Oral cancer detection and progression prediction using noninvasive cytology-based DNA ploidy approach.

BACKGROUND: Despite the oral cavity being readily accessible, oral cancer (OC) remains a significant burden. The objective of this study is to develop a DNA ploidy-based cytology test for early detection of high-risk oral lesions. METHODS: This retrospective study was conducted using 569 oral brushing samples collected from 95 normal and 474 clinically abnormal mucosa with biopsy diagnosis of reactive, low-grade or high-grade precancer or cancers. Brushing cells were processed to characterize DNA ploidy. A two-step DNA ploidy-based algorithm, the DNA ploidy oral cytology (DOC) test, was developed using a training set, and verified in test and validation sets to differentiate high-grade lesions (HGLs) from normal. The prognostic value of the test was evaluated by an independent outcome cohort, including progressed and non-progressing normal, reactive and low-grade lesions. Classification performance was assessed by accuracy, sensitivity, and specificity, while the prognostic value was evaluated by using the Cox proportional hazards analysis on 3-year progression-free survival (PFS). RESULTS: The developed DOC test exhibited high accuracy for detecting HGLs in the test and validation sets, with a sensitivity of 0.97 and 0.96, respectively. Its application to the Outcome cohort demonstrated significant prognostic value for 3-year PFS (log rank, p < 0.001). Multivariate analysis showed that high-grade pathology was the only variable explaining positive DOC test, not age, smoking, or lesional site. CONCLUSION: Clinical implementation of the DOC test could provide an effective screening method for detecting HGLs for biopsy and lesions at risk of progression.

Developmental transcription factor NFIB is a putative target of oncofetal miRNAs and is associated with tumour aggressiveness in lung adenocarcinoma.

Genes involved in fetal lung development are thought to play crucial roles in the malignant transformation of adult lung cells. Consequently, the study of lung tumour biology in the context of lung development has the potential to reveal key developmentally relevant genes that play critical roles in lung cancer initiation/progression. Here, we describe for the first time a comprehensive characterization of miRNA expression in human fetal lung tissue, with subsequent identification of 37 miRNAs in non-small cell lung cancer (NSCLC) that recapitulate their fetal expression patterns. Nuclear factor I/B (NFIB), a transcription factor essential for lung development, was identified as a potential frequent target for these 'oncofetal' miRNAs. Concordantly, analysis of NFIB expression in multiple NSCLC independent cohorts revealed its recurrent underexpression (in ∼40-70% of tumours). Interrogation of NFIB copy number, methylation, and mutation status revealed that DNA level disruption of this gene is rare, and further supports the notion that oncofetal miRNAs are likely the primary mechanism responsible for NFIB underexpression in NSCLC. Reflecting its functional role in regulating lung differentiation, low expression of NFIB was significantly associated with biologically more aggressive subtypes and, ultimately, poorer survival in lung adenocarcinoma patients. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Quantification of confocal fluorescence microscopy for the detection of cervical intraepithelial neoplasia.

BACKGROUND: Cervical cancer remains a major health problem, especially in developing countries. Colposcopic examination is used to detect high-grade lesions in patients with a history of abnormal pap smears. New technologies are needed to improve the sensitivity and specificity of this technique. We propose to test the potential of fluorescence confocal microscopy to identify high-grade lesions. METHODS: We examined the quantification of ex vivo confocal fluorescence microscopy to differentiate among normal cervical tissue, low-grade Cervical Intraepithelial Neoplasia (CIN), and high-grade CIN. We sought to (1) quantify nuclear morphology and tissue architecture features by analyzing images of cervical biopsies; and (2) determine the accuracy of high-grade CIN detection via confocal microscopy relative to the accuracy of detection by colposcopic impression. Forty-six biopsies obtained from colposcopically normal and abnormal cervical sites were evaluated. Confocal images were acquired at different depths from the epithelial surface and histological images were analyzed using in-house software. RESULTS: The features calculated from the confocal images compared well with those features obtained from the histological images and histopathological reviews of the specimens (obtained by a gynecologic pathologist). The correlations between two of these features (the nuclear-cytoplasmic ratio and the average of three nearest Delaunay-neighbors distance) and the grade of dysplasia were higher than that of colposcopic impression. The sensitivity of detecting high-grade dysplasia by analysing images collected at the surface of the epithelium, and at 15 and 30 µm below the epithelial surface were respectively 100, 100, and 92 %. CONCLUSIONS: Quantitative analysis of confocal fluorescence images showed its capacity for discriminating high-grade CIN lesions vs. low-grade CIN lesions and normal tissues, at different depth of imaging. This approach could be used to help clinicians identify high-grade CIN in clinical settings.

DNA Ploidy as a Potential Adjunct Prognostic Marker of Low-Risk Prostate Cancer Progression after Radical Prostatectomy.

