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.

Identification of a serum-based microRNA signature that detects recurrent oral squamous cell carcinoma before it is clinically evident.

BACKGROUND: Survival rates for oral squamous cell carcinoma (OSCC) have remained poor for decades, a fact largely attributable to late-stage diagnoses and high recurrence rates. We report analysis of serum miRNA expression in samples from patients with high-risk oral lesions (HRL, including OSCC/carcinoma in situ lesions) and healthy non-cancer controls, with the aim of non-invasively detecting primary or recurrent disease before it is clinically evident. METHODS: Discovery, test, and validation sets were defined from a total of 468 serum samples (305 HRL and 163 control samples). Samples were analysed using multiple qRT-PCR platforms. RESULTS: A two-miRNA classifier comprised of miR-125b-5p and miR-342-3p was defined following discovery and test analyses. Analysis in an independent validation cohort reported sensitivity and specificity of ~74% for this classifier. Significantly, when this classifier was applied to serial serum samples taken from patients both before treatment and during post-treatment surveillance, it identified recurrence an average of 15 months prior to clinical presentation. CONCLUSIONS: These results indicate this serum miRNA classifier is effective as a simple, non-invasive monitoring tool for earlier detection of recurrent disease when lesions are typically smaller and amenable to a wider array of treatment options to improve survival.

Use of DNA image cytometry in conducting oral cancer screening in rural India.

OBJECTIVES: Oral cancer screening can assist in the early detection of oral potentially malignant lesions (OPMLs) and prevention of oral cancers. It can be challenging for clinicians to differentiate OPMLs from benign conditions. Adjunct screening tools such as fluorescence visualisation (FV) and DNA image cytometry (DNA-ICM) have shown success in identifying OPMLs in high-risk clinics. For the first time we aimed to assess these technologies in Indian rural settings and evaluate if these tools helped clinicians identify high-risk lesions during screening. METHODS: Dental students and residents screened participants in five screening camps held in villages outside of Hyderabad, India, using extraoral, intraoral, and FV examinations. Lesion and normal tissue brushings were collected for DNA-ICM analysis and cytology. RESULTS: Of the 1116 participants screened, 184 lesions were observed in 152 participants. Based on white light examination (WLE), 45 lesions were recommended for biopsy. Thirty-five were completed on site; 25 (71%) were diagnosed with low-grade dysplasias (17 mild, 8 moderate) and the remaining 10 showed no signs of dysplasia. FV loss was noted in all but one dysplastic lesion and showed a sensitivity of 96% and specificity of 17%. Cytology combined with DNA-ICM had a sensitivity of 64% and specificity of 86% in detecting dysplasia. CONCLUSION: DNA-ICM combined with cytology identified the majority of dysplastic lesions and identified additional lesions, which were not considered high-risk during WLE and biopsy on site. Efforts to follow-up with these participants are ongoing. FV identified most high-risk lesions but added limited value over WLE.

An improved algorithm using a Health Canada-approved DNA-image cytometry system for non-invasive screening of high-grade oral lesions.

BACKGROUND: DNA-image cytometry (DNA-ICM) is able to detect gross alterations of cellular DNA-content representing aneuploidy, a biomarker of malignancy. A Health Canada-approved DNA-ICM system, ClearCyte® in combination with a cytopathologist's review, has demonstrated high sensitivity (89%) and specificity (97%) in identifying high-grade oral lesions. The study objective was to create an improved automated algorithm (iClearcyte) and test its robustness in differentiating high grade from benign reactive oral lesions without a cytopathologist's input. METHODS: A set of 214 oral brushing samples of oral cancer (n = 92), severe dysplasia (n = 20), reactive lesions (n = 52), and normal samples (n = 50) were spun down onto slides and stained using Feulgen-Thionin reaction. Following ClearCyte® scan, nuclear features were calculated, and nuclei categorized into "diploid," "hyperdiploid," "tetraploid," and "aneuploid" DNA ploidy groups by the ClearCyte® software. The samples were randomized into training and test sets (70:30) based on patient's age, sex, tobacco use, and lesion site risk. The training set was used to create a new algorithm which was then validated using the remaining samples in the test set, where sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: The proposed iClearCyte algorithm (>1 "aneuploid" cell or ≥ 1.7% combined "hyperdiploid" and "tetraploid" nuclei frequency) identified high-grade samples with sensitivity, specificity, PPV, and NPV of 100.0%, 86.7%, 89.7%, and 100.0%, respectively, in the test set. CONCLUSION: The iClearCyte test has potential to serve as a robust non-invasive automated oral cancer screening tool promoting early oral cancer detection and decreasing the number of unnecessary invasive biopsies.

