scholarly journals Deep Learning-Based Pixel-Wise Lesion Segmentation on Oral Squamous Cell Carcinoma Images

2020 ◽  
Vol 10 (22) ◽  
pp. 8285
Author(s):  
Francesco Martino ◽  
Domenico D. Bloisi ◽  
Andrea Pennisi ◽  
Mulham Fawakherji ◽  
Gennaro Ilardi ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Deep Learning ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Ground Truth ◽  
Lesion Segmentation ◽  
Ground Truth Data ◽  
Tcga Dataset

Oral squamous cell carcinoma is the most common oral cancer. In this paper, we present a performance analysis of four different deep learning-based pixel-wise methods for lesion segmentation on oral carcinoma images. Two diverse image datasets, one for training and another one for testing, are used to generate and evaluate the models used for segmenting the images, thus allowing to assess the generalization capability of the considered deep network architectures. An important contribution of this work is the creation of the Oral Cancer Annotated (ORCA) dataset, containing ground-truth data derived from the well-known Cancer Genome Atlas (TCGA) dataset.

Zinc α-2 Glycoprotein (ZAG) a Novel Biomarker for the Detection of Oral Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Mehwish Feroz Ali
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Malignant Lesion ◽  
Tobacco Consumption ◽  
Constant Stimulus ◽  
Dysplastic Lesion ◽  
Cancerous Lesion

Oral cancer, the most challenging and life threatening disease in the field of dentistry, may start as a reactive lesion due to constant stimulus from tobacco consumption, transform into a pre-malignant lesion (dysplastic lesion) and ultimately develop into a cancerous lesion (Invasive carcinoma). There is a fundamental revolution taking place in the analyzing methods; extraction of biological protein from the saliva rather than from tissues or blood. Several of the biomarkers have been studied with pro-carcinogenic effects like Interleukins (ILs), tumor necrosis factor (TNF) and leptin, but only a few have been stated in the literature, which show anti-cancer characteristics like adiponectin and zinc alpha-2 glycoprotein. This review explored the diagnostic and prognostic values of a biomarkers zinc alpha-2 glycoprotein (ZAG) in adults suspected of oral squamous cell carcinoma (OSCC). The PubMed, EMBASE and Google Scholar were searched for scientific studies reported on the potential mechanism of zinc alpha-2 glycoprotein. All the research articles were selected in which ZAG is applied solely or in conjunction with other biomarkers in oral cancer and other cancers. These literatures were carefully assessed to find out and compile the diagnostic and prognostic values and to inquire therapeutic action of ZAG in the process of carcinogenesis.

scholarly journals Downregulation of ceramide synthase 1 promotes oral cancer through endoplasmic reticulum stress

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Wen Chen ◽  
Chenzhou Wu ◽  
Yafei Chen ◽  
Yuhao Guo ◽  
Ling Qiu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Endoplasmic Reticulum ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Endoplasmic Reticulum Stress ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Migration And Invasion ◽  
Ceramide Synthase

AbstractC18 ceramide plays an important role in the occurrence and development of oral squamous cell carcinoma. However, the function of ceramide synthase 1, a key enzyme in C18 ceramide synthesis, in oral squamous cell carcinoma is still unclear. The aim of our study was to investigate the relationship between ceramide synthase 1 and oral cancer. In this study, we found that the expression of ceramide synthase 1 was downregulated in oral cancer tissues and cell lines. In a mouse oral squamous cell carcinoma model induced by 4-nitroquinolin-1-oxide, ceramide synthase 1 knockout was associated with the severity of oral malignant transformation. Immunohistochemical studies showed significant upregulation of PCNA, MMP2, MMP9, and BCL2 expression and downregulation of BAX expression in the pathological hyperplastic area. In addition, ceramide synthase 1 knockdown promoted cell proliferation, migration, and invasion in vitro. Overexpression of CERS1 obtained the opposite effect. Ceramide synthase 1 knockdown caused endoplasmic reticulum stress and induced the VEGFA upregulation. Activating transcription factor 4 is responsible for ceramide synthase 1 knockdown caused VEGFA transcriptional upregulation. In addition, mild endoplasmic reticulum stress caused by ceramide synthase 1 knockdown could induce cisplatin resistance. Taken together, our study suggests that ceramide synthase 1 is downregulated in oral cancer and promotes the aggressiveness of oral squamous cell carcinoma and chemotherapeutic drug resistance.

