A Transcriptional Signature of PDGF-DD Activated Natural Killer Cells Predicts More Favorable Prognosis in Low-Grade Glioma

Regulation of KLRC and Ceacam gene expression by miR-141 supports cell proliferation and metastasis in cervical cancer cells

INTRODUCTION

MicroRNAs (miRNAs) are single RNA molecules that act as global regulators of gene expression in mammalian cells and thus constitute attractive targets in treating cancer. Here we aimed to investigate the possible involvement of miRNA-141 (miR-141) in cervical cancer and to identify its potential targets in cervical cancer cell lines.

METHODS

The level of miR-141 in HeLa and C-33A cells has been assessed using the quantitative real-time PCR (qRT-PCR). A new miR-141 construct has been performed in a CMV promoter vector tagged with GFP. Using microarray analysis, we identified the potentially regulated genes by miR-141 in transfected HeLa cells. The protein profile of killer-like receptor C1 (KLRC1), KLRC3, carcinoembryonic antigen-related cell adhesion molecule 3 (CAM3), and CAM6 was investigated in HeLa cells transfected with either an inhibitor, antagonist miR-141, or miR-141 overexpression vector using immunoblotting and flow cytometry assay. Finally, ELISA assay has been used to monitor the produced cytokines from transfected HeLa cells.

RESULTS

The expression of miR-141 significantly increased in HeLa and C-33A cells compared to the normal cervical HCK1T cell line. Transfection of HeLa cells with an inhibitor, antagonist miR-141, showed a potent effect on cancer cell viability, unlike the transfection of miR-141 overexpression vector. The microarray data of HeLa cells overexpressed miR-141 provided a hundred of downregulated genes, including KLRC1, KLRC3, CAM3, and CAM6. KLRC1 and KLRC3 expression profiles markedly depleted in HeLa cells transfected with miR-141 overexpression accompanied by decreasing interleukin 8 (IL-8), indicating the role of miR-141 in avoiding programmed cells death in HeLa cells. Likewise, CAM3 and CAM6 expression reduced markedly in miR-141 transduced cells accompanied by an increasing level of transforming growth factor beta (TGF-β), indicating the impact of miR-141 in cancer cell migration. The IntaRNA program and miRWalk were used to check the direct interaction and potential binding sites between miR-141 and identified genes. Based on this, the seeding regions of each potential target was cloned upstream of the luciferase reporter gene in the pGL3 control vector. Interestingly, the luciferase activities of constructed vectors were significantly decreased in HeLa cells pre-transfected with miR-141 overexpression vector, while increasing enormously in cells pre-transfected with miR-141 specific inhibitor.

CONCLUSION

Together, these data uncover an efficient miR-141-based mechanism that supports cervical cancer progression and identifies miR-141 as a credible therapeutic target.

Cuprotosis clusters predict prognosis and immunotherapy response in low-grade glioma

Cuprotosis, an emerging mode of cell death, has recently caught the attention of researchers worldwide. However, its impact on low-grade glioma (LGG) patients has not been fully explored. To gain a deeper insight into the relationship between cuprotosis and LGG patients' prognosis, we conducted this study in which LGG patients were divided into two clusters based on the expression of 18 cuprotosis-related genes. We found that LGG patients in cluster A had better prognosis than those in cluster B. The two clusters also differed in terms of immune cell infiltration and biological functions. Moreover, we identified differentially expressed genes (DEGs) between the two clusters and developed a cuprotosis-related prognostic signature through the least absolute shrinkage and selection operator (LASSO) analysis in the TCGA training cohort. This signature divided LGG patients into high- and low-risk groups, with the high-risk group having significantly shorter overall survival (OS) time than the low-risk group. Its predictive reliability for prognosis in LGG patients was confirmed by the TCGA internal validation cohort, CGGA325 cohort and CGGA693 cohort. Additionally, a nomogram was used to predict the 1-, 3-, and 5-year OS rates of each patient. The analysis of immune checkpoints and tumor mutation burden (TMB) has revealed that individuals belonging to high-risk groups have a greater chance of benefiting from immunotherapy. Functional experiments confirmed that interfering with the signature gene TNFRSF11B inhibited LGG cell proliferation and migration. Overall, this study shed light on the importance of cuprotosis in LGG patient prognosis. The cuprotosis-related prognostic signature is a reliable predictor for patient outcomes and immunotherapeutic response and can help to develop new therapies for LGG.

