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1.
Oral Dis ; 2023 Mar 09.
Article in English | MEDLINE | ID: mdl-36892444

ABSTRACT

OBJECTIVE: Proliferative verrucous leukoplakia (PVL) has high rates of malignant transformation into oral squamous cell carcinoma (OSCC), but the clinical and evolutionary pattern of OSCC from PVL (PVL-OSCC) is more favorable than that of OSCC not preceded by PVL (OSCC). Here, we aimed to explore the pathophysiologic differences between PVL-OSCC and OSCC through transcriptomic and DNA methylation analyses. MATERIALS AND METHODS: In this case-control study, oral biopsies from 8 PVL-OSCC and 10 OSCC patients were obtained for global sequencing using RNAseq and a genome-wide DNA methylation analysis via the Infinium EPIC Platform (graphical abstract). RESULTS: One hundred and thirty-three differentially expressed genes (DEGs) were detected, 94 of them upregulated in OSCC. Most of these genes were previously described in cancer and associated with prognosis. The integrative analysis revealed 26 DEGs, corresponding to 37 CpGs, whose promoters were regulated by DNA methylation. Twenty-nine of the CpGs were found as hypermethylated in PVL-OSCC. Only 5 of the genes that were aberrantly methylated and differentially expressed were upregulated in PVL-OSCC patients, whereas 21 were underexpressed. CONCLUSIONS: PVL-OSCC patients presented lower expression of cancer-related genes. Hypermethylation of the promoter region of many genes was also noticed, indicating that DNA methylation could be a regulatory mechanism.

2.
Int J Mol Sci ; 24(4)2023 Feb 09.
Article in English | MEDLINE | ID: mdl-36834903

ABSTRACT

The role of dysbiosis in the development and progression of oral potentially malignant disorders (OPMDs) remains largely unknown. Here, we aim to characterize and compare the oral microbiome of homogeneous leucoplakia (HL), proliferative verrucous leukoplakia (PVL), oral squamous cell carcinoma (OSCC), and OSCC preceded by PVL (PVL-OSCC). Fifty oral biopsies from HL (n = 9), PVL (n = 12), OSCC (n = 10), PVL-OSCC (n = 8), and healthy (n = 11) donors were obtained. The sequence of the V3-V4 region of the 16S rRNA gene was used to analyze the composition and diversity of bacterial populations. In the cancer patients, the number of observed amplicon sequence variants (ASVs) was lower and Fusobacteriota constituted more than 30% of the microbiome. PVL and PVL-OSCC patients had a higher abundance of Campilobacterota and lower Proteobacteria than any other group analyzed. A penalized regression was performed to determine which species were able to distinguish groups. HL is enriched in Streptococcus parasanguinis, Streptococcus salivarius, Fusobacterium periodonticum, Prevotella histicola, Porphyromonas pasteri, and Megasphaera micronuciformis; PVL is enriched in Prevotella salivae, Campylobacter concisus, Dialister pneumosintes, and Schaalia odontolytica; OSCC is enriched in Capnocytophaga leadbetteri, Capnocytophaga sputigena, Capnocytophaga gingivalis, Campylobacter showae, Metamycoplasma salivarium, and Prevotella nanceiensis; and PVL-OSCC is enriched in Lachnospiraceae bacterium, Selenomonas sputigena, and Prevotella shahii. There is differential dysbiosis in patients suffering from OPMDs and cancer. To the best of our knowledge, this is the first study comparing the oral microbiome alterations in these groups; thus, additional studies are needed.