scholarly journals Salivary LDOC1 is a gender-difference biomarker of oral squamous cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6732 ◽  
Author(s):  
Chung-Ji Liu ◽  
Jen-Hao Chen ◽  
Shih-Min Hsia ◽  
Chiu-Chu Liao ◽  
Hui-Wen Chang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Suppressor Gene ◽  
Clinicopathological Characteristics ◽  
Pcr Analysis ◽  
Expression Levels ◽  
Low Levels

Background The X-linked tumor suppressor gene LDOC1 is reported to be involved in oral cancer. The detection of biomarkers in salivary RNA is a non-invasive strategy for diagnosing many diseases. The aim of the present study was to investigate the potential of salivary LDOC1 as a biomarker of oral cancer. Methods We determined the expression levels of LDOC1 in the saliva of oral squamous cell carcinoma (OSCC) subjects, and investigated its correlation with various clinicopathological characteristics. The expression levels of salivary LDOC1 were detected in 53 OSCC subjects and 43 healthy controls using quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis. We used Fisher’s exact test to analyze the correlations between expression levels and clinicopathological characteristics. Results Salivary LDOC1 was significantly upregulated in females with OSCC (p = 0.0072), and significantly downregulated in males with OSCC (p = 0.0206). Eighty-nine percent of male OSCC subjects who smoked expressed low levels of LDOC1. OSCC cell lines derived from male OSCC subjects expressed low levels of LDOC1. Conclusions A high level of salivary LDOC1 expression is a biomarker of OSCC in females. A high percentage of male OSCC subjects who smoke express low levels of salivary LDOC1. A low level of salivary LDOC1 expression is a biomarker of OSCC in males.

scholarly journals Deep Machine Learning for Oral Cancer: From Precise Diagnosis to Precision Medicine

2022 ◽  
Vol 2 ◽  
Author(s):  
Rasheed Omobolaji Alabi ◽  
Alhadi Almangush ◽  
Mohammed Elmusrati ◽  
Antti A. Mäkitie
Keyword(s):  
Machine Learning ◽  
Squamous Cell Carcinoma ◽  
Deep Learning ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Precision Medicine ◽  
Treatment Planning ◽  
Squamous Cell ◽  
Early Stage ◽  
Learning Technology

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide and its incidence is on the rise in many populations. The high incidence rate, late diagnosis, and improper treatment planning still form a significant concern. Diagnosis at an early-stage is important for better prognosis, treatment, and survival. Despite the recent improvement in the understanding of the molecular mechanisms, late diagnosis and approach toward precision medicine for OSCC patients remain a challenge. To enhance precision medicine, deep machine learning technique has been touted to enhance early detection, and consequently to reduce cancer-specific mortality and morbidity. This technique has been reported to have made a significant progress in data extraction and analysis of vital information in medical imaging in recent years. Therefore, it has the potential to assist in the early-stage detection of oral squamous cell carcinoma. Furthermore, automated image analysis can assist pathologists and clinicians to make an informed decision regarding cancer patients. This article discusses the technical knowledge and algorithms of deep learning for OSCC. It examines the application of deep learning technology in cancer detection, image classification, segmentation and synthesis, and treatment planning. Finally, we discuss how this technique can assist in precision medicine and the future perspective of deep learning technology in oral squamous cell carcinoma.

scholarly journals Saliva protein biomarkers to detect oral squamous cell carcinoma in a high-risk population in Taiwan

2016 ◽  
Vol 113 (41) ◽  
pp. 11549-11554 ◽  
Author(s):  
Jau-Song Yu ◽  
Yi-Ting Chen ◽  
Wei-Fan Chiang ◽  
Yung-Chin Hsiao ◽  
Lichieh Julie Chu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Low Risk ◽  
Healthy Controls ◽  
Protein Biomarkers