Exploring the prognostic potential of m6A methylation regulators in low-grade glioma: implications for tumor microenvironment modulation

BACKGROUND

The biological behavior of low-grade glioma (LGG) is significantly affected by N6-methyladenosine (m6A) methylation, an essential epigenetic alteration. Therefore, it is crucial to create a prognostic model for LGG by utilizing genes that regulate m6A methylation.

METHODS

Using TCGA and GTEx databases. We examined m6A modulator levels in LGG and normal tissues, and investigated PD-L1 and PD-1 expression, immune scores, immune cell infiltration, tumor immune microenvironment (TIME) and potential underlying mechanisms in different LGG clusters. We also performed immunohistochemistry and RT-qPCR to identify essential m6A adjustment factor.

RESULTS

The results showed that m6A regulatory element expression was significantly increased in LGG tissues and was significantly associated with TMIE. A substantial increase in PD-L1 and PD-1 levels in LGG tissues and high-risk cohorts was observed. PD-L1 expression was positively correlated with FTO, ZCCHC4, and HNRNPD, whereas PD-1 expression was negatively correlated with FTO, ZC3H7B, and HNRNPD. The prognostic signature created using regulators of m6A RNA methylation was shown to be strongly associated with the overall survival of LGG patients, and FTO and ZCCHC4 were confirmed as independent prognostic markers by clinical samples. Furthermore, the results revealed different TIME characteristics between the two groups of patients, indicating disrupted signaling pathways associated with LGG.

CONCLUSION

Our results present that the m6A regulators play vital role in regulating PD-L1/PD-1 expression and the infiltration of immune cells, thereby exerting a sizable impact on the TIME of LGG. Therefore, m6A regulators have precise predictive value in the prognosis of LGG.

Radiogenomic landscape: Assessment of specific phagocytosis regulators in lower-grade gliomas

Genome-wide CRISPR-Cas9 knockout screens have emerged as a powerful method for identifying key genes driving tumor growth. The aim of this study was to explore the phagocytosis regulators (PRs) specifically associated with lower-grade glioma (LGG) using the CRISPR-Cas9 screening database. Identifying these core PRs could lead to novel therapeutic targets and pave the way for a non-invasive radiogenomics approach to assess LGG patients' prognosis and treatment response. We selected 24 PRs that were overexpressed and lethal in LGG for analysis. The identified PR subtypes (PRsClusters, geneClusters, and PRs-score models) effectively predicted clinical outcomes in LGG patients. Immune response markers, such as CTLA4, were found to be significantly associated with PR-score. Nine radiogenomics models using various machine learning classifiers were constructed to uncover survival risk. The area under the curve (AUC) values for these models in the test and training datasets were 0.686 and 0.868, respectively. The CRISPR-Cas9 screen identified novel prognostic radiogenomics biomarkers that correlated well with the expression status of specific PR-related genes in LGG patients. These biomarkers successfully stratified patient survival outcomes and treatment response using The Cancer Genome Atlas (TCGA) database. This study has important implications for the development of precise clinical treatment strategies and holds promise for more accurate therapeutic approaches for LGG patients in the future.

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

The role of angiogenic growth factors in the immune microenvironment of glioma

Angiogenic growth factors (AGFs) are a class of secreted cytokines related to angiogenesis that mainly include vascular endothelial growth factors (VEGFs), stromal-derived factor-1 (SDF-1), platelet-derived growth factors (PDGFs), fibroblast growth factors (FGFs), transforming growth factor-beta (TGF-β) and angiopoietins (ANGs). Accumulating evidence indicates that the role of AGFs is not only limited to tumor angiogenesis but also participating in tumor progression by other mechanisms that go beyond their angiogenic role. AGFs were shown to be upregulated in the glioma microenvironment characterized by extensive angiogenesis and high immunosuppression. AGFs produced by tumor and stromal cells can exert an immunomodulatory role in the glioma microenvironment by interacting with immune cells. This review aims to sum up the interactions among AGFs, immune cells and cancer cells with a particular emphasis on glioma and tries to provide new perspectives for understanding the glioma immune microenvironment and in-depth explorations for anti-glioma therapy.

