Effects of Hypoxia in Intestinal Tumors on Immune Cell Behavior in the Tumor Microenvironment

Identification of SLC2A3 as a prognostic indicator correlated with the NF-κB/EMT axis and immune response in head and neck squamous cell carcinoma

SLC2A3 is an important member of the glucose transporter superfamily. It has been recently suggested that upregulation of SLC2A3 is associated with poor survival and acts as a prognostic marker in a variety of tumors. Unfortunately, the prognostic role of SLC2A3 in head and neck squamous cell carcinoma (HNSC) is less known. In the present study, we analyzed SLC2A3 expression in HNSC and its correlation with prognosis using TCGA and GEO databases. The results showed that SLC2A3 mRNA expression was higher in HNSC compared with adjacent normal tissues, which was validated with our 9 pairs of HNSC specimens. Moreover, high SLC2A3 expression predicted poor prognosis in HNSC patients. Mechanistically, GSEA revealed that high expression of SLC2A3 was enriched in epithelial-mesenchymal transition (EMT) and NF-κB signaling. In HNSC cell lines, SLC2A3 knockdown inhibited cell proliferation and migration. In addition, NF-κB P65 and EMT-related gene expression was suppressed upon SLC2A3 knockdown, indicating that SLC2A3 may play a preeminent role in the progression of HNSC through the NF-κB/EMT axis. Meanwhile, the expression of SLC2A3 was negatively correlated with immune cells, suggesting that SLC2A3 may be involved in the immune response in HNSC. The correlation between SLC2A3 expression and drug sensitivity was further assessed. In conclusion, our study demonstrated that SLC2A3 could predict the prognosis of HNSC patients and mediate the progression of HNSC via the NF-κB/EMT axis and immune responses.

The mitochondrial energy metabolism pathway-related signature predicts prognosis and indicates immune microenvironment infiltration in osteosarcoma

BACKGROUND

Abnormalities in the mitochondrial energy metabolism pathways are closely related to the occurrence and development of many cancers. Furthermore, abnormal genes in mitochondrial energy metabolism pathways may be novel targets and biomarkers for the diagnosis and treatment of osteosarcoma. In this study, we aimed to establish a mitochondrial energy metabolism-related gene signature for osteosarcoma prognosis.

METHODS

We first obtained differentially expressed genes based on the metastatic status of 84 patients with osteosarcoma from the TARGET database. After Venn analysis of differentially expressed genes and mitochondrial energy metabolism pathway-related genes (MMRGs), 2 key genes were obtained using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis. Next, we used these 2 genes to establish a prognostic signature. Subsequent analyses elucidated the correlation between these 2 key genes with clinical features and 28 types of immune cells. Pathway changes in osteosarcoma pathogenesis under different metastatic states were clarified using gene set enrichment analysis (GSEA) of differentially expressed genes.

RESULTS

A gene signature composed of 2 key prognosis-related genes (KCNJ5 and PFKFB2) was identified. A risk score was calculated based on the gene signature, which divided osteosarcoma patients into low- or high-risk groups that showed good and poor prognosis, respectively. High expression of these 2 key genes is associated with low-risk group in patients with osteosarcoma. We constructed an accurate nomogram to help clinicians assess the survival time of patients with osteosarcoma. The results of immune cell infiltration level showed that the high-risk group had lower levels of immune cell infiltration. GSEA revealed changes in immune regulation and hypoxia stress pathways in osteosarcoma under different metastatic states.

CONCLUSION

Our study identified an excellent gene signature that could be helpful in improving the prognosis of patients with osteosarcoma.

Natural killer cell-related prognosis signature predicts immune response in colon cancer patients

Background: Natural killer (NK) cells are crucial components of the innate immune system that fight tumors and viral infections. Patients with colorectal cancer (CRC) have a poor prognosis, and immunotherapeutic tools play a key role in the treatment of CRC. Methods: Public data on CRC patients was collected from the TCGA and the GEO databases. Tissue data of CRC patients were collected from Guangxi Medical University Affiliated Cancer Hospital. An NK-related prognostic model was developed by the least absolute shrinkage and selection operator (LASSO) and Cox regression method. Validation data were collected from different clinical subgroups and an external independent validation cohort to verify the model's accuracy. In addition, multiple external independent immunotherapy datasets were collected to further examine the value of NK-related risk scores (NKRS) in the prediction of immunotherapy response. Potential biological functions of key genes were examined by methods of cell proliferation, apoptosis and Western blotting. Results: A novel prognostic model for CRC patients based on NK-related genes was developed and NKRS was generated. There was a significantly poorer prognosis among the high-NKRS group. Based on immune response prediction, patients with low NKRS may be more suitable for immunotherapy and they are more sensitive to immunotherapy. The proliferation rate of CRC cells was significantly reduced and apoptosis of CRC cells was increased after SLC2A3 was knocked down. SLC2A3 was also found to be associated with the TGF-β signaling pathway. Conclusion: NKRS has potential applications for predicting prognostic status and response to immunotherapy in CRC patients. SLC2A3 has potential as a therapeutic target for CRC.

