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

High hypoxia status in pancreatic cancer is associated with multiple hallmarks of an immunosuppressive tumor microenvironment

Introduction

Pancreatic ductal adenocarcinoma (PDAC), the most common form of pancreatic cancer, is a particularly lethal disease that is often diagnosed late and is refractory to most forms of treatment. Tumour hypoxia is a key hallmark of PDAC and is purported to contribute to multiple facets of disease progression such as treatment resistance, increased invasiveness, metabolic reprogramming, and immunosuppression.

Methods

We used the Buffa gene signature as a hypoxia score to profile transcriptomics datasets from PDAC cases. We performed cell-type deconvolution and gene expression profiling approaches to compare the immunological phenotypes of cases with low and high hypoxia scores. We further supported our findings by qPCR analyses in PDAC cell lines cultured in hypoxic conditions.

Results

First, we demonstrated that this hypoxia score is associated with increased tumour grade and reduced survival suggesting that this score is correlated to disease progression. Subsequently, we compared the immune phenotypes of cases with high versus low hypoxia score expression (HypoxiaHI vs. HypoxiaLOW) to show that high hypoxia is associated with reduced levels of T cells, NK cells and dendritic cells (DC), including the crucial cDC1 subset. Concomitantly, immune-related gene expression profiling revealed that compared to HypoxiaLOW tumours, mRNA levels for multiple immunosuppressive molecules were notably elevated in HypoxiaHI cases. Using a Random Forest machine learning approach for variable selection, we identified LGALS3 (Galectin-3) as the top gene associated with high hypoxia status and confirmed its expression in hypoxic PDAC cell lines.

Discussion

In summary, we demonstrated novel associations between hypoxia and multiple immunosuppressive mediators in PDAC, highlighting avenues for improving PDAC immunotherapy by targeting these immune molecules in combination with hypoxia-targeted drugs.

Onward Spread from Liver Metastases Is a Major Cause of Multi-Organ Metastasis in a Mouse Model of Metastatic Colon Cancer

Colorectal cancer metastasizes predominantly to the liver but also to the lungs and the peritoneum. The presence of extra-hepatic metastases limits curative (surgical) treatment options and is associated with very poor survival. The mechanisms governing multi-organ metastasis formation are incompletely understood. Here, we tested the hypothesis that the site of tumor growth influences extra-hepatic metastasis formation. To this end, we implanted murine colon cancer organoids into the primary tumor site (i.e., the caecum) and into the primary metastasis site (i.e., the liver) in immunocompetent mice. The organoid-initiated liver tumors were significantly more efficient in seeding distant metastases compared to tumors of the same origin growing in the caecum (intra-hepatic: 51 vs. 40%, p = 0.001; peritoneal cavity: 51% vs. 33%, p = 0.001; lungs: 30% vs. 7%, p = 0.017). The enhanced metastatic capacity of the liver tumors was associated with the formation of 'hotspots' of vitronectin-positive blood vessels surrounded by macrophages. RNA sequencing analysis of clinical samples showed a high expression of vitronectin in liver metastases, along with signatures reflecting hypoxia, angiogenesis, coagulation, and macrophages. We conclude that 'onward spread' from liver metastases is facilitated by liver-specific microenvironmental signals that cause the formation of macrophage-associated vascular hotspots. The therapeutic targeting of these signals may help to contain the disease within the liver and prevent onward spread.

Hypoxia at 3D organoid establishment selects essential subclones within heterogenous pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is especially hypoxic and composed of heterogeneous cell populations containing hypoxia-adapted cells. Hypoxia as a microenvironment of PDAC is known to cause epithelial-mesenchymal transition (EMT) and resistance to therapy. Therefore, cells adapted to hypoxia possess malignant traits that should be targeted for therapy. However, current 3D organoid culture systems are usually cultured under normoxia, losing hypoxia-adapted cells due to selectivity bias at the time of organoid establishment. To overcome any potential selection bias, we focused on oxygen concentration during the establishment of 3D organoids. We subjected identical PDAC surgical samples to normoxia (O2 20%) or hypoxia (O2 1%), yielding glandular and solid organoid morphology, respectively. Pancreatic cancer organoids established under hypoxia displayed higher expression of EMT-related proteins, a Moffitt basal-like subtype transcriptome, and higher 5-FU resistance in contrast to organoids established under normoxia. We suggest that hypoxia during organoid establishment efficiently selects for hypoxia-adapted cells possibly responsible for PDAC malignant traits, facilitating a fundamental source for elucidating and developing new treatment strategies against PDAC.

