2/neu (Her2) receptor amplification, typically follows an aggressive course that includes high relapse rates, rapid progression, and poor outcome. Advances in treatment have been limited by molecular heterogeneity within TNBCs and lack of effective molecular targets. Although a subset of TNBC associated with tumor infiltrating lymphocytes (TILS) is more immunogenic than other breast cancers, response to immunotherapy has been variable and reported in only 10-40% of cases. Identification of prognostic immune biomarkers will identify novel therapeutic targets and facilitate appropriate patient selection for therapy. Aim: To analyze the immune gene expression profile in TNBC and identify a prognostic marker. Methods: Targeted mRNA sequencing was performed on formalin fixed paraffin embedded whole sections from 30 treatment naïve TNBC with TILs (15 cases with a favorable outcome (recurrence free overall survival (OS) ≥5yrs) and 15 with unfavorable outcome (never disease free or dead of disease in &amp;lt; 5yrs) using the HTG Edge Seq Assay (HTG Molecular Diagnostics, Inc. Tucson AZ) to analyze the differential expression of 1392 immune related genes in their Precision Immuno-Oncology Panel. The top 40 up- and down- regulated DE genes with adjusted p-value of &amp;lt; 0.001 were then validated against the TNBC mRNA profiles in The Cancer Genome Atlas (TCGA) database. LAG3 was one of four genes that showed significant differential expression in both data sets. We used immunohistochemistry (IHC) (Rabbit monoclonal AntiLAG3 antibody, Abcam plc.) to analyze LAG3 expression in whole sections from 57 consecutive TNBCs where tumor excision had been the first line treatment. All patients were female, age 29-89 years (median 55 yrs). The infiltrating ductal carcinomas varied from 0.6 to 9.0 cm (median 2.6 cm). All tumors were ER-, PR-, Her2- with a median Ki67 of 42%. 26 patients had metastatic carcinoma in 1-17 lymph nodes (median 2). Two patients had metastatic disease at presentation. Disease free survival (DFS) varied from 0 to 114.8 months (median 81.4 mos.), and overall survival (OS) varied from 7.6 to 114.8 months (median 81.5 mos.). LAG3 expression was categorized as negative (0), low (1+) and high (2+). The student t-test was used to correlate LAG3 expression with DFS and OS. Results: Differential expression analysis from our data set yielded 222 statistically significant differentially expressed genes. Validation against the TCGA TNBC data set revealed 4 common genes, one of which is LAG3. Only TILS showed LAG3 expression by IHC: 10 cases no expression, 17 low expression and 29 high expression. Median DFS and OS in TNBC with no LAG3 expression was 32.3 and 55.2 months, in TNBC with low expression 83.3 and 81.1 and those with high expression was 82 and 82.1 month. Median DFS and OS in LAG3 negative cases was significantly different from those in LAG3 positive cases (p=0.038, p=0.013) and between LAG3 0 and LAG3 2+ positive cases (p=0.002, p=0.0018). No difference in either median DFS or OS was seen when LAG3 1+ and LAG3 2+ cases were compared. Conclusions: 1. LAG3 is a prognostic marker for TNBCs. 2. LAG3 is expressed only on TILS and shows heterogenous expression. 3. TNBC with no LAG3 expression had a median survival of 32 months, suggesting they might benefit from more aggressive therapy than TNBC that express LAG3. 4. Confirmation of these results requires a larger TNBC cohort. Citation Format: Shikha Bose, Yizhou Wang, V Krishnan Ramanujan, Ann E. Walts. LAG3+ Tumor Infiltrating Lymphocytes Predict Outcome in Treatment Naïve Triple Negative Breast Carcinoma [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 P3-05-09.

