Early Diagnosis Of Oral Cancer Research Articles

Comparison of knowledge, awareness, and behaviors toward oral cancer among dental students and dentists: an online cross-sectional questionnaire in Türkiye

ObjectiveThis cross-sectional online questionnaire-based study evaluated the knowledge, awareness, and behaviors of dentists and senior dental students regarding oral cancer (OC).Materials and methodsThis study included 168 dentists and senior dental students who had completed all theoretical educations and clinical practices. An online survey was administered to all participants to assess their awareness of the risk factors for OC, clinical knowledge, and behaviors. The participants’ demographic characteristics and knowledge of OC were analyzed.ResultsOf the participants, 48.8% were female and 51.2% were male. Their mean age was 27.04 ± 5.56 years (range: 21–51). In addition, 59.5% were dentists, and 40.5% were senior dental students. The dentists’ mean time since graduation was 6.38 ± 5.64 years (range: 1–27). Routine oral mucosa examination for OC was significantly more frequent among the dentists than the senior dental students (p < 0.05). Among all participants, 33% of dentists and 51.5% of senior dental students had poor knowledge of OC-related or possibly predisposing factors. Routine evaluation of OC-related and predisposing risk factors, including human papillomavirus infection, smoking, alcohol use, trauma-related non-healing oral lesions caused by long-term incompatible prostheses, and poor oral hygiene, was significantly more frequent among the dentists than the senior dental students (p < 0.05).ConclusionEducating dental students about a more comprehensive oral examination and early diagnosis of OC would help overcome the current lack of adequate knowledge and attitudes in OC prevention and early detection. A core curriculum compatible with the global standards on OC should be provided to dental students.

AWARENESS ABOUT THE ORAL CANCER AMONG UNDERGRADUATE STUDENTS OF ALLIED HEALTH SCIENCES IN PESHAWAR.

Oral cancer is a malignancy that affects the lips or oral cavity. Oral cancer causes about 20000 deaths worldwide. In Pakistan, it is the second most prevalent kind of cancer. The main obstacle to early diagnosis of oral cancer is the lack of information about oral cancer. Therefore, raising awareness among students is necessary and very helpful in controlling, early identification and prevention of oral cancer. Objective: To assess the level of awareness regarding oral cancer among undergraduate students. Methods. A descriptive cross-sectional study was carried out among undergraduate students of Allied Health Sciences Institutes in Peshawar. Data were collected from 312 undergraduate students through questionnaires. A convenient sampling technique was used for participant selection. Written informed consent was taken from all participants. Results: Out of 312 participants there were 124(39.7%) females and 188(60.3%) were males. About 65.7% were aware of oral cancer, and 71.2% were aware that oral cancer is due to alcohol drinking habits. 79.2% were aware that consumption of paan masala or guthka may cause oral cancer. 70.8% were aware that oral cancer is an infectious disease. Most of the students had poor knowledge regarding oral cancer as a disease of old age. Only 58.9% had information concerning the prevention of oral cancer. The majority of students were unaware of the treatment cost of oral cancer. More than half of the students (78.5%) were interested in information and education regarding oral cancer. Conclusion: The study concluded that students are decent or moderately aware. However, many lack basic knowledge regarding the initial signs and symptoms of oral cancer and its subsequent causes and effects, which could minimize the approach to overcoming the said problem.

Deep neural network uncertainty estimation for early oral cancer diagnosis.

Early diagnosis in oral cancer is essential to reduce both morbidity and mortality. This study explores the use of uncertainty estimation in deep learning for early oral cancer diagnosis. We develop a Bayesian deep learning model termed 'Probabilistic HRNet', which utilizes the ensemble MC dropout method on HRNet. Additionally, two oral lesion datasets with distinct distributions are created. We conduct a retrospective study to assess the predictive performance and uncertainty of Probabilistic HRNet across these datasets. Probabilistic HRNet performs optimally on the In-domain test set, achieving an F1 score of 95.3% and an AUC of 96.9% by excluding the top 30% high-uncertainty samples. For evaluations on the Domain-shift test set, the results show an F1 score of 64.9% and an AUC of 80.3%. After excluding 30% of the high-uncertainty samples, these metrics improve to an F1 score of 74.4% and an AUC of 85.6%. Redirecting samples with high uncertainty to experts for subsequent diagnosis significantly decreases the rates of misdiagnosis, which highlights that uncertainty estimation is vital to ensure safe decision making for computer-aided early oral cancer diagnosis.

