Two immune-enhanced molecular subtypes differ in inflammation, checkpoint signaling and outcome of advanced head and neck squamous cell carcinoma

Molecular basis, potential biomarkers, and future prospects of OSCC and PD-1/PD-L1 related immunotherapy methods

Oral squamous cell carcinoma (OSCC) affects a large number of individuals worldwide. Despite advancements in surgery, radiation, and chemotherapy, satisfactory outcomes have not been achieved. In recent years, the success of drugs targeting programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) has led to breakthroughs in cancer treatment, but systematic summaries on their effectiveness against OSCC are lacking. This article reviews the latest research on the PD-1/PD-L1 pathway and the potential of combination therapy based on this pathway in OSCC. Further, it explores the mechanisms involved in the interaction of this pathway with exosomes and protein-protein interactions, and concludes with potential future OSCC therapeutic strategies.

90 K increased delivery efficiency of extracellular vesicles through mediating internalization

Using mass spectrometry-based high-throughput proteomics, we identified a membrane protein on extracellular vesicles (EVs), 90 K, which predicts poor overall survival of patients with head and neck cancer. 90 K levels in serum EVs could serve as an independent factor for poor prognosis of patients with head and neck cancer. Pre-treatment of immune competent mice with tumor-derived EVs (TDEs) elicited an immune-suppressive microenvironment for tumor cells, which was regulated by 90 K. The immunosuppressive function of TDE-90 K depends on the presence of myeloid derived suppressor cells (MDSCs) rather than regulatory T cells. The immune regulatory role of TDEs on MDSCs depends on miR-21 which is encapsulated in TDEs. Moreover, 90 K is required for the internalization of TDE cargo though interacting with integrin-β1 and anti-siglec-9 rather than directly affecting the immune function of MDSCs. 90 K modification of γδT cell-derived EVs (γδTEVs) could increase the delivery efficiency and therapeutic effect of PD-L1 siRNA by γδTEVs. We concluded that as a secreted protein modulating cell-cell and cell-matrix interactions, 90 K can be carried by TDEs to mediate the internalization and delivery of TDEs cargo by recipient cells. This function of 90 K could be utilized to improve the efficiency of EV-based drug delivery.

A Robust Prognostic Signature of Tumor Microenvironment in Colorectal Cancer

Background: Colorectal cancer (CRC) has been a major public health problem. Tumor microenvironment (TME) greatly contributes to the heterogeneity of CRC and is crucial for the regulation of CRC progression. The authors' study aimed to develop a robust prognostic signature for CRC patients based on TME-related genes. Materials and Methods: Gene expression data and clinicopathologic information of CRC patients were collected from Gene Expression Omnibus and The Cancer Genome Atlas databases. TME-related genes with prognostic value were identified by Cox regression and bootstrap method. The authors used the prognostic genes to construct a robust prognostic model using the least absolute shrinkage and selection operator (LASSO) regression method. The immune and stromal cell abundance of CRC samples were estimated by a microenvironment cell populations-counter method. Results: Based on a training set that comprised 893 CRC samples and 4775 TME-related genes, they established a prognostic model consisting of 25 TME-related genes. With specific risk score formulae, the prognostic model divided CRC patients into high-risk and low-risk subgroups with significantly different survival, which were further confirmed in validation cohorts consisting of other 473 CRC cases or subpopulation of specific stages. The result of time-dependent receiver operating characteristic analysis demonstrated strong predictive accuracy of the prognostic model both in training and validation cohorts. Multivariate Cox regression analysis showed that the 25-gene signature was an independent prognostic factor for overall survival, which was validated through clinical subgroups analysis. Further analysis revealed that CRC samples of high-risk group was abundant of stromal-relevant processes and had a significantly higher proportion of fibroblasts and endothelial cells infiltration. Conclusion: The authors established a robust prognostic signature of 25 TME-related genes which may be an effective tool for prognostic prediction and CRC patient stratification to assist in making treatment decisions.

Oncogenic signaling pathway dysregulation landscape reveals the role of pathways at multiple omics levels in pan-cancer

Dysregulation of signaling pathways plays an essential role in cancer. However, there is not a comprehensive understanding on how oncogenic signaling pathways affect the occurrence and development with a common molecular mechanism of pan-cancer. Here, we investigated the oncogenic signaling pathway dysregulation by using multi-omics data on patients from TCGA from a pan-cancer perspective to identify commonalities across different cancer types. First, the pathway dysregulation profile was constructed by integrating typical oncogenic signaling pathways and the gene expression of TCGA samples, and four molecular subtypes with significant phenotypic and clinical differences induced by different oncogenic signaling pathways were identified: TGF-β+ subtype; cell cycle, MYC, and NF2− subtype; cell cycle and TP53+ subtype; and TGF-β and TP53− subtype. Patients in the TGF-β+ subtype have the best prognosis; meanwhile, the TGF-β+ subtype is associated with hypomethylation. Moreover, there is a higher level of immune cell infiltration but a slightly worse survival prognosis in the cell cycle, MYC, and NF2− subtype patients due to the effect of T-cell dysfunction. Then, the prognosis and subtype classifiers constructed by differential genes on a multi-omics level show great performance, indicating that these genes can be considered as biomarkers with potential therapeutic and prognostic significance for cancers. In summary, our study identified four oncogenic signaling pathway–driven patterns presented as molecular subtypes and their related potential prognostic biomarkers by integrating multiple omics data. Our discovery provides a perspective for understanding the role of oncogenic signaling pathways in pan-cancer.