Tumor necrosis factor-α-inducible protein 8-like protein 3 (TIPE3): a novel prognostic factor in colorectal cancer

BackgroundTo explore the correlation of tumor necrosis factor-α-induced protein 8-like protein 3 (TIPE3) expressions in colorectal cancer (CRC) with tumor-immune infiltration and patient prognosis.MethodsFormalin-fixed paraffin-embedded tumor samples from CRC patients (n = 110) were used in this study. Immunohistochemistry staining of TIPE3 and three prognostic immune biomarkers (CD8, CD20, and CD66b) was conducted in the tumor tissues and adjacent normal tissues. A Cox regression analysis of univariate and multivariate variables was performed to assess the correlation between TIPE3 and patient prognosis.ResultWe found that TIPE3 was mainly expressed in the cytoplasm, with a small amount in the nucleus. The expression of TIPE3 in tumor tissues is significantly higher than in adjacent normal tissues, and it is significantly correlated with the survival rate of patients in tumor tissues (p = 0.0038) and adjacent normal tissues (p<0.0001). Patients with a high TIPE3 expression had a lower survival rate, while patients with a low TIPE3 expression had a higher survival rate. Univariate regression analysis showed that the TIPE3 expression in tumor tissues (p = 0.007), the TIPE3 expression in adjacent normal tissues (p<0.001), the number of CD8+ T cells in tumor tissues (p = 0.020), the number of CD20+ B cells in tumor tissues (p = 0.023), the number of CD20+ B cells in adjacent normal tissues (p = 0.023), the number of CD66b+ neutrophils in tumor tissues (p = 0.005), the number of CD66b+ neutrophils in adjacent normal tissues (p<0.001), lymphatic metastasis (p = 0.010), TNM stage (p = 0.013), and tumor grade (p = 0.027) were significantly correlated with overall survival (OS). These prognostic factors were then subjected to multivariate regression analysis, and the results showed that the expression of TIPE3, the number of CD8+ T cells, and the number of CD66b+ neutrophils were prognostic factors affecting the OS rate of CRC patients.ConclusionWe found that the TIPE3 protein is upregulated in CRC cancer tissues and is correlated with survival rate.

Prognostic value of preoperative soluble interleukin 2 receptor α as a novel immune biomarker in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is regarded as the deadliest gynecological cancer, and the demand for novel noninvasive prognostic biomarkers remains significant. This study aimed to investigate the prognostic value of preoperative blood biomarkers in EOC patients. In total, 73 patients who had undergone ovarian mass resection were enrolled. Serum concentration of biomarkers, including soluble interleukin 2 receptor α (sIL-2R), was measured 1-2weeks before surgery. Independent prognostic factors for progression-free survival (PFS) were investigated with multivariate Cox regression analysis. A prognostic model was subsequently developed and evaluated by discrimination, calibration and clinical net benefit. Furthermore, transcriptome data of 376 EOC cases from The Cancer Genome Atlas (TCGA) were analyzed with ESTIMATE, CIBERSORT and Maftools algorithm to evaluate the correlation of IL2RA expression with tumor immune microenvironment and immunotherapeutic response. High sIL-2R concentration was found to be the only significant prognostic blood biomarker for PFS by multivariate Cox regression analysis in our center. A prognostic nomogram was developed with satisfactory discrimination, calibration and clinical net benefit. In addition, higher IL2RA expression was significantly associated with higher immune scores, activated CD4+ T cells, M2 macrophages and resting dendritic cells in TCGA data. Furthermore, IL2RA expression was closely related to TMB scores. sIL-2R is a potential prognostic immune biomarker for EOC patients, and a comprehensive prognostic model comprising sIL-2R with satisfactory discrimination and clinical appliance was developed. Therefore, we recommend routine sIL-2R testing in EOC patients.