Cu2+-doped zeolitic imidazolate frameworks and gold nanoparticle (AuNPs@ZIF-8/Cu) nanocomposites enable label-free and highly sensitive electrochemical detection of oral cancer-related biomarkers.

It is of great significance to accurately and sensitively detect oral cancer-related biomarkers (ORAOV 1) for the early diagnosis of oral cancer. Present here is a novel electrochemical biosensor based on Cu2+-doped zeolitic imidazolate frameworks and gold nanoparticle (AuNPs@ZIF-8/Cu) nanocomposites and a one-step strand displacement reaction for label-free, simple and sensitive detection of ORAOV 1 in saliva. It is worth noting that AuNPs@ZIF-8/Cu nanocomposites show large electrochemically effective surface area, good electrical conductivity and electrocatalytic activity due to the synergistic effect of metal nanoparticles (MNPs) and ZIF-8. Consequently, the newly developed electrochemical sensor displays a wide linear range of 0.1-104 pM and a low limit of detection (LOD) of 63 fM. Meanwhile, the electrochemical biosensor can distinguish single base mismatch. The relative standard deviation (RSD) of intra-assays and inter-assays is 1.46% and 1.76%, respectively, and the peak current values decline by 9.20% with a RSD value of 1.35% after being stored at 4 °C for 7 days, suggesting that the newly designed electrochemical sensor exhibits good selectivity, reproducibility and stability to detect ORAOV 1. More importantly, this novel electrochemical sensor is found to be applicable for detecting ORAOV 1 in human saliva samples with a satisfactory result. The RSD values range from 1.15% to 1.77%, and the recoveries range from 95.46% to 112.98%.

Early Diagnosis of Oral Cancer Using Image Processing and Artificial Intelligence

There has yet to be a comprehensive investigation on enhancing the diagnostic accuracy of oral disease using handheld smartphone photographic photos. To overcome the difficulties associated with the automatic detection of oral illnesses, we describe an approach based on smartphone image diagnosis powered by a deep learning algorithm. The centered rule method of image capture was offered as a quick and easy way to get high-quality pictures of the mouth. A resampling method was proposed to mitigate the influence of image variability from handheld smartphone cameras, and a medium-sized oral dataset with five types of disorders was developed based on this approach. Finally, we introduce a recently developed deep-learning network to assess oral cancer diagnosis. On 455 test images, the proposed technique showed an impressive 83.0% sensitivity, 96.6% specificity, 84.3% accuracy, and 83.6% F1. The proposed center positioning method was about 8% higher than a simulated random positioning method; the resampling process had an additional 6% performance improvement. The performance of a deep learning algorithm for detecting oral cancer can be enhanced by capturing oral photos centered on the lesion. Primary oral cancer diagnosis using smartphone-based images with deep learning offers promising potential.

Early diagnosis of oral cancer using a hybrid arrangement of deep belief networkand combined group teaching algorithm

Oral cancer can occur in different parts of the mouth, including the lips, palate, gums, and inside the cheeks. If not treated in time, it can be life-threatening. Incidentally, using CAD-based diagnosis systems can be so helpful for early detection of this disease and curing it. In this study, a new deep learning-based methodology has been proposed for optimal oral cancer diagnosis from the images. In this method, after some preprocessing steps, a new deep belief network (DBN) has been proposed as the main part of the diagnosis system. The main contribution of the proposed DBN is its combination with a developed version of a metaheuristic technique, known as the Combined Group Teaching Optimization algorithm to provide an efficient system of diagnosis. The presented method is then implemented in the “Oral Cancer (Lips and Tongue) images dataset” and a comparison is done between the results and other methods, including ANN, Bayesian, CNN, GSO-NN, and End-to-End NN to show the efficacy of the techniques. The results showed that the DBN-CGTO method achieved a precision rate of 97.71%, sensitivity rate of 92.37%, the Matthews Correlation Coefficient of 94.65%, and 94.65% F1 score, which signifies its ability as the highest efficiency among the others to accurately classify positive samples while remaining the independent correct classification of negative samples.

