scholarly journals Identification of Immune-Related LncRNA Pairs for Predicting Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Xueying Wang ◽  
Kui Cao ◽  
Erliang Guo ◽  
Xionghui Mao ◽  
Lunhua Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Clinical Outcome ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Neck Squamous Cell Carcinoma

Long noncoding RNAs (lncRNAs) have multiple functions with regard to the cancer immunity response and the tumor microenvironment. The prognosis of head and neck squamous cell carcinoma (HNSCC) is still poor currently, and it may be effective to predict the clinical outcome and immunotherapeutic response of HNSCC by immunogenic analysis. Therefore, by using univariate COX analysis and Lasso Cox regression, we identified a signature consisting of 21 immune-related lncRNA pairs (IRLPs) that predicted clinical outcome and Immunotherapeutic response in HNSCC. Specifically, it was associated with immune cell infiltration (i.e., T cells CD4 memory resting, CD8 T cells, macrophages M0, M2, and NK cells), and more importantly this signature was strongly related with immune checkpoint inhibitors (ICIs) [such as PDCD1 (r = -0.35, P < 0.001), CTLA4 (r = -0.26, P < 0.001), LAG3 (r = -0.22, P < 0.001) and HAVCR2 (r = -0.2, P < 0.001)] and immunotherapy-related biomarkers (MMR and HLA). The present study highlighted the value of the 21 IRLPs signature as a predictor of prognosis and immunotherapeutic response in HNSCC.

scholarly journals Highly Multiplexed Digital Spatial Profiling of the Tumor Microenvironment of Head and Neck Squamous Cell Carcinoma Patients

2021 ◽  
Vol 10 ◽  
Author(s):  
Arutha Kulasinghe ◽  
Touraj Taheri ◽  
Ken O’Byrne ◽  
Brett G. M. Hughes ◽  
Liz Kenny ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Neck Squamous Cell Carcinoma ◽  
Protein Markers ◽  
Spatial Profiling

BackgroundImmune checkpoint inhibitors (ICI) have shown durable and long-term benefits in a subset of head and neck squamous cell carcinoma (HNSCC) patients. To identify patient-responders from non-responders, biomarkers are needed which are predictive of outcome to ICI therapy. Cues in the tumor microenvironment (TME) have been informative in understanding the tumor-immune contexture.MethodsIn this preliminary study, the NanoString GeoMx™ Digital Spatial Profiling (DSP) technology was used to determine the immune marker and compartment specific measurements in a cohort of HNSCC tumors from patients receiving ICI therapy.ResultsOur data revealed that markers involved with immune cell infiltration (CD8 T-cells) were not predictive of outcome to ICI therapy. Rather, a number of immune cell types and protein markers (CD4, CD68, CD45, CD44, CD66b) were found to correlate with progressive disease. Cross platform comparison with the Opal Vectra (Perkin Elmer) for a number of markers across similar regions of interest demonstrated concordance for pan-cytokeratin, CD8, and PD-L1.ConclusionThis study, to our knowledge, represents the first digital spatial analysis of HNSCC tumors. A larger cohort of HNSCC will be required to orthogonally validate the findings.

scholarly journals Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-42
Author(s):  
Ya Guo ◽  
Wei Kang Pan ◽  
Zhong Wei Wang ◽  
Wang Hui Su ◽  
Kun Xu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Regulatory T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Cox Regression ◽  
Cerna Network

Objectives. Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients. Methods and Results. Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis. Conclusions. We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.

scholarly journals An Immune Feature-Based, Three-Gene Scoring System for Prognostic Prediction of Head-and-Neck Squamous Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Yamin Zhang ◽  
Xiayan Luo ◽  
Jing Yu ◽  
Kejia Qian ◽  
Huiyong Zhu
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Candidate Genes ◽  
Risk Score ◽  
Squamous Cell ◽  
Scoring System ◽  
Cox Regression ◽  
Neck Squamous Cell Carcinoma

Head-and-neck squamous cell carcinoma (HNSCC) is characterized by a high frequency of neck lymph node metastasis (LNM), a key prognostic factor. Therefore, identifying the biological processes during LNM of HNSCC has significant clinical implications for risk stratification. This study performed Gene Ontology enrichment analysis of differentially expressed genes between tumors with LNM and those without LNM and identified the involvement of immune response in the lymphatic metastasis of HNSCC. We further identified greater infiltrations of CD8+ T cells in tumors than in adjacent normal tissues through immunochemistry in the patient cohort (n = 62), indicating the involvement of CD8+ T cells in the antitumor immunity. Hierarchical clustering analysis was conducted to initially identify the candidate genes relevant to lymphocyte-mediated antitumor response. The candidate genes were applied to construct a LASSO Cox regression analysis model. Three genes were eventually screened out as progression‐related differentially expressed candidates in HNSCC and a risk scoring system was established based on LASSO Cox regression model to predict the outcome in patients with HNSCC. The score was calculated using the formula: 0.0636 × CXCL11 − 0.4619 × CXCR3 + 0.2398 × CCR5. Patients with high scores had significantly worse overall survival than those with low scores (p < 0.001). The risk score showed good performance in characterizing tumor-infiltrating lymphocytes and provided a theoretical basis for stratifying patients receiving immune therapies. Additionally, a nomogram including the risk score, age, and TNM stage was constructed. The prediction model displayed marginally better discrimination ability and higher agreement in predicting the survival of patients with HNSCC compared with the TNM stage.