Identification of Hypoxia-Associated Signature in Colon Cancer to Assess Tumor Immune Microenvironment and Predict Prognosis Based on 14 Hypoxia-Associated Genes

Purpose

Colon cancer is the main malignant tumor of the digestive tract. Hypoxia is highly related to the occurrence, progression and tumor immune microenvironment (TIME) of cancer. The aim of this study was to identify a hypoxia-associated signature with high accuracy for predicting the prognosis and TIME of colon cancer.

Methods

Download colon cancer data from the GEO and TCGA databases. A novel hypoxia risk model was identified to predict the prognosis of colon cancer patients. Subsequently, GSEA, TIME and mutation analysis were performed in the hypoxia high and low risk score groups. Finally, the signature gene ANKZF1 was selected for functional verification at the cellular level.

Results

A novel hypoxia risk model was identified. The risk score was significantly associated with poorer overall survival in colon cancer, and could be used as an independent prognostic factor for colon cancer. GSEA analysis found that the processes related to stimulate tumor proliferation and anti-apoptosis were significantly enriched in the hypoxia high risk score group. The expression of immunosuppressive cells and most immune checkpoints in the high risk score group was significantly higher than that in the low risk score group. In vitro cell experiments showed that knockdown the expression of ANKZF1 could inhibit the proliferation, migration and invasion of colon cancer cells.

Conclusion

Hypoxia plays an important role in evaluating the TIME and predicting the prognosis of colon cancer.

N6-methyladenosine related gene expression signatures for predicting the overall survival and immune responses of patients with colorectal cancer

N6-methyladenosine (m6A) modification has been demonstrated to exhibit a crucial prognostic effect on colorectal cancer (CRC). Nonetheless, potential mechanism of m6A in survival rate and immunotherapeutic response remains unknown. Here we investigated the genes associated with m6A regulators and developed a risk score for predicting the overall survival (OS) of CRC patients. RNA-seq transcriptomic profiling data of COAD/READ samples were obtained from The Cancer Genome Atlas (TCGA) database. Absolute Shrinkage and Selection Operator (LASSO)- Cox regression analysis was conducted to identify the m6A-related gene expression signatures and the selected genes were inputted into stepwise regression to develop a prognostic risk score in TCGA, and its predictive performance of CRC survival was further validated in Gene Expression Omnibus (GEO) datasets. According to our results, the risk score comprising 18 m6A-related mRNAs was significantly associated with CRC survival in both TCGA and GEO datasets. And the stratified analysis also confirmed that high-risk score acted as a poor factor in different age, sex, T stage, and tumour, node, metastasis (TNM) stages. The m6A-related prognostic score in combination with clinical characteristics yielded time-dependent area under the receiver operating characteristic curve (AUCs) of 0.85 (95%CI: 0.79-0.91), 0.84 (95%CI: 0.79-0.90) and 0.80 (95%CI: 0.71-0.88) for the prediction of the 1-, 3-, 5-year OS of CRC in TCGA cohort. Furthermore, mutation of oncogenes occurred more frequently in the high-risk group and the composition of immune cells in tumour microenvironment (TME) was significantly distinct between the low- and high-risk groups. The low-risk group had a lower microsatellite instability (MSI) score, T-cell exclusion score and dysfunction score, implying that low-risk patients may have a better immunotherapy response than high-risk patients. In summary, a prognostic risk score derived from m6A-related gene expression signatures could serve as a potential prognostic predictor for CRC survival and indicator for predicting immunotherapy response in CRC patients.

Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction

BACKGROUND

Currently, patients with diabetic erectile dysfunction (DMED) were not satisfied with the effects of first-line phosphodiesterase type 5 inhibitors (PDE5Is). Hence, this paper was designed to mine hub biomarkers in DMED and explore its potential mechanisms.