Racial/ethnic variation in the prevalence of vaccine-related human papillomavirus genotypes.

Objective: There are currently three licensed human papillomavirus (HPV) vaccines that protect against cervical cancer. Here we compare the prevalence of bi-, quadri-, and nonavalent vaccine-related HPV genotypes in a multi-ethnic sample of non-Hispanic white, non-Hispanic black, Hispanic, and Asian women. Design: Patients in this analysis (n = 419) represent a subset of women with a previous abnormal Pap test participating in a clinical trial. HPV genotyping was conducted using the Roche Linear Array. Prevalent HPV genotypes were grouped according to their inclusion in each of the vaccines: bivalent (16, 18), quadrivalent (16, 18, 6, 11), and nonavalent (16, 18, 31, 33, 45, 52, 58, 6, 11). Results: The prevalence of HPV genotypes covered by the bi-/quadrivalent vaccines was lowest among non-Hispanic black (15%) and Hispanic women (20%), compared to non-Hispanic white (38%) and Asian women (38%). Across all racial/ethnic groups, a large proportion of infections (38%-49%) were with genotypes included in the nonavalent vaccine. However, the prevalence of HPV genotypes not covered by any vaccine was significantly higher among non-Hispanic black (36%) and Hispanic women (42%), compared to non-Hispanic white (24%) and Asian women (16%) (p < 0.001). Racial/ethnic differences in HPV genotype prevalence were observed when controlling for demographic and sexual behavior characteristics, as well as when restricting the analysis to women with CIN 2+. Conclusion: Our data suggest racial/ethnic differences in the prevalence of vaccine-related HPV genotypes. In particular, non-Hispanic black and Hispanic women had the lowest prevalence of HPV genotypes covered by the bi-/quadrivalent vaccines. While a large proportion of their infections were covered by the nonavalent vaccine, non-Hispanic black and Hispanic women also had the highest prevalence of HPV genotypes not covered by any vaccine.

Quantification of large scale DNA organization for predicting prostate cancer recurrence.

This study investigates whether Genomic Organization at Large Scales (which we propose to call GOALS) as quantified via nuclear phenotype characteristics and cell sociology features (describing cell organization within tissue) collected from prostate tissue microarrays (TMAs) can separate biochemical failure from biochemical nonevidence of disease (BNED) after radical prostatectomy (RP). Of the 78 prostate cancer tissue cores collected from patients treated with RP, 16 who developed biochemical relapse (failure group) and 16 who were BNED patients (nonfailure group) were included in the analyses (36 cores from 32 patients). A section from this TMA was stained stoichiometrically for DNA using the Feulgen-Thionin methodology, and scanned with a Pannoramic MIDI scanner. Approximately 110 nuclear phenotypic features, predominately quantifying large scale DNA organization (GOALS), were extracted from each segmented nuclei. In addition, the centers of these segmented nuclei defined a Voronoi tessellation and subsequent architectural analysis. Prostate TMA core classification as biochemical failure or BNED after RP using GOALS features was conducted (a) based on cell type and cell position within the epithelium (all cells, all epithelial cells, epithelial >2 cell layers away from basement membrane) from all cores, and (b) based on epithelial cells more than two cell layers from the basement membrane using a Classifier trained on Gleason 6, 8, 9 (16 cores) only and applied to a Test set consisting of the Gleason 7 cores (20 cores). Successful core classification as biochemical failure or BNED after RP by a linear classifier was 75% using all cells, 83% using all epithelial cells, and 86% using epithelial >2 layers. Overall success of predicted classification by the linear Classifier of (b) was 87.5% using the Training Set and 80% using the Test Set. Overall success of predicted progression using Gleason score alone was 75% for Gleason >7 as failures and 69% for Gleason >6 as failures. © 2017 International Society for Advancement of Cytometry.

