Relation of a hypoxia metagene derived from head and neck cancer to prognosis of multiple cancers

Transcriptomic and epigenetic landscape of nimorazole-enhanced radiochemotherapy in head and neck cancer

BACKGROUND

Hypoxia remains a challenge for the therapeutic management of head and neck squamous cell carcinoma (HNSCC). The combination of radiotherapy with nimorazole has shown treatment benefit in HNSCC, but the precise underlying molecular mechanisms remain unclear.

PURPOSE

To assess and to characterize the transcriptomic/epigenetic landscape of HNSCC tumor models showing differential therapeutic response to fractionated radiochemotherapy (RCTx) combined with nimorazole.

MATERIALS/METHODS

Bulk RNA-sequencing and DNA methylation experiments were conducted using untreated and treated HNSCC xenografts after 10 fractions of RCTx with and without nimorazole. These tumor models (FaDu, SAS, Cal33, SAT and UT-SCC-45) previously showed a heterogeneous response to RCTx with nimorazole. The prognostic impact of candidate genes was assessed using clinical and gene expression data from HNSCC patients treated with primary RCTx within the DKTK-ROG.

RESULTS

Nimorazole responder and non-responder tumor models showed no differences in hypoxia gene signatures However, non-responder models showed upregulation of metabolic pathways. From that, a subset of 15 differentially expressed genes stratified HNSCC patients into low and high-risk groups with distinct outcome.

CONCLUSION

In the present study, we found that nimorazole non-responder models were characterized by upregulation of genes involved in Retinol metabolism and xenobiotic metabolic process pathways, which might contribute to identify mechanisms of resistance to nitroimidazole compounds and potentially expand the repertoire of therapeutic options to treat HNSCC.

Exploring the Correlation Between Hypoxia, HIF1A Variants, and Breast Cancer in Different Ethnicities, and Bangladeshi Women: Through ELISA and Integrative Multi-Omics Analysis

Background

Hypoxia, a condition where there is a lack of oxygen, is known to play a role in cancer progression.

Objective

This study investigates the correlation between HIF1A gene-altered expression and hypoxia in Bangladeshi breast cancer (BC) cases and TCGA_BC datasets.

Design

This case-control study compares BC cases to healthy controls to understand the relationship between gene changes and cancer.

Method

This study used advanced analysis methods to examine the transcriptional landscape of BC, and quantitatively assessed its correlation using integrated multi-omics analysis.

Results

In Bangladeshi BC cases, the T allele of HIF1A rs1154946 correlates notably (P-value < .001) with BC incidence. ELISA results confirmed a significant association (P-value < .005) between elevated HIF1A expression and BC-related hypoxia. Bioinformatics eQTL analysis validated the correlation between increased HIF1A expression and rs11549465 T allele (P-value < .01). Structural analyses suggested that rs11549465 (P582S) mutation may decrease protein stability (ΔΔG-value: -1.24 kcal/mole), potentially affecting HIF1A function. HIF1A enrichment analysis in BC underscores strong associations with oxygen levels, hypoxia, metabolic processes, apoptosis, and programed cell death (P-value < .001). Transcriptomic data demonstrated a robust correlation (P-value < .0001) between HIF1A expression and copy-number alterations, mutations, and abnormal methylation. Altered HIF1A expression showed strong negative correlations (P-value < .00001) with methylation and the expression of the ER (ESR1), in Whites. Survival analysis revealed marked differences in overall survival linked to high and low HIF1A expression (P-value < .00001). Furthermore, HIF1A expression significantly correlated (P-value < .000001) with hypoxia, TMB, MSI, and immune infiltration by CD8+ T cells, neutrophils, dendritic, and macrophages, providing deeper insights into the BC microenvironment.

Conclusion

Thus, the HIF1A gene could serve as a promising biomarker for breast cancer progression, control, and survival across ethnicities, emphasizing its role in disease development and regulation.

A comprehensive landscape analysis of autophagy in cancer development and drug resistance

Background

Autophagy plays important roles in cancer progression and therapeutic resistance, and the autophagy underlying the tumor pathogenesis and further mechanisms of chemoresistance emergence remains unknown.

Methods

In this study, via the single-sample gene set enrichment analysis (ssGSEA) method, an autophagy 45-gene list was identified to evaluate samples' autophagy activity, verified through six GEO datasets with a confirmed autophagy phenotype. It was further utilized to distinguish tumors into autophagy score-high and score-low subtypes, and analyze their transcriptome landscapes, including survival analysis, correlation analysis of autophagy- and resistance-related genes, biological functional enrichment, and immune- and hypoxia-related and genomic heterogeneity comparison, in TCGA pan-cancer datasets. Furthermore, we performed an analysis of autophagy status in breast cancer chemoresistance combined with multiple GEO datasets and in vitro experiments to validate the mechanisms of potential anticancer drugs for reversing chemoresistance, including CCK-8 cell viability assays, RT-qPCR, and immunofluorescence.

Results

The 45-gene list was used to identify autophagy score-high and score-low subtypes and further analyze their multi-dimensional features. We demonstrated that cancer autophagy status correlated with significantly different prognoses, molecular alterations, biological process activations, immunocyte infiltrations, hypoxia statuses, and specific mutational processes. The autophagy score-low subtype displayed a more favorable prognosis compared with the score-high subtype, associated with their immune-activated features, manifested as high immunocyte infiltration, including high CD8+T, Tfh, Treg, NK cells, and tumor-associated macrophages M1/M2. The autophagy score-low subtype also showed a high hypoxia score, and hypoxic tumors showed a significantly differential prognosis in different autophagy statuses. Therefore, "double-edged" cell fates triggered by autophagy might be closely correlated with the immune microenvironment and hypoxia induction. Results demonstrated that dysregulated autophagy was involved in many cancers and their therapeutic resistance and that the autophagy was induced by the resistance-reversing drug response, in five breast cancer GEO datasets and validated by in vitro experiments. In vitro, dihydroartemisinin and artesunate could reverse breast cancer doxorubicin resistance, through inducing autophagy via upregulating LC3B and ATG7.

Conclusion

Our study provided a comprehensive landscape of the autophagy-related molecular and tumor microenvironment patterns for cancer progression and resistance, and highlighted the promising potential of drug-induced autophagy in the activation of drug sensitivity and reversal of resistance.

Clinical relevance and therapeutic predictive ability of hypoxia biomarkers in head and neck cancer tumour models

Tumour hypoxia promotes poor patient outcomes, with particularly strong evidence for head and neck squamous cell carcinoma (HNSCC). To effectively target hypoxia, therapies require selection biomarkers and preclinical models that can accurately model tumour hypoxia. We established 20 patient-derived xenograft (PDX) and cell line-derived xenograft (CDX) models of HNSCC that we characterised for their fidelity to represent clinical HNSCC in gene expression, hypoxia status and proliferation and that were evaluated for their sensitivity to hypoxia-activated prodrugs (HAPs). PDX models showed greater fidelity in gene expression to clinical HNSCC than cell lines, as did CDX models relative to their paired cell lines. PDX models were significantly more hypoxic than CDX models, as assessed by hypoxia gene signatures and pimonidazole immunohistochemistry, and showed similar hypoxia gene expression to clinical HNSCC tumours. Hypoxia or proliferation status alone could not determine HAP sensitivity across our 20 HNSCC and two non-HNSCC tumour models by either tumour growth inhibition or killing of hypoxia cells in an ex vivo clonogenic assay. In summary, our tumour models provide clinically relevant HNSCC models that are suitable for evaluating hypoxia-targeting therapies; however, additional biomarkers to hypoxia are required to accurately predict drug sensitivity.

MCTP1 increases the malignancy of androgen-deprived prostate cancer cells by inducing neuroendocrine differentiation and EMT

Neuroendocrine prostate cancer (PCa) (NEPC), an aggressive subtype that is associated with poor prognosis, may arise after androgen deprivation therapy (ADT). We investigated the molecular mechanisms by which ADT induces neuroendocrine differentiation in advanced PCa. We found that transmembrane protein 1 (MCTP1), which has putative Ca2+ sensing function and multiple Ca2+-binding C2 domains, was abundant in samples from patients with advanced PCa. MCTP1 was associated with the expression of the EMT-associated transcription factors ZBTB46, FOXA2, and HIF1A. The increased abundance of MCTP1 promoted PC3 prostate cancer cell migration and neuroendocrine differentiation and was associated with SNAI1-dependent EMT in C4-2 PCa cells after ADT. ZBTB46 interacted with FOXA2 and HIF1A and increased the abundance of MCTP1 in a hypoxia-dependent manner. MCTP1 stimulated Ca2+ signaling and AKT activation to promote EMT and neuroendocrine differentiation by increasing the SNAI1-dependent expression of EMT and neuroendocrine markers, effects that were blocked by knockdown of MCTP1. These data suggest an oncogenic role for MCTP1 in the maintenance of a rare and aggressive prostate cancer subtype through its response to Ca2+ and suggest its potential as a therapeutic target.

HIF1A-dependent overexpression of MTFP1 promotes lung squamous cell carcinoma development by activating the glycolysis pathway

Introduction

Mitochondrial fission process 1 (MTFP1) is an inner mitochondrial membrane (IMM) protein implicated in the development and progression of various tumors, particularly lung squamous cell carcinoma (LUSC). This study aims to provide a more theoretical basis for the treatment of LUSC.

Methods

Through bioinformatics analysis, MTFP1 was identified as a novel target gene of HIF1A. MTFP1 expression in LUSC was examined using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Proteomics Data Commons (PDC) databases. The Kaplan-Meier plotter (KM plotter) database was utilized to evaluate its correlation with patient survival. Western blot and chromatin immunoprecipitation (ChIP) assays were employed to confirm the regulatory relationship between MTFP1 and HIF1A. Additionally, cell proliferation, colony formation, and migration assays were conducted to investigate the mechanism by which MTFP1 enhances LUSC cell proliferation and metastasis.