METHODS

Gene expression matrix of DMED was downloaded from the gene expression omnibus (GEO; GSE2457) dataset. The top 20 genes were selected based on the connectivity degrees in protein-protein interaction (PPI) network. Functional enrichment analysis was utilized to reveal DMED-related signaling pathways. We also explored the roles of immunity, m6A, ferroptosis, or cuproptosis in DMED and constructed Sprague Dawley (SD) rats DMED model to verify gene expressions by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

Based on the threshold, a total of 122 differently expressed genes (DEGs) were identified in DMED, including 39 up-regulated and 83 down-regulated genes. Functional enrichment analysis implied that these DEGs were significantly enriched in peroxisome proliferator-activated receptors, ferroptosis, hypoxia-inducible factor 1 signaling pathways, and so on. SD rats DMED model was also successfully established by us and validated by intracavernous pressure/mean arterial pressure, Masson's trichrome staining, and immunohistochemical analysis. We further verified the expression of these top 20 genes from the PPI network by qRT-PCR in the SD rats DMED model and finally identified Sparc, Lox, Srebf1, and Mmp3 as hub biomarkers (all p < 0.05). As for immunity and cuproptosis, our analysis indicated that DMED had nothing to do with them (all p > 0.05). Actually, DMED was markedly associated with m6A regulators and ferroptosis.

CONCLUSIONS

We identified Sparc, Lox, Srebf1, and Mmp3 as potential hub biomarkers in the SD rats DMED model for future drug development and found its significant associations with m6A regulators and ferroptosis, but not with immunity or cuproptosis.

Predictive Models for Colon Adenocarcinoma Diagnosis, Prognosis, and Immune Microenvironment Based on 2 Hypoxia-Related Genes: KDM3A and ENO3

Background: Hypoxia is known to play a critical role in tumor occurrence, progression, prognosis, and therapy resistance. However, few studies have investigated hypoxia markers for diagnosing and predicting prognosis in colon adenocarcinoma (COAD). This study aims to identify a hypoxia genes-based biomarker for predicting COAD patients' prognosis and response to immunotherapy on an individual basis. Methods: Hypoxia-related genes were extracted from the Molecular Signatures Database. Gene expression, clinical data, and mutation data of COAD were collected retrospectively from the Cancer Genome Atlas, the Gene Expression Omnibus, and the International Cancer Genome Consortium databases. Univariate and multivariate cox regression, and the least absolute shrinkage and selection operator method were used to select the genes most associated with the prognosis of COAD patients. Kaplan-Meier survival analysis, receiver operating characteristic curves, calibration curves, and decision curve analyses were performed to validate the efficacy of the signature in predicting the prognosis of COAD patients. EdU incorporation assays, cell survival assays, western blot assays, and trans-well invasion assays were performed to further confirm the function of the screened genes in tumorigenesis. Results: ENO3 and KDM3A were identified as key genes for constructing prognostic and diagnostic signatures, which were found to be independent risk factors for predicting the prognosis and diagnosis of COAD patients. Using these signatures, COAD patients could be stratified into high-risk and low-risk groups, with the latter exhibiting better overall survival outcomes. Moreover, the high-risk group displayed elevated levels of immune checkpoint genes and tumor mutation burden, indicating that these patients may benefit from immune checkpoint inhibitor therapy. Conclusion: The signature developed in this study demonstrates excellent efficacy in prognosticating the outcomes of COAD patients. Moreover, it can serve as a valuable tool for clinicians to identify COAD patients who are suitable for ICI therapy.

Prediction of immunotherapy efficacy and immunomodulatory role of hypoxia in colorectal cancer

