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 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 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 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 &lt; 0.001), CTLA4 (r = -0.26, P &lt; 0.001), LAG3 (r = -0.22, P &lt; 0.001) and HAVCR2 (r = -0.2, P &lt; 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 Analysis of radiotherapy‑induced alteration of CD8+ T cells and PD‑L1 expression in patients with uterine cervical squamous cell carcinoma

2021 ◽  
Vol 21 (6) ◽  
Author(s):  
Yasumasa Mori ◽  
Hiro Sato ◽  
Takuya Kumazawa ◽  
Tiara Permata ◽  
Yuya Yoshimoto ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cd8 T Cells ◽  
Cervical Squamous Cell Carcinoma

scholarly journals 903 Human cancer-associated fibroblast subsets can predict immune checkpoint response in head and neck cancer patients

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A947-A947
Author(s):  
Diana Graves ◽  
Aleksandar Obradovic ◽  
Michael Korrer ◽  
Yu Wang ◽  
Sohini Roy ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Head And Neck Cancer ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Single Cell ◽  
Rna Sequencing ◽  
Neck Cancer ◽  
Squamous Cell ◽  
Single Cell Rna Sequencing

BackgroundUse of anti-PD-1 immune checkpoint inhibitors (ICI) is currently the first line therapy for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), but critical work remains in identifying factors guiding resistance mechanisms.1 2 While recent studies have specifically implicated cancer-associated fibroblasts (CAFs) as potential mediators of immunotherapy response, the immunoregulatory role of CAFs in head and neck cancer has not been thoroughly explored.3–5MethodsTo determine if there are changes in cell populations associated with anti-PD-1 therapy in head and neck cancer patients, we performed high dimensional single-cell RNA sequencing (scRNA-SEQ) from a neoadjuvant trial of 50 advanced-stage head and neck squamous cell carcinoma (HNSCC) patients that were treated with the anti-PD-1 therapy, nivolumab, for the duration of one month. Tumor specimens were analyzed pre- and post-treatment with single-cell RNA sequencing performed on 4 patients as well as bulk RNA sequencing on 40 patients. Matched scRNA-SEQ data was analyzed using the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) and Virtual Inference of Protein-activity by Enriched Regulon (VIPER) bioinformatic analysis platform to determine TME cells that correlated with response and resistance to nivolumab.6 For CAF functional studies, surgical tumor specimens were processed and enriched for CAF subtypes, and these were co-cultured with T cells from peripheral blood and tumor infiltrating lymphocytes.ResultsWe identified 14 distinct cell types present in HNSCC patients. Of these 14 cell types, the fibroblast subtype showed significant changes in abundance following nivolumab treatment. We identified 5 distinct clusters of cancer-associated fibroblast subsets (HNCAF-0, 1, 2, 3, and 4) of which, two clusters, HNCAF-0 and HNCAF-3 were predictive of patient response to anti-PD-1 therapy. To determine the significance of these CAF subsets’ function, we isolated HNCAF-0/3 cells from primary HNSCC tumor specimens and co-cultured with primary human T cells. Analysis by flow cytometry showed that HNCAF-0/3 reduced TGFβ-dependent PD-1+TIM-3+ exhaustion of T cells and increased CD103+NKG2A+ resident memory phenotype and cytotoxicity to enhance overall function.ConclusionsTo our knowledge, we are the first to characterize CAF heterogeneity within the head and neck TME and show direct immunostimulatory activity of CAFs. Our findings demonstrate the functional importance of CAF subsets in modulating the immunoregulatory milieu of the human HNSCC, and we have identified clinically actionable CAF subtypes that can be used as a biomarker of response and resistance in future clinical trials.Trial RegistrationNCT03238365ReferencesFerris RL, Blumenschein Jr G, Fayette J, Guigay J, Colevas AD, Licitra L, Harrington K, Kasper S, Vokes EE, Even C, et al. Nivolumab for recurrent squamous-cell carcinoma of the head and neck. N Engl J Med 2016;375:1856–1867.Seiwert TY, Burtness B, Mehra R, Weiss J, Berger R, Eder JP, Heath K, McClanahan T, Lunceford J, Gause C, et al. Safety and clinical activity of pembrolizumab for treatment of recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-012): an open-label, multicentre, phase 1b trial. Lancet Oncol 2016;17:956–965.Dominguez CX, Muller S, Keerthivasan S, Koeppen H, Hung J, Gierke S, Breart B, Foreman O, Bainbridge TW, Castiglioni A, et al. Single-cell RNA sequencing reveals stromal evolution into LRRC15(+) myofibroblasts as a determinant of patient response to cancer immunotherapy. Cancer Discov 2020;10:232–253.Feig C, Jones JO, Kraman M, Wells RJ, Deonarine A, Chan DS, Connell CM, Roberts EW, Zhao Q, Caballero OL, et al. Targeting CXCL12 from FAP-expressing carcinoma-associated fibroblasts synergizes with anti-PD-L1 immunotherapy in pancreatic cancer. Proc Natl Acad Sci U S A 2013;110:20212–20217.Kieffer Y, Hocine HR, Gentric G, Pelon F, Bernard C, Bourachot B, Lameiras S, Albergante L, Bonneau C, Guyard A, et al. Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer. Cancer Discov 2020;10:1330–1351.Obradovic A, Chowdhury N, Haake SM, Ager C, Wang V, Vlahos L, Guo XV, Aggen DH, Rathmell WK, Jonasch E, et al. Single-cell protein activity analysis identifies recurrence-associated renal tumor macrophages. Cell 2021;184:2988–3005.Ethics ApprovalPatients provided informed consent for this work. All experimental procedures were approved by the Institutional Review Board of Vanderbilt University Medical Center (IRB: 171883).