Results

Our findings revealed that MTFP1 overexpression correlated with poor prognosis in LUSC patients(P < 0.05). Moreover, MTFP1 was closely associated with hypoxia and glycolysis in LUSC (R = 0.203; P < 0.001, R = 0.391; P < 0.001). HIF1A was identified as a positive regulator of MTFP1. Functional enrichment analysis demonstrated that MTFP1 played a role in controlling LUSC cell proliferation. Cell proliferation, colony formation, and migration assays indicated that MTFP1 promoted LUSC cell proliferation and metastasis by activating the glycolytic pathway (P < 0.05).

Conclusions

This study establishes MTFP1 as a novel HIF1A target gene that promotes LUSC growth by activating the glycolytic pathway. Investigating MTFP1 may contribute to the development of effective therapies for LUSC patients, particularly those lacking targeted oncogene therapies.

An Immune Gene Expression Risk Score for Distant Metastases after Radiotherapy for Cervical Cancer

PURPOSE

To develop an immune-based gene expression risk score to identify patients with cervical cancer at increased risk of distant metastases (DM).

EXPERIMENTAL DESIGN

Tumor biopsies were obtained from 81 patients prior to chemoradiotherapy. Whole-transcriptome RNA sequencing was performed (Illumina NextSeq500). Beginning with 4,723 immune-related genes, a 55-gene risk score for DM was derived using Cox modeling and principal component analysis. It was validated in independent cohorts of 274 patients treated at the Norwegian Radium Hospital (NRH) and 206 patients from The Cancer Genome Atlas (TCGA).

RESULTS

The risk score was predictive of DM (HR, 2.7; P < 0.0001) and lower cause-specific survival (CSS) by univariate analysis (HR, 2.0; P = 0.0003) and multivariate analysis adjusted for clinical factors (DM HR, 3.0; P < 0.0001; CSS HR, 2.2; P = 0.0004). The risk score predicted DM (HR, 1.4; P = 0.05) and CSS (HR, 1.48; P = 0.013) in the NRH cohort and CSS (HR, 1.4; P = 0.03) in TCGA cohort. Higher risk scores were associated with lower CIBERSORT estimates of tumor-infiltrating immune cells, including CD8 T cells and M1 and M2 macrophages (all P < 0.001). Higher risk scores were associated with lower expression (all P < 0.001) of important chemokines (CXCL12, CXCR4), IFN-regulated genes (IRF1, STAT1, IDO1), and immune checkpoint regulators (PD-1, PD-L1, CTLA-4).

CONCLUSIONS

The immune metastatic risk score addresses important challenges in the treatment of cervical cancer-identifying patients at high risk of DM after radiotherapy. The findings of this study indicate that high tumor mutational burden and a "cold," immune-excluded tumor microenvironment influence distant metastatic recurrence. Further validation of the risk score is needed.

Acetyl-CoA synthetase 2 contributes to a better prognosis for liver cancer by switching acetate-glucose metabolism

Acetyl-CoA synthetase 2 (ACSS2)-dependent acetate usage has generally been associated with tumorigenesis and increased malignancy in cancers under nutrient-depleted conditions. However, the nutrient usage and metabolic characteristics of the liver differ from those of other organs; therefore, the mechanism of ACSS2-mediated acetate metabolism may also differ in liver cancer. To elucidate the underlying mechanisms of ACSS2 in liver cancer and acetate metabolism, the relationships between patient acetate uptake and metabolic characteristics and between ACSS2 and tumor malignancies were comprehensively studied in vitro, in vivo and in humans. Clinically, we initially found that ACSS2 expression was decreased in liver cancer patients. Moreover, PET-CT imaging confirmed that lower-grade cancer cells take up more 11C-acetate but less 18F-fluorodeoxyglucose (18F-FDG); however, this trend was reversed in higher-grade cancer. Among liver cancer cells, those with high ACSS2 expression avidly absorbed acetate even in a glucose-sufficient environment, whereas those with low ACSS2 expression did not, thereby showing correlations with their respective ACSS2 expression. Metabolomic isotope tracing in vitro and in vivo revealed greater acetate incorporation, greater lipid anabolic metabolism, and less malignancy in high-ACSS2 tumors. Notably, ACSS2 downregulation in liver cancer cells was associated with increased tumor occurrence in vivo. In human patient cohorts, patients in the low-ACSS2 subgroup exhibited reduced anabolism, increased glycolysis/hypoxia, and poorer prognosis. We demonstrated that acetate uptake by ACSS2 in liver cancer is independent of glucose depletion and contributes to lipid anabolic metabolism and reduced malignancy, thereby leading to a better prognosis for liver cancer patients.

Inhibition of CD38 enzymatic activity enhances CAR-T cell immune-therapeutic efficacy by repressing glycolytic metabolism

Chimeric antigen receptor (CAR)-T therapy has shown superior efficacy against hematopoietic malignancies. However, many patients failed to achieve sustainable tumor control partially due to CAR-T cell exhaustion and limited persistence. In this study, by performing single-cell multi-omics data analysis on patient-derived CAR-T cells, we identify CD38 as a potential hallmark of exhausted CAR-T cells, which is positively correlated with exhaustion-related transcription factors and further confirmed with in vitro exhaustion models. Moreover, inhibiting CD38 activity reverses tonic signaling- or tumor antigen-induced exhaustion independent of single-chain variable fragment design or costimulatory domain, resulting in improved CAR-T cell cytotoxicity and antitumor response. Mechanistically, CD38 inhibition synergizes the downregulation of CD38-cADPR -Ca2+ signaling and activation of the CD38-NAD+-SIRT1 axis to suppress glycolysis. Collectively, our findings shed light on the role of CD38 in CAR-T cell exhaustion and suggest potential clinical applications of CD38 inhibition in enhancing the efficacy and persistence of CAR-T cell therapy.

TFRC, associated with hypoxia and immune, is a prognostic factor and potential therapeutic target for bladder cancer

BACKGROUND

Bladder cancer is a common malignancy of the urinary system, and the survival rate and recurrence rate of patients with muscular aggressive (MIBC) bladder cancer are not ideal. Hypoxia is a pathological process in which cells acquire special characteristics to adapt to anoxic environment, which can directly affect the proliferation, invasion and immune response of bladder cancer cells. Understanding the exact effects of hypoxia and immune-related genes in BLCA is helpful for early assessment of the prognosis of BLCA. However, the prognostic model of BLCA based on hypoxia and immune-related genes has not been reported.

PURPOSE

Hypoxia and immune cell have important role in the prognosis of bladder cancer (BLCA). The aim of this study was to investigate whether hypoxia and immune related genes could be a novel tools to predict the overall survival and immunotherapy of BLCA patients.

METHODS

First, we downloaded transcriptomic data and clinical information of BLCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A combined hypoxia and immune signature was then constructed on the basis of the training cohort via least absolute shrinkage and selection operator (LASSO) analysis and validated in test cohort. Afterwards, Kaplan-Meier curves, univariate and multivariate Cox and subgroup analysis were employed to assess the accuracy of our signature. Immune cell infiltration, checkpoint and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were used to investigate the immune environment and immunotherapy of BLCA patients. Furthermore, we confirmed the role of TFRC in bladder cancer cell lines T24 and UMUC-3 through cell experiments.

RESULTS

A combined hypoxia and immune signature containing 8 genes were successfully established. High-risk group in both training and test cohorts had significantly poorer OS than low-risk group. Univariate and multivariate Cox analysis indicated our signature could be regarded as an independent prognostic factor. Different checkpoint was differently expressed between two groups, including CTLA4, HAVCR2, LAG3, PD-L1 and PDCD1. TIDE analysis indicated high-risk patients had poor response to immunotherapy and easier to have immune escape. The drug sensitivity analysis showed that high-risk group patients were more potentially sensitive to many drugs. Meanwhile, TFRC could inhibit the proliferation and invasion ability of T24 and UMUC-3 cells.

CONCLUSION

A combined hypoxia and immune-related gene could be a novel predictive model for OS and immunotherapy estimation of BLCA patients and TFRC could be used as a potential therapeutic target in the future.

Identification of Hypoxia Prognostic Signature in Glioblastoma Multiforme Based on Bulk and Single-Cell RNA-Seq

Glioblastoma (GBM) represents a profoundly aggressive and heterogeneous brain neoplasm linked to a bleak prognosis. Hypoxia, a common feature in GBM, has been linked to tumor progression and therapy resistance. In this study, we aimed to identify hypoxia-related differentially expressed genes (DEGs) and construct a prognostic signature for GBM patients using multi-omics analysis. Patient cohorts were collected from publicly available databases, including the Gene Expression Omnibus (GEO), the Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas-Glioblastoma Multiforme (TCGA-GBM), to facilitate a comprehensive analysis. Hypoxia-related genes (HRGs) were obtained from the Molecular Signatures Database (MSigDB). Differential expression analysis revealed 41 hypoxia-related DEGs in GBM patients. A consensus clustering approach, utilizing these DEGs' expression patterns, identified four distinct clusters, with cluster 1 showing significantly better overall survival. Machine learning techniques, including univariate Cox regression and LASSO regression, delineated a prognostic signature comprising six genes (ANXA1, CALD1, CP, IGFBP2, IGFBP5, and LOX). Multivariate Cox regression analysis substantiated the prognostic significance of a set of three optimal signature genes (CP, IGFBP2, and LOX). Using the hypoxia-related prognostic signature, patients were classified into high- and low-risk categories. Survival analysis demonstrated that the high-risk group exhibited inferior overall survival rates in comparison to the low-risk group. The prognostic signature showed good predictive performance, as indicated by the area under the curve (AUC) values for one-, three-, and five-year overall survival. Furthermore, functional enrichment analysis of the DEGs identified biological processes and pathways associated with hypoxia, providing insights into the underlying mechanisms of GBM. Delving into the tumor immune microenvironment, our analysis revealed correlations relating the hypoxia-related prognostic signature to the infiltration of immune cells in GBM. Overall, our study highlights the potential of a hypoxia-related prognostic signature as a valuable resource for forecasting the survival outcome of GBM patients. The multi-omics approach integrating bulk sequencing, single-cell analysis, and immune microenvironment assessment enhances our understanding of the intricate biology characterizing GBM, thereby potentially informing the tailored design of therapeutic interventions.