Subject(s)
Carcinoma, Squamous Cell , Microbiota , Mouth Neoplasms , Humans , Mouth Neoplasms/pathology , Carcinoma, Squamous Cell/pathology , Dysbiosis , RNA, Ribosomal, 16S/genetics , Leukoplakia, Oral
3.
Article in English | MEDLINE | ID: mdl-36585342

ABSTRACT

OBJECTIVE: The aim of this study was to determine the prevalence of acute oral mucosal toxicities in non-irradiated patients treated with systemic antineoplastics agents. The secondary objective was to find out differences in its prevalence among the different types of systemic antineoplastics. STUDY DESIGN: A systematic review and meta-analysis was performed. Articles from 2010 to July 2022 were retrieved and included if patients were adults undergoing oral assessment after administration of commercially available systemic antineoplastics. Data was extracted and pooled proportions were estimated using random-effect model method (Der Simonian and Lair). RESULTS: Eighty-two articles were included in the study. The overall prevalence of acute oral mucosal damage across studies was 38.2% (95% CI: 33.1%-43.3%). The prevalence was 42.9% (95% CI: 32.8%-53%) in patients treated with chemotherapy alone, 38% (95% CI: 29.1%-47%) in patients treated with a combination of chemotherapy and targeted therapies, and 32.1% (95% CI: 26.8%-37.5%) in targeted therapies alone-treated patients. No statistically significant differences were found in the prevalence of oral mucosal toxicities between the different types of systemic antineoplastic treatments. CONCLUSIONS: Oral mucosal toxicity is a major side effect in non-irradiated cancer patients undergoing systemic antineoplastics.


Subject(s)
Antineoplastic Agents , Adult , Humans , Prevalence , Antineoplastic Agents/adverse effects , Mouth Mucosa
4.
Oral Oncol ; 132: 105967, 2022 09.
Article in English | MEDLINE | ID: mdl-35763911

ABSTRACT

OBJECTIVES: To estimate the probability of malignancy of an oral leukoplakia lesion using Deep Learning, in terms of evolution to cancer and high-risk dysplasia. MATERIALS AND METHODS: A total of 261 oral leukoplakia lesions with a mean of 5.5 years follow-up were analysed from standard digital photographs. A deep learning pipeline composed by a U-Net based segmentation of the lesion followed by a multi-task CNN classifier was used to predict the malignant transformation and the risk of dysplasia of the lesion. An explainability heatmap is constructed using LIME in order to interpret the decision of the model for each output. RESULTS: A Dice coefficient of 0.561 was achieved on the segmentation task. For the prediction of a malignant transformation, the model provided a sensitivity of 1 with a specificity of 0.692. For the prediction of high-risk dysplasia, the model achieved a specificity of 0.740 and a sensitivity of 0.928. CONCLUSION: The proposed model using deep learning can be a helpful tool for predicting the possible malignant evolution of oral leukoplakias. The generated heatmap provides a high confidence on the output of the model and enables its interpretability.


Subject(s)
Deep Learning , Cell Transformation, Neoplastic/pathology , Humans , Hyperplasia , Leukoplakia, Oral/pathology
5.
Int J Mol Sci ; 22(12)2021 Jun 08.
Article in English | MEDLINE | ID: mdl-34201191

ABSTRACT

The role of oxidative stress (OS) in cancer is a matter of great interest due to the implication of reactive oxygen species (ROS) and their oxidation products in the initiation of tumorigenesis, its progression, and metastatic dissemination. Great efforts have been made to identify the mechanisms of ROS-induced carcinogenesis; however, the validation of OS byproducts as potential tumor markers (TMs) remains to be established. This interventional study included a total of 80 colorectal cancer (CRC) patients and 60 controls. By measuring reduced glutathione (GSH), its oxidized form (GSSG), and the glutathione redox state in terms of the GSSG/GSH ratio in the serum of CRC patients, we identified significant changes as compared to healthy subjects. These findings are compatible with the effectiveness of glutathione as a TM. The thiol redox state showed a significant increase towards oxidation in the CRC group and correlated significantly with both the tumor state and the clinical evolution. The sensitivity and specificity of serum glutathione levels are far above those of the classical TMs CEA and CA19.9. We conclude that the GSSG/GSH ratio is a simple assay which could be validated as a novel clinical TM for the diagnosis and monitoring of CRC.


