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Somatic copy number alterations associating with alcohol drinking and smoking in head and neck squamous cell carcinoma

ABSTRACT: Background: The most important risk factors for head and neck squamous carcinoma (HNSCC) are tobacco smoking and alcohol consumption, while subgroups are caused by infection with human papillomaviruses (HPV) or Epstein-Barr virus (EBV). Here, we studied alterations of somatic copy-number in whole genome, p16 protein and TP53 mutations by alcohol drinking, smoking and viral infections. Methods: We conducted a prospective cohort study. DNA obtained from tumors and margin samples as well as peripheral blood was assayed by array comparative genomic hybridization using Agilent Whole Human Genome 180K. Mutations of p53 gene by direct sequencing, detection of HPV by polymerase-chain-reaction (PCR), quantification of EBV by reverse transcription-PCR and p16 immunohistochemical (IHC) staining were also performed.

ORGANISM(S): Homo sapiens

PROVIDER: GSE47443 | GEO | 2013/07/01

SECONDARY ACCESSION(S): PRJNA205622

REPOSITORIES: GEO

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Project description:Background: The most important risk factors for head and neck squamous carcinoma (HNSCC) are tobacco smoking and alcohol consumption, while subgroups are caused by infection with human papillomaviruses (HPV) or Epstein-Barr virus (EBV). Here, we studied alterations of somatic copy-number in whole genome, p16 protein and TP53 mutations by alcohol drinking, smoking and viral infections. Methods: We conducted a prospective cohort study. DNA obtained from tumors and margin samples as well as peripheral blood was assayed by array comparative genomic hybridization using Agilent Whole Human Genome 180K. Mutations of p53 gene by direct sequencing, detection of HPV by polymerase-chain-reaction (PCR), quantification of EBV by reverse transcription-PCR and p16 immunohistochemical (IHC) staining were also performed. prospective cohort study: 225 tumor samples were analyzed by Agilent-022060 SurePrint G3 Human CGH miroarray 4x180K. Log2 Ratio (tumor sample DNA/normal DNA) were compared among none alcohol drinkers, moderate alcohol drinkers, heavy alcohol drinkers, none smokers, moderate smokers, heavy smokers and both. Sample characteristics weres scored as following; Human Papilloma Virus Infection (gene detected by PCR in tumor sample): positive=1; negative=0 p16 protein immunohistochemistry: positive=1; negative=0 tumor grade: matured=0; moderate=1; immature=2 Radiotherapy with or without chemotherapy after operation: performed =1; not performed =0 Recurrence/relapse: rec =1; not rec =0 suvival status:death=1; survive=0 smoking status (Pack year of smoking): none smoker=0; pack-year <20 = 1 (moderate smoker); pack-year <=20 = 2 (heavy smoker) alcohol drinking: Alcohol drinkers were divided into non-drinker or less than one drink per day =0: one and more but less than two drinks per day = moderate drinker 1: two and more drinks per day=heavy drinker 2: during the 20 years preceding their treatment for HNSCC. One drink was defined as containing approximately 10g of alcohol, which is considered equal to 30 ml of hard liquor, 100 ml of wine containing 12% alcohol, or 360 ml of beer.

Project description:This is the glycopeptide part of the above project. Purpose: No blood-based biomarkers to detect OPSCC early before symptoms develop or before clinically visible. Diagnosis is solely based on histology of a visible tumour. Most OPSCC patients are diagnosed at an advanced stage, which leads to significant morbidity and poor survival. If high-risk patients were identified with blood-based biomarkers before clear clinical manifestations, tumours could be detected and treated at an earlier stage. Causes of OPSCC include smoking, alcohol misuse, and human papillomavirus (HPV). Tumours are separated according to WHO recommendations into HPV+ OPSCC and HPV- OPSCC using the proxy histological marker p16. We additionally separated our patients into these groups to determine whether the serum glycopeptides would differ between HPV+ and HPV- tumours, as these are distinct clinical entities. Patients and Methods: Pre-treatment sera from 74 patients with OPSCC (including 26 p16- tumours and 48 p16+ tumours) and 12 controls were used, collected between the years 2012 and 2015 at the Department of Otorhinolaryngology – Head and Neck Surgery, Helsinki University Hospital, Helsinki, Finland. Samples were grouped as follows: early stage p16+ OPSCC (stage I only), early stage p16- OPSCC (stage I-II), p16+ (any stage), p16- (any stage), controls. In-parallel quantitative bulk serum proteomics and serum glycopeptidomics were performed. Results: We identified 78 bulk proteins in the serum, of which 33 significantly differed between early-stage p16- OPSCC and controls, 22 between early-stage p16+ OPSCC and controls, 1 between early-stage p16+ and early-stage p16- OPSCCs, and 30 between all p16+ and p16- OPSCCs. We identified glycopeptides from proteins including but not limited to alpha-1-antitrypsin, haptoglobin, and Immunoglobulin heavy constant alpha 1, and compared these with the protein expression levels in each comparison. Conclusions: We have identified novel serum glycopeptide biomarkers detect early-stage OPSCCs, to be evaluated further as a diagnostic panel to detect preclinical OPSCC in at-risk patients.