Expression of Tumor Suppressor SFRP1 Predicts Biological Behaviors and Prognosis: A Potential Target for Oral Squamous Cell Carcinoma

Background: Genomic instability is implicated in the initiation and progression of oral squamous cell carcinoma (OSCC). Tumor suppressor Secreted Frizzled-Related Protein 1 (SFRP1) may participate in the aberrant evolution of OSCC, the intrinsic molecular mechanisms of which may provide effective therapeutic targets. Methods: A bioinformatics analysis was carried out on a publicly available database using R language to map the prognostic value, immune infiltration and enrichment of SFRP1 expression. Subsequently, in vitro experiments were conducted to unveil the biological function of SFRP1. Results: SFRP1 was found to be ubiquitously lowly expressed in OSCC using a Wilcoxon rank-sum test. Univariate analysis confirmed that those patients characterized by a low SFRP1 expression were significantly associated with advanced T-stage, clinical stage and poor mortality (p < 0.05). Furthermore, SFRP1 displayed a positive performance in tumor immune infiltration, especially in mast cells. Functional annotations indicated that highly expressed SFRP1 was associated with membrane potential and passive transmembrane transporter activity and it was mainly enriched in calcium pathway and neuroactive ligand−receptor interaction. In vitro, the overexpression of SFRP1 inhibited its proliferation, migration, and invasion and resulted in G0+G1 phase arrest within Cal27 cells (p < 0.05). Conclusions: The bioinformation data suggest that SFRP1 expression provides an insight into the risk and prognostic stratification in OSCC. SFRP1 was validated as a potential biomarker with anticarcinogenic behaviors for use in targeted therapy.

The Chemokines Initiating and Maintaining Immune Hot Phenotype Are Prognostic in ICB of HNSCC

Background: The immune checkpoint blockade (ICB) with anti-programmed cell death protein 1(PD-1) on HNSCC is not as effective as on other tumors. In this study, we try to find out the key factors in the heterogeneous tumor-associated monocyte/macrophage (TAMM) that could regulate immune responses and predict the validity of ICB on HNSCC.

Experimental Design: To explore the correlation of the TAMM heterogeneity with the immune properties and prognosis of HNSCC, we established the differentiation trajectory of TAMM by analyzing the single-cell RNA-seq data of HNSCC, by which the HNSCC patients were divided into different sub-populations. Then, we exploited the topology of the network to screen out the genes critical for immune hot phenotype of HNSCC, as well as their roles in TAMM differentiation, tumor immune cycle, and progression. Finally, these key genes were used to construct a neural net model via deep-learning framework to predict the validity of treatment with anti-PD-1/PDL-1

Results: According to the differentiation trajectory, the genes involved in TAMM differentiation were categorized into early and later groups. Then, the early group genes divided the HNSCC patients into sub-populations with more detailed immune properties. Through network topology, CXCL9, 10, 11, and CLL5 related to TAMM differentiation in the TME were identified as the key genes initiating and maintaining the immune hot phenotype in HNSCC by remarkably strengthening immune responses and infiltration. Genome wide, CASP8 mutations were found to be key to triggering immune responses in the immune hot phenotype. On the other hand, in the immune cold phenotype, the evident changes in CNV resulted in immune evasion by disrupting immune balance. Finally, based on the framework of CXCL9-11, CLL5, CD8+, CD4+ T cells, and Macrophage M1, the neural network model could predict the validity of PD-1/PDL-1 therapy with 75% of AUC in the test cohort.

Conclusion: We concluded that the CXCL9, 10,11, and CCL5 mediated TAMM differentiation and constructed immune hot phenotype of HNSCC. Since they positively regulated immune cells and immune cycle in HNSCC, the CXCL9-11 and CCL5 could be used to predict the effects of anti-PD-1/PDL-1 therapy on HNSCC.

Tissue and circulating PD-L2: moving from health and immune-mediated diseases to head and neck oncology

Amongst the chief targets of immune-checkpoint inhibitors (ICIs), namely the Programmed cell death protein 1 (PD-1)/PD-Ligands (Ls) axis, most research has focused on PD-L1, while to date PD-L2 is still under-investigated. However, emerging data support PD-L2 relevant expression in malignancies of the head and neck area, mostly in head and neck squamous cell carcinoma (HNSCC) and salivary gland cancers (SGCs). In this context, ICIs have achieved highly heterogeneous outcomes, emphasizing an urgent need for the identification of predictive biomarkers. With the present review, we aimed at describing PD-L2 biological significance by focusing on its tissue expression, its binding to PD-1 and RGMb receptors, and its impact on physiological and anti-cancer immune response. Specifically, we reported PD-L2 expression rates and significant clinical correlates among different head and neck cancer histotypes. Finally, we described the biology of soluble PD-L2 form and its potential application as a prognostic and/or predictive circulating biomarker.

Integrated Multi-Omics Analysis Identified PTPRG and CHL1 as Key Regulators of Immunophenotypes in Clear Cell Renal Cell Carcinoma(ccRCC)

Despite the increasing importance and status of immune checkpoint blockade (ICB), little is known about the underlying molecular mechanisms determining the target clear cell renal cell carcinoma (ccRCC) population. In this study, we screened out 6 immune cells strongly correlated with expression levels of PD-L1 and IFN-γ based on the ccRCC samples extracted from GSE and TCGA data sets. By performing unsupervised clustering and lasso regression analysis, we grouped the ccRCC into 4 clusters and selected the two most distinct sub-clusters for further investigation-cluster A1 and B1. Next, we compared the two clusters in terms of mRNA, somatic mutations, copy number variations, DNA methylation, miRNA, lncRNA and constructed the differentially expressed genes (DEGs) hub by combing together the previous results at levels of DNA methylation, miRNA, and lncRNA. PTPRG and CHL1 were identified as key nodes in the regulation hub of immunophenotypes in ccRCC patients. Finally, we established the prognosis model by using Lasso-Cox regression and Kaplan-Meier analysis, recognizing WNT2, C17orf66, and PAEP as independent significant risk factors while IRF4 as an independent protective factor.