Dissection of the bone marrow microenvironment in hairy cell leukaemia identifies prognostic tumour and immune related biomarkers

Hairy cell leukaemia (HCL) is a rare CD20+ B cell malignancy characterised by rare “hairy” B cells and extensive bone marrow (BM) infiltration. Frontline treatment with the purine analogue cladribine (CDA) results in a highly variable response duration. We hypothesised that analysis of the BM tumour microenvironment would identify prognostic biomarkers of response to CDA. HCL BM immunology pre and post CDA treatment and healthy controls were analysed using Digital Spatial Profiling to assess the expression of 57 proteins using an immunology panel. A bioinformatics pipeline was developed to accommodate the more complex experimental design of a spatially resolved study. Treatment with CDA was associated with the reduction in expression of HCL tumour markers (CD20, CD11c) and increased expression of myeloid markers (CD14, CD68, CD66b, ARG1). Expression of HLA-DR, STING, CTLA4, VISTA, OX40L were dysregulated pre- and post-CDA. Duration of response to treatment was associated with greater reduction in tumour burden and infiltration by CD8 T cells into the BM post-CDA. This is the first study to provide a high multiplex analysis of HCL BM microenvironment demonstrating significant immune dysregulation and identify biomarkers of response to CDA. With validation in future studies, prospective application of these biomarkers could allow early identification and increased monitoring in patients at increased relapse risk post CDA.

Fibrinogen-to-Albumin Ratio is Associated with All-Cause Mortality in Cancer Patients.

BackgroundPast studies have identified fibrinogen-to-albumin ratio (FAR) as a novel prognostic immune biomarker in various diseases. Here, we investigated the prognostic value of FAR in all combined cancer mortality.MethodsWe extracted patient data from the Multiparameter Intelligent Monitoring in Intensive Care Database III. FAR was measured prior to hospital admission. Only first admission data from each patient were used. Baseline data were extracted within 24 h after admission. The clinical endpoints were 90- and 365-day all-cause cancer mortality. Cox proportional hazards models and subgroup analyses were used to determine the relationship between FAR and these clinical endpoints.ResultsA total of 652 eligible patients were enrolled. Upon adjusting for age and gender, multivariate analysis revealed correlation between higher FAR values and increased risk of all-cause mortality. After adjusting for more confounding factors, higher FAR values significantly correlated with 90- and 365-day all-cause mortality relative to low FAR values (tertile 3 vs tertile 1: HR, 95% CI: 1.65, 1.15–2.39; 1.52, 1.10–2.10).ConclusionOur findings indicate that FAR may predict the risk of cancer mortality and is an independent prognostic indicator of all-cause mortality in cancer patients.

Potential Prognostic Immune Biomarkers of Overall Survival in Ovarian Cancer Through Comprehensive Bioinformatics Analysis: A Novel Artificial Intelligence Survival Prediction System.

Background: The tumour immune microenvironment plays an important role in the biological mechanisms of tumorigenesis and progression. Artificial intelligence medicine studies based on big data and advanced algorithms are helpful for improving the accuracy of prediction models of tumour prognosis. The current research aims to explore potential prognostic immune biomarkers and develop a predictive model for the overall survival of ovarian cancer (OC) based on artificial intelligence algorithms.Methods: Differential expression analyses were performed between normal tissues and tumour tissues. Potential prognostic biomarkers were identified using univariate Cox regression. An immune regulatory network was constructed of prognostic immune genes and their highly related transcription factors. Multivariate Cox regression was used to identify potential independent prognostic immune factors and develop a prognostic model for ovarian cancer patients. Three artificial intelligence algorithms, random survival forest, multitask logistic regression, and Cox survival regression, were used to develop a novel artificial intelligence survival prediction system.Results: The current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes between tumour samples and normal samples. Further univariate Cox regression identified 84 prognostic immune gene biomarkers for ovarian cancer patients in the model dataset (GSE32062 dataset and GSE53963 dataset). An immune regulatory network was constructed involving 63 immune genes and 5 transcription factors. Fourteen immune genes (PSMB9, FOXJ1, IFT57, MAL, ANXA4, CTSH, SCRN1, MIF, LTBR, CTSD, KIFAP3, PSMB8, HSPA5, and LTN1) were recognised as independent risk factors by multivariate Cox analyses. Kaplan-Meier survival curves showed that these 14 prognostic immune genes were closely related to the prognosis of ovarian cancer patients. A prognostic nomogram was developed by using these 14 prognostic immune genes. The concordance indexes were 0.760, 0.733, and 0.765 for 1-, 3-, and 5-year overall survival, respectively. This prognostic model could differentiate high-risk patients with poor overall survival from low-risk patients. According to three artificial intelligence algorithms, the current study developed an artificial intelligence survival predictive system that could provide three individual mortality risk curves for ovarian cancer.Conclusion: In conclusion, the current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes in ovarian cancer patients. Multivariate Cox analyses identified fourteen prognostic immune biomarkers for ovarian cancer. The current study constructed an immune regulatory network involving 63 immune genes and 5 transcription factors, revealing potential regulatory associations among immune genes and transcription factors. The current study developed a prognostic model to predict the prognosis of ovarian cancer patients. The current study further developed two artificial intelligence predictive tools for ovarian cancer, which are available at https://zhangzhiqiao8.shinyapps.io/Smart_Cancer_Survival_Predictive_System_17_OC_F1001/ and https://zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_17_OC_F1001/. An artificial intelligence survival predictive system could help improve individualised treatment decision-making.

