Inter-observer agreement among specialists in the diagnosis of oral potentially malignant disorders and oral cancer using store-and-forward technology.

OBJECTIVES: Oral cancer is a leading cause of morbidity and mortality. Screening and mobile Health (mHealth)-based approach facilitates early detection remotely in a resource-limited settings. Recent advances in eHealth technology have enabled remote monitoring and triage to detect oral cancer in its early stages. Although studies have been conducted to evaluate the diagnostic efficacy of remote specialists, to our knowledge, no studies have been conducted to evaluate the consistency of remote specialists. The aim of this study was to evaluate interobserver agreement between specialists through telemedicine systems in real-world settings using store-and-forward technology. MATERIALS AND METHODS: The two remote specialists independently diagnosed clinical images (n=822) from image archives. The onsite specialist diagnosed the same participants using conventional visual examination, which was tabulated. The diagnostic accuracy of two remote specialists was compared with that of the onsite specialist. Images that were confirmed histopathologically were compared with the onsite diagnoses and the two remote specialists. RESULTS: There was moderate agreement (k= 0.682) between two remote specialists and (k= 0.629) between the onsite specialist and two remote specialists in the diagnosis of oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, respectively, and those of remote specialist 2 were 95.8% and 60%, respectively, each compared with histopathology. CONCLUSION: The diagnostic accuracy of the two remote specialists was optimal, suggesting that "store and forward" technology and telehealth can be an effective tool for triage and monitoring of patients. CLINICAL RELEVANCE: Telemedicine is a good tool for triage and enables faster patient care in real-world settings.

Cancer stem cells and fibroblast niche cross talk in an in-vitro oral dysplasia model.

Understanding the cellular interactions during oral carcinogenesis has the potential to identify novel prognostic and therapeutic targets. This study aimed at investigating the cancer stem cell (CSC)-fibroblast niche interactions using in-vitro dysplastic cell line models developed from different stages of 4NQO-induced oral carcinogenic mice model. The spontaneously transformed epithelial cells (DysMSCTR6, 14 and 16) were developed from three time points (mild/moderate/severe), while two fibroblast cell lines (FibroMSCTR12, 16) were developed from moderate and severe dysplastic tissue. The epithelial (Epcam+/Ck+) and the fibroblast cell lines (Vimentin+/α-SMA+/Ck-) were authenticated and assessment of cells representing progressive grades of dysplastic severity indicated a significant increase in dysplastic marker profile (P < 0.05). Evaluation of the CSC characteristics showed that an increase in expression of Cd133, Cd44, Aldh1a1, Notch1, and Sox2 was accompanied by an increase in migratory (P > 0.05) and colony formation capacity (P > 0.005). Targeting Notch1 (GSI inhibitor PZ0187; 30 µM), showed a significant reduction in cell proliferation capacity (P < 0.05) and in the dysplastic marker profile. Further, Notch1 inhibition resulted in down regulation of Cd133 and Aldh1a 1 (P < 0.05) and a complete abrogation of colony formation ability (P < 0.0001). The effect of niche interactions evaluated using FibroMSCTR12-conditioned media studies, revealed an enrichment of ALDH1A1+ cells (P < 0.05), induction of spheroid formation ability (P < 0.0001) and increased proliferation capacity (3.7 fold; P < 0.005). Although PZ0187 reduced cell viability by ∼40%, was unable to abrogate the conditioned-media induced increase in proliferation capacity completely. This study reports a Notch-1 dependent enrichment of CSC properties during dysplastic progression and a Notch-1 independent dysplastic cell-fibroblast interaction during oral carcinogenesis.

Evaluation of a Lectin-Based Imaging System for the Chairside Detection of Oral Dysplasia and Malignancy.