PURPOSE: Post prostatectomy PSA kinetics and General Grade Groups (GGG) are the strongest prognostic markers of biochemical recurrence (BCR) and prostate cancer (PCa)-specific mortality after radical prostatectomy. Despite having low-risk PCa, some patients will experience BCR, for some, clinically significant BCR. There is a need for an objective prognostic marker at the time of prostatectomy to improve risk stratification within this population. In this study, we investigated the prognostic potential of DNA ploidy. MATERIALS AND METHODS: Prostatectomy samples from 97 patients with GGG1 and GGG2 with a low-risk CAPRA-S score were included in this study. PCa tissue with the worst Gleason pattern underwent tissue disaggregation, cell isolation and staining with a DNA stoichiometric stain. Using image cytometry, DNA ploidy was measured and a Ploidy Score (PS) was generated. RESULTS: Among the 97 patients, 79 had no BCR, 18 experienced BCR, of which 14 had a PSA doubling time (PSA-DT) >1 year (low-risk group) and 4 had a PSA-DT of <1 year (high-risk group). Using Logistic regression analysis, only pathological T stage (pT) and PS independently predicted BCR with PS being the most significant (p = 0.001). The number of aneuploid cells was significantly higher in the high-risk group compared to the other groups (p = 1.7x10-11). PS combined with GGG diagnosis further stratified risk groups of biochemical recurrence free survival within CAPRA-S low-risk cohort. CONCLUSION: DNA ploidy is an independent prognostic marker of BCR in low-risk PCa after radical prostatectomy, which could early on identify potentially aggressive PCa recurrences and introduce a more personalized approach to salvage treatments.

Identification of Malignancy-Associated Changes in Histologically Normal Tumor-Adjacent Epithelium of Patients with HPV-Positive Oropharyngeal Cancer.

The incidence of HPV-positive oropharyngeal cancer (HPV+ OPC) is increasing, thus presenting new challenges for disease detection and management. Noninvasive methods involving brush biopsies of diseased tissues were recently reported as insufficient for tumor detection in HPV+ OPC patients, likely due to differences between the site of tumor initiation at the base of involuted crypts and the site of brush biopsy at the crypt surface. We hypothesized that histologically normal surface epithelial cells in the oropharynx contain changes in nuclear morphology that arise due to tumor proximity. We analyzed the nuclear phenotype of matched tumor, tumor-adjacent normal, and contralateral normal tissues from biopsies of nine HPV+ OPC patients. Measurements of 89 nuclear features were used to train a random forest-based classifier to discriminate between normal and tumor nuclei. We then extracted voting scores from the trained classifier, which classify nuclei on a continuous scale from zero ("normal-like") to one ("tumor-like"). In each case, the average score of the adjacent normal nuclei was intermediate between the tumor and contralateral normal nuclei. These results provide evidence for the existence of phenotypic changes in histologically normal, tumor-adjacent surface epithelial cells, which could be used as brush biopsy-based biomarkers for HPV+ OPC detection.

Large-scale DNA organization is a prognostic marker of breast cancer survival.

Breast cancer is the leading cause of cancer-related deaths among women worldwide. We investigated whether changes in large-scale DNA organization (LDO) of tumor epithelial nuclei are an indicator of the aggressiveness of the tumor. We tested our algorithm on a set of 172 duplicates TMA cores samples coming from 95 breast cancer patients. Thirty-five patients died of breast cancer, and 60 were still alive 10 years after surgery. Duplicates cores were used to create training and test set. The TMA slides were stained with Feulgen-thionin and imaged using our in-house high-resolution Imaging system. Automated segmentation of cell nuclei followed by manual selection of intact, in-focus nuclei resulted in an average of 50 cell nuclei per sample available for analysis. Using forward stepwise linear discriminant analysis, a combination of six features that combined linearly gave the best discrimination between the two groups of cells: cells collected from 'deceased' patients TMA specimens and cells collected from "survivors" patients TMA specimens. Five of these features measure the spatial organization of DNA chromatin. The resulting canonical score is named cell LDO score. A patient LDO score, percentage of cell nuclei with a cell LDO score higher than a predefined cutoff value, was processed for the specimens in the test set, and a cutoff value was defined to classify patients with a low or a high LDO score. Using this binary test, 82.1% of patients were correctly classified are "deceased" or "survivors," with a specificity of 79% and a sensitivity of 88%. The relative risk of death of an individual with a high LDO score was nine times higher than for a patient with a low LDO score. When testing the combination of LDO score, node status, histological grade, and tumor grade to predict breast cancer survival, LDO was the most significant predictor. LDO classification was also highly associated with survival for only grade 1 and 2 patients as well as for only grade 3 patients. Our result confirms the potential of LDO to measure phenotypic changes associated with more aggressive disease and could be evaluated to identify patients more likely to benefit from adjuvant therapies.

Automated Region-based Prostate Cancer Cell Nuclei Localization. Part of a Prognostic Modality Tool for Prostate Cancer Patients.

