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.

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.

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.​.

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.

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.

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.

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.

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.

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.

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.

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.

Multi-scale tissue architecture analysis of favorable-risk prostate cancer: Correlation with biochemical recurrence.

PURPOSE: Prostate cancer (PCa) with biopsy-based grade group (GG) 1 or 2 characteristics has a favorable outcome, yet some cases still progress after radical prostatectomy and present with biochemical recurrence (BCR). We hypothesized that the multi-scale tissue architecture (MSTA) analysis score would correlate with the aggressive PCa phenotype and could be used as a tool for risk assessment to improve the management of patients with favorable-risk PCa. MATERIALS AND METHODS: MSTA was evaluated in needle-biopsy samples from 115 patients with favorable-risk PCa, as defined by GG1 and GG2, a prostate-specific antigen (PSA) level of <10 ng/mL, a clinical stage of cT1c to cT2b, and general Gleason GG (GGG) and expert pathologist-assessed GG (EGG). Algorithms based on Voronoi diagrams were applied to all Feulgen-thionin-stained diagnostic areas. One hundred tissue architecture features were calculated and an MSTA score, a linear combination of the most discriminant features, was generated. Correlation of MSTA score with BCR and other clinical variables was investigated. RESULTS: In a univariate regression model, EGG, clinical stage, and MSTA were significant predictors of BCR (respective p-values: 0.0016, 0.016, and 0.028). Survival analysis showed that patients with a high MSTA score were more likely to experience BCR than were patients with a low MSTA score (odds ratio, 2.9). Combining MSTA with GG assessment resulted in a significant stratification of risk for BCR. CONCLUSIONS: MSTA score could be used as an objective adjunct risk stratification tool to pathologist assessments and could improve the management of patients with favorable-risk PCa.

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.

Cervical cytology reproducibility and associated clinical and demographic factors.

BACKGROUND: Although the Pap test has been the standard screening method for cervical precancer/cancer detection, it has been criticized for having a relatively low sensitivity and a low reproducibility between pathologists. There is limited knowledge about inter-rater agreement and what clinical and demographic factors are associated with disagreements between pathologists reading the same Pap smear. METHODS: This study aimed to assess inter- and intra- rater agreement of the Pap smear in 1619 cytologic slides with biopsy confirmation, using kappa statistics. Clinical and demographic factors associated with higher odds of inter-rater agreement were also examined and stratified by histologic diagnosis grade. RESULTS: Using a five grade classification system, the overall kappa statistics for total, inter-rater, and intra-rater samples were 0.62, 0.57, and 0.88 (unweighted) and 0.83, 0.81, and 0.95 (weighted), respectively. In stratified analyses by histologic grade, total kappas ranged from 0.40 (atypia) to 0.64 (human papilloma virus/CIN 1). Factors such as referral for abnormal Pap test (diagnostic vs screening population), recruiting site, and parity were found to be associated with higher agreement between the two cytologic readings. CONCLUSIONS: We observed relatively higher levels of agreement compared with other studies. However, variability was considerable and agreement was generally moderate, suggesting that cervical screening test accuracy and reproducibility needs to be improved.

The role of DNA image cytometry in screening oral potentially malignant lesions using brushings: A systematic review.

It is believed that the majority of oral cancers develop from oral potentially malignant lesions (OPML). Though they can be easily detected during screening, risk stratification is difficult. During screening clinicians often find it difficult to distinguish OPMLs from benign lesions, and predicting OPML at risk of malignant transformation is particularly challenging. DNA aneuploidy has been known to be a marker of malignancy in a number of sites including the oral cavity. We performed a systematic review to evaluate the effectiveness of DNA-ICM using brushings in differentiating OPMLs from benign/inflammatory lesions during screening and in predicting malignant transformation. MEDLINE, Pubmed, EMBASE electronic databases were systematically searched using a combination of keywords and subject headings. A total of 11 articles satisfied our inclusion criteria. These studies reported a wide range of sensitivity (16-96.4%) and specificity (90-100%) due to the differences in study design, definitions of high risk or low risk lesions and DNA-ICM protocol used. No long-term longitudinal studies were identified to assess the role of DNA-ICM using brushings in predicting malignant transformation. No studies evaluated the role of DNA-ICM in community screening settings. A number of studies combined DNA-ICM with other techniques like cytology or argyrophilic nucleolar organizer region counts leading to improved test results. In spite of DNA aneuploidy being accepted as a marker of malignancy, there is limited evidence of DNA-ICM using brushings being successful as an adjunct oral cancer screening tool. Longitudinal studies and large community screening studies need to be undertaken to draw stronger conclusion.

Hyperspectral cell sociology reveals spatial tumor-immune cell interactions associated with lung cancer recurrence.

