Prognostic implications of p16 and HPV discordance in oropharyngeal cancer (HNCIG-EPIC-OPC): a multicentre, multinational, individual patient data analysis

Background p16(INK4a) (p16) immunohistochemistry is the most widely used biomarker assay for inferring HPV causation in oropharyngeal cancer in clinical and trial settings. However, discordance exists between p16 and HPV DNA or RNA status in some patients with oropharyngeal cancer. We aimed to clearly quantify the extent of discordance, and its prognostic implications. Methods In this multicentre, multinational individual patient data analysis, we did a literature search in PubMed and Cochrane database for systematic reviews and original studies published in English between Jan 1, 1970, and Sept 30, 2022. We included retrospective series and prospective cohorts of consecutively recruited patients previously analysed in individual studies with minimum cohort size of 100 patients with primary squamous cell carcinoma of the oropharynx. Patient inclusion criteria were diagnosis with a primary squamous cell carcinoma of oropharyngeal cancer; data on p16 immunohistochemistry and on HPV testing; information on age, sex, tobacco, and alcohol use; staging by TNM 7th edition; information on treatments received; and data on clinical outcomes and follow-up (date of last follow-up if alive, date of recurrence or metastasis, and date and cause of death). There were no limits on age or performance status. The primary outcomes were the proportion of patients of the overall cohort who showed the different p16 and HPV result combinations, as well as 5-year overall survival and 5-year disease-free survival. Patients with recurrent or metastatic disease or who were treated palliatively were excluded from overall survival and disease-free survival analyses. Multivariable analysis models were used to calculate adjusted hazard ratios (aHR) for different p16 and HPV testing methods for overall survival, adjusted for prespecified confounding factors. Findings Our search returned 13 eligible studies that provided individual data for 13 cohorts of patients with oropharyngeal cancer from the UK, Canada, Denmark, Sweden, France, Germany, the Netherlands, Switzerland, and Spain. 7895 patients with oropharyngeal cancer were assessed for eligibility. 241 were excluded before analysis, and 7654 were eligible for p16 and HPV analysis. 5714 (74middot7%) of 7654 patients were male and 1940 (25middot3%) were female. Ethnicity data were not reported. 3805 patients were p16-positive, 415 (10middot9%) of whom were HPV-negative. This proportion differed significantly by geographical region and was highest in the areas with lowest HPV-attributable fractions (r=-0middot744, p=0middot0035). The proportion of patients with p16+/HPV- oropharyngeal cancer was highest in subsites outside the tonsil and base of tongue (29middot7% vs 9middot0%, p<0middot0001). 5-year overall survival was 81middot1% (95% CI 79middot5-82middot7) for p16+/HPV+, 40middot4% (38middot6-42middot4) for p16-/HPV-, 53middot2% (46middot6-60middot8) for p16-/HPV+, and 54middot7% (49middot2-60middot9) for p16+/HPV-. 5-year disease-free survival was 84middot3% (95% CI 82middot9-85middot7) for p16+/HPV+, 60middot8% (58middot8-62middot9) for p16-/HPV-; 71middot1% (64middot7-78middot2) for p16-/HPV+, and 67middot9% (62middot5-73middot7) for p16+/HPV-. Results were similar across all European sub-regions, but there were insufficient numbers of discordant patients from North America to draw conclusions in this cohort. Interpretation Patients with discordant oropharyngeal cancer (p16-/HPV+ or p16+/HPV-) had a significantly worse prognosis than patients with p16+/HPV+ oropharyngeal cancer, and a significantly better prognosis than patients with p16-/HPV- oropharyngeal cancer. Along with routine p16 immunohistochemistry, HPV testing should be mandated for clinical trials for all patients (or at least following a positive p16 test), and is recommended where HPV status might influence patient care, especially in areas with low HPV-attributable fractions. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd

Thyroid cancer susceptibility polymorphisms: confirmation of loci on chromosomes 9q22 and 14q13, validation of a recessive 8q24 locus and failure to replicate a locus on 5q24

Five single nucleotide polymorphisms (SNPs) associated with thyroid cancer (TC) risk have been reported: rs2910164 (5q24); rs6983267 (8q24); rs965513 and rs1867277 (9q22); and rs944289 (14q13). Most of these associations have not been replicated in independent populations and the combined effects of the SNPs on risk have not been examined. This study genotyped the five TC SNPs in 781 patients recruited through the TCUKIN study. Genotype data from 6122 controls were obtained from the CORGI and Wellcome Trust Case-Control Consortium studies. Significant associations were detected between TC and rs965513A (p=6.35×10−34), rs1867277A (p=5.90×10−24), rs944289T (p=6.95×10−7), and rs6983267G (p=0.016). rs6983267 was most strongly associated under a recessive model (PGG vs GT + TT=0.004), in contrast to the association of this SNP with other cancer types. However, no evidence was found of an association between rs2910164 and disease under any risk model (p>0.7). The rs1867277 association remained significant (p=0.008) after accounting for genotypes at the nearby rs965513 (p=2.3×10−13) and these SNPs did not tag a single high risk haplotype. The four validated TC SNPs accounted for a relatively large proportion (∼11%) of the sibling relative risk of TC, principally owing to the large effect size of rs965513 (OR 1.74)

Unsupervised morphological segmentation of tissue compartments in histopathological images

Algorithmic segmentation of histologically relevant regions of tissues in digitized histopathological images is a critical step towards computer-assisted diagnosis and analysis. For example, automatic identification of epithelial and stromal tissues in images is important for spatial localisation and guidance in the analysis and characterisation of tumour micro-environment. Current segmentation approaches are based on supervised methods, which require extensive training data from high quality, manually annotated images. This is often difficult and costly to obtain. This paper presents an alternative data-independent framework based on unsupervised segmentation of oropharyngeal cancer tissue micro-arrays (TMAs). An automated segmentation algorithm based on mathematical morphology is first applied to light microscopy images stained with haematoxylin and eosin. This partitions the image into multiple binary ‘virtual-cells’, each enclosing a potential ‘nucleus’ (dark basins in the haematoxylin absorbance image). Colour and morphology measurements obtained from these virtual-cells as well as their enclosed nuclei are input into an advanced unsupervised learning model for the identification of epithelium and stromal tissues. Here we exploit two Consensus Clustering (CC) algorithms for the unsupervised recognition of tissue compartments, that consider the consensual opinion of a group of individual clustering algorithms. Unlike most unsupervised segmentation analyses, which depend on a single clustering method, the CC learning models allow for more robust and stable detection of tissue regions. The proposed framework performance has been evaluated on fifty-five hand-annotated tissue images of oropharyngeal tissues. Qualitative and quantitative results of the proposed segmentation algorithm compare favourably with eight popular tissue segmentation strategies. Furthermore, the unsupervised results obtained here outperform those obtained with individual clustering algorithms