An attomolar-level electrochemical DNA biosensor based on target-triggered and entropy-driven catalytic amplification integrated with AuNPs@ZIF-8 nanocomposites for oral cancer overexpressed 1 detection

It is of great interest and necessity to develop a nonenzymatic, simple but highly sensitive biosensor for early diagnosis of oral cancer. Present here is an electrochemical DNA biosensor which integrates a target-triggered, entropy-driven, nonenzymatic and isothermal amplification strategy with gold nanoparticles/zeolitic imidazolate frameworks-8 (AuNPs@ZIF-8) nanocomposites for ultra-sensitive detection of oral cancer-related biomarker (ORAOV 1) in saliva. It is worth noting that the nuclease is not involved in the whole reaction process, which is simple and flexible in design only using a series of linear single-stranded DNA, avoiding undesired secondary structure interference. Meanwhile, due to the synergistic effect of AuNPs and ZIF-8, AuNPs@ZIF-8 nanocomposites display high stability, excellent electrical conductivity and exceptional electrocatalytic activity, further enhancing the electrochemical signal and avoiding labeling electrochemical signal probes. Experimental results demonstrate that this electrochemical DNA biosensor has a wide linear range (1 fM ∼1 nM), a low limit of detection (163 aM), excellent specificity, superior reproducibility and stability to ORAOV 1. More importantly, the actual application of the newly developed electrochemical biosensor is exemplified in human saliva with satisfactory recoveries. Therefore, the newly developed electrochemical biosensor has a broad application prospect in the nondestructive and early screening of oral cancer.

Evaluation of awareness of oral cancer and oral premalignant lesions in dentistry students: A three-center study

Objectives: This study aimed to evaluate the awareness of oral cancer and oral premalignant lesions in dentistry student at three different faculties. Materials and Methods: The question-based questionnaire study included 382 fourth- and fifth-year students (n=382; 239 females, 143 males) from three different dentistry faculties in Türkiye. A cross-sectional questionnaire consisting of 43 questions about oral premalignant lesions and oral cancer was administered to fourth- and fifth-year students to assess awareness of knowledge, attitudes, and practical approaches between May 2023 and June 2023. Results: A statistically significant difference was observed between male and female fourth-year students (p=0.024). The mean values of male students were higher than female students. The highest values in terms of knowledge in the fourth and fifth years were observed in the Uşak University. In the fifth-year students, the highest values in terms of attitude and practice were observed in the students of Uşak University. Fifth-year students of Uşak University showed higher values in terms of knowledge, attitude, and practice than fourth-year students. In terms of attitude, fifth-year students of Tokat University showed higher values than fourth-year students. In total, fifth-year students showed higher values in terms of knowledge and attitude than fourth-year students. Tokat University showed higher awareness of oral premalignant lesions than the other universities. Conclusion: Early diagnosis of oral cancer and oral premalignant lesions are among the important responsibilities of dentists. Increasing the awareness of dentists in this area can contribute to the solution of a prominent public health problem.

Protocol for correlation of histological risk assessment/scoring system with a depth of invasion in oral squamous cell carcinoma

Introduction: The commonest type of cancer in the head and neck region is oral squamous cell carcinoma (OSCC) due to its high rates of occurrence and mortality. The early diagnosis of oral cancer gives better prognosis. Brandwein-Gensler criteria predict the early stage of OSCC cases with a high risk of locoregional recurrence. Objectives: To correlate Brandwein-Gensler criteria and depth of invasion of OSCC with three-year survival. Methodology: In the study, hematoxylin-eosin (HE)-stained section slides will be used to evaluate Brandwein and Gensler criteria and depth of invasion in resected tissue specimens of OSCC cases. Expected results: The present study will find the correlation between Brandwein-Gensler criteria and depth of invasion in OSCC in order to evaluate the locoregional recurrence in OSCC cases. In high-risk OSCC cases, there may be increased depth of invasion in resected tissues. Conclusions: We hypothesized that the correlation between Brandwein-Gensler criteria and depth of invasion can be used as an independent predictor for locoregional recurrence in OSCC.