Combining bulk and single-cell RNA-sequencing data to develop an NK cell-related prognostic signature for hepatocellular carcinoma based on an integrated machine learning framework

BACKGROUND

The application of molecular targeting therapy and immunotherapy has notably prolonged the survival of patients with hepatocellular carcinoma (HCC). However, multidrug resistance and high molecular heterogeneity of HCC still prevent the further improvement of clinical benefits. Dysfunction of tumor-infiltrating natural killer (NK) cells was strongly related to HCC progression and survival benefits of HCC patients. Hence, an NK cell-related prognostic signature was built up to predict HCC patients' prognosis and immunotherapeutic response.

METHODS

NK cell markers were selected from scRNA-Seq data obtained from GSE162616 data set. A consensus machine learning framework including a total of 77 algorithms was developed to establish the gene signature in TCGA-LIHC data set, GSE14520 data set, GSE76427 data set and ICGC-LIRI-JP data set. Moreover, the predictive efficacy on ICI response was externally validated by GSE91061 data set and PRJEB23709 data set.

RESULTS

With the highest C-index among 77 algorithms, a 11-gene signature was established by the combination of LASSO and CoxBoost algorithm, which classified patients into high- and low-risk group. The prognostic signature displayed a good predictive performance for overall survival rate, moderate to high predictive accuracy and was an independent risk factor for HCC patients' prognosis in TCGA, GEO and ICGC cohorts. Compared with high-risk group, low-risk patients showed higher IPS-PD1 blocker, IPS-CTLA4 blocker, common immune checkpoints expression but lower TIDE score, which indicated low-risk patients might be prone to benefiting from ICI treatment. Moreover, a real-world cohort, PRJEB23709, also revealed better immunotherapeutic response in low-risk group.

CONCLUSIONS

Overall, the present study developed a gene signature based on NK cell-related genes, which offered a novel platform for prognosis and immunotherapeutic response evaluation of HCC patients.

Natural killer cell-related prognostic risk model predicts prognosis and treatment outcomes in triple-negative breast cancer

Background

Natural killer (NK) cells are crucial to the emergence, identification, and prognosis of cancers. The roles of NK cell-related genes in the tumor immune microenvironment (TIME) and immunotherapy treatment are unclear. Triple-negative breast cancer (TNBC) is a highly aggressive malignant tumor. Hence, this study was conducted to develop a reliable risk model related to NK cells and provide a novel system for predicting the prognosis of TNBC.

Methods

NK cell-related genes were collected from previous studies. Based on TCGA and GEO database, univariate and LASSO cox regression analysis were used to establish the NK cell-related gene signature. The patients with TNBC were separated to high-risk and low-risk groups. After that, survival analysis was conducted and the responses to immunotherapies were evaluated on the basis of the signature. Moreover, the drug sensitivity of some traditional chemotherapeutic drugs was assessed by using the "oncoPredict" R package. In addition, the expression levels of the genes involved in the signature were validated by using qRT-PCR in TNBC cell lines.

Results

The patients with TNBC were divided into high- and low-risk groups according to the median risk score of the 5-NK cell-related gene signature. The low-risk group was associated with a better clinical outcome. Besides, the differentially expressed genes between the different risk groups were enriched in the biological activities associated with immunity. The tumor immune cells were found to be highly infiltrated in the low-risk groups. In accordance with the TIDE score and immune checkpoint-related gene expression analysis, TNBC patients in the low-risk groups were suggested to have better responses to immunotherapies. Eventually, some classical anti-tumor drugs were shown to be less effective in high-risk groups than in low-risk groups.