Abstract PS16-01: Intra-epithelial tumor immune landscapes are associated with clinical outcomes in early-stage triple-negative breast cancer

Abstract Introduction: Stromal tumor-infiltrating lymphocytes (sTILs) have established prognostic and predictive significance in triple-negative breast cancer (TNBC). However, the roles of other immune cells in TNBC are less well-established. We performed high-plex quantitative spatial profiling in a cohort of early-stage TNBC to 1) apply spatial context to tumoral immune landscapes and 2) identify immune proteins associated with clinical outcomes, independently of TILs and other established prognostic clinicopathologic variables, in patients (pts) treated with or without adjuvant chemotherapy (CTX). Methods: The Mayo TNBC cohort comprises pts with centrally-verified, CTX-naive tumors resected from 1985-2012. Using a cohort-based TMA, with Nanostring GeoMX DSP, we quantitated 58 proteins within spatially-distinct intra-epithelial, cytokeratin-positive tumor segments and adjacent cytokeratin-negative/nuclei-positive stromal segments. Differentially-expressed (DE) proteins were identified using a negative binomial generalized linear model (SNR&amp;gt;2, p&amp;lt; 0.05) and a target DE protein set was dichotomized (80th percentile). After adjusting for prognostic clinicopathologic variables, proteins associated with recurrence-free survival (RFS, defined as time from surgery to either local, regional, and distant recurrence, or death by any cause) were identified by performing variable selection using the Akaike Information Criterion (AIC) obtained from fitting all possible Cox proportional hazards regression models (performed separately for intra-epithelial/stromal segments, and in groups +/- adjuvant CTX. Results: From the TNBC TMA, DSP data (N=250 tumors) included 169 pts who received adjuvant CTX+ and 81 who did not (CTX-). Overall, 85/250 developed recurrent disease. In the CTX+ group, intra-epithelial tumor segments from pts without recurrent disease were enriched in 10 immune proteins, including CD8, markers involved in antigen presentation/dendritic cells (CD11c, CD40, HLA-DR) or NK cells (CD56) (FC: 1.4-2.1, p&amp;lt;0.05); CD14 was increased in stroma (FC: 1.5, p&amp;lt;0.05). In contrast, in the CTX- group, both the intra-epithelial tumor and stromal segments from pts without recurrences were enriched in immune proteins (N= 12 and 15 respectively; FC 1.6-5.5, p&amp;lt; 0.05) most markedly CD40, IDO1 and HLA-DR (FC: 3.2-5.5, p&amp;lt; 0.05). Overall, CD3, CD4, CD27, CD44, and ICOS among others were enriched only in the CTX- group; CD14 and CD56 were enriched only in the CTX+ group. Based on these spatial data, biologic function and DSP data from another set of TNBC (FinXX trial), CD11c, CD14, CD27, CD40, CD56, and IDO1 were selected for RFS analysis. After applying our model selection criterion and adjusting for pt age at surgery, tumor size, lymph node status, and sTILs, intra-epithelial CD56 was independently associated with improved RFS in the CTX+ group (HR: 0.31[0.12, 0.81]). In the CTX- group, intra-epithelial CD11c was independently associated with improved RFS (0.10 [0.01, 0.81]). Conclusion: In this early-stage TNBC cohort, spatially-distinct tumor immune landscapes were associated with RFS but differed according to receipt of CTX after surgical resection. In the patients who received CTX, the intra-epithelial compartment, rather than stromal compartment, was immune-enriched in pts without recurrences. Among a targeted protein set, intra-epithelial CD56 remained associated with improved outcomes, independent of sTILs and other clinicopathologic features. In the CTX- group, spatial landscapes were more balanced, and intra-epithelial CD11c was independently associated with improved outcomes. These data provide insight into the spatial context of intrinsic immune landscapes in TNBC, and identify candidate prognostic immune biomarkers which may inform therapeutic strategies. Citation Format: Jodi M Carter, Saranya Chumsri, David W Hillman, David M Zahrieh, Yaohua Ma, Xue Wang, Jennifer M Kachergus, Judy C Boughey, Minetta C Liu, Krishna R Kalari, JC Villasboas, Roberto A Leon Ferre, Fergus J Couch, Matthew P Goetz, E. Aubrey Thompson. Intra-epithelial tumor immune landscapes are associated with clinical outcomes in early-stage triple-negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS16-01.