PURPOSE: Currently available oral cancer screening adjuncts have not enhanced clinical screening methods because of high false positives and negatives, highlighting the need for a molecularly specific technique for accurate screening of suspicious oral lesions. The purpose of this study was to evaluate the in vivo screening accuracy of an oral lesion identification system that evaluates aberrant glycosylation patterns using a fluorescently labeled lectin (wheat germ agglutinin and fluorescein isothiocyanate [WGA-FITC]). MATERIALS AND METHODS: The authors designed and implemented a prospective cohort study at 3 institutions composed of patients with and without suspicious oral lesions. Oral cavities were screened by clinical examination and with the oral lesion identification system according to a stepwise procedure that included the topical application and fluorescence visualization of a fluorescent nuclear stain and WGA-FITC. Tissue samples were obtained from all enrolled patients for histopathological diagnosis and were used to calculate sensitivity and specificity metrics (primary outcome variable) irrespective of the oral lesion identification system result. RESULTS: The sample was composed of 97 patients; 86 had 100 clinically suspicious lesions and 11 without such lesions were included as a control group. Use of the oral lesion identification system resulted in 100, 100, and 74% sensitivity for cancer, high-grade dysplasia, and low-grade dysplasia, respectively, and a specificity of 80%. Clinical diagnosis yielded similar sensitivity values of 84, 100, and 88% for cancer, high-grade dysplasia, and low-grade dysplasia, respectively, and a specificity of 76%. Use of the oral lesion identification system enhanced the visualization of lesion dimensionality and borders. CONCLUSIONS: The results of this study suggest the oral lesion identification system was a beneficial adjunct to standard clinical examination, because the system provided sensitivity and specificity values similar to or greater than clinical diagnosis.

A Novel Mobile Health Approach to Early Diagnosis of Oral Cancer.

AIM: The incidence of oral cancer is high in India, which can be reduced by early detection. We aimed to empower frontline health care providers (FHP) for early detection and connect specialist to rural population through mHealth. MATERIALS AND METHODS: We provided training to FHPs in examination of oral cavity, use of mobile phone for image capture, and risk factor analysis. The FHPs were selected from different cohorts in resource-constrained settings. The workflow involved screening of high-risk individuals in door-to-door and workplace settings, and capture of images of suspected lesions. Uploaded data were interpreted and recommendation was sent by specialist from a remote location. Their recommendation was intimated to FHPs who arranged for further action. Two more initiatives, one for multiple dental schools and another for private practitioners, were undertaken. RESULTS: During the period from 2010 to 2018, 42,754 subjects have been screened, and 5,406 subjects with potentially malignant disorders have been identified. The prevalence of potentially malignant disorders varied from 0.8 to 62% at different cohorts; 516 biopsies have been performed at remote locations. CONCLUSION: Connecting specialists to rural population was made possible through the use of mobile health. Trained FHP were able to reach out to the population. Electronic data capture facilitated efficient follow-up. The program was very cost-effective with screening completed under $1 per person. CLINICAL SIGNIFICANCE: In view of the high incidence of oral cancer in India, and the resource-constrained settings, mobile health paves the way for better access to specialist care for the rural population.

Cancer stem cell mediated acquired chemoresistance in head and neck cancer can be abrogated by aldehyde dehydrogenase 1 A1 inhibition.

Chemoresistance leading to disease relapse is one of the major challenges to improve outcome in head and neck cancers. Cancer Stem Cells (CSCs) are increasingly being implicated in chemotherapy resistance, this study investigates the correlation between CSC behavior and acquired drug resistance in in vitro cell line models. Cell lines resistant to Cisplatin (Cal-27 CisR, Hep-2 CisR) and 5FU (Cal-27 5FUR) with high Resistance Indices (RI) were generated (RI ≥ 3) by short-term treatment of head and neck squamous cell carcinoma (HNSCC) cell lines with chemotherapeutic drugs (Cisplatin, Docetaxel, 5FU), using a dose-incremental strategy. The cell lines (Cal-27 DoxR, Hep-2 DoxR, Hep-2 5FUR) that showed low RI, nevertheless had a high cross resistance to Cisplatin/5FU (P < 0.05). Cal-27 CisR and DoxR showed 12-14% enrichment of CD44+ cells, while CisR/5FUR showed 4-6% increase in ALDH1A1+ cells as compared to parental cells (P < 0.05). Increased expression of stem cell markers (CD44, CD133, NOTCH1, ALDH1A1, OCT4, SOX2) in these cell lines, correlated with enhanced spheroid/colony formation, migratory potential, and increased in vivo tumor burden (P < 0.05). Inhibition of ALDH1A1 in Cal-27 CisR led to down regulation of the CSC markers, reduction in migratory, self-renewal and tumorigenic potential (P < 0.05) accompanied by an induction of sensitivity to Cisplatin (P < 0.05). Further, ex vivo treatment of explants (n = 4) from HNSCC patients with the inhibitor (NCT-501) in combination with Cisplatin showed a significant decrease in proliferating cells as compared to individual treatment (P = 0.001). This study hence suggests an ALDH1A1-driven, CSC-mediated mechanism in acquired drug resistance of HNSCC, which may have therapeutic implications. © 2016 Wiley Periodicals, Inc.

