Dataset Information

Prognostic impact of additional HPV diagnostics in 102 patients with p16-stratified advanced oropharyngeal squamous cell carcinoma.

ABSTRACT:

Purpose

p16 overexpression was considered as surrogate marker to identify human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCCs).

Methods

102 patients with advanced stage OPSCCs treated primarily by transoral lasermicrosurgery were included. Prognostic associations of p16- and HPV-status were analyzed separately and combined.

Results

In contrast to p16, the HPV-status resulted in no significant survival discrepancies (5-year overall survival (OS) HPV-positive 64.9%, HPV-negative 78.7%). Combining both markers, p16-positive (p16-positive/HPV-positive, p16-positive/HPV-negative) and p16-negative/HPV-negative groups demonstrated comparable high survival (OS 78.1% vs. 85.6% vs. 73.6%). Lowest survival was observed for patients with p16-negative/HPV-positive OPSCCs (OS 40.8%). Never smoking patients with p16-positive OPSCCs demonstrated the highest survival, whereas within former/current smokers with p16-positive and p16-negative disease it was comparable low (OS 90.0% vs. 63.0% vs. 57.4%).

Conclusions

p16- and HPV-status should not be considered as equivalent markers for a better prognosis. Furthermore, they should not generally predominate patient associated factors like smoking.

SUBMITTER: Weiss BG

PROVIDER: S-EPMC8131341 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Importance:Clinical trials that deintensify treatment for patients with suspected human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) use p16 expression to identify HPV-mediated tumors and guide treatment. While p16 staining has a strong correlation with good outcomes, approximately 12% of p16-positive patients have recurrent disease. Biomarkers that reveal tumor-specific characteristics, such as nodal involvement, may change therapy decisions. Objective:To assess whether if a tumor-specific genetic signature exists for node-negative vs node-positive HPV 16-positive/p16-positive OPSCCs. Design, Setting, and Participants:This was a retrospective cohort study with randomized case selection for p16 OPSCCs undertaken at a university-based, tertiary care cancer center. Samples were collected from patients with p16-positive OPSCC. A total of 21 HPV 16/p16-positive tumors were used in this study. Main Outcomes and Measures:Gene expression profiles of node-negative vs node-positive tumor samples were evaluated using a differential expression analysis approach and the sensitivity and specificity of a molecular signature was determined. Results:Among the 21 patients in the study (3 women, 18 men; mean [SD] age, 54.6 [9.6] years), 6 had node-negative disease and 15 had node-positive disease. Using differential expression analysis, we found 146 genes that were significantly different in patients with node-negative disease vs those with node-positive disease, of which 15 genes were used to create a genetic signature that could distinguish node-negative-like from node-positive-like disease. The resultant molecular signature has a sensitivity of 88.2% (95% CI, 63.6%-98.5%) and specificity of 85.7% (95% CI, 42.1%-99.6%). The positive likelihood ratio of this signature was 6.1 (95% CI, 1.0-38.2) and the negative likelihood ratio was 0.1 (95% CI, 0.04-0.5). Given this population's prevalence of node-positive disease of 70.8%, the positive- and negative-predicative values for this gene signature were 93.7% (95% CI, 70.8%-98.9%) and 75.0% (95% CI, 44.1%-92.0%), respectively. In addition, we developed a gene signature using agnostic, machine learning software that identified a 40-gene profile that predicts node-negative disease from node-positive disease (area under the curve, 0.93; 95% CI, 0.63-1.00). Conclusions and Relevance:Many HPV-16 and p16-positive tumors are treated as "lower-risk," but they do not have similar genetic compositions at the biological level. The identification of subgroups with unique expression patterns, such as those with nodal metastases, may guide physicians toward alternative or more aggressive therapies. In our study, unguided clustering suggested that that the larger biological characteristics of a tumor could be a better prognostic biomarker.

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

Project description:BACKGROUNDPatients with p16+ oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are currently no reliable biomarkers of treatment failure for p16+ OPSCC. Pathologist-based visual assessment of tumor cell multinucleation (MN) has been shown to be independently prognostic of disease-free survival (DFS) in p16+ OPSCC. However, its quantification is time intensive, subjective, and at risk of interobserver variability.METHODSWe present a deep-learning-based metric, the multinucleation index (MuNI), for prognostication in p16+ OPSCC. This approach quantifies tumor MN from digitally scanned H&E-stained slides. Representative H&E-stained whole-slide images from 1094 patients with previously untreated p16+ OPSCC were acquired from 6 institutions for optimization and validation of the MuNI.RESULTSThe MuNI was prognostic for DFS, overall survival (OS), or distant metastasis-free survival (DMFS) in p16+ OPSCC, with HRs of 1.78 (95% CI: 1.37-2.30), 1.94 (1.44-2.60), and 1.88 (1.43-2.47), respectively, independent of age, smoking status, treatment type, or tumor and lymph node (T/N) categories in multivariable analyses. The MuNI was also prognostic for DFS, OS, and DMFS in patients with stage I and stage III OPSCC, separately.CONCLUSIONMuNI holds promise as a low-cost, tissue-nondestructive, H&E stain-based digital biomarker test for counseling, treatment, and surveillance of patients with p16+ OPSCC. These data support further confirmation of the MuNI in prospective trials.FUNDINGNational Cancer Institute (NCI), NIH; National Institute for Biomedical Imaging and Bioengineering, NIH; National Center for Research Resources, NIH; VA Merit Review Award from the US Department of VA Biomedical Laboratory Research and Development Service; US Department of Defense (DOD) Breast Cancer Research Program Breakthrough Level 1 Award; DOD Prostate Cancer Idea Development Award; DOD Lung Cancer Investigator-Initiated Translational Research Award; DOD Peer-Reviewed Cancer Research Program; Ohio Third Frontier Technology Validation Fund; Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering; Clinical and Translational Science Award (CTSA) program, Case Western Reserve University; NCI Cancer Center Support Grant, NIH; Career Development Award from the US Department of VA Clinical Sciences Research and Development Program; Dan L. Duncan Comprehensive Cancer Center Support Grant, NIH; and Computational Genomic Epidemiology of Cancer Program, Case Comprehensive Cancer Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the US Department of VA, the DOD, or the US Government.