Is there a role for [18F]-FMISO PET to guide dose adaptive radiotherapy in head and neck cancer? A review of the literature

Purpose

Hypoxia is a major cause of radioresistance in head and neck cancer (HNC), resulting in treatment failure and disease recurrence. 18F-fluoromisonidazole [18F]FMISO PET has been proposed as a means of localising intratumoural hypoxia in HNC so that radiotherapy can be specifically escalated in hypoxic regions. This concept may not be deliverable in routine clinical practice, however, given that [18F]FMISO PET is costly, time consuming and difficult to access. The aim of this review was to summarise clinical studies involving [18F]FMISO PET to ascertain whether it can be used to guide radiotherapy treatment in HNC.

Methods

A comprehensive literature search was conducted on PubMed and Web of Science databases. Studies investigating [18F]FMISO PET in newly diagnosed HNC patients were considered eligible for review.

Results

We found the following important results from our literature review: 1)Studies have focussed on comparing [18F]FMISO PET to other hypoxia biomarkers, but currently there is no evidence of a strong correlation between [18F]FMISO and these biomarkers.2)The results of [18F]FMISO PET imaging are not necessarily repeatable, and the location of uptake may vary during treatment.3)Tumour recurrences do not always occur within the pretreatment hypoxic volume on [18F]FMISO PET.4)Dose modification studies using [18F]FMISO PET are in a pilot phase and so far, none have demonstrated the efficacy of radiotherapy dose painting according to [18F]FMISO uptake on PET.

Conclusions

Our results suggest it is unlikely [18F]FMISO PET will be suitable for radiotherapy dose adaptation in HNC in a routine clinical setting. Part of the problem is that hypoxia is a dynamic phenomenon, and thus difficult to delineate on a single scan. Currently, it is anticipated that [18F]FMISO PET will remain useful within the research setting only.

A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer

Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which are qualitative and do not account for noncancerous elements within the tumor microenvironment. Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts, including the Prostate, Lung, Colorectal, and Ovarian Cancer trial, Cancer Prevention Study-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists in predicting survival outcomes, independent of tumor-node-metastasis stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve patient prognosis.

Identification of Proteome-Based Immune Subtypes of Early Hepatocellular Carcinoma and Analysis of Potential Metabolic Drivers

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, ranking fourth in frequency. The relationship between metabolic reprogramming and immune infiltration has been identified as having a crucial impact on HCC progression. However, a deeper understanding of the interplay between the immune system and metabolism in the HCC microenvironment is required. In this study, we used a proteomic dataset to identify three immune subtypes (IM1-IM3) in HCC, each of which has distinctive clinical, immune, and metabolic characteristics. Among these subtypes, IM3 was found to have the poorest prognosis, with the highest levels of immune infiltration and T-cell exhaustion. Furthermore, IM3 showed elevated glycolysis and reduced bile acid metabolism, which was strongly correlated with CD8 T cell exhaustion and regulatory T cell accumulation. Our study presents the proteomic immune stratification of HCC, revealing the possible link between immune cells and reprogramming of HCC glycolysis and bile acid metabolism, which may be a viable therapeutic strategy to improve HCC immunotherapy.

Genomic characterization of IDH-mutant astrocytoma progression to grade 4 in the treatment setting

As the progression of low-grade diffuse astrocytomas into grade 4 tumors significantly impacts patient prognosis, a better understanding of this process is of paramount importance for improved patient care. In this project, we analyzed matched IDH-mutant astrocytomas before and after progression to grade 4 from six patients (discovery cohort) with genome-wide sequencing, 21 additional patients with targeted sequencing, and 33 patients from Glioma Longitudinal AnalySiS cohort for validation. The Cancer Genome Atlas data from 595 diffuse gliomas provided supportive information. All patients in our discovery cohort received radiation, all but one underwent chemotherapy, and no patient received temozolomide (TMZ) before progression to grade 4 disease. One case in the discovery cohort exhibited a hypermutation signature associated with the inactivation of the MSH2 and DNMT3A genes. In other patients, the number of chromosomal rearrangements and deletions increased in grade 4 tumors. The cell cycle checkpoint gene CDKN2A, or less frequently RB1, was most commonly inactivated after receiving both chemo- and radiotherapy when compared to other treatment groups. Concomitant activating PDGFRA/MET alterations were detected in tumors that acquired a homozygous CDKN2A deletion. NRG3 gene was significantly downregulated and recurrently altered in progressed tumors. Its decreased expression was associated with poorer overall survival in both univariate and multivariate analysis. We also detected progression-related alterations in RAD51B and other DNA repair pathway genes associated with the promotion of error-prone DNA repair, potentially facilitating tumor progression. In our retrospective analysis of patient treatment and survival timelines (n = 75), the combination of postoperative radiation and chemotherapy (mainly TMZ) outperformed radiation, especially in the grade 3 tumor cohort, in which it was typically given after primary surgery. Our results provide further insight into the contribution of treatment and genetic alterations in cell cycle, growth factor signaling, and DNA repair-related genes to tumor evolution and progression.

KEAP1/NFE2L2 Pathway Signature Outperforms KEAP1/NFE2L2 Mutation Status and Reveals Alternative Pathway-Activating Mutations in NSCLC

INTRODUCTION

Activation of the antioxidant KEAP1/NFE2L2 (NRF2) pathway leads to increased glutamine dependence and an aggressive phenotype in NSCLC. Because this pathway has been explored as a clinical target, we developed a transcriptomic signature for identifying KEAP1/NFE2L2-activated tumors.

METHODS

A total of 971 NSCLC samples were used to train an expression signature (K1N2-score) to predict KEAP1/NFE2L2 mutations. There were 348 in-house NSCLCs that were analyzed using a NanoString expression panel for validation.

RESULTS

The 46-gene K1N2 score robustly predicted KEAP1/NFE2L2 mutations in the validation set irrespective of histology and mutation (area under the curve: 89.5, sensitivity: 90.2%), suggesting that approximately 90% of KEAP1/NFE2L2 mutations are pathway-activating. The K1N2-score outperformed KEAP1/NFE2L2 mutational status when predicting patient survival (score p = 0.047; mutation p = 0.215). In K1N2 score-positive but KEAP1/NFE2L2 wild-type samples, enrichment testing identified SMARCA4/BRG1 and CUL3 mutations as mimics of KEAP1/NFE2L2 mutations.

CONCLUSIONS

The K1N2-score identified KEAP1/NFE2L2-activated NSCLC by robustly detecting KEAP1/NFE2L2mut cases and discovering alternative genomic activators. It is a potential means for selecting patients with a constitutively active KEAP1/NFE2L2 pathway.

Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor with different genetic and molecular alterations. Schemes for ccRCC classification system based on multiomics are urgent, to promote further biological insights. Two hundred and fifty-five ccRCC patients with paired data of clinical information, transcriptome expression profiles, copy number alterations, DNA methylation, and somatic mutations were collected for identification. Bioinformatic analyses were performed based on our team's recently developed R package "MOVICS." With 10 state-of-the-art algorithms, we identified the multiomics subtypes (MoSs) for ccRCC patients. MoS1 is an immune exhausted subtype, presented the poorest prognosis, and might be caused by an exhausted immune microenvironment, activated hypoxia features, but can benefit from PI3K/AKT inhibitors. MoS2 is an immune "cold" subtype, which represented more mutation of VHL and PBRM1, favorable prognosis, and is more suitable for sunitinib therapy. MoS3 is the immune "hot" subtype, and can benefit from the anti-PD-1 immunotherapy. We successfully verified the different molecular features of the three MoSs in external cohorts GSE22541, GSE40435, and GSE53573. Patients that received Nivolumab therapy helped us to confirm that MoS3 is suitable for anti-PD-1 therapy. E-MTAB-3267 cohort also supported the fact that MoS2 patients can respond more to sunitinib treatment. We also confirm that SETD2 is a tumor suppressor in ccRCC, along with the decreased SETD2 protein level in advanced tumor stage, and knock-down of SETD2 leads to the promotion of cell proliferation, migration, and invasion. In summary, we provide novel insights into ccRCC molecular subtypes based on robust clustering algorithms via multiomics data, and encourage future precise treatment of ccRCC patients.

Clinically impactful metabolic subtypes of pancreatic ductal adenocarcinoma (PDAC)

Background: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a diverse tumor microenvironment. The heterogeneous cellular composition of PDAC makes it challenging to study molecular features of tumor cells using extracts from bulk tumor. The metabolic features in tumor cells from clinical samples are poorly understood, and their impact on clinical outcomes are unknown. Our objective was to identify the metabolic features in the tumor compartment that are most clinically impactful. Methods: A computational deconvolution approach using the DeMixT algorithm was applied to bulk RNASeq data from The Cancer Genome Atlas to determine the proportion of each gene's expression that was attributable to the tumor compartment. A machine learning algorithm designed to identify features most closely associated with survival outcomes was used to identify the most clinically impactful metabolic genes. Results: Two metabolic subtypes (M1 and M2) were identified, based on the pattern of expression of the 26 most important metabolic genes. The M2 phenotype had a significantly worse survival, which was replicated in three external PDAC cohorts. This PDAC subtype was characterized by net glycogen catabolism, accelerated glycolysis, and increased proliferation and cellular migration. Single cell data demonstrated substantial intercellular heterogeneity in the metabolic features that typified this aggressive phenotype. Conclusion: By focusing on features within the tumor compartment, two novel and clinically impactful metabolic subtypes of PDAC were identified. Our study emphasizes the challenges of defining tumor phenotypes in the face of the significant intratumoral heterogeneity that typifies PDAC. Further studies are required to understand the microenvironmental factors that drive the appearance of the metabolic features characteristic of the aggressive M2 PDAC phenotype.