Curcumin and metformin-mediated chemoprevention of oral cancer is associated with inhibition of cancer stem cells.

Effective chemoprevention is critical for improving outcomes of oral cancer. As single agents, curcumin and metformin are reported to exhibit chemopreventive properties, in vitro as well as in patients with oral cancer. In this study, the chemopreventive efficacy of this drug combination was tested in a 4-nitro quinoline-1-oxide (4NQO) induced mice oral carcinogenesis model. Molecular analysis revealed a cancer stem cell (CSC)-driven oral carcinogenic progression in this model, wherein a progressive increase in the expression of CSC-specific markers (CD44 and CD133) was observed from 8th to 25th week, at transcript (40-100-fold) and protein levels (P ≤ 0.0001). Chemopreventive treatment of the animals at 17th week with curcumin and metformin indicated that the combination regimen decreased tumor volume when compared to the control arm (0.69+0.03 vs 6.66+2.4 mm3 ; P = 0.04) and improved overall survival of the animals (P = 0.03). Assessment of the molecular status showed an overall downregulation of CSC markers in the treatment arms as compared to the untreated control. Further, in vitro assessment of the treatment on the primary cells generated from progressive stages of 4NQO-induced mice tissue showed a concordant and consistent downregulation of the CSC markers following combination treatment (P < 0.05). The treatment also inhibited the migratory and self-renewal properties of these cells; the effect of which was prominent in the cultures of early dysplastic tissue (P < 0.002). Collectively, our observations suggest that the combination of curcumin and metformin may improve chemopreventive efficacy against oral squamous cell carcinoma through a CSC-associated mechanism.

Cancer stem cell markers in patterning differentiation and in prognosis of oral squamous cell carcinoma.

Differentiation is a major histological parameter determining tumor aggressiveness and prognosis of the patient; cancer stem cells with their slow dividing and undifferentiated nature might be one of the factors determining the same. This study aims to correlate cancer stem cell markers (CD44 and CD147) with tumor differentiation and evaluate their subsequent effect on prognosis. Immunohistochemical analysis in treatment naïve oral cancer patients (n = 53) indicated that the expression of CD147 was associated with poorly differentiated squamous cell carcinoma and moderately differentiated squamous cell carcinoma (p < 0.01). Furthermore, co-expression analysis showed that 45% each of moderately differentiated squamous cell carcinoma and poorly differentiated squamous cell carcinoma patients were CD44high/CD147high as compared to only 10% of patients with well-differentiated squamous cell carcinoma. A three-way analysis indicated that differentiation correlated with recurrence and survival (p < 0.05) in only the patients with CD44high/CD147high cohort. Subsequently, relevance of these cancer stem cell markers in patterning the differentiation characteristics was evaluated in oral squamous cell carcinoma cell lines originating from different grades of oral cancer. Flowcytometry-based analysis indicated an increase in CD44+/CD147+ cells in cell lines of poorly differentiated squamous cell carcinoma (94.35 ± 1.14%, p < 0.001) and moderately differentiated squamous cell carcinoma origin (93.49 ± 0.47%, p < 0.001) as compared to cell line of well-differentiated squamous cell carcinoma origin (23.12% ± 0.49%). Expression profiling indicated higher expression of cancer stem cell and epithelial-mesenchymal transition markers in SCC029B (poorly differentiated squamous cell carcinoma originated; p ≤ 0.001), which was further translated into increased spheroid formation, migration, and invasion (p < 0.001) as compared to cell line of well-differentiated squamous cell carcinoma origin. This study suggests that CD44 and CD147 together improve the prognostic efficacy of tumor differentiation; in vitro results further point out that these markers might be determinant of differentiation characteristics, imparting properties of increased self-renewal, migration, and invasion.

Rapid and Label-Free Histopathology of Oral Lesions Using Deep Learning Applied to Optical and Infrared Spectroscopic Imaging Data.

