Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

Background. The 5-year overall survival rate of ovarian cancer (OC) patients is less than 40%. Hypoxia promotes the proliferation of OC cells and leads to the decline of cell immunity. It is crucial to find potential predictors or risk model related to OC prognosis. This study aimed at establishing the hypoxia-associated gene signature to assess tumor immune microenvironment and predicting the prognosis of OC. Methods. The gene expression data of 378 OC patients and 370 OC patients were downloaded from datasets. The hypoxia risk model was constructed to reflect the immune microenvironment in OC and predict prognosis. Results. 8 genes (AKAP12, ALDOC, ANGPTL4, CITED2, ISG20, PPP1R15A, PRDX5, and TGFBI) were included in the hypoxic gene signature. Patients in the high hypoxia risk group showed worse survival. Hypoxia signature significantly related to clinical features and may serve as an independent prognostic factor for OC patients. 2 types of immune cells, plasmacytoid dendritic cell and regulatory T cell, showed a significant infiltration in the tissues of the high hypoxia risk group patients. Most of the immunosuppressive genes (such as ARG1, CD160, CD244, CXCL12, DNMT1, and HAVCR1) and immune checkpoints (such as CD80, CTLA4, and CD274) were upregulated in the high hypoxia risk group. Gene sets related to the high hypoxia risk group were associated with signaling pathways of cell cycle, MAPK, mTOR, PI3K-Akt, VEGF, and AMPK. Conclusion. The hypoxia risk model could serve as an independent prognostic indicator and reflect overall immune response intensity in the OC microenvironment.

The effect of hypoxia on PD-L1 expression in bladder cancer

Introduction Recent data has demonstrated that hypoxia drives an immunosuppressive tumour microenvironment (TME) via various mechanisms including hypoxia inducible factor (HIF)-dependent upregulation of programmed death ligand 1 (PD-L1). Both hypoxia and an immunosuppressive TME are targetable independent negative prognostic factors for bladder cancer. Therefore we sought to investigate whether hypoxia is associated with upregulation of PD-L1 in the disease. Materials and methods Three human muscle-invasive bladder cancer cell lines (T24, J82, UMUC3) were cultured in normoxia (20% oxygen) or hypoxia (1 and 0.1% oxygen) for 24 h. Differences in PD-L1 expression were measured using Western blotting, quantitative polymerase chain reaction (qPCR) and flow cytometry (≥3 independent experiments). Statistical tests performed were unpaired t tests and ANOVA. For in silico work an hypoxia signature was used to apply hypoxia scores to muscle-invasive bladder cancers from a clinical trial (BCON; n = 142) and TCGA (n = 404). Analyses were carried out using R and RStudio and statistical tests performed were linear models and one-way ANOVA. Results When T24 cells were seeded at < 70% confluence, there was decreased PD-L1 protein (p = 0.009) and mRNA (p < 0.001) expression after culture in 0.1% oxygen. PD-L1 protein expression decreased in both 0.1% oxygen and 1% oxygen in a panel of muscle-invasive bladder cancer cells: T24 (p = 0.009 and 0.001), J82 (p = 0.008 and 0.013) and UMUC3 (p = 0.003 and 0.289). Increasing seeding density decreased PD-L1 protein (p < 0.001) and mRNA (p = 0.001) expression in T24 cells grown in both 20 and 1% oxygen. Only when cells were 100% confluent, were PD-L1 protein and mRNA levels higher in 1% versus 20% oxygen (p = 0.056 and p = 0.037). In silico analyses showed a positive correlation between hypoxia signature scores and PD-L1 expression in both BCON (p = 0.003) and TCGA (p < 0.001) cohorts, and between hypoxia and IFNγ signature scores (p < 0.001 for both). Conclusion Tumour hypoxia correlates with increased PD-L1 expression in patient derived bladder cancer tumours. In vitro PD-L1 expression was affected by cell density and decreased PD-L1 expression was observed after culture in hypoxia in muscle-invasive bladder cancer cell lines. As cell density has such an important effect on PD-L1 expression, it should be considered when investigating PD-L1 expression in vitro.