Project description:This is the proteomics part of the above project. Purpose: No blood-based biomarkers to detect OPSCC early before symptoms develop or before clinically visible. Diagnosis is solely based on histology of a visible tumour. Most OPSCC patients are diagnosed at an advanced stage, which leads to significant morbidity and poor survival. If high-risk patients were identified with blood-based biomarkers before clear clinical manifestations, tumours could be detected and treated at an earlier stage. Causes of OPSCC include smoking, alcohol misuse, and human papillomavirus (HPV). Tumours are separated according to WHO recommendations into HPV+ OPSCC and HPV- OPSCC using the proxy histological marker p16. We additionally separated our patients into these groups to determine whether the serum glycopeptides would differ between HPV+ and HPV- tumours, as these are distinct clinical entities. Patients and Methods: Pre-treatment sera from 74 patients with OPSCC (including 26 p16- tumours and 48 p16+ tumours) and 12 controls were used, collected between the years 2012 and 2015 at the Department of Otorhinolaryngology – Head and Neck Surgery, Helsinki University Hospital, Helsinki, Finland. Samples were grouped as follows: early stage p16+ OPSCC (stage I only), early stage p16- OPSCC (stage I-II), p16+ (any stage), p16- (any stage), controls. In-parallel quantitative bulk serum proteomics and serum glycopeptidomics were performed. Results: We identified 78 bulk proteins in the serum, of which 33 significantly differed between early-stage p16- OPSCC and controls, 22 between early-stage p16+ OPSCC and controls, 1 between early-stage p16+ and early-stage p16- OPSCCs, and 30 between all p16+ and p16- OPSCCs. We identified glycopeptides from proteins including but not limited to alpha-1-antitrypsin, haptoglobin, and Immunoglobulin heavy constant alpha 1, and compared these with the protein expression levels in each comparison. Conclusions: We have identified novel serum glycopeptide biomarkers detect early-stage OPSCCs, to be evaluated further as a diagnostic panel to detect preclinical OPSCC in at-risk patients.

Project description:The global rise of HPV(+) oropharyngeal squamous cell carcinoma (OPSCC) has generated considerable interest underlying its etiology and management. Despite an overall decline in head and neck malignancies, the incidence in OPSCC has by contrast sharply risen, with HPV(+) subtypes now comprising 80% of all OPSCC.1,2 Relative to HPV(-) OPSCC, HPV(+) patients are more responsive to chemoradiation and harbor a 52% risk-of-death reduction.3 Despite this distinct outcome, treatment regimens remain the same for all OPSCC subtypes (smoking-driven and virus-driven), rather than an adaptive approach to what most consider distinct diseases. The short-term effects (e.g., mucositis, odynophagia) and long-term toxicities (e.g., xerostomia, dysphagia, ototoxicity) from treatment substantially affect quality of life, and rival the impact of the cancer itself. Recently published as well as ongoing trials are actively examining deintensification approaches2,4-9, with the goal of diminishing treatment sequelae for HPV(+) subtypes. While deintensification may decrease chemoradiation-related toxicities, it nonetheless may also undertreat a meaningful percentage of HPV(+) patients who may then recur. In examining national trials, 19% of HPV(+) patients had disease progression after therapy, with a two-year survival rate of 60%.10 Current methods to ascertain HPV status involve p16 staining. However, on comparison with gold standard E6/E7 expression by qPCR, p16 harbored a 15% false positivity rate11, suggesting limited utility as a sole biomarker for deintensification. Improved molecular stratification would greatly enhance the clinician’s ability to precisely tailor treatment while minimizing the risk of jeopardizing outcomes. One approach encompasses in-depth proteomic profiling of HPV(+) OPSCC to reveal distinct protein expression profiles and delineate clinically relevant upstream pathways. In turn, these proteomic differences may distinguish higher-risk disease (cases predisposed to recurrence that may benefit from treatment intensification) from lower-risk phenotypes (cases whose treatment response is sufficiently robust to warrant deintensification). Here, two HPV(+) OPSCC cohorts stratified by treatment response are compared via a hybrid data dependent acquisition/data independent acquisition (DDA/DIA) approach via mass spectrometry. We focused on detection of low-abundance proteins to highlight proteomic signatures that can be potentially exploited for treatment stratification.

Project description:INTRODUCTION: CDKN2A (p16) inactivation is common in lung cancer and occurs via homozygous deletions, methylation of promoter region, or point mutations. Although p16 promoter methylation has been linked to KRAS mutation and smoking, the associations between p16 inactivation mechanisms and other common genetic mutations and smoking status are still controversial or unknown. METHODS: We determined all three p16 inactivation mechanisms with the use of multiple methodologies for genomic status, methylation, RNA, and protein expression, and correlated them with EGFR, KRAS, STK11 mutations and smoking status in 40 cell lines and 45 tumor samples of primary non-small-cell lung carcinoma. We also performed meta-analyses to investigate the impact of smoke exposure on p16 inactivation. RESULTS: p16 inactivation was the major mechanism of RB pathway perturbation in non-small-cell lung carcinoma, with homozygous deletion being the most frequent method, followed by methylation and the rarer point mutations. Inactivating mechanisms were tightly correlated with loss of mRNA and protein expression. p16 inactivation occurred at comparable frequencies regardless of mutational status of EGFR, KRAS, and STK11, however, the major inactivation mechanism of p16 varied. p16 methylation was linked to KRAS mutation but was mutually exclusive with EGFR mutation. Cell lines and tumor samples demonstrated similar results. Our meta-analyses confirmed a modest positive association between p16 promoter methylation and smoking. CONCLUSION: Our results confirm that all the inactivation mechanisms are truly associated with loss of gene product and identify specific associations between p16 inactivation mechanisms and other genetic changes and smoking status. 40 NSCLC cell lines were profiled on Illumina WG6-V3 expression arrays. They consist of 4 groups of 10 cell lines each: non-smokers with EGFR mutation, non-smokers with EGFR wild-type, smokers with KRAS mutation, smokers with KRAS wild-type. Note that smoking status is not always clear.