PTTG and PBF Functionally Interact with p53 and Predict Overall Survival in Head and Neck Cancer.
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ABSTRACT:
SUBMITTER: Read ML
PROVIDER: S-EPMC6193540 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Publications
PTTG and PBF Functionally Interact with p53 and Predict Overall Survival in Head and Neck Cancer.
Read Martin L ML Read Martin L ML Modasia Bhavika B Fletcher Alice A Thompson Rebecca J RJ Brookes Katie K Rae Peter C PC Nieto Hannah R HR Poole Vikki L VL Roberts Sally S Roberts Sally S Campbell Moray J MJ Boelaert Kristien K Turnell Andrew S AS Smith Vicki E VE Mehanna Hisham H Mehanna Hisham H McCabe Christopher J CJ
Cancer research 20180828 20
Head and neck squamous cell carcinoma (HNSCC) is the 6th most common cancer worldwide and poses a significant health burden due to its rising incidence. Although the proto-oncogene pituitary tumor-transforming gene 1 (PTTG) predicts poor patient outcome, its mechanisms of action are incompletely understood. We show here that the protein PBF modulates PTTG function, is overexpressed in HNSCC tumors, and correlates with significantly reduced survival. Lentiviral shRNA attenuation of PTTG or PBF ex ...[more]
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Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers. The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients.MethodIn this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy.ResultsWe extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database. Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively. Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk (HR = 1.144, 95% CI = 1.044 ~ 1.251) and the lowest risk (HR = 0.580, 95% CI = 0.400 ~ 0.839) in HNSCC, respectively. We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC. The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively. Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset. On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset.ConclusionTaken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset. Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.
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Project description:A major challenge in radiomics is assembling data from multiple centers. Sharing data between hospitals is restricted by legal and ethical regulations. Distributed learning is a technique, enabling training models on multicenter data without data leaving the hospitals ("privacy-preserving" distributed learning). This study tested feasibility of distributed learning of radiomics data for prediction of two year overall survival and HPV status in head and neck cancer (HNC) patients. Pretreatment CT images were collected from 1174 HNC patients in 6 different cohorts. 981 radiomic features were extracted using Z-Rad software implementation. Hierarchical clustering was performed to preselect features. Classification was done using logistic regression. In the validation dataset, the receiver operating characteristics (ROC) were compared between the models trained in the centralized and distributed manner. No difference in ROC was observed with respect to feature selection. The logistic regression coefficients were identical between the methods (absolute difference <10-7). In comparison of the full workflow (feature selection and classification), no significant difference in ROC was found between centralized and distributed models for both studied endpoints (DeLong p > 0.05). In conclusion, both feature selection and classification are feasible in a distributed manner using radiomics data, which opens new possibility for training more reliable radiomics models.
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Project description:Poor oral hygiene is an established risk factor of head and neck cancer (HNC); however, its role in the survival of HNC patients is unclear. This study evaluated the association between oral hygiene habits, including regular dental visits, frequency of tooth brushing, and use of dental floss, and the overall survival (OS) of HNC patients using interview data collected from 740 HNC patients. In addition, the interactions between oral hygiene and the polymorphisms of TLR2 and TLR4 on the OS of HNC patients were assessed. The analysis indicated that poor oral hygiene was significantly associated with poorer OS of HNC patients (hazard ratio (HR) = 1.38, 95% confidence interval (CI): 1.03-1.86). This association was modified by a single nucleotide polymorphism, rs11536889, of TLR4. A significant association between poor oral hygiene and worse survival of HNC was observed among those with the CG or CC genotype (HR = 2.32, 95% CI: 1.41-3.82) but not among those with the GG genotype (HR = 0.95, 95% CI: 0.65-1.40). Our results suggested that poor oral hygiene is not only a risk factor but may also be a prognostic factor of HNC.