Conclusion

The 5-NK cell-related gene signature exhibit outstanding predictive performance and provide fresh viewpoints for evaluating the success of immunotherapy. It will provide new insights to achieve precision and integrated treatment for TNBC in the future.

Identification of natural killer cell-related characteristics to predict the clinical prognosis and immune microenvironment of patients with low-grade glioma

BACKGROUND

Individuals with low-grade glioma (LGG) have a dismal prognosis, and most patients will eventually progress to high-grade disease. Therefore, it is crucial to accurately determine their prognoses.

METHODS

Seventy-nine NK cell genes were downloaded from the LM22 database and univariate Cox regression analysis was utilized to detect NK cell-related genes affecting prognosis. Molecular types were established for LGG using the "ConsensusClusterPlus" R package. The results from a functional enrichment analysis and the immune microenvironment were intensively explored to determine molecular heterogeneity and immune characteristics across distinct subtypes. Furthermore, a RiskScore model was developed and verified using expression profiles of NK cells, and a nomogram consisting of the RiskScore model and clinical traits was constructed. Moreover, pan-cancer traits of NK cells were also investigated.

RESULTS

The C1 subtype included the greatest amount of immune infiltration and the poorest prognosis among well-established subtypes. The majority of enriched pathways were those involved in tumor progression, including epithelial-mesenchymal transition and cell cycle pathways. Differentially expressed genes among distinct subtypes were determined and used to develop a novel RiskScore model. This model was able to distinguish low-risk patients with LGG from those with high-risk disease. An accurate nomogram including the RiskScore, disease grade and patient's age was constructed to predict clinical outcomes of LGG patients. Finally, a pan-cancer analysis further highlighted the crucial roles of NK cell-related genes in the tumor microenvironment.

CONCLUSIONS

An NK cell-related RiskScore model can accurately predict the prognoses of patients with LGG and provide valuable insights into personalized medicine.

IL17RB and IL17REL Expression Are Associated with Improved Prognosis in HPV-Infected Head and Neck Squamous Cell Carcinomas

Changes in the cellular secretome are implicated in virus infection, malignancy, and anti-tumor immunity. We analyzed the association between transcriptional signatures (TS) from 24 different immune and stromal cell types on the prognosis of HPV-infected and HPV-free head and neck squamous carcinoma (HNSCC) patients from The Cancer Genome Atlas (TCGA) cohort. We found that HPV-positive HNSCC patients have tumors with elevated immune cell TS and improved prognosis, which was specifically associated with an increased tumor abundance of memory B and activated natural killer (NK) cell TS, compared to HPV-free HNSCC patients. HPV-infected patients upregulated many transcripts encoding secreted factors, such as growth factors, hormones, chemokines and cytokines, and their cognate receptors. Analysis of secretome transcripts and cognate receptors revealed that tumor expression of IL17RB and IL17REL are associated with a higher viral load and memory B and activated NK cell TS, as well as improved prognosis in HPV-infected HNSCC patients. The transcriptional parameters that we describe may be optimized to improve prognosis and risk stratification in the clinic and provide insights into gene and cellular targets that may potentially enhance anti-tumor immunity mediated by NK cells and memory B cells in HPV-infected HNSCC patients.

Advances in NK cell therapy for brain tumors

Despite advances in treatment regimens that comprise surgery, chemotherapy, and radiation, outcome of many brain tumors remains dismal, more so when they recur. The proximity of brain tumors to delicate neural structures often precludes complete surgical resection. Toxicity and long-term side effects of systemic therapy remain a concern. Novel therapies are warranted. The field of NK cell-based cancer therapy has grown exponentially and currently constitutes a major area of immunotherapy innovation. This provides a new avenue for the treatment of cancerous lesions in the brain. In this review, we explore the mechanisms by which the brain tumor microenvironment suppresses NK cell mediated tumor control, and the methods being used to create NK cell products that subvert immune suppression. We discuss the pre-clinical studies evaluating NK cell-based immunotherapies that target several neuro-malignancies and highlight advances in molecular imaging of NK cells that allow monitoring of NK cell-based therapeutics. We review current and ongoing NK cell based clinical trials in neuro-oncology.

