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Haralick texture features are used to quantify the spatial distribution of signal intensities within an image. In this study, the heterogeneity of proliferation (Ki-67 expression) and immune cells (CD45 expression) within tumors was quantified and used to classify histologic characteristics of larynx and hypopharynx carcinomas. Of 21 laryngectomy specimens, 74 whole-mount tumor slides were scored on histologic characteristics. Ki-67 and CD45 immunohistochemistry was performed, and all sections were digitized. The tumor area was annotated in QuPath. Haralick features independent of the diaminobenzidine intensity were extracted from the isolated diaminobenzidine signal to quantify intratumor heterogeneity. Haralick features from both Ki-67 and CD45 were used as input for a principal component analysis. A linear support vector machine was fitted to the first 4 principal components for classification and validated with a leave-one-patient-out cross-validation method. Significant differences in individual Haralick features were found between cohesive and noncohesive tumors for CD45 (angular second motion: P =.03, inverse difference moment: P =.009, and entropy: P =.02) and between the larynx and hypopharynx tumors for both CD45 (angular second motion: P =.03, inverse difference moment: P =.007, and entropy: P =.005) and Ki-67 (correlation: P =.003). Therefore, these features were used for classification. The linear classifier resulted in a classification accuracy of 85% for site of origin and 81% for growth pattern. A leave-one-patient-out cross-validation resulted in an error rate of 0.27 and 0.35 for both classifiers, respectively. In conclusion, we show a method to quantify intratumor heterogeneity of immunohistochemistry biomarkers using Haralick features. This study also shows the feasibility of using these features to classify tumors by histologic characteristics. The classifiers created in this study are a proof of concept because more data are needed to create robust classifiers, but the method shows potential for automated tumor classification., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Asbestos describes a group of naturally occurring fibrous silicate mineral compounds that have been associated with a number of respiratory maladies, including mesothelioma and lung cancer. In addition, based primarily on epidemiologic studies, asbestos has been implicated as a risk factor for laryngeal and pharyngeal squamous cell carcinoma (SCC). The main objective of this work was to strengthen existing evidence via empirical demonstration of persistent asbestos fibers embedded in the tissue surrounding laryngeal and pharyngeal SCC, thus providing a more definitive biological link between exposure and disease. Six human papillomavirus (HPV)-negative laryngeal (n = 4) and pharyngeal (n = 2) SCC cases with a history working in an asbestos-exposed occupation were selected from a large population-based case-control study of head and neck cancer. A laryngeal SCC case with no history of occupational asbestos exposure was included as a control. Tissue cores were obtained from adjacent nonneoplastic tissue in tumor blocks from the initial primary tumor resection, and mineral fiber analysis was performed using a scanning electron microscope equipped with an energy dispersive X-ray analyzer (EDXA). Chrysotile asbestos fiber bundles were identified in 3/6 of evaluated cases with a history of occupational asbestos exposure. All three cases had tumors originating in the larynx. In addition, a wollastonite fiber of unclear significance was identified one of the HPV-negative pharyngeal SCC cases. No mineral fibers were identified in adjacent tissue of the case without occupational exposure. The presence of asbestos fibers in the epithelial tissue surrounding laryngeal SCC in cases with a history of occupational asbestos exposure adds a key line of physical evidence implicating asbestos as an etiologic factor.

Tissue microarrays are a powerful new tissue-conserving technology in the study of cancer, allowing simultaneous study of a large number of tumor specimens. We sought to ascertain the utility of tissue microarrays in head and neck cancer pathology using squamous cell carcinoma of the larynx as a model system. Whole-specimen slides from 44 different laryngeal squamous cell carcinomas were stained for p53 expression. Microarrays were then generated by taking six 0.6-mm core biopsies from each of the 44 specimens. The whole sections and the microarrays were independently scored for p53 expression. Twenty-three (53%) of the 44 tumor specimens were positive for p53. Forty-four of the 264 core biopsies (17%) were not given a score because of the lack of tumor cells. Seventy-eight percent of the individual discs on the microarray had scores in agreement with those of the whole-section slides. Among biopsy discs with tumor cells present, 94.5% were in agreement with the whole-section slide. The average probability that four randomly chosen biopsy discs, considered together, would accurately identify the presence of p53 staining in a whole section was 0.97 (95% CI.93-1.0). We conclude that tissue microarrays for squamous cell carcinomas can accurately represent immunohistochemical results of whole-slide specimens when four or more samples are used. Tissue microarrays are an important technique that may be applied to immunohistochemical studies of head and neck cancer.