A Transcriptional Signature of IL-2 Expanded Natural Killer Cells Predicts More Favorable Prognosis in Bladder Cancer

TIM-3/Galectin-9 and CD160 expression in salivary adenoid cystic carcinoma

OBJECTIVE

Investigating T-cell immunoglobulin and mucin-domain containing-3 (TIM-3), Galectin 9 (Gal-9), CD160 expression and tumor-infiltrating lymphocytes (TILs) and correlation with clinicopathological characteristics of salivary adenoid cystic carcinoma (SACC).

METHODS

Sixty cases of SACC were detected by immunohistochemical staining to evaluate TIM-3, Gal-9, and CD160 expression and analyze the correlation between TIM-3, Gal-9, CD160 expression and clinicopathologic features by rank-sum test. The association of TILs with TIM-3, Gal-9, and CD160 expression in SACC stromal was done by Chi-square test.

RESULTS

TIM-3 and CD160 overexpression were correlated with recurrence of SACC (p = 0.029, p = 0.007, respectively). High Gal-9 expression was correlated with pathological classification (p = 0.018). The average percentage of TILs was 18.2% in SACC and most of TILs were more likely to occur in minor salivary glands (p = 0.038). Pairwise positive correlations were observed between the expression of TIM-3, Gal-9, and CD160 in tumor cells as well as in TILs, respectively.

CONCLUSION

Low density of TILs was characteristic of the SACC microenvironment, with upregulation of TIM-3, Gal-9, and CD160 all occurring. However, TIM-3, Gal-9, and CD160 expression in the stromal dependent on the number of TILs represent potential therapeutic targets in SACC.

Pan-Cancer Analysis Shows that KIFC2 is a Potential Prognostic and Immunotherapeutic Biomarker for Multiple Cancer Types Including Bladder Cancer

KIFC2 plays an important role in prostate cancer progression and chemotherapy resistance, but the mechanism of its involvement in other malignancies remains unclear. Therefore, this study aimed to analyze and validate the mechanism of effect of KIFC2 in multiple tumors. Bioinformatic analysis was performed in conjunction with multiple databases (The Cancer Genome Atlas, Genotype-Tissue Expression Project, Human Protein Atlas, etc.) to fully explore the potential role of KIFC2 within individual tumors and to analyze the correlation with major research components such as prognosis, mutations, and the tumor microenvironment. The expression of KIFC2 demonstrates a significant correlation with the prognosis, clinical phenotype, tumor mutational burden, microsatellite instability, and tumor microenvironment across various malignancies and is associated with the modulation of diverse functional and signaling pathways. The differences in the expression of KIFC2 in the bladder cancer tissues (14 pairs) were statistically significant. The pan-cancer analysis in this study revealed the multifunctionality of KIFC2 in a variety of tumors, indicating a possible prognostic predictor and potential therapeutic target for tumors.

Advances in tumor microenvironment and underlying molecular mechanisms of bladder cancer: a systematic review

Bladder cancer is one of the most frequent malignant tumors of the urinary system. The prevalence of bladder cancer among men and women is roughly 5:2, and both its incidence and death have been rising steadily over the past few years. At the moment, metastasis and recurrence of advanced bladder cancer-which are believed to be connected to the malfunction of multigene and multilevel cell signaling network-remain the leading causes of bladder cancer-related death. The therapeutic treatment of bladder cancer will be greatly aided by the elucidation of these mechanisms. New concepts for the treatment of bladder cancer have been made possible by the advancement of research technologies and a number of new treatment options, including immunotherapy and targeted therapy. In this paper, we will extensively review the development of the tumor microenvironment and the possible molecular mechanisms of bladder cancer.

cellsig plug-in enhances CIBERSORTx signature selection for multidataset transcriptomes with sparse multilevel modelling

MOTIVATION

The precise characterization of cell-type transcriptomes is pivotal to understanding cellular lineages, deconvolution of bulk transcriptomes, and clinical applications. Single-cell RNA sequencing resources like the Human Cell Atlas have revolutionised cell-type profiling. However, challenges persist due to data heterogeneity and discrepancies across different studies. One limitation of prevailing tools such as CIBERSORTx is their inability to address hierarchical data structures and handle nonoverlapping gene sets across samples, relying on filtering or imputation.