Dissecting Tumor Antigens and Immune Subtypes of Glioma to Develop mRNA Vaccine

Background

Nowadays, researchers are leveraging the mRNA-based vaccine technology used to develop personalized immunotherapy for cancer. However, its application against glioma is still in its infancy. In this study, the applicable candidates were excavated for mRNA vaccine treatment in the perspective of immune regulation, and suitable glioma recipients with corresponding immune subtypes were further investigated.

Methods

The RNA-seq data and clinical information of 702 and 325 patients were recruited from TCGA and CGGA, separately. The genetic alteration profile was visualized and compared by cBioPortal. Then, we explored prognostic outcomes and immune correlations of the selected antigens to validate their clinical relevance. The prognostic index was measured via GEPIA2, and infiltration of antigen-presenting cells (APCs) was calculated and visualized by TIMER. Based on immune-related gene expression, immune subtypes of glioma were identified using consensus clustering analysis. Moreover, the immune landscape was visualized by graph learning-based dimensionality reduction analysis.

Results

Four glioma antigens, namely ANXA5, FKBP10, MSN, and PYGL, associated with superior prognoses and infiltration of APCs were selected. Three immune subtypes IS1-IS3 were identified, which fundamentally differed in molecular, cellular, and clinical signatures. Patients in subtypes IS2 and IS3 carried immunologically cold phenotypes, whereas those in IS1 carried immunologically hot phenotype. Particularly, patients in subtypes IS3 and IS2 demonstrated better outcomes than that in IS1. Expression profiles of immune checkpoints and immunogenic cell death (ICD) modulators showed a difference among IS1-IS3 tumors. Ultimately, the immune landscape of glioma elucidated considerable heterogeneity not only between individual patients but also within the same immune subtype.

Conclusions

ANXA5, FKBP10, MSN, and PYGL are identified as potential antigens for anti-glioma mRNA vaccine production, specifically for patients in immune subtypes 2 and 3. In summary, this study may shed new light on the promising approaches of immunotherapy, such as devising mRNA vaccination tailored to applicable glioma recipients.

Identification of three immune molecular subtypes associated with immune profiles, immune checkpoints, and clinical outcome in multiple myeloma

Purpose

To identify the immune molecular subtype for MM to help achieve individualized and precise targeted therapy.

Methods

The GDC API was used to download the TCGA‐MM profile dataset, which contains 859 samples in total, all of which were anterior to the standard treatment after diagnosis. Moreover, 282, 298, and 258 samples were stage I, stage II, and stage III separately. We used the immune gene expression profile for consistent clustering; and used the R software package ConsensusClusterPlus to sort the immune molecular subtypes. Correlation between subtypes and clinical features, immunity, and prognosis was then analyzed.

Results

A total of 859 tumor samples were separated into these three subtypes, which were not meaningfully related to age or sex but showed a remarkable association with stage. The results suggested that obvious differences in immune metagene expression and expression of 10 immune checkpoint genes appeared among the three subtypes.

Conclusion

The three subtypes are distinctly different in terms of immune metagenes, immune checkpoint molecules, and clinical prognosis. The discovery of the immune microenvironment of MM could further reveal the strategy for immunotherapy in MM and provide a promising candidate prognostic tool for survival.

High SEC61G expression predicts poor prognosis in patients with Head and Neck Squamous Cell Carcinomas

Background: Overexpression of the membrane protein SEC61 translocon gamma subunit (SEC61G) has been observed in a variety of cancers; however, its role in head and neck squamous cell carcinomas (HNSCC) is unknown. This study aimed to elucidate the relationship between SEC61G and HNSCC based on data from The Cancer Genome Atlas (TCGA) database. Methods: Data for HNSCC patients were collected from TCGA and the expression level of SEC61G was compared between paired HNSCC and normal tissues using the Wilcoxon rank-sum test. The relationship between clinicopathologic features and SEC61G expression was also analyzed using the Wilcoxon rank-sum test and logistic regression. Receiver operating characteristic (ROC) curves were generated to evaluate the value of SEC61G as a binary classifier using the area under the curve (AUC value). The association of clinicopathologic characteristics with prognosis in HNSCC patients was assessed using Cox regression and the Kaplan-Meier methods. A nomogram, based on Cox multivariate analysis, was used to predict the impact of SEC61G on prognosis. Functional enrichment analysis was performed to determine the hallmark pathways associated with differentially expressed genes in HNSCC patients exhibiting high and low SEC61G expression. Results: The expression of SEC61G was significantly elevated in HNSCC tissues compared to normal tissues (P < 0.001). The high expression of SEC61G was significantly correlated with the T stage, M stage, clinical stage, TP53 mutation status, PIK3CA mutation status, primary therapy outcome, and cervical lymph node dissection (all P < 0.05). Meanwhile, ROC curves suggested the significant diagnostic ability of SEC61G for HNSCC (AUC = 0.923). Kaplan-Meier survival analysis showed that patients with HNSCC characterized by high SEC61G expression had a poorer prognosis than patients with low SEC61G expression (hazard ratio = 1.95, 95% confidence interval 1.48-2.56, P < 0.001). Univariate and multivariate analyses revealed that SEC61G was independently associated with overall survival (P = 0.027). Functional annotations indicated that SEC61G is involved in pathways related to translation and regulation of SLITs/ROBOs expression, SRP-dependent co-translational protein targeting to the membrane, nonsense-mediated decay, oxidative phosphorylation, and Parkinson's disease. Conclusion: SEC61G plays a vital role in HNSCC progression and prognosis; it may, therefore, serve as an effective biomarker for the prediction of patient survival.