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Project description:ImportanceData are limited on the prognostic value of human papillomavirus (HPV) status for head and neck carcinoma subsites.ObjectiveTo determine whether HPV positivity at each head and neck subsite is associated with improved overall survival.Design, setting, and participantsThis retrospective population-based cohort study used the National Cancer Database to identify patients diagnosed with head and neck squamous cell carcinomas from January 1, 2010, to December 31, 2014. Patients were classified according to the location of their primary malignancy into 1 of the 6 main subsites of the upper aerodigestive tract: oral cavity, oropharynx, nasopharynx, hypopharynx, larynx, and sinonasal tract. Patients were also classified by their HPV status. Data collection for this study took place from January 1, 2010, to December 31, 2014. Data analysis was conducted from August 1, 2017, to September 30, 2017.Main outcomes and measuresThe difference in 5-year overall survival between patients with HPV-positive status and those with HPV-negative status in various head and neck carcinoma subsites; the role of HPV status in an unadjusted Cox multivariate regression model.ResultsOf the 175 223 total number of patients identified (129 634 [74.0%] male; 45 589 [26.0%] female; mean [SD] age, 63.1 [11.9] years), 133 273 (76.1%) were ineligible and 41 950 (23.9%) were included in the sample. This sample included 16 644 patients (39.7%) with HPV-positive tumors and 25 306 (60.3%) with HPV-negative tumors. Patients with an HPV-positive status were more likely to be younger, be white, be male, present with local T category tumors, and have poor differentiation on histologic examination. HPV-positive status was associated with survival at 4 tumor subsites: oral cavity (hazard ratio [HR], 0.76; 95% CI, 0.66-0.87), oropharynx (HR, 0.44; 95% CI, 0.41-0.47), hypopharynx (HR, 0.59; 95% CI, 0.45-0.77), and larynx (HR, 0.71; 95% CI, 0.59-0.85). The HPV status was the greatest factor in survival outcome between the HPV-positive and -negative cohorts at the oropharynx subsite (77.6% vs 50.7%; survival difference, 26.9%; 95% CI, 25.6%-28.2%) and hypopharynx subsites (52.2% vs 28.8%; survival difference, 23.4%; 95% CI, 17.5%-29.3%). For the nasopharynx (HR, 1.03; 95% CI, 0.75-1.42) and sinonasal tract (HR, 0.63; 95% CI, 0.39-1.01) subsites, HPV-positive status was not an independent prognostic factor.Conclusions and relevanceHuman papillomavirus positivity was associated with improved survival in 4 subsites (oropharynx, hypopharynx, oral cavity, and larynx), and the largest survival difference was noted in the oropharynx and hypopharynx subsites. In the nasopharynx and sinonasal tract subsites, HPV positivity had no association with overall survival. Given these results, routine testing for HPV at the oropharynx, hypopharynx, oral cavity, and larynx subsites may be warranted.
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Project description:Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These "causality challenges" hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate "personal mechanism signatures" of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of "Oncogenic FAIME Features of HNSCC" (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p<0.001) is more significant than the gene overlap (genes:4%). These Oncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (n?=?35 and 91, F-accuracy?=?100% and 97%, empirical p<0.001, area under the receiver operating characteristic curves?=?99% and 92%), and stratify recurrence-free survival in patients from two independent studies (p?=?0.0018 and p?=?0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to discrete-class prediction. In contrast, FAIME calculates mechanism profiles for individual patients without requiring group assignment in validation sets. FAIME is more amenable for clinical deployment since it translates the gene-level measurements of each given sample into pathways and molecular function profiles that can be applied to analyze continuous phenotypes in clinical outcome studies (e.g. survival time, tumor volume).
