Xiangjian Wang, Shenjie Xu, Tao Fu, Yang Wu, Weilian Sun
Background
Programmed cell death ligand 1 (PD-L1) and human leukocyte antigen/major histocompatibility complex (HLA/MHC) are two main kinds of immunophenotypes affecting the susceptibility to anti-PD therapy. Our previous study found that down-regulation of flap endonuclease-1 (FEN1) could not only inhibit PD-L1 expression, but also upregulate HLA expression in head and neck squamous cell carcinoma (HNSCC). We aimed to clarify whether downregulating FEN1 cloud enhance the response to PD-1 blockade, and possible mechanisms in HNSCC in vitro.
Methods
Differential expression of FEN1 in HNSCC tumor and normal tissues were explored in the TIMER and TISIDB datasets. A HNSCC cells/CD8+ T cells co-culture model was established. HNSCC cell cycle and apoptosis were recorded by flow cytometry. Immune activity markers of granzyme A, granzyme B, and PRF1 expressed in the CD8+ T cells, and IFN-γ, IL-2, and TNF-α secreted in the supernatants were detected by western blot, ELISA, respectively.
Results
FEN1 was highly expressed in HNSCC and associated with low immune infiltration. Downregulating FEN1 could induce HLA class I expression, and inhibit PD-L1 expression in HNSCC cells. Functionally, FEN1 knockdown enhanced the response to αPD-1 mAb by mediating G2/M phase arrest, apoptosis of HNSCC cells. Mechanistically, targeting FEN1 synergized with αPD-1 mAb could reinforce the antitumor response of CD8+ T cells against HNSCC cells, as indicated by increasing granzyme A, granzyme B, and PRF1 expressions, and promoting IFN-γ, IL-2, and TNF-α secretions.
Conclusion
These findings might offer a potential combined strategy for patients resistant to anti-PD therapy via combining FEN1 knockdown and PD-1 blockade.
{"title":"Combination of downregulating FEN1 and PD-1 blockade enhances antitumor activity of CD8+ T cells against HNSCC cells in vitro","authors":"Xiangjian Wang, Shenjie Xu, Tao Fu, Yang Wu, Weilian Sun","doi":"10.1111/jop.13485","DOIUrl":"10.1111/jop.13485","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Programmed cell death ligand 1 (PD-L1) and human leukocyte antigen/major histocompatibility complex (HLA/MHC) are two main kinds of immunophenotypes affecting the susceptibility to anti-PD therapy. Our previous study found that down-regulation of flap endonuclease-1 (FEN1) could not only inhibit PD-L1 expression, but also upregulate HLA expression in head and neck squamous cell carcinoma (HNSCC). We aimed to clarify whether downregulating FEN1 cloud enhance the response to PD-1 blockade, and possible mechanisms in HNSCC in vitro.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Differential expression of FEN1 in HNSCC tumor and normal tissues were explored in the TIMER and TISIDB datasets. A HNSCC cells/CD8+ T cells co-culture model was established. HNSCC cell cycle and apoptosis were recorded by flow cytometry. Immune activity markers of granzyme A, granzyme B, and PRF1 expressed in the CD8+ T cells, and IFN-γ, IL-2, and TNF-α secreted in the supernatants were detected by western blot, ELISA, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>FEN1 was highly expressed in HNSCC and associated with low immune infiltration. Downregulating FEN1 could induce HLA class I expression, and inhibit PD-L1 expression in HNSCC cells. Functionally, FEN1 knockdown enhanced the response to αPD-1 mAb by mediating G2/M phase arrest, apoptosis of HNSCC cells. Mechanistically, targeting FEN1 synergized with αPD-1 mAb could reinforce the antitumor response of CD8+ T cells against HNSCC cells, as indicated by increasing granzyme A, granzyme B, and PRF1 expressions, and promoting IFN-γ, IL-2, and TNF-α secretions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>These findings might offer a potential combined strategy for patients resistant to anti-PD therapy via combining FEN1 knockdown and PD-1 blockade.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41125536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial—Where have the last 8 years gone?","authors":"Peter A. Brennan","doi":"10.1111/jop.13486","DOIUrl":"10.1111/jop.13486","url":null,"abstract":"","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10363160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniela Giraldo-Roldan, Erin Crespo Cordeiro Ribeiro, Anna Luiza Damaceno Araújo, Paulo Victor Mendes Penafort, Viviane Mariano da Silva, Jeconias Câmara, Hélder Antônio Rebelo Pontes, Manoela Domingues Martins, Márcio Campos Oliveira, Alan Roger Santos-Silva, Marcio Ajudarte Lopes, Luiz Paulo Kowalski, Matheus Cardoso Moraes, Pablo Agustin Vargas
Background
Odontogenic tumors (OT) are composed of heterogeneous lesions, which can be benign or malignant, with different behavior and histology. Within this classification, ameloblastoma and ameloblastic carcinoma (AC) represent a diagnostic challenge in daily histopathological practice due to their similar characteristics and the limitations that incisional biopsies represent. From these premises, we wanted to test the usefulness of models based on artificial intelligence (AI) in the field of oral and maxillofacial pathology for differential diagnosis. The main advantages of integrating Machine Learning (ML) with microscopic and radiographic imaging is the ability to significantly reduce intra-and inter observer variability and improve diagnostic objectivity and reproducibility.