A prognostic immune predictor, HLA-DRA, plays diverse roles in non-muscle invasive and muscle invasive bladder cancer

BackgroundThere is an increasing demand for prognostic immune biomarkers of cancer. The prognostic significance of immune markers has been shown for various cancers, but biomarkers of bladder cancer (BCa) have not been fully evaluated. To clarify the role of human leukocyte antigen DR alpha chain (HLA-DRA) in BCa development, we examined expression of HLA-DRA mRNA in tissue samples of non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC). Materials and MethodsTissues of 96 NMIBC, 43 MIBC and 59 controls comprising noncancerous BCa surrounding tissues were used to examine the expression of HLA-DRA gene by real-time polymerase chain reaction. The expression of up-stream genes regulating HLA-DRA were also measured to explain the role of HLA-DRA in BCa. ResultsPatients with high grade NMIBC showed higher expression of HLA-DRA than those with low grade NMIBC (P < 0.05). In addition, NMIBC patients who progressed to MIBC showed high expression of HLA-DRA mRNA. Kaplan-Meier analysis showed that NMIBC patients with low expression of HLA-DRA had better progression-free survival than those with high expression (P = 0.004). Moreover, the expression of genes regulating HLA-DRA varied in NMIBC and MIBC, indicating a different immunoregulation effect of HLA-DRA in both cancers. ConclusionsHigh expression of HLA-DRA in NMIBC patients has implications for patient stratification strategies, as well as for BCa tumor immunology.

A novel immune-related genes prognosis biomarker for hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is closely associated with the immune microenvironment. To identify the effective population before administering treatment, the establishment of prognostic immune biomarkers is crucial for early HCC diagnosis and treatment.Results: A total of 335 IRGs identified from 788 overlapping IRGs were associated with the survival of HCC. A prognostic immunoscore model was identified. The Kaplan-Meier survival curves and time-dependent ROC analysis revealed a powerful prognostic performance of immunoscore signature via multi validation. Besides, the immunoscore signature exhibited a better predictive power compared to other prognostic signatures. Gene set enrichment analysis showed multiple signaling differences between the high and low immunoscore group. Furthermore, immunoscore was significantly associated with multiple immune cells and immune infiltration in the tumor microenvironment.Conclusions: We identified the immunoscore as a robust marker for predicting HCC patient survival.Methods: Three sets of immune-related genes (IRGs) were integrated to identify the overlapping IRGs. Weighted gene co-expression network analysis was performed to obtain the survival-related IRGs. Further, the prognostic immunoscore model was constructed via LASSO-penalized Cox regression analysis. Then the prognostic performance of immunoscore was evaluated. In addition, ESTIMATE and CIBERSORT algorithms were applied to explore the relationship between immunoscore and tumor immune microenvironment.