Hypoxia signature: A useful tool for hypoxia recognition among aircrew

Introduction: Hypoxia, often referred to as “silent killer,” a common aeromedical stressor in aviation, may have catastrophic events in-flight unless recognized well in time. On exposure to hypoxia, an individual manifests a specific spectrum of symptoms referred to as “hypoxia signature.” The present study was conducted to assess the manifestation of “hypoxia signature” on repeated exposure to simulated hypobaric hypoxia for its potential usage as a tool for hypoxia recognition. Material and Methods: Twenty-two healthy adult volunteers were subjected to a simulated altitude of 22,000 feet for a duration of 5 min in the hypobaric altitude chamber. The symptoms experienced by the participants at the said altitude were recorded using a questionnaire. The heart rate (HR) and oxygen saturation (SpO2) were recorded during the exposure. The hypoxia exposure was repeated two more times with a minimum interval of 3 weeks between each. Paired t-test was used to compare the mean values of physiological parameters (HR and SpO2) between ground level and 22000 feet recorded in all the three exposures. The hypoxia symptoms and their severity reported during the exposures were compared with those of recalled symptoms (reported after 3 weeks of exposure) using McNemar test and Wilcoxon Signed Rank test, respectively. Results: Paired t-test revealed a statistically significant increase in HR and fall in SpO2 with rise in altitude from ground level to 22000 feet. The three most common symptoms consistently observed were lightheadedness, thinking slow, and warm feeling. The common hypoxic symptoms and their severity scores reported at 22,000 feet compared with recalled counterpart during subsequent exposures did not reveal any significant differences (P > 0.05). Conclusion: There was a high degree of similarity in the frequency and severity score of symptoms between acute exposure to hypobaric hypoxia and recall indicating evidence of repeatability of symptoms across the three sessions of hypoxia exposure within the individuals. This brings out the usefulness of “hypoxia signature” as a tool for hypoxia recognition and its application in hypoxia indoctrination and training for aircrew.

CSIG-12. THE ROLE OF HYPOXIA SIGNALING AS AN ONCOGENIC EFFECTOR IN ACVR1-MUTANT DIFFUSE INTRINSIC PONTINE GLIOMA

Diffuse intrinsic pontine gliomas (DIPG) are aggressive and highly treatment resistant pediatric tumors of the brainstem. The majority of the DIPG tumors (60-80%) carry somatic histone H3 mutations resulting in a global reduction of H3K27 trimethylation and subsequently a unique epigenetic landscape. Moreover, activating mutations in ACVR1 – the gene encoding for the BMP receptor ALK2 – were recently described in a large subset of DIPGs, suggestive of an oncogenic role of signaling from this receptor. Potential mechanisms of ACVR1-driven oncogenesis, however, remain poorly understood. Similar and overlapping ACVR1 mutations have been described in the rare disorder Fibrodysplasia Ossificans Progressiva (FOP), and evidence from FOP models have suggested several links between hypoxia signaling, BMP signaling, and FOP pathogenesis. We used cultured DIPG cells and adult glioma cells respectively to test the activity of the hypoxia pathway using a hypoxia-responsive elements (HRE)-luciferase reporter assay. Intriguingly, DIPG but not glioma cells overexpressing a mutant ACVR1 construct significantly elevated hypoxia signaling at hypoxia. BMP ligand stimulation resulted in a dose-dependent increase of hypoxia signaling in DIPG cells. By querying clinical gene expression data, we found elevated hypoxia signature scores in pediatric gliomas with mutant ACVR1 as compared to those with wildtype ACVR1. Finally, ACVR1 mutations frequently co-occur with Histone 3.3 and 3.1 mutations, and the hypoxia signature score was significantly higher than baseline only in tumors also harboring these Histone 3.3 or 3.1 mutations. Together, these data support the notion that hypoxia signaling is elevated downstream of ACVR1 specifically in pediatric gliomas and prompts for evaluation of hypoxia signaling as potential therapeutical target in DIPG.

A Hypoxia Signature for Predicting Prognosis and Tumor Immune Microenvironment in Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare malignancy with dismal prognosis. Hypoxia is one of characteristics of cancer leading to tumor progression. For ACC, however, no reliable prognostic signature on the basis of hypoxia genes has been built. Our study aimed to develop a hypoxia-associated gene signature in ACC. Data of ACC patients were obtained from TCGA and GEO databases. The genes included in hypoxia risk signature were identified using the Cox regression analysis as well as LASSO regression analysis. GSEA was applied to discover the enriched gene sets. To detect a possible connection between the gene signature and immune cells, the CIBERSORT technique was applied. In ACC, the hypoxia signature including three genes (CCNA2, COL5A1, and EFNA3) was built to predict prognosis and reflect the immune microenvironment. Patients with high-risk scores tended to have a poor prognosis. According to the multivariate regression analysis, the hypoxia signature could be served as an independent indicator in ACC patients. GSEA demonstrated that gene sets linked to cancer proliferation and cell cycle were differentially enriched in high-risk classes. Additionally, we found that PDL1 and CTLA4 expression were significantly lower in the high-risk group than in the low-risk group, and resting NK cells displayed a significant increase in the high-risk group. In summary, the hypoxia risk signature created in our study might predict prognosis and evaluate the tumor immune microenvironment for ACC.

Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer

ObjectivesThis study aimed to develop and validate a hypoxia signature for predicting survival outcomes in patients with bladder cancer.MethodsWe downloaded the RNA sequence and the clinicopathologic data of the patients with bladder cancer from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/repository?facetTab=files) and the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. Hypoxia genes were retrieved from the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Differentially expressed hypoxia-related genes were screened by univariate Cox regression analysis and Lasso regression analysis. Then, the selected genes constituted the hypoxia signature and were included in multivariate Cox regression to generate the risk scores. After that, we evaluate the predictive performance of this signature by multiple receiver operating characteristic (ROC) curves. The CIBERSORT tool was applied to investigate the relationship between the hypoxia signature and the immune cell infiltration, and the maftool was used to summarize and analyze the mutational data. Gene-set enrichment analysis (GSEA) was used to investigate the related signaling pathways of differentially expressed genes in both risk groups. Furthermore, we developed a model and presented it with a nomogram to predict survival outcomes in patients with bladder cancer.ResultsEight genes (AKAP12, ALDOB, CASP6, DTNA, HS3ST1, JUN, KDELR3, and STC1) were included in the hypoxia signature. The patients with higher risk scores showed worse overall survival time than the ones with lower risk scores in the training set (TCGA) and two external validation sets (GSE13507 and GSE32548). Immune infiltration analysis showed that two types of immune cells (M0 and M1 macrophages) had a significant infiltration in the high-risk group. Tumor mutation burden (TMB) analysis showed that the risk scores between the wild types and the mutation types of TP53, MUC16, RB1, and FGFR3 were significantly different. Gene-Set Enrichment Analysis (GSEA) showed that immune or cancer-associated pathways belonged to the high-risk groups and metabolism-related signal pathways were enriched into the low-risk group. Finally, we constructed a predictive model with risk score, age, and stage and validated its performance in GEO datasets.ConclusionWe successfully constructed and validated a novel hypoxia signature in bladder cancer, which could accurately predict patients’ prognosis.

An Eight-Gene Hypoxia Signature Predicts Survival in Pancreatic Cancer and Is Associated With an Immunosuppressed Tumor Microenvironment

Intratumoral hypoxia is a widely established element of the pancreatic tumor microenvironment (TME) promoting immune escape, tumor invasion, and progression, while contributing to treatment resistance and poor survival. Despite this critical role, hypoxia is underrepresented in molecular signatures of pancreatic ductal adenocarcinoma (PDA) and concurrent investigations into the hypoxia-immune status are lacking. In this work a literature-based approach was applied to derive an eight-gene hypoxia signature that was validated in fourteen cancer cell lines and in a cohort of PDA. The eight-gene hypoxia signature was significantly associated with overall survival in two distinct PDA datasets and showed independent prognostic value in multivariate analysis. Comparative analysis of tumors according to their hypoxia score (high versus low) determined that tumors with high hypoxia were significantly less enriched in cytotoxic T-cells, and cytolytic activity. In addition, they had lower expression of cytokines and tumor inflammatory markers, pointing to the signature’s ability to discern an immune “cold”, hypoxic TME. Combining the signature with an immune metric highlighted a worse survival probability in patients with high hypoxia and low immune reactivity, indicating that this approach could further refine survival estimates. Hypoxia as determined by our signature, was significantly associated with certain immune checkpoint inhibitors (ICI) biomarkers, suggesting that the signature reflects an aspect of the TME that is worth pursuing in future clinical trials. This is the first work of its kind in PDA, and our findings on the hypoxia-immune tumor contexture are not only relevant for ICI but could also guide combinatorial hypoxia-mediated therapeutic strategies in this cancer type.

A miRNA signature predicts benefit from addition of hypoxia-modifying therapy to radiation treatment in invasive sbladder cancer

Background miRNAs are promising biomarkers in oncology as their small size makes them less susceptible to degradation than mRNA in FFPE tissue. We aimed to derive a hypoxia-associated miRNA signature for bladder cancer. Methods Taqman miRNA array cards identified miRNA seed genes induced under hypoxia in bladder cancer cell lines. A signature was derived using feature selection methods in a TCGA BLCA training data set. miRNA expression data were generated for 190 tumours from the BCON Phase 3 trial and used for independent validation. Results A 14-miRNA hypoxia signature was derived, which was prognostic for poorer overall survival in the TCGA BLCA cohort (n = 403, p = 0.001). Univariable analysis showed that the miRNA signature predicted an overall survival benefit from having carbogen–nicotinamide with radiotherapy (HR = 0.30, 95% CI 0.094–0.95, p = 0.030) and performed similarly to a 24-gene mRNA signature (HR = 0.47, 95% CI 0.24–0.92, p = 0.025). Combining the signatures improved performance (HR = 0.26, 95% CI 0.08–0.82, p = 0.014) with borderline significance for an interaction test (p = 0.065). The interaction test was significant for local relapse-free survival LRFS (p = 0.033). Conclusion A 14-miRNA hypoxia signature can be used with an mRNA hypoxia signature to identify bladder cancer patients benefitting most from having carbogen and nicotinamide with radiotherapy.

Determination of hypoxia signature to predict prognosis and the tumor immune microenvironment in melanoma

The hypoxia score is identified as an independent prognostic factor and a predictive biomarker of the immune microenvironment for melanoma.