Cancer-associated fibroblasts in gastric cancer affect malignant progression via the CXCL12-CXCR4 axis

Background: Cancer-associated fibroblasts (CAFs) are principal constituents of the tumor microenvironment (TME) and play a critical role in tumor progression. The CXCL12/CXCR4 axis regulates multiple facets of the TME. The aim of this study was to determine the relationship between CXCL12 expression in CAFs and the malignant progression of gastric cancer (GC).

Methods: In the GEO (Gene Expression Omnibus) database, we performed transcriptome analysis on paired gastric cancer RNA sequencing samples, and scRNA analysis was performed on advanced malignant GC samples from the scRNA sequencing data set. Fibroblast cells were co-cultured with GC cells, and invasion, migration, epithelial-mesenchymal transformation (EMT) were determined. After blocking the expression of fibroblast CXCL12, cells were co-cultured with a GC cell line. Detection of GC cell line invasion, migration, EMT and CXCR4, Wnt5a and β-Catenin expression levels was performed. Primary CAFs and gastric normal fibroblasts were isolated and CXCL12 mRNA and protein expression were determined. In addition, a cohort of 285 GC cases was established, protein expression was evaluated immunohistochemically, and prognostic results were analyzed.

Results: GC transcriptome analysis suggested that cytokine-cytokine receptor interaction and the Wnt signaling pathway in GC tissues were significantly up-regulated. scRNA analysis of advanced malignant GC samples showed that severe intestinal metaplasia (SIM) in GC specimens of different malignant grades had obvious fibroblast clusters compared to non-atrophic gastritis (NAG) and early gastric cancer (EGC). In the SIM group, fibroblast cluster, CXCL12, CXCR4, and Wnt5a were overexpressed. Co-culturing with fibroblast cells significantly increased the invasion, migration, and EMT of GC cells, and blocking CXCL12 in CAFs disturbed the expression of Wnt5a and β-catenin. In our cohort of GC patients, high CXCL12 expression in CAFs significantly correlated with histological grade (P = 0.012) and TNM stage (P = 0.014), as well as with poor overall survival (p = 0.0107).

Conclusion: High expression of CXCL12 in CAFs in a GC microenvironment can affect the migration, invasion, and EMT of GC cells. Furthermore, it can cause poor prognosis in patients with GC.

Profiles of immune cell infiltration in head and neck squamous carcinoma

Tumor immune infiltration cells (TIICs) are highly heterogeneous, not only in different cancer subtypes but also within different cancer regions. We conducted the Cell-type Identification using Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method. We assessed the relative proportions of 22 TIICs in HNSC using publicly available TCGA transcriptional datasets, analyzed the proportions of TIICs between HNSC tissues and normal tissues, along with accompanying clinicopathological data, and the impact of TIICs on clinical outcome. After the filter criteria, a total of 395 patients were included in the analysis. We found significant differences in naïve B cells, monocytes, resting mast cells, activated mast cells, CD8⁺ T cells, and M0 macrophages between HNSC tissues and adjacent non-cancer tissues. We also found that some TIIC subgroups were significantly associated with clinical parameters. Moreover, the patients with low Tregs fraction had worse OS and DFS than those with high Tregs fraction. However, low M0 macrophages fraction was associated with better OS and DFS in HNSC patients. Moreover, Tregs and M0 macrophages are likely to be important determinants of prognosis, which may serve as a potential immunotherapy target for HNSC. Then, we screened the immune-related differentially expressed genes (DEGs), performed the GO and KEGG enrichment analysis, constructed the protein–protein interaction network, and screened the prognosis-related hub genes in HNSC. However, further clinical investigation and basic experiments are needed to validate our results, and uncover the molecular mechanisms interlinking TIICs in HNSC and their roles in prognosis and therapy.

Immune-Related Mutational Landscape and Gene Signatures: Prognostic Value and Therapeutic Impact for Head and Neck Cancer

Simple Summary

Immunotherapy has emerged as a standard-of-care for most human malignancies, including head and neck cancer, but only a limited number of patients exhibit a durable clinical benefit. An urgent medical need is the establishment of accurate response predictors, which is handicapped by the growing body of molecular, cellular and clinical variables that modify the complex nature of an effective anti-tumor immune response. This review summarizes more recent efforts to elucidate immune-related mutational landscapes and gene expression signatures by integrative analysis of multi-omics data, and highlights their potential therapeutic impact for head and neck cancer. A better knowledge of the underlying principles and relevant interactions could pave the way for rational therapeutic combinations to improve the efficacy of immunotherapy, in particular for those cancer patients at a higher risk for treatment failure.

Abstract

Immunotherapy by immune checkpoint inhibition has become a main pillar in the armamentarium to treat head and neck cancer and is based on the premise that the host immune system can be reactivated to successfully eliminate cancer cells. However, the response rate remains low and only a small subset of head and neck cancer patients achieves a durable clinical benefit. The availability of multi-omics data and emerging computational technologies facilitate not only a deeper understanding of the cellular composition in the tumor immune microenvironment but also enables the study of molecular principles in the complex regulation of immune surveillance versus tolerance. These knowledges will pave the way to apply immunotherapy more precisely and effectively. This review aims to provide a holistic view on how the immune landscape dictates the tumor fate and vice versa, and how integrative analysis of multi-omics data contribute to our current knowledge on the accuracy of predictive biomarkers and on a broad range of factors influencing the response to immunotherapy in head and neck cancer.