Higher TIGIT+CD226- γδ T cells in Patients with Acute Myeloid Leukemia

ABSTRACT The diverse structural and functional heterogeneity of γδ T cells is related to their distinct role in cancer immunity. The different phenotypes of γδ T cells in patients with acute myeloid leukemia (AML) is far from clear. In particular, the expression pattern of co-inhibitory and co-stimulatory receptors on γδ T cells remains unknown. In this study, we analyzed the distribution of γδ T cell subsets by expression of the immune checkpoint co-inhibitor TIGIT (T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain) and its competing co-stimulatory receptor CD226 in AML patients of different clinical statuses (including de novo AML, AML in non-remission (NR), and AML in complete remission (CR)). Our data demonstrated an imbalanced distribution of TIGIT and CD226 on γδ T cells with a decrease in CD226+ γδ T cells and an increase in TIGIT+ γδ T cells in de novo AML patients, while TIGIT−CD226+ γδ T cells were restored in AML patients who achieved CR after chemotherapy. Moreover, the patients who had higher TIGIT+CD226− γδ T cells showed lower overall survival rate for non-M3 AML, which may be considered a novel prognostic immune biomarker. In conclusion, our study reveals for the first time that imbalance in the TIGIT/CD226 axis might be related to different clinical outcomes for AML patients. Abbreviations: AML: acute myeloid leukemia; CR: complete remission; ICs: immune checkpoints; PD-1: programmed death-1; γδ T cells: gamma delta T cells; TCR: T cell receptor; MHC: major histocompatibility complex; TIGIT: T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain; NK: natural killer; PB: Peripheral blood; NR: non-remission; FAB: French-American-British; WHO: World Health Organization; HIs: healthy individuals; OS: overall survival

Initial absolute monocyte count as an immune biomarker for clinical response in acute myeloid leukemia with monocytic differentiation

BackgroundAbsolute monocyte count (AMC) correlates with survival outcomes in various hematologic malignancies. However, its role in myeloid malignancies including AML needs to be highlighted. So, this prospective cohort study aimed to assess the effect of AMC on the treatment outcome and survival in a 56 adult de novo AML patients with monocytic differentiation, admitted to the Clinical Hematology Unit, Internal Medicine Department, in a tertiary referral hospital in Egypt, from July 2016 to June 2019.ResultsThe initial AMC was measured either by manual differential or the hematology automatic analyzer Sysmex XN-2000 and patients were classified by using receiver operating characteristic curve into two groups monocytopenic (≤ 4 × 109/L) and non-monocytopenic (> 4 × 109/L) group; including 24 (42.9%) and 32 (57.1%) patients, respectively. After a median follow up period of 7.7 (range 0.5–33.2) months, the monocytopenic group was associated with a significantly higher CR rate (P = 0.019), with a lower death as well as relapse and early relapse rates (P = 0.011, 0.033, and 0.002, respectively). Moreover, low initial AMC along with intensive induction were independently associated with complete response to induction chemotherapy with HR, 5.04 [1.37–18.58], P = 0.015, and 5.67 [1.48–21.71], P = 0.011, respectively by using the multivariate logistic regression model. Regarding survival, the monocytopenic group was associated with a better 3-year disease-free survival rate (P = 0.011) in univariate Cox regression only but did not reach significance in the multivariate model and did not affect the overall survival as well.ConclusionInitial AMC was found to be an independent prognostic immune biomarker for treatment response in AML patients with monocytic differentiation. However, it did not appear as an independent predictor of survival in a multivariate analysis.Graphical abstract