Development and validation of a new comorbidity index for patients with head and neck squamous cell carcinoma in Japan.
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ABSTRACT:
SUBMITTER: Takenaka Y
PROVIDER: S-EPMC5544709 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide, accounting for almost 50% of all malignancies in developing nations. Autophagy plays a vital role in cancer initiation, malignant progression, and resistance to treatment. However, autophagy-related gene sets have rarely been analyzed in HNSCC. Hence, it is necessary to assess its clinical and pathological significance in a larger cohort of patients with HNSCC. The purpose of this study was to establish a novel autophagy-related prognostic marker for HNSCC. We screened 232 autophagy-related genes (ARGs) and identified 38 differentially expressed ARGs in The Cancer Genome Atlas (TCGA) cohorts. The prognosis-related ARGs signature, established using the univariate and multivariate Cox proportional regression models, consists of 10 ARGs that could divide patients into high-risk and low-risk groups. Survival analysis indicated that patients in the high-risk group had dramatically shorter overall survival compared with their low-risk counterparts. Cox regression analysis further confirmed the independent prognostic value of the autophagy-related signature, and the area under the receiver operating characteristic curve of the combined prognostic model was 0.722. Finally, the efficacy of autophagy-related signature was also validated by an independent cohort from the Gene Expression Omnibus (GEO) database. Collectively, we successfully constructed a novel autophagy-related signature for the prediction of prognosis in patients with HNSCC.
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Project description:Quantitative (iTRAQ 4-plex) proteomic analysis of progressive head and neck cancers
2022-03-01 | PXD001438 | Pride
Project description:For locally advanced head and neck squamous cell carcinoma (HNSCC), therapeutic decisions depend on comorbidity or age. We estimated the treatment outcomes of patients with different Charlson comorbidity index (CCI) scores and ages to determine whether aggressive treatment improves survival.Data from the Taiwan National Health Insurance and cancer registry databases were analyzed, and we included >20-year-old patients with American Joint Committee on Cancer (AJCC) stage III or IV HNSCC (International Classification of Diseases, Ninth Revision, Clinical Modification codes 140.0-148.9) undergoing surgery, chemotherapy (CT), radiotherapy (RT), concurrent chemoradiotherapy (CCRT), sequential CT and RT, or surgery with adjuvant treatment. The exclusion criteria were a past cancer history, distant metastasis, AJCC stage I or II, missing sex data, an age < 20 years, nasopharyngeal cancer, in situ carcinoma, sarcoma, and HNSCC recurrence. The index date was the date of first HNSCC diagnosis, and comorbidities were scored using the CCI. The enrolled patients were categorized into Group 1 (curative-intent aggressive treatments) and Group 2 (best supportive care or palliative treatments).We enrolled 21,174 stage III or IV HNSCC patients without distant metastasis (median follow-up, 3.25 years). Groups 1 and 2 comprised 18,584 and 2232 patients, respectively. After adjustment for age, sex, and clinical stage, adjusted hazard ratios (95% confidence intervals) of overall death in Group 1 were 0.33 (0.31-0.35), 0.34 (0.31-0.36), and 0.37 (0.28-0.49), and those of all-cause death among patients undergoing curative surgical aggressive treatments were 1.13 (0.82-1.55), 0.67 (0.62-0.73), and 0.49 (0.46-0.53) for CCI scores of ?10, 5 to 9, and <5, respectively.Aggressive treatments improve survival in elderly (?65 years) and critically ill HNSCC patients. Curative nonsurgical aggressive treatments including definitive RT or CCRT might be suitable for HNSCC patients with CCI scores ?10.