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Project description:The proto-oncogene PTTG and its binding partner PBF have been widely studied in multiple cancer types, particularly thyroid and colorectal, but their combined role in tumourigenesis is uncharacterised. Here, we show for the first time that together PTTG and PBF significantly modulate DNA damage response (DDR) genes, including p53 target genes, required to maintain genomic integrity in thyroid cells. Critically, DDR genes were extensively repressed in primary thyrocytes from a bitransgenic murine model (Bi-Tg) of thyroid-specific PBF and PTTG overexpression. Irradiation exposure to amplify p53 levels further induced significant repression of DDR genes in Bi-Tg thyrocytes (P=2.4 × 10-4) compared with either PBF- (P=1.5 × 10-3) or PTTG-expressing thyrocytes (P=NS). Consistent with this, genetic instability was greatest in Bi-Tg thyrocytes with a mean genetic instability (GI) index of 35.8±2.6%, as well as significant induction of gross chromosomal aberrations in thyroidal TPC-1 cells following overexpression of PBF and PTTG. We extended our findings to human thyroid cancer using TCGA data sets (n=322) and found striking correlations with PBF and PTTG expression in well-characterised DDR gene panel RNA-seq data. In addition, genetic associations and transient transfection identified PBF as a downstream target of the receptor tyrosine kinase-BRAF signalling pathway, emphasising a role for PBF as a novel component in a pathway well described to drive neoplastic growth. We also showed that overall survival (P=1.91 × 10-5) and disease-free survival (P=4.9 × 10-5) was poorer for TCGA patients with elevated tumoural PBF/PTTG expression and mutationally activated BRAF. Together our findings indicate that PBF and PTTG have a critical role in promoting thyroid cancer that is predictive of poorer patient outcome.
| S-EPMC5563453 | biostudies-literature
Project description:Importance:Patients with head and neck cancer receive care at academic comprehensive cancer programs (ACCPs), integrated network cancer programs (INCPs), comprehensive community cancer programs (CCCPs), and community cancer programs (CCPs). The type of treatment facility may be associated with overall survival. Objective:To examine whether type of treatment facility is associated with overall survival after a diagnosis of head and neck cancer. Design, Setting, and Participants:This population-based retrospective cohort study included patients from the National Cancer Database, a prospectively maintained, hospital-based cancer registry of patients treated at more than 1500 US hospitals. Participants were diagnosed with malignant tumors of the head and neck from January 1, 2004, through December 31, 2016. Data were analyzed from May 1 through November 30, 2019. Exposures:Treatment at facilities classified as ACCPs, INCPs, CCCPs, or CCPs. Main Outcomes and Measures:Overall survival after diagnosis and treatment of head and neck cancer was the primary outcome. The secondary outcome was the odds of receiving treatment at ACCPs and INCPs vs CCCPs and CCPs. Multivariable Cox proportional hazards regression and univariable and multivariable logistic regression models were used for analysis. Results:A total of 525?740 patients (368?821 men [70.2%]; mean [SD] age, 63.3 [14.0] years) were diagnosed with malignant tumors of the head and neck during the study period. Among them, 36?595 patients (7.0%) were treated at CCPs; 174?658 (33.2%), at CCCPs; 232?867 (44.3%), at ACCPs; and 57?857 (11.0%), at INCPs. The median survival for patients with aerodigestive cancers was 69.2 (95% CI, 68.6-69.8) months; salivary gland cancers, 107.2 (95% CI, 103.9-110.2) months; and skin cancers, 113.2 (95% CI, 111.4-114.6) months. Improved overall survival was associated with treatment at ACCPs (hazard ratio [HR], 0.89; 95% CI, 0.88-0.91), INCPs (HR, 0.94; 95% CI, 0.92-0.96), and CCCPs (HR, 0.94; 95% CI, 0.92-0.95) compared with CCPs. Compared with patients with private insurance, those with government insurance (odds ratio [OR], 1.35; 95% CI, 1.29-1.41), no insurance (OR, 1.12; 95% CI, 1.09-1.16), or Medicaid (OR, 1.17; 95% CI, 1.14-1.20) were more likely to receive treatment at ACCPs and INCPs, whereas patients with Medicare were less likely to receive treatment at ACCPs and INCPs (OR, 0.95; 95% CI, 0.94-0.97). Compared with white patients, black (OR, 1.55; 95% CI, 1.52-1.59) and Asian (OR, 1.56; 95% CI, 1.49-1.63) patients were more likely to receive care at ACCPs and INCPs. Compared with patients from lower-income areas, patients from high-income areas were more likely to receive treatment at ACCPs and INCPs (OR, 1.25; 95% CI, 1.22-1.28). Conclusions and Relevance:These findings suggest that treatment at ACCPs and INCPs was associated with a better overall survival rate in patients with head and neck cancer. Key social determinants of health such as race/ethnicity, socioeconomic status, and type of insurance were associated with receiving treatment at ACCPs and INCPs.