The Immune Profile of Pituitary Adenomas and a Novel Immune Classification for Predicting Immunotherapy Responsiveness

CONTEXT

The tumor immune microenvironment is associated with clinical outcomes and immunotherapy responsiveness.

OBJECTIVE

To investigate the intratumoral immune profile of pituitary adenomas (PAs) and its clinical relevance and to explore a novel immune classification for predicting immunotherapy responsiveness.

DESIGN, PATIENTS, AND METHODS

The transcriptomic data from 259 PAs and 20 normal pituitaries were included for analysis. The ImmuCellAI algorithm was used to estimate the abundance of 24 types of tumor-infiltrating immune cells (TIICs) and the expression of immune checkpoint molecules (ICMs).

RESULTS

The distributions of TIICs differed between PAs and normal pituitaries and varied among PA subtypes. T cells dominated the immune microenvironment across all subtypes of PAs. The tumor size and patient age were correlated with the TIIC abundance, and the ubiquitin-specific protease 8 (USP8) mutation in corticotroph adenomas influenced the intratumoral TIIC distributions. Three immune clusters were identified across PAs based on the TIIC distributions. Each cluster of PAs showed unique features of ICM expression that were correlated with distinct pathways related to tumor development and progression. CTLA4/CD86 expression was upregulated in cluster 1, whereas programmed cell death protein 1/programmed cell death 1 ligand 2 (PD1/PD-L2) expression was upregulated in cluster 2. Clusters 1 and 2 exhibited a "hot" immune microenvironment and were predicted to exhibit higher immunotherapy responsiveness than cluster 3, which exhibited an overall "cold" immune microenvironment.

CONCLUSIONS

We summarized the immune profile of PAs and identified 3 novel immune clusters. These findings establish a foundation for further immune studies on PAs and provide new insights into immunotherapy strategies for PAs.

Development of an Immune-Related Risk Signature for Predicting Prognosis in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LSCC) is the most common subtype of non-small cell lung cancer. Immunotherapy has become an effective treatment in recent years, while patients showed different responses to the current treatment. It is vital to identify the potential immunogenomic signatures to predict patient' prognosis. The expression profiles of LSCC patients with the clinical information were downloaded from TCGA database. Differentially expressed immune-related genes (IRGs) were extracted using edgeR algorithm, and functional enrichment analysis showed that these IRGs were primarily enriched in inflammatory- and immune-related processes. "Cytokine-cytokine receptor interaction" and "PI3K-AKT signaling pathway" were the most enriched KEGG pathways. 27 differentially expressed IRGs were significantly correlated with the overall survival (OS) of patients using univariate Cox regression analysis. A prognostic risk signature that comprises seven IRGs (GCCR, FGF8, CLEC4M, PTH, SLC10A2, NPPC, and FGF4) was developed with effective predictive performance by multivariable Cox stepwise regression analysis. Most importantly, the signature could be an independent prognostic predictor after adjusting for clinicopathological parameters, and also validated in two independent LSCC cohorts (GSE4573 and GSE17710). Potential molecular mechanisms and tumor immune landscape of these IRGs were investigated through computational biology. Analysis of tumor infiltrating lymphocytes and immune checkpoint molecules revealed distinct immune landscape in high- and low-risk group. The study was the first time to construct IRG-based immune signature in the recognition of disease progression and prognosis of LSCC patients.

Development and verification of a personalized immune prognostic feature in breast cancer

IMPACT STATEMENT

Breast cancer is among the highest prevalent malignant tumors worldwide with a low survival ratio. Immune-related genes have great potential as prognostic indicator in many types of tumors. Therefore, we have attempted to develop immune-related gene markers to enhance the prognosis of breast cancer. 17-IRGPs signature was constructed as a newly developed prognostic indicator to predict the survival of BC patients.

The tumor immune microenvironmental analysis of 2,033 transcriptomes across 7 cancer types

Understanding the tumor microenvironment is important to efficiently identify appropriate patients for immunotherapies in a variety of cancers. Here, we presented the tumor microenvironmental analysis of 2,033 cancer samples across 7 cancer types: colon adenocarcinoma, skin cutaneous melanoma, kidney renal papillary cell carcinoma, sarcoma, pancreatic adenocarcinoma, glioblastoma multiforme, and pheochromocytoma / paraganglioma from The Cancer Genome Atlas cohort. Unsupervised hierarchical clustering based on the gene expression profiles separated the cancer samples into two distinct clusters, and characterized those into immune-competent and immune-deficient subtypes using the estimated abundances of infiltrated immune and stromal cells. We demonstrated differential tumor microenvironmental characteristics of immune-competent subtypes across 7 cancer types, particularly immunosuppressive tumor microenvironment features in kidney renal papillary cell carcinoma with significant poorer survival rates and immune-supportive features in sarcoma and skin cutaneous melanoma. Additionally, differential genomic instability patterns between the subtypes were found across the cancer types, and discovered that immune-competent subtypes in most of cancer types had significantly higher immune checkpoint gene expressions. Overall, this study suggests that our subtyping approach based on transcriptomic data could contribute to precise prediction of immune checkpoint inhibitor responses in a wide range of cancer types.