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Project description:Head and neck squamous cell carcinoma (HNSCC) is among the most destructive of tumors, leading to considerable morbidity and mortality. Abnormal immune microenvironment is closely associated with tumor progression. This study aimed to construct a robust immune prognostic model for HNSCC. The RNA-seq transcriptome data and clinical information of HNSCC were downloaded from The Cancer Genome Atlas (TCGA) database. The key pathways and transcriptional factors (TFs) that are correlated with significantly altered immune related genes were identified. A robust immune prognostic model was constructed and further validated using a discovery-validation cohort design. An immune prognostic signature-based nomogram model was also developed. We have identified 400 significantly changed immune related genes in HNSCC. In addition, functional analysis of the altered immune related genes revealed many biological functions and pathways that might affect the tumor immune microenvironment. FOXP3, SNAI2, and STAT1 were identified as the hub TFs for regulating immunological changes in HNSCC. Moreover, an immune related gene-based prognostic signature significantly associated with the overall survival (OS) of HNSCC was constructed in the discovery cohort, and successfully validated in the validation cohort. Finally, a nomogram model based on immune prognostic signature was built and exhibited good performance for predicting the OS of HNSCC. In conclusion, the immune prognostic model is robust for predicting the prognosis of HNSCC and may evolve as a promising tool for risk evaluation and therapeutic selection.
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Project description:BackgroundRadiomics-based non-invasive biomarkers are promising to facilitate the translation of therapeutically related molecular subtypes for treatment allocation of patients with head and neck squamous cell carcinoma (HNSCC).MethodsWe included 113 HNSCC patients from The Cancer Genome Atlas (TCGA-HNSCC) project. Molecular phenotypes analyzed were RNA-defined HPV status, five DNA methylation subtypes, four gene expression subtypes and five somatic gene mutations. A total of 540 quantitative image features were extracted from pre-treatment CT scans. Features were selected and used in a regularized logistic regression model to build binary classifiers for each molecular subtype. Models were evaluated using the average area under the Receiver Operator Characteristic curve (AUC) of a stratified 10-fold cross-validation procedure repeated 10 times. Next, an HPV model was trained with the TCGA-HNSCC, and tested on a Stanford cohort (N = 53).FindingsOur results show that quantitative image features are capable of distinguishing several molecular phenotypes. We obtained significant predictive performance for RNA-defined HPV+ (AUC = 0.73), DNA methylation subtypes MethylMix HPV+ (AUC = 0.79), non-CIMP-atypical (AUC = 0.77) and Stem-like-Smoking (AUC = 0.71), and mutation of NSD1 (AUC = 0.73). We externally validated the HPV prediction model (AUC = 0.76) on the Stanford cohort. When compared to clinical models, radiomic models were superior to subtypes such as NOTCH1 mutation and DNA methylation subtype non-CIMP-atypical while were inferior for DNA methylation subtype CIMP-atypical and NSD1 mutation.InterpretationOur study demonstrates that radiomics can potentially serve as a non-invasive tool to identify treatment-relevant subtypes of HNSCC, opening up the possibility for patient stratification, treatment allocation and inclusion in clinical trials. FUND: Dr. Gevaert reports grants from National Institute of Dental & Craniofacial Research (NIDCR) U01 DE025188, grants from National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (NIBIB), R01 EB020527, grants from National Cancer Institute (NCI), U01 CA217851, during the conduct of the study; Dr. Huang and Dr. Zhu report grants from China Scholarship Council (Grant NO:201606320087), grants from China Medical Board Collaborating Program (Grant NO:15-216), the Cyrus Tang Foundation, and the Zhejiang University Education Foundation during the conduct of the study; Dr. Cintra reports grants from São Paulo State Foundation for Teaching and Research (FAPESP), during the conduct of the study.
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Project description:Head and neck squamous cell carcinoma (HNSCC) is one of the greatest public challenges because of delayed diagnosis and poor prognosis. In this study, we established an autophagy-associated long non-coding (Lnc)RNA prognostic signature to assess the prognosis of HNSCC patients. The LncRNA expression profiles and clinical information of 499 HNSCC samples were available in The Cancer Genome Atlas. Autophagic LncRNAs were analyzed using Pearson correlation. A co-expression network showed the interactions between autophagic genes and LncRNAs. An autophagic LncRNAs prognostic signature, consisting of MYOSLID, AL139287.1, AC068580.1, AL022328.2, AC104083.1, AL160006.1, AC116914.2, LINC00958, and AL450992.2, was developed through uni- and multivariate Cox regressions. High- and low-risk groups were classified based on the median risk scores. The high-risk group had significantly worse overall survival according to Kaplan-Meier curve analysis. Multivariate Cox regression demonstrated that risk scores were a significant independent prognostic factor (hazard ratio = 1.739, 95% confidence interval: 1.460-2.072), with an area under the curve of 0.735. Principal component analysis distinguished two categories based on the nine-LncRNA prognostic signature. In conclusion, this novel autophagic LncRNA signature is an independent prognostic factor and may suggest novel therapeutic targets for HNSCC.