BACKGROUND: The tumor microenvironment (TME) is a complex mixture of tumor epithelium, stroma and immune cells, and the immune component of the TME is highly prognostic for tumor progression and patient outcome. In lung cancer, anti-PD-1 therapy significantly improves patient survival through activation of T cell cytotoxicity against tumor cells. Direct contact between CD8+ T cells and target cells is necessary for CD8+ T cell activity, indicating that spatial organization of immune cells within the TME reflects a critical process in anti-tumor immunity. Current immunohistochemistry (IHC) imaging techniques identify immune cell numbers and densities, but lack assessment of cell-cell spatial relationships (or "cell sociology"). Immune functionality, however, is often dictated by cell-to-cell contact and cannot be resolved by simple metrics of cell density (for example, number of cells per mm2). To address this issue, we developed a Hyperspectral Cell Sociology technology platform for the analysis of cell-cell interactions in multi-channel IHC-stained tissue. METHODS: Tissue sections of primary tumors from lung adenocarcinoma patients with known clinical outcome were stained using multiplex IHC for CD3, CD8, and CD79a, and hyperspectral image analysis determined the phenotype of all cells. A Voronoi diagram for each cell was used to approximate cell boundaries, and the cell type of all neighboring cells was identified and quantified. Monte Carlo analysis was used to assess whether cell sociology patterns were likely due to random distributions of the cells. RESULTS: High density of intra-tumoral CD8+ T cells was significantly associated with non-recurrence of tumors. A cell sociology pattern of CD8+ T cells surrounded by tumor cells was more significantly associated with non-recurrence compared to CD8+ T cell density alone. CD3+ CD8- T cells surrounded by tumor cells was also associated with non-recurrence, but at a similar significance as cell density alone. Cell sociology metrics improved recurrence classifications of 12 patients. Monte Carlo re-sampling analysis determined that these cell sociology patterns were non-random. CONCLUSION: Hyperspectral Cell Sociology expands our understanding of the complex interplay between tumor cells and immune infiltrate. This technology could improve predictions of responses to immunotherapy and lead to a deeper understanding of anti-tumor immunity.

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.

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.

Using quantitative tissue phenotype to assess the margins of surgical samples from a pan-Canadian surgery study.

BACKGROUND: The purpose of this study was to use quantitative tissue phenotype (QTP) to assess the surgical margins to examine if a fluorescence visualization-guided surgical approach produces a shift in the surgical field by sparing normal tissue while catching high-risk tissue. METHODS: Using our QTP to calculate the degree of nuclear chromatin abnormalities, Nuclear Phenotypic Score (NPS), we analyzed 1290 biopsy specimens taken from surgical samples of 248 patients enrolled in the Efficacy of Optically-guided Surgery in the Management of Early-staged Oral Cancer (COOLS) trial. Multiple margin specimens were collected from each surgical specimen according to the presence of fluorescence visualization alterations and the distance to the surgical margins. RESULTS: The NPS in fluorescence visualization-altered (fluorescence visualization-positive) samples was significantly higher than that in fluorescence visualization-retained (fluorescence visualization-negative) samples. There was a constant trend of decreasing NPS of margin samples from non-adjacent-fluorescence visualization margins to adjacent-fluorescence visualization margins. CONCLUSION: Our results suggested that using fluorescence visualization to guide surgery has the potential to spare more normal tissue at surgical margins.

Automatic labeling of molecular biomarkers of immunohistochemistry images using fully convolutional networks.

This paper addresses the problem of quantifying biomarkers in multi-stained tissues based on the color and spatial information of microscopy images of the tissue. A deep learning-based method that can automatically localize and quantify the regions expressing biomarker(s) in any selected area on a whole slide image is proposed. The deep learning network, which we refer to as Whole Image (WI)-Net, is a fully convolutional network whose input is the true RGB color image of a tissue and output is a map showing the locations of each biomarker. The WI-Net relies on a different network, Nuclei (N)-Net, which is a convolutional neural network that classifies each nucleus separately according to the biomarker(s) it expresses. In this study, images of immunohistochemistry (IHC)-stained slides were collected and used. Images of nuclei (4679 RGB images) were manually labeled based on the expressing biomarkers in each nucleus (as p16 positive, Ki-67 positive, p16 and Ki-67 positive, p16 and Ki-67 negative). The labeled nuclei images were used to train the N-Net (obtaining an accuracy of 92% in a test set). The trained N-Net was then extended to WI-Net that generated a map of all biomarkers in any selected sub-image of the whole slide image acquired by the scanner (instead of classifying every nucleus image). The results of our method compare well with the manual labeling by humans (average F-score of 0.96). In addition, we carried a layer-based immunohistochemical analysis of cervical epithelium, and showed that our method can be used by pathologists to differentiate between different grades of cervical intraepithelial neoplasia by quantitatively assessing the percentage of proliferating cells in the different layers of HPV positive lesions.