RESULTS

Here, we present cellsig, a Bayesian sparse multilevel model designed to improve signature estimation by adjusting data for multilevel effects and modelling for gene-set sparsity. Our model is tailored to large-scale, heterogeneous pseudobulk and bulk RNA sequencing data collections with nonoverlapping gene sets. We tested the performances of cellsig on a novel curated Human Bulk Cell-type Catalogue, which harmonizes 1435 samples across 58 datasets. We show that cellsig significantly enhances cell-type marker gene ranking performance. This approach is valuable for cell-type signature selection, with implications for marker gene validation, single-cell annotation, and deconvolution benchmarks.

AVAILABILITY AND IMPLEMENTATION

Codes and the interactive app are available at https://github.com/stemangiola/cellsig; and the database is available at https://doi.org/10.5281/zenodo.7582421.

The tumor micro-environment in pediatric glioma: friend or foe?

Brain tumors are the leading cause of morbidity and mortality related to cancer in children, where high-grade glioma harbor the worst prognosis. It has become obvious that pediatric glioma differs significantly from their adult counterparts, rendering extrapolations difficult. Curative options for several types of glioma are lacking, albeit ongoing research efforts and clinical trials. As already proven in the past, inter- and intratumoral heterogeneity plays an important role in the resistance to therapy and thus implicates morbidity and mortality for these patients. However, while less studied, the tumor micro-environment (TME) adds another level of heterogeneity. Knowledge gaps exist on how the TME interacts with the tumor cells and how the location of the various cell types in the TME influences tumor growth and the response to treatment. Some studies identified the presence of several (immune) cell types as prognostic factors, but often lack a deeper understanding of the underlying mechanisms, possibly leading to contradictory findings. Although the TME in pediatric glioma is regarded as "cold", several treatment options are emerging, with the TME being the primary target of treatment. Therefore, it is crucial to study the TME of pediatric glioma, so that the interactions between TME, tumoral cells and therapeutics can be better understood before, during and after treatment. In this review, we provide an overview of the available insights into the composition and role of the TME across different types of pediatric glioma. Moreover, where possible, we provide a framework on how a particular TME may influence responses to conventional- and/or immunotherapy.

Positive regulatory loop of platelet-derived growth factor DD-induced STAT3 activation is associated with poor prognosis in advanced urothelial carcinoma

Immune checkpoint inhibitor (ICI) therapy has been established for patients with advanced urothelial cancer (UC). The necessity of overcoming resistance to ICIs and identifying a predictive factor for the same has been highlighted, such as the assessment of combination therapy with other targeted drugs and the characterization of molecular signatures in the tumor microenvironment. Recently, we reported that low hemoglobin (Hb) levels and a high platelet-to-lymphocyte ratio (PLR) were significantly associated with overall survival in patients with UC who did not benefit from pembrolizumab treatment. In the present study, we identified a possible link between these unfavorable prognostic indicators and PDGF-DD-induced STAT3 activation in UC. Overlapping patients between the high STAT3- or phosphorylated STAT3-positive score group (as assessed by immunohistochemistry) and low Hb levels or high PLR group (as assessed by blood tests) showed significantly worse outcomes after pembrolizumab treatment. Additionally, using the bladder cancer JMSU1 cell line, we demonstrated a possible positive regulatory loop between autocrine/paracrine PDGF-DD and STAT3 signaling. Therefore, we suggest that STAT3 inhibition and PDGF-DD detection in the tumor microenvironment might represent a potential therapeutic strategy to overcome resistance to pembrolizumab. Moreover, this can help identify patients with UC who could benefit from combination treatment.

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.

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.

Platelet, a key regulator of innate and adaptive immunity

Platelets, anucleate blood components, represent the major cell type involved in the regulation of hemostasis and thrombosis. In addition to performing haemostatic roles, platelets can influence both innate and adaptive immune responses. In this review, we summarize the development of platelets and their functions in hemostasis. We also discuss the interactions between platelet products and innate or adaptive immune cells, including neutrophils, monocytes, macrophages, T cells, B cells and dendritic cells. Activated platelets and released molecules regulate the differentiation and function of these cells via platelet-derived receptors or secreting molecules. Platelets have dual effects on nearly all immune cells. Understanding the exact mechanisms underlying these effects will enable further application of platelet transfusion.

PDGF-D-induced immunoproteasome activation and cell-cell interactions

Platelet-derived growth factor-D (PDGF-D) is abundantly expressed in ocular diseases. Yet, it remains unknown whether and how PDGF-D affects ocular cells or cell-cell interactions in the eye. In this study, using single-cell RNA sequencing (scRNA-seq) and a mouse model of PDGF-D overexpression in retinal pigment epithelial (RPE) cells, we found that PDGF-D overexpression markedly upregulated the key immunoproteasome genes, leading to increased antigen processing/presentation capacity of RPE cells. Also, more than 6.5-fold ligand-receptor pairs were found in the PDGF-D overexpressing RPE-choroid tissues, suggesting markedly increased cell-cell interactions. Moreover, in the PDGF-D-overexpressing tissues, a unique cell population with a transcriptomic profile of both stromal cells and antigen-presenting RPE cells was detected, suggesting PDGF-D-induced epithelial-mesenchymal transition of RPE cells. Importantly, administration of ONX-0914, an immunoproteasome inhibitor, suppressed choroidal neovascularization (CNV) in a mouse CNV model in vivo. Together, we show that overexpression of PDGF-D increased pro-angiogenic immunoproteasome activities, and inhibiting immunoproteasome pathway may have therapeutic value for the treatment of neovascular diseases.

Tumor microenvironment and epithelial-mesenchymal transition in bladder cancer: Cytokines in the game?

Bladder cancer (BlCa) is a highly immunogenic cancer. Bacillus Calmette-Guérin (BCG) is the standard treatment for non-muscle invasive bladder cancer (NMIBC) patients and, recently, second-line immunotherapies have arisen to treat metastatic BlCa patients. Understanding the interactions between tumor cells, immune cells and soluble factors in bladder tumor microenvironment (TME) is crucial. Cytokines and chemokines released in the TME have a dual role, since they can exhibit both a pro-inflammatory and anti-inflammatory potential, driving infiltration and inflammation, and also promoting evasion of immune system and pro-tumoral effects. In BlCa disease, 70-80% are non-muscle invasive bladder cancer, while 20-30% are muscle-invasive bladder cancer (MIBC) at the time of diagnosis. However, during the follow up, about half of treated NMIBC patients recur once or more, with 5-25% progressing to muscle-invasive bladder cancer, which represents a significant concern to the clinic. Epithelial-mesenchymal transition (EMT) is one biological process associated with tumor progression. Specific cytokines present in bladder TME have been related with signaling pathways activation and EMT-related molecules regulation. In this review, we summarized the immune landscape in BlCa TME, along with the most relevant cytokines and their putative role in driving EMT processes, tumor progression, invasion, migration and metastasis formation.

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.

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.

Characterization of Ligand-Receptor Pair in Bladder Cancer Develops a Validated Scoring Model for Prognosis and Treatment Response

The role of ligand-receptor (LR) pairs in disease progression has been explored in bladder cancer. However, the relationship of LR pairs with cancer prognosis and treatment response remains poorly understood. We characterized the LR pair network and identified three distinct molecular subtypes with distinct biologic features based on the TCGA database (n = 406) and validated in GSE13507 (n = 165) and GSE32894 (n = 224). Three subtypes were compared for differences in patient clinical characteristics, genomic, and transcriptomic features. A multivariate Lasso Cox regression model was applied to construct an LR pairs-based scoring model to stratify the prognostic risk of patients. We demonstrated the high LR. score patients had better responses in chemotherapy, while low LR. score patients may benefit from immune checkpoint blockade (ICB). Collectively, we identified three LR pair-related subtypes associated with prognosis. We constructed and validated a LR pairs-based gene signature, which helps to predict prognosis and differentiate the susceptible population to chemotherapy and immunotherapy in patients with bladder cancer. Among the LR pairs significantly related to prognosis, ANAX1−EGFR axis was found to be potential therapeutic target for treatment of bladder cancer.

An HDAC9-associated immune-related signature predicts bladder cancer prognosis

Background

The close relationship between histone deacetylase 9 (HDAC9) and immunity has attracted attention. We constructed an immune signature for HDAC9, a vital epigenetic modification, to predict the survival status and treatment benefits in bladder cancer (BC).

Methods

An exhaustive analysis of HDAC9 and immunology via the tumor and immune system interaction database (TISIDB) was performed, and an immune prognostic risk signature was developed based on genes enriched in the top five immune-related pathways under high HDAC9 status. Comprehensive analysis of survival curves and Cox regression were used to estimate the effectiveness of the risk signature. The relationship between immunological characteristics and the risk score was evaluated, and the mechanisms were also explored.

Results

In the TISIDB, HDAC9 was closely related to various immunological characteristics. The risk signature was obtained based on genes related to prognosis enriched in the top five immune-related pathways under high HDAC9 status. The survival rate of the high-risk BC patients was poor. The risk score was closely related to multiple immunological characteristics, drug sensitivity, immunotherapy benefits and biofunctions.

Conclusion

An immune-related prognostic signature established for HDAC9 expression status could independently predict the prognosis of BC patients. The use of this signature could help clinicians make personalized treatment decisions.