Theoretical Background to Automated Diagnosing of Oral Leukoplakia: A Preliminary Report
Ontology highlight
ABSTRACT:
SUBMITTER: Jurczyszyn K
PROVIDER: S-EPMC7509569 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The unsupervised hierarchical clustering analysis of the 122 miRNAs revealed a marked separation of mtOLK from OLK, suggesting that this differential expression profile might be used as a possible phenotypic discriminator between OLK and mtOLK.Comparing with OLK, 72 up-regulated and 50 down-regulated miRNAs were found in the mtOLK (p < 0.01) In the study presented here,20 OLK（OLK), 5 mtOLK（Ca） tissues and 5 normal mucousal tissues（N） were examined by miRNA array
2011-11-02 | E-GEOD-33299 | biostudies-arrayexpress
Project description:The unsupervised hierarchical clustering analysis of the 122 miRNAs revealed a marked separation of mtOLK from OLK, suggesting that this differential expression profile might be used as a possible phenotypic discriminator between OLK and mtOLK.Comparing with OLK, 72 up-regulated and 50 down-regulated miRNAs were found in the mtOLK (p < 0.01)
2011-11-02 | GSE33299 | GEO
Project description:Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.
| S-EPMC5542248 | biostudies-other
Project description:Objective: While some oral carcinomas appear to arise de novo, others develop within long-standing conditions of the oral cavity that have malignant potential, now known as oral potentially malignant disorders (OPMDs). The oral bacteriome associated with OPMD has been studied to a lesser extent than that associated with oral cancer. To characterize the association in detail we compared the bacteriome in whole mouth fluid (WMF) in patients with oral leukoplakia, oral cancer and healthy controls. Methods: WMF bacteriome from 20 leukoplakia patients, 31 patients with oral cancer and 23 healthy controls were profiled using the Illumina MiSeq platform. Sequencing reads were processed using DADA2, and taxonomical classification was performed using the phylogenetic placement method. Sparse Partial Least Squares Regression Discriminant Analysis model was used to identify bacterial taxa that best discriminate the studied groups. Results: We found considerable overlap between the WMF bacteriome of leukoplakia and oral cancer while a clearer separation between healthy controls and the former two disorders was observed. Specifically, the separation was attributed to 14 taxa belonging to the genera Megaspheara, unclassified enterobacteria, Prevotella, Porphyromonas, Rothia and Salmonella, Streptococcus, and Fusobacterium. The most discriminative bacterial genera between leukoplakia and oral cancer were Megasphaera, unclassified Enterobacteriae, Salmonella and Prevotella. Conclusion: Oral bacteria may play a role in the early stages of oral carcinogenesis as a dysbiotic bacteriome is associated with oral leukoplakia and this resembles that of oral cancer more than healthy controls. Our findings may have implications for developing oral cancer prevention strategies targeting early microbial drivers of oral carcinogenesis.
| S-EPMC7734041 | biostudies-literature
Project description:BackgroundThe grading of oral epithelial dysplasia is often time-consuming for oral pathologists and the results are poorly reproducible between observers. In this study, we aimed to establish an objective, accurate and useful detection and grading system for oral epithelial dysplasia in the whole-slides of oral leukoplakia.MethodsFour convolutional neural networks were compared using the image patches from 56 whole-slide of oral leukoplakia labeled by pathologists as the gold standard. Sequentially, feature detection models were trained, validated and tested with 1,000 image patches using the optimal network. Lastly, a comprehensive system named E-MOD-plus was established by combining feature detection models and a multiclass logistic model.ResultsEfficientNet-B0 was selected as the optimal network to build feature detection models. In the internal dataset of whole-slide images, the prediction accuracy of E-MOD-plus was 81.3% (95% confidence interval: 71.4-90.5%) and the area under the receiver operating characteristic curve was 0.793 (95% confidence interval: 0.650 to 0.925); in the external dataset of 229 tissue microarray images, the prediction accuracy was 86.5% (95% confidence interval: 82.4-90.0%) and the area under the receiver operating characteristic curve was 0.669 (95% confidence interval: 0.496 to 0.843).ConclusionsE-MOD-plus was objective and accurate in the detection of pathological features as well as the grading of oral epithelial dysplasia, and had potential to assist pathologists in clinical practice.
| S-EPMC11005210 | biostudies-literature
Project description:BACKGROUND: The construction of a whole-genome physical map has been an essential component of numerous genome projects initiated since the inception of the Human Genome Project. Its usefulness has been proved for whole-genome shotgun projects as a post-assembly validation and recently it has also been used in the assembly step to constrain on BACs positions. Fingerprinting is usually the method of choice for construction of physical maps. A clone fingerprint is composed of true peaks representing real fragments and background peaks, mainly composed of E. coli genomic DNA, partial digestions, star activity by-products, and machine background. High-throughput fingerprinting leads to the production of thousands of BAC clone fingerprints per day. That is why background peaks removal has become an important issue and needs to be automatized, especially in capillary electrophoresis based fingerprints. RESULTS: At the moment, the only tools available for such a task are GenoProfiler and its descendant FPMiner. The large variation in the quality of fingerprints that is usually present in large fingerprinting projects represents a major difficulty in the correct removal of background peaks that has only been partially addressed by the methods so far adopted that all require a long manual optimization of parameters. Thus, we implemented a new data-independent tool, FPB (FingerPrint Background removal), suitable for large scale projects as well as mapping of few clones. CONCLUSION: FPB is freely available at http://www.appliedgenomics.org/tools.php. FPB was used to remove the background from all fingerprints of three grapevine physical map projects. The first project consists of about 50,000 fingerprints, the second one consists of about 70,000 fingerprints, and the third one consists of about 45,000 fingerprints. In all cases a successful assembly was built.