BACKGROUND: Prostate cancer is a disease of disrupted cell genomes. Quantification of DNA from cytology preparations can yield prognostic information about tissue biological behaviors; however, this process is very labor-intensive to perform. Quantitative digital pathology can measure the structural chromatin changes associated with neoplasia and can enable prognostic and predictive assays based on imaging of sectioned prostate tissue. OBJECTIVE: To design an automated system to recognize and localize cell nuclei in images of stained sectioned tissue (first step in enabling quantitative digital pathology). STUDY DESIGN: Images of Feulgen-thionin-stained prostate cancer tissue microarray constructed from the surgical specimens of 33 prostate cancer patients were acquired for this study. We implemented a new image segmentation technique to overcome tissue complexity, cell clusters, background noise, image and tissue inhomogeneities, and other imaging issues that introduce uncertainties into the segmentation method and developed a fully automated system to localized prostate cell nuclei. RESULTS: We applied our algorithm on our dataset and obtained a 96.6% true-positive rate and a 12% false-positive rate. CONCLUSION: In this paper we present a new method to automatically localize thionin-stained prostate cancer cells, enabling the extraction of various nuclear and cell sociology features with high precision.

Diffuse optical microscopy for quantification of depth-dependent epithelial backscattering in the cervix.

A fiber optic imaging approach is presented using structured illumination for quantification of almost pure epithelial backscattering. We employ multiple spatially modulated projection patterns and camera-based reflectance capture to image depth-dependent epithelial scattering. The potential diagnostic value of our approach is investigated on cervical ex vivo tissue specimens. Our study indicates a strong backscattering increase in the upper part of the cervical epithelium caused by dysplastic microstructural changes. Quantization of relative depth-dependent backscattering is confirmed as a potentially useful diagnostic feature for detection of precancerous lesions in cervical squamous epithelium.

Light scattering from normal and dysplastic cervical cells at different epithelial depths: finite-difference time-domain modeling with a perfectly matched layer boundary condition.

The finite-difference time-domain (FDTD) method provides a flexible approach to studying the scattering that arises from arbitrarily inhomogeneous structures. We implemented a three-dimensional FDTD program code to model light scattering from biological cells. The perfectly matched layer (PML) boundary condition has been used to terminate the FDTD computational grid. We investigated differences in angle-dependent scattering properties of normal and dysplastic cervical cells. Specifically, the scattering patterns and phase functions have been computed for normal and dysplastic cervical cells at three different epithelial depths, namely, basal/parabasal, intermediate, and superficial. Construction of cervical cells within the FDTD computational grid is based on morphological and chromatin texture features obtained from quantitative histopathology. The results show that angle-dependent scattering characteristics are different not only for normal and dysplastic cells but also for cells at different epithelial depths. The calculated scattering cross-sections are significantly greater for dysplastic cells. The scattering cross-sections of cells at different depths indicate that scattering decreases in going from the superficial layer to the intermediate layer, but then increases in the basal/parabasal layer. This trend for epithelial cell scattering has also been observed in confocal images of ex vivo cervical tissue.

Evaluation of HPV infection and smoking status impacts on cell proliferation in epithelial layers of cervical neoplasia.

Accurate cervical intra-epithelial neoplasia (CIN) lesion grading is needed for effective patient management. We applied computer-assisted scanning and analytic approaches to immuno-stained CIN lesion sections to more accurately delineate disease states and decipher cell proliferation impacts from HPV and smoking within individual epithelial layers. A patient cohort undergoing cervical screening was identified (n = 196) and biopsies of varying disease grades and with intact basement membranes and epithelial layers were obtained (n = 261). Specimens were sectioned, stained (Mib1), and scanned using a high-resolution imaging system. We achieved semi-automated delineation of proliferation status and epithelial cell layers using Otsu segmentation, manual image review, Voronoi tessellation, and immuno-staining. Data were interrogated against known status for HPV infection, smoking, and disease grade. We observed increased cell proliferation and decreased epithelial thickness with increased disease grade (when analyzing the epithelium at full thickness). Analysis within individual cell layers showed a ≥50% increase in cell proliferation for CIN2 vs. CIN1 lesions in higher epithelial layers (with minimal differences seen in basal/parabasal layers). Higher rates of proliferation for HPV-positive vs. -negative cases were seen in epithelial layers beyond the basal/parabasal layers in normal and CIN1 tissues. Comparing smokers vs. non-smokers, we observed increased cell proliferation in parabasal (low and high grade lesions) and basal layers (high grade only). In sum, we report CIN grade-specific differences in cell proliferation within individual epithelial layers. We also show HPV and smoking impacts on cell layer-specific proliferation. Our findings yield insight into CIN progression biology and demonstrate that rigorous, semi-automated imaging of histopathological specimens may be applied to improve disease grading accuracy.

Use of nuclear morphometry characteristics to distinguish between normal and abnormal cervical glandular histologies.

This is a methodological study exploring the use of quantitative histopathology applied to the cervix to discriminate between normal and cancerous (consisting of adenocarcinoma and adenocarcinoma in situ) tissue samples. The goal is classifying tissue samples, which are populations of cells, from measurements on the cells. Our method uses one particular feature, the IODs-Index, to create a tissue level feature. The specific goal of this study is to find a threshold for the IODs-Index that is used to create the tissue level feature. The main statistical tool is Receiver Operating Characteristic (ROC) curve analysis. When applied to the data, our method achieved promising results with good estimated sensitivity and specificity for our data set. The optimal threshold for the IODs-Index was found to be 2.12.