Oral potentially malignant disorders (OPMDs) are precursors to over 80% of oral cancers. Hematoxylin and eosin (H&E) staining, followed by pathologist interpretation of tissue and cellular morphology, is the current gold standard for diagnosis. However, this method is qualitative, can result in errors during the multi-step diagnostic process, and results may have significant inter-observer variability. Chemical imaging (CI) offers a promising alternative, wherein label-free imaging is used to record both the morphology and the composition of tissue and artificial intelligence (AI) is used to objectively assign histologic information. Here, we employ quantum cascade laser (QCL)-based discrete frequency infrared (DFIR) chemical imaging to record data from oral tissues. In this proof-of-concept study, we focused on achieving tissue segmentation into three classes (connective tissue, dysplastic epithelium, and normal epithelium) using a convolutional neural network (CNN) applied to three bands of label-free DFIR data with paired darkfield visible imaging. Using pathologist-annotated H&E images as the ground truth, we demonstrate results that are 94.5% accurate with the ground truth using combined information from IR and darkfield microscopy in a deep learning framework. This chemical-imaging-based workflow for OPMD classification has the potential to enhance the efficiency and accuracy of clinical oral precancer diagnosis.

Two by Two Factorial Design using Metformin and Curcumin for Second Primary Head and Neck Cancer Prevention Trial.

OBJECTIVE: The 2x2 factorial design is an effective method that allows for multiple comparisons, especially in the context of interactions between different interventions, without substantially increasing the required sample size. In view of the considerable preclinical evidence for Curcumin and Metformin in preventing the development and progression of head and neck squamous cell carcinoma (HNSCC), this study describes the protocol of the clinical trial towards applying the drug combination in prevention of second primary tumors. METHODS: We have applied the trial design to a large phase IIB/III double-blind, multi-centric, placebo-controlled, randomized clinical trial to determine the safety and efficacy of Metformin and Curcumin in the prevention of second primary tumours (SPT) of the aerodigestive tract following treatment of HNSCC (n=1,500) [Clinical Registry of India, CTRI/2018/03/012274]. Patients recruited in this trial will receive Metformin (with placebo), Curcumin (with placebo), Metformin, and Curcumin or placebo alone for a period of 36 months. The primary endpoint of this trial is the development of SPT, while the secondary endpoints are toxicities associated with the agents, incidence of recurrence, and identifying potential biomarkers. In this article, we discuss the 2x2 factorial design and how it applies to the head and neck cancer chemoprevention trial. CONCLUSION: 2x2 factorial design is an effective trial design for chemoprevention clinical trials where the effectiveness of multiple interventions needs to be tested parallelly.

CD44-SNA1 integrated cytopathology for delineation of high grade dysplastic and neoplastic oral lesions.

The high prevalence of oral potentially-malignant disorders exhibits diverse severity and risk of malignant transformation, which mandates a Point-of-Care diagnostic tool. Low patient compliance for biopsies underscores the need for minimally-invasive diagnosis. Oral cytology, an apt method, is not clinically applicable due to a lack of definitive diagnostic criteria and subjective interpretation. The primary objective of this study was to identify and evaluate the efficacy of biomarkers for cytology-based delineation of high-risk oral lesions. A comprehensive systematic review and meta-analysis of biomarkers recognized a panel of markers (n: 10) delineating dysplastic oral lesions. In this observational cross sectional study, immunohistochemical validation (n: 131) identified a four-marker panel, CD44, Cyclin D1, SNA-1, and MAA, with the best sensitivity (>75%; AUC>0.75) in delineating benign, hyperplasia, and mild-dysplasia (Low Risk Lesions; LRL) from moderate-severe dysplasia (High Grade Dysplasia: HGD) along with cancer. Independent validation by cytology (n: 133) showed that expression of SNA-1 and CD44 significantly delineate HGD and cancer with high sensitivity (>83%). Multiplex validation in another cohort (n: 138), integrated with a machine learning model incorporating clinical parameters, further improved the sensitivity and specificity (>88%). Additionally, image automation with SNA-1 profiled data set also provided a high sensitivity (sensitivity: 86%). In the present study, cytology with a two-marker panel, detecting aberrant glycosylation and a glycoprotein, provided efficient risk stratification of oral lesions. Our study indicated that use of a two-biomarker panel (CD44/SNA-1) integrated with clinical parameters or SNA-1 with automated image analysis (Sensitivity >85%) or multiplexed two-marker panel analysis (Sensitivity: >90%) provided efficient risk stratification of oral lesions, indicating the significance of biomarker-integrated cytopathology in the development of a Point-of-care assay.