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.

Cooperation and competition in the dynamics of tissue architecture during homeostasis and tumorigenesis.

The construction of a network of cell-to-cell contacts makes it possible to characterize the patterns and spatial organization of tissues. Such networks are highly dynamic, depending on the changes of the tissue architecture caused by cell division, death and migration. Local competitive and cooperative cell-to-cell interactions influence the choices cells make. We review the literature on quantitative data of epithelial tissue topology and present a dynamical network model that can be used to explore the evolutionary dynamics of a two dimensional tissue architecture with arbitrary cell-to-cell interactions. In particular, we show that various forms of experimentally observed types of interactions can be modelled using game theory. We discuss a model of cooperative and non-cooperative cell-to-cell communication that can capture the interplay between cellular competition and tissue dynamics. We conclude with an outlook on the possible uses of this approach in modelling tumorigenesis and tissue homeostasis.

Molecular fixative enables expression microarray analysis of microdissected clinical cervical specimens.

Formalin-fixed tissue has been a mainstay of clinical pathology laboratories, but formalin alters many biomolecules, including nucleic acids and proteins. Meanwhile, frozen tissues contain better-preserved biomolecules, but tissue morphology is affected, limiting their diagnostic utility. Molecular fixatives promise to bridge this gap by simultaneously preserving morphology and biomolecules, enabling clinical diagnosis and molecular analyses on the same specimen. While previous reports have broadly evaluated the use of molecular fixative in various human tissues, we present here the first detailed assessment of the applicability of molecular fixative to both routine histopathological diagnosis and molecular analysis of cervical tissues. Ten specimens excised via the loop electrosurgical excision procedure, which removes conical tissue samples from the cervix, were cut into alternating pieces preserved in either formalin or molecular fixative. Cervical specimens preserved in molecular fixative were easily interpretable, despite featuring more eosinophilic cytoplasm and more recognizable chromatin texture than formalin-fixed specimens. Immunohistochemical staining patterns of p16 and Ki-67 were similar between fixatives, although Ki-67 staining was stronger in the molecular fixative specimens. The RNA of molecular fixative specimens from seven cases representing various dysplasia grades was assessed for utility in expression microarray analysis. Cluster analysis and scatter plots of duplicate samples suggest that data of sufficient quality can be obtained from as little as 50ng of RNA from molecular fixative samples. Taken together, our results show that molecular fixative may be a more versatile substitute for formalin, simultaneously preserving tissue morphology for clinical diagnosis and biomolecules for immunohistochemistry and gene expression analysis.

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.

Polymorphisms in the Nonhomologous End-joining DNA Repair Pathway are Associated with HPV Integration in Cervical Dysplasia.