Methods
Thirty Digitized slides were collected from different diagnostic centers of oral pathology in Brazil. After performing manual annotation in the region of interest, the images were segmented and fragmented into small patches. In the supervised learning methodology for image classification, three models (ResNet50, DenseNet, and VGG16) were focus of investigation to provide the probability of an image being classified as class0 (i.e., ameloblastoma) or class1 (i.e., Ameloblastic carcinoma).
Results
The training and validation metrics did not show convergence, characterizing overfitting. However, the test results were satisfactory, with an average for ResNet50 of 0.75, 0.71, 0.84, 0.65, and 0.77 for accuracy, precision, sensitivity, specificity, and F1-score, respectively.
Conclusions
The models demonstrated a strong potential of learning, but lack of generalization ability. The models learn fast, reaching a training accuracy of 98%. The evaluation process showed instability in validation; however, acceptable performance in the testing process, which may be due to the small data set. This first investigation opens an opportunity for expanding collaboration to incorporate more complementary data; as well as, developing and evaluating new alternative models.
{"title":"Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas","authors":"Daniela Giraldo-Roldan, Erin Crespo Cordeiro Ribeiro, Anna Luiza Damaceno Araújo, Paulo Victor Mendes Penafort, Viviane Mariano da Silva, Jeconias Câmara, Hélder Antônio Rebelo Pontes, Manoela Domingues Martins, Márcio Campos Oliveira, Alan Roger Santos-Silva, Marcio Ajudarte Lopes, Luiz Paulo Kowalski, Matheus Cardoso Moraes, Pablo Agustin Vargas","doi":"10.1111/jop.13481","DOIUrl":"10.1111/jop.13481","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Odontogenic tumors (OT) are composed of heterogeneous lesions, which can be benign or malignant, with different behavior and histology. Within this classification, ameloblastoma and ameloblastic carcinoma (AC) represent a diagnostic challenge in daily histopathological practice due to their similar characteristics and the limitations that incisional biopsies represent. From these premises, we wanted to test the usefulness of models based on artificial intelligence (AI) in the field of oral and maxillofacial pathology for differential diagnosis. The main advantages of integrating Machine Learning (ML) with microscopic and radiographic imaging is the ability to significantly reduce intra-and inter observer variability and improve diagnostic objectivity and reproducibility.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Thirty Digitized slides were collected from different diagnostic centers of oral pathology in Brazil. After performing manual annotation in the region of interest, the images were segmented and fragmented into small patches. In the supervised learning methodology for image classification, three models (ResNet50, DenseNet, and VGG16) were focus of investigation to provide the probability of an image being classified as class0 (i.e., ameloblastoma) or class1 (i.e., Ameloblastic carcinoma).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The training and validation metrics did not show convergence, characterizing overfitting. However, the test results were satisfactory, with an average for ResNet50 of 0.75, 0.71, 0.84, 0.65, and 0.77 for accuracy, precision, sensitivity, specificity, and F1-score, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The models demonstrated a strong potential of learning, but lack of generalization ability. The models learn fast, reaching a training accuracy of 98%. The evaluation process showed instability in validation; however, acceptable performance in the testing process, which may be due to the small data set. This first investigation opens an opportunity for expanding collaboration to incorporate more complementary data; as well as, developing and evaluating new alternative models.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10241771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Luíza Damaceno Araújo, Viviane Mariano da Silva, Matheus Cardoso Moraes, Henrique Alves de Amorim, Felipe Paiva Fonseca, Maria Sissa Pereira Sant'Ana, Ricardo Alves Mesquita, Bruno Augusto Linhares Almeida Mariz, Hélder Antônio Rebelo Pontes, Lucas Lacerda de Souza, Cristina Saldivia-Siracusa, Syed Ali Khurram, Alexander T. Pearson, Manoela Domingues Martins, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Luiz Paulo Kowalski, Alan Roger Santos-Silva
Background
Dysplasia grading systems for oral epithelial dysplasia are a source of disagreement among pathologists. Therefore, machine learning approaches are being developed to mitigate this issue.