Oral cancer detection using convolutional neural network optimized by combined seagull optimization algorithm

Early diagnosis of oral cancer is crucial for improving patient outcomes and saving lives. However, inaccurate and improper diagnosis can hinder effective treatment. This paper presents a novel method for detecting oral cancer using an optimized version of Convolutional Neural Network (CNN). While basic CNNs have been widely used for image classification tasks, the incorporation of the Seagull Optimization Algorithm and Particle Swarm Optimization Algorithm in optimizing the CNN architecture specifically for oral cancer detection is a unique approach that is provided in this study. By combining these algorithms, the proposed method optimizes the CNN's architecture, parameters, and training process specifically for oral cancer detection. This optimization enhances the performance and accuracy of the CNN in identifying cancerous regions in oral images. Unlike previous approaches, our method incorporates advanced image processing techniques, including noise reduction, contrast enhancement, and data augmentation, to enhance the quality of input data extracted from the Oral Cancer (Lips and Tongue) images (OCI) dataset. The optimized CNN architecture uses its ability to learn intricate patterns and features from the enhanced images, enabling more accurate identification of cancerous regions. To evaluate the effectiveness of our approach, we compare it against Textural analysis, FCM, CNN, R-CNN, and ResNet-101 using four measurement indices. Results demonstrate that our proposed CSOA-based CNN system achieves the highest accuracy rate (96.94%) compared to other methods, indicating its superior performance in oral cancer detection. Furthermore, our precision rate of 94.65% and recall rate of 91.60% highlight the model's high correctness and positive classification ability. Finally, our proposed method achieves the highest F1-score (88.55%), emphasizing its superiority over other comparative methods. Through our innovative integration of the Seagull Optimization Algorithm and Particle Swarm Optimization Algorithm with CNN, coupled with advanced image processing techniques, we provide a reliable and effective solution for early detection of oral cancer.

ASSESSMENT OF KNOWLEDGE REGARDING EARLY SIGNS OF ORAL CANCER AMONG ADULTS IN SELECTED RURAL AND URBAN COMMUNITY, WEST BENGAL

Oral cancer is one of the public health problem in today’s world. It is one among the ten commonest cancers within the world. Recognition of early signs helps in early diagnosis of oral cancer and quick, successful, and less aggressive treatment or management. If the cancer is detected at an initial stage, then the 85% people can survive for 5-year.Aim: This study aims to assess the knowledge regarding early signs of oral cancer among adults in selected rural and urban community, West Bengal.Methods: A descriptive survey research was carried out with total 200 male adults aged 18 to 50 years, of selected rural and urban community, West Bengal. Data were collected through non probability purposive sampling technique. Validated structured interview schedule was used to collect data. Data were collected on adults’ demographic characteristics and knowledge regarding early signs of oral cancer.Result: The result revealed that in rural community most of the adults (50%) had average knowledge and in urban community most of the adults (37%) had good knowledge. There is significant difference between the knowledge scores among adults of rural and urban community (p&lt;0.001). Adults of urban community are more knowledgeable than adults of rural community. Chi- square test revealed that there was a significant association of knowledge with age, educational status (p&lt;0.001) and habit and addiction (p&lt;0.01) of rural adults and monthly family income, habit and addiction and information received by the adults of urban community are significantly associated with their knowledge (p&lt;0.001).Conclusion: There is the need to increase awareness in the community through educational programmes on early signs of oral cancer which will be helpful in early detection and diagnosis of same, as well as take timely precautionary measures to prevent oral cancer and thereby reducing the morbidity, mortality, and global burden of oral cancer.

The trend of oral cancer screening in Bangladesh, perceptions, and risk factors: a model comparison approach

Background: Oral cancer (OC) is a leading cause of death among cancer patients and a major public health concern in Bangladesh. Timely OC screening can help in the early detection of OC and could reduce the mortality rate in Bangladesh. We aimed to assess the tend of OC screening, perception and risk factors among dental patients. Methods: This was a facility-based cross-sectional study among 423 participants with dental problems using a convenience sampling technique. The collected data were analyzed by IBM SPSS 25 and various statistics, such as the chi-squared test, Poisson regression, logistic regression, etc., were used to attain the objectives. Results: Only 2.4% of the study participants underwent OC screening before the study period. The use of smokeless tobacco and smoking were significantly associated with the tend of OC screening. According to the Poisson model, previous smokeless tobacco users were 5 times (odds ratio (OR): 5.403, P&lt;0.05) more likely than non-users to go for OC screening, which was 8 times (OR: 7.729, P=0.033) for the binary logistic regression. Having a family history of OC increased the odds of receiving an OC screening by nine times (OR: 9.544, P&lt;0.002) compared to individuals without a family history of OC; it was 16 times (OR: 16.438, P=0.001) for the binary logistic regression. Conclusions: This study shows former smokeless tobacco users and past smokers are more likely to uptake OC screening than non-users. In addition, patients having a family history of OC increased the odds of receiving OC screening than subjects without a family history of OC. The lack of OC screening in Bangladesh highlights the need to implement a national-level screening program to help with the early diagnosis of OC and its prevention.