Contribution of natural killer cells in innate immunity against colorectal cancer

Natural killer cells are members of the innate immune system and promote cytotoxic activity against tumor or infected cells independently from MHC recognition. NK cells are modulated by the expression of activator/inhibitory receptors. The ratio of this activator/inhibitory receptors is responsible for the cytotoxic activity of NK cells toward the target cells. Owing to the potent anti-tumor properties of NK cells, they are considered as interesting approach in tumor treatment. Colorectal cancer (CRC) is the second most common cause of death in the world and the incidence is about 2 million new cases per year. Metastatic CRC is accompanied by a poor prognosis with less than three years of overall survival. Chemotherapy and surgery are the most adopted treatments. Besides, targeted therapy and immune checkpoint blockade are novel approach to CRC treatment. In these patients, circulating NK cells are a prognostic marker. The main target of CRC immune cell therapy is to improve the tumor cell's recognition and elimination by immune cells. Adaptive NK cell therapy is the milestone to achieve the purpose. Allogeneic NK cell therapy has been widely investigated within clinical trials. In this review, we focus on the NK related approaches including CAR NK cells, cell-based vaccines, monoclonal antibodies and immunomodulatory drugs against CRC tumoral cells.

A novel natural killer cell-related signatures to predict prognosis and chemotherapy response of pancreatic cancer patients

Background: Natural killer (NK) cells are involved in monitoring and eliminating cancers. The purpose of this study was to develop a NK cell-related genes (NKGs) in pancreatic cancer (PC) and establish a novel prognostic signature for PC patients. Methods: Omic data were downloaded from The Cancer Genome Atlas Program (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), and used to generate NKG-based molecular subtypes and construct a prognostic signature of PC. NKGs were downloaded from the ImmPort database. The differences in prognosis, immunotherapy response, and drug sensitivity among subtypes were compared. 12 programmed cell death (PCD) patterns were acquired from previous study. A decision tree and nomogram model were constructed for the prognostic prediction of PC. Results: Thirty-two prognostic NKGs were identified in PC patients, and were used to generate three clusters with distinct characteristics. PCD patterns were more likely to occur at C1 or C3. Four prognostic DEGs, including MET, EMP1, MYEOV, and NGFR, were found among the clusters and applied to construct a risk signature in TCGA dataset, which was successfully validated in PACA-CA and GSE57495 cohorts. The four gene expressions were negatively correlated with methylation level. PC patients were divided into high and low risk groups, which exerts significantly different prognosis, clinicopathological features, immune infiltration, immunotherapy response and drug sensitivity. Age, N stage, and the risk signature were identified as independent factors of PC prognosis. Low group was more easily to happened on PCD. A decision tree and nomogram model were successfully built for the prognosis prediction of PC patients. ROC curves and DCA curves demonstrated the favorable and robust predictive capability of the nomogram model. Conclusion: We characterized NKGs-derived molecular subtypes of PC patients, and established favorable prognostic models for the prediction of PC prognosis, which may serve as a potential tool for prognosis prediction and making personalized treatment in PC.

Cell signaling activation and extracellular matrix remodeling underpin glioma tumor microenvironment heterogeneity and organization

PURPOSE

Tumor cells thrive by adapting to the signals in their microenvironment. To adapt, cancer cells activate signaling and transcriptional programs and migrate to establish micro-niches, in response to signals from neighboring cells and non-cellular stromal factors. Understanding how the tumor microenvironment evolves during disease progression is crucial to deciphering the mechanisms underlying the functional behavior of cancer cells.

METHODS

Multiplex immunohistochemistry, spatial analysis and histological dyes were used to identify and measure immune cell infiltration, cell signal activation and extracellular matrix deposition in low-grade, high-grade astrocytoma and glioblastoma.