Lineage Plasticity in SCLC Generates Non-Neuroendocrine Cells Primed for Vasculogenic Mimicry

INTRODUCTION

Vasculogenic mimicry (VM), the process of tumor cell transdifferentiation to endow endothelial-like characteristics supporting de novo vessel formation, is associated with poor prognosis in several tumor types, including SCLC. In genetically engineered mouse models (GEMMs) of SCLC, NOTCH, and MYC co-operate to drive a neuroendocrine (NE) to non-NE phenotypic switch, and co-operation between NE and non-NE cells is required for metastasis. Here, we define the phenotype of VM-competent cells and molecular mechanisms underpinning SCLC VM using circulating tumor cell-derived explant (CDX) models and GEMMs.

METHODS

We analyzed perfusion within VM vessels and their association with NE and non-NE phenotypes using multiplex immunohistochemistry in CDX, GEMMs, and patient biopsies. We evaluated their three-dimensional structure and defined collagen-integrin interactions.

RESULTS

We found that VM vessels are present in 23/25 CDX models, 2 GEMMs, and in 20 patient biopsies of SCLC. Perfused VM vessels support tumor growth and only NOTCH-active non-NE cells are VM-competent in vivo and ex vivo, expressing pseudohypoxia, blood vessel development, and extracellular matrix organization signatures. On Matrigel, VM-primed non-NE cells remodel extracellular matrix into hollow tubules in an integrin β1-dependent process.

CONCLUSIONS

We identified VM as an exemplar of functional heterogeneity and plasticity in SCLC and these findings take considerable steps toward understanding the molecular events that enable VM. These results support therapeutic co-targeting of both NE and non-NE cells to curtail SCLC progression and to improve the outcomes of patients with SCLC in the future.

Tamoxifen-predictive value of gene expression signatures in premenopausal breast cancer: data from the randomized SBII:2 trial

BACKGROUND

Gene expression (GEX) signatures in breast cancer provide prognostic information, but little is known about their predictive value for tamoxifen treatment. We examined the tamoxifen-predictive value and prognostic effects of different GEX signatures in premenopausal women with early breast cancer.

METHODS

RNA from formalin-fixed paraffin-embedded tumor tissue from premenopausal women randomized between two years of tamoxifen treatment and no systemic treatment was extracted and successfully subjected to GEX profiling (n = 437, NanoString Breast Cancer 360™ panel). The median follow-up periods for a recurrence-free interval (RFi) and overall survival (OS) were 28 and 33 years, respectively. Associations between GEX signatures and tamoxifen effect were assessed in patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+ /HER2-) tumors using Kaplan-Meier estimates and Cox regression. The prognostic effects of GEX signatures were studied in the entire cohort. False discovery rate adjustments (q-values) were applied to account for multiple hypothesis testing.

RESULTS

In patients with ER+/HER2- tumors, FOXA1 expression below the median was associated with an improved effect of tamoxifen after 10 years with regard to RFi (hazard ratio [HR]FOXA1(high) = 1.04, 95% CI = 0.61-1.76, HRFOXA1(low) = 0.30, 95% CI = 0.14-0.67, qinteraction = 0.0013), and a resembling trend was observed for AR (HRAR(high) = 1.15, 95% CI = 0.60-2.20, HRAR(low) = 0.42, 95% CI = 0.24-0.75, qinteraction = 0.87). Similar patterns were observed for OS. Tamoxifen was in the same subgroup most beneficial for RFi in patients with low ESR1 expression (HRRFi ESR1(high) = 0.76, 95% CI = 0.43-1.35, HRRFi, ESR1(low) = 0.56, 95% CI = 0.29-1.06, qinteraction = 0.37). Irrespective of molecular subtype, higher levels of ESR1, Mast cells, and PGR on a continuous scale were correlated with improved 10 years RFi (HRESR1 = 0.80, 95% CI = 0.69-0.92, q = 0.005; HRMast cells = 0.74, 95% CI = 0.65-0.85, q < 0.0001; and HRPGR = 0.78, 95% CI = 0.68-0.89, q = 0.002). For BC proliferation and Hypoxia, higher scores associated with worse outcomes (HRBCproliferation = 1.54, 95% CI = 1.33-1.79, q < 0.0001; HRHypoxia = 1.38, 95% CI = 1.20-1.58, q < 0.0001). The results were similar for OS.

CONCLUSIONS

Expression of FOXA1 is a promising predictive biomarker for tamoxifen effect in ER+/HER2- premenopausal breast cancer. In addition, each of the signatures BC proliferation, Hypoxia, Mast cells, and the GEX of AR, ESR1, and PGR had prognostic value, also after adjusting for established prognostic factors. Trial registration This trial was retrospectively registered in the ISRCTN database the 6th of December 2019, trial ID: https://clinicaltrials.gov/ct2/show/ISRCTN12474687 .

VHL L169P Variant Does Not Alter Cellular Hypoxia Tension in Clear Cell Renal Cell Carcinoma

In the current era of tumor genome sequencing, single amino acid missense variants in the von Hippel-Lindau (VHL) tumor suppressor gene are frequently identified in clear cell renal carcinoma (ccRCC). Due to the incomplete knowledge of the structural architecture of VHL protein, the functional significance of many missense mutations cannot be assigned. L169P is one such missense mutation identified in the case of aggressive, metastatic ccRCC. Here, we characterized the biochemical activity, transcriptomic hypoxia signature and biological functions of the L169P variant. Lentiviral vector expressing either wildtype (WT) or L169P VHL were used to transduce two VHL-deficient human ccRCC cell lines, 786-O and RCC4. The stability of the VHL protein and the expression level of VHL, HIF1α and HIF2α were analyzed. The impact of restoring L169P or WT VHL on the hypoxia gene expression program in 786-O cells was assessed by mRNA sequencing (RNAseq) and computed hypoxic scores. The impact of restoring VHL expression on the growth of ccRCC models was assessed in cell cultures and in chorioallantoic membrane (CAM) xenografts. In the 786-O cells, the protein stability of L169P VHL was comparable to WT VHL. No obvious difference in the capability of degrading HIF1α and HIF2α was observed between WT and L169P VHL in the 786-O or RCC4 cells. The hypoxic scores were not significantly different in the 786-O cells expressing either wildtype or L169P VHL. From the cellular function perspective, both WT and L169P VHL slowed cell proliferation in vitro and in vivo. The L169P VHL variant is comparable to WT VHL in terms of protein stability, ability to degrade HIF1α factors and ability to regulate hypoxia gene expression, as well as in the suppression of ccRCC tumor cell growth. Taken together, our data indicate that the L169P VHL variant alone is unlikely to drive the oncogenesis of sporadic ccRCC.

Multidisciplinary docking, kinetics and X-ray crystallography studies of baicalein acting as a glycogen phosphorylase inhibitor and determination of its' potential against glioblastoma in cellular models

Glycogen phosphorylase (GP) is the rate-determining enzyme in the glycogenolysis pathway. Glioblastoma (GBM) is amongst the most aggressive cancers of the central nervous system. The role of GP and glycogen metabolism in the context of cancer cell metabolic reprogramming is recognised, so that GP inhibitors may have potential treatment benefits. Here, baicalein (5,6,7-trihydroxyflavone) is studied as a GP inhibitor, and for its effects on glycogenolysis and GBM at the cellular level. The compound is revealed as a potent GP inhibitor against human brain GPa (Ki = 32.54 μM), human liver GPa (Ki = 8.77 μM) and rabbit muscle GPb (Ki = 5.66 μM) isoforms. It is also an effective inhibitor of glycogenolysis (IC50 = 119.6 μM), measured in HepG2 cells. Most significantly, baicalein demonstrated anti-cancer potential through concentration- and time-dependent decrease in cell viability for three GBM cell-lines (U-251 MG, U-87 MG, T98-G) with IC50 values of ∼20-55 μM (48- and 72-h). Its effectiveness against T98-G suggests potential against GBM with resistance to temozolomide (the first-line therapy) due to a positive O6-methylguanine-DNA methyltransferase (MGMT) status. The solved X-ray structure of rabbit muscle GP-baicalein complex will facilitate structure-based design of GP inhibitors. Further exploration of baicalein and other GP inhibitors with different isoform specificities against GBM is suggested.

HIF-1α drives resistance to ferroptosis in solid tumors by promoting lactate production and activating SLC1A1

Solid tumors have developed robust ferroptosis resistance. The mechanism underlying ferroptosis resistance regulation in solid tumors, however, remains elusive. Here, we report that the hypoxic tumor microenvironment potently promotes ferroptosis resistance in solid tumors in a hypoxia-inducible factor 1α (HIF-1α)-dependent manner. In combination with HIF-2α, which promotes tumor ferroptosis under hypoxia, HIF-1α is the main driver of hypoxia-induced ferroptosis resistance. Mechanistically, HIF-1α-induced lactate contributes to ferroptosis resistance in a pH-dependent manner that is parallel to the classical SLC7A11 and FSP1 systems. In addition, HIF-1α also enhances transcription of SLC1A1, an important glutamate transporter, and promotes cystine uptake to promote ferroptosis resistance. In support of the role of hypoxia in ferroptosis resistance, silencing HIF-1α sensitizes mouse solid tumors to ferroptosis inducers. In conclusion, our results reveal a mechanism by which hypoxia drives ferroptosis resistance and identify the combination of hypoxia alleviation and ferroptosis induction as a promising therapeutic strategy for solid tumors.