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Project description:Human papillomavirus (HPV) is associated with the development of head and neck squamous cell carcinomas (HNSC). Cisplatin is used to treat HNSC and induces DNA adducts including interstrand crosslinks (ICLs). Previous reports have shown that HPV positive HNSC patients respond better to cisplatin therapy. Our previous reports highlight that loss of base excision repair (BER) and mismatch repair (MMR) results in cisplatin resistance. Of importance, uracil DNA glycosylase (UNG) is required to initiate the BER response to cisplatin treatment and maintain drug sensitivity. These previous results highlight that specific cytidine deaminases could play an important role in the cisplatin response by activating the BER pathway to mediate drug sensitivity. The APOBEC3 (A3) family of cytidine deaminases are enzymes that restrict HPV as part of the immune defense to viral infection. In this study, the Cancer Genome Atlas (TCGA) HNSC data were used to assess the association between the expression of the seven proteins in the A3 cytidine deaminase family, HPV-status and survival outcomes. Higher A3 G expression in HPV-positive tumors corresponds with better overall survival (OS) (HR 0.33, 95 % CI 0.11-0.93, p = 0.04). FaDu and Scc-25 HNSC cell lines were used to assess alterations in A3, BER and MMR expression in response to cisplatin. We demonstrate that A3, Pol?, and MSH6 knockdown in HNSC cells results in resistance to cisplatin and carboplatin as well as an increase in the rate of ICL removal in FaDu and Scc-25 HNSC cells. Our results suggest that A3s activate BER in HNSC, mediate repair of cisplatin ICLs and thereby, sensitize cells to cisplatin which likely contributes to the improved patient responses observed in HPV infected patients.
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Project description:BackgroundThe purpose of this retrospective analysis was to build and validate nomograms to predict the cancer-specific survival (CSS) and overall survival (OS) of head and neck neuroendocrine carcinoma (HNNEC) patients.MethodsA total of 493 HNNEC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015, and 74 HNNEC patients were collected from the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital (HCH) between 2008 and 2020. Patients from SEER were randomly assigned into training (N=345) and internal validation (N=148) groups, and the independent data group (N=74) from HCH was used for external validation. Independent prognostic factors were collected using an input method in a Cox regression model, and they were then included in nomograms to predict 3-, 5-, and 10-year CSS and OS rates of HNNEC patients. Finally, we evaluated the internal and external validity of the nomograms using the consistency index, while assessing their prediction accuracy using calibration curves. A receiver operating curve (ROC) was also used to measure the performance of the survival models.ResultsThe 3-, 5-, and 10-year nomograms of this analysis demonstrated that M classification had the largest influence on CSS and OS of HNNEC, followed by the AJCC stage, N stage, age at diagnosis, sex/gender, radiation therapy, and marital status. The training validation C-indexes for the CSS and OS models were 0.739 and 0.713, respectively. Those for the internal validation group were 0.726 and 0.703, respectively, and for the external validation group were 0.765 and 0.709, respectively. The area under the ROC curve (AUC) of 3-, 5-, and 10-year CSS and OS models were 0.81, 0.82, 0.82, and 0.78, 0.81, and 0.82, respectively. The C-indexes were all higher than 0.7, indicating the high accuracy ability of our model's survival prediction.ConclusionsIn this study, prognosis nomograms in HNNEC patients were constructed to predict CSS and OS for the first time. Clinicians can identify patients' survival risk better and help patients understand their survival prognosis for the next 3, 5, and 10 years more clearly by using these nomograms.
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