Case Reports in Oncological Medicine

Case Reports in Oncological Medicine / 2013 / Article

Case Report | Open Access

Volume 2013 |Article ID 270362 |

Anthony C. Nichols, Michelle Chan-Seng-Yue, John Yoo, Sumit K. Agrawal, Maud H. W. Starmans, Daryl Waggott, Nicholas J. Harding, Samuel A. Dowthwaite, David A. Palma, Kevin Fung, Bret Wehrli, S. Danielle MacNeil, Philippe Lambin, Eric Winquist, James Koropatnick, Joe S. Mymryk, Paul C. Boutros, John W. Barrett, "A Case Report and Genetic Characterization of a Massive Acinic Cell Carcinoma of the Parotid with Delayed Distant Metastases", Case Reports in Oncological Medicine, vol. 2013, Article ID 270362, 7 pages, 2013.

A Case Report and Genetic Characterization of a Massive Acinic Cell Carcinoma of the Parotid with Delayed Distant Metastases

Academic Editor: D. V. Jones
Received06 Feb 2013
Accepted04 Mar 2013
Published03 Apr 2013


We describe the presentation, management, and clinical outcome of a massive acinic cell carcinoma of the parotid gland. The primary tumor and blood underwent exome sequencing which revealed deletions in CDKN2A as well as PPP1R13B, which induces p53. A damaging nonsynonymous mutation was noted in EP300, a histone acetylase which plays a role in cellular proliferation. This study provides the first insights into the genetic underpinnings of this cancer. Future large-scale efforts will be necessary to define the mutational landscape of salivary gland malignancies to identify therapeutic targets and biomarkers of treatment failure.

1. Introduction

Salivary gland cancers account for 0.3–0.9% of all cancers [1, 2], and acinic cell carcinoma (AciCC) accounts for 5–11% of these [3, 4]. AciCC most commonly arises in the parotid gland and typically presents at an early stage allowing surgical treatment with favorable five-year survival rates in excess of 90% [4]. However, approximately 19% of cases present with advanced stage disease, which is associated with a higher rate of distant metastases and poorer survival [4]. To date, this tumor type has not been genetically characterized.

2. Case Report

Our patient is a morbidly obese (375 lbs) 58-year-old woman who presented to the head and neck surgery clinic with a right parotid mass and intact facial nerve function. She underwent a fine needle aspiration which was consistent with a Warthin’s tumor. CT imaging demonstrated a 5.8 cm right parotid mass. She was scheduled for surgery, but was lost to followup. She presented again to the head and neck surgery clinic one year later with significant interval growth of the mass and a partial right facial paresis (Figures 1(a) and 1(b)). A CT scan demonstrated a 11.2 × 9.4 × 10.7 cm mass centered in the right parotid effacing the jugular vein and abutting the mandible and skull base with extension along the facial nerve to the geniculate ganglion (Figures 1(c) and 1(d)). She was taken to the operating room and underwent a radical parotidectomy with facial nerve sacrifice, radical neck dissection, parapharyngeal space resection, and lateral temporal bone resection (Figures 2(a), 2(b), and 2(c)). The tumor was found to be invading the jugular foramen requiring occlusion of the sigmoid sinus and packing of the jugular foramen for vascular control. The tumor was also noted to be extending medially to the geniculate ganglion of the facial nerve. Gross tumor removal was accomplished (Figure 2(d)). We were not able to obtain a negative margin on the proximal facial nerve; thus, the ipsilateral masseter nerve was grafted to the buccal and marginal mandibular branches of the distal facial nerve. Her face was further rehabilitated with a static palmaris longus sling and temporary tarsorraphy, which was later replaced with a gold weight. The defect was reconstructed with a large cervicofacial rotation flap and a radial forearm free flap (Figure 2(e)). Pathologic examination revealed a 14 cm low-grade acinic cell carcinoma with extensive perineural and lymphovascular spread. The lymph node dissection yielded 29 lymph nodes, all of which were negative for malignancy. Postoperatively, she received 6000 cGy in 30 fractions using intensity modulated radiation therapy (IMRT) to the primary site and neck. During and after radiation, the patient experienced massive weight loss, losing approximately 200 lbs. Follow-up imaging one year after treatment revealed no evidence of local or regional recurrence; however, there was interval development of multiple new bilateral lung nodules up to 0.9 cm highly suspicious for metastases (Figures 3(a) and 3(b)). They were deemed too small to be biopsied percutaneously. The patient was referred for consideration of palliative chemotherapy; however, as she was asymptomatic the decision was made to follow her with serial imaging.

3. DNA Extraction, Exome Sequencing, and Bioinformatics Methods

Ethical approval was obtained from the University of Western Ontario Health Sciences Research Ethics and informed consent was obtained from the patient. DNA extraction from blood and tumor samples was carried out as previously described [5]. Exome sequencing was performed by Otogenetics (Tucker, Georgia) using the Agilent Human All Exon 50 Mbp exome capture kit with 30-fold coverage with 100 base-pair paired-end reads. The reference blood and primary tumor samples were aligned to the human hg19 reference sequence using Novoalign (v2.07.14). A maximum of five repeat alignments, defined as having a score difference of zero, were reported in the final output. SAM formatted output was specified with appropriate read group information provided. The remaining parameters were set to default values. Low-quality alignments, defined as alignments with low confidence in the reported position due to multiple alignment hits or poor base quality, were removed from the BAM files using SAMtools (v0.1.18) [6] by specifying the 30 quality filter. Additionally, unaligned and nonprimary reads (only 1 alignment, called the primary alignment, was retained in cases of multiple alignments) were removed by again using SAMtools (v0.1.18) and specifying the -F4 and –F 256 flags, respectively [6]. PCR artifacts were removed using MarkDuplicates tool from Picard (v1.66) with default settings. Samples were then processed as a matched set through the GATK (v1.3-16) pipeline [7, 8]. Samples were initially locally realigned using the IndelRealigner walker from the GATK package with known insertions and deletions found in dbSNP build 135. This was followed by base quality recalibration using GATK. Finally, variants were called and filtered using the GATK UnifiedGenotyper and VariantFiltration walkers again with default settings. Somatic variants within the targeted regions were identified using an in-house Perl library. To be classified as a somatic variant, the following conditions had to be met: (1) a tumor variant was identified by GATK and had a minimum 20x coverage and (2) the variant base was not seen at that position in the corresponding normal sample (20x coverage). The genes were annotated using RefGene and the consequences of the variations were identified using ANNOVAR dated 2012-03-08 [9]. As a final filtration step, any somatic variants, found in genes identified by Fuentes et al. as possible problematic genes for sequencing data, were removed [10]. Next, copy-number variants in the target regions were predicted with contra (v2.0.3) using default parameters [11]. DNAcopy (v1.32.0) was used to segment the copy numbers for visualization. This was done using default settings. Visualizations were generated using R (v2.15.2) and the lattice (v0.20-11) and latticeExtra (v0.6-24) packages. Of the target bases, approximately 60% were covered at a minimum of 20x collapsed coverage in the blood sample and 63% in the tumor.

4. Interpretation of Identified Mutations

Our bioinformatics pipeline identified 14 nonsynonymous mutations (Table 1) and significant copy-number variations (CNVs) in 35 genes including 31 amplifications and 4 deletions (Table 2). CNVs were classified as significant if they met an adjusted value threshold value of 0.05. A comprehensive listing of the single-nucleotide variants, (SNVs) identified including noncoding regions is provided in the Supplementary Table  S1 available online at The amplifications occurred preferentially in chromosome 2 and chromosome 9 , with single-amplification loci in chromosomes 14 and 22 (Table 2). The coding SNVs and all CNVs are illustrated in Figure 4. In addition, there were two deletions on chromosome 9 (CDKN2A and MTAP), one on chromosome 14 (PPP1R13B) and one on chromosome 3 (ETV5). All of the identified single-nucleotide variant mutations were heterozygous. Thirteen exhibited nonsynonymous changes in the respective proteins and one was a nonsense mutation which led to premature termination of the protein (GRIK3).

GeneChrPositionReference alleleTumor alleleZygosityRegionTypeTranscriptExonCDS positionProtein change


Chr: chromosome, Bolded genes are in cosmic v61.

GeneChrStart coordinateEnd coordinateAdjusted mean log ratio valueAdjusted valueGain/loss

AAK1269752135697522641.719 Gain
ABCA191075867421075868621.908 Gain
ABCA1222158903892158905091.846 Gain
AGAP122367919802367921002.084 Gain
ALDH1A1975533626755337461.595 Gain
ASAP22950854095086601.931 Gain
CDKN2A92197444021974830−4.943 Loss
CERKL21824301381824302581.672 Gain
CLASP121220984191220985391.990 Gain
ETV53185823397185823517−1.623 Loss
EXD391402506491402508771.883 Gain
GABBR291011564361011565561.864 Gain
GSN91240761661240763161.636 Gain
IL18RAP21030408171030409371.602 Gain
INPP4A299136444991366841.894 Gain
ITGA421823888771823889971.965 Gain
LOC375190224390449243905692.155 Gain
LOC966102222657565226576851.907 Gain
MERTK21127659451127661691.473 Gain
MERTK21127781451127782651.707 Gain
MFSD621913544821913546021.980 Gain
MTAP92183789721838017−4.841 Loss
NGEF22337458472337459671.612 Gain
NUP18891317192101317193301.627 Gain
POLR1E937489294374894142.029 Gain
POMT21477753065777531851.796 Gain
PPIG21704606731704607931.944 Gain
PPP1R13B14104201451104201571−1.855 Loss
PSMD591235913711235914911.845 Gain
RNASEH12359621135963311.911 Gain
SH3RF321099880291099881492.909 Gain
SLC46A291156420101156421301.621 Gain
SULT6B1237415566374156861.530 Gain
TESK1935607906356080261.688 Gain
TTC27232929895329300151.466 Gain

Chr: chromosome, bolded genes are in cosmic v61.

Several of these aberrations are plausibly associated to tumor formation and growth. Most critically, somatic deletion of the potent tumor-suppressor CDKN2A was identified. CDKN2A is one of the most widely mutated genes in human malignancies. According to the ICGC data-coordinating centre, it is mutated in up to half of glioblastoma multiforme, 14% of squamous cell carcinomas of the lung, and a third of all pancreatic adenocarcinomas [12]. It functions by stabilizing TP53 by sequestering the MDM2 ubiquitin ligase and by inhibiting CDK4-mediated G1 progression through the cellcycle. In addition, a deletion of 120 nucleotides of methylthioadenosine phosphorylase (MTAP) was identified, which is an important protein for salvaging adenine and methionine [13]. MTAP is located upstream of CDKN2A, frequently deficient in cancers, and often codeleted with p16 [13].

Also of great note, a nonsynonymous mutation in the E1A binding protein p300 (EP300) was identified. This protein functions as a histone acetyltransferase that regulates transcription via chromatin remodeling and is important in cell proliferation and differentiation [14]. EP300 interacts with hundreds of cellular transcriptional regulators [15] and is a key regulator of p53 function [16]. The observed mutation converts a glutamine to leucine at position 340 within the TAZ1 (CH1) zinc finger domain, which interacts with numerous transcription factors [17] and viral oncoproteins including human papillomavirus E7 [18]. The glutamine that is mutated is known to be involved in the interaction with STAT2, a key component of the interferon response, and potentially many other targets of the TAZ1 domain [19]. EP300 is frequently mutated in several tumour types [2022] and its inactivation is thought to play a major role in the development of small cell lung cancer [21]. Loss of EP300 function would result in unopposed histone deacetylation, potentially creating an opportunity for targeted therapy with histone deacetylase (HDAC) inhibitors [23].

There was also a deletion identified in PPP1R13B which encodes the apoptosis stimulating of p53 protein 1 (ASPP1) [24]. Specifically, ASPP1 binds to p53 and enhances its ability to specifically stimulate expression of proapoptotic target genes, but not genes involved in cell cycle arrest [25]. Thus, ASPP1 functions as a tumor suppressor gene and has been shown to be downregulated in breast cancer [25] and leukemia cell lines [26], suggesting that the loss of this gene may play an important role in cancer progression. The role of the mutated genes in initiation and progression of AciCC identified in our study will require further investigation.

5. Discussion

AciCC is the least aggressive major salivary gland malignancy [27]. Typically these lesions are present at an early stage with low-grade histology and are cured at a high rate solely with surgery [4]. However, a subset presents with higher grade histology and/or advanced local, regional, and distant disease that portends a poorer outcome despite the addition of adjuvant radiation [4]. Currently, there are few treatment options available to be offered these patients when they relapse. For rare tumors such as AciCC, the standard mechanism to identify chemotherapeutic agents through a series of phase I, II, and III trials is not feasible due to limited patient numbers. A focused strategy based on tumor biology is necessary. The advent of massively parallel sequencing has led to incredible advances in the understanding of tumor genetics and biology. Recent exome sequencing of head and neck squamous cell carcinoma (HNSCC) has revealed that the mutational landscape of HNSCC is dominated by mutations in tumor suppressor genes, with only rare targetable mutations in oncogenes [28, 29]. However, studies of other cancers such as melanoma have revealed clearly targetable changes such as activating mutations in BRAF, which have already had a profound impact on clinical care [30]. Our study has provided the first glimpse of the genetic underpinnings of AciCC, highlighting changes in the tumor suppressors CDKN2A and PPP1R13B. There was also a mutation in the histone acetyltransferase EP300 that could reduce the acetylation of various targets. This mutation may make this tumor more susceptible to histone deacetylase inhibitors, which are already showing promise in vitro and in early-stage clinical trials [31, 32]. Future large-scale studies of salivary malignancies utilizing next generation sequencing (as for other cancers [33, 34]) will provide hope for improved patient outcomes.

6. Conclusion

Acinic cell carcinoma is a relatively rare salivary gland malignancy that typically has a favorable prognosis when treated solely with surgery. A small subset of these cancers present with advanced-stage disease which can be associated with poorer survival despite the addition of adjuvant radiation. Further study is necessary to understand the biology of salivary gland malignancies in order to develop adjuvant therapies to improve outcomes for patients with high-risk disease.

Authors’ Contribution

A. C. Nichols, M. Chan-Seng-Yue, P. C. Boutros, and J. W. Barrett contributed equally to this work.


The authors have no financial interests in companies or other entities that have an interest in the information in the contribution (e.g., grants, advisory boards, employment, consultancies, contracts, honoraria, royalties, expert testimony, partnerships, or stock ownership in medically-related fields).

Conflict of Interests

The authors declare that they have no conflict of interests.


Exome sequencing was performed by Otogenetics (Tucker, GA, USA). This work was performed with the support of the Western University Translational Head and Neck Cancer Program to A. C. Nichols and the Ontario Institute for Cancer Research to P. C. Boutros through funding provided by the Government of Ontario.

Supplementary Materials

Supplementary Table: Complete list of somatic mutations identified in an acinic cell carcinoma. Single nucleotide polymorphisms (SNPs) were identified in the manner outlined in the bioinformatics methods of Section 3 of the manuscript. Variants were filtered against the gene exclusion list from Fuentes et al. [10].

  1. Supplementary Table


  1. SEER Cancer Statistics Review, 1975–2009, National Cancer Institute, Bethesda, Md, USA, 2012.
  2. J. M. Jessup, H. R. Menck, D. P. Winchester, S. A. Hundahl, and G. P. Murphy, “The National Cancer Data Base report on patterns of hospital reporting,” Cancer, vol. 78, pp. 1829–1837, 1996. View at: Google Scholar
  3. A. M. Cesinaro, M. Criscuolo, G. Collina, R. Galetti, M. Migaldi, and F. Lo Bianco, “Salivary gland tumors: revision of 391 cases according to the new WHO classification,” Pathologica, vol. 86, no. 6, pp. 602–605, 1994. View at: Google Scholar
  4. H. T. Hoffman, L. H. Karnell , R. A. Robinson, J. A. Pinkston, and H. R. Menck, “National Cancer Data Base report on cancer of the head and neck: acinic cell carcinoma,” Head & Neck, vol. 21, pp. 297–309, 1999. View at: Google Scholar
  5. A. C. Nichols, M. Chan-Seng-Yue, J. Yoo et al., “A pilot study comparing HPV-positive and HPV-negative head and neck squamous cell carcinomas by whole exome sequencing,” ISRN Oncology, vol. 2012, Article ID 809370, 9 pages, 2012. View at: Publisher Site | Google Scholar
  6. H. Li, B. Handsaker, A. Wysoker et al., “The sequence alignment/map format and SAMtools,” Bioinformatics, vol. 25, no. 16, pp. 2078–2079, 2009. View at: Publisher Site | Google Scholar
  7. M. A. Depristo, E. Banks, R. Poplin et al., “A framework for variation discovery and genotyping using next-generation DNA sequencing data,” Nature Genetics, vol. 43, no. 5, pp. 491–501, 2011. View at: Publisher Site | Google Scholar
  8. A. McKenna, M. Hanna, E. Banks et al., “The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data,” Genome Research, vol. 20, no. 9, pp. 1297–1303, 2010. View at: Publisher Site | Google Scholar
  9. K. Wang, M. Li, and H. Hakonarson, “ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data,” Nucleic Acids Research, vol. 38, no. 16, p. e164, 2010. View at: Publisher Site | Google Scholar
  10. K. V. Fuentes Fajardo, D. Adams, C. E. Mason et al., “Detecting false-positive signals in exome sequencing,” Human Mutation, vol. 33, pp. 609–613, 2012. View at: Google Scholar
  11. J. Li, R. Lupat , K. C. Amarasinghe et al., “CONTRA: copy number analysis for targeted resequencing,” Bioinformatics, vol. 28, pp. 1307–1313, 2012. View at: Google Scholar
  12. T. J. Hudson, W. Anderson, A. Aretz et al., “International network of cancer genome projects,” Nature, vol. 464, no. 7291, pp. 993–998, 2010. View at: Publisher Site | Google Scholar
  13. C. C. Collins, S. V. Volik , A. V. Lapuk et al., “Next generation sequencing of prostate cancer from a patient identifies a deficiency of methylthioadenosine phosphorylase, an exploitable tumor target,” Molecular Cancer Therapeutics, vol. 11, pp. 775–783, 2012. View at: Google Scholar
  14. R. Eckner, “p300 and CBP as transcriptional regulators and targets of oncogenic events,” Biological Chemistry, vol. 377, no. 11, pp. 685–688, 1996. View at: Google Scholar
  15. D. C. Bedford, L. H. Kasper, T. Fukuyama, and P. K. Brindle, “Target gene context influences the transcriptional requirement for the KAT3 family of CBP and p300 histone acetyltransferases,” Epigenetics, vol. 5, no. 1, pp. 9–15, 2010. View at: Publisher Site | Google Scholar
  16. A. S. Coutts and N. B. La Thangue, “The p53 response: emerging levels of co-factor complexity,” Biochemical and Biophysical Research Communications, vol. 331, no. 3, pp. 778–785, 2005. View at: Publisher Site | Google Scholar
  17. R. H. Goodman and S. Smolik, “CBP/p300 in cell growth, transformation, and development,” Genes and Development, vol. 14, no. 13, pp. 1553–1577, 2000. View at: Google Scholar
  18. A. Bernat, N. Avvakumov, J. S. Mymryk, and L. Banks, “Interaction between the HPV E7 oncoprotein and the transcriptional coactivator p300,” Oncogene, vol. 22, no. 39, pp. 7871–7881, 2003. View at: Publisher Site | Google Scholar
  19. J. M. Wojciak, M. A. Martinez-Yamout, H. J. Dyson, and P. E. Wright, “Structural basis for recruitment of CBP/p300 coactivators by STAT1 and STAT2 transactivation domains,” The EMBO Journal, vol. 28, no. 7, pp. 948–958, 2009. View at: Publisher Site | Google Scholar
  20. M. Le Gallo, A. J. O'Hara, M. L. Rudd et al., “Exome sequencing of serous endometrial tumors identifies recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes,” Nature Genetics, vol. 44, pp. 1310–1315, 2012. View at: Google Scholar
  21. M. Peifer, L. Fernandez-Cuesta, M. L. Sos et al., “Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer,” Nature Genetics, vol. 44, pp. 1104–1110, 2012. View at: Google Scholar
  22. J. Zhang, L. Ding, L. Holmfeldt et al., “The genetic basis of early T-cell precursor acute lymphoblastic leukaemia,” Nature, vol. 481, pp. 157–163, 2012. View at: Google Scholar
  23. C. L. Andersen., H. Hasselbalch, and K. Gronbaek, “Lack of somatic mutations in the catalytic domains of CREBBP and EP300 genes implies a role for histone deacetylase inhibition in myeloproliferative neoplasms,” Leukemia Research, vol. 36, pp. 485–487, 2012. View at: Google Scholar
  24. Z. J. Liu, X. Lu, and S. Zhong, “ASPP—apoptotic specific regulator of p53,” Biochimica et Biophysica Acta, vol. 1756, no. 1, pp. 77–80, 2005. View at: Publisher Site | Google Scholar
  25. Y. Samuels-Lev, D. J. O'Connor, D. Bergamaschi et al., “ASPP proteins specifically stimulate the apoptotic function of p53,” Molecular Cell, vol. 8, no. 4, pp. 781–794, 2001. View at: Publisher Site | Google Scholar
  26. Z. J. Liu, Y. Zhang, X. B. Zhang, and X. Yang, “Abnormal mRNA expression of ASPP members in leukemia cell lines,” Leukemia, vol. 18, no. 4, p. 880, 2004. View at: Publisher Site | Google Scholar
  27. N. Bhattacharyya and M. P. Fried, “Nodal metastasis in major salivary gland cancer: predictive factors and effects on survival,” Archives of Otolaryngology, vol. 128, no. 8, pp. 904–908, 2002. View at: Google Scholar
  28. N. Agrawal, M. J. Frederick, C. R. Pickering et al., “Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1,” Science, vol. 333, pp. 1154–1157, 2011. View at: Google Scholar
  29. N. Stransky, A. M. Egloff, A. D. Tward et al., “The mutational landscape of head and neck squamous cell carcinoma,” Science, vol. 333, pp. 1157–1160, 2011. View at: Google Scholar
  30. G. Bollag, J. Tsai, J. Zhang et al., “Vemurafenib: the first drug approved for BRAF-mutant cancer,” Nature Reviews Drug Discovery, vol. 11, pp. 873–886, 2012. View at: Google Scholar
  31. J. Barretina, G. Caponigro, N. Stransky et al., “The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity,” Nature, vol. 483, pp. 603–607, 2012. View at: Google Scholar
  32. H. V. Diyabalanage, M. L. Granda, and J. M. Hooker, “Combination therapy: histone deacetylase inhibitors and platinum-based chemotherapeutics for cancer,” Cancer Letters, vol. 329, no. 1, pp. 1–8, 2012. View at: Publisher Site | Google Scholar
  33. “Comprehensive molecular characterization of human colon and rectal cancer,” Nature, vol. 487, pp. 330–337, 2012. View at: Publisher Site | Google Scholar
  34. “Comprehensive molecular portraits of human breast tumours,” Nature, vol. 490, pp. 61–70, 2012. View at: Publisher Site | Google Scholar

Copyright © 2013 Anthony C. Nichols et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.