Most cases of oral squamous cell carcinoma (OSCC) develop from visible oral potentially malignant disorders (OPMDs). The latter exhibit heterogeneous subtypes with different transformation potentials, complicating the early detection of OSCC during routine visual oral cancer screenings. To develop clinically applicable biomarkers, we collected saliva samples from 96 healthy controls, 103 low-risk OPMDs, 130 high-risk OPMDs, and 131 OSCC subjects. These individuals were enrolled in Taiwan’s Oral Cancer Screening Program. We identified 302 protein biomarkers reported in the literature and/or through in-house studies and prioritized 49 proteins for quantification in the saliva samples using multiple reaction monitoring-MS. Twenty-eight proteins were successfully quantified with high confidence. The quantification data from non-OSCC subjects (healthy controls + low-risk OPMDs) and OSCC subjects in the training set were subjected to classification and regression tree analyses, through which we generated a four-protein panel consisting of MMP1, KNG1, ANXA2, and HSPA5. A risk-score scheme was established, and the panel showed high sensitivity (87.5%) and specificity (80.5%) in the test set to distinguish OSCC samples from non-OSCC samples. The risk score >0.4 detected 84% (42/50) of the stage I OSCCs and a significant portion (42%) of the high-risk OPMDs. Moreover, among 88 high-risk OPMD patients with available follow-up results, 18 developed OSCC within 5 y; of them, 77.8% (14/18) had risk scores >0.4. Our four-protein panel may therefore offer a clinically effective tool for detecting OSCC and monitoring high-risk OPMDs through a readily available biofluid.

Upregulated histone deacetylase 2 gene correlates with the progression of oral squamous cell carcinoma

2020 ◽  
Vol 29 (4) ◽  
pp. 543-552
Author(s):  
Akhilesh Krishna ◽  
Vineeta Singh ◽  
Shraddha Singh ◽  
Sachil Kumar ◽  
Vijay Kumar ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Protein Level ◽  
Histone Deacetylases ◽  
Cellular Proliferation ◽  
Mrna Levels ◽  
Histone Deacetylase 2

BACKGROUND: Histone deacetylases (HDACs) are considered as an essential regulator of cellular proliferation, differentiation, and apoptosis. The HDAC2 enzyme of Class I HDACs plays an important role in tumor progression of human malignancies. OBJECTIVE: The aim of the present study was to analyze the HDAC2 gene expression in pre-oral cancer and oral squamous cell carcinoma (OSCC), and its association with clinico-pathological features. METHODS: The HDAC2 protein expression was analyzed through the immunohistochemistry and western blot techniques in 82 oral pre-malignant, 90 OSCC, and 16 normal control tissues. qRT-PCR was used to quantify the mRNA fold change in all groups. RESULTS: The HDAC2 protein and mRNA levels were significantly higher in OSCC and pre-oral cancer groups compared to the controls. Immunostaining of HDAC2 protein was enhanced in 84.4% of OSCC and 67.1% of pre-cancerous tissue sections (p< 0.01). The mean protein level was analyzed as 1.96 ± 0.44 in oral carcinoma, 1.61 ± 0.39 in pre-cancer and 0.96 ± 0.10 in control tissues. In addition, HDAC2 mean protein level was associated with histological differentiation (OR = 25, p< 0.05) and tumor-node-metastasis (TNM) stages (OR = 6.2, p< 0.05) of OSCC patients. CONCLUSIONS: The upregulated HDAC2 gene in pre-cancer and OSCC tissues indicates its crucial role in the transformation of pre-malignant to malignant carcinoma. It could be a potential cancer biomarker of prognosis and targeted therapy in OSCC.

scholarly journals β-Catenin/CBP inhibition alters epidermal growth factor receptor fucosylation status in oral squamous cell carcinoma

2020 ◽  
Vol 16 (3) ◽  
pp. 195-209 ◽  
Author(s):  
Kevin Brown Chandler ◽  
Khalid A. Alamoud ◽  
Vanessa L. Stahl ◽  
Bach-Cuc Nguyen ◽  
Vinay K. Kartha ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Epidermal Growth Factor Receptor ◽  
Growth Factor ◽  
Oral Cancer ◽  
Epidermal Growth Factor ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Growth Factor Receptor ◽  
Epidermal Growth

Genomic and structural analyses reveal that β-catenin/CBP signaling represses epidermal growth factor receptor (EGFR) N-glycan antennary fucosylation in oral cancer.

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