Assessing the prognostic value of tumor-infiltrating CD57+ cells in advanced stage head and neck cancer using QuPath digital image analysis

This study aimed to assess the prognostic value of intratumoral CD57+ cells in head and neck squamous cell carcinoma (HNSCC) and to examine the reproducibility of these analyses using QuPath. Pretreatment biopsies of 159 patients with HPV-negative, stage III/IV HNSCC treated with chemoradiotherapy were immunohistochemically stained for CD57. The number of CD57+ cells per mm2 tumor epithelium was quantified by two independent observers and by QuPath, software for digital pathology image analysis. Concordance between the observers and QuPath was assessed by intraclass correlation coefficients (ICC). The correlation between CD57 and clinicopathological characteristics was assessed; associations with clinical outcome were estimated using Cox proportional hazard analysis and visualized using Kaplan-Meier curves. The patient cohort had a 3-year OS of 65.8% with a median follow-up of 54 months. The number of CD57+ cells/mm2 tumor tissue did not correlate to OS, DFS, or LRC. N stage predicted prognosis (OS: HR 0.43, p = 0.008; DFS: HR 0.41, p = 0.003; LRC: HR 0.24, p = 0.007), as did WHO performance state (OS: HR 0.48, p = 0.028; LRC: 0.33, p = 0.039). Quantification by QuPath showed moderate to good concordance with two human observers (ICCs 0.836, CI 0.805–0.863, and 0.741, CI 0.692–0.783, respectively). In conclusion, the presence of CD57+ TILs did not correlate to prognosis in advanced stage, HPV-negative HNSCC patients treated with chemoradiotherapy. Substantial concordance between human observers and QuPath was found, confirming a promising future role for digital, algorithm driven image analysis

In the mix: the potential benefits of adding GM-CSF to CpG-B in the local treatment of patients with early-stage melanoma

Whereas TLR9 agonists are recognized as powerful stimulators of antitumor immunity, GM-CSF has had mixed reviews. In previously reported randomized trials we assessed the effects of local immune modulation in early-stage melanoma with CpG-B alone or with GM-CSF. Here we discuss the added value of GM-CSF and show sex-related differences

Comparison of three PD-L1 immunohistochemical assays in head and neck squamous cell carcinoma (HNSCC)

Expression of programmed cell death-ligand 1 (PD-L1) is being used as predictive biomarker for immunotherapy in head and neck squamous cell carcinoma (HNSCC). Several antibodies are available for PD-L1 testing and multiple staining and scoring methods are used. This study aimed to compare the performance of two PD-L1 standardized assays (SP263 and 22C3 pharmDx) and one laboratory-developed test (LDT) (22C3) in HNSCC using the tumor proportion score (TPS) and the combined positive score (CPS). Pretreatment biopsies from 147 HNSCC patients were collected in a tissue-microarray (TMA). Serial sections of the TMA were immunohistochemically stained for PD-L1 expression using 22C3 pharmDx on the Dako Link 48 platform, SP263 on the Ventana Benchmark Ultra platform, and 22C3 as an LDT on the Ventana Benchmark Ultra. Stained slides were assessed for TPS and CPS. Cutoffs of ≥1% and ≥50% for TPS and ≥1 and ≥20 for CPS were used. Concordance between the different staining assays was moderate to poor for TPS (intraclass correlation coefficient (ICC) 0.46) as well as for CPS (ICC 0.34). When stratifying patients by clinically relevant cutoffs, considerable differences between the assays were observed: concordance was poor for both TPS and CPS. Generally, SP263 stained a higher percentage of cells than the other assays, especially when using the CPS. Moderate concordance was shown between three different PD-L1 immunohistochemical assays and considerable differences in PD-L1 positivity were observed when using clinically relevant cutoffs. This should be taken into account when using PD-L1 expression to guide clinical practice

Predicting HPV association using deep learning and regular H&E stains allows granular stratification of oropharyngeal cancer patients

Abstract Human Papilloma Virus (HPV)-associated oropharyngeal squamous cell cancer (OPSCC) represents an OPSCC subgroup with an overall good prognosis with a rising incidence in Western countries. Multiple lines of evidence suggest that HPV-associated tumors are not a homogeneous tumor entity, underlining the need for accurate prognostic biomarkers. In this retrospective, multi-institutional study involving 906 patients from four centers and one database, we developed a deep learning algorithm (OPSCCnet), to analyze standard H&E stains for the calculation of a patient-level score associated with prognosis, comparing it to combined HPV-DNA and p16-status. When comparing OPSCCnet to HPV-status, the algorithm showed a good overall performance with a mean area under the receiver operator curve (AUROC) = 0.83 (95% CI = 0.77-0.9) for the test cohort (n = 639), which could be increased to AUROC = 0.88 by filtering cases using a fixed threshold on the variance of the probability of the HPV-positive class - a potential surrogate marker of HPV-heterogeneity. OPSCCnet could be used as a screening tool, outperforming gold standard HPV testing (OPSCCnet: five-year survival rate: 96% [95% CI = 90–100%]; HPV testing: five-year survival rate: 80% [95% CI = 71–90%]). This could be confirmed using a multivariate analysis of a three-tier threshold (OPSCCnet: high HR = 0.15 [95% CI = 0.05–0.44], intermediate HR = 0.58 [95% CI = 0.34–0.98] p = 0.043, Cox proportional hazards model, n = 211; HPV testing: HR = 0.29 [95% CI = 0.15–0.54] p < 0.001, Cox proportional hazards model, n = 211). Collectively, our findings indicate that by analyzing standard gigapixel hematoxylin and eosin (H&E) histological whole-slide images, OPSCCnet demonstrated superior performance over p16/HPV-DNA testing in various clinical scenarios, particularly in accurately stratifying these patients