| S-EPMC2689866 | biostudies-other
Project description:Background/purpose:Oral submucous fibrosis (OSF) is a potentially malignant disorder of oral squamous cell carcinoma (SCC). In this study, we obtained the genetic expression signatures of OSF and SCC by microarray analysis. Materials and methods:Five patients with clinically evident OSF, five patients with SCC who also had existing OSF, and four normal volunteers who did not have a history of chewing betel quids were recruited. Biopsy specimens were obtained with an approved Institutional Review Board protocol. Total RNA from OSF or SCC was isolated and hybridized to a Human Oligo 1A (V2) Microarray (G4110B) chip against normal control RNA that was pooled from the four healthy volunteers. Results:We found similar, but distinct genetic expression signatures for OSF and SCC. At the hierarchical clustering analysis, 24 known genes (23 upregulated and 1 downregulated) in OSF were differentially expressed consistently in all participants. Among the genes, XRCC5 was cloned and transfected into oral cancer GNM cells. The results demonstrated that the overexpression of XRCC5 increased the resistance of GNM cells to low-density X-ray irradiation and promoted the cell growth rate. Conclusion:The distinct but similar genetic expression signatures seen in OSF and SCC suggested that this expression may be used as a supplemental diagnostic tool in pathology practice. This preliminary study showed that the XRCC5 gene promoted GNM cell growth and conferred resistance to low-density X-ray irradiation. Further studies on the effect of XRCC5 in oral cancer cells are in progress.
| S-EPMC6395281 | biostudies-literature
Project description:Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma (OSCC). Test outcome is reported as "negative", "atypical" (defined as abnormal epithelial changes of uncertain diagnostic significance), and "positive" (defined as definitive cellular evidence of epithelial dysplasia or carcinoma). The major challenge is how to properly manage the "atypical" patients in order to diagnose OSCC early and prevent OSCC. In this study, we collected exfoliative cytology data, histopathology data, and clinical data of normal subjects (n=102), oral leukoplakia (OLK) patients (n=82), and OSCC patients (n=93), and developed a data analysis procedure for quantitative risk stratification of OLK patients. This procedure involving a step called expert-guided data transformation and reconstruction (EdTAR) which allows automatic data processing and reconstruction and reveals informative signals for subsequent risk stratification. Modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Among the several models tested using resampling methods for parameter pruning and performance evaluation, Support Vector Machine (SVM) was found to be optimal with a high sensitivity (median>0.98) and specificity (median>0.99). With the SVM model, we constructed an oral cancer risk index (OCRI) which may potentially guide clinical follow-up of OLK patients. One OLK patient with an initial OCRI of 0.88 developed OSCC after 40 months of follow-up. In conclusion, we have developed a statistical method for qualitative risk stratification of OLK patients. This method may potentially improve cost-effectiveness of clinical follow-up of OLK patients, and help design clinical chemoprevention trial for high-risk populations.
| S-EPMC4433206 | biostudies-literature
Project description:ObjectivesTo identify possible associations between patients' demographics and habits and the clinical aspects and histopathological characteristics of oral leukoplakia (OL) at patients' first visit.MethodA total of 140 consecutive patients with OL at a single institute between 1997 and 2019. All biopsies were microscopically examined for classic dysplasia (CD) (WHO definition oral epithelial dysplasia) and differentiated dysplasia (DD) known from differentiated vulvar intraepithelial neoplasia. Clinical characteristics were correlated to histopathological diagnosis and odds ratios (OR) were calculated.ResultsA total of 96 females and 44 males, mean age 58 years, were presented. OLs were found mainly on the tongue (41%) and floor of mouth (FOM) (18%). Homogeneous OLs (58%) were associated with smoking, FOM and size <2cm and non-homogeneous OLs (42%) with non-smokers. No dysplasia was present in 40% and any dysplasia (AD) in 60%. Tongue OLs were correlated with AD (OR:6.0) and CD (OR:5.7). FOM OLs were correlated with CD (OR:4.5). DD was correlated with non-homogeneous OLs (OR:2.6).ConclusionsCD was most frequently observed in tongue and FOM OLs, while DD was associated with non-homogeneous OLs. In this series of patients, there was no consistent reliable association between the clinical and histopathological features and clinical characteristics can therefore not substitute microscopic examination of biopsies.
| S-EPMC10078678 | biostudies-literature
Project description:Fanconi anemia (FA) is a rare genetic disease involving an increased risk of developing acute myeloid leukemia and solid tumors, especially head-and-neck squamous cell carcinomas, for which the oral cavity is the most frequent site of occurrence. The patient presented in this study underwent allogeneic hematopoietic stem cell transplantation (HSCT) and developed nonhomogeneous oral leukoplakia after 7 years, which was promptly removed and diagnosed with high-grade epithelial dysplasia. Many risk conditions for oral squamous cell carcinoma were featured in the present case including FA, allogeneic HSCT, graft-versus-host disease, immunosuppressive therapy, female gender, nonsmoker, tongue location and nonhomogeneous type of leukoplakia. Close follow-up of the entire upper aerodigestive tract mucosa and early removal of all suspected lesions are highly recommended in the management of such patients.
| S-EPMC9017844 | biostudies-literature