Prognostic biomarkers for the response to the radiosensitizer nimorazole combined with RCTx: a pre-clinical trial in HNSCC xenografts

BACKGROUND

Tumor hypoxia is associated with resistance to radiotherapy and chemotherapy. In head and neck squamous cell carcinoma (HNSCC), nimorazole, an oxygen mimic, combined with radiotherapy (RT) enabled to improve loco-regional control (LRC) in some patients with hypoxic tumors but it is unknown whether this holds also for radiochemotherapy (RCTx). Here, we investigated the impact of nimorazole combined with RCTx in HNSCC xenografts and explored molecular biomarkers for its targeted use.

METHODS

Irradiations were performed with 30 fractions in 6 weeks combined with weekly cisplatin. Nimorazole was applied before each fraction, beginning with the first or after ten fractions. Effect of RCTx with or without addition of nimorazole was quantified as permanent local control after irradiation. For histological evaluation and targeted gene expression analysis, tumors were excised untreated or after ten fractions. Using quantitative image analysis, micromilieu parameters were determined.

RESULTS

Nimorazole combined with RCTx significantly improved permanent local control in two tumor models, and showed a potential improvement in two additional models. In these four models, pimonidazole hypoxic volume (pHV) was significantly reduced after ten fractions of RCTx alone. Our results suggest that nimorazole combined with RCTx might improve TCR compared to RCTx alone if hypoxia is decreased during the course of RCTx but further experiments are warranted to verify this association. Differential gene expression analysis revealed 12 genes as potential for RCTx response. When evaluated in patients with HNSCC who were treated with primary RCTx, these genes were predictive for LRC.

CONCLUSIONS

Nimorazole combined with RCTx improved local tumor control in some but not in all HNSCC xenografts. We identified prognostic biomarkers with the potential for translation to patients with HNSCC.

Prognosis to Radiation Unlocked: How Hypoxia Methylome May Hold the Key in HNSCC

Hypoxia in head and neck tumors has proven to be predictive of outcomes. Current hypoxia signatures have failed for patient treatment selection. In a recent study, the authors identified a hypoxia methylation signature as a more robust biomarker in head and neck squamous cell carcinoma and shed light into the mechanism of hypoxia-mediated treatment resistance. See related article by Tawk et al., p. 3051.

DNA-Methylome-Based Tumor Hypoxia Classifier Identifies HPV-Negative Head and Neck Cancer Patients at Risk for Locoregional Recurrence after Primary Radiochemotherapy

PURPOSE

Tumor hypoxia is a paradigmatic negative prognosticator of treatment resistance in head and neck squamous cell carcinoma (HNSCC). The lack of robust and reliable hypoxia classifiers limits the adaptation of stratified therapies. We hypothesized that the tumor DNA methylation landscape might indicate epigenetic reprogramming induced by chronic intratumoral hypoxia.

EXPERIMENTAL DESIGN

A DNA-methylome-based tumor hypoxia classifier (Hypoxia-M) was trained in the TCGA (The Cancer Genome Atlas)-HNSCC cohort based on matched assignments using gene expression-based signatures of hypoxia (Hypoxia-GES). Hypoxia-M was validated in a multicenter DKTK-ROG trial consisting of human papillomavirus (HPV)-negative patients with HNSCC treated with primary radiochemotherapy (RCHT).

RESULTS

Although hypoxia-GES failed to stratify patients in the DKTK-ROG, Hypoxia-M was independently prognostic for local recurrence (HR, 4.3; P = 0.001) and overall survival (HR, 2.34; P = 0.03) but not distant metastasis after RCHT in both cohorts. Hypoxia-M status was inversely associated with CD8 T-cell infiltration in both cohorts. Hypoxia-M was further prognostic in the TCGA-PanCancer cohort (HR, 1.83; P = 0.04), underscoring the breadth of this classifier for predicting tumor hypoxia status.

CONCLUSIONS

Our findings highlight an unexplored avenue for DNA methylation-based classifiers as biomarkers of tumoral hypoxia for identifying high-risk features in patients with HNSCC tumors. See related commentary by Heft Neal and Brenner, p. 2954.

Characterizing cancer metabolism from bulk and single-cell RNA-seq data using METAFlux

Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing metabolic reprogramming in the tumor microenvironment (TME) is of emerging importance in cancer research and patient care. However, recent technologies only measure a subset of metabolites and cannot provide in situ measurements. Computational methods such as flux balance analysis (FBA) have been developed to estimate metabolic flux from bulk RNA-seq data and can potentially be extended to single-cell RNA-seq (scRNA-seq) data. However, it is unclear how reliable current methods are, particularly in TME characterization. Here, we present a computational framework METAFlux (METAbolic Flux balance analysis) to infer metabolic fluxes from bulk or single-cell transcriptomic data. Large-scale experiments using cell-lines, the cancer genome atlas (TCGA), and scRNA-seq data obtained from diverse cancer and immunotherapeutic contexts, including CAR-NK cell therapy, have validated METAFlux's capability to characterize metabolic heterogeneity and metabolic interaction amongst cell types.

Machine Learning & Molecular Radiation Tumor Biomarkers

Developing radiation tumor biomarkers that can guide personalized radiotherapy clinical decision making is a critical goal in the effort towards precision cancer medicine. High-throughput molecular assays paired with modern computational techniques have the potential to identify individual tumor-specific signatures and create tools that can help understand heterogenous patient outcomes in response to radiotherapy, allowing clinicians to fully benefit from the technological advances in molecular profiling and computational biology including machine learning. However, the increasingly complex nature of the data generated from high-throughput and "omics" assays require careful selection of analytical strategies. Furthermore, the power of modern machine learning techniques to detect subtle data patterns comes with special considerations to ensure that the results are generalizable. Herein, we review the computational framework of tumor biomarker development and describe commonly used machine learning approaches and how they are applied for radiation biomarker development using molecular data, as well as challenges and emerging research trends.

Identification of a NACC1-Regulated Gene Signature Implicated in the Features of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC), characterized by a deficiency in estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor2 (HER2), is among the most lethal subtypes of breast cancer (BC). Nevertheless, the molecular determinants that contribute to its malignant phenotypes such as tumor heterogeneity and therapy resistance, remain elusive. In this study, we sought to identify the stemness-associated genes involved in TNBC progression. Using bioinformatics approaches, we found 55 up- and 9 downregulated genes in TNBC. Out of the 55 upregulated genes, a 5 gene-signature (CDK1, EZH2, CCNB1, CCNA2, and AURKA) involved in cell regeneration was positively correlated with the status of tumor hypoxia and clustered with stemness-associated genes, as recognized by Parametric Gene Set Enrichment Analysis (PGSEA). Enhanced infiltration of immunosuppressive cells was also positively correlated with the expression of these five genes. Moreover, our experiments showed that depletion of the transcriptional co-factor nucleus accumbens-associated protein 1 (NAC1), which is highly expressed in TNBC, reduced the expression of these genes. Thus, the five genes signature identified by this study warrants further exploration as a potential new biomarker of TNBC heterogeneity/stemness characterized by high hypoxia, stemness enrichment, and immune-suppressive tumor microenvironment.

Repurposing Sulfasalazine as a Radiosensitizer in Hypoxic Human Colorectal Cancer

xCT overexpression in cancer cells has been linked to tumor growth, metastasis and treatment resistance. Sulfasalazine (SSZ), an FDA-approved drug for the treatment of rheumatoid sarthritis, and inflammatory bowel diseases, has anticancer properties via inhibition of xCT, leading to the disruption of redox homeostasis. Since reactive oxygen species (ROS) are pivotal for the efficacy of radiotherapy (RT), elevated levels of ROS are associated with improved RT outcomes. In this study, the influence of SSZ treatment on the radiosensitivity of human colorectal cancer (CRC) cells was investigated. Our principal finding in human HCT116 and DLD-1 cells was that SSZ enhances the radiosensitivity of hypoxic CRC cells but does not alter the intrinsic radiosensitivity. The radiosensitizing effect was attributed to the depletion of glutathione and thioredoxin reductase levels. In turn, the reduction leads to excessive levels of ROS, increased DNA damage, and ferroptosis induction. Confirmation of these findings was performed in 3D models and in DLD-1 xenografts. Taken together, this study is a stepping stone for applying SSZ as a radiosensitizer in the clinic and confirms that xCT in cancer cells is a valid radiobiological target.

Purinergic GPCR-integrin interactions drive pancreatic cancer cell invasion

Pancreatic ductal adenocarcinoma (PDAC) continues to show no improvement in survival rates. One aspect of PDAC is elevated ATP levels, pointing to the purinergic axis as a potential attractive therapeutic target. Mediated in part by highly druggable extracellular proteins, this axis plays essential roles in fibrosis, inflammation response, and immune function. Analyzing the main members of the PDAC extracellular purinome using publicly available databases discerned which members may impact patient survival. P2RY2 presents as the purinergic gene with the strongest association with hypoxia, the highest cancer cell-specific expression, and the strongest impact on overall survival. Invasion assays using a 3D spheroid model revealed P2Y2 to be critical in facilitating invasion driven by extracellular ATP. Using genetic modification and pharmacological strategies, we demonstrate mechanistically that this ATP-driven invasion requires direct protein-protein interactions between P2Y2 and αV integrins. DNA-PAINT super-resolution fluorescence microscopy reveals that P2Y2 regulates the amount and distribution of integrin αV in the plasma membrane. Moreover, receptor-integrin interactions were required for effective downstream signaling, leading to cancer cell invasion. This work elucidates a novel GPCR-integrin interaction in cancer invasion, highlighting its potential for therapeutic targeting.

VHL-HIF-2α axis-induced SEMA6A upregulation stabilized β-catenin to drive clear cell renal cell carcinoma progression

SEMA6A is a multifunctional transmembrane semaphorin protein that participates in various cellular processes, including axon guidance, cell migration, and cancer progression. However, the role of SEMA6A in clear cell renal cell carcinoma (ccRCC) is unclear. Based on high-throughput sequencing data, here we report that SEMA6A is a novel target gene of the VHL-HIF-2α axis and overexpressed in ccRCC. Chromatin immunoprecipitation and reporter assays revealed that HIF-2α directly activated SEMA6A transcription in hypoxic ccRCC cells. Wnt/β-catenin pathway activation is correlated with the expression of SEMA6A in ccRCC; the latter physically interacted with SEC62 and promoted ccRCC progression through SEC62-dependent β-catenin stabilization and activation. Depletion of SEMA6A impaired HIF-2α-induced Wnt/β-catenin pathway activation and led to defective ccRCC cell proliferation both in vitro and in vivo. SEMA6A overexpression promoted the malignant phenotypes of ccRCC, which was reversed by SEC62 depletion. Collectively, this study revealed a potential role for VHL-HIF-2α-SEMA6A-SEC62 axis in the activation of Wnt/β-catenin pathway. Thus, SEMA6A may act as a potential therapeutic target, especially in VHL-deficient ccRCC.

Novel hypoxia-related gene signature for predicting prognoses that correlate with the tumor immune microenvironment in NSCLC

Background: Intratumoral hypoxia is widely associated with the development of malignancy, treatment resistance, and worse prognoses. The global influence of hypoxia-related genes (HRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response is unclear in patients with non-small cell lung cancer (NSCLC). Method: RNA-seq and clinical data for NSCLC patients were derived from The Cancer Genome Atlas (TCGA) database, and a group of HRGs was obtained from the MSigDB. The differentially expressed HRGs were determined using the limma package; prognostic HRGs were identified via univariate Cox regression. Using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, an optimized prognostic model consisting of nine HRGs was constructed. The prognostic model's capacity was evaluated by Kaplan‒Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis in the TCGA (training set) and GEO (validation set) cohorts. Moreover, a potential biological pathway and immune infiltration differences were explained. Results: A prognostic model containing nine HRGs (STC2, ALDOA, MIF, LDHA, EXT1, PGM2, ENO3, INHA, and RORA) was developed. NSCLC patients were separated into two risk categories according to the risk score generated by the hypoxia model. The model-based risk score had better predictive power than the clinicopathological method. Patients in the high-risk category had poor recurrence-free survival in the TCGA (HR: 1.426; 95% CI: 0.997-2.042; p = 0.046) and GEO (HR: 2.4; 95% CI: 1.7-3.2; p < 0.0001) cohorts. The overall survival of the high-risk category was also inferior to that of the low-risk category in the TCGA (HR: 1.8; 95% CI: 1.5-2.2; p < 0.0001) and GEO (HR: 1.8; 95% CI: 1.4-2.3; p < 0.0001) cohorts. Additionally, we discovered a notable distinction in the enrichment of immune-related pathways, immune cell abundance, and immune checkpoint gene expression between the two subcategories. Conclusion: The proposed 9-HRG signature is a promising indicator for predicting NSCLC patient prognosis and may be potentially applicable in checkpoint therapy efficiency prediction.

A subnetwork-based framework for prioritizing and evaluating prognostic gene modules from cancer transcriptome data

Cancer prognosis prediction is critical to the clinical decision-making process. Currently, the high availability of transcriptome datasets allows us to extract the gene modules with promising prognostic values. However, the biomarker identification is greatly challenged by tumor and patient heterogeneity. In this study, a framework of three subnetwork-based strategies is presented, incorporating hypothesis-driven, data-driven, and literature-based methods with informative visualization to prioritize candidate genes. By applying the proposed approaches to a head and neck squamous cell cancer (HNSCC) transcriptome dataset, we successfully identified multiple HNSCC-specific gene modules with improved prognostic values and mechanism information compared with the standard gene panel selection methods. The proposed framework is general and can be applied to any type of omics data. Overall, the study demonstrates and supports the use of the subnetwork-based approach for distilling reliable and biologically meaningful prognostic factors.

Stabilized COre gene and Pathway Election uncovers pan-cancer shared pathways and a cancer-specific driver

Approaches systematically characterizing interactions via transcriptomic data usually follow two systems: (i) coexpression network analyses focusing on correlations between genes and (ii) linear regressions (usually regularized) to select multiple genes jointly. Both suffer from the problem of stability: A slight change of parameterization or dataset could lead to marked alterations of outcomes. Here, we propose Stabilized COre gene and Pathway Election (SCOPE), a tool integrating bootstrapped least absolute shrinkage and selection operator and coexpression analysis, leading to robust outcomes insensitive to variations in data. By applying SCOPE to six cancer expression datasets (BRCA, COAD, KIRC, LUAD, PRAD, and THCA) in The Cancer Genome Atlas, we identified core genes capturing interaction effects in crucial pan-cancer pathways related to genome instability and DNA damage response. Moreover, we highlighted the pivotal role of CD63 as an oncogenic driver and a potential therapeutic target in kidney cancer. SCOPE enables stabilized investigations toward complex interactions using transcriptome data.

SETD7 Expression Is Associated with Breast Cancer Survival Outcomes for Specific Molecular Subtypes: A Systematic Analysis of Publicly Available Datasets

SETD7 is a lysine N-methyltransferase that targets many proteins important in breast cancer (BC). However, its role and clinical significance remain unclear. Here, we used online tools and multiple public datasets to explore the predictive potential of SETD7 expression (high or low quartile) considering BC subtype, grade, stage, and therapy. We also investigated overrepresented biological processes associated with its expression using TCGA-BRCA data. SETD7 expression was highest in the Her2 (ERBB2)-enriched molecular subtype and lowest in the basal-like subtype. For the basal-like subtype specifically, higher SETD7 was consistently correlated with worse recurrence-free survival (p < 0.009). High SETD7-expressing tumours further exhibited a higher rate of ERBB2 mutation (20% vs. 5%) along with a poorer response to anti-Her2 therapy. Overall, high SETD7-expressing tumours showed higher stromal and lower immune scores. This was specifically related to higher counts of cancer-associated fibroblasts and endothelial cells, but lower B and T cell signatures, especially in the luminal A subtype. Genes significantly associated with SETD7 expression were accordingly overrepresented in immune response processes, with distinct subtype characteristics. We conclude that the prognostic value of SETD7 depends on the BC subtype and that SETD7 may be further explored as a potential treatment-predictive marker for immune checkpoint inhibitors.

Pan-cancer analysis of tissue and single-cell HIF-pathway activation using a conserved gene signature

Activation of cellular hypoxia pathways, orchestrated by HIF (hypoxia-inducible factor) transcription factors, is a common feature of multiple tumor types, resulting from microenvironment factors and oncogenic mutation. Although they help drive many of the "hallmarks" of cancer and are associated with poor outcome and resistance to therapy, the transcriptional targets of HIF vary considerably depending on the cell type. By integrating 72 genome-wide assays of HIF binding and transcriptional regulation from multiple cancer types, we define a consensus set of 48 HIF target genes that is highly conserved across cancer types and cell lineages. These genes provide an effective marker of HIF activation in bulk and single-cell transcriptomic analyses across a wide range of cancer types and in malignant and stromal cell types. This allows the tissue-orchestrated responses to the hypoxic tumor microenvironment and to oncogenic HIF activation to be deconvoluted at the tumor and single-cell level.

Hypoxia-driven immunosuppression by Treg and type-2 conventional dendritic cells in HCC

BACKGROUND AND AIMS

Hypoxia is one of the central players in shaping the immune context of the tumor microenvironment (TME). However, the complex interplay between immune cell infiltrates within the hypoxic TME of HCC remains to be elucidated.

APPROACH AND RESULTS

We analyzed the immune landscapes of hypoxia-low and hypoxia-high tumor regions using cytometry by time of light, immunohistochemistry, and transcriptomic analyses. The mechanisms of immunosuppression in immune subsets of interest were further explored using in vitro hypoxia assays. Regulatory T cells (Tregs) and a number of immunosuppressive myeloid subsets, including M2 macrophages and human leukocyte antigen-DR isotype (HLA-DR^lo ) type 2 conventional dendritic cell (cDC2), were found to be significantly enriched in hypoxia-high tumor regions. On the other hand, the abundance of active granzyme B^hi PD-1^lo CD8⁺ T cells in hypoxia-low tumor regions implied a relatively active immune landscape compared with hypoxia-high regions. The up-regulation of cancer-associated genes in the tumor tissues and immunosuppressive genes in the tumor-infiltrating leukocytes supported a highly pro-tumorigenic network in hypoxic HCC. Chemokine genes such as CCL20 (C-C motif chemokine ligand 20) and CXCL5 (C-X-C motif chemokine ligand 5) were associated with recruitment of both Tregs and HLA-DR^lo cDC2 to hypoxia-high microenvironments. The interaction between Tregs and cDC2 under a hypoxic TME resulted in a loss of antigen-presenting HLA-DR on cDC2.

CONCLUSIONS

We uncovered the unique immunosuppressive landscapes and identified key immune subsets enriched in hypoxic HCC. In particular, we identified a potential Treg-mediated immunosuppression through interaction with a cDC2 subset in HCC that could be exploited for immunotherapies.