Evaluation of salivary Chemerin in oral leukoplakia, oral squamous cell carcinoma and healthy controls

Introduction: Chemerin is a multifunctional chemoattractant cytokine, encoded by RARRES2 gene. Its role in oral carcinogenesis is largely unexplored. Study was undertaken to evaluate the role of salivary chemerin as a potential biomarker in the early diagnosis of oral cancer and to elucidate the clinicopathologic and prognostic significance of chemerin in different grades of Oral Squamous Cell Carcinoma (OSCC) and oral leukoplakia. Materials and Methods: The study comprised 96 subjects, divided into 3 groups, each consisting of 32 subjects. These groups were clinically and histopathologically diagnosed with OSCC, oral leukoplakia, and healthy controls, respectively. The whole unstimulated saliva (1.5 mL) was collected from the subjects using passive drool technique and immediately centrifuged at 3000 rpm for 10 minutes. The salivary chemerin level was estimated using the competitive sandwich enzyme-linked immunosorbent assay method. The statistical analysis was performed using R software EZR version 1.32. Independent t-tests, analysis of variance tests, and Scheffe Multiple Comparisons were carried out to compare quantitative parameters. A receiver operating characteristic (ROC) curve was plotted to assess diagnostic accuracy of salivary chemerin. Results: Significantly higher levels of salivary chemerin were observed in OSCC and oral leukoplakia patients compared to healthy controls (P &lt; 0.05). The study further established an increase in salivary chemerin concentration in different histological grades of OSCC and oral leukoplakia. ROC curve analysis suggested that salivary chemerin is a highly sensitive and specific indicator for early screening and detection of oral leukoplakia and OSCC. Conclusion: Salivary chemerin can be considered as a reliable and specific indicator for the early screening and detection of oral leukoplakia and OSCC and a highly sensitive biomarker which may aid in detection of malignant transformation of oral leukoplakia.

Early Diagnosis of Oral Cancer: A Complex Polyhedral Problem with a Difficult Solution.

Oral and oropharyngeal cancers are a growing problem, accounting for 377,713 and 98,412 new cases per year all over the world and 177,757 and 48,143 deaths annually, respectively. Despite the substantial improvement in diagnostic procedures and treatment techniques in recent years, the mortality rate has not decreased substantially in the last 40 years, which is still close to 50% of cases. The major cause responsible for this high mortality is associated with the high percentage of oral cancers diagnosed in advanced stages (stages III and IV) where the treatment harbors poor efficacy, resulting in challenges, mutilations, or disability. The main reason for cancer to be diagnosed at an advanced stage is a diagnostic delay, so it is critical to reduce this delay in order to improve the prognosis of patients suffering from oral cancer. The causes of oral cancer diagnostic delay are complex and concern patients, healthcare professionals, and healthcare services. In this manuscript, oral cancer diagnostic delay is critically reviewed based on current evidence, as well as their major causes, main problems, and potential improvement strategies.

Oral cancer and the importance of the dental surgeon for early diagnosis

Between 2016 and 2017, more than 600 thousand new cases of cancer occurred in Brazil, with emphasis on oral cancer occupying the fifth place of incidence among men and seventh among women. Based on these data, the study aims to demonstrate the importance of dental surgeons in the early diagnosis of oral cancer, described, through the literature review, as characteristics of potentially fundamental cancerous oral lesions to be recognized and differentiated by these professionals. It is concluded that with the techniques of clinical examination and anamnesis, the dentist plays a fundamental role in the levels of primary and secondary prevention, in the detection of risky behavior and in the application of resources that enable the diagnosis of a malignant lesion at an early stage.