In silico analysis reveals EP300 as a panCancer inhibitor of anti-tumor immune response via metabolic modulation

The tumor immune microenvironment (TIME) of head and neck squamous cell carcinomas (HNSCC) and other solid malignancies is a key determinant of therapy response and prognosis. Among other factors, it is shaped by the tumor mutational burden and defects in DNA repair enzymes. Based on the TCGA database we aimed to define specific, altered genes associated with different TIME types, which might represent new predictive markers or targets for immuno-therapeutic approaches. The HNSCC cohort of the TCGA database was used to define 3 TIME types (immune-activated, immune-suppressed, immune-absent) according to expression of immune-related genes. Mutation frequencies were correlated to the 3 TIME types. Overall survival was best in the immune-activated group. 9 genes were significantly differentially mutated in the 3 TIME types with strongest differences for TP53 and the histone-acetyltransferase EP300. Mutations in EP300 correlated with an immune-activated TIME. In panCancer analyses anti-tumor immune activity was increased in EP300 mutated esophageal, stomach and prostate cancers. Downregulation of EP300 gene expression was associated with higher anti-tumor immunity in most solid malignancies. Since EP300 is a promoter of glycolysis, which negatively affects anti-tumor immune response, we analyzed the association of EP300 with tumor metabolism. PanCancer tumor metabolism was strongly shifted towards oxidative phosphorylation in EP300 downregulated tumors. In silico analyses of of publicly available in vitro data showed a decrease of glycolysis-associated genes after treatment with the EP300 inhibitor C646. Our study reveals associations of specific gene alterations with different TIME types. In detail, we defined EP300 as a panCancer inhibitor of the TIME most likely via metabolic modulation. In this context EP300 represents a promising predictive biomarker and an immuno-therapeutic target.

Integrative Analysis of Multi-omics Data Identified EGFR and PTGS2 as Key Nodes in a Gene Regulatory Network Related to Immune Phenotypes in Head and Neck Cancer

PURPOSE

Malignant progression exhibits a tightly orchestrated balance between immune effector response and tolerance. However, underlying molecular principles that drive the establishment and maintenance of the tumor immune phenotype remain to be elucidated.

EXPERIMENTAL DESIGN

We trained a novel molecular classifier based on immune cell subsets related to programmed death-ligand 1 (PD-L1) and interferon γ (IFNγ) expression, which revealed distinct subgroups with higher (cluster A) or lower (subcluster B3) cytotoxic immune phenotypes. Integrative analysis of multi-omics data was conducted to identify differences in genetic and epigenetic landscapes as well as their impact on differentially expressed genes (DEG) among immune phenotypes. A prognostic gene signature for immune checkpoint inhibition (ICI) was established by a least absolute shrinkage and selection operator (LASSO)-Cox regression model.

RESULTS

Mutational landscape analyses unraveled a higher frequency of CASP8 somatic mutations in subcluster A1, while subcluster B3 exhibited a characteristic pattern of copy-number alterations affecting chemokine signaling and immune effector response. The integrative multi-omics approach identified EGFR and PTGS2 as key nodes in a gene regulatory network related to the immune phenotype, and several DEGs related to the immune phenotypes were affected by EGFR inhibition in tumor cell lines. Finally, we established a prognostic gene signature by a LASSO-Cox regression model based on DEGs between nonprogressive disease and progressive disease subgroups for ICI.

CONCLUSIONS

Our data highlight a complex interplay between genetic and epigenetic events in the establishment of the tumor immune phenotype and provide compelling experimental evidence that a patient with squamous cell carcinoma of the head and neck at higher risk for ICI treatment failure might benefit from a combination with EGFR inhibition.

Identification of immune-enhanced molecular subtype associated with BRCA1 mutations, immune checkpoints and clinical outcome in ovarian carcinoma

Ovarian carcinoma has the highest mortality among the malignant tumours in gynaecology, and new treatment strategies are urgently needed to improve the clinical status of ovarian carcinoma patients. The Cancer Genome Atlas (TCGA) cohort were performed to explore the immune function of the internal environment of tumours and its clinical correlation with ovarian carcinoma. Finally, four molecular subtypes were obtained based on the global immune‐related genes. The correlation analysis and clinical characteristics showed that four subtypes were all significantly related to clinical stage; the immune scoring results indicated that most immune signatures were upregulated in C3 subtype, and the majority of tumour‐infiltrating immune cells were upregulated in both C3 and C4 subtypes. Compared with other subtypes, C3 subtype had a higher BRCA1 mutation, higher expression of immune checkpoints, and optimal survival prognosis. These findings of the immunological microenvironment in tumours may provide new ideas for developing immunotherapeutic strategies for ovarian carcinoma.

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

For many years, head and neck squamous cell carcinoma (HNSCC) has been considered as a single entity. However, in the last decades HNSCC complexity and heterogeneity have been recognized. In parallel, high-throughput omics techniques had allowed picturing a larger spectrum of the behavior and characteristics of molecules in cancer and a large set of omics web-based tools and informative repository databases have been developed. The objective of the present review is to provide an overview on biological, prognostic and predictive molecular signatures in HNSCC. To contextualize the selected data, our literature survey includes a short summary of the main characteristics of omics data repositories and web-tools for data analyses. The timeframe of our analysis was fixed, encompassing papers published between January 2015 and January 2019. From more than 1000 papers evaluated, 61 omics studies were selected: 33 investigating mRNA signatures, 11 and 13 related to miRNA and other non-coding-RNA signatures and 4 analyzing DNA methylation signatures. More than half of identified signatures (36) had a prognostic value but only in 10 studies selection of a specific anatomical sub-site (8 oral cavity, 1 oropharynx and 1 both oral cavity and oropharynx) was performed. Noteworthy, although the sample size included in many studies was limited, about one-half of the retrieved studies reported an external validation on independent dataset(s), strengthening the relevance of the obtained data. Finally, we highlighted the development and exploitation of three gene-expression signatures, whose clinical impact on prognosis/prediction of treatment response could be high. Based on this overview on omics-related literature in HNSCC, we identified some limits and strengths. The major limits are represented by the low number of signatures associated to DNA methylation and to non-coding RNA (miRNA, lncRNA and piRNAs) and the availability of a single dataset with multiple omics on more than 500 HNSCC (i.e. TCGA). The major strengths rely on the integration of multiple datasets through meta-analysis approaches and on the growing integration among omics data obtained on the same cohort of patients. Moreover, new approaches based on artificial intelligence and informatic analyses are expected to be available in the next future.

