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A gene expression-based immune content predictor for survival and postoperative radiotherapy response in head and neck cancer.

ABSTRACT: The immune infiltration in the tumor microenvironment has been demonstrated to be relevant to radiotherapy response. Here, we sought to understand the immune infiltration in head and neck cancer (HNC) and evaluate its significance in predicting prognosis and radiotherapy response. Using RNA sequencing data of 522 retrospective head and neck squamous cell carcinomas (HNSCCs), we constructed an immune content score based on genes related to 6 prognostic infiltrating cell types. Unsupervised hallmark pathway clustering demonstrated an immune-related tumor cluster containing the immune content score. Patients with high immune content scores exhibited favorable overall survival and disease-free survival (DFS). Moreover, the immune content score was an independent prognostic factor for DFS in HNSCC. Interestingly, the immune content score was strongly associated with radiation response pathways. These results were also extended to nasopharyngeal carcinoma. Furthermore, patients in the low immune content score group significantly gained overall survival benefits from postoperative radiotherapy (PORT), whereas patients in the high immune content score group did not. Therefore, this study identifies the immune content score as a prognostic tool, which might have a potential association with PORT response, thereby facilitating outcome prediction and treatment decision in HNC.

SUBMITTER: Li Y

PROVIDER: S-EPMC8430044 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceThe standard of care for initiation of postoperative radiotherapy (PORT) in head and neck squamous cell carcinoma (HNSCC) is within 6 weeks of surgical treatment. Delays in guideline-adherent PORT initiation are common, associated with mortality, and a measure of quality care, but patient-specific tools to estimate the risk of these delays are lacking.ObjectiveTo develop and validate 2 nomograms (that use presurgical and postsurgical data) for predicting delayed PORT initiation.Design, setting, and participantsThis cohort study obtained patient data from January 1, 2004, to December 31, 2015, from the National Cancer Database. Adults aged 18 years or older with a newly diagnosed HNSCC who underwent surgical treatment and PORT at a Commission on Cancer-accredited facility were included. Data analysis was conducted from June 2, 2019, to January 29, 2020.ExposuresSurgical treatment and PORT.Main outcomes and measuresThe primary outcome measure was PORT initiation more than 6 weeks after the surgical intervention. Multivariable logistic regression models were created in a random selection of 80% of the sample (derivation cohort) and were internally validated with bootstrapping, assessed for discrimination by calibration plots and the concordance (C) index, and externally validated in the remaining 20% of the sample (validation cohort).ResultsThe study included 60 766 adults with HNSCC who were grouped into derivation and validation cohorts. The derivation cohort comprised 48 625 patients (mean [SD] age, 59.59 [11.3] years; 36 825 men [75.7%]) selected randomly from the full sample, whereas 12 151 patients (mean [SD] age, 59.63 [11.2] years; 9266 men [76.3%]) composed the validation cohort. The rate of PORT delay was 55.8% (n=27140) in the derivation cohort and 56.7% (n=6900) in the validation cohort. Both nomograms created to predict the risk of PORT initiation delay used variables, including race/ethnicity, insurance type, tumor site, and facility type. The nomogram based on presurgical variables included clinical stage and severity of comorbidity, whereas the nomogram with postsurgical variables included US region, length of stay, and care fragmentation between surgical and radiotherapy facilities. For the presurgical nomogram, the concordance indices were 0.670 (95% CI, 0.664-0.676) in the derivation cohort and 0.674 (95% CI, 0.662-0.685) in the validation cohort. For the nomogram with postsurgical variables, the concordance indices were 0.691 (95% CI, 0.686-0.696) in the derivation cohort and 0.694 (95% CI, 0.685-0.704) in the validation cohort.Conclusions and relevanceThis study found that a nomogram developed with presurgical data to generate personalized estimates of PORT initiation delay may improve pretreatment counseling and the delivery of interventions to patients at high risk for such a delay. A nomogram including postsurgical data can drive institutional quality improvement initiatives and enhance risk-adjusted comparisons of delay rates across facilities.

Project description:Background and purposeHead and neck squamous carcinoma (HNSCC), characterized by immunosuppression, is a group of highly heterogeneous cancers. Although immunotherapy exerts a promising influence on HNSCC, the response rate remains low and varies in assorted primary sites. Immunological mechanisms underlying HNSCC pathogenesis and treatment response are not fully understood. This study aimed to develop a differentially expressed genes (DEGs)-based risk model to predict immunotherapy efficacy and stratify prognosis of HNSCC patients.Materials and methodsThe expression profiles of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The tumor microenvironment and immune response were estimated by cell type identification via estimating relative subset of known RNA transcripts (CIBERSORT) and immunophenoscore (IPS). The differential expression pattern based on human papillomavirus status was identified. A DEGs-based prognostic risk model was developed and validated. All statistical analyses were performed with R software (version 3.6.3).ResultsBy using the TCGA database, we identified DKK1, HBEGF, RNASE7, TNFRSF12A, INHBA, and IPIK3R3 as DEGs that were associated with patients' overall survival (OS). Patients were stratified into the high- and low-risk subgroups according to a DEGs-based prognostic risk model. Significant difference in OS was found between the high- and low-risk patients (1.64 vs. 2.18 years, P = 0.0017). In multivariate Cox analysis, the risk model was an independent prognostic factor for OS (hazard radio = 1.06, 95% confidence interval [1.02-1.10], P = 0.004). More CD8+ T cells and regulatory T cells were observed in the low-risk group and associated with a favorable prognosis. The IPS analysis suggested that the low-risk patients possessed a higher IPS score and a higher immunoreactivity phenotype, which were correlated with better immunotherapy response.ConclusionCollectively, we established a reliable DEGs-based risk model with potential prognostic value and capacity to predict the immunophenotype of HNSCC patients.

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A gene expression-based immune content predictor for survival and postoperative radiotherapy response in head and neck cancer.

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