Previous evidence indicates that human papillomavirus (HPV) integration status may be associated with cervical cancer development and progression. However, host genetic variation within genes that may play important roles in the viral integration process is understudied. The aim of this study was to examine the association between HPV16 and HPV18 viral integration status and SNPs in nonhomologous-end-joining (NHEJ) DNA repair pathway genes on cervical dysplasia. Women enrolled in two large trials of optical technologies for cervical cancer detection and positive for HPV16 or HPV18 were selected for HPV integration analysis and genotyping. Associations between SNPs and cytology (normal, low-grade, or high-grade lesions) were evaluated. Among women with cervical dysplasia, polytomous logistic regression models were used to evaluate the effect of each SNP on viral integration status. Of the 710 women evaluated [149 high-grade squamous intraepithelial lesion (HSIL), 251; low-grade squamous intraepithelial lesion (LSIL, 310 normal)], 395 (55.6%) were positive for HPV16 and 192 (27%) were positive for HPV18. Tag-SNPs in 13 DNA repair genes, including RAD50, WRN, and XRCC4, were significantly associated with cervical dysplasia. HPV16 integration status was differential across cervical cytology, but overall, most participants had a mix of both episomal and integrated HPV16. Four tag-SNPs in the XRCC4 gene were found to be significantly associated with HPV16 integration status. Our findings indicate that host genetic variation in NHEJ DNA repair pathway genes, specifically XRCC4, are significantly associated with HPV integration, and that these genes may play an important role in determining cervical cancer development and progression. PREVENTION RELEVANCE: HPV integration in premalignant lesions and is thought to be an important driver of carcinogenesis. However, it is unclear what factors promote integration. The use of targeted genotyping among women presenting with cervical dysplasia has the potential to be an effective tool in assessing the likelihood of progression to cancer.

Delineating spatial cell-cell interactions in the solid tumour microenvironment through the lens of highly multiplexed imaging.

The growth and metastasis of solid tumours is known to be facilitated by the tumour microenvironment (TME), which is composed of a highly diverse collection of cell types that interact and communicate with one another extensively. Many of these interactions involve the immune cell population within the TME, referred to as the tumour immune microenvironment (TIME). These non-cell autonomous interactions exert substantial influence over cell behaviour and contribute to the reprogramming of immune and stromal cells into numerous pro-tumourigenic phenotypes. The study of some of these interactions, such as the PD-1/PD-L1 axis that induces CD8+ T cell exhaustion, has led to the development of breakthrough therapeutic advances. Yet many common analyses of the TME either do not retain the spatial data necessary to assess cell-cell interactions, or interrogate few (<10) markers, limiting the capacity for cell phenotyping. Recently developed digital pathology technologies, together with sophisticated bioimage analysis programs, now enable the high-resolution, highly-multiplexed analysis of diverse immune and stromal cell markers within the TME of clinical specimens. In this article, we review the tumour-promoting non-cell autonomous interactions in the TME and their impact on tumour behaviour. We additionally survey commonly used image analysis programs and highly-multiplexed spatial imaging technologies, and we discuss their relative advantages and limitations. The spatial organization of the TME varies enormously between patients, and so leveraging these technologies in future studies to further characterize how non-cell autonomous interactions impact tumour behaviour may inform the personalization of cancer treatment.​.

Classifying tissue samples from measurements on cells with within-class tissue sample heterogeneity.

We consider here the problem of classifying a macro-level object based on measurements of embedded (micro-level) observations within each object, for example, classifying a patient based on measurements on a collection of a random number of their cells. Classification problems with this hierarchical, nested structure have not received the same statistical understanding as the general classification problem. Some heuristic approaches have been developed and a few authors have proposed formal statistical models. We focus on the problem where heterogeneity exists between the macro-level objects within a class. We propose a model-based statistical methodology that models the log-odds of the macro-level object belonging to a class using a latent-class variable model to account for this heterogeneity. The latent classes are estimated by clustering the macro-level object density estimates. We apply this method to the detection of patients with cervical neoplasia based on quantitative cytology measurements on cells in a Papanicolaou smear. Quantitative cytology is much cheaper and potentially can take less time than the current standard of care. The results show that the automated quantitative cytology using the proposed method is roughly equivalent to clinical cytopathology and shows significant improvement over a statistical model that does not account for the heterogeneity of the data.

Aberrant expression of long noncoding RNAs in cervical intraepithelial neoplasia.