Immunotherapy has been used in the clinical treatment of colorectal cancer (CRC); however, most patients fail to achieve satisfactory survival benefits. Biomarkers with high specificity and sensitivity are being increasingly developed to predict the efficacy of CRC immunotherapy. In addition to DNA alteration markers, such as microsatellite instability/mismatch repair and tumor mutational burden, immune cell infiltration and immune checkpoints (ICs), epigenetic changes and no-coding RNA, and gut microbiomes all show potential predictive ability. Recently, the hypoxic tumor microenvironment (TME) has been identified as a key factor mediating CRC immune evasion and resistance to treatment. Hypoxia-inducible factor-1α is the central transcription factor in the hypoxia response that drives the expression of a vast number of survival genes by binding to the hypoxia response element in cancer and immune cells in the TME. Hypoxia regulates angiogenesis, immune cell infiltration and activation, expression of ICs, and secretion of various immune molecules in the TME and is closely associated with the immunotherapeutic efficacy of CRC. Currently, various agents targeting hypoxia have been found to improve the TME and enhance the efficacy of immunotherapy. We reviewed current markers commonly used in CRC to predict therapeutic efficacy and the mechanisms underlying hypoxia-induced angiogenesis and tumor immune evasion. Exploring the mechanisms by which hypoxia affects the TME will assist the discovery of new immunotherapeutic predictive biomarkers and development of more effective combinations of agents targeting hypoxia and immunotherapy.

GPC1 promotes the growth and migration of colorectal cancer cells through regulating the TGF-β1/SMAD2 signaling pathway

In this study, we analyzed GPC family genes in colorectal cancer (CRC) and the possible mechanism of action of GPC1 in CRC. CRC patient data were extracted from The Cancer Genome Atlas, and the prognostic significance of GPC1 expression and its association with clinicopathological features were identified by Kolmogorov–Smirnov test. CRC patients with high GPC1 expression had poor overall survival compared with patients with low GPC1 expression. In vitro experiments demonstrated that knockdown of GPC1 significantly inhibited the proliferation and migration and promoted cell apoptosis in CRC cell lines. Gene Ontology analysis of differential genes indicated that GPC1 may influence the TGF-β1 signaling pathway. Additional experiments revealed that silencing GPC1 suppressed the levels of TGF-β1 and p-SMAD2 but increased the expression of SMAD2. Taken together, these findings suggest that GPC1 may function as a tumor promoter in CRC cells through promoting TGF-β signaling pathway. Our results also indicate that GPC1 may serve as a critical effector in CRC progression and a new potential target for CRC therapy.

Transmembrane Protein-Based Risk Model and H3K4me3 Modification Characteristics in Lung Adenocarcinoma

The role and mechanism of transmembrane proteins (TMEMs) in tumorigenesis remain unclear. Based on 4 independent cohorts containing 1,208 cases, we identified 3 TMEMs (TMEM273, TMEM164, and TMEM125), which were used to construct a risk model to predict the prognosis of LUAD. The two patterns based on the risk score exhibited a high degree of consistency with the characteristics of immune cell infiltration and epigenetic distribution. Patients with a low-risk score, characterized by an increased activation of immunity, H3K4me3 modification, tumor cell apoptosis, chemokine secretion, and TMB, had better disease-free survival (DFS) and overall survival (OS). Obvious immunosuppression, increased epithelial–mesenchymal transition, a low H3K4me3 level, shortened cell cycle, and accelerated cell division manifested in high-risk patients, with poorer DFS and OS. The model showed a better prognostic value than the tumor immune dysfunction and exclusion score. Correlation analysis told us that patients with high scores were suitable for treatment with CD276 inhibitors for their higher levels of CD276 expression. The risk score had a strong negative correlation with HAVCR2 and ICOS among patients with EGFR-WT, KRAS-WT, STK11-WT, or TP53-MUT, and patients with these mutation types with low scores were suitable for treatment with HAVCR2 or ICOS inhibitors. This work comprehensively analyzed the role and mechanism of TMEMs in LUAD and revealed the characteristics of histone methylation modification. The TMEM-based signature gave us deep insight into immune cell infiltration profiles and provided an individualized immunotherapy strategy.

Establishment and Analysis of Hypoxia-Related Model in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most common cancers in the world. Hypoxia is closely related to immunity in tumor microenvironment and also affects the prognosis of patients. However, there is still a lack of articles related to tumor hypoxia in oral squamous cell carcinoma. Therefore, we aimed to develop a hypoxia model for future application in patient prognosis analysis and immunotherapy. The transcriptome and survival information of OSCC were downloaded from GEO database. The Cox regression model of the lasso method was used to identify prognostic genes and develop gene characteristics based on hypoxia immunity. According to the median risk value, the patients were divided into high-risk group and low-risk group. Then, the estimated algorithm was used to estimate the relationship between hypoxia and immune status. At the same time, we evaluated the correlation and expression differences of immune-related genes between different risk groups. By using the lasso model, we identified two genes, including PFKP and SERPINE1, to construct gene signatures for risk stratification. We observed that both genes were highly expressed in the high-risk group, which was not conducive to the prognosis of the tumor. In addition, in the analysis of the degree of immune infiltration, we observed that there were differences in the content of a variety of immune cells between the two groups. It can be seen that there were great differences in the immune cells constituting the tumor microenvironment in oral squamous cell carcinoma. There remain significant differences in the expression levels of multitudinous immune-related genes. These immune-related genes include CCL chemokines, Chemokine (C-X-C motif) ligand (CXCL), CD antigens, HSP family, interferon family, and interleukin family. The hypoxia-immune-based gene signature represents a promising tool for risk stratification tool in oral squamous cell carcinoma cancer. It might serve as a prognostic classifier for clinical decision-making regarding individualized prognostication and treatment and follow-up scheduling.

