Abstract
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer type globally and contributes significantly to burden of disease in South Asia. In Pakistan, HNSCC is among the most commonly diagnosed cancer in males and females. The increasing regional burden of HNSCC along with a unique set of risk factors merited a deeper investigation of the disease at the genomic level. Whole exome sequencing of HNSCC samples and matched normal genomic DNA analysis (n=7) was performed. Significant somatic single nucleotide variants (SNVs) were identified and pathway analysis performed to determine frequently affected signaling pathways. We identified significant, novel recurrent mutations in ASNS (asparagine synthetase) that may affect substrate binding, and variants in driver genes including TP53, PIK3CA, FGFR2, ARID2, MLL3, MYC and ALK. Using the IntOGen platform, we identified MAP kinase, cell cycle, actin cytoskeleton regulation, PI3K-Akt signaling and other pathways in cancer as affected in the samples. This data is the first of its kind from the Pakistani population. The results of this study can guide a better mechanistic understanding of HNSCC in the population, ultimately contributing new, rational therapeutic targets for the treatment of the disease.
Keywords:
Head and neck squamous cell carcinoma (HNSCC); whole exome sequencing; driver mutation; novel mutation; Pakistani population
Introduction
Head and neck squamous cell carcinomas (HNSCC), which include tumours of the oral cavity, oropharynx, hypopharynx and larynx, are the sixth most common cancer worldwide with a global incidence of ~600,000 cases (Jemal et al., 2005Jemal A, Murray T, Ward E, Samuels A, Tiwari RC, Ghafoor A, Feuer EJ and Thun MJ (2005) Cancer statistics, 2005. CA Cancer J Clin 55:10-30., 2011Jemal A, Bray F, Center MM, Ferlay J, Ward E and Forman D (2011) Global cancer statistics. CA Cancer J Clin 61:69-90.; Hayat et al., 2007Hayat MJ, Howlader N, Reichman ME and Edwards BK (2007) Cancer statistics, trends, and multiple primary cancer analyses from the Surveillance, Epidemiology, and End Results (SEER) Program. Oncologist 12:20-37.; Murar and Forastiere, 2008Murar S and Forastiere A (2008) Head and neck cancer: Changing epidemiology, diagnosis and treatment. Mayo Clinic Proc 83:489-501.; Ferlay et al., 2011Ferlay J, Shin HR, Bray F, Forman D, Mathers C and Parkin DM (2011) Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 127:2893-2917.). In Pakistan, a developing country in South Asia, HNSCC is among the most commonly diagnosed cancers in both males and females (Bhurgri et al., 2006Bhurgri Y, Bhurgri A, Usman A, Pervez S, Kayani N, Bashir I, Ahmed R and Hasan SH (2006) Epidemiological review of head and neck cancers in Karachi. Asian Pac J Cancer Prev 7:195-200.; Masood et al., 2015Masood K, Masood A, Zafar J, Shahid A, Kamran M, Murad S, Masood M, Alluddin Z, Riaz M, Akhter N et al. (2015) Trends and analysis of cancer incidence for common male and female cancers in the population of Punjab province of Pakistan during 1984 to 2014. Asian Pac J Cancer Prev 16:5297-5304.). The major risk factors for HNSCC include tobacco use, alcohol consumption, and human papilloma virus (HPV) infection (Leemans et al., 2018Leemans CR, Snijders PJF and Brakenhoff RH (2018) The molecular landscape of head and neck cancer. Nat Rev Cancer 18:269-282.).
HPV-negative disease accounts for ~80% of the HNSCC cases (Leemans et al., 2011Leemans CR, Braakhuis BJ and Brakenhoff RH (2011) The molecular biology of head and neck cancer. Nat Rev Cancer 11:9-22.). Unlike developed countries, the incidence of HPV-negative disease has steadily increased in developing countries (Leemans et al., 2011Leemans CR, Braakhuis BJ and Brakenhoff RH (2011) The molecular biology of head and neck cancer. Nat Rev Cancer 11:9-22.). The increased incidence in both males and females in Pakistan can be attributed to the prevalence of traditional risk factor such as smoking. The use of smokeless tobacco, betel nut, gutka (a preparation of crushed areca nut, tobacco, slaked lime and other flavorings) and betel quid or paan (a preparation of betel leaf, areca nut and occasionally tobacco) along with its related products are additional risk factors in this part of the world (Gupta and Johnson, 2014Gupta B and Johnson NW (2014) Systematic review and meta-analysis of association of smokeless tobacco and of betel quid without tobacco with incidence of oral cancer in South Asia and the Pacific. PLoS One 9:e113385.; Khan et al., 2014Khan Z, Tonnies J and Muller S (2014) Smokeless tobacco and oral cancer in South Asia: A systematic review with meta-analysis. J Cancer Epidemiol 2014:394696.; Li et al., 2014Li WC, Lee PL, Chou IC, Chang WJ, Lin SC and Chang KW (2014) Molecular and cellular cues of diet-associated oral carcinogenesis - with an emphasis on areca-nut-induced oral cancer development. J Oral Pathol Med 44:167-177.).
HNSCC is associated with considerable disease-related mortality and treatment-related morbidity (Forastiere et al., 2001Forastiere A, Koch W, Trotti A and Sidransky D (2001) Head and neck cancer. N Engl J Med 345:1890-1900.) and is a major public health concern for Pakistan (Bhurgri et al., 2002Bhurgri Y, Bhurgri A, Hasan SH, Usman A, Faridi N, Malik J, Khurshid M, Zaidi SM, Pervez S, Kayani N, et al. (2002) Cancer patterns in Karachi division (1998-1999). J Pak Med Assoc 52:244-246.; Bhurgri 2004Bhurgri Y (2004) Karachi Cancer Registry Data - implications for the National Cancer Control Program of Pakistan. Asian Pac J Cancer Prev 5:77-82., 2005Bhurgri Y (2005) Cancer of the oral cavity - trends in Karachi South (1995-2002). Asian Pac J Cancer Prev 6:22-26.; Warnakulasuriya 2009Warnakulasuriya S (2009) Global epidemiology of oral and oropharyngeal cancer. Oral Oncol 45:309-316.; Bray et al., 2012Bray F, Ren JS, Masuyer E and Ferlay J (2012) Global estimates of cancer prevalence for 27 sites in the adult population in 2008. Int J Cancer 132:1133-1145.) and worldwide. Despite the advances in all the major treatments for HNSCC including surgery, radiotherapy and chemotherapy, the mortality rate is ~50% (Laramore et al., 1992Laramore GE, Scott CB, al-Sarraf M, Haselow RE, Ervin TJ, Wheeler R, Jacobs JR, Schuller DE, Gahbauer RA, Schwade JG et al. (1992) Adjuvant chemotherapy for resectable squamous cell carcinomas of the head and neck: report on Intergroup Study 0034. Int J Radiat Oncol Biol Phys 23:705-713.; Leemans et al., 2018Leemans CR, Snijders PJF and Brakenhoff RH (2018) The molecular landscape of head and neck cancer. Nat Rev Cancer 18:269-282.). The existing literature focuses primarily on HNSCC in North American and European populations. There is a dearth of information specific for the South Asian population. The unique set of population-specific risk factors, germline variability and molecular heterogeneity of HNSCC demands a thorough molecular profiling of these tumours in this population in order to understand tumour progression, and identify actionable targets for therapy, leading to improved patient care. The aim of the study described here was to identify the global genetic aberrations underlying HPV-negative HNSCC in the South Asian (Pakistani) population.