Identification of potential prognostic biomarkers among gene models for coiled-coil domain-containing family members in hepatocellular carcinoma elucidates their influence on the hypoxia pathway and immune microenvironment

Background

The family of coiled-coil domain-containing (CCDC) proteins participates in a wide range of physiological functions and plays a pivotal role in governing the invasion and metastasis of malignant tumor cells. Nonetheless, the precise mechanism governing the interaction among the immune microenvironment, hypoxia pathway, and proliferation in hepatocellular carcinoma (HCC) remains elusive. In this study, our objective was to identify the prognostic significance of CCDC family genes in HCC.

Methods

We conducted an analysis of RNA-seq data from HCC patients sourced from The Cancer Genome Atlas (TCGA) database. Our analysis involved comparing the expression profiles of 168 CCDC family genes between tumor and normal tissues to identify differentially expressed genes (DEGs). The prognostic value of these genes was verified using overall survival (OS) data from TCGA-LIHC patients, employing Univariate and multivariate Cox proportional hazards regression models and Kaplan-Meier plots. Subsequently, we constructed a prognostic signature known as the CCDC score and validated it using additional datasets (ICGC-LIRI-JP and GSE14520). Additionally, we performed functional enrichment analysis and conducted an assessment of the tumor immune microenvironment (TIME).

Results

We identified 34 DEGs of the CCDC family. Among them, six DEGs (CCDC6/22/51/59/132/134) were upregulated and associated with poor prognosis. Higher CCDC score was an independent predictor of poor OS in TCGA-HCC patients (P<0.001, HR =2.37), which was validated in the ICGC-LIRI-JP (P=0.021, HR =2.15) and GSE14520 (P=0.002, HR =2.23) datasets. Functional enrichment analysis showed that hypoxia pathway genes were enriched in the high CCDC score group. Furthermore, immune microenvironment analysis demonstrated that high CCDC score was associated with a suppressed TIME caused by the extrinsic immune escape.

Conclusions

The CCDC score, derived from six CCDC genes, exhibits remarkable expression levels in liver cancer and holds promise as an independent prognostic indicator. Our bioinformatics analysis revealed a high CCDC score is strongly associated with activation of the hypoxia pathway and an immunosuppressive tumor microenvironment in HCC. This profound finding may serve as a cornerstone for innovative targeted drug therapies and pave the way for further investigations into the underlying mechanisms of CCDC-related carcinogenesis in liver cancer.

Hypoxia induces immunosuppression, metastasis and drug resistance in pancreatic cancers

Pancreatic cancer is one of the common malignant tumors of the digestive system and is known as the "king of cancers". It is extremely difficult to diagnose at an early stage, the disease progresses rapidly, and the effect of chemotherapy and radiotherapy is poor, so the prognosis of pancreatic cancer patients is very poor. Numerous studies have suggested that hypoxia is closely related to the development and progression of pancreatic cancer. Inadequate blood supply and desmoplasia in the microenvironment of pancreatic cancer can result in its extreme hypoxia. This hypoxic microenvironment can further contribute to angiogenesis and desmoplasia. Hypoxia is mediated by the complex hypoxia inducible factor (HIF) signaling pathway and plays an important role in the formation of a highly immunosuppressive microenvironment and the metastasis of pancreatic cancer. Further work on the hypoxic microenvironment will help clarify the specific mechanisms of the role of hypoxia in pancreatic cancer and provide a basis for the realization of hypoxia-targeted therapeutic and diagnostic strategies.