scholarly journals Biomarkers for Immune Modulatory Treatment in Head and Neck Squamous Cell Carcinoma (HNSCC)

2021 ◽  
pp. 83-91
Author(s):  
Danny Rischin
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Neck Squamous Cell Carcinoma

AbstractImmune checkpoint inhibitors have changed the standard of care for recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC). However, only a minority of patients respond, hence the search for predictive biomarkers. Potential predictive biomarkers for immune checkpoint inhibitors discussed in this chapter include (1) Immune checkpoint ligand expression e.g., PD-L1, (2) biomarkers of a T-cell inflamed tumour microenvironment (TME) such as gene expression profiles of activated T cells, (3) biomarkers of tumour neoepitope burden such as tumour mutation burden (TMB) and (4) multidimensional quantitative techniques. At present only PD-L1 expression has been shown to have clinical utility in head and neck cancer. It enriches for populations more likely to respond, but the false positive predictive value remains high. In the pivotal Keynote−048 trial that established a role for pembrolizumab (anti-PD1) monotherapy and pembrolizumab + chemotherapy as treatment options in first-line R/M HNSCC, primary endpoints included overall survival in defined subgroups based on PD-L1 expression. In this trial the combined positive score (CPS) was used which takes into account PD-L1 expression in tumour and immune cells. Based on this trial regulatory approvals for first-line pembrolizumab in R/M HNSCC require assessment of PD-L1 expression using the CPS. Finally we discuss emerging evidence that locoregionally advanced HPV-associated oropharyngeal cancers that have high expression of CD103 positive CD8 T cells have an excellent prognosis and features that suggest increased probability of responding to anti-PD1/PD-L1, raising the possibility of incorporating these immune therapies as part of a de-escalation trial strategy.

scholarly journals Prognostic value of novel immune-related genomic biomarkers identified in head and neck squamous cell carcinoma

2020 ◽  
Vol 8 (2) ◽  
pp. e000444
Author(s):  
Yao Yao ◽  
Zhongyi Yan ◽  
Senlin Lian ◽  
Liangnian Wei ◽  
Chao Zhou ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Rna Sequencing ◽  
Squamous Cell ◽  
Cox Regression ◽  
Neck Squamous Cell Carcinoma ◽  
Kaplan Meier ◽  
Immune Related Genes

BackgroundThe immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, a paucity of robust, reliable immune-related biomarkers has been identified that are capable of estimating prognosis in HNSCC patients.MethodsHigh-throughput RNA sequencing was performed in tumors and matched adjacent tissues from five HNSCC patients, and the immune signatures expression of 730 immune-related transcripts selected from the nCounter PanCancer Immune Profiling Panel were assessed. Survival analyzes were performed in a training cohort, consisting of 416 HNSCC cases, retrieved from The Cancer Genome Atlas (TCGA) database. A prognostic signature was built, using elastic net-penalized Cox regression and backward, stepwise Cox regression analyzes. The outcomes were validated by an independent cohort of 115 HNSCC patients, using tissue microarrays and immunohistochemistry staining. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was also used to estimate the relative fractions of 22 immune-cell types and their correlations coefficients with prognostic biomarkers.ResultsCollectively, 248 immune-related genes were differentially expressed in paired tumors and normal tissues using RNA sequencing. After process screening in the training TCGA cohort, four immune-related genes (PVR, TNFRSF12A, IL21R, and SOCS1) were significantly associated with overall survival (OS). Integrating these genes with Path_N stage, a multiplex model was built and suggested better performance in determining 5 years OS (receiver operating characteristic (ROC) analysis, area under the curve (AUC)=0.709) than others. Further protein-based validation was conducted in 115 HNSCC patients. Similarly, high expression of PVR and TNFRSF12A were associated with poor OS (Kaplan-Meier p=0.017 and 0.0032), while high expression of IL21R and SOCS1 indicated favorable OS (Kaplan-Meier p<0.0001 and =0.0018). The integrated model with Path_N stage still demonstrated efficacy in OS evaluation (Kaplan-Meier p<0.0001, ROC AUC=0.893). Besides, the four prognostic genes were significantly correlated with activated CD8+ T cells, CD4+ T cells, follicular helper T cells and regulatory T cells, implying the possible involvement of these genes in the immunoregulation and development of HNSCC.ConclusionsThe well-established model encompassing both immune-related biomarkers and clinicopathological factor might serve as a promising tool for the prognostic prediction of HNSCC.

scholarly journals Automated PD-L1 Scoring Using Artificial Intelligence in Head and Neck Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 4409
Author(s):  
Behrus Puladi ◽  
Mark Ooms ◽  
Svetlana Kintsler ◽  
Khosrow Siamak Houschyar ◽  
Florian Steib ◽  
...  
Keyword(s):  
Neural Networks ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Patient Selection ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Neck Squamous Cell Carcinoma ◽  
Novel Approach