Inter-observer agreement among specialists in the diagnosis of Oral Potentially Malignant Disorders and Oral Cancer using Store-and-Forward technology.

Oral Cancer is one of the most common causes of morbidity and mortality. Screening and mobile Health (mHealth) based approach facilitates remote early detection of Oral cancer in a resource-constrained settings. The emerging eHealth technology has aided specialist reach to rural areas enabling remote monitoring and triaging to downstage Oral cancer. Though the diagnostic accuracy of the remote specialist has been evaluated, there are no studies evaluating the consistency among the remote specialists, to the best of our knowledge. The purpose of the study was to evaluate the interobserver agreement between the specialists through telemedicine systems in real-world settings using store and forward technology. Two remote specialists independently diagnosed the clinical images from image repositories, and the diagnostic accuracy was compared with onsite specialist and histopathological diagnosis when available. Moderate agreement (k = 0.682) between two remote specialists and (k = 0.629) between the onsite specialist and two remote specialists in diagnosing oral lesions. The sensitivity and specificity of remote specialist 1 were 92.7% and 83.3%, whereas remote specialist 2 was 95.8% and 60%, respectively, compared to histopathology. The store and forward technology and telecare can be effective tools in triaging and surveillance of patients.

Interpretable and Reliable Oral Cancer Classifier with Attention Mechanism and Expert Knowledge Embedding via Attention Map.

Convolutional neural networks have demonstrated excellent performance in oral cancer detection and classification. However, the end-to-end learning strategy makes CNNs hard to interpret, and it can be challenging to fully understand the decision-making procedure. Additionally, reliability is also a significant challenge for CNN based approaches. In this study, we proposed a neural network called the attention branch network (ABN), which combines the visual explanation and attention mechanisms to improve the recognition performance and interpret the decision-making simultaneously. We also embedded expert knowledge into the network by having human experts manually edit the attention maps for the attention mechanism. Our experiments have shown that ABN performs better than the original baseline network. By introducing the Squeeze-and-Excitation (SE) blocks to the network, the cross-validation accuracy increased further. Furthermore, we observed that some previously misclassified cases were correctly recognized after updating by manually editing the attention maps. The cross-validation accuracy increased from 0.846 to 0.875 with the ABN (Resnet18 as baseline), 0.877 with SE-ABN, and 0.903 after embedding expert knowledge. The proposed method provides an accurate, interpretable, and reliable oral cancer computer-aided diagnosis system through visual explanation, attention mechanisms, and expert knowledge embedding.

BCA101 Is a Tumor-Targeted Bifunctional Fusion Antibody That Simultaneously Inhibits EGFR and TGFß Signaling to Durably Suppress Tumor Growth.

The EGFR and TGFß signaling pathways are important mediators of tumorigenesis, and cross-talk between them contributes to cancer progression and drug resistance. Therapies capable of simultaneously targeting EGFR and TGFß could help improve patient outcomes across various cancer types. Here, we developed BCA101, an anti-EGFR IgG1 mAb linked to an extracellular domain of human TGFßRII. The TGFß "trap" fused to the light chain in BCA101 did not sterically interfere with its ability to bind EGFR, inhibit cell proliferation, or mediate antibody-dependent cellular cytotoxicity. Functional neutralization of TGFß by BCA101 was demonstrated by several in vitro assays. BCA101 increased production of proinflammatory cytokines and key markers associated with T-cell and natural killer-cell activation, while suppressing VEGF secretion. In addition, BCA101 inhibited differentiation of naïve CD4+ T cells to inducible regulatory T cells (iTreg) more strongly than the anti-EGFR antibody cetuximab. BCA101 localized to tumor tissues in xenograft mouse models with comparable kinetics to cetuximab, both having better tumor tissue retention over TGFß "trap." TGFß in tumors was neutralized by approximately 90% in animals dosed with 10 mg/kg of BCA101 compared with 54% in animals dosed with equimolar TGFßRII-Fc. In patient-derived xenograft mouse models of head and neck squamous cell carcinoma, BCA101 showed durable response after dose cessation. The combination of BCA101 and anti-PD1 antibody improved tumor inhibition in both B16-hEGFR-expressing syngeneic mouse models and in humanized HuNOG-EXL mice bearing human PC-3 xenografts. Together, these results support the clinical development of BCA101 as a monotherapy and in combination with immune checkpoint therapy. SIGNIFICANCE: The bifunctional mAb fusion design of BCA101 targets it to the tumor microenvironment where it inhibits EGFR and neutralizes TGFß to induce immune activation and to suppress tumor growth.