Materials and Methods
Ethics approval and consent to participate
The Aga Khan University Ethics Review Committee approved the procedures used in collecting and processing of participant material and information (reference #: 1003-Sur/ERC-08). Written informed consent to participate was obtained from all subjects.
Sample collection
Fresh tumour tissue and matched blood were obtained from treatment-naïve patients undergoing surgical resection of HNSCC primary tumour at the Aga Khan University Hospital in Karachi, Pakistan. Patients with confirmed histological diagnosis of HNSCC were included in this study. At the time of resection, fresh tumour tissue away from the necrotic core measuring at least 0.5 cm2 was collected and stored in RNAlater® solution (Thermo Fisher Scientific) at -80 °C till further processing. Formalin-fixed tumour tissue samples were assessed by a histopathologist for tumour content and cellularity based on hematoxylin and eosin (H&E) staining. Seven tumour samples negative for HPV with at least 70% cancer cells and 1 μg (50 ng/μl) of extracted DNA (both tumour as well as genomic DNA) were utilized for whole exome sequencing.
DNA extraction
Genomic and tumour DNA was extracted in-house using TRIzol® Reagent (Invitrogen, USA) according to manufacturer’s instructions. Tumour DNA was extracted from at least 50 mg of tissue and genomic DNA was extracted from 3-5 mL of peripheral blood samples obtained before patients underwent surgical procedure. DNA yield and quality was assessed both in-house using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA) and by Macrogen Inc. (Seoul, South Korea) using PicoGreen® Assay (Invitrogen, USA).
Tumour HPV status
Formalin-fixed paraffin embedded (FFPE) tumour blocks were retrieved and DNA was extracted for assessing HPV status. PCR detection was performed using two sets of general HPV primers (GP5/GP6) (Baay et al., 1996Baay MF, Quint WG, Koudstaal J, Hollema H, Duk JM, Burger MP, Stolz E and Herbrink P (1996) Comprehensive study of several general and type-specific primer pairs for detection of human papillomavirus DNA by PCR in paraffin-embedded cervical carcinomas. J Clin Microbiol 34:745-747.; Khan et al., 2007Khan S, Jaffer NN, Khan MN, Rai MA, Shafiq M, Ali A, Pervez S, Khan N, Aziz A and Ali SH (2007) Human papillomavirus subtype 16 is common in Pakistani women with cervical carcinoma. Int J Infect Dis 11:313-317.). Additionally, HPV in situ hybridization (ISH) was performed on FFPE blocks using GenPoint assay according to the manufacturer’s instructions (Dako, Denmark). Dako assay can detect HPV-DNA from 13 high-risk genotypes.
Whole Exome Sequencing (WES)
WES was performed by Macrogen Inc. (Seoul, South Korea). 1-2 μg of tumour and genomic DNA was fragmented by nebulization. DNA libraries were prepared from each sample using TruSeq DNA Sample Prep Kit using the manufacturer’s protocol (Illumina, USA). Unique molecular indices were used for each sample. Exome enrichment was performed using the TruSeq Exome Enrichment kit (Illumina, USA). Paired-end sequencing was performed on Illumina HiSeq 2000 instrument. Each read was of 100 bp size.
Availability of data and materials
The data sets supporting the results of this article are included within the article and its supplementary files. The raw sequencing data of those patients that consented to deposition of data in a public database (4 out of 7 total) have been deposited in NCBI’s Sequence Read Archive and are accessible through accession number SRP083063.
Data analysis
Paired-end sequence reads from Illumina were mapped against UCSC Human Genome (hg) 19 using BWA (Li and Durbin 2009Li H and Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754-1760.). Local realignment was performed using Genome Analysis Tool Kit (GATK) to improve mapping quality (McKenna et al., 2010McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M et al. (2010) The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297-1303.). Single nucleotide variants (SNVs) were identified in both somatic and germline DNA using MuTect (high-confidence mode) with default settings. Somatic variants were defined as those SNVs which were only identified in the somatic DNA and not seen in germline DNA. Variants marked REJECT were excluded from downstream analysis. Tumour mutational burden was calculated as previously described by others (Chalmers et al., 2017Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, Schrock A, Campbell B, Shlien A, Chmielecki J et al. (2017) Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 9:34.). All mutations were annotated and prioritized using Variant Effect Predictor (VEP) and ANNOVAR. Further characterization of SNVs into missense, nonsense, frameshift, stop loss and stop gain variants was done using wANNOVAR, SNPEFF, SIFT and Polyphen. All somatic missense mutations were analysed for their likely tumourigenic impact based on CHASM (Cancer-specific High-throughput Annotation of Somatic Mutations) (Carter et al., 2009Carter H, Chen S, Isik L, Tyekucheva S, Velculescu VE, Kinzler KW, Vogelstein B and Karchin R (2009) Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations. Cancer Res 69:6660-6667.; Wong et al., 2011Wong WC, Kim D, Carter H, Diekhans M, Ryan MC and Karchin R (2011) CHASM and SNVBox: Toolkit for detecting biologically important single nucleotide mutations in cancer. Bioinformatics 27:2147-2148.) and the IntOGen-mutations platform (Gonzalez-Perez et al., 2013Gonzalez-Perez A, Perez-Llamas C, Deu-Pons J, Tamborero D, Schroeder MP, Jene-Sanz A, Santos A and Lopez-Bigas N (2013) IntOGen-mutations identifies cancer drivers across tumor types. Nat Methods 10:1081-1082.). A cut-off score threshold of ≤ 0.2 for FDR with a p-value of ≤ 0.05 was applied. The annotation ranked the SNVs for somatic driver mutations for specific cancer tissue types, predicted protein functional impact, allele frequencies from the 1000 Genomes Project and ESP6500 populations, and previous cancer association of the gene harbouring the variants. CHASM training set is composed of a positive class of driver mutations from the COSMIC database and VEST training set comprising a positive class of disease mutations from the Human Gene Mutation Database 66 and a negative class of variants detected in the ESP6500 population and 1000 Genomes Project cohort with an allele frequency of >1%. SNPeff (Cingolani et al., 2012Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, Land SJ, Lu X and Ruden DM (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6:80-92.) and CHASM were used to identify stop-gain, start-loss and splice site variants in nonsynonymous coding region. Those SNVs identified by both tools were selected as significant. Mutations in non-coding regions were annotated using CADD and a cut-off threshold score of ≥15 with p<10–5 applied to predict benign and deleterious variants (Kircher et al., 2014Kircher M, Witten DM, Jain P, O’Roak BJ, Cooper GM and Shendure J (2014) A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet 46:310-315.). Pathway analysis was carried out using the IntOGen-Mutations platform (Gonzalez-Perez et al., 2013Gonzalez-Perez A, Perez-Llamas C, Deu-Pons J, Tamborero D, Schroeder MP, Jene-Sanz A, Santos A and Lopez-Bigas N (2013) IntOGen-mutations identifies cancer drivers across tumor types. Nat Methods 10:1081-1082.) and significantly (p≤0.05) affected pathways in the cohort and genes within identified.