Immune checkpoint inhibitors (ICI) represent a new therapeutic approach in recurrent and metastatic head and neck squamous cell carcinoma (HNSCC). The patient selection for the PD-1/PD-L1 inhibitor therapy is based on the degree of PD-L1 expression in immunohistochemistry reflected by manually determined PD-L1 scores. However, manual scoring shows variability between different investigators and is influenced by cognitive and visual traps and could therefore negatively influence treatment decisions. Automated PD-L1 scoring could facilitate reliable and reproducible results. Our novel approach uses three neural networks sequentially applied for fully automated PD-L1 scoring of all three established PD-L1 scores: tumor proportion score (TPS), combined positive score (CPS) and tumor-infiltrating immune cell score (ICS). Our approach was validated using WSIs of HNSCC cases and compared with manual PD-L1 scoring by human investigators. The inter-rater correlation (ICC) between human and machine was very similar to the human-human correlation. The ICC was slightly higher between human-machine compared to human-human for the CPS and ICS, but a slightly lower for the TPS. Our study provides deeper insights into automated PD-L1 scoring by neural networks and its limitations. This may serve as a basis to improve ICI patient selection in the future.

scholarly journals Tumor hypoxia is associated with resistance to PD-1 blockade in squamous cell carcinoma of the head and neck

2021 ◽  
Vol 9 (5) ◽  
pp. e002088
Author(s):  
Dan P Zandberg ◽  
Ashley V Menk ◽  
Maria Velez ◽  
Daniel Normolle ◽  
Kristin DePeaux ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Cd8 T Cells ◽  
Oxidative Metabolism ◽  
Cox Regression ◽  
Tumor Hypoxia ◽  
Parental Line

The majority of patients with recurrent/metastatic squamous cell carcinoma of the head and neck (HNSCC) (R/M) do not benefit from anti-PD-1 therapy. Hypoxia induced immunosuppression may be a barrier to immunotherapy. Therefore, we examined the metabolic effect of anti-PD-1 therapy in a murine MEER HNSCC model as well as intratumoral hypoxia in R/M patients. In order to characterize the tumor microenvironment in PD-1 resistance, a MEER cell line was created from the parental line that are completely resistant to anti-PD-1. These cell lines were then metabolically profiled using seahorse technology and injected into C57/BL6 mice. After tumor growth, mice were pulsed with pimonidazole and immunofluorescent imaging was performed to analyze hypoxia and T cell infiltration. To validate the preclinical results, we analyzed tissues from R/M patients (n=36) treated with anti-PD-1 mAb, via immunofluorescent imaging for number of CD8+ T cells (CD8), Tregs and the percent area (CAIX) and mean intensity (I) of carbonic anhydrase IX in tumor. We analyzed disease control rate (DCR), progression free survival (PFS), and overall survival (OS) using proportional odds and proportional hazards (Cox) regression. We found that anti-PD-1 resistant MEER has significantly higher oxidative metabolism, while there was no difference in glycolytic metabolism. Intratumoral hypoxia was significantly increased and CD8+ T cells decreased in anti-PD-1 resistant tumors compared with parental tumors in the same mouse. In R/M patients, lower tumor hypoxia by CAIX/I was significantly associated with DCR (p=0.007), PFS, and OS, and independently associated with response (p=0.028) and PFS (p=0.04) in a multivariate model including other significant immune factors. During PD-1 resistance, tumor cells developed increased oxidative metabolism leading to increased intratumoral hypoxia and a decrease in CD8+ T cells. Lower tumor hypoxia was independently associated with increased efficacy of anti-PD-1 therapy in patients with R/M HNSCC. To our knowledge this is the first analysis of the effect of hypoxia in this patient population and highlights its importance not only as a predictive biomarker but also as a potential target for therapeutic intervention.

scholarly journals Bioinformatics analysis of DNMT1 expression and its role in head and neck squamous cell carcinoma prognosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jili Cui ◽  
Lian Zheng ◽  
Yuanyuan Zhang ◽  
Miaomiao Xue
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Hub Genes ◽  
Significant Difference ◽  
Dnmt1 Expression

AbstractHead and neck squamous cell carcinoma (HNSCC) is the sixth most common type of malignancy in the world. DNA cytosine-5-methyltransferase 1 (DNMT1) play key roles in carcinogenesis and regulation of the immune micro-environment, but the gene expression and the role of DNMT1 in HNSCC is unknown. In this study, we utilized online tools and databases for pan-cancer and HNSCC analysis of DNMT1 expression and its association with clinical cancer characteristics. We also identified genes that positively and negatively correlated with DNMT1 expression and identified eight hub genes based on protein–protein interaction (PPI) network analysis. Enrichment analyses were performed to explore the biological functions related with of DNMT1. The Tumor Immune Estimation Resource (TIMER) database was performed to explore the relationship between DNMT1 expression and immune-cell infiltration. We demonstrated that DNMT1 gene expression was upregulated in HNSCC and associated with poor prognosis. Based on analysis of the eight hub genes, we determined that DNMT1 may be involved in cell cycle, proliferation and metabolic related pathways. We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.

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