OBJECTIVE: Long noncoding RNAs (lncRNAs) are a unique class of messenger RNA-like transcripts of at least 200 nucleotides in length with no significant protein-coding capacity. Aberrant lncRNA expression is emerging as a major component of the cancer transcriptome. Here, we sought to determine if differential lncRNA expression is a feature of the human cervical intraepithelial neoplasia (CIN) transcriptome. METHODS: Sequence data were derived from 16 long serial analyses of gene expression (L-SAGE) libraries constructed from cervical specimens representing mild (CIN1), moderate (CIN2), and severe (CIN3) histopathologic grades of CIN. A novel lncRNA discovery pipeline was developed to query the expression of lncRNAs within the SAGE data sets. RESULTS: A total of 2,230,370 sequence tags were delineated from the 16 SAGE libraries, representing the expression of 367,482 unique tags at varying abundance. Using a novel stepwise filtering strategy, we analyzed the cervical SAGE libraries and identified the expression profiles of 1056 lncRNAs in the human cervix. We present the first lncRNA expression profile derived from nonneoplastic cervical tissue and establish that changes in lncRNA expression do occur in cervical intraepithelial lesions. Our analysis also shows statistically significant aberrant expression of lncRNAs in the 3 CIN grades, suggesting that these unique noncoding RNA transcripts may contribute to the development and progression of precursor lesions. CONCLUSIONS: Through the analysis of L-SAGE libraries constructed from cervical specimens, we provide the first lncRNA expression profile of the cervix and demonstrate aberrant expression in early-stage neoplasia.

Improvement in Work Productivity After Group Voice Therapy in Professional Voice Users.

OBJECTIVE: A disordered voice may significantly impair the ability of workers to perform optimally on the job, especially those classified as professional voice users (PVU). Voice therapy is a common treatment option for voice disorders, but there are few studies demonstrating its effect on work productivity. The objective of this study was to evaluate the change in work productivity in PVU after group voice therapy. STUDY DESIGN: Prospective cohort study SETTING: Academic Voice Center METHODS: PVUs whose primary treatment for their voice disorder was voice therapy were recruited. Participants completed a 7-week group voice therapy course from January 2018 to December 2020. Participants completed the validated Work Productivity and Activity Impairment questionnaire (WPAI) which measured presenteeism (on the job work productivity impairment) and absenteeism (time missed from work), general self-efficacy scale (GSES), and Voice handicap index -10 (VHI-10) before and after group voice therapy. Changes in scores before and after therapy were compared using a Wilcoxon Signed-Rank test. RESULTS: Twenty-seven PVU were recruited; 25 had complete data (100% female, mean age 45.4 years, 68% teachers). Presenteeism (SD) decreased from 72.0% (23.3) to 36.8% (24.8), which represented a significant improvement of 35.2% (27.8) [95% CI 21.7-38.7; P < 0.001]. Activity impairment decreased from 48.4% (32.0) to 25.6% (23.8), which represented a significant improvement of 22.8% (26.5) [95% CI 20.7-37.0; P < 0.00]. There was no change in absenteeism (P = 0.27). Patients had high mean GSES of 34.4 (3.7) and abnormal mean VHI-10 of 18.2 (7.2). Changes in VHI-10 and GSES were not significant. CONCLUSION: PVU had an improvement in work productivity that was largely represented by decreased presenteeism after completing group voice therapy.

Accuracy of optical spectroscopy for the detection of cervical intraepithelial neoplasia: Testing a device as an adjunct to colposcopy.