Trial watch: chemotherapy-induced immunogenic cell death in immuno-oncology

The term ‘immunogenic cell death’ (ICD) denotes an immunologically unique type of regulated cell death that enables, rather than suppresses, T cell-driven immune responses that are specific for antigens derived from the dying cells. The ability of ICD to elicit adaptive immunity heavily relies on the immunogenicity of dying cells, implying that such cells must encode and present antigens not covered by central tolerance (antigenicity), and deliver immunostimulatory molecules such as damage-associated molecular patterns and cytokines (adjuvanticity). Moreover, the host immune system must be equipped to detect the antigenicity and adjuvanticity of dying cells. As cancer (but not normal) cells express several antigens not covered by central tolerance, they can be driven into ICD by some therapeutic agents, including (but not limited to) chemotherapeutics of the anthracycline family, oxaliplatin and bortezomib, as well as radiation therapy. In this Trial Watch, we describe current trends in the preclinical and clinical development of ICD-eliciting chemotherapy as partner for immunotherapy, with a focus on trials assessing efficacy in the context of immunomonitoring.

Integrated analysis of transcriptome data revealed MMP3 and MMP13 as critical genes in anaplastic thyroid cancer progression

To better understand the molecular mechanisms of anaplastic thyroid carcinoma (ATC), we aimed to identify the hub genes specifically involved in ATC by integrated bioinformatics analysis. In this study, using three Gene Expression Omnibus data sets with the same platform GPL570, we screened hub genes involved in ATC progression. In vitro experiments, such as western blot analysis, Transwell assays, and coimmunoprecipitation, was performed to verify our findings. By comparing three subtypes of thyroid cancer with normal tissue, we found ATC harbored more changed genes than well and poorly differentiated thyroid cancer. Using specifically differentially expressed genes between ATC and normal thyroid tissues to perform Gene ontology (GO) analysis, ATC showed enrichments of GO terms involved in lymphocyte migration and activation, collagen catabolic and metabolic process, thyroid hormone synthesis, and embolism. Using genes involved in extracellular matrix, coexpression network analysis and protein-protein interaction analysis were performed to identify matrix metalloproteinase 3 (MMP3) and MMP13 as two hub genes. Our experimental data indicated that both MMP3 and MMP13 were upregulated in ATC and knockdown of either of them could notably suppress ATC cell invasion and migration. Mechanistically, Gene Set Enrichment Analysis, coimmunoprecipitation, and rescue experiments revealed MMP3 and MMP13 not only interacted with each other, but also regulated each other through the janus kinase/signal transducer and activator of transcription 3 and mammalian target of rapamycin pathways. In conclusion, we identified a specific molecular mechanisms for the development of ATC by integrated analysis of transcriptome and in vitro experiments, which suggested that MMP3 and MMP13 might be developed as novel therapeutic targets for ATC.

Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma

The immune environment in primary tumor has a profound impact on immunotherapy. However, the clinical relevance of immune environment in hepatocellular carcinoma (HCC) is largely unknown. Here, the immune profile and its clinical response in HCC were investigated. The gene expression profiles of 569 HCCs from three cohorts (The Cancer Genome Atlas, TCGA, n = 257; Gene Expression Omnibus, GEO, n = 170; International Cancer Genome Consortium, ICGC, n = 142) were used in the current study. Five gene expression subtypes (C1–C5) responsible for global immune genes were identified in HCCs at stage I/II. It was found that subtype C4 was associated with upregulation and subtype C5 was associated with downregulation of immune profiles in most metagenes. Immune-correlation analysis of the five subtypes demonstrated that C3 and C4 had higher immune score and better prognostic outcome, as compared with other subtypes. Moreover, the mutation frequencies of TP53, CTNNB1, and AXIN1 had significant difference in the five subgroups. Further, the expression of PDCD1, CD274, PDCD1LG2, CTLA4, CD86, and CD80 was higher in subtype C4 in comparison with the other subtypes. The WGCNA of immune-related genes in the five subtypes revealed that blue and turquoise modules were positively correlated with subtype C4 and were associated with 12 common pathways in the KEGG database. These results were validated in external cohorts from the NCI (National Cancer Institute) cohort (GSE14520) and the ICGC (International Cancer Genome Consortium) cohort. In summary, one immune-enhanced subtype and one immune-decreased subtype having different immune and clinical characteristics may provide guidance for developing novel treatment strategies for immune system malfunction-related cancer.

An EV-Associated Gene Signature Correlates with Hypoxic Microenvironment and Predicts Recurrence in Lung Adenocarcinoma

Extracellular vesicles (EVs) mediate intercellular communications in the tumor microenvironment and contribute to the aggressive phenomenon of cancers. Although EVs in body fluids are supposed to be ideal biomarkers for cancer diagnosis and prognosis, it remains difficult to distinguish the tumor-derived EVs from those released by other tissues. We hypothesized that analyzing the EV-related molecules in tumor tissues would help to estimate the prognostic value of tumor-specific EVs. Here, we investigate the expression of coding genes of proteins carried by small EVs (sEVs) in primary lung adenocarcinoma. Based on the protein-protein interaction network, we identified three network modules (3-PPI-Mod) as a signature that could predict recurrence. This signature was validated in three independent datasets and demonstrated better prognostic value than signature generated from gene expression alone. Meanwhile, the high-risk subgroup assigned by the signature could benefit from adjuvant chemotherapy, although it was not beneficial in unselected patients. Two out of three modules were enriched by proteins identified in sEVs from non-small-cell lung cancer cells. Furthermore, the two modules were remarkably correlated with intratumoral hypoxia score. These results suggest that the 3-PPI-Mod signature was enriched in tumor-derived sEVs and could serve as a prognostic and predictive biomarker for lung adenocarcinoma.