Subject(s)
Biomarkers, Tumor/metabolism , Colorectal Neoplasms/pathology , Glutathione/chemistry , Glutathione/metabolism , Oxidative Stress , Reactive Oxygen Species/metabolism , Aged , Case-Control Studies , Colorectal Neoplasms/metabolism , Female , Humans , Male , Middle Aged , Oxidation-Reduction
6.
Med. oral patol. oral cir. bucal (Internet) ; 25(1): e34-e48, ene. 2020. tab, graf
Article in English | IBECS | ID: ibc-196194

ABSTRACT

BACKGROUND: A study is made of the association between maxillary sinus pathology and odontogenic lesions in patients evaluated with cone beam computed tomography. MATERIAL AND METHODS: A literature search was made in five databases and OpenGrey. Methodological assessment was carried out using the Newcastle-Ottawa tool for observational studies. The random-effects model was used for the meta-analysis. RESULTS: Twenty-one studies were included in the qualitative review and 6 in the meta-analysis. Most presented moderate or low risk of bias. The periodontal disease showed to be associated with the thickening of the sinus membrane (TSM). Mucous retention cysts and opacities were reported in few studies. The presence of periapical lesions (PALs) was significantly associated to TSM (OR = 2.43 (95%CI:1.71-3.46); I2 = 34.5%) and to odontogenic maxillary sinusitis (OMS)(OR = 1.77 (95%CI: 1.20-2.61); I2 = 35.5%). CONCLUSIONS: The presence of PALs increases the probability of TSM and OMS up to 2.4-fold and 1.7-fold respec-tively. The risk differences suggests that about 58 and 37 of out every 100 maxillary sinuses having antral teeth with PALs are associated with an increased risk TSM and OMS respectively. The meta-evidence obtained in this study was of moderate certainty, and although the magnitude of the observed associations may vary, their direc-tion in favor sinus disorders appearance, would not change as a result


No disponible


Subject(s)
Humans , Male , Female , Maxillary Sinus/pathology , Periapical Diseases/pathology , Maxillary Sinusitis/pathology , Odontogenic Cysts/pathology , Cone-Beam Computed Tomography , Mucocele/pathology , Risk Factors
7.
Med. oral patol. oral cir. bucal (Internet) ; 25(1): e71-e83, ene. 2020. tab, ilus
Article in English | IBECS | ID: ibc-196198

ABSTRACT

BACKGROUND: Medication-related osteonecrosis of the jaw (MRONJ) is a rare, but serious adverse effect of certain drugs, of which bisphosphonates are the most widely known. This pathology is also associated with other medications such as the biologic antiresorptive agent, denosumab and some antiangiogenics such as sunitinib, bevacizumab or aflibercept. Very recently, new medications have also been associated with osteonecrosis of the jaw (ONJ). The objectives were to update the list of medications associated with ONJ, to analyze the fundamental aspects of this list and to describe the level of evidence available. MATERIAL AND METHODS: A narrative bibliographic review was made, using the PubMed-MedLine, DOAJ and SCI-ELO databases. Additional information was obtained through the online Medication Information Centre of the Spanish Agency of Medicines and Medical Devices (AEMPS - CIMA), the websites of the US Food & Drugs Administration (Drugs@FDA) and the European Medicines Agency (EMA). RESULTS: The latest drugs identified as potential facilitators of this pathology include a number of anti-VEGF based antiangiogenic drugs and anti-TKI and different types of immunomodulators. Neither the level of evidence in this association nor the risk are equal for all these drugs. On the other hand, over the coming years, new drugs will be marketed with similar action mechanisms to those that are recognized as having this adverse effect. CONCLUSIONS: No effective therapy is currently known for the treatment of ONJ. Therefore, in order to prevent new cases of MRONJ, it is essential for all oral healthcare professionals to be fully up-to-date with the etiopathogenic aspects of this pathology and to be aware of those drugs considered to be a risk


No disponible


Subject(s)
Humans , Bisphosphonate-Associated Osteonecrosis of the Jaw/etiology , Bone Density Conservation Agents/adverse effects , Angiogenesis Inhibitors/adverse effects , Bisphosphonate-Associated Osteonecrosis of the Jaw/prevention & control , Risk Factors , Denosumab/adverse effects , Bevacizumab/adverse effects , Sunitinib/adverse effects
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