Non-invasive imaging of oral potentially malignant and malignant lesions: A systematic review and meta-analysis.

Non-invasive (NI) imaging techniques have been developed to overcome the limitations of invasive biopsy procedures, which is the gold standard in diagnosis of oral dysplasia and Oral Squamous Cell Carcinoma (OSCC). This systematic review and meta- analysis was carried out with an aim to investigate the efficacy of the NI-imaging techniques in the detection of dysplastic oral potentially malignant disorders (OPMDs) and OSCC. Records concerned in the detection of OPMDs, Oral Cancer were identified through search in PubMed, Science direct, Cochrane Library electronic database (January 2000 to October 2020) and additional manual searches. Out of 529 articles evaluated for eligibility, 56 satisfied the pre-determined inclusion criteria, including 13 varying NI-imaging techniques. Meta-analysis consisted 44 articles, wherein majority of the studies reported Autofluorescence (AFI-38.6%) followed by Chemiluminescence (CHEM), Narrow Band Imaging (NBI) (CHEM, NBI-15.9%), Fluorescence Spectroscopy (FS), Diffuse Reflectance Spectroscopy (DRS), (FS, DRS-13.6%) and 5aminolevulinic acid induced protoporphyrin IX fluorescence (5ALA induced PPIX- 6.8%). Higher sensitivities (Sen) and specificities (Spe) were obtained using FS (Sen:74%, Spe:96%, SAUC=0.98), DRS (Sen:79%, Spe:86%, SAUC = 0.91) and 5 ALA induced PPIX (Sen:91%, Spe:78%, SAUC = 0.98) in the detection of dysplastic OPMDs from non-dysplastic lesions(NDLs). AFI, FS, DRS, NBI showed higher sensitivities and SAUC (>90%) in differentiating OSCC from NDLs. Analysed NI-imaging techniques suggests the higher accuracy levels in the diagnosis of OSCC when compared to dysplastic OPMDs. 5 ALA induced PPIX, DRS and FS showed evidence of superior accuracy levels in differentiation of dysplastic OPMDs from NDLs, however results need to be validated in a larger number of studies.

Systematic Review and Meta-Analysis to Identify the Immunocytochemical Markers Effective in Delineating Benign from Malignant Thyroid Lesions in FNAC Samples.

Conventional cytology-based diagnosis for thyroid cancer is limited with more than 30-45% of nodules categorized as indeterminate, necessitating surgery for confirming or refuting the diagnosis. This systematic review and meta-analysis were aimed at identifying immunocytochemical markers effective in delineating benign from malignant thyroid lesions in fine needle aspiration cytology (FNAC) samples, thereby improving the accuracy of cytology diagnosis. A systematic review of relevant articles (2000-2021) from online databases was carried out and the search protocol registered in PROSPERO database (CRD42021229121). The quality of studies was assessed using QUADAS-2. Review Manager 5.4.1 from Cochrane collaboration and MetaDisc Version 1.4 was used to conduct the meta-analysis. Bias in the studies were visually analyzed using funnel plots, and statistical significance was evaluated by Egger's test. Systematic review identified 64 original articles, while meta-analysis in eligible articles (n = 41) identified a panel of 5 markers, Galectin-3, HBME-1, CK-19, CD-56, and TPO. Assessment of the diagnostic performance revealed that Gal-3 (sensitivity: 0.81; CI: 0.79-0.83; specificity: 0.84; CI: 0.82-0.85) and HBME-1 (sensitivity: 0.83; Cl: 0.81-0.86; specificity: 0.85; CI: 0.83-0.86) showed high accuracy in delineating benign from malignant thyroid nodules. Efficacy analysis in indeterminate nodules showed Gal-3 and HBME-1 have high specificity of 0.86 (CI 0.84-0.89) and 0.82 (CI 0.78-0.86), respectively, and low sensitivity of 0.76 (CI 0.72-0.80) and 0.75 (CI 0.70-0.80), respectively. Diagnostic odds ratio (DOR) of Galectin-3 and HBME-1 were 39.18 (CI 23.38-65.65) and 24.44 (CI 11.16-53.54), respectively. Significant publication bias was observed for the markers Galectin-3 and CK-19 (p < 0.05). The panel of 5 markers identified from this meta-analysis are high-confidence candidates that need to be validated in thyroid cytology to establish their efficacy and enable clinical applicability.