Screening responsive or resistant biomarkers of immune checkpoint inhibitors based on online databases

Immune checkpoint inhibitors are a promising strategy in the treatment of cancer, especially advanced types. However, not all patients are responsive to immune checkpoint inhibitors. The response rate depends on the immune microenvironment, tumor mutational burden (TMB), expression level of immune checkpoint proteins, and molecular subtypes of cancers. Along with the Cancer Genome Project, various open access databases, including The Cancer Genome Atlas and Gene Expression Omnibus, provide large volumes of data, which allow researchers to explore responsive or resistant biomarkers of immune checkpoint inhibitors. In this review, we introduced some methodologies on database selection, biomarker screening, current progress of immune checkpoint blockade in solid tumor treatment, possible mechanisms of drug resistance, strategies of overcoming resistance, and indications for immune checkpoint inhibitor therapy.

Identification of discrepancy between CTLA4 expression and CTLA4 activation in gastric cancer

Objective: Recently, immune checkpoints blockers showed higher anti-tumor activity for advanced gastric cancer (GC). The purpose of the study is to find out predictive biomarkers related to anti-cytotoxic lymphocyte antigen 4 (CTLA4) therapy. Materials and methods: Datasets of gene expression omnibus (GEO), the cancer genome atlas (TCGA), and gene set enrichment analysis (GESA) were extracted. Differential expression of CTLA4 between cancer tissues and normal mucosa, enrichment of WT (wild type) vs. CTLA4_KO (knockout) upregulated gene set and clinical significance were analyzed. The expression of CTLA4, CD3, and granzyme A (GZMA) were validated on 30 cases of Chinese GC. Microsatellite instability (MSI) marker MLH1 and Epstein-Barr virus (EBV) marker EBER were examined on 30 cases of Chinese GC by immunohistochemistry and in situ hybridization. Results: CTLA4 was upregulated in GC tissue relative to normal mucosa in datasets of GSE27342 (fold change = 1.586, p < .001) and GSE63089 (fold change = 1.365, p < .001). Increased CTLA4 expression was positively related to CTLA4 activation. EBV-associated GC (EBVaGC) and microsatellite instability GC (MSIGC) disclosed higher CTLA4 levels than other GCs. Genomic stability GC (GSGC) also showed higher enrichment score of CTLA4 activation. CTLA4 activation resulted in shorter overall survival in GC. The expression level of CTLA4 was well correlated to expression levels of GZMA (R = 0.701, p < .001) and CD3 (R = 0.750, p < .001). Conclusions: Based on bioinformatics analysis, GSGC should be worth noticed as a potential GC subtypes responsive to anti-CTLA4 treatment.

Comprehensive analysis of the tumor immune micro-environment in non-small cell lung cancer for efficacy of checkpoint inhibitor

Characterizing the molecular immune subtype and micro-environment of lung cancer is necessary to understand immunogenic interactions between infiltrating immune and stromal cells, and how tumor cells overcome immune checkpoint blockades. This study seeks to identify computational methodologies for subtyping gene expression-based tumor-immune micro-environment interactions, which differentiate non-small cell lung cancer (NSCLC) into immune-defective and immune-competent subtypes. Here, 101 lung squamous cell carcinomas (LUSCs) and 87 lung adenocarcinomas (LUADs) tumor samples have been analyzed. Several micro-environmental factors differentially induce LUAD or LUSC immune subtypes, as well as immune checkpoint expression. In particular, tumor-associated macrophages (TAMs) are key immune cells play a vital role in inflammation and cancer micro-environments of LUSCs; whereas, regulatory B cells are immunosuppressive and tumorigenic in LUADs. Additionally, cytolytic activity upon CD8⁺ T cell activation is decreased by the abundance of B cells and macrophages in immune-competent subtypes. Therefore, identifying immune subtypes in lung cancer and their impact on tumor micro-environment will lead to clinical tools for assessing LUADs and LUSCs in patients, as well as maximize the efficacy of immune checkpoint inhibitors.

Gene-expression signature predicts survival benefit from postoperative chemoradiotherapy in head and neck squamous cell carcinoma

Postoperative radiotherapy or concurrent chemoradiotherapy are routine clinical options for the treatment of head and neck squamous cell carcinoma (HNSCC). However, the benefit of adding chemotherapy to radiotherapy is contested. The present study aimed to develop a gene signature to predict the clinical benefit of postoperative chemoradiotherapy using public data from The Cancer Genome Atlas. A 22-gene signature was established, which demonstrated the best predictive value. Patients were separated into low-score and high-score subgroups based on the expression score of the 22-gene signature. In the high-score subgroup, patients who received chemoradiotherapy demonstrated improved overall survival, relapse-free survival and local regional control compared with those who received radiotherapy alone. However, in the low-score subgroup adding chemotherapy to radiotherapy was associated with worse patient outcomes. The predictive value of the 22-gene signature was independent of the conventional clinical variables. Gene set enrichment analysis revealed that the expression signatures of hypoxia phenotype and stem-like traits were significantly enriched in the low-score subgroup. In addition, the low-score subgroup was associated with the gene sets involved in resistance to anticancer drugs. In conclusion, hypoxia- or stem-like gene expression properties are associated with chemotherapy-resistance in HNSCC. The 22-gene signature may be useful as a predictive marker to help distinguish patients who will benefit from postoperative concurrent chemoradiotherapy.