A novel 3-miRNA network regulates tumour progression in oral squamous cell carcinoma

BackgroundLate diagnosis is one of the major confounders in oral squamous cell carcinoma (OSCC). Despite recent advances in molecular diagnostics, no disease-specific biomarkers are clinically available for early risk prediction of OSCC. Therefore, it is important to identify robust biomarkers that are detectable using non-invasive liquid biopsy techniques to facilitate the early diagnosis of oral cancer. This study identified potential salivary exosome-derived miRNA biomarkers and crucial miRNA-mRNA networks/underlying mechanisms responsible for OSCC progression.MethodsSmall RNASeq (n = 23) was performed in order to identify potential miRNA biomarkers in both tissue and salivary exosomes derived from OSCC patients. Further, integrated analysis of The Cancer Genome Atlas (TCGA) datasets (n = 114), qPCR validation on larger patient cohorts (n = 70) and statistical analysis with various clinicopathological parameters was conducted to assess the effectiveness of the identified miRNA signature. miRNA-mRNA networks and pathway analysis was conducted by integrating the transcriptome sequencing and TCGA data. The OECM-1 cell line was transfected with the identified miRNA signature in order to observe its effect on various functional mechanisms such as cell proliferation, cell cycle, apoptosis, invasive as well as migratory potential and the downstream signaling pathways regulated by these miRNA-mRNA networks.ResultsSmall RNASeq and TCGA data identified 12 differentially expressed miRNAs in OSCC patients compared to controls. On validating these findings in a larger cohort of patients, miR-140-5p, miR-143-5p, and miR-145-5p were found to be significantly downregulated. This 3-miRNA signature demonstrated higher efficacy in predicting disease progression and clinically correlated with poor prognosis (p < 0.05). Transcriptome, TCGA, and miRNA-mRNA network analysis identified HIF1a, CDH1, CD44, EGFR, and CCND1 as hub genes regulated by the miRNA signature. Further, transfection-mediated upregulation of the 3-miRNA signature significantly decreased cell proliferation, induced apoptosis, resulted in G2/M phase cell cycle arrest and reduced the invasive and migratory potential by reversing the EMT process in the OECM-1 cell line.ConclusionsThus, this study identifies a 3-miRNA signature that can be utilized as a potential biomarker for predicting disease progression of OSCC and uncovers the underlying mechanisms responsible for converting a normal epithelial cell into a malignant phenotype.

Opal photonic crystal-enhanced upconversion turn-off fluorescent immunoassay for salivary CEA with oral cancer.

The point-of-care test of tumor markers in saliva with high specificity and sensitivity for early diagnosis of oral cancer is of great interest and significance, but remaining a daunting challenge due to the low concentration of such biomarkers in oral fluid. Herein, a turn-off biosensor based on opal photonic crystal (OPC) enhanced upconversion fluorescence is proposed to detect the carcinoembryonic antigen (CEA) in saliva by applying fluorescence resonance energy transfer sensing strategy. Hydrophilic PEI ligands are modified on upconversion nanoparticles to enhance the sensitivity of biosensor by promoting sufficient contact between saliva and detection region. As a substrate for the biosensor, OPC can also provide a local-field effect for greatly enhanced upconversion fluorescence by coupling the stop band and excitation light, and a 66-fold amplification of the upconversion fluorescence signal was obtained. For the CEA detection in spiked saliva, such sensors showed a favorable linear relationship at 0.1-2.5ngmL-1 and more than 2.5ngmL-1, respectively. The limit of detection was down to 0.1ngmL-1. Moreover, by monitoring real saliva, the effective discrepancy between patients and healthy people was confirmed, indicating remarkable practical application value in clinical early diagnosis and home-based self-monitoring of tumors.