Establishment and characterization of novel autologous pair cell lines from two Indian non­habitual tongue carcinoma patients.

Oral tongue squamous cell carcinoma (OTSCC) is one of the major causes of fatality in India due to very high percentage of patients with habits of smoking and chewing tobacco and associated products. Being highly heterogeneous in nature, every patient poses a different challenge clinically. To understand disease progression in an improved way, knowledge of cross­talk between tumor stroma and the tumor cells becomes indispensable. Patient­derived in vitro cell line models are helpful to understand the complexity of diseases. However, they have very low efficiency of establishment from the tumor samples, particularly the cancer­associated fibroblasts (CAFs). In the present study, two novel autologous pairs were immortalized spontaneously from non­habitual, HPV­positive patients, who presented with OTSCC. The epithelial and fibroblast cell lines had typical polygonal and spindle­shaped morphology, respectively. Positive staining with epithelial specific Pan­cytokeratin (PanCK) and fibroblast specific protein (FSP­1) further confirmed their epithelial and fibroblast origin. Unique Short Tandem Repeat (STR) profile of the cultures confirmed their novelty, while the similarity of the STR profiles between the epithelial and fibroblast cells from the same patient, confirmed their autologous nature. DNA analysis revealed aneuploidy of the established cultures. An increase in the tumorigenic potential of the established epithelial cultures upon treatment with CAF­conditioned medium proved the 'CAF­ness' of the established fibroblast cells. The established cultures are the first of their kind which would serve as a useful platform in understanding the tumor­stroma cross­talk in tongue cancer progression.

Oral epithelial cell segmentation from fluorescent multichannel cytology images using deep learning.

BACKGROUND AND OBJECTIVES: Cytology is a proven, minimally-invasive cancer screening and surveillance strategy. Given the high incidence of oral cancer globally, there is a need to develop a point-of-care, automated, cytology-based screening tool. Oral cytology image analysis has multiple challenges such as, presence of debris, blood cells, artefacts, and clustered cells, which necessitate a skilled expertise for single-cell detection of atypical cells for diagnosis. The main objective of this study is to develop a semantic segmentation model for Single Epithelial Cell (SEC) separation from fluorescent, multichannel, microscopic oral cytology images and classify the segmented images. METHODS: We have used multi-channel, fluorescent, microscopic images (number of images; n = 2730), which were stained differentially for cytoplasm and nucleus. The cytoplasmic and cell membrane markers used in the study were Mackia Amurensis Agglutinin (MAA; n: 2364) and Sambucus Nigra Agglutinin-1 (SNA-1; n: 366) with a nuclear stain DAPI. The cytology images were labelled for SECs, cluster of cells, artefacts, and blood cells. In this study, we used encoder-decoder models based on the well-established U-Net architecture, modified U-Net and ResNet-34 for multi-class segmentation. The experiments were performed with different class combinations of data to reduce imbalance. The derived MAA dataset (n: 14,706) of SEC, cluster, and artefacts/blood cells were used for developing a classification model. InceptionV3 model and a new custom Convolutional-Neural-Network (CNN) model (Artefact-Net) were trained to classify SNA-1 marker stained segmented images (n:6101). For segmentation models, Intersection Over Union (IoU) and F1 score were used as the evaluation matrices, while the classification models were evaluated using the conventional classification metrics like precision, recall and F1-Score. RESULTS: The U-Net and the modified U-Net models gave the best IoU overall (0.73-0.76) as well as for SEC segmentation (079). The images segmented using the modified U-Net model were classified by Artefact-Net and Inception V3 model with F1 scores of 0.96 and 0.95 respectively. The Artefact-Net, when compared to InceptionV3, provided a better precision and F1 score in classifying clusters (Precision: 0.91 vs 0.80; F1: 0.91 vs 0.86). CONCLUSION: This study establishes a pipeline for SEC segmentation with the segmented component containing only single cells. The pipline will enable automated, cytology-based early detection with reduced bias.

T-Cell Infiltration and Immune Checkpoint Expression Increase in Oral Cavity Premalignant and Malignant Disorders.