Testing emerging technologies involves the evaluation of biologic plausibility, technical efficacy, clinical effectiveness, patient satisfaction, and cost-effectiveness. The objective of this study was to select an effective classification algorithm for optical spectroscopy as an adjunct to colposcopy and obtain preliminary estimates of its accuracy for the detection of CIN 2 or worse. We recruited 1,000 patients from screening and prevention clinics and 850 patients from colposcopy clinics at two comprehensive cancer centers and a community hospital. Optical spectroscopy was performed, and 4,864 biopsies were obtained from the sites measured, including abnormal and normal colposcopic areas. The gold standard was the histologic report of biopsies, read 2 to 3 times by histopathologists blinded to the cytologic, histopathologic, and spectroscopic results. We calculated sensitivities, specificities, receiver operating characteristic (ROC) curves, and areas under the ROC curves. We identified a cutpoint for an algorithm based on optical spectroscopy that yielded an estimated sensitivity of 1.00 [95% confidence interval (CI) = 0.92-1.00] and an estimated specificity of 0.71 [95% CI = 0.62-0.79] in a combined screening and diagnostic population. The positive and negative predictive values were 0.58 and 1.00, respectively. The area under the ROC curve was 0.85 (95% CI = 0.81-0.89). The per-patient and per-site performance were similar in the diagnostic and poorer in the screening settings. Like colposcopy, the device performs best in a diagnostic population. Alternative statistical approaches demonstrate that the analysis is robust and that spectroscopy works as well as or slightly better than colposcopy for the detection of CIN 2 to cancer.

Assessment of internal refractive index profile of stochastically inhomogeneous nuclear models via analysis of two-dimensional optical scattering patterns.

SIGNIFICANCE: Optical scattering signals obtained from tissue constituents contain a wealth of structural information. Conventional intensity features, however, are mostly dictated by the overall morphology and mean refractive index of these constituents, making it very difficult to exclusively sense internal refractive index fluctuations. AIM: We perform a systematic analysis to elucidate how changes in internal refractive index profile of cell nuclei can best be detected via optical scattering. APPROACH: We construct stochastically inhomogeneous nuclear models and numerically simulate their azimuth-resolved scattering patterns. We then process these two-dimensional patterns with the goal of identifying features that directly point to subnuclear structure. RESULTS: Azimuth-dependent intensity variations over the side scattering range provide significant insights into subnuclear refractive index profile. A particular feature we refer to as contrast ratio is observed to be highly sensitive to the length scale and extent of refractive index fluctuations; further, this feature is not susceptible to changes in the overall size and mean refractive index of nuclei, thereby allowing for selective tracking of subnuclear structure that can be linked to chromatin distribution. CONCLUSIONS: Our analysis will potentially pave the way for scattering-based assessment of chromatin reorganization that is considered to be a key hallmark of precancer progression.

Predicting Progression of Low-Grade Oral Dysplasia Using Brushing-Based DNA Ploidy and Chromatin Organization Analysis.

Most oral cancers arise from oral potentially malignant lesions, which show varying grades of dysplasia. Risk of progression increases with increasing grade of dysplasia; however, risk prediction among oral low-grade dysplasia (LGD), that is, mild and moderate dysplasia can be challenging as only 5%-15% transform. Moreover, grading of dysplasia is subjective and varies with the area of the lesion being biopsied. To date, no biomarkers or tools are used clinically to triage oral LGDs. This study uses a combination of DNA ploidy and chromatin organization (CO) scores from cells obtained from lesion brushings to identify oral LGDs at high-risk of progression. A total of 130 lesion brushings from patients with oral LGDs were selected of which 16 (12.3%) lesions progressed to severe dysplasia or cancer. DNA ploidy and CO scores were analyzed from nuclear features measured by our in-house DNA image cytometry (DNA-ICM) system and used to classify brushings into low-risk and high-risk. A total of 57 samples were classified as high-risk of which 13 were progressors. High-risk DNA brushing was significant for progression (P = 0.001) and grade of dysplasia (P = 0.004). Multivariate analysis showed high-risk DNA brushing showed 5.1- to 8-fold increased risk of progression, a stronger predictor than dysplasia grading and lesion clinical features. DNA-ICM can serve as a non-invasive, high-throughput tool to identify high-risk lesions several years before transformation. This will help clinicians focus on such lesions whereas low-risk lesions may be spared from unnecessary biopsies.Prevention Relevance: DNA ploidy and chromatin organization of cells collected from oral potentially malignant lesions (OPMLs) can identify lesions at high-risk of progression several years prior. This non-invasive test would enable clinicians to triage high-risk (OPMLs) for closer follow-up while low-risk lesions can undergo less frequent biopsies reducing burden on healthcare resources.