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Project description:Most head and neck cancers are derived from the mucosal epithelium in the oral cavity, pharynx and larynx and are known collectively as head and neck squamous cell carcinoma (HNSCC). Oral cavity and larynx cancers are generally associated with tobacco consumption, alcohol abuse or both, whereas pharynx cancers are increasingly attributed to infection with human papillomavirus (HPV), primarily HPV-16. Thus, HNSCC can be separated into HPV-negative and HPV-positive HNSCC. Despite evidence of histological progression from cellular atypia through various degrees of dysplasia, ultimately leading to invasive HNSCC, most patients are diagnosed with late-stage HNSCC without a clinically evident antecedent pre-malignant lesion. Traditional staging of HNSCC using the tumour-node-metastasis system has been supplemented by the 2017 AJCC/UICC staging system, which incorporates additional information relevant to HPV-positive disease. Treatment is generally multimodal, consisting of surgery followed by chemoradiotherapy (CRT) for oral cavity cancers and primary CRT for pharynx and larynx cancers. The EGFR monoclonal antibody cetuximab is generally used in combination with radiation in HPV-negative HNSCC where comorbidities prevent the use of cytotoxic chemotherapy. The FDA approved the immune checkpoint inhibitors pembrolizumab and nivolumab for treatment of recurrent or metastatic HNSCC and pembrolizumab as primary treatment for unresectable disease. Elucidation of the molecular genetic landscape of HNSCC over the past decade has revealed new opportunities for therapeutic intervention. Ongoing efforts aim to integrate our understanding of HNSCC biology and immunobiology to identify predictive biomarkers that will enable delivery of the most effective, least-toxic therapies.
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Project description:Evidence shows that defects in RNA-binding proteins (RBPs) are closely related to the occurrence and development of HNSCC. We obtained 502 tumors and 44 normal samples from the TCGA database, among which 190 differentially expressed RBPs were screened. Finally, a prognostic model containing nine RBPs (CELF2, CPEB1, DDX39B, EIF3L, EZH2, KHDRBS3, RNASE10, RNASE3 and SIDT1) was produced. Further analysis showed that the overall survival rate in the high-risk group was lower than that in the low-risk group. The area under the ROC curve (AUC) in the training and testing groups was significant (3-year AUC, 0.735 vs 0.796; 5-year AUC, 0.821 vs 0.804). In addition, a comprehensive analysis of nine identified RBPs showed that most of them were related to the OS of HNSCC patients, and three of them (CELF2, EZH2, and SIDT1) were differentially expressed in HNSCC and control tissues at the protein level. In addition, our data revealed that the identified RBPs are highly interconnected, with high frequency copy number changes in HNSCC samples. GSEA indicated that the abnormal biological processes related to RNA and the activation of some classical tumor signaling pathways were important driving forces for the development of HNSCC. Our results provide novel insights into the pathogenesis of HNSCC, among which nine RBP markers have potential application value in clinical decision-making and individualized treatment of HNSCC.
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Project description:Head and neck epithelial tissue tumors may be identified as head and neck squamous cell carcinoma (HNSC). Numerous malignancies are encouraged by dysregulation of the FGF19-β-Klotho (KLB) axis in the tumor microenvironment. Using protein databases and RT-qPCR, we examined KLB expression in HNSC. In HNSC, higher KLB expression was linked to longer survival times and better prognoses. Furthermore, variations in drug susceptibility and immunological infiltration were noted according to KLB expression levels. These results underscore the importance of KLB in the course and management of HNSC by indicating that it may function as a possible prognostic marker and influence immunological and therapeutic responses in these individuals. Further study on HNSC is necessary to investigate KLB's potential as a therapeutic target and prognostic indicator.
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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.
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