scholarly journals An integrated nomogram combining lncRNAs classifier and clinicopathologic factors to predict the recurrence of head and neck squamous cell carcinoma

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jie Cui ◽  
Qingquan Wen ◽  
Xiaojun Tan ◽  
Jinsong Piao ◽  
Qiong Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Calibration Curve ◽  
Cox Regression ◽  
Curve Analysis ◽  
Tnm Stage ◽  
Decision Curve Analysis ◽  
Clinicopathologic Factors

AbstractLong non-coding RNAs (lncRNAs) which have little or no protein-coding capacity, due to their potential roles in the cancer disease, caught a particular interest. Our study aims to develop an lncRNAs-based classifier and a nomogram incorporating the lncRNAs classifier and clinicopathologic factors to help to improve the accuracy of recurrence prediction for head and neck squamous cell carcinoma (HNSCC) patients. The HNSCC lncRNAs profiling data and the corresponding clinicopathologic information were downloaded from TANRIC database and cBioPortal. Using univariable Cox regression and Least absolute shrinkage and selection operator (LASSO) analysis, we developed 15-lncRNAs-based classifier related to recurrence. On the basis of multivariable Cox regression analysis results, a nomogram integrating the genomic and clinicopathologic predictors was built. The predictive accuracy and discriminative ability of the inclusive nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was conducted to evaluate clinical value of our nomogram. Consequently, fifteen recurrence-free survival (RFS) -related lncRNAs were identified, and the classifier consisting of the established 15 lncRNAs could effectively divide patients into high-risk and low-risk subgroup. The prediction ability of the 15-lncRNAs-based classifier for predicting 3- year and 5-year RFS were 0.833 and 0.771. Independent factors derived from multivariable analysis to predict recurrence were number of positive LNs, margin status, mutation count and lncRNAs classifier, which were all embedded into the nomogram. The calibration curve for the recurrence probability showed that the predictions based on the nomogram were in good coincide with practical observations. The C-index of the nomogram was 0.76 (0.72–0.79), and the area under curve (AUC) of nomogram in predicting RFS was 0.809, which were significantly higher than traditional TNM stage and 15-lncRNAs-based classifier. Decision curve analysis further demonstrated that our nomogram had larger net benefit than TNM stage and 15-lncRNAs-based classifier. The results were confirmed externally. In summary, a visually inclusive nomogram for patients with HNSCC, comprising genomic and clinicopathologic variables, generates more accurate prediction of the recurrence probability when compared TNM stage alone, but more additional data remains needed before being used in clinical practice.

Sign in / Sign up

Export Citation Format

Share Document