Inhibition of Phosphoglycerate Dehydrogenase Radiosensitizes Human Colorectal Cancer Cells under Hypoxic Conditions

Simple Summary

Colorectal cancer is the third most prevalent cancer worldwide. Treatment options for these patients consist of surgery combined with chemotherapy and/or radiotherapy. However, a subset of tumors will not respond to therapy or acquire resistance during the course of the treatment, leading to patient relapse. The interplay between reprogramming cancer metabolism and radiotherapy has become an appealing strategy to improve a patient’s outcome. Due to the overexpression of certain enzymes in a variety of cancer types, including colorectal cancer, the serine synthesis pathway has recently become an attractive metabolic target. We demonstrated that by inhibiting the first enzyme of this pathway, namely phosphoglycerate dehydrogenase (PHGDH), tumor cells that are deprived of oxygen (as is generally the case in solid tumors) respond better to radiation, leading to increased tumor cell killing in an experimental model of human colorectal cancer.

Abstract

Augmented de novo serine synthesis activity is increasingly apparent in distinct types of cancers and has mainly sparked interest by investigation of phosphoglycerate dehydrogenase (PHGDH). Overexpression of PHGDH has been associated with higher tumor grade, shorter relapse time and decreased overall survival. It is well known that therapeutic outcomes in cancer patients can be improved by reprogramming metabolic pathways in combination with standard treatment options, for example, radiotherapy. In this study, possible metabolic changes related to radioresponse were explored upon PHGDH inhibition. Additionally, we evaluated whether PHGDH inhibition could improve radioresponse in human colorectal cancer cell lines in both aerobic and radiobiological relevant hypoxic conditions. Dysregulation of reactive oxygen species (ROS) homeostasis and dysfunction in mitochondrial energy metabolism and oxygen consumption rate were indicative of potential radiomodulatory effects. We demonstrated that PHGDH inhibition radiosensitized hypoxic human colorectal cancer cells while leaving intrinsic radiosensitivity unaffected. In a xenograft model, the first hints of additive effects between PHGDH inhibition and radiotherapy were demonstrated. In conclusion, this study is the first to show that modulation of de novo serine biosynthesis enhances radioresponse in hypoxic colorectal cancer cells, mainly mediated by increased levels of intracellular ROS.

Identification of m6A modification patterns and development of m6A-hypoxia prognostic signature to characterize tumor microenvironment in triple-negative breast cancer

Background

N6-methylation (m6A) modification of RNA has been found to have essential effects on aspects of the tumor microenvironment (TME) including hypoxia status and mobilization of immune cells. However, there are no studies to explore the combined effect of m6A modification and hypoxia on molecular heterogeneity and TME of triple-negative breast cancer (TNBC).

Methods

We collected The Cancer Genome Atlas (TCGA-TNBC, N=139), the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC-TNBC, N=297), the GSE103091, GSE21653, and GSE135565 series from the Gene Expression Omnibus (GEO-TNBC, N=247), and FUSCCTNBC (N=245) for our study. The non-negative matrix factorization algorithm was used to cluster TNBC samples. Immune cell infiltration was analyzed by the CIBERSORT algorithm. The enrichment scores were calculated by single-sample gene set enrichment analysis(ssGSEA) to characterize TME in TNBC samples. Immunohistochemistry (IHC) and qRT-PCR were performed to detect the gene expression.

Results

Based on the expression of m6A-related genes, we identified three distinct m6A clusters (denoted A, B, and C) in TNBC samples. Comparing the TME characteristics among the three clusters, we observed that cluster C was strongly related to hypoxia status and immune suppression, whereas clusters A and B displayed more immune cell infiltration. Therefore, we combine m6A and hypoxia related genes to classify two m6A-hypoxia clusters of TNBC and screened six prognostic genes by LASSO-Cox regression to construct a m6A-hypoxia signature(MHPS), which divided TNBC samples into high- and low-risk groups. We identified different TME features, immune cell infiltration between the two groups, and a better immunotherapy response was observed in the low-risk group. A nomogram was constructed with tumor size, lymph node, and risk score to improve clinical application of MHPS.

Conclusion

We identified distinct TME characteristics of TNBC based on three different m6A modification patterns. Then, we constructed a specific m6A-hypoxia signature for TNBC to evaluate risk and predict immunotherapy response of patients, to enable more accurate treatment in the future.

Breast Cancer Subtypes Based on Hypoxia-Related Gene Sets Identify Potential Therapeutic Agents

Purpose: The hypoxic tumor microenvironment was reported to be involved in different tumorigenesis mechanisms of breast cancer (BC). We aimed to establish a hypoxia-related gene signature to identify a new BC subtype through the clustering analysis and explore potential compounds targeting the BC subtypes.

Methods: Gene expression data and clinical features of BC and adjacent non-tumor tissues were downloaded from the Cancer Genome Atlas-Breast cancer (TCGA-BRCA) database. We comprehensively revealed the activity changes of Gene Ontology (GO) biological processes (BP) gene sets in BC by gene set variation analysis (GSVA) and identified three hypoxia-related BC subtypes. We then matched the differentially expressed gene profile of each subtype with the gene profile in CMap database to identify the potential agents targeting the BC subtypes.

Results: 562 of Gene Ontology biological processes gene sets significantly correlated with hypoxia score in breast cancer. 969 BC patients were clustered into three subtypes based on the enrichment score of hypoxia-associated gene sets. Subtype 1 patients displayed better survival than subtype 2 and 3. KEGG pathway enrichment analysis of each subtype was performed based on the unique differential expression genes profile. In subtype 1, the upregulated genes were associated with lipid and amino acid metabolism regulation; in subtype 2, the upregulated genes were associated with metabolic energy regulation, while in subtype 3, the upregulated genes were associated with apoptosis and protein process. Using the CMap database, 55, 111 and 63 compounds were identified, targeting subtype 1, 2, and 3, respectively.

Conclusion: In this study, novel hypoxia-related subtypes were developed for patients with BC. In addition, biological processes associated with differential expression genes profile and potential therapeutic target compounds were identified in each subtype. The new classification might provide a better understanding of the role of hypoxia in breast cancer and more individualized treatment for patients.

Differential HIF2α Protein Expression in Human Carotid Body and Adrenal Medulla under Physiologic and Tumorigenic Conditions

Hypoxia-inducible factors (HIF) 2α and 1α are the major oxygen-sensing molecules in eukaryotic cells. HIF2α has been pathogenically linked to paraganglioma and pheochromocytoma (PPGL) arising in sympathetic paraganglia or the adrenal medulla (AM), respectively. However, its involvement in the pathogenesis of paraganglioma arising in the carotid body (CB) or other parasympathetic ganglia in the head and neck (HNPGL) remains to be defined. Here, we retrospectively analyzed HIF2α by immunohistochemistry in 62 PPGL/HNPGL and human CB and AM, and comprehensively evaluated the HIF-related transcriptome of 202 published PPGL/HNPGL. We report that HIF2α is barely detected in the AM, but accumulates at high levels in PPGL, mostly (but not exclusively) in those with loss-of-function mutations in VHL and genes encoding components of the succinate dehydrogenase (SDH) complex. This is associated with upregulation of EPAS1 and the HIF2α-regulated genes COX4I2 and ADORA2A. In contrast, HIF2α and HIF2α-regulated genes are highly expressed in CB and HNPGL, irrespective of VHL and SDH dysfunctions. We also found that HIF2α and HIF1α protein expressions are not correlated in PPGL nor HNPGL. In addition, HIF1α-target genes are almost exclusively overexpressed in VHL-mutated HNPGL/PPGL. Collectively, the data suggest that involvement of HIF2α in the physiology and tumor pathology of human paraganglia is organ-of-origin-dependent and HIF1α-independent.

Oxygen Measurement in Microdevices

Oxygen plays a fundamental role in respiration and metabolism, and quantifying oxygen levels is essential in many environmental, industrial, and research settings. Microdevices facilitate the study of dynamic, oxygen-dependent effects in real time. This review is organized around the key needs for oxygen measurement in microdevices, including integrability into microfabricated systems; sensor dynamic range and sensitivity; spatially resolved measurements to map oxygen over two- or three-dimensional regions of interest; and compatibility with multimodal and multianalyte measurements. After a brief overview of biological readouts of oxygen, followed by oxygen sensor types that have been implemented in microscale devices and sensing mechanisms, this review presents select recent applications in organs-on-chip in vitro models and new sensor capabilities enabling oxygen microscopy, bioprocess manufacturing, and pharmaceutical industries. With the advancement of multiplexed, interconnected sensors and instruments and integration with industry workflows, intelligent microdevice-sensor systems including oxygen sensors will have further impact in environmental science, manufacturing, and medicine.

Hypoxia-induced inhibin promotes tumor growth and vascular permeability in ovarian cancers

Hypoxia, a driver of tumor growth and metastasis, regulates angiogenic pathways that are targets for vessel normalization and ovarian cancer management. However, toxicities and resistance to anti-angiogenics can limit their use making identification of new targets vital. Inhibin, a heteromeric TGFβ ligand, is a contextual regulator of tumor progression acting as an early tumor suppressor, yet also an established biomarker for ovarian cancers. Here, we find that hypoxia increases inhibin levels in ovarian cancer cell lines, xenograft tumors, and patients. Inhibin is regulated primarily through HIF-1, shifting the balance under hypoxia from activins to inhibins. Hypoxia regulated inhibin promotes tumor growth, endothelial cell invasion and permeability. Targeting inhibin in vivo through knockdown and anti-inhibin strategies robustly reduces permeability in vivo and alters the balance of pro and anti-angiogenic mechanisms resulting in vascular normalization. Mechanistically, inhibin regulates permeability by increasing VE-cadherin internalization via ACVRL1 and CD105, a receptor complex that we find to be stabilized directly by inhibin. Our findings demonstrate direct roles for inhibins in vascular normalization via TGF-β receptors providing new insights into the therapeutic significance of inhibins as a strategy to normalize the tumor vasculature in ovarian cancer.