Quantitative nuclear phenotype signatures predict nodal disease in oral squamous cell carcinoma.

BACKGROUND: Early-stage oral squamous cell carcinoma (OSCC) patients have a one-in-four risk of regional metastasis (LN+), which is also the most significant prognostic factor for survival. As there are no validated biomarkers for predicting LN+ in early-stage OSCC, elective neck dissection often leads to over-treatment and under-treatment. We present a machine-learning-based model using the quantitative nuclear phenotype of cancer cells from the primary tumor to predict the risk of nodal disease. METHODS AND FINDINGS: Tumor specimens were obtained from 35 patients diagnosed with primary OSCC and received surgery with curative intent. Of the 35 patients, 29 had well (G1) or moderately (G2) differentiated tumors, and six had poorly differentiated tumors. From each, two consecutive sections were stained for hematoxylin & eosin and Feulgen-thionin staining. The slides were scanned, and images were processed to curate nuclear morphometric features for each nucleus, measuring nuclear morphology, DNA amount, and chromatin texture/organization. The nuclei (n = 384,041) from 15 G1 and 14 G2 tumors were randomly split into 80% training and 20% test set to build the predictive model by using Random Forest (RF) analysis which give each tumor cell a score, NRS. The area under ROC curve (AUC) was 99.6% and 90.7% for the training and test sets, respectively. At the cutoff score of 0.5 as the median NRS of each region of interest (n = 481), the AUC was 95.1%. We then developed a patient-level model based on the percentage of cells with an NRS ≥ 0.5. The prediction performance showed AUC of 97.7% among the 80% (n = 23 patient) training set and with the cutoff of 61% positive cells achieved 100% sensitivity and 91.7% specificity. When applying the 61% cutoff to the 20% test set patients, the model achieved 100% accuracy. CONCLUSIONS: Our findings may have a clinical impact with an easy, accurate, and objective biomarker from routine pathology tissue, providing an unprecedented opportunity to improve neck management decisions in early-stage OSCC patients.

Factors Associated with Failure of Botulinum Toxin Injection in Adductor Spasmodic Dysphonia.

OBJECTIVE: Electromyography (EMG) Guided botulinum toxin (BTX) injection is considered first-line treatment for adductor spasmodic dysphonia (SD). Failure rate can range between 6% and 29%. Study objective was to determine which factors were associated with failure. METHODS: This was a retrospective review conducted at a tertiary, academic center. Adductor SD patients presenting for BTX injections from August 2017 to October 2018 were eligible. Age, gender, Voice Handicap Index (VHI-10), Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), number of injections, disease duration, unilateral/bilateral injection, right/left injection, dose quantity, body mass index (BMI), professional voice user, employment, psychiatric comorbidity, breathiness, and dysphagia were investigated. Outcomes included failure as defined by the patient and dosage change. Univariate and multivariate statistical analysis was conducted. RESULTS: Sixty seven out of 564 injections (12%) were categorized as failure by 131 patients. In multivariate analysis, dosage change was associated with shorter duration of good effect (P < .001), BTX dose (P = .016), breathiness (P < .001), bilateral injection (P = .024), dysphagia (P = .012) and professional voice user (P = .021). Failure was associated with first injection with a new physician (P < .001), professional voice user P < .001) and lack of breathiness (P = .003). Failure rate was not associated with age, gender, VHI-10, CAPE-V, disease duration, left/right injection, dose quantity, BMI, psychiatric comorbidity, and dysphagia. CONCLUSION: Failure rate was 12% and associated with patients' first injection with a physician, professional voice user, and lack of breathiness. Dosage change occurred in 29% of injections and was associated with injection side effects, bilateral injections, BTX dose, professional voice user, and shorter duration of good effect.Level of evidence: 3.