The immune cell niche associated with oral dysplastic lesion progression to carcinoma is poorly understood. We identified T regulatory cells (Treg), CD8+ effector T cells (Teff) and immune checkpoint molecules across oral dysplastic stages of oral potentially malignant disorders (OPMD). OPMD and oral squamous cell carcinoma (OSCC) tissue sections (N = 270) were analyzed by immunohistochemistry for Treg (CD4, CD25 and FoxP3), Teff (CD8) and immune checkpoint molecules (PD-1 and PD-L1). The Treg marker staining intensity correlated significantly (p < 0.01) with presence of higher dysplasia grade and invasive cancer. These data suggest that Treg infiltration is relatively early in dysplasia and may be associated with disease progression. The presence of CD8+ effector T cells and the immune checkpoint markers PD-1 and PD-L1 were also associated with oral cancer progression (p < 0.01). These observations indicate the induction of an adaptive immune response with similar Treg and Teff recruitment timing and, potentially, the early induction of exhaustion. FoxP3 and PD-L1 levels were closely correlated with CD8 levels (p < 0.01). These data indicate the presence of reinforcing mechanisms contributing to the immune suppressive niche in high-risk OPMD and in OSCC. The presence of an adaptive immune response and T-cell exhaustion suggest that an effective immune response may be reactivated with targeted interventions coupled with immune checkpoint inhibition.

Exploring uncertainty measures in convolutional neural network for semantic segmentation of oral cancer images.

Significance: Oral cancer is one of the most prevalent cancers, especially in middle- and low-income countries such as India. Automatic segmentation of oral cancer images can improve the diagnostic workflow, which is a significant task in oral cancer image analysis. Despite the remarkable success of deep-learning networks in medical segmentation, they rarely provide uncertainty quantification for their output. Aim: We aim to estimate uncertainty in a deep-learning approach to semantic segmentation of oral cancer images and to improve the accuracy and reliability of predictions. Approach: This work introduced a UNet-based Bayesian deep-learning (BDL) model to segment potentially malignant and malignant lesion areas in the oral cavity. The model can quantify uncertainty in predictions. We also developed an efficient model that increased the inference speed, which is almost six times smaller and two times faster (inference speed) than the original UNet. The dataset in this study was collected using our customized screening platform and was annotated by oral oncology specialists. Results: The proposed approach achieved good segmentation performance as well as good uncertainty estimation performance. In the experiments, we observed an improvement in pixel accuracy and mean intersection over union by removing uncertain pixels. This result reflects that the model provided less accurate predictions in uncertain areas that may need more attention and further inspection. The experiments also showed that with some performance compromises, the efficient model reduced computation time and model size, which expands the potential for implementation on portable devices used in resource-limited settings. Conclusions: Our study demonstrates the UNet-based BDL model not only can perform potentially malignant and malignant oral lesion segmentation, but also can provide informative pixel-level uncertainty estimation. With this extra uncertainty information, the accuracy and reliability of the model's prediction can be improved.

Development of a Low-cost NGS Test for the Evaluation of Thyroid Nodules.

Ultrasound-guided fine needle aspiration cytology (FNAC) is the preferred method of identifying malignancy in palpable thyroid nodules using the Bethesda reporting system. However, in around 30-40% of FNACs (Bethesda categories III, IV, and V), the results are indeterminate and surgery is required to confirm malignancy. Out of those who undergo surgery, only 10-40% of patients in these categories are found to have malignancies, thus proving surgery to be unnecessary for some patients or to be incomplete in others. While molecular testing on thyroid FNAC material is part of the American Thyroid Association (ATA) guidelines in evaluating thyroid nodules, it is currently unavailable in India due to cost constraints. In this study, we prospectively collected FNAC samples from sixty-nine patients who presented with palpable thyroid nodules. We designed a cost-effective next-generation sequencing (NGS) test to query multiple variants in the DNA and RNA isolated from the fine needle aspirate. The identification of oncogenic variants was considered to be indicative of malignancy, and confirmed by surgical histopathology. The panel showed an overall sensitivity of 81.25% and a specificity of 100%, while in the case of Bethesda categories III, IV, and V, the sensitivity was higher (87.5%) and the specificity was established at 100%. The panel could thereby serve as a rule-in test for the diagnosis of thyroid cancer and therefore help identify patients who require surgery, especially in the indeterminate Bethesda categories III, IV, and V.