Hypoxia increases levels of the heteromeric TGFβ ligand inhibin in ovarian cancer and inhibin promotes tumor growth, endothelial cell invasion and permeability.

Hypoxia classifier for transcriptome datasets

Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1-5%[Formula: see text]) for 2-48 h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed of 3-5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.

Construction of a Prognostic Model for Hypoxia-Related LncRNAs and Prediction of the Immune Landscape in the Digestive System Pan-Cancer

Digestive system pan-cancer is a general term for digestive system tumors including colorectal carcinoma (CRC), esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), and liver hepatocellular carcinoma (LIHC). Since the anatomical location, function and metabolism are closely related, there may be similarities in development and progression of these tumors. Hypoxia is the consequence of an imbalance between oxygen demand and supply, and intracellular hypoxia is associated with malignant progression, treatment resistance, and poor prognosis in tumors. Therefore, an urgent and challenging task is to investigate the molecular mechanisms associated with hypoxia in digestive system pan-cancer for the prognosis and treatment of digestive tract tumors. In this study, we identified 18 hypoxia-related lncRNAs (HRlncRNAs) by co-expression analysis between hypoxia genes and lncRNAs from digestive system pan-cancer. Six HRlncRNAs were then obtained using lasso regression and multivariate cox analysis to construct a prognostic model. Next, the Akaike information criterion (AIC) values for 3-year receiver operating curve (ROC) were counted to determine the cut-off point and establish an optimal model to distinguish between high- or low-risk groups among patients with digestive system pan-cancer. To evaluate the stability of the prognosis model, we validated it in terms of survival outcomes, clinicopathological stage, tumor-infiltrating immune cells, immune checkpoint inhibitors (ICIs) and anticancer drugs sensitivity. The results suggested that high- risk group had a worse prognosis and a more positive association with tumor-infiltrating immune cells such as B cells, cancer-associated fibroblasts, endothelial cells, monocytes, macrophages and bone marrow dendritic cells in digestive system pan-cancer. Immune checkpoint inhibitors (ICIs) related biomarkers discovered that high-risk group was positively correlated with high expression of HAVCR2 in digestive system pan-cancer. The anticancer drugs sensitivity analysis showed that the high-risk group was associated with the lower half-inhibitory centration (IC50) of Imatinib in digestive system pan-cancer. In conclusion, the prognostic model of HRlncRNAs showed a promising clinical prediction value and may provide a useful reference for the diagnosis and treatment of the digestive system tumors.

Development of a prediction model for radiotherapy response among patients with head and neck squamous cell carcinoma based on the tumor immune microenvironment and hypoxia signature

INTRODUCTION

The immune system and hypoxia are major factors influencing radiosensitivity in patients with different cancer types. This study aimed at developing a model to predict radiotherapy response in patients with head and neck squamous cell carcinoma (HNSCC) based on the tumor immune microenvironment and hypoxia signature.

MATERIALS AND METHODS

We first evaluated the hypoxia status and tumor immune microenvironment in the Cancer Genome Atlas (TCGA) cohort by using transcriptomic data. Differentially expressed genes (DEGs) were identified between the "high immunity and low hypoxia" and "low immunity and high hypoxia" groups and those DEGs significantly associated with disease-specific survival in the univariate Cox regression analysis were selected as the prognostic DEGs. We selected the immune hypoxia-related genes (IHRGs) by intersecting prognostic DEGs with immune and hypoxia gene sets. We used the IHRGs to train a multivariate Cox regression model in the TCGA cohort, based on which we calculated the IHRG prognostic index (IHRGPI) for each patient and validated its efficacy in predicting radiotherapy response in the Gene Expression Omnibus cohorts. Furthermore, we explored potential mechanisms and effective combinational treatment strategies for different IHRGPI groups.

RESULTS

Five IHRGs were used to construct the IHRGPI, which was used to dichotomize the cohorts. The patients with lower IHRGPI showed a better radiotherapy response across different cohorts and endpoints, including overall survival, progression-free survival, and recurrence-free survival (p < 0.05). Patients with higher IHRGPI showed greater hypoxia and lesser immune cell infiltration. A lower IHRGPI indicated a better immunotherapy response, while a higher IHRGPI indicated a better chemotherapy response.

CONCLUSIONS

IHRGPI is promising for predicting radiotherapy response and guiding combinational treatment strategies in patients with HNSCC.

HIF activation enhances FcγRIIb expression on mononuclear phagocytes impeding tumor targeting antibody immunotherapy

BACKGROUND

Hypoxia is a hallmark of the tumor microenvironment (TME) and in addition to altering metabolism in cancer cells, it transforms tumor-associated stromal cells. Within the tumor stromal cell compartment, tumor-associated macrophages (TAMs) provide potent pro-tumoral support. However, TAMs can also be harnessed to destroy tumor cells by monoclonal antibody (mAb) immunotherapy, through antibody dependent cellular phagocytosis (ADCP). This is mediated via antibody-binding activating Fc gamma receptors (FcγR) and impaired by the single inhibitory FcγR, FcγRIIb.

METHODS

We applied a multi-OMIC approach coupled with in vitro functional assays and murine tumor models to assess the effects of hypoxia inducible factor (HIF) activation on mAb mediated depletion of human and murine cancer cells. For mechanistic assessments, siRNA-mediated gene silencing, Western blotting and chromatin immune precipitation were utilized to assess the impact of identified regulators on FCGR2B gene transcription.

RESULTS

We report that TAMs are FcγRIIbbright relative to healthy tissue counterparts and under hypoxic conditions, mononuclear phagocytes markedly upregulate FcγRIIb. This enhanced FcγRIIb expression is transcriptionally driven through HIFs and Activator protein 1 (AP-1). Importantly, this phenotype reduces the ability of macrophages to eliminate anti-CD20 monoclonal antibody (mAb) opsonized human chronic lymphocytic leukemia cells in vitro and EL4 lymphoma cells in vivo in human FcγRIIb+/+ transgenic mice. Furthermore, post-HIF activation, mAb mediated blockade of FcγRIIb can partially restore phagocytic function in human monocytes.

CONCLUSION

Our findings provide a detailed molecular and cellular basis for hypoxia driven resistance to antitumor mAb immunotherapy, unveiling a hitherto unexplored aspect of the TME. These findings provide a mechanistic rationale for the modulation of FcγRIIb expression or its blockade as a promising strategy to enhance approved and novel mAb immunotherapies.

Breast cancer hypoxia in relation to prognosis and benefit from radiotherapy after breast-conserving surgery in a large, randomised trial with long-term follow-up

Background

Breast-conserving surgery followed by radiotherapy is part of standard treatment for early-stage breast cancer. Hypoxia is common in cancer and may affect the benefit of radiotherapy. Cells adapt to hypoxic stress largely via the transcriptional activity of hypoxia-inducible factor (HIF)-1α. Here, we aim to determine whether tumour HIF-1α-positivity and hypoxic gene-expression signatures associated with the benefit of radiotherapy, and outcome.

Methods

Tumour HIF-1α-status and expression of hypoxic gene signatures were retrospectively analysed in a clinical trial where 1178 women with primary T1-2N0M0 breast cancer were randomised to receive postoperative radiotherapy or not and followed 15 years for recurrence and 20 years for breast cancer death.

Results

The benefit from radiotherapy was similar in patients with HIF-1α-positive and -negative primary tumours. Both ipsilateral and any breast cancer recurrence were more frequent in women with HIF-1α-positive primary tumours (hazard ratio, HR_{0–5 yrs}1.9 [1.3–2.9], p = 0.003 and HR_{0–5 yrs} = 2.0 [1.5–2.8], p < 0.0001). Tumour HIF-1α-positivity is also associated with increased breast cancer death (HR_{0–10 years} 1.9 [1.2–2.9], p = 0.004). Ten of the 11 investigated hypoxic gene signatures correlated positively to HIF-1α-positivity, and 5 to increased rate/risk of recurrence.

Conclusions

The benefit of postoperative radiotherapy persisted in patients with hypoxic primary tumours. Patients with hypoxic primary breast tumours had an increased risk of recurrence and breast cancer death.

Construction and Verification of a Combined Hypoxia and Immune Index for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive malignancies in humans. Hypoxia-related genes are now recognized as a reflection of poor prognosis in cancer patients with cancer. Meanwhile, immune-related genes play an important role in the occurrence and progression of ccRCC. Nevertheless, reliable prognostic indicators based on hypoxia and immune status have not been well established in ccRCC. The aims of this study were to develop a new gene signature model using bioinformatics and open databases and to validate its prognostic value in ccRCC. The data used for the model structure can be accessed from The Cancer Genome Atlas database. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the hypoxia- and immune-related genes associated with prognostic risk, which were used to develop a characteristic model of prognostic risk. Kaplan-Meier and receiver-operating characteristic curve analyses were performed as well as independent prognostic factor analyses and correlation analyses of clinical characteristics in both the training and validation cohorts. In addition, differences in tumor immune cell infiltrates were compared between the high and low risk groups. Overall, 30 hypoxia- and immune-related genes were identified, and five hypoxia- and immune-related genes (EPO, PLAUR, TEK, TGFA, TGFB1) were ultimately selected. Survival analysis showed that the high-risk score on the hypoxia- and immune-related gene signature was significantly associated with adverse survival outcomes. Furthermore, clinical ccRCC samples from our medical center were used to validate the differential expression of the five genes in tumor tissue compared to normal tissue through quantitative real-time polymerase chain reaction (qRT-PCR). However, more clinical trials are needed to confirm these results, and future experimental studies must verify the potential mechanism behind the predictive value of the hypoxia- and immune-related gene signature.