A Novel Pancreatic Cancer Hypoxia Status Related Gene Signature for Prognosis and Therapeutic Responses

Pancreatic cancer (PAC) is a highly fatal and aggressive type of cancer. Hypoxia is a common feature of PAC. The aim of this study was to develop a hypoxia status-related prognostic model for predicting the survival outcomes in PAC. The data sets of PAC from The Cancer Genome Atlas and the International Cancer Genome Consortium were used to construct and validate the signature. A 6 hypoxia status-related differential expression genes prognostic model for predicting the survival outcomes was established. The Kaplan-Meier analysis and Received operating characteristic curve indicated the good performance of the signature at predicting overall survival. Univariate and Multivariate Cox regression revealed that the signature was an independent prognostic factor in PAC. Weighted Gene Co-expression Network Analysis and immune infiltration analysis indicated that Immune-related pathways and immune cell infiltration was mostly enriched in the low-risk group, which presented a better prognosis. We also evaluated the predictive of the signature for immunotherapy and chemoradiotherapy. Risk gene LY6D may be a potential prognostic predictor of PAC. This model can be used as an independent prognostic factor for predicting clinical outcomes and a possible classifier for response to chemotherapy.

CD8 + T cell infiltration is associated with improved survival and negatively correlates with hypoxia in clear cell ovarian cancer

Unlike other histological types of epithelial ovarian carcinoma, clear cell ovarian carcinoma (CCOC) has poor response to therapy. In many other carcinomas, expression of the hypoxia-related enzyme Carbonic anhydrase IX (CAIX) by cancer cells is associated with poor prognosis, while the presence of CD8 + tumor-infiltrating lymphocytes (TIL) is positively prognostic. We employed [¹⁸F]EF5-PET/CT imaging, transcriptome profiling, and spatially-resolved histological analysis to evaluate relationships between CAIX, CD8, and survival in CCOC. Tissue microarrays (TMAs) were evaluated for 218 cases in the Canadian COEUR study. Non-spatial relationships between CAIX and CD8 were investigated using Spearman rank correlation, negative binomial regression and gene set enrichment analysis. Spatial relationships at the cell level were investigated using the cross K-function. Survival analysis was used to assess the relationship of CAIX and CD8 with patient survival for 154 cases. CD8 + T cell infiltration positively predicted survival with estimated hazard ratio 0.974 (95% CI 0.950, 1000). The negative binomial regression analysis found a strong TMA effect (p-value < 0.0001). It also indicated a negative association between CD8 and CAIX overall (p-value = 0.0171) and in stroma (p-value = 0.0050) but not in tumor (p-value = 0.173). Examination of the spatial association between the locations of CD8 + T cells and CAIX cells found a significant amount of heterogeneity in the first TMA, while in the second TMA there was a clear signal indicating negative spatial association in stromal regions. These results suggest that hypoxia may contribute to immune exclusion, primarily mediated by effects in stroma.

Glioblastoma glycolytic signature predicts unfavorable prognosis, immunological heterogeneity, and ENO1 promotes microglia M2 polarization and cancer cell malignancy

Glioblastomas are the most malignant brain tumors, whose progress was promoted by aberrate aerobic glycolysis. The immune environment was highly engaged in glioblastoma formation, while its interaction with aerobic glycolysis remained unclear. Herein, we build a 7-gene Glycolytic Score (GS) by Elastic Net in the training set and two independent validating sets. The GS predicted malignant features and poor survival with good performances. Immune functional analyses and Cibersort calculation identified depressed T cells, B cells, natural killer cells immunity, and high immunosuppressive cell infiltration in the high-GS group. Also, high expressions of the immune-escape genes were discovered. Subsequently, the single-cell analyses validated the glycolysis-related immunosuppression. The functional results manifested the high-GS neoplastic cells' association with T cells, NK cells, and macrophage function regulation. The intercellular cross-talk showed strong associations between high-GS neoplastic cells and M2 macrophages/microglia in several immunological pathways. We finally confirmed that ENO1, the key gene of the GS, promoted M2 microglia polarization and glioblastoma cell malignant behaviors via immunofluorescence, clone formation, CCK8, and transwell rescue experiments. These results indicated the interactions between cancerous glycolysis and immunosuppression and glycolysis' role in promoting glioblastoma progression. Conclusively, we built a robust model and discovered strong interaction between GS and immune, shedding light on prognosis management improvement and therapeutic strategies development for glioblastoma patients.