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.

A Prognostic Model Using Immune-Related Genes for Colorectal Cancer

There is evidence suggesting that immune genes play pivotal roles in the development and progression of colorectal cancer (CRC). Colorectal carcinoma patient data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) were randomly classified into a training set, a test set, and an external validation set. Differentially expressed gene (DEG) analyses, univariate Cox regression, and the least absolute shrinkage and selection operator (LASSO) were used to identify survival-associated immune genes and develop a prognosis model. Receiver operating characteristic (ROC) analysis and principal component analysis (PCA) were used to evaluate the discrimination of the risk models. The model genes predicted were verified using the Human Protein Atlas (HPA) databases, colorectal cell lines, and fresh CRC and adjacent tissues. To understand the relationship between IRGs and immune invasion and the TME, we analyzed the content of immune cells and scored the TME using CIBERSORT and ESTIMATE algorithms. Finally, we predicted the potential sensitive chemotherapeutic drugs in different risk score groups by the Genomics of Drug Sensitivity in Cancer (GDSC). A total of 491 IRGs were screened, and 14 IRGs were identified to be significantly related to overall survival (OS) and applied to construct an immune-related gene (IRG) prognostic signature (IRGSig) for CRC patients. Calibration plots showed that nomograms have powerful predictive ability. PCA and ROC analysis further verified the predictive value of this fourteen-gene prognostic model in three independent databases. Furthermore, we discovered that the tumor microenvironment changed significantly during the tumor development process, from early to middle to late stage, which may be an essential factor for tumor deterioration. Finally, we selected six commonly used chemotherapeutic drugs that have the potential to be useful in the treatment of CRC. Altogether, immune genes were used to construct a prognosis model for CRC patients, and a variety of methods were used to test the accuracy of this model. In addition, we explored the immune mechanisms of CRC through immune cell infiltration and TME in CRC. Furthermore, we assessed the therapeutic sensitivity of many commonly used chemotherapeutic medicines in individuals with varying risk factors. Finally, the immune risk model and immune mechanism of CRC were thoroughly investigated in this paper.

Polydopamine-coated UiO-66 nanoparticles loaded with perfluorotributylamine/tirapazamine for hypoxia-activated osteosarcoma therapy

Background

Hypoxia is a characteristic of solid tumors that can lead to tumor angiogenesis and early metastasis, and addressing hypoxia presents tremendous challenges. In this work, a nanomedicine based on oxygen-absorbing perfluorotributylamine (PFA) and the bioreductive prodrug tirapazamine (TPZ) was prepared by using a polydopamine (PDA)-coated UiO-66 metal organic framework (MOF) as the drug carrier.

Results

The results showed that TPZ/PFA@UiO-66@PDA nanoparticles significantly enhanced hypoxia, induced cell apoptosis in vitro through the oxygen-dependent HIF-1α pathway and decreased oxygen levels in vivo after intratumoral injection. In addition, our study demonstrated that TPZ/PFA@UiO-66@PDA nanoparticles can accumulate in the tumor region after tail vein injection and effectively inhibit tumor growth when combined with photothermal therapy (PTT). TPZ/PFA@UiO-66@PDA nanoparticles increased HIF-1α expression while did not promote the expression of CD31 in vivo during the experiment.

Conclusions

By using TPZ and PFA and the enhanced permeability and retention effect of nanoparticles, TPZ/PFA@UiO-66@PDA can target tumor tissues, enhance hypoxia in the tumor microenvironment, and activate TPZ. Combined with PTT, the growth of osteosarcoma xenografts can be effectively inhibited.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-01013-0.