Brush Cytology on Pre-Malignant and Malignant Oral Lesions with Histopathological correlation

Introduction: Oral cancer is the sixth most common malignancy worldwide and accounts for 30% of all cancers in India, with 5-year survival rate, except when diagnosed in the early stages. Hence, early diagnosis of oral cancer is very much essential for the sake of the patient. However its burden on the economy for providinghealthcare is substantial and with the increasing incidence of oral cancer in developing countries like India and the other South-East-Asian countries, the role of screening methodologies for early detection of pre – cancerous and cancerous lesions of oral cavity are becoming more vital&#x0D; Methodology: An observational cross-sectional study conducted in the departments of Otolaryngology &amp; head neck surgery in close association with department of Pathology in a tertiary based teaching institute in North Bengal, India, during April 2021 to March 2022. All the patients aged above 18 years, who visited the outpatient department of Otolaryngology &amp; Head Neck Surgery, and admitted in the ward of the same, having oral lesions which are clinically suspected as pre- malignant and malignant lesions were included in this study.&#x0D; Results: The study population comprised of total 69 cases. Among them 47 cases (~68%) were malignantlesions, 13 (~19%) cases were pre-malignant and 9 (~13%) cases were diagnosed as benign lesions consideringHistopathology result. 30 (63.8%) out of 47 malignant cases show class-5 cytological grading in brush cytology smear, stained with Pap stain. 25.5% of the malignant cases were in class-4 and 10.6% cases were in class-3 whereas, in premalignant cases (n=13), 3 cases were in class-2 and 7 cases were in class-3 and 3 were in class-1. Maximum value of AgNOR counts for benign, pre malignant and malignant lesions were 3.54, 4.16, 7.28 respectively.&#x0D; Conclusion: The brush cytology with PAP grading and AgNOR analysis in clinically suspected oral lesionscan be used as an early diagnostic tool for diagnosing oral squamous cell carcinoma especially for lower socio-economic status people who present with late stages.

Early Diagnosis of Oral Cancer and Lesions in Fanconi Anemia Patients: A Prospective and Longitudinal Study Using Saliva and Plasma.

Fanconi anemia (FA) patients display an exacerbated risk of oral squamous cell carcinoma (OSCC) and oral potentially malignant lesions (OPMLs) at early ages. As patients have defects in their DNA repair mechanisms, standard-of-care treatments for OSCC such as radiotherapy and chemotherapy, give rise to severe toxicities. New methods for early diagnosis are urgently needed to allow for treatment in early disease stages and achieve better clinical outcomes. We conducted a prospective, longitudinal study wherein liquid biopsies from sixteen patients with no clinical diagnoses of OPML and/or OSCC were analyzed for the presence of mutations in cancer genes. The DNA from saliva and plasma were sequentially collected and deep-sequenced, and the clinical evaluation followed over a median time of approximately 2 years. In 9/16 FA patients, we detected mutations in cancer genes (mainly TP53) with minor allele frequencies (MAF) of down to 0.07%. Importantly, all patients that had mutations and clinical follow-up data after mutation detection (n = 6) developed oral precursor lesions or OSCC. The lead-time between mutation detection and tumor diagnosis ranged from 23 to 630 days. Strikingly, FA patients without mutations displayed a significantly lower risk of developing precursor lesions or OSCCs. Therefore, our diagnostic approach could help to stratify FA patients into risk groups, which would allow for closer surveillance for OSCCs or precursor lesions.

A Simple and Sensitive Electrochemical Sandwich‐Like Immunosensor for Interleukin‐8 Utilizing Carbon Black as a Sensing Platform and Silver‐Ferrocene as a Signal Amplifier

AbstractDesigning sensitive and low‐cost method for interleukin‐8 (IL‐8) determination is of great significance in the early diagnosis of oral cancer. In the present work, a simple, low‐cost and sensitive sandwich‐like electrochemical immunosensor of IL‐8 was developed by introducing perylene tetracarboxylic acid‐carbon black (PTCA‐CB) as sensing platform and silver‐ferrocene (Ag−Fc) as signal amplifier. PTCA‐CB can offer large surface area and high conductivity as well as the stable supporter to assemble primary antibody (Ab1), while Ag could carry Fc probe and secondary antibodies (Ab2) to produce Ab2−Ag−Fc signal amplifier. In the presence of IL‐8 with different concentrations, the peak currents from the formed sandwich‐like structure Ab2−Ag−Fc/IL‐8/Ab1/CB can increase with the increase of IL‐8 concentration, a sensitive and low‐cost electrochemical immunosensor for IL‐8 was thus constructed based on this principle. After optimizing the related control conditions, a wide linear range (3.0 pg mL−1 to 2.0 ng mL−1) and very low detection limit (1.0 pg mL−1) were achieved, it's thus convinced the developed sensor has important clinical applications.