Hypoxia, a Targetable Culprit to Counter Pancreatic Cancer Resistance to Therapy

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, and it is a disease of dismal prognosis. While immunotherapy has revolutionized the treatment of various solid tumors, it has achieved little success in PDAC. Hypoxia within the stroma-rich tumor microenvironment is associated with resistance to therapies and promotes angiogenesis, giving rise to a chaotic and leaky vasculature that is inefficient at shuttling oxygen and nutrients. Hypoxia and its downstream effectors have been implicated in immune resistance and could be contributing to the lack of response to immunotherapy experienced by patients with PDAC. Paradoxically, increasing evidence has shown hypoxia to augment genomic instability and mutagenesis in cancer, suggesting that hypoxic tumor cells could have increased production of neoantigens that can potentially enable their clearance by cytotoxic immune cells. Strategies aimed at relieving this condition have been on the rise, and one such approach opts for normalizing the tumor vasculature to reverse hypoxia and its downstream support of tumor pathogenesis. An important consideration for the successful implementation of such strategies in the clinic is that not all PDACs are equally hypoxic, therefore hypoxia-detection approaches should be integrated to enable optimal patient selection for achieving improved patient outcomes.

Single-cell RNA sequencing reveals the effects of chemotherapy on human pancreatic adenocarcinoma and its tumor microenvironment

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perform single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we find a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibit similar transcriptional responses to chemotherapy and do not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observe decreased ligand-receptor interactions in treated samples, particularly between TIGIT on CD8 + T cells and its receptor on cancer cells, and identify TIGIT as the major inhibitory checkpoint molecule of CD8 + T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy.

Chronic hypoxia is associated with transcriptomic reprogramming and increased genomic instability in cancer cells

Hypoxia afflicts the microenvironment of solid tumors fueling malignancy. We investigated the impact of long hypoxia exposure on transcriptional remodeling, tumor mutational burden (TMB), and genomic instability of cancer cells that were grouped based on their inherent sensitivity or resistance to hypoxia. A hypoxia score was used as a metric to distinguish between the most hypoxia-sensitive (hypoxia high (HH)), and most resistant (hypoxia low (HL)) cancer cells. By applying whole exome sequencing and microarray analysis, we showed that the HH group was indeed more sensitive to hypoxia, having significantly higher TMB (p = 0.03) and copy number losses (p = 0.03), as well as a trend of higher transcriptional response. Globally cells adapted by decreasing expression of genes involved in metabolism, proliferation, and protein maturation, and increasing alternative splicing. They accumulated mutations, especially frameshift insertions, and harbored increased copy number alterations, indicating increased genomic instability. Cells showing highest TMB simultaneously experienced a significant downregulation of DNA replication and repair and chromosomal maintenance pathways. A sixteen-gene common response to chronic hypoxia was put forth, including genes regulating angiogenesis and proliferation. Our findings show that chronic hypoxia enables survival of tumor cells by metabolic reprogramming, modulating proliferation, and increasing genomic instability. They additionally highlight key adaptive pathways that can potentially be targeted to prevent cancer cells residing in chronically hypoxic tumor areas from thriving.

Prognostic biomarkers of pancreatic cancer identified based on a competing endogenous RNA regulatory network

BACKGROUND

Pancreatic cancer is an insidious and heterogeneous malignancy with poor prognosis that is often locally unresectable. Therefore, determining the underlying mechanisms and effective prognostic indicators of pancreatic cancer may help optimize clinical management. This study was conducted to develop a prognostic model for pancreatic cancer based on a competing endogenous RNA (ceRNA) network.

METHODS

We obtained transcriptomic data and corresponding clinicopathological information of pancreatic cancer samples from The Cancer Genome Atlas (TCGA) database (training set). Based on the ceRNA interaction network, we screened candidate genes to build prediction models. Univariate Cox regression analysis was performed to screen for genes associated with prognosis, and least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive model. A receiver operating characteristic (ROC) curve was drawn, and the C-index was calculated to evaluate the accuracy of the prediction model. Furthermore, we downloaded transcriptomic data and related clinical information of pancreatic cancer samples from the Gene Expression Omnibus database (validation set) to evaluate the robustness of our prediction model.

RESULTS

Eight genes (ANLN, FHDC1, LY6D, SMAD6, ACKR4, RAB27B, AUNIP, and GPRIN3) were used to construct the prediction model, which was confirmed as an independent predictor for evaluating the prognosis of patients with pancreatic cancer through univariate and multivariate Cox regression analysis. By plotting the decision curve, we found that the risk score model is an independent predictor has the greatest impact on survival compared to pathological stage and targeted molecular therapy.

CONCLUSIONS

An eight-gene prediction model was constructed for effectively and independently predicting the prognosis of patients with pancreatic cancer. These eight genes identified show potential as diagnostic and therapeutic targets.

Heterogeneous cancer-associated fibroblasts: A new perspective for understanding immunosuppression in pancreatic cancer

Immunotherapy has shown promising efficacy in the treatment of a wide range of cancers; however, it has had little effect on pancreatic cancer. Cancer-associated fibroblasts (CAFs), the predominant mesenchymal cells present in the pancreatic cancer microenvironment, are powerful supporters of the malignant progression of pancreatic cancer. CAFs can modify the microenvironment, establish a refuge to aid cancer cells in immune escape by secreting large amounts of extracellular matrix, and produce soluble cytokines and exosomal vesicles. Hence, CAFs are important contributors to the failure of immunotherapy. Current in-depth studies of CAFs have shown that CAFs are a heterogeneous population of mesenchymal cells; therefore, the functional complexity of their populations needs in-depth explorations in future studies. This review summarizes how heterogeneous CAFs help cancer cells achieve immune escape and suggests potential directions for using CAFs as targets to address immune escape.

Construction of a hypoxia-derived gene model to predict the prognosis and therapeutic response of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most common cancer worldwide and has a poor prognosis in the advanced stage. Increasing evidence has shown that hypoxia contributes to genetic alterations that have essential effects on the occurrence and progression of cancers. However, the exact roles hypoxia-related genes play in HNSCC remain unclear. In this study, we downloaded the mRNA expression profiles and clinical data of patients with HNSCC from The Cancer Genome Atlas and Gene Expression Omnibus. Two molecular subtypes were identified based on prognostic hypoxia-related genes using the ConsensusClusterPlus method. ESTIMATE was used to calculate the immune score of each patient. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology were used for functional annotation. A prognostic risk model was generated by Cox regression and least absolute shrinkage and selection operator analysis. We identified two distinct molecular subtypes, cluster 1 and cluster 2, based on 200 hypoxia-related genes. Additionally, we identified three hypoxia-immune subgroups (hypoxia-high/immune-low, hypoxia-low/immune-high, and mixed subgroups). The hypoxia-high/immune-low group had the worst prognosis, while the hypoxia-low/immune-high group had the best prognosis. Patients in the hypoxia-low/immune-high group were more sensitive to anti-PD-L1 treatment and chemotherapy than those in the hypoxia-high/immune-low group. Furthermore, we constructed a prognostic risk model based on the differentially expressed genes between the hypoxia-immune subgroups. The survival analysis and time-dependent ROC analysis results demonstrated the good performance of the established 7-gene signature for predicting HNSCC prognosis. In conclusions, the constructed hypoxia-related model might serve as a promising biomarker for the diagnosis and prognosis of HNSCC, and it could predict immunotherapy and chemotherapy efficacy in HNSCC.

A New Hypoxia-Related Prognostic Risk Score (HPRS) Model Was Developed to Indicate Prognosis and Response to Immunotherapy for Lung Adenocarcinoma

Background

Hypoxia is a typical microenvironmental feature of most solid tumors, affecting a variety of physiological processes. We developed a hypoxia-related prognostic risk score (HPRS) model to reveal tumor microenvironment (TME) and predict prognosis of lung adenocarcinoma (LUAD).

Methods

LUAD sample expression data were from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) Cox regression identified hypoxia-related genes (HRGs) to create HPRS. The prognostic value, genetic mutation and TME, and therapeutic response of distinct HPRS groups were analyzed. Univariate and multivariate Cox regression analysis identified independent factors associated with the prognosis of LUAD. A decision tree based on HPRS and clinicopathological variables was established using the classification system based on decision tree algorithm. A nomogram was constructed with important clinical features and HPRS by the RMS package.

Results

A HPRS model with five HRGs was developed and verified in two separate cohorts of GEO. HPRS model divided patients with LUAD into two groups. High HPRS was related to high probability of genetic alterations. HPRS could predict the prognosis, TME, and sensitivity to immunotherapy/chemotherapy of LUAD. The decision tree defined four risk subgroups with significant OS differences. Nomogram with integrated HPRS and clinical features had acceptable accuracy in predicting LUAD prognosis.

Conclusions

A HPRS model was developed to evaluate prognosis, genetic alterations, TME, and response to immunotherapy, which may provide theoretical reference for the study of molecular mechanism of hypoxia in LUAD.

Development and validation of a hypoxia-stemness-based prognostic signature in pancreatic adenocarcinoma

Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive and fatal gastrointestinal malignancies with high morbidity and mortality worldwide. Accumulating evidence has revealed the clinical significance of the interaction between the hypoxic microenvironment and cancer stemness in pancreatic cancer progression and therapies. This study aims to identify a hypoxia-stemness index-related gene signature for risk stratification and prognosis prediction in PAAD.

Methods: The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm. Univariate Cox regression and LASSO regression analyses were then performed to establish a hypoxia-mRNAsi-related gene signature, and its prognostic performance was verified in both the TCGA-PAAD and GSE62452 corhorts by Kaplan-Meier and receiver operating characteristic (ROC) analyses. Additionally, we further validated the expression levels of signature genes using the TCGA, GTEx and HPA databases as well as qPCR experiments. Moreover, we constructed a prognostic nomogram incorporating the eight-gene signature and traditional clinical factors and analyzed the correlations of the risk score with immune infiltrates and immune checkpoint genes.

Results: The mRNAsi values of PAAD samples were significantly higher than those of normal samples (p &lt; 0.001), and PAAD patients with high mRNAsi values exhibited worse overall survival (OS). A novel prognostic risk model was successfully constructed based on the eight-gene signature comprising JMJD6, NDST1, ENO3, LDHA, TES, ANKZF1, CITED, and SIAH2, which could accurately predict the 1-, 3-, and 5-year OS of PAAD patients in both the training and external validation datasets. Additionally, the eight-gene signature could distinguish PAAD samples from normal samples and stratify PAAD patients into low- and high-risk groups with distinct OS. The risk score was closely correlated with immune cell infiltration patterns and immune checkpoint molecules. Moreover, calibration analysis showed the excellent predictive ability of the nomogram incorporating the eight-gene signature and traditional clinical factors.

Conclusion: We developed a hypoxia-stemness-related prognostic signature that reliably predicts the OS of PAAD. Our findings may aid in the risk stratification and individual treatment of PAAD patients.

A Novel Defined Hypoxia-Related Gene Signature for Prognostic Prediction of Patients With Ewing Sarcoma

The therapeutic strategy of Ewing sarcoma (EWS) remains largely unchanged over the past few decades. Hypoxia is reported to have an impact on tumor cell progression and is regarded as a novel potential therapeutic target in tumor treatment. This study aimed at developing a prognostic gene signature based on hypoxia-related genes (HRGs). EWS patients from GSE17674 in the GEO database were analyzed as a training cohort, and differently expressed HRGs between tumor and normal samples were identified. The univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analyses were used in this study. A total of 57 EWS patients from the International Cancer Genome Consortium (ICGC) database were set as the validation cohort. A total of 506 differently expressed HRGs between tumor and normal tissues were identified, among which 52 were associated with the prognoses of EWS patients. Based on 52 HRGs, EWS patients were divided into two molecular subgroups with different survival statuses. In addition, a prognostic signature based on 4 HRGs (WSB1, RXYLT1, GLCE and RORA) was constructed, dividing EWS patients into low- and high-risk groups. The 2-, 3- and 5-years area under the receiver operator characteristic curve of this signature was 0.913, 0.97 and 0.985, respectively. It was found that the survival rates of patients in the high-risk group were significantly lower than those in the low-risk group (p < 0.001). The risk level based on the risk score could serve as an independent clinical factor for predicting the survival probabilities of EWS patients. Additionally, antigen-presenting cell (APC) related pathways and T cell co-inhibition were differently activated in two risk groups, which may result in different prognoses. CTLA4 may be an effective immune checkpoint inhibitor to treat EWS patients. All results were verified in the validation cohort. This study constructed 4-HRGs as a novel prognostic marker for predicting survival in EWS patients.

miRNA Pattern in Hypoxic Microenvironment of Kidney Cancer—Role of PTEN

MicroRNAs are post-transcriptional regulators of gene expression, and disturbances of their expression are the basis of many pathological states, including cancers. The miRNA pattern in the context of tumor microenvironment explains mechanisms related to cancer progression and provides a potential target of modern therapies. Here we show the miRNA pattern in renal cancer focusing on hypoxia as a characteristic feature of the tumor microenvironment and dysregulation of PTEN, being a major tumor suppressor. Methods comprised the CRSPR/Cas9 mediated PTEN knockout in the Renca kidney cancer cell line and global miRNA expression analysis in both in vivo and in vitro (in normoxic and hypoxic conditions). The results were validated on human cancer models with distinct PTEN status. The increase in miR-210-3p in hypoxia was universal; however, the hypoxia-induced decrease in PTEN was associated with an increase in miR-221-3p, the loss of PTEN affected the response to hypoxia differently by decreasing miR-10b-5p and increasing miR-206-3p. In turn, the complete loss of PTEN induces miR-155-5p, miR-100-5p. Upregulation of miR-342-3p in knockout PTEN occurred in the context of the whole tumor microenvironment. Thus, effective identification of miRNA patterns in cancers must consider the specificity of the tumor microenvironment together with the mutations of key suppressors.

Robust Validation and Comprehensive Analysis of a Novel Signature Derived from Crucial Metabolic Pathways of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a dismal prognosis. PDAC have extensively reprogrammed metabolic characteristics influenced by interactions with normal cells, the effects of the tumor microenvironment and oncogene-mediated cell-autonomous pathways. In this study, we found that among all cancer hallmarks, metabolism played an important role in PDAC. Subsequently, a 16-gene prognostic signature was established with genes derived from crucial metabolic pathways, including glycolysis, bile acid metabolism, cholesterol homeostasis and xenobiotic metabolism (gbcx). The signature was used to distinguish overall survival in multiple cohorts from public datasets as well as a validation cohort followed up by us at Shanghai Cancer Center. Notably, the gbcx-related risk score (gbcxMRS) also accurately predicted poor PDAC subtypes, such as pure-basal-like and squamous types. At the same time, it also predicted PDAC recurrence. The gbcxMRS was also associated with immune cells, especially CD8 T cells, Treg cells. Furthermore, a high gbcxMRS may indicate high drug sensitivity to irinotecan and docetaxel and CTLA4 inhibitor immunotherapy. Taken together, these results indicate a robust and reproducible metabolic-related signature based on analysis of the overall pathogenesis of pancreatic cancer, which may have excellent prognostic and therapeutic implications for PDAC.

The Effect of Hypoxia and Hypoxia-Associated Pathways in the Regulation of Antitumor Response: Friends or Foes?

Hypoxia is an environmental stressor that is instigated by low oxygen availability. It fuels the progression of solid tumors by driving tumor plasticity, heterogeneity, stemness and genomic instability. Hypoxia metabolically reprograms the tumor microenvironment (TME), adding insult to injury to the acidic, nutrient deprived and poorly vascularized conditions that act to dampen immune cell function. Through its impact on key cancer hallmarks and by creating a physical barrier conducive to tumor survival, hypoxia modulates tumor cell escape from the mounted immune response. The tumor cell-immune cell crosstalk in the context of a hypoxic TME tips the balance towards a cold and immunosuppressed microenvironment that is resistant to immune checkpoint inhibitors (ICI). Nonetheless, evidence is emerging that could make hypoxia an asset for improving response to ICI. Tackling the tumor immune contexture has taken on an in silico, digitalized approach with an increasing number of studies applying bioinformatics to deconvolute the cellular and non-cellular elements of the TME. Such approaches have additionally been combined with signature-based proxies of hypoxia to further dissect the turbulent hypoxia-immune relationship. In this review we will be highlighting the mechanisms by which hypoxia impacts immune cell functions and how that could translate to predicting response to immunotherapy in an era of machine learning and computational biology.

Strategies for Remodeling the Tumor Microenvironment Using Active Ingredients of Ginseng-A Promising Approach for Cancer Therapy

The tumor microenvironment (TME) plays a key role in promoting the initiation and progression of tumors, leading to chemoradiotherapy resistance and immunotherapy failure. Targeting of the TME is a novel anti-tumor therapeutic approach and is currently a focus of anti-tumor research. Panax ginseng C. A. Meyer (ginseng), an ingredient of well-known traditional Asia medicines, exerts beneficial anti-tumor effects and can regulate the TME. Here, we present a systematic review that describes the current status of research efforts to elucidate the functions and mechanisms of ginseng active components (including ginsenosides and ginseng polysaccharides) for achieving TME regulation. Ginsenosides have variety effects on TME, such as Rg3, Rd and Rk3 can inhibit tumor angiogenesis; Rg3, Rh2 and M4 can regulate the function of immune cells; Rg3, Rd and Rg5 can restrain the stemness of cancer stem cells. Ginseng polysaccharides (such as red ginseng acidic polysaccharides and polysaccharides extracted from ginseng berry and ginseng leaves) can regulate TME mainly by stimulating immune cells. In addition, we propose a potential mechanistic link between ginseng-associated restoration of gut microbiota and the tumor immune microenvironment. Finally, we describe recent advances for improving ginseng efficacy, including the development of a nano-drug delivery system. Taken together, this review provides novel perspectives on potential applications for ginseng active ingredients as anti-cancer adjuvants that achieve anti-cancer effects by reshaping the tumor microenvironment.

Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma

BACKGROUND

Acidosis in the tumor microenvironment (TME) is involved in tumor immune dysfunction and tumor progression. We attempted to develop an acidosis-related index (ARI) signature to improve the prognostic prediction of pancreatic carcinoma (PC).

METHODS

Differential gene expression analyses of two public datasets (GSE152345 and GSE62452) from the Gene Expression Omnibus database were performed to identify the acidosis-related genes. The Cancer Genome Atlas-pancreatic carcinoma (TCGA-PAAD) cohort in the TCGA database was set as the discovery dataset. Univariate Cox regression and the Kaplan-Meier method were applied to screen for prognostic genes. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish the optimal model. The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm.

RESULTS

We identified 133 acidosis-related genes, of which 37 were identified as prognostic genes by univariate Cox analysis in combination with the Kaplan-Meier method (p values of both methods < 0.05). An acidosis-related signature involving seven genes (ARNTL2, DKK1, CEP55, CTSV, MYEOV, DSG2, and GBP2) was developed in TCGA-PAAD and further validated in GSE62452. Patients in the acidosis-related high-risk group consistently showed poorer survival outcomes than those in the low-risk group. The 5-year AUCs (areas under the curve) for survival prediction were 0.738 for TCGA-PAAD and 0.889 for GSE62452, suggesting excellent performance. The low-risk group in TCGA-PAAD showed a higher abundance of CD8+ T cells and activated natural killer cells and was predicted to possess an elevated proportion of immunotherapeutic responders compared with the high-risk counterpart.

CONCLUSIONS

We developed a reliable acidosis-related signature that showed excellent performance in prognostic prediction and correlated with tumor immune infiltration, providing a new direction for prognostic evaluation and immunotherapy management in PC.

The impact of hypoxia on immune state in cancer

Hypoxia is a known feature of solid tumors and a critical promoter of tumor hallmarks. Hypoxia influences tumor immunity in a way favoring immune evasion and resistance. Extreme hypoxia and aberrant hypoxia-inducible factor-1 (HIF-1) activity in tumor microenvironment (TME) is a drawback for effective immunotherapy. Infiltration and activity of CD8⁺ T cells is reduced in such condition, whereas regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) show high activities. Highly hypoxic TME also impairs maturation and activity of dendritic cell (DCs) and natural killer (NK) cells. In addition, the hypoxic TME positively is linked positively with metabolic changes in cells of immune system. These alterations are indicative of a need for hypoxia modulation as a complementary targeting strategy to go with immune checkpoint inhibitor (ICI) therapy.