ASNS protein modeling
The homology model of human asparagine synthetase was constructed using crystal structural coordinates of the enzyme from Escherichia coli (PDB id 1CT9). The Modeller program (Fiser and Sali, 2003Fiser A and Sali A (2003) Modeller: Generation and refinement of homology-based protein structure models. Methods Enzymol 374:461-491.) was used to build the asparagine synthetase model.
Results
Clinical characteristics and HPV-status of HNSCC patients
Primary tumour samples from 7 treatment-naïve HNSCC patients (Figure S1), along with their matched genomic DNA, were used for this study. The detailed demographics and clinical characteristics of these patients are provided in Table 1. The samples were taken from five male and two female patients, who had an average age at diagnosis of 54 years (SD = 13.24). Two patients reported a family history of cancer; one patient had a personal history of smoking (110 pack years), two of oral tobacco use, one of alcohol and oral tobacco use, and four reported use of betel nut/quid. All samples were negative for human papilloma virus (Figure 1).
Clinical characteristics of HNSCC patients. Data that is unavailable is indicated with a dash (-).
Human papilloma virus (HPV) detection. PCR (left) for HPV detection using GP5/GP6 primers (expected product ~150bp). HPV in situ hybridization (right) using GenPoint in a representative HPV-negative HNSCC sample at a magnification of 40 x 10X; inset at magnification of 4 x 10X shows control HPV-positive nuclei stained brown.
Summary of exome capture and sequencing results
Paired-end whole exome sequencing (WES) of all seven HNSCC samples and matched genomic DNA was performed on Illumina HiSeq 2000 platform. Each read was of 100 bp size. Additional details of the sequencing, including coverage and depth, are summarized in Table S1. Whole exome sequencing revealed a total of 3,959 single nucleotide variants across all 7 HNSCC samples, of which 2,547 are novel (Figure 2; Table 2, left panel). Nonsynonymous mutation rates ranged from 2.11 to 5.02 mutations per megabase (mean = 3.07) (Table 2, right panel). Several mutations recurred in more than one sample in both coding (Figure 3; Table 3) and non-coding regions (Table S2). Nonsense and splice site variants were also identified in all samples (Table S3).
Mutational landscape of HNSCC tumours. Left panel: Number of mutations (known and novel) in HNSCC patients Middle panel: significant somatic nucleotide variants (synonymous, nonsynonymous missense) Right panel: Rate of synonymous, nonsynonymous and other (3’ UTR, 3’ flank, 5’ UTR, 5’ flank, intron, splice site) mutations expressed in mutations per megabase of covered target sequence.
Somatic coding single nucleotide variants (SNV) found in ≥ 2 HNSCC patients and dbSNP database. The variant allele frequency (VAF) on the x-axis indicates the proportion of reads with the variant allele within individual samples.
Somatic coding single nucleotide variants (SNVs) found in ≥2 HNSCC patients. NS: nonsynonymous; S: synonymous. The variant allele frequency (VAF) indicates the proportion of reads with the variant allele within individual samples.
Mutational landscape in HNSCC patients
On average, 227 coding mutations were identified per tumour, 39% of which are synonymous. The majority of the mutations identified were nonsynonymous missense mutations and mutations in the 3’ UTR region (Table 2). Filtering for driver and other significant variants using CHASM revealed alterations in genes that have been implicated in HNSCC or other cancers (Figure 2, middle panel; Table 4). Driver missense mutations in FGFR2 (Fibroblast Growth Factor Receptor 2), SETBP1 (SET Binding Protein 1), PIK3CA (Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha), IGF2BP3 (Insulin Like Growth Factor 2 MRNA Binding Protein 3), TP53 (Tumour Protein P53), PTPN11 (Protein Tyrosine Phosphatase, Non-Receptor Type 11) and NF2 (Neurofibromin 2) were identified. Significant missense mutations were also identified in ASNS (Asparagine Synthetase (Glutamine-Hydrolyzing)) in four of the seven samples. Other genes that exhibited recurrent mutations included the CLMN (Calmin) gene (5/7), CHEK2 (Checkpoint Kinase 2) (3/7), and DRD5 (Dopamine Receptor D5) and PAK2 (P21 (RAC1) Activated Kinase 2) (2/7) (Table 3). These recurrent mutation sites have not been reported as hotspots in previous HNSCC sequencing studies.
Somatic single nucleotide variants (SNVs) in HNSCC patients in coding regions. NS MS: nonsynonymous missense; S: synonymous. Driver missense variants are in bold text and synonymous variants in possible driver genes are marked with an asterisk (*).The variant allele frequency (VAF) indicates the proportion of reads with the variant allele within individual samples. The minor allele frequency (MAF) signifies prevalence of the known variants in the global population as per the ExAc dataset.
Synonymous variants in previously identified driver genes ARID2 (AT-Rich Interaction Domain 2), ALK (Anaplastic Lymphoma Receptor Tyrosine Kinase), MLL3 [Myeloid/Lymphoid Or Mixed-Lineage Leukemia 3, also known as KMT2C (Lysine Methyltransferase 2C)] and MYC (V-Myc Avian Myelocytomatosis Viral Oncogene Homolog), were also identified (Figure 2, middle panel; Table 4). The ASNS gene was found to have a synonymous mutation in three samples, and recurrent synonymous mutations were also observed in CHEK2 and DRD5 genes (Table 3). Splice site variants in FCGR2A (Fc Fragment of IgG, Low Affinity IIa, Receptor (CD32)) and two genes involved in eukaryotic translation initiation [EIF4B (Eukaryotic Translation Initiation Factor 4B) and EIF4A3 (Eukaryotic Translation Initiation Factor 4A3)] were seen in two of the seven samples (Table S3). Significant non-coding mutations were filtered using CADD (Table S4). In the 3’UTR region, mutations in IGF1R (Insulin Like Growth Factor 1 Receptor) and ERBB4 (Erb-B2 Receptor Tyrosine Kinase 4) were identified as significant. Another eukaryotic translation initiation factor, EIF2B4 (Eukaryotic Translation Initiation Factor 2B Subunit Delta), exhibited significant splice site variance. IntOGen pathway analysis revealed that the MAP kinase pathway was the most significantly affected pathway in all samples tested. In addition, cell cycle, actin cytoskeleton regulation, PI3K-Akt signaling and other pathways in cancer were among those significantly enriched for exomic alterations in all samples (Table 5). Genes with driver mutations implicated in multiple pathways included FGFR2, PIK3CA, and TP53. Significant mutations in the pathway genes were all deleterious with respect to protein function as predicted by SIFT and PolyPhen.
Significantly involved pathways (p ≤ 0.05) identified by IntOGen-Mutations platform. Driver mutations in each pathway are in bold text and marked with an asterisk (*).
Asparagine synthetase protein modeling
The ASNS gene codes for asparagine synthetase, which catalyzes the formation of asparagine from glutamine, aspartate and ATP. Protein modeling of the effect of the three novel, recurrent mutations in ASNS identified in this cohort revealed that the mutated amino acids (p.A13T, p.A25V and p.M22T) are located in the vicinity (within 10 Å distance) of the glutamine binding pocket (Figure 4).
Homology model of the N-terminal domain of human asparagine synthetase (ASNS) complexed with glutamine (Gln). Amino acid changes due to nonsynonymous mutations in ASNS are indicated.
Discussion
This is the first study reported in the literature to describe the mutational landscape of Pakistani HNSCC patients. We performed exome sequencing of a small set of HPV-negative HNSCC patients from Pakistan. We identified a total of ~4000 somatic variants (novel and known). Previous studies have reported greater number of mutations in HPV-negative as compared to HPV-positive HNSCC tumours (Riaz et al., 2014Riaz N, Morris LG, Lee W and Chan TA (2014) Unraveling the molecular genetics of head and neck cancer through genome-wide approaches. Genes Dis 1:75-86.; Beck and Golemis, 2016Beck TN and Golemis EA (2016) Genomic insights into head and neck cancer. Cancers Head Neck 1:1.). As a comparison, Stransky et al. (2011)Stransky N, Egloff AM, Tward AD, Kostic AD, Cibulskis K, Sivachenko A, Kryukov GV, Lawrence MS, Sougnez C, McKenna A et al. (2011) The mutational landscape of head and neck squamous cell carcinoma. Science 333:1157-1160. on average found 130 coding mutations per tumour (25% synonymous), while in the current cohort an average of 227 coding mutations per tumour (39% synonymous) were identified.
Several variants were found in more than one sample and in genes that have been previously identified to play a role in HNSCC carcinogenesis. Next generation sequencing studies in other populations have identified mutations in the tumour suppressor gene TP53, which is associated with smoking-related disease, and the oncogene PIK3CA, at a mutation rate of 40-60% and 6-8%, respectively (Agrawal et al., 2011Agrawal N, Frederick MJ, Pickering CR, Bettegowda C, Chang K, Li RJ, Fakhry C, Xie TX, Zhang J, Wang J et al. (2011) Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1. Science 333:1154-1157.; Stransky et al., 2011Stransky N, Egloff AM, Tward AD, Kostic AD, Cibulskis K, Sivachenko A, Kryukov GV, Lawrence MS, Sougnez C, McKenna A et al. (2011) The mutational landscape of head and neck squamous cell carcinoma. Science 333:1157-1160.; Loyo et al., 2013Loyo M, Li RJ, Bettegowda C, Pickering CR, Frederick MJ, Myers JN and Agrawal N (2013) Lessons learned from next-generation sequencing in head and neck cancer. Head Neck 35:454-463.). The TCGA study, with the largest cohort to date, reported a TP53 mutation rate of 72% and PIK3CA mutation rate of 18-21% (TCGA 2015The Cancer Genome Atlas Network (2015) Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517:576–582.). Mutations in TP53 gene were detected in two of the seven cases in the current study, and in PIK3CA in one patient. In a comparative genomic analysis of HPV-positive and HPV-negative tumours, the former showed mutations in FGFR2 and MLL3, among others. The mutational spectrum in HPV-negative tumours closely resembled lung and esophageal squamous cell carcinomas, with mutations identified in genes including TP53, MLL2/3, NOTCH1, PIK3CA and DDR2 (Seiwert et al., 2015Seiwert TY, Zuo Z, Keck MK, Khattri A, Pedamallu CS, Stricker T, Brown C, Pugh TJ, Stojanov P, Cho J et al. (2015) Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas. Clin Cancer Res 21:632-641.). The HPV-negative cohort in the current study exhibited a nonsense variant (p.Y223X) in DDR2 in a single sample. A different nonsense mutation (p.R709X) and missense mutations (p.I474M; p.I724M) have been previously identified exclusively in HNSCC recurrences (Hedberg et al., 2015Hedberg ML, Goh G, Chiosea SI, Bauman JE, Freilino ML, Zeng Y, Wang L, Diergaarde BB, Gooding WE, Lui VW et al. (2015) Genetic landscape of metastatic and recurrent head and neck squamous cell carcinoma. J Clin Invest 126:169-180.). DDR2 and FGFR2, which was identified as having a potential missense driver mutation in one sample in the current study, are both genes that code for receptor tyrosine kinases and are potentially targetable for therapeutics. In addition, an SNV was identified in MLL3 in a sample that also exhibited an SNV in the driver gene MYC. MLL genes encode histone lysine methyltransferases that are involved in chromatin remodeling. Recurrent mutations in MLL genes have been identified in several other cancers, including lung squamous cell carcinoma, and been associated with poor clinical outcomes (Morin et al., 2011Morin RD, Mendez-Lago M, Mungall AJ, Goya R, Mungall KL, Corbett RD, Johnson NA, Severson TM, Chiu R, Field M et al. (2011) Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma. Nature 476:298-303.; Grasso et al., 2012Grasso CS, Wu YM, Robinson DR, Cao X, Dhanasekaran SM, Khan AP, Quist MJ, Jing X, Lonigro RJ, Brenner JC et al. (2012) The mutational landscape of lethal castration-resistant prostate cancer. Nature 487:239-243.; Jones et al., 2012Jones DT, Jager N, Kool M, Zichner T, Hutter B, Sultan M, Cho YJ, Pugh TJ, Hovestadt V, Stutz AM et al. (2012) Dissecting the genomic complexity underlying medulloblastoma. Nature 488:100-105.; Kim et al., 2014Kim Y, Hammerman PS, Kim J, Yoon JA, Lee Y, Sun JM, Wilkerson MD, Pedamallu CS, Cibulskis K, Yoo YK et al. (2014) Integrative and comparative genomic analysis of lung squamous cell carcinomas in East Asian patients. J Clin Oncol 32:121-128.; Seiwert et al., 2015Seiwert TY, Zuo Z, Keck MK, Khattri A, Pedamallu CS, Stricker T, Brown C, Pugh TJ, Stojanov P, Cho J et al. (2015) Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas. Clin Cancer Res 21:632-641.). The oncogene MYC is most often altered in HPV-negative HNSCC tumours (TCGA 2015The Cancer Genome Atlas Network (2015) Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517:576–582.).
Additionally, we discovered recurrent significant missense mutations in ASNS (asparagine synthetase) gene in 4 out of 7 samples. These SNVs in ASNS have not previously been reported in the literature as significant in HNSCC pathogenesis. The ASNS gene codes for a ubiquitously expressed, ATP-dependent enzyme that converts aspartate and glutamine to asparagine and glutamate (Balasubramanian et al., 2013Balasubramanian MN, Butterworth EA and Kilberg MS (2013) Asparagine synthetase: regulation by cell stress and involvement in tumor biology. Am J Physiol Endocrinol Metab 304:E789-799.). The protein folds into two distinct domains, where the N-terminal domain contains two layers of antiparallel beta-sheets. The active site responsible for the binding and hydrolysis of glutamine is situated between these layers and important, evolutionarily conserved side chains involved in glutamine binding within the substrate binding pocket include Arg 49, Asn 74, Glu 76, and Asp 98 (Van Heeke and Schuster, 1989Van Heeke G and Schuster SM (1989) The N-terminal cysteine of human asparagine synthetase is essential for glutamine-dependent activity. J Biol Chem 264:19475-19477.). While the amino acids mutated as a result of the novel and recurrent mutations in ASNS identified in this cohort are not part of the glutamine binding pocket, protein modeling revealed their proximity to the region. Therefore, these mutations may affect glutamine binding during catalysis. Elevated levels of ASNS play a role in drug resistance in acute lymphoblastic leukemias and have been implicated in solid tumour adaptation to nutrient deprivation and hypoxia (Balasubramanian et al., 2013Balasubramanian MN, Butterworth EA and Kilberg MS (2013) Asparagine synthetase: regulation by cell stress and involvement in tumor biology. Am J Physiol Endocrinol Metab 304:E789-799.). ASNS expression has also been shown to be an independent factor affecting survival in hepatocellular carcinoma and low ASNS levels are correlated with poorer surgical outcomes (Zhang et al., 2013Zhang B, Dong LW, Tan YX, Zhang J, Pan YF, Yang C, Li MH, Ding ZW, Liu LJ, Jiang TY et al. (2013) Asparagine synthetase is an independent predictor of surgical survival and a potential therapeutic target in hepatocellular carcinoma. Br J Cancer 109:14-23.). In HNSCC, deregulation of miR-183-5p and its target gene ASNS has been documented in a radiochemotherapy cell culture model of primary HNSCC cells and is a potential prognostic marker for radiochemotherapy outcome (Summerer et al., 2015Summerer I, Hess J, Pitea A, Unger K, Hieber L, Selmansberger M, Lauber K and Zitzelsberger H (2015) Integrative analysis of the microRNA-mRNA response to radiochemotherapy in primary head and neck squamous cell carcinoma cells. BMC Genomics 16:654.). Two recent reports have further elucidated the role of ASNS in carcinogenesis. One showed that ASNS expression in primary tumours is correlated with metastatic relapse and bioavailability of asparagine regulates metastatic potential and progression in breast cancer cells, potentially by affecting the epithelial-to-mesenchymal transition (Knott et al., 2018Knott SRV, Wagenblast E, Khan S, Kim SY, Soto M, Wagner M, Turgeon MO, Fish L, Erard N, Gable AL et al. (2018) Asparagine bioavailability governs metastasis in a model of breast cancer. Nature 554:378.). ASNS was also identified as a key target of the KRAS-ATF4 axis in non-small-cell lung cancer. Oncogenic KRAS regulates amino acid homeostasis and cellular response to nutrient stress via the ATF4 target ASNS, which subsequently contributes to inhibition of apoptosis and increase in proliferation of cancer cells (Gwinn et al., 2018Gwinn DM, Lee AG, Briones-Martin-Del-Campo M, Conn CS, Simpson DR, Scott AI, Le A, Cowan TM, Ruggero D and Sweet-Cordero EA (2018) Oncogenic KRAS regulates amino acid homeostasis and asparagine biosynthesis via ATF4 and alters sensitivity to L-asparaginase. Cancer Cell 33:91-107 e106.). While KRAS mutations are uncommon in HNSCC, particularly as compared to HRAS (Rothenberg and Ellisen, 2012Rothenberg SM and Ellisen LW (2012) The molecular pathogenesis of head and neck squamous cell carcinoma. J Clin Invest 122:1951-1957.), mutations in ASNS could effectively have the same functional consequences. Given the role of ASNS in cellular stress and the unfolded protein response, it is an intriguing target for further study in HNSCC pathogenesis.
The current analysis also revealed significant low-frequency driver mutations in SETBP1, IGF2BP3, PTPN11 and NF2. SETBP1 was identified in a patient who also had a driver mutation in FGFR2. SETBP1 encodes a nuclear protein and its overexpression results in inhibition of the tumour-suppressor PP2A serine-threonine phosphatase activity (Cristobal et al., 2010Cristobal I, Blanco FJ, Garcia-Orti L, Marcotegui N, Vicente C, Rifon J, Novo FJ, Bandres E, Calasanz MJ, Bernabeu C et al. (2010) SETBP1 overexpression is a novel leukemogenic mechanism that predicts adverse outcome in elderly patients with acute myeloid leukemia. Blood 115:615-625.). Mutations in SETBP1 resulting in overexpression or gain of function have been documented previously in hematological malignancies (Ciccone et al., 2015Ciccone M, Calin GA and Perrotti D (2015) From the Biology of PP2A to the PADs for therapy of hematologic malignancies. Front Oncol 5:21.).
An IGF2BP3 mutation was found in a sample that also had driver mutations in PIK3CA and TP53. The protein product of IGF2BP3 is an RNA-binding factor that promotes cancer invasion by binding to transcripts that encode proteins, such as CD44, for functions related to cell migration, proliferation and adhesion (Ennajdaoui et al., 2016Ennajdaoui H, Howard JM, Sterne-Weiler T, Jahanbani F, Coyne DJ, Uren PJ, Dargyte M, Katzman S, Draper JM, Wallace A et al. (2016) IGF2BP3 modulates the interaction of invasion-associated transcripts with RISC. Cell Rep 15:1876-1883.). IGF2BP3 mutations and copy number variations have been reported previously in HNSCC (Lin et al., 2011Lin CY, Chen ST, Jeng YM, Yeh CC, Chou HY, Deng YT, Chang CC and Kuo MY (2011) Insulin-like growth factor II mRNA-binding protein 3 expression promotes tumor formation and invasion and predicts poor prognosis in oral squamous cell carcinoma. J Oral Pathol Med 40:699-705.; Clauditz et al., 2013Clauditz TS, Wang CJ, Gontarewicz A, Blessmann M, Tennstedt P, Borgmann K, Tribius S, Sauter G, Dalchow C, Knecht R et al. (2013) Expression of insulin-like growth factor II mRNA-binding protein 3 in squamous cell carcinomas of the head and neck. J Oral Pathol Med 42:125-132.; Jimenez et al., 2015Jimenez L, Jayakar SK, Ow TJ and Segall JE (2015) Mechanisms of invasion in head and neck cancer. Arch Pathol Lab Med 139:1334-1348.), and its role in cell invasiveness and metastasis in several other cancers has been documented in the literature (Schaeffer et al., 2010Schaeffer DF, Owen DR, Lim HJ, Buczkowski AK, Chung SW, Scudamore CH, Huntsman DG, Ng SS and Owen DA (2010) Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) overexpression in pancreatic ductal adenocarcinoma correlates with poor survival. BMC Cancer 10:59.; Lin et al., 2011Lin CY, Chen ST, Jeng YM, Yeh CC, Chou HY, Deng YT, Chang CC and Kuo MY (2011) Insulin-like growth factor II mRNA-binding protein 3 expression promotes tumor formation and invasion and predicts poor prognosis in oral squamous cell carcinoma. J Oral Pathol Med 40:699-705.; Taniuchi et al., 2014Taniuchi K, Furihata M, Hanazaki K, Saito M and Saibara T (2014) IGF2BP3-mediated translation in cell protrusions promotes cell invasiveness and metastasis of pancreatic cancer. Oncotarget 5:6832-6845.; Hsu et al., 2015Hsu KF, Shen MR, Huang YF, Cheng YM, Lin SH, Chow NH, Cheng SW, Chou CY and Ho CL (2015) Overexpression of the RNA-binding proteins Lin28B and IGF2BP3 (IMP3) is associated with chemoresistance and poor disease outcome in ovarian cancer. Br J Cancer 113:414-424.; Shantha Kumara et al., 2015Shantha Kumara H, Kirchoff D, Caballero OL, Su T, Ahmed A, Herath SA, Njoh L, Cekic V, Simpson AJ, Cordon-Cardo C et al. (2015) Expression of the cancer testis antigen IGF2BP3 in colorectal cancers; IGF2BP3 holds promise as a specific immunotherapy target. Oncoscience 2:607-614.; Belharazem et al., 2016Belharazem D, Magdeburg J, Berton AK, Beissbarth L, Sauer C, Sticht C, Marx A, Hofheinz R, Post S, Kienle P et al. (2016) Carcinoma of the colon and rectum with deregulation of insulin-like growth factor 2 signaling: clinical and molecular implications. J Gastroenterol 51:971–984.; de Lint et al., 2016de Lint K, Poell JB, Soueidan H, Jastrzebski K, Vidal Rodriguez J, Lieftink C, Wessels LF and Beijersbergen RL (2016) Sensitizing triple-negative breast cancer to PI3K inhibition by co-targeting IGF1R. Mol Cancer Ther 15:1545-1556.; Ennajdaoui et al., 2016Ennajdaoui H, Howard JM, Sterne-Weiler T, Jahanbani F, Coyne DJ, Uren PJ, Dargyte M, Katzman S, Draper JM, Wallace A et al. (2016) IGF2BP3 modulates the interaction of invasion-associated transcripts with RISC. Cell Rep 15:1876-1883.).
Mutations in PTPN11 and NF2 genes were found in the same sample. The protein encoded by the proto-oncogene PTPN11 is a cytoplasmic tyrosine phosphatase, which is widely expressed in most tissues and known to play a regulatory role in normal hematopoiesis, and in mitogenic activation, metabolic control, transcription regulation, and cell migration signaling pathways (Chan and Feng, 2007Chan RJ and Feng GS (2007) PTPN11 is the first identified proto-oncogene that encodes a tyrosine phosphatase. Blood 109:862-867.). Somatic PTPN11 mutations have been detected in juvenile myelomonocytic leukemia, myelodysplastic syndromes and acute myeloid leukemia (Tartaglia et al., 2003Tartaglia M, Niemeyer CM, Fragale A, Song X, Buechner J, Jung A, Hahlen K, Hasle H, Licht JD and Gelb BD (2003) Somatic mutations in PTPN11 in juvenile myelomonocytic leukemia, myelodysplastic syndromes and acute myeloid leukemia. Nat Genet 34:148-150.; Chan and Feng, 2007Chan RJ and Feng GS (2007) PTPN11 is the first identified proto-oncogene that encodes a tyrosine phosphatase. Blood 109:862-867.). While PTPN11 mutations have not been reported previously in HNSCC, this gene has been identified as a target of the tumour-suppressive microRNA miR-489. Knockdown of PTPN11 in HNSCC cell lines resulted in the inhibition of cell proliferation (Kikkawa et al., 2010Kikkawa N, Hanazawa T, Fujimura L, Nohata N, Suzuki H, Chazono H, Sakurai D, Horiguchi S, Okamoto Y and Seki N (2010) miR-489 is a tumour-suppressive miRNA target PTPN11 in hypopharyngeal squamous cell carcinoma (HSCC). Br J Cancer 103:877-884.). Neurofibromatosis type 2 (NF2) is a tumour suppressor gene on chromosome 22q12 that encodes for merlin, a membrane-cytoskeleton scaffolding protein that inhibits key signaling pathways crucial to cell proliferation, such as the PI3K pathway. Somatic NF2 mutations have been reported in a number of different cancers (Schroeder et al., 2014Schroeder RD, Angelo LS and Kurzrock R (2014) NF2/merlin in hereditary neurofibromatosis 2 versus cancer: biologic mechanisms and clinical associations. Oncotarget 5:67-77.). In HNSCC, chromosome 22q is a frequent site of allele loss. Merlin and the cytoplasmic tail of CD44, which is regulated at the transcript level by IGF2BP3 gene product as mentioned above, create a molecular switch complex that is responsible for either cell growth or proliferation (Morrison et al., 2001Morrison H, Sherman LS, Legg J, Banine F, Isacke C, Haipek CA, Gutmann DH, Ponta H and Herrlich P (2001) The NF2 tumor suppressor gene product, merlin, mediates contact inhibition of growth through interactions with CD44. Genes Dev 15:968-980.).
In addition to non-synonymous mutations, synonymous mutations are known to frequently act as driver mutations in cancers (Supek et al., 2014Supek F, Minana B, Valcarcel J, Gabaldon T and Lehner B (2014) Synonymous mutations frequently act as driver mutations in human cancers. Cell 156:1324-1335.). We identified SNVs in MLL3, ARID2 and ALK. Mutations in MLL and ARID gene families have been previously documented for HNSCC (India Project Team of the International Cancer Genome Consortium, 2013India Project Team of the International Cancer Genome Consortium (2013) Mutational landscape of gingivo-buccal oral squamous cell carcinoma reveals new recurrently-mutated genes and molecular subgroups. Nat Commun 4:2873.; Martin et al., 2014Martin D, Abba MC, Molinolo AA, Vitale-Cross L, Wang Z, Zaida M, Delic NC, Samuels Y, Lyons JG and Gutkind JS (2014) The head and neck cancer cell oncogenome: a platform for the development of precision molecular therapies. Oncotarget 5:8906-8923.). The ALK gene encodes yet another receptor tyrosine kinase, which has been found to be aberrantly expressed in several tumours, including anaplastic large cell lymphomas (Chiarle et al., 2008Chiarle R, Voena C, Ambrogio C, Piva R and Inghirami G (2008) The anaplastic lymphoma kinase in the pathogenesis of cancer. Nat Rev Cancer 8:11-23.; Salaverria et al., 2008Salaverria I, Bea S, Lopez-Guillermo A, Lespinet V, Pinyol M, Burkhardt B, Lamant L, Zettl A, Horsman D, Gascoyne R et al. (2008) Genomic profiling reveals different genetic aberrations in systemic ALK-positive and ALK-negative anaplastic large cell lymphomas. Br J Haematol 140:516-526.), neuroblastoma (Lasorsa et al., 2016Lasorsa VA, Formicola D, Pignataro P, Cimmino F, Calabrese FM, Mora J, Esposito MR, Pantile M, Zanon C, De Mariano M et al. (2016) Exome and deep sequencing of clinically aggressive neuroblastoma reveal somatic mutations that affect key pathways involved in cancer progression. Oncotarget 7 21840–21852.; Theruvath et al., 2016Theruvath J, Russo A, Kron B, Paret C, Wingerter A, El Malki K, Neu MA, Alt F, Staatz G, Stein R et al. (2016) Next-generation sequencing reveals germline mutations in an infant with synchronous occurrence of nephro- and neuroblastoma. Pediatr Hematol Oncol 33:264-275.; Ueda et al., 2016Ueda T, Nakata Y, Yamasaki N, Oda H, Sentani K, Kanai A, Onishi N, Ikeda K, Sera Y, Honda ZI et al. (2016) ALKR1275Q perturbs extracellular matrix, enhances cell invasion and leads to the development of neuroblastoma in cooperation with MYCN. Oncogene 35:4447-4458.) and non-small cell lung cancer (Soda et al., 2007Soda M, Choi YL, Enomoto M, Takada S, Yamashita Y, Ishikawa S, Fujiwara S, Watanabe H, Kurashina K, Hatanaka H et al. (2007) Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature 448:561-566.; Quere et al., 2016Quere G, Descourt R, Robinet G, Autret S, Raguenes O, Fercot B, Alemany P, Uguen A, Ferec C, Quintin-Roue I et al. (2016) Mutational status of synchronous and metachronous tumor samples in patients with metastatic non-small-cell lung cancer. BMC Cancer 16:210.).
A study of gingivo-buccal oral squamous cell carcinoma (OSCC-GB), an HNSCC clinical sub-type, in the Indian population revealed frequently altered genes that are specific to OSCC-GB and others that are also affected in HNSCC (India Project Team of the International Cancer Genome Consortium, 2013India Project Team of the International Cancer Genome Consortium (2013) Mutational landscape of gingivo-buccal oral squamous cell carcinoma reveals new recurrently-mutated genes and molecular subgroups. Nat Commun 4:2873.). Altered genes that are common between the OSCC-GB study and the current study in the Pakistani population are ARID2 and TP53. MLL family member MLL4 was also identified as a frequently altered gene specific to OSCC-GB. Other genes identified in the study in the Indian population, such as CASP8, HRAS and NOTCH1, are also altered in HNSCC in other populations (albeit at different frequencies and with varying significance) (Agrawal et al., 2011Agrawal N, Frederick MJ, Pickering CR, Bettegowda C, Chang K, Li RJ, Fakhry C, Xie TX, Zhang J, Wang J et al. (2011) Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1. Science 333:1154-1157.; Stransky et al., 2011Stransky N, Egloff AM, Tward AD, Kostic AD, Cibulskis K, Sivachenko A, Kryukov GV, Lawrence MS, Sougnez C, McKenna A et al. (2011) The mutational landscape of head and neck squamous cell carcinoma. Science 333:1157-1160.; Seiwert et al., 2015Seiwert TY, Zuo Z, Keck MK, Khattri A, Pedamallu CS, Stricker T, Brown C, Pugh TJ, Stojanov P, Cho J et al. (2015) Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas. Clin Cancer Res 21:632-641.; The Cancer Genome Atylas Network, 2015The Cancer Genome Atlas Network (2015) Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517:576–582.; Al-Hebshi et al., 2016Al-Hebshi NN, Li S, Nasher AT, El-Setouhy M, Alsanosi R, Blancato J and Loffredo C (2016) Exome sequencing of oral squamous cell carcinoma in users of Arabian snuff reveals novel candidates for driver genes. Int J Cancer 139:363-372.), but were not identified in this study.
The small sample size is a limitation of this study, which may explain low frequency of commonly mutated genes and why some of the commonly occurring HNSCC mutations such as NOTCH1 and HRAS were not identified in this small cohort. However, given limited resources, it was deemed important to establish preliminary data prior to a larger scale study. The approach of using a smaller discovery cohort followed by validation of identified mutations in a larger cohort has been proposed and taken by others and reported in the literature (Bacchetti et al., 2011Bacchetti P, Deeks SG and McCune JM (2011) Breaking free of sample size dogma to perform innovative translational research. Sci Transl Med 3:87ps24.; Nichols et al., 2012Nichols AC, Chan-Seng-Yue M, Yoo J, Xu W, Dhaliwal S, Basmaji J, Szeto CC, Dowthwaite S, Todorovic B, Starmans MH et al. (2012) A pilot study comparing HPV-positive and HPV-negative head and neck squamous cell carcinomas by whole exome sequencing. ISRN Oncol 2012:809370.; Romero Arenas et al., 2014Romero Arenas MA, Fowler RG, San Lucas FA, Shen J, Rich TA, Grubbs EG, Lee JE, Scheet P, Perrier ND and Zhao H (2014) Preliminary whole-exome sequencing reveals mutations that imply common tumorigenicity pathways in multiple endocrine neoplasia type 1 patients. Surgery 156:1351-1357; discussion 1357-1358.; Hedberg et al., 2015Hedberg ML, Goh G, Chiosea SI, Bauman JE, Freilino ML, Zeng Y, Wang L, Diergaarde BB, Gooding WE, Lui VW et al. (2015) Genetic landscape of metastatic and recurrent head and neck squamous cell carcinoma. J Clin Invest 126:169-180.). It is also possible that given the heterogeneous nature of this disease and unique set of risk factors compared to Western countries, the predominant driver gene mutations may vary among populations. Previous studies in East and South Asian populations with oral squamous cell carcinoma have highlighted that the pattern of genetic mutations is significantly different from tumour profiles in other studies largely conducted in Caucasian populations (Vettore et al., 2015Vettore AL, Ramnarayanan K, Poore G, Lim K, Ong CK, Huang KK, Leong HS, Chong FT, Lim TK, Lim WK et al. (2015) Mutational landscapes of tongue carcinoma reveal recurrent mutations in genes of therapeutic and prognostic relevance. Genome Med 7:98.; Su et al., 2017Su SC, Lin CW, Liu YF, Fan WL, Chen MK, Yu CP, Yang WE, Su CW, Chuang CY, Li WH et al. (2017) Exome sequencing of oral squamous cell carcinoma reveals molecular subgroups and novel therapeutic opportunities. Theranostics 7:1088-1099.). Population-based differences in mutational profile have also been documented for other cancer types. In lung cancers, several studies have highlighted the geographic variations in genes such as EGFR and LKBI between Asian (Chinese, Japanese, Korean) and Caucasian populations (Koivunen et al., 2008Koivunen JP, Kim J, Lee J, Rogers AM, Park JO, Zhao X, Naoki K, Okamoto I, Nakagawa K, Yeap BY et al. (2008) Mutations in the LKB1 tumour suppressor are frequently detected in tumours from Caucasian but not Asian lung cancer patients. Br J Cancer 99:245-252.; Mitsudomi, 2014Mitsudomi T (2014) Molecular epidemiology of lung cancer and geographic variations with special reference to EGFR mutations. Transl Lung Cancer Res 2014:205-211.; Li et al., 2015Li C, Gao Z, Li F, Li X, Sun Y, Wang M, Li D, Wang R, Fang R, Pan Y et al. (2015) Whole exome sequencing identifies frequent somatic mutations in cell-cell adhesion genes in Chinese patients with lung squamous cell carcinoma. Sci Rep 5:14237.).
This is the first report describing the mutational spectrum of Pakistani HNSCC patients. In addition to reporting known HNSCC mutations, we have identified novel, recurrent mutations in ASNS and other genes in the Pakistani population. It has been well established that a complex interplay of genetic and environmental factors results in varying risk of cancer development and treatment outcomes across different ethnicities and geographic regions (Ma et al., 2010Ma BB, Hui EP and Mok TS (2010) Population-based differences in treatment outcome following anticancer drug therapies. Lancet Oncol 11:75-84.). Such diversity among different populations can be explained by the type and frequency of variations in both germline and somatic genomes (Wang and Wheeler, 2014Wang L and Wheeler DA (2014) Genomic sequencing for cancer diagnosis and therapy. Annu Rev Med 65:33-48.). Therefore, this study is an important step towards gaining a better mechanistic understanding of the complex nature of HNSCC. Future studies will be undertaken to confirm and validate the findings from this study in a larger cohort. Additionally, functional analysis of mutations and correlation with clinical outcomes will be performed.
Acknowledgments
This work was supported by the Higher Education Commission of Pakistan (20-1224-R&D/2009 to K.G. and M.J.K). The funding source had no involvement in the study design and conduct or preparation of the article. The authors gratefully acknowledge Aisha Nazir for her role in pre-sequencing sample processing, Muhammed Murtaza and Faiz Gani for their input and support in the initial stages of this project, and Faizan Saleem for his help with data analysis. HPV primers (GP5/GP6) were graciously provided by Dr SH Ali (then at Aga Khan University, Pakistan).
Conflict of Interest
The authors have no conflicts to declare.
Author contributions
KG was involved in conceiving and designing the study, data analysis and interpretation, and drafted the manuscript; SSR conceived and designed the study, processed the samples prior to sequencing, analyzed and interpreted the data and contributed in writing the manuscript; SAR and MKA were involved in data analysis and interpretation, and contributed to the manuscript; SM contributed to data acquisition and manuscript writing; RA performed the histopathological examination of HNSCC samples and contributed to the manuscript; MJK was involved in conceiving and designing the study and was responsible for sample resection and acquisition. All authors read and approved the final version of the manuscript.
References
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Supplementary material
The following online material is available for this article
Table S1 Whole exome sequencing data summary.
Table S2 Somatic non-coding single nucleotide variants (SNVs) found in ≥ 2 HNSCC patients.
Publication Dates
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Publication in this collection
14 Nov 2019 -
Date of issue
Jul-Sep 2019
History
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Received
10 Jan 2018 -
Accepted
28 Nov 2018