Methods
This cross-sectional study included a cohort of 82 patients with oral potentially malignant disorders and correspondent 98 hematoxylin and eosin-stained whole slide images with biopsied-proven dysplasia. All whole-slide images were manually annotated based on the binary system for oral epithelial dysplasia. The annotated regions of interest were segmented and fragmented into small patches and non-randomly sampled into training/validation and test subsets. The training/validation data were color augmented, resulting in a total of 81,786 patches for training. The held-out independent test set enrolled a total of 4,486 patches. Seven state-of-the-art convolutional neural networks were trained, validated, and tested with the same dataset.
Results
The models presented a high learning rate, yet very low generalization potential. At the model development, VGG16 performed the best, but with massive overfitting. In the test set, VGG16 presented the best accuracy, sensitivity, specificity, and area under the curve (62%, 62%, 66%, and 65%, respectively), associated with the higher loss among all Convolutional Neural Networks (CNNs) tested. EfficientB0 has comparable metrics and the lowest loss among all convolutional neural networks, being a great candidate for further studies.
Conclusion
The models were not able to generalize enough to be applied in real-life datasets due to an overlapping of features between the two classes (i.e., high risk and low risk of malignization).
{"title":"The use of deep learning state-of-the-art architectures for oral epithelial dysplasia grading: A comparative appraisal","authors":"Anna Luíza Damaceno Araújo, Viviane Mariano da Silva, Matheus Cardoso Moraes, Henrique Alves de Amorim, Felipe Paiva Fonseca, Maria Sissa Pereira Sant'Ana, Ricardo Alves Mesquita, Bruno Augusto Linhares Almeida Mariz, Hélder Antônio Rebelo Pontes, Lucas Lacerda de Souza, Cristina Saldivia-Siracusa, Syed Ali Khurram, Alexander T. Pearson, Manoela Domingues Martins, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Luiz Paulo Kowalski, Alan Roger Santos-Silva","doi":"10.1111/jop.13477","DOIUrl":"10.1111/jop.13477","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Dysplasia grading systems for oral epithelial dysplasia are a source of disagreement among pathologists. Therefore, machine learning approaches are being developed to mitigate this issue.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This cross-sectional study included a cohort of 82 patients with oral potentially malignant disorders and correspondent 98 hematoxylin and eosin-stained whole slide images with biopsied-proven dysplasia. All whole-slide images were manually annotated based on the binary system for oral epithelial dysplasia. The annotated regions of interest were segmented and fragmented into small patches and non-randomly sampled into training/validation and test subsets. The training/validation data were color augmented, resulting in a total of 81,786 patches for training. The held-out independent test set enrolled a total of 4,486 patches. Seven state-of-the-art convolutional neural networks were trained, validated, and tested with the same dataset.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The models presented a high learning rate, yet very low generalization potential. At the model development, VGG16 performed the best, but with massive overfitting. In the test set, VGG16 presented the best accuracy, sensitivity, specificity, and area under the curve (62%, 62%, 66%, and 65%, respectively), associated with the higher loss among all Convolutional Neural Networks (CNNs) tested. EfficientB0 has comparable metrics and the lowest loss among all convolutional neural networks, being a great candidate for further studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The models were not able to generalize enough to be applied in real-life datasets due to an overlapping of features between the two classes (i.e., high risk and low risk of malignization).</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10298180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUND Oral squamous cell carcinoma (OSCC) is a widespread disease with only 50%-60% 5-year survival. Individuals with potentially malignant precursor lesions are at high risk. METHODS Survival could be increased by effective, affordable, and simple screening methods, along with a shift from incisional tissue biopsies to non-invasive brush biopsies for cytology diagnosis, which are easy to perform in primary care. Along with the explainable, fast, and objective artificial intelligence characterisation of cells through deep learning, an easy-to-use, rapid, and cost-effective methodology for finding high-risk lesions is achievable. The collection of cytology samples offers the further opportunity of explorative genomic analysis. RESULTS Our prospective multicentre study of patients with leukoplakia yields a vast number of oral keratinocytes. In addition to cytopathological analysis, whole-slide imaging and the training of deep neural networks, samples are analysed according to a single-cell RNA sequencing protocol, enabling mapping of the entire keratinocyte transcriptome. Mapping the changes in the genetic profile, based on mRNA expression, facilitates the identification of biomarkers that predict cancer transformation. CONCLUSION This position paper highlights non-invasive methods for identifying patients with oral mucosal lesions at risk of malignant transformation. Reliable non-invasive methods for screening at-risk individuals bring the early diagnosis of OSCC within reach. The use of biomarkers to decide on a targeted therapy is most likely to improve the outcome. With the large-scale collection of samples following patients over time, combined with genomic analysis and modern machine-learning-based approaches for finding patterns in data, this path holds great promise.
{"title":"A paradigm shift in the prevention and diagnosis of oral squamous cell carcinoma","authors":"Jan-Michaél Hirsch, Ronak Sandy, Bengt Hasséus, Joakim Lindblad","doi":"10.1111/jop.13484","DOIUrl":"10.1111/jop.13484","url":null,"abstract":"BACKGROUND Oral squamous cell carcinoma (OSCC) is a widespread disease with only 50%-60% 5-year survival. Individuals with potentially malignant precursor lesions are at high risk. METHODS Survival could be increased by effective, affordable, and simple screening methods, along with a shift from incisional tissue biopsies to non-invasive brush biopsies for cytology diagnosis, which are easy to perform in primary care. Along with the explainable, fast, and objective artificial intelligence characterisation of cells through deep learning, an easy-to-use, rapid, and cost-effective methodology for finding high-risk lesions is achievable. The collection of cytology samples offers the further opportunity of explorative genomic analysis. RESULTS Our prospective multicentre study of patients with leukoplakia yields a vast number of oral keratinocytes. In addition to cytopathological analysis, whole-slide imaging and the training of deep neural networks, samples are analysed according to a single-cell RNA sequencing protocol, enabling mapping of the entire keratinocyte transcriptome. Mapping the changes in the genetic profile, based on mRNA expression, facilitates the identification of biomarkers that predict cancer transformation. CONCLUSION This position paper highlights non-invasive methods for identifying patients with oral mucosal lesions at risk of malignant transformation. Reliable non-invasive methods for screening at-risk individuals bring the early diagnosis of OSCC within reach. The use of biomarkers to decide on a targeted therapy is most likely to improve the outcome. With the large-scale collection of samples following patients over time, combined with genomic analysis and modern machine-learning-based approaches for finding patterns in data, this path holds great promise.","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jop.13484","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10234257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jijun Chen, Liang Wang, Danhua Ma, He Zhang, Jiayan Fan, Hongyan Gao, Xinyu Xia, Wei Wu, Yuyuan Shi
Background
In this study, we aimed to investigate the potential of miR-19a as a biomarker of OSCC and its underlying molecular mechanisms.
Methods
We collected serum and saliva samples from 66 OSCC patients and 66 healthy control subjects. Real-time PCR analysis, bioinformatic analysis and luciferase assays were performed to establish a potential signaling pathway of miR-19a/GRK6/GPCRs/PKC. Flowcytometry and Transwell assays were performed to observe the changes in cell apoptosis, metastasis and invasion.
Results
We found that miR-19a, GPR39 mRNA and PKC mRNA were upregulated while GRK6 mRNA was downregulated in the serum and saliva samples collected from OSCC patients. Moreover, in silico analysis confirmed a potential binding site of miR-19a on the 3′UTR of GRK6 mRNA, and the subsequent luciferase assays confirmed the molecular binding between GRK6 and miR-19a. We further identified that the over-expression of miR-19a could regulate the signaling between GRK6, GPR39 and PKC via the signaling pathway of miR-19a/GRK6/GPR39/PKC, which accordingly resulted in suppressed cell apoptosis and promoted cell migration and invasion.
Conclusion
Collectively, the findings of our study propose that miR-19a is a crucial mediator in the advancement of OSCC, offering a potential avenue for the development of innovative therapeutic interventions aimed at regulating GRK6 and its downstream signaling pathways.
{"title":"miR-19a may function as a biomarker of oral squamous cell carcinoma (OSCC) by regulating the signaling pathway of miR-19a/GRK6/GPCRs/PKC in a Chinese population","authors":"Jijun Chen, Liang Wang, Danhua Ma, He Zhang, Jiayan Fan, Hongyan Gao, Xinyu Xia, Wei Wu, Yuyuan Shi","doi":"10.1111/jop.13478","DOIUrl":"10.1111/jop.13478","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In this study, we aimed to investigate the potential of miR-19a as a biomarker of OSCC and its underlying molecular mechanisms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We collected serum and saliva samples from 66 OSCC patients and 66 healthy control subjects. Real-time PCR analysis, bioinformatic analysis and luciferase assays were performed to establish a potential signaling pathway of miR-19a/GRK6/GPCRs/PKC. Flowcytometry and Transwell assays were performed to observe the changes in cell apoptosis, metastasis and invasion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We found that miR-19a, GPR39 mRNA and PKC mRNA were upregulated while GRK6 mRNA was downregulated in the serum and saliva samples collected from OSCC patients. Moreover, in silico analysis confirmed a potential binding site of miR-19a on the 3′UTR of GRK6 mRNA, and the subsequent luciferase assays confirmed the molecular binding between GRK6 and miR-19a. We further identified that the over-expression of miR-19a could regulate the signaling between GRK6, GPR39 and PKC via the signaling pathway of miR-19a/GRK6/GPR39/PKC, which accordingly resulted in suppressed cell apoptosis and promoted cell migration and invasion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Collectively, the findings of our study propose that miR-19a is a crucial mediator in the advancement of OSCC, offering a potential avenue for the development of innovative therapeutic interventions aimed at regulating GRK6 and its downstream signaling pathways.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10235553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oral squamous cell carcinoma is the most common phenotype in pathology, which accounts for 80% of all oral cancers. The therapeutic methods of oral squamous cell carcinoma include surgical excision, chemotherapy, and radiotherapy. Whereas, the high recurrence rate and poor prognosis lead to a 5-year survival rate less than 50%. In order to explore more therapeutic strategies of oral squamous cell carcinoma, the relevant risk factors, mechanisms, and diagnostics are widely detected. The various exosome-mediated biological effects on the development of oral squamous cell carcinoma have drawn lots of attention. Exosomes, a kind of extracellular vesicles secreted from host cells and transferred to other cells, show great potential in the regulations of tumorigenesis, progression, and metastasis on oral squamous cell carcinoma. Moreover, some studies reported that the exosomes could interact with tumor microenvironment and be applied to diagnosis or therapy of oral squamous cell carcinoma. In this work, we will summarize the frontier studies of exosomes in the tumor growth, tumor-associated angiogenesis, invasion, and metastasis of oral squamous cell carcinoma, and then probe the current biological functions and applications of exosomes and exosome-derived materials for the therapeutic strategies of oral squamous cell carcinoma, which would help us to update the understanding of exosomes in oral squamous cell carcinoma.
{"title":"Emerging functions and applications of exosomes in oral squamous cell carcinoma","authors":"Yingchun Qie, Xia Sun, Yongqiang Yang, Tao Yan","doi":"10.1111/jop.13479","DOIUrl":"10.1111/jop.13479","url":null,"abstract":"<p>Oral squamous cell carcinoma is the most common phenotype in pathology, which accounts for 80% of all oral cancers. The therapeutic methods of oral squamous cell carcinoma include surgical excision, chemotherapy, and radiotherapy. Whereas, the high recurrence rate and poor prognosis lead to a 5-year survival rate less than 50%. In order to explore more therapeutic strategies of oral squamous cell carcinoma, the relevant risk factors, mechanisms, and diagnostics are widely detected. The various exosome-mediated biological effects on the development of oral squamous cell carcinoma have drawn lots of attention. Exosomes, a kind of extracellular vesicles secreted from host cells and transferred to other cells, show great potential in the regulations of tumorigenesis, progression, and metastasis on oral squamous cell carcinoma. Moreover, some studies reported that the exosomes could interact with tumor microenvironment and be applied to diagnosis or therapy of oral squamous cell carcinoma. In this work, we will summarize the frontier studies of exosomes in the tumor growth, tumor-associated angiogenesis, invasion, and metastasis of oral squamous cell carcinoma, and then probe the current biological functions and applications of exosomes and exosome-derived materials for the therapeutic strategies of oral squamous cell carcinoma, which would help us to update the understanding of exosomes in oral squamous cell carcinoma.</p>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10590265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ke Yang, Guixin Zhu, Yanan Sun, Yaying Hu, Yinan Lv, Yiwei Li, Juncheng Pan, Fu Chen, Yi Zhou, Jiali Zhang
Background
We aimed to establish image recognition and survival prediction models using a novel scoring system of cyclin D1 expression pattern in patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.
Methods
The clinicopathological data of 610 patients with human papillomavirus-negative oral/oropharyngeal squamous cell carcinoma were analyzed retrospectively. Cox univariate and multivariate risk regression analyses were performed to compare cyclin D1 expression pattern scoring with the traditional scoring method—cyclin D1 expression level scoring—in relation to patients' overall and progression-free survival. An image recognition model employing the cyclin D1 expression pattern scoring system was established by YOLOv5 algorithms. From this model, two independent survival prediction models were established using the DeepHit and DeepSurv algorithms.
Results
Cyclin D1 had three expression patterns in oral and oropharyngeal squamous cell carcinoma cancer nests. Superior to cyclin D1 expression level scoring, cyclin D1 expression pattern scoring was significantly correlated with the prognosis of patients with oral squamous cell carcinoma (p < 0.0001) and oropharyngeal squamous cell carcinoma (p < 0.05). Moreover, it was an independent prognostic risk factor in both oral squamous cell carcinoma (p < 0.0001) and oropharyngeal squamous cell carcinoma (p < 0.05). The cyclin D1 expression pattern-derived image recognition model showed an average test set accuracy of 78.48% ± 4.31%. In the overall survival prediction models, the average concordance indices of the test sets established by DeepSurv and DeepHit were 0.71 ± 0.02 and 0.70 ± 0.01, respectively.
Conclusion
Combined with the image recognition model of the cyclin D1 expression pattern, the survival prediction model had a relatively good prediction effect on the overall survival prognosis of patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.
{"title":"Prognostic significance of cyclin D1 expression pattern in HPV-negative oral and oropharyngeal carcinoma: A deep-learning approach","authors":"Ke Yang, Guixin Zhu, Yanan Sun, Yaying Hu, Yinan Lv, Yiwei Li, Juncheng Pan, Fu Chen, Yi Zhou, Jiali Zhang","doi":"10.1111/jop.13482","DOIUrl":"10.1111/jop.13482","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>We aimed to establish image recognition and survival prediction models using a novel scoring system of cyclin D1 expression pattern in patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The clinicopathological data of 610 patients with human papillomavirus-negative oral/oropharyngeal squamous cell carcinoma were analyzed retrospectively. Cox univariate and multivariate risk regression analyses were performed to compare cyclin D1 expression pattern scoring with the traditional scoring method—cyclin D1 expression level scoring—in relation to patients' overall and progression-free survival. An image recognition model employing the cyclin D1 expression pattern scoring system was established by YOLOv5 algorithms. From this model, two independent survival prediction models were established using the DeepHit and DeepSurv algorithms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Cyclin D1 had three expression patterns in oral and oropharyngeal squamous cell carcinoma cancer nests. Superior to cyclin D1 expression level scoring, cyclin D1 expression pattern scoring was significantly correlated with the prognosis of patients with oral squamous cell carcinoma (<i>p</i> < 0.0001) and oropharyngeal squamous cell carcinoma (<i>p</i> < 0.05). Moreover, it was an independent prognostic risk factor in both oral squamous cell carcinoma (<i>p</i> < 0.0001) and oropharyngeal squamous cell carcinoma (<i>p</i> < 0.05). The cyclin D1 expression pattern-derived image recognition model showed an average test set accuracy of 78.48% ± 4.31%. In the overall survival prediction models, the average concordance indices of the test sets established by DeepSurv and DeepHit were 0.71 ± 0.02 and 0.70 ± 0.01, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Combined with the image recognition model of the cyclin D1 expression pattern, the survival prediction model had a relatively good prediction effect on the overall survival prognosis of patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10227369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dipti Sharma, Sagar N. Pawar, Prasad Sulkshane, Rohit Waghole, Mohd Yasser, Sushil S. Pawar, Sadhana Kannan, Nazia Chaudhary, Anjali Kalwar, Rahul Patil, Sudhir Nair, Sorab N. Dalal, Tanuja Teni
Background
Translationally controlled tumour protein (TCTP) is a multifunctional protein elevated in multiple cancers. However, studies on its role in oral carcinogenesis and prognosis are rare. We recently reported the role of its interacting partner, MCL1, in oral cancer progression and outcome. Hence, the present study aimed to assess TCTP expression in oral tumorigenesis and its association with patient outcomes alone and in combination with MCL1.
Methods
TCTP expression was assessed by immunohistochemistry and immunoblotting in oral tissues and cells, respectively. Cell viability post siRNA/dihydroartemisinin treatment was analysed by tetrazolium salt assay. Cell survival, invasion and tumorigenic potential post TCTP knockdown were assessed by clonogenic, Matrigel and soft-agar assays, respectively. The association of TCTP with patient outcome was analysed by Kaplan–Meier and Cox regression.
Results
TCTP was significantly overexpressed in oral premalignant lesions (p < 0.0001), oral tumours (p < 0.0001) and oral dysplastic and cancer cells versus normal oral mucosa and also in recurrent (p < 0.05) versus non-recurrent oral tumours. Further, elevated TCTP was significantly (p < 0.05) associated with poor recurrence free survival (RFS) and poor overall survival (OS; hazard ratio = 2.29; p < 0.05). Intriguingly, the high co-expression of TCTP and MCL1 further reduced the RFS (p < 0.05) and OS (p < 0.05; hazard-ratio = 3.49; p < 0.05). Additionally, TCTP knockdown decreased survival (p < 0.05), invasion (p < 0.01) and in vitro tumorigenic potential (p < 0.0001). Dihydroartemisinin treatment reduced TCTP levels and viability of oral cancer cells.
Conclusion
Our studies demonstrate an oncogenic role of TCTP in oral cancer progression and poor outcome. Thus, TCTP may be a potential prognostic marker and therapeutic target in oral cancers.
{"title":"Elevated translationally controlled tumour protein promotes oral cancer progression and poor outcome","authors":"Dipti Sharma, Sagar N. Pawar, Prasad Sulkshane, Rohit Waghole, Mohd Yasser, Sushil S. Pawar, Sadhana Kannan, Nazia Chaudhary, Anjali Kalwar, Rahul Patil, Sudhir Nair, Sorab N. Dalal, Tanuja Teni","doi":"10.1111/jop.13467","DOIUrl":"10.1111/jop.13467","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Translationally controlled tumour protein (TCTP) is a multifunctional protein elevated in multiple cancers. However, studies on its role in oral carcinogenesis and prognosis are rare. We recently reported the role of its interacting partner, MCL1, in oral cancer progression and outcome. Hence, the present study aimed to assess TCTP expression in oral tumorigenesis and its association with patient outcomes alone and in combination with MCL1.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>TCTP expression was assessed by immunohistochemistry and immunoblotting in oral tissues and cells, respectively. Cell viability post siRNA/dihydroartemisinin treatment was analysed by tetrazolium salt assay. Cell survival, invasion and tumorigenic potential post TCTP knockdown were assessed by clonogenic, Matrigel and soft-agar assays, respectively. The association of TCTP with patient outcome was analysed by Kaplan–Meier and Cox regression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>TCTP was significantly overexpressed in oral premalignant lesions (<i>p</i> < 0.0001), oral tumours (<i>p</i> < 0.0001) and oral dysplastic and cancer cells versus normal oral mucosa and also in recurrent (<i>p</i> < 0.05) versus non-recurrent oral tumours. Further, elevated TCTP was significantly (<i>p</i> < 0.05) associated with poor recurrence free survival (RFS) and poor overall survival (OS; hazard ratio = 2.29; <i>p</i> < 0.05). Intriguingly, the high co-expression of TCTP and MCL1 further reduced the RFS (<i>p</i> < 0.05) and OS (<i>p</i> < 0.05; hazard-ratio = 3.49; <i>p</i> < 0.05). Additionally, TCTP knockdown decreased survival (<i>p</i> < 0.05), invasion (<i>p</i> < 0.01) and in vitro tumorigenic potential (<i>p</i> < 0.0001). Dihydroartemisinin treatment reduced TCTP levels and viability of oral cancer cells.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our studies demonstrate an oncogenic role of TCTP in oral cancer progression and poor outