Prognostic biomarkers of human papilloma virus (HPV)-positive neoplasia of the upper aerodigestive tract: a systematic review
Systematic Review

Prognostic biomarkers of human papilloma virus (HPV)-positive neoplasia of the upper aerodigestive tract: a systematic review

Peta-Lee Sacks1, Raquel Alvarado1, Raymond Sacks1,2,3,4, Richard Gallagher5,6, Richard Harvey1,2,5

1Rhinology and Skull Base Research Group, Applied Medical Research Centre, University of New South Wales, Sydney, Australia; 2Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia; 3The University of Sydney Medical School, University of Sydney, Sydney, Australia; 4Concord General Hospital, Sydney, Australia; 5Department of Otolaryngology/Skull Base Surgery, St. Vincent’s Hospital, Sydney, Australia; 6University of Notre Dame, NSW, Australia

Contributions: (I) Conception and design: All authors; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Peta-Lee Sacks, MD. Rhinology Research Group, Applied Medical Research Centre, 405 Liverpool St, Darlinghurst, 2010, NSW, Australia. Email: petasacks@gmail.com.

Background: HPV-positivity in oropharyngeal cancer represents a distinct biological entity in terms of underlying genetics and clinical behaviour. Next-generation sequencing has enabled researchers to identify biomarkers associated with neoplasia that may aid in predicting tumour behaviour and offer potential treatment targets. This systematic review aims to evaluate the current known prognostic biomarkers of human papilloma virus (HPV)-positive upper aerodigestive tract (UADT) neoplasia.

Methods: Data sources include Embase (1947–2015), Medline (1946–2015), Cochrane Central Register of Controlled Trials, Cochrane ENT Disorders Group Trials Register and mRCT. The above sources were searched on 19th December 2015 using a comprehensive strategy for studies evaluating clinical outcomes of known prognostic biomarkers of HPV-positive UADT. Articles were limited to English language and human subjects. All studies that provided original data on the clinical implications of biomarkers in HPV-positive neoplasia were included. Outcomes relating to malignant conversion, recurrence, regional and metastatic spread as well as response to treatment were evaluated.

Results: The search returned 4,702 records with thirty-one case series included in the final qualitative synthesis. These encompassed studies evaluating overall survival (n=21), disease-specific survival (n=10), recurrence (n=23), response to treatment (n=2) and risk of metastasis (n=2) with some studies evaluating more than one outcome. Overexpression of p53 and EGFR were not found to be reliable indicators of prognosis with studies demonstrating mixed results.

Conclusions: It is well established that HPV-positivity correlates with improved prognosis in most UADT squamous cell carcinoma (SCC). However, there are no reliable biomarkers that can predict which tumours may fall into the more aggressive subset in this group.

Keywords: Squamous cell carcinoma (SCC); human papilloma virus (HPV); biomarker; oncogene; tumour suppressor gene

Received: 23 February 2018; Accepted: 23 May 2018; Published online: 01 June 2018.

doi: 10.21037/ajo.2018.05.03

Introduction

Head and neck malignancy is the sixth most common cancer globally with an incidence of half a million cases per year (1). More than 90% of these are squamous cell carcinoma (SCC), a genetically heterogenous neoplasm (2). Head and neck SCC is primarily associated with alcohol and tobacco consumption however human papilloma virus (HPV) infection is becoming increasingly common as a predisposing factor. HPV is thought to promote malignant transformation by surpassing cell cycle checkpoints and thus causing genomic instability. Inverted papilloma (IP) is a locally aggressive, benign sinonasal neoplasm, notable for its tendency for local recurrence and potential for malignant transformation. The incidence of malignant transformation varies in the literature but is largely regarded to be between 5% and 15% (3). Whilst HPV has been implicated in the pathogenesis of IP and its malignant transformation to SCC, studies have not consistently demonstrated a true connection between the virus and IP (4-6). The relationship between HPV and recurrence or malignant transformation of benign IP remains controversial.

In oropharyngeal SCC, HPV positivity represents a distinct biological entity, both in terms of its underlying genetics and clinical behaviour. Next generation sequencing has enabled researchers to begin identifying biomarkers associated with HPV-positive and negative SCC, which can aid in predicting tumour behaviour as well as offering potential targets for treatment in the future. HPV positive tumours have already been demonstrated to have lower mutation rates than their HPV-negative counterparts and mutated genes rarely overlap between these two groups (7,8).

P16, a cyclin dependent kinase inhibitor, is frequently underexpressed in HPV-negative oropharyngeal SCC and overexpressed in HPV positive tumours. Thus, P16 is utilized as a first-line test for determination of HPV status as well as serves as an independent prognostic tool (9,10).

Currently, the gold standard of care of HPV positive cancers involves either surgery with adjuvant radiotherapy +/− chemotherapy or definitive concurrent chemoradiotherapy (11,12). HPV positive oropharyngeal SCC is associated with an improved prognosis and better response to treatment. This finding has been replicated in sinonasal malignancy (13) but remains to be proven in other subsites. Despite this association, a small subset of HPV-positive patients have been demonstrated to have less favourable outcomes. Whilst tobacco smoking has been implicated as a risk factor for poorer outcomes (14,15), few other poor prognostic factors in HPV-positive SCC have been described in the literature. Approximately 10% of HPV positive patients are at high risk of developing distant metastasis and whilst this rate is similar to that of HPV-negative tumours, metastasis in HPV positive cancers tend to occur later and be more disseminated (16-18). This study aims to systematically review the literature and assess the evidence for known biomarkers in HPV positive neoplasia of the upper aerodigestive tract (UADT), that may aid in predicting which patients may go on to have poorer outcomes or respond poorly to treatment.

Methods

A systematic review was performed to evaluate the literature regarding prognostic biomarkers in HPV positive neoplasia of the UADT. The methods of this review were in keeping with PRISMA guidelines (19) and/or the Cochrane Handbook for Systematic Reviews of Interventions where applicable (20).

Eligibility criteria

Studies containing original data pertaining prognostic outcomes of any biomarkers in HPV positive neoplasia of the UADT were considered for inclusion in this study. HPV-positive status was defined by polymerase chain reaction (PCR), in situ hybridization (ISH) or P16 immunohistochemistry (IHC). No age or comorbidity restrictions were applied. Studies assessing biomarkers in both HPV-positive and negative neoplasia were included only if they reported extractable data pertaining specifically to HPV-positive tumours. Case series, case-control studies, crossover studies, cohort studies and randomized controlled trials (RCTs) were included. Only manuscripts published in English were eligible; reviews, guidelines, letters, and editorials with no original data were excluded, as were case reports, conference abstracts, in vitro and animal studies.

Information sources

A systematic electronic search was performed until December 19th 2015 on the Embase (1974–2015), Medline (1946–2015) databases as well as Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, current issue), Cochrane Ear, Nose and Throat Disorders Group Trials Register and mRCT (metaRegister of Controlled Trials including www.ClinicalTrials.gov). Reference lists of identified publications were scanned for additional studies.

Search methods

A search strategy was designed for each database (Table 1) to identify all studies evaluating prognostic biomarkers of HPV-positive neoplasia of the UADT.

Table 1

Search strategy

Papilloma
   [1] exp Papilloma, inverted
   [2] exp Papilloma
   [3] (epithelial papilloma OR schneiderian papilloma OR papillary sinusitis OR soft papilloma OR transitional cell papilloma OR inverting papilloma OR inverted papilloma).mp
   [4] [1] OR [2] OR [3]
SCC
   [5] exp Carcinoma, squamous cell
   [6] (dysplasia OR metaplasia OR atypia OR carcinoma in situ)
   [7] (cancer* or carcinoma* or neoplas* or tumor* or tumour* or malignan* or SCC*).mp
   [8] [5] OR [6] OR [7]
Nasal cavity
   [9] exp Nose
   [10] exp Nasal cavity
   [11] exp nasal mucosa
   [12] exp paranasal sinuses
   [13] exp paranasal sinus diseases
   [14] exp nasopharynx
   [15] (nose OR nasal$ OR sinus$ OR rhinosinus$ OR paranasal$ OR rhiniti$ OR nasosinus$ OR pansinus$).mp
   [16] [9] OR [10] OR [11] OR [12] OR [13] OR [14] OR [15]
Oral cavity and oropharynx
   [17] exp Mouth
   [18] exp Lip
   [19] exp Tongue
   [20] exp Mouth mucosa
   [21] exp Salivary glands
   [22] (oral$ or intra-oral$ or intraoral$ or “intra oral$” or gingiva$ or oropharyn$ or mouth$ or tongue$ or cheek$ or gum$ or palatal$ or palate$ or “head and neck”).mp.
   [23] [17] OR [18] OR [19] OR [20] OR [21] OR [22]
HPV
   [24] exp tumor virus
   [25] exp papillomavirus infections
   [26] (hpv* or papillomavir* or (papilloma* and vir*) OR human papilloma virus).mp.
   [27] [24] OR [25] OR [26]
[43] [4] OR [8]
[44] [16] OR [23]
[37] [43] AND [44] AND [27]

SCC, squamous cell carcinoma; HPV, human papilloma virus.

Study selection

One author (PL Sacks) reviewed and selected trials found in the searches and evaluated them against the inclusion criteria. In cases where PL Sacks was unsure as to whether the trial was relevant, a second review author (R Harvey) was consulted. Initial screening was upon title review, with brief abstract review if there was uncertainty. The remaining selection underwent stringent abstract review, with discussion between reviewers if uncertain about relevance of individual studies. The full texts of the subsequent selection were analyzed, with study exclusion if not relevant.

Data extraction

A structured data collection form was used for data extraction. The data extraction sheet was pilot-tested on ten randomly-selected included studies and refined accordingly. One review author (PL Sacks) extracted the following data from included studies and a second author (R Harvey) was consulted if any uncertainty arose:

  • Study characteristics including study design, inclusion and exclusion criteria, total number of patients, total number of HPV-positive patients, HPV detection method, primary intervention, outcomes assessed, biomarkers assessed and length of follow-up;
  • Population demographics including age, gender, smoking and alcohol status, diagnosis, stage at diagnosis;
  • Outcomes including percentage of biomarker expressed in population, overall survival, disease-specific survival, recurrence, response to treatment and distant metastasis.

Summary measures

Proportions of individual biomarker expression were calculated manually. Hazard ratios and 95% confidence intervals for each prognostic outcome were extracted from manuscripts when available.

A qualitative synthesis was performed where a thematic organisation was created based on endpoint of each study. Outcomes assessed included treatment effects, severity effects and overall mortality.

Results

Search results

The search strategy found 4,702 records. This was reduced to 3,327 after the removal of duplicates. Title and abstract review excluded a further 3,100 articles, leaving 227 full text articles to be assessed for eligibility. There were 31 studies included in the final qualitative synthesis (Figure 1). All 31 articles were case series and all investigated malignant disease of the UADT. Twenty-four articles looked exclusively at oropharyngeal or oral SCC. Characteristics of included studies are described in Table 2.

Figure 1 PRISMA flow diagram illustrating selection process.

Table 2

Characteristics of included studies

Author Year Study design Diagnosis Primary intervention Total no. patients (n) No. HPV+ patients (n) HPV diagnosis method Age (mean/median) (years) Gender (% female) % smokers Biomarker(s) assessed
Qian et al. (21) 2015 Case series OPSCC NR 96 68 NR 57 17.7% 80.2% Heregulin, HER3
Zhang et al. (22) 2015 Case series OPSCC NR 1,008 233 PCR or ISH 55.8 13.5% 75.5% SNP in promoter region of FAS and FASLG
Balermpas et al. (23) 2014 Case series All HNSCC Radiotherapy 106 42 P16 IHC 60.6 20.7% 55% CD68+, CD163+, CD11B+
Kim et al. (24) 2014 Case series OPSCC Chemotherapy 74 21 PCR 70 7% NR P53, beta-tubulin, BCL2, ERCC1
Ko et al. (25) 2014 Case series Oral and OPSCC Surgery 167 36 ISH 56 18.6% 65.5% miR21
Liu et al. (26) 2014 Case series OPSCC Surgery and Radiotherapy 105 48 PCR/P16 IHC 58.5 20% 75.2% Ki67
Ryu et al. (27) 2014 Case series Tonsillar SCC Surgery 42 30 PCR 58 9.5% 64.3% Cyclin D1, pRB, p53
Tertipis et al. (28) 2014 Case series Tongue SCC Radiotherapy 278 207 Multiplex assay 60 24.6% 64.7% LMP10
Vainshtein et al. (29) 2014 Case series Stage III or IV OPSCC Radiotherapy 198 184 PCR or ISH 55 10.9% 56.6% EGFR
Zhang et al. (30) 2014 Case series OPSCC NR 846 158 PCR or ISH 55.6 13.1% 62.7% TNF-alpha
Bauman et al. (31) 2013 Case series Stage III–IV HNSCC Chemo-radiotherapy 90 56 P16 IHC NR 12% 77% ERCC1
Chandarana et al. (32) 2013 Case series OP and oral SCC Radiotherapy 85 26 P16 IHC 57.2 (oral), 52.3 (OP) 74.1% 88.2% EGFR
Chiosea et al. (33) 2013 Case series HPV+ OPSCC Chemo-radiotherapy 75 75 ISH 56 14.7% 53.3% PIK3CA
Kaka et al. (34) 2013 Case series HPV+ OPSCC Chemo-radiotherapy 15 15 P16 IHC/CISH 59 14% 57% P53, NOTCH
Scantlebury et al. (35) 2013 Case series OPSCC Surgery 202 150 RNA ISH/P16 IHC 56.8 11.9% 70.8% Cyclin D1
Song et al. (36) 2013 Case series OPSCC NR 658 102 PCR 55.3 14.4% 63.4% SNP in nucleotide excision repair pathway
Badoual et al. (37) 2012 Case series All HN SCC NR 64 32 INNO-LiPA genotyping
extra assay		 NR 34% NR PD-1-positive cells, CD8+, CD4+
Gubanova et al. (38) 2012 Case series OPSCC NR 40 20 PCR 58.2 20% 47.5% SMG1, ATM, ATR
Husain et al. (39) 2012 Case series All HNSCC NR 101 29 P16 IHC NR 18.4% 80.7% EGFR
Lim et al. (40) 2012 Case series All HNSCC Radiotherapy 87 28 P16 IHC 56.6 13.7% NR ATM
Park et al. (41) 2012 Case series OPSCC Surgery 86 46 PCR 62.1 16.3% 69.8% pRB, cyclin D1, CDK4, p21
Hao et al. (42) 2011 Case series SCC neck node unknown primary Chemo-radiotherapy 55 30 CISH and PCR 54.8 16.4% 76.4% ERCC1
Moeller et al. (43) 2011 Case series All HNSCC Radiotherapy 89 36 PCR 60 18% 64% Ku80
Al-Swiahb et al. (9) 2010 Case series OPSCC Surgery 220 33 PCR 51.3 42% 79% P53, EGFR
Hong et al. (44) 2010 Case series OPSCC NR 270 99 PCR/P16 IHC 59.8 21% NR EGFR
Nichols et al. (45) 2010 Case series OPSCC Chemo-radiotherapy 68 53 ISH NR 14.7% 51.5% Bcl2
Chung et al. (46) 2009 Case series Stage IV tonsillar SCC Chemo-radiotherapy 46 23 PCR 53 13% <50% P53, pRB, p21
Fallai et al. (47) 2009 Case series OPSCC Chemo-radiotherapy 78 9 PCR 56.4 92% NR P53
Fei et al. (48) 2009 Case series Tonsillar SCC NR 85 42 PCR or P16 IHC 59 18.8% NR VEGF, EGFR
Klussmann et al. (49) 2009 Case series OPSCC Radiotherapy 60 28 PCR/P16 IHC 60 22% 80% 11q13 amplification, 16q loss, 9p loss
Kumar et al. (50) 2008 Case series Stage III and IV OPSCC Chemotherapy 42 25 PCR 62 24% 78% EGFR, P53, BCL-xL

OPSCC, oropharyngeal squamous cell carcinoma; HNSCC, head and neck squamous cell carcinoma; NR, not reported; HPV, human papilloma virus; PCR, polymerase chain reaction; ISH, in situ hybridization; IHC, immunohistochemistry; P16, protein 16 (inhibitor of cyclin dependent kinases); CISH, chromogenic in situ hybridization; RNA, ribonucleic acid; INNO-LiPA, innogenetics; HER3, human epidermal growth factor receptor 3; SNP, single nucleotide polymorphism; FAS, Fas cell surface death receptor; FASLG, FAS ligand; CD, cluster of differentiation; P53, protein 53; BCL2, B-cell lymphoma 2; ERCC1, excision repair cross-complementation group 1; miR21, microRNA-21; Ki67, marker of proliferation Ki-67; pRB, retinoblastoma protein; LMP10, low molecular weight protein 10; EGFR, epidermal growth factor receptor; TNF-alpha, tumour necrosis factor alpha; PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha; PD-1, programmed cell death protein 1; SMG1, suppressor with morphogenetic effect on genitalia; ATM, ataxia telangiectasia mutated; ATR, ataxia telangiectasia and Rad3 related; p21, protein 21; CDK4, cyclin dependent kinase 4; VEGF, vascular endothelial growth factor; BCL-xL, B-cell lymphoma-extra large.

Qualitative synthesis and thematic organisation

Study outcomes were organised into broad thematic groups. These included 21 studies evaluating overall survival, ten studies evaluating disease specific survival, 23 studies evaluating recurrence, two studies evaluating response to treatment and two studies evaluating risk of metastasis with some studies evaluating more than one outcome

Overall survival

There were 21 studies evaluating overall survival with a total number of 25 biomarkers investigated. There were five studies evaluating epidermal growth factor receptor (EGFR) with a total of 254 patients. Two studies (9,50) found that overexpression of EGFR was associated with worse overall survival whilst three studies (39,44,51) demonstrated no correlation amongst HPV-positive patients. There were four studies evaluating p53 with a total of 107 patients. Amongst HPV-positive patients, two studies (9,24) found that overexpression of p53 correlated with worse overall survival whilst two studies (27,46) found no correlation. Two studies (43,48) evaluated VEGF with a total of 78 patients and both found overexpression of VEGF to be associated with worse overall survival. Two studies (27,46) evaluated pRb with a total of 53 patients and both found no correlation with overall survival. Correlations of other biomarkers evaluated in less than two studies can be found in Table 3.

Table 3

Biomarkers predicting overall survival (OS)

Biomarker Studies (n) Patients (n) % of tumours expressing biomarker Summary
EGFR 5 254 50% 2 studies—low expression EGFR associated with high OS: P=0.01, no HR reported (Al-Swiahb et al., 2010); P=0.03, no HR reported (Kumar et al., 2008)
3 studies—no correlation with overall survival: P=0.4, no HR reported (Husain et al., 2012); P=0.22, HR 1.86 (95% CI, 0.68–5.13) (Qian et al., 2015); P=0.29, HR 1.42 (95% CI, 0.39–5.19) (Hong et al., 2010)
p53 4 107 14% 2 studies—low expression p53 associated with high OS: P≤0.01, no HR reported (Al-Swiahb et al., 2010); P=0.01, no HR reported (Kim et al., 2014)
2 studies—no correlation with overall survival: P=0.48, no HR reported (Chung et al., 2009); P=0.43, HR 0.43 (95% CI 0.13-1.45) (Ryu et al., 2014)
VEGF 2 78 59.50% 2 studies—high VEGF correlated with worse OS: P=0.06, HR 2.94 (95% CI, 0.94–12.91) (Fei et al., 2009); P=0.04, no HR reported (Moeller et al., 2011)
pRB 2 53 11.30% 2 studies—no correlation with OS: P=0.21, no HR reported (Chung et al., 2009); P=0.272, HR 0.47 (95% CI, 0.12–1.80)] (Ryu et al., 2014)
p21 1 23 78% 1 study—no correlation with OS: P=0.66, no HR reported (Chung et al., 2009)
Cyclin D1 1 150 3.70% 1 study—intensity of expression associated with better OS: P=0.038, no HR reported (Scantlebury et al., 2013)
ERCC1 1 30 50% 1 study—no correlation with OS: P=0.58, HR 1.5 (95% CI, 0.3–6.8) (Hao et al., 2012)
PD-1+ve cells 1 32 59% 1 study—high numbers of PD-1+ T cells correlated with better OS: P=0.025, HR 0.13 (95% CI, 0.02–0.067) (Badoual et al., 2013)
CD8+ 1 32 53% 1 study—no correlation with better OS: P=0.6, HR 0.7 (95% CI, 0.14–3.6) (Badoual et al., 2013)
CD4+ 1 32 68.70% 1 study—no correlation with OS: P=0.7, HR 1.36 (95% CI, 0.22–8.6) (Badoual et al., 2013)
CD163+ 1 42 42.90% 1 study—no correlation with OS: P=0.112, no HR reported (Balermpas et al., 2014)
CD11B+ 1 42 53.60% 1 study—no correlation with OS: P=0.394, no HR reported (Balermpas et al., 2014)
SMG1 1 20 15% High SMG1 expression correlated with poor OS: no P value nor HR (Gubanova et al., 2012)
Beta tubulin 1 21 4.70% Class III beta tubulin correlated with better OS: P=0.012, no HR reported (Kim et al., 2014)
11q13 amp 1 28 7.10% 1 study—11q13 amp associated with worse OS: P=0.02, no HR reported (Klussman et al., 2009)
16q loss 1 28 28.60% 1 study—16q loss associated with improved OS: P=0.01, no HR reported (Klussman et al., 2009)
9p loss 1 28 10.70% 1 study—9p loss associated with worse OS: P<0.0015, no HR reported (Klussman et al., 2009)
Ku80 1 36 NR 1 study—no correlation with OS (data not reported) (Moeller et al., 2011)
CDK4 1 46 43.50% 1 study—high CDK4 associated with worse OS: P=0.011, HR 2.91 (95% CI, 2.25–3.38) (Park et al., 2012)
Heregulin 1 57 47.40% 1 study—high heregulin correlated with worse OS: P=0.049, HR 3.30 (95% CI, 0.94–11.57) (Qian et al., 2015)
HER3 1 67 49.30% 1 study—no correlation with OS: P=0.94, HR 0.82 (95% CI, 0.31–2.22) (Qian et al., 2015)
HER2 1 68 50% 1 study—no correlation with OS: P=0.85, HR 1.10 (95% CI, 0.41–2.91) (Qian et al., 2015)
LMP10 1 207 44.44% nuclear 1 study—nuclear [P=0.162, HR 1.673 (95% CI, 0.813–3.445)] nor cytoplasmic [P=0.164, HR 0.590 (95% CI, 0.281–1.240)] expression not correlated with OS (Tertipis et al., 2014)
47.83% cytoplasm
Bcl2 1 53 39.60% 1 study—high Bcl2 correlated with worse OS: P=0.0064, HR 6.9 (95% CI, 1.7–27)
(Nichols et al., 2010)
Ki67 1 48 54.10% 1 study—no correlation with OS: P=0.144, HR 0.21 (95% CI, 0.08–0.56) (Liu et al., 2014)

EGFR, epidermal growth factor receptor; p53, protein 53; VEGF, vascular endothelial growth factor; pRB, retinoblastoma protein; p21, protein 21; ERCC1, excision repair cross-complementation group 1; PD-1, programmed cell death protein 1; CD, cluster of differentiation; SMG1, suppressor with morphogenetic effect on genitalia; CDK4, cyclin dependent kinase 4; HER3, human epidermal growth factor receptor 3; LMP10, low molecular weight protein 10; BCL2, B-cell lymphoma 2; Ki67, marker of proliferation Ki-67; HR, hazard ratio; CI, confidence interval.

Disease specific survival

There were ten studies evaluating disease specific survival with a total number of eight biomarkers investigated. EGFR was evaluated in three studies, including a total of 93 patients and correlated with worse disease specific survival in all three studies (32,48,50). Correlations of other biomarkers evaluated in less than two studies can be found in Table 4.

Table 4

Biomarkers predicting disease specific survival (DSS)

Biomarker Studies (n) Patients (n) % expressed Summary
EGFR 3 93 50.5% 3 studies—EGFR correlated with worse DSS: P=0.04, no HR reported (Kumar et al., 2008); P=0.04, no HR reported (Fei et al., 2009); P=0.01, no HR reported (Chandarana et al., 2013)
p53 1 35 5% 1 study—no correlation with DSS: P=0.272, no HR reported (Kim et al., 2014)
ERCC1 1 30 50% 1 study—no correlation with DSS: P=0.85, HR 1.2 (95% CI, 0.2–8.5) (Hao et al., 2011)
MiR21 1 36 28% 1 study—no correlation with DSS: P=0.486, no HR reported (Ko et al.,2014)
PIK3CA mutation 1 75 31% 1 study—no correlation with DSS: P=0.8, no HR reported (Chiosea et al., 2013)
CDK4 1 46 43% 1 study—high CDK4 associated with worse DSM: P=0.007, HR 2.91 (95% CI, 2.25–3.38) (Park et al., 2012)
Cyclin D1 1 150 58.8% 1 study—intensity of expression associated with worse DSS: P=0.015, no HR reported (Scantlebury et al., 2013)
Ki67 1 48 56% 1 study—no correlation with OS: P=0.137, HR 0.23 (95% CI, 0.08–0.68) (Liu et al., 2014)

EGFR, epidermal growth factor receptor; p53, protein 53; ERCC1, excision repair cross-complementation group 1; PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha; CDK4, cyclin dependent kinase 4; Ki67, marker of proliferation Ki-67; HR, hazard ratio; CI, confidence interval.

Locoregional recurrence

There were 23 studies evaluating rates of locoregional recurrence with 37 biomarkers investigated. There were four studies evaluating EGFR with a total of 354 patients. One study (48) found that overexpression of EGFR was associated with increased rates of recurrence whilst three studies (29,39,44) demonstrated no correlation amongst HPV-positive patients. There were four studies evaluating p53 with a total of 98 patients. Amongst HPV-positive patients, two studies (27,47) found that overexpression of p53 correlated with increased recurrence rates whilst two studies (43,46) found no correlation. Three studies evaluated ERCC1 with a total of 186 patients. Two studies (36,42) demonstrated no correlation between ERCC1 levels and recurrence. However, one study (31) demonstrated increased recurrence rates with higher expression of ERCC1. Two studies evaluated pRb with a total of 53 patients. One study (27) demonstrated increased recurrence rates with overexpression in pRb whereas one study (46) found no correlation. Two studies evaluated loss of ataxia telangiectasia mutated (ATM) with a total of 64 patients. One study (43) found that ATM loss correlated with increased recurrence rate whereas one study found no correlation (40). Correlations of other biomarkers evaluated in less than two studies can be found in Table 5.

Table 5

Biomarkers predicting risk of recurrence

Biomarker Studies (n) Patients (n) % expressed Summary
p53 4 98 16.1% 2 studies—high p53 expression correlated with increased risk of recurrence: P=0.046, HR 0.31 (95% CI, 0.10–0.98) (Ryu et al., 2014); P<0.01, no HR reported (Fallai et al., 2009)
2 studies—no correlation with recurrence: P=0.54, no HR reported (Chung et al., 2009); data not reported (Moeller et al., 2011)
EGFR 4 354 46.7% 1 study—high EGFR expression correlated with increased risk of recurrence: P=0.02, no HR reported (Fei et al., 2009)
3 studies—no correlation with recurrence: P=0.97, no HR reported (Husain et al., 2012); P=0.73, HR 3.84 (95% CI, 0.48–30.84) (Hong et al., 2010); P=0.205, HR 1.71 (95% CI, 0.75–3.87) (Vainshtein et al., 2014)
ERCC1 3 186 38.7% 2 studies—no correlation with recurrence: P=0.75, HR 0.7 (95% CI, 0.1–4.5) (Hao et al., 2010); P=0.138, HR 0.4 (95% CI, 0.1–1.3) (Song et al., 2013)
1 study—ERCC1 correlated with increased recurrence rates: ERCC1 (FL297): P=0.04, HR 10.1 (no 95% CI); ERCC1 (4F9): P=0.04, HR 13.7 (no 95% CI) (Bauman et al., 2013)
pRB 2 53 11.3% 1 study—low pRB associated with decreased risk of recurrence: P=0.01, HR 0.08 (95% CI, 0.02–0.35) (Ryu et al., 2014)
1 study—no correlation with recurrence: P=0.54, no HR reported (Chung et al., 2009)
ATM 2 64 10.7% 1 study—no correlation with recurrence (data not reported) (Lim et al., 2012)
1 study—ATM loss correlated with increased recurrence rate: P=0.03, no HR reported (Moeller et al., 2011)
ATR 1 36 NR 1 study–ATR loss correlated with increased risk of recurrence: P=0.03, no HR reported (Moeller et al., 2011)
P21 1 23 78% 1 study—no correlation with recurrence: P=0.43, no HR reported (Chung et al., 2009)
PD-1+ve cells 1 32 59% 1 study—no correlation with recurrence (data not reported) (Badoual et al., 2013)
CD163+ 1 42 42.9% 1 study—no correlation with recurrence: P=0.146, no HR reported (Balermpas et al., 2014)
CD11B+ 1 42 53.6% 1 study—no correlation with recurrence: P=0.418, no HR reported (Balermpas et al., 2014)
Ki67 1 48 56% 1 study—Ki67 positivity inversely associated with recurrence: P=0.015, HR 0.21 (95% CI, 0.08–0.56) (Liu et al., 2014)
Cyclin D1 1 150 58.8% 1 study—intensity of expression correlated with recurrence: P=0.014, no HR reported (Scantlebury et al., 2013)
VEGF 1 42 59% 1 study—no correlation with recurrence: P=0.4, HR 1.43 (95% CI, 0.63–3.53) (Fei et al., 2009)
SMG1 1 20 28% 1 study—low SMG-1 correlated with decreased incidence of recurrence (no P value nor HR) (Gubanova et al., 2012)
16q loss 1 28 29% 1 study—16q loss correlated with decreased rate of recurrence: P=0.008, no HR reported) (Klussmann et al., 2009)
9p loss 1 28 11% 1 study—9p loss correlated with decreased rate of recurrence: P=0.04, no HR reported (Klussmann et al., 2009)
miR21 1 36 28% 1 study—no correlation: P=0.564, no HR reported (Ko et al., 2014)
Ku80 1 36 NR 1 study—no correlation (data not reported) (Moeller et al., 2011)
E-cadherin 1 36 NR 1 study—E-cadherin expression correlated with increased risk of recurrence: P=0.04, no HR reported (Moeller et al., 2011)
Bcl2 1 53 39.6% 1 study—high Bcl2 correlated with higher risk of recurrence: P=0.004, HR 7.6 (95% CI, 1.9–30) (Nichols et al., 2010)
CDK4 1 46 43.5% 1 study—high CDK4 associated with increased recurrence: P=0.009, HR 2.87 (95% CI, 2.51–3.46) (Park et al., 2012)
Heregulin 1 68 47.4% 1 study—no correlation with recurrence: P=0.309, no HR reported (Qian et al., 2015)
XPC rs2228000 1 102 47.1% 1 study—SNP correlated with increased rate of recurrence: P=0.051, HR 1.6 (95% CI, 1.0–4.1) (Song et al., 2013)
XPC rs2228001 1 102 29.4% 1 study—no correlation with recurrence: P=0.523, HR 0.7 (95% CI, 0.3–2.0) (Song et al., 2013)
XPA rs1800975 1 102 51.9% 1 study—no correlation with recurrence: P=0.933, HR 1.0 (95% CI, 0.4–2.4) (Song et al., 2013)
XPD rs1799793 1 102 56.9% 1 study—SNP correlated with increased rate of recurrence: P=0.002, HR 0.2 (95% CI, 0.1–0.5) (Song et al., 2013)
XPD rs13181 1 102 55.9% 1 study—no correlation with recurrence: P=0.100, HR 0.4 (95% CI, 0.2–1.1) (Song et al., 2013)
XPG rs17655 1 102 31.4% 1 study—SNP correlated with increased rate of recurrence: P=0.036, HR 0.1 (95% CI, 0.0–0.9) (Song et al., 2013)
LMP10 1 207 44.4% nucleus; 47.8% cytoplasm 1 study—fraction of nuclear expression correlated with lower incidence of recurrence: P=0.009, HR 2.25 (95% CI, 1.35–7.85); cytoplasm expression did not correlated: P=0.093, HR 2.07 (95% CI, 0.89–4.84) (Tertipis et al., 2014)
TNF alpha-308 (rs1800629) GG 1 158 63% 1 study—GG genotype correlated with increased recurrence: P=0.005, HR 5.1 (95% CI, 1.4–18.4) (Zhang et al., 2014)
TNF alpha-857 (rs1799724) CC 1 158 87% 1 study—no correlation with recurrence: P=0.594, HR 1.4 (95% CI, 0.3–5.9) (Zhang et al., 2014)
TNF alpha-863 (rs1800630) CC 1 158 46.8% 1 study—CC genotype correlated with increased recurrence: P=0.007, HR 3.7 (95% CI, 1.5–9.1) (Zhang et al., 2014)
TNF alpha-1031 (rs1799964) TT 1 158 69.6% 1 study—no correlation with recurrence: P=0.100, HR 0.6 (95% CI, 0.2–1.3) (Zhang et al., 2014)
FAS1377 G>A GA+AA 1 233 8.5% 1 study—no correlation with recurrence: P=0.662, HR 0.8 (95% CI, 0.2–3.3) (Zhang et al., 2015)
FAS670 A>G AA+GG 1 233 46.4% 1 study—AG+GG mutation associated with increased risk of recurrence: P<0.0001, HR 12.9 (95% CI, 3.8–43.6) (Zhang et al., 2015)
FASLG844 C>T CC+TT 1 233 35.2% 1 study—AG+GG mutation associated with increased risk of recurrence: P<0.0001, HR 8.1 (95% CI, 3.6–18.6) (Zhang et al., 2015)
FASLG124 A>G AG+GG 1 233 20.6% 1 study—no correlation with recurrence: P=0.100, HR 1.6 (95% CI, 0.8–3.3) (Zhang et al., 2015)

p53, protein 53; EGFR, epidermal growth factor receptor; ERCC1, excision repair cross-complementation group 1; pRB, retinoblastoma protein; ATM, ataxia telangiectasia mutated; ATR, ataxia telangiectasia and Rad3 related; p21, protein 21; PD-1, programmed cell death protein 1; CD, cluster of differentiation; VEGF, vascular endothelial growth factor; Ki67, marker of proliferation Ki-67; SMG1, suppressor with morphogenetic effect on genitalia; BCL2, B-cell Lymphoma 2; CDK4, cyclin dependent kinase 4; SNP, single nucleotide polymorphism; LMP10, low molecular weight protein 10; TNF-alpha, tumour necrosis factor alpha; FAS, Fas cell surface death receptor; FASLG, FAS ligand; HR, hazard ratio; CI, confidence interval.

Response to treatment

There were two studies evaluating response to treatment with one biomarker investigated in each study. ERCC1 correlated with better response to treatment (31) and SMG-1 negative tumours correlated with higher radiation sensitivity (38) (Table 6).

Table 6

Biomarkers predicting response to treatment

Biomarker Studies (n) Patients (n) % expressed Summary
ERCC1 1 56 35.7% 1 study—ERCC1 (fl297): P=0.041; ERCC1 (4f9): P=0.016, correlated with better complete response (no HR reported) (Bauman et al., 2013)
SMG1 1 20 28% 1 study—SMG1 negative tumours correlated with higher radiation sensitivity (no data values reported) (Gubanova et al., 2012)

ERCC1, excision repair cross-complementation group 1; SMG1, suppressor with morphogenetic effect on genitalia; HR, hazard ratio; CI, confidence interval.

Distant metastasis

There were two studies evaluating rates of distant metastasis with four biomarkers investigated in total. Only NOTCH was found to be lower in patients developing distant metastasis (34) with p53, CD163 and CD11b showing no correlation (23,34) (Table 7).

Table 7

Biomarkers predicting risk of distant metastasis

Biomarker Studies (n) Patients (n) % expressed Summary
p53 1 15 NR 1 study—no correlation with metastasis: P=0.5, no HR reported (Kaka et al., 2013)
NOTCH 1 15 NR 1 study—NOTCH lower in patients developing metastasis: P=0.04, no HR reported (Kaka et al., 2013)
CD163 1 42 42.9% 1 study—no correlation with development of DM: P=0.140, no HR reported (Balermpas et al., 2014)
CD11b 1 42 53.6% 1 study—no correlation with development of DM: P=0.417, no HR reported (Balermpas et al., 2014)

p53, protein 53; CD, cluster of differentiation; HR, hazard ratio; CI, confidence interval; NR, not reported.

Discussion

It is well described that particularly in the oropharyngeal literature, HPV-positive neoplasia represents a distinct clinical and biological entity from that of HPV-negative neoplasia. When functioning properly, p53 responds to cellular injury resulting in cell cycle arrest, attempted DNA repair, and, if DNA repair is ineffective, apoptosis. Mutations in p53 have been well established in HPV-negative SCC with prevalence in the literature to be between 47–100% (7,8,52). In this study, mutated p53 was prevalent in only 14% of HPV-positive cases. Overexpression of p53 was not found to be a reliable indicator of prognosis in this review with studies demonstrating mixed results. This contrasts with that of HPV-negative neoplasia in the literature in which p53 mutation has been demonstrated to be a poor prognostic indicator (53,54). EGFR activation induces cellular proliferation and prevents apoptosis. In the current review, EGFR overexpression showed 50% prevalence amongst HPV-positive patients, compared to more than 90% of HPV-negative or undifferentiated patients in the literature (55,56). Studies evaluating the prognostic value of EGFR showed mixed results in HPV-positive neoplasia, again contrasting the undifferentiated literature (55,56). Whilst there are a vast array of studies appraising prognostic biomarkers in UADT neoplasia, few studies differentiated between HPV-positive and negative tumours despite these essentially representing distinct pathologies. In this review, there were no biomarkers that reliably demonstrated prognostic value in HPV-positive tumours specifically in multiple studies.

All thirty-one included studies evaluated SCC of the UADT. There were no studies that met the inclusion criteria that evaluated prognostic biomarkers in HPV-positive benign neoplasia such as IP. Laryngeal papillomatosis is a relapsing remitting growth of the upper respiratory tract and is a benign manifestation of HPV. Recent studies have documented a high prevalence (20–50%) of laryngeal dysplasia in patients who have had a diagnosis of laryngeal papillomatosis (57-59). Whilst HPV has been implicated in the pathogenesis of IP and its malignant transformation to SCC, studies have not consistently demonstrated a true connection between the virus and IP nor whether or not HPV-positive IP behaves like HPV-positive malignant neoplasia, representing less aggressive disease (4-6).

Limitations in this analysis of the literature included the heterogeneity of the included studies such as differing primary modes of treatment, different population severity and variable follow-up periods. This restricts comparison of the studies and increases risk of confounding. Whilst there were many different biomarkers assessed in the various studies, few of these had more than one study to compare results. Meta-analysis was not considered appropriate due to the heterogeneity of populations, treatments and disease. Exclusion of studies that did not specifically examine HPV-positive neoplasia as distinct from HPV-negative neoplasia may have limited results, as the majority of studies identified in the search did not differentiate between these groups in their analysis.

Conclusions

It is well established that HPV-positivity correlates with improved prognosis in oropharyngeal SCC. However, there are no reliable biomarkers that can predict which tumours may fall into the more aggressive subset in this group. Further research is required to establish reliable prognostic biomarkers of HPV-positive SCC of the UADT. Furthermore, the influence of HPV on the behavioral or oncogenic influence in benign papilloma has yet to be fully defined.

Acknowledgments

Funding: None.

Footnote

Conflicts of Interest: RH serves as the unpaid Editor-in-Chief of Australian Journal of Otolaryngology. R Sacks: Medtronic and Nycomed, consultant; Merck Sharp & Dohme and Arthrocare, speakers’ bureau. R Harvey: Medtronic, Olympus, and NeilMed Pharmaceuticals, consultant, with research grant funding received from Meda Pharmaceuticals and Stallergenes; GlaxoSmithKline and Arthrocare, speakers’ bureau. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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doi: 10.21037/ajo.2018.05.03
Cite this article as: Sacks PL, Alvarado R, Sacks R, Gallagher R, Harvey R. Prognostic biomarkers of human papilloma virus (HPV)-positive neoplasia of the upper aerodigestive tract: a systematic review. Aust J Otolaryngol 2018;1:14.

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