RESULTS

We show that lower grade astrocytoma tissue is largely devoid of infiltrating immune cells and extracellular matrix proteins, while high-grade astrocytoma exhibits abundant immune cell infiltration, activation, and extensive tissue remodeling. Spatial analysis shows that most T-cells are restricted to perivascular regions, but bone marrow-derived macrophages penetrate deep into neoplastic cell-rich regions. The tumor microenvironment is characterized by heterogeneous PI3K, MAPK and CREB signaling, with specific signaling profiles correlating with distinct pathological hallmarks, including angiogenesis, tumor cell density and regions where neoplastic cells border the extracellular matrix. Our results also show that tissue remodeling is important in regulating the architecture of the tumor microenvironment during tumor progression.

CONCLUSION

The tumor microenvironment in malignant astrocytoma, exhibits changes in cell composition, cell signaling activation and extracellular matrix deposition during disease development and that targeting the extracellular matrix, as well as cell signaling activation will be critical to designing personalized therapy.

N6-methyladenosine RNA methylation regulator-related alternative splicing gene signature as prognostic predictor and in immune microenvironment characterization of patients with low-grade glioma

Background: N6-methyladenosine (m6A) RNA methylation is an important epigenetic modification affecting alternative splicing (AS) patterns of genes to regulate gene expression. AS drives protein diversity and its imbalance may be an important factor in tumorigenesis. However, the clinical significance of m6A RNA methylation regulator-related AS in the tumor microenvironment has not been investigated in low-grade glioma (LGG).

Methods: We used 12 m6A methylation modulatory genes (WTAP, FTO, HNRNPC, YTHDF2, YTHDF1, YTHDC2, ALKBH5, YTHDC1, ZC3H13, RBM15, METTL14, and METTL3) from The Cancer Genome Atlas (TCGA) database as well as the TCGA-LGG (n = 502) dataset of AS events and transcriptome data. These data were downloaded and subjected to machine learning, bioinformatics, and statistical analyses, including gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Univariate Cox, the Least Absolute Shrinkage and Selection Operator (LASSO), and multivariable Cox regression were used to develop prognostic characteristics. Prognostic values were validated using Kaplan-Maier survival analysis, proportional risk models, ROC curves, and nomograms. The ESTIMATE package, TIMER database, CIBERSORT method, and ssGSEA algorithm in the R package were utilized to explore the role of the immune microenvironment in LGG. Lastly, an AS-splicing factor (SF) regulatory network was examined in the case of considering the role of SFs in regulating AS events.

Results: An aggregate of 3,272 m6A regulator-related AS events in patients with LGG were screened using six machine learning algorithms. We developed eight AS prognostic characteristics based on splice subtypes, which showed an excellent prognostic prediction performance. Furthermore, quantitative prognostic nomograms were developed and showed strong validity in prognostic prediction. In addition, prognostic signatures were substantially associated with tumor immune microenvironment diversity, ICB-related genes, and infiltration status of immune cell subtypes. Specifically, UGP2 has better promise as a prognostic factor for LGG. Finally, splicing regulatory networks revealed the potential functions of SFs.

Conclusion: The present research offers a novel perspective on the role of AS in m6A methylation. We reveal that m6A methylation regulator-related AS events can mediate tumor progression through the immune-microenvironment, which could serve as a viable biological marker for clinical stratification of patients with LGG so as to optimize treatment regimens.

Identification and Validation of a Novel Signature Based on NK Cell Marker Genes to Predict Prognosis and Immunotherapy Response in Lung Adenocarcinoma by Integrated Analysis of Single-Cell and Bulk RNA-Sequencing

Natural killer (NK) cells, the effectors of the innate immune system, have a remarkable influence on cancer prognosis and immunotherapy. In this study, a total of 1,816 samples from nine independent cohorts in public datasets were enrolled. We first conducted a comprehensive analysis of single-cell RNA-sequencing data of lung adenocarcinoma (LUAD) from the Gene Expression Omnibus (GEO) database and determined 189 NK cell marker genes. Subsequently, we developed a seven-gene prognostic signature based on NK cell marker genes in the TCGA LUAD cohort, which stratified patients into high-risk and low-risk groups. The predictive power of the signature was well verified in different clinical subgroups and GEO cohorts. With a multivariate analysis, the signature was identified as an independent prognostic factor. Low-risk patients had higher immune cell infiltration states, especially CD8⁺ T cells and follicular helper T cells. There existed a negative association between inflammatory activities and risk score, and the richness and diversity of the T-cell receptor (TCR) repertoire was higher in the low-risk groups. Importantly, analysis of an independent immunotherapy cohort (IMvigor210) revealed that low-risk patients had better immunotherapy responses and prognosis than high-risk patients. Collectively, our study developed a novel signature based on NK cell marker genes, which had a potent capability to predict the prognosis and immunotherapy response of LUAD patients.

Role of the ITAM-Bearing Receptors Expressed by Natural Killer Cells in Cancer

Natural Killer (NK) cells are innate lymphoid cells (ILCs) capable of recognizing and directly killing tumor cells. They also secrete cytokines and chemokines, which participate in the shaping of the adaptive response. NK cells identify tumor cells and are activated through a net positive signal from inhibitory and activating receptors. Several activating NK cell receptors are coupled to adaptor molecules containing an immunoreceptor tyrosine-based activation motif (ITAM). These receptors include CD16 and the natural cytotoxic receptors NKp46, NKp44, NKp30 in humans. The powerful antitumor NK cell response triggered by these activating receptors has made them attractive targets for exploitation in immunotherapy. In this review, we will discuss the different activating receptors associated with ITAM-bearing cell surface receptors expressed on NK cells, their modulations in the tumor context and the various therapeutic tools developed to boost NK cell responses in cancer patients.

circ-0007707/miR-429/PDGFD Pathway Regulates the Progression of Gastric Cancer by Modulating the Immune-Gene Signature

Background

Immunotherapy is an important treatment modality for gastric cancer, therefore, it is crucial to understand the regulators of the tumor microenvironment in gastric cancer. Numerous studies have shown that noncoding RNAs have a critical status in the tumor progression, and the influence of competing endogenous RNA (ceRNA) networks on gastric adenocarcinoma has been widely discussed over the years, but the connection between ceRNA networks and the immune microenvironment of cancer is unclear. This study was aimed at exploring how ceRNA networks influence the prognosis of patients with gastric cancer by modulating the tumor microenvironment.

Methods

The Gene Expression Omnibus was analyzed to obtain differential expression matrixes of the noncoding RNAs (circular RNAs (circRNAs), microRNAs (miRNAs)), and mRNAs. The Circular RNA Interactome web tool and TargetScan were applied to determine the miRNA binding sites of the circRNAs and miRNA target genes. The Cancer Genome Atlas provided prognostic genes for gastric cancer, and Cytoscape created the ceRNA networks. Real-time quantitative reverse transcription polymerase chain reaction and western blot assay were adopted to find out how the ceRNA network regulates the expression of the hub gene. Additionally, the TISIDB and TIMER databases were used to assess the link between the hub gene and immunotherapy, with TISIDB providing the immune genes that are coexpressed with the hub gene. Furthermore, the immune-gene signature was constructed by using Cox regression analysis. Moreover, the nomogram, which could predict the prognostic role of gastric cancer patients was created on the basis of the immune-gene signature.

Results

In gastric cancer, the circ-0007707/miR-429/PDGFD pathway had a differential expression. The results demonstrated that the pathway could regulate the progression and immune microenvironment of gastric cancer by modulating the immune-gene signature, which included two immune genes (TAB1 and CXCR4). Moreover, the low-risk group patients had better survival.

Conclusion

The circ-0007707/miR-429/PDGFD pathway may play a regulatory role in the progression and prognosis of gastric cancer by interfering with the tumor microenvironment, and the PDGFD-related immune-gene signature could be considered a moderator of prognostic factor for gastric cancer and to guide immunotherapy programs.

O-GlcNAcylation and Its Role in Cancer-Associated Inflammation

Cancer cells, as well as surrounding stromal and inflammatory cells, form an inflammatory tumor microenvironment (TME) to promote all stages of carcinogenesis. As an emerging post-translational modification (PTM) of serine and threonine residues of proteins, O-linked-N-Acetylglucosaminylation (O-GlcNAcylation) regulates diverse cancer-relevant processes, such as signal transduction, transcription, cell division, metabolism and cytoskeletal regulation. Recent studies suggest that O-GlcNAcylation regulates the development, maturation and functions of immune cells. However, the role of protein O-GlcNAcylation in cancer-associated inflammation has been less explored. This review summarizes the current understanding of the influence of protein O-GlcNAcylation on cancer-associated inflammation and the mechanisms whereby O-GlcNAc-mediated inflammation regulates tumor progression. This will provide a theoretical basis for further development of anti-cancer therapies.

The Systematic Landscape of Nectin Family and Nectin-Like Molecules: Functions and Prognostic Value in Low Grade Glioma

Objective: Nectin and nectin-like molecules (Necls) are molecules that are involved in cell–cell adhesion and other vital cellular processes. This study aimed to determine the expression and prognostic value of nectin and Necls in low grade glioma (LGG).

Materials and Methods: Differentially expressed nectin and Necls in LGG samples and the relationship of nectin family and Necls expression with prognosis, clinicopathological parameters, and survival were explored using The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and Repository of Molecular Brain Neoplasia Data (REMBRANDT) databases. Univariate and multivariate Cox analysis models were performed to construct the prognosis-related gene signature. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves and multivariate Cox regression analysis, were utilized to evaluate the prognostic capacity of the four-gene signature. Gene ontology (GO)enrichment analysis and Gene Set Enrichment Analyses (GSEA) were performed to further understand the underlying molecular mechanisms. The Tumor Immune Estimation Resource (TIMER) was used to explore the relationship between the four-gene signature and tumor immune infiltration.

Results: Several nectin and Necls were differentially expressed in LGG. Kaplan–Meier survival analyses and Univariate Cox regression showed patients with high expression of NECTIN2 and PVR and low expression of CADM2 and NECTIN1 had worse prognosis among TCGA, CGGA, and REMBRANDT database. Then, a novel four-gene signature was built for LGG prognosis prediction. ROC curves, KM survival analyses, and multivariate COX regression indicated the new signature was an independent prognostic indicator for overall survival. Finally, GSEA and GO enrichment analyses revealed that immune-related pathways participate in the molecular mechanisms. The risk score had a strong negative correlation with tumor purity and data of TIMER showed different immune cell proportions (macrophage and myeloid dendritic cell) between high- and low-risk groups. Additionally, signature scores were positively related to multiple immune-related biomarkers (IL 2, IL8 and IFNγ).

Conclusion: Our results offer an extensive analysis of nectin and Necls levels and a four-gene model for prognostic prediction in LGG, providing insights for further investigation of CADM2, NECTIN1/2, and PVR as potential clinical and immune targets in LGG.

The Biological Role and Therapeutic Potential of NK Cells in Hematological and Solid Tumors

NK cells are an attractive target for cancer immunotherapy due to their potent antitumor activity. The main advantage of using NK cells as cytotoxic effectors over T cells is a reduced risk of graft versus host disease. At present, several variants of NK-cell-based therapies are undergoing clinical trials and show considerable effectiveness for hematological tumors. In these types of cancers, the immune cells themselves often undergo malignant transformation, which determines the features of the disease. In contrast, the current use of NK cells as therapeutic agents for the treatment of solid tumors is much less promising. Most studies are at the stage of preclinical investigation, but few progress to clinical trials. Low efficiency of NK cell migration and functional activity in the tumor environment are currently considered the major barriers to NK cell anti-tumor therapies. Various therapeutic combinations, genetic engineering methods, alternative sources for obtaining NK cells, and other techniques are aiming at the development of promising NK cell anticancer therapies, regardless of tumorigenesis. In this review, we compare the role of NK cells in the pathogenesis of hematological and solid tumors and discuss current prospects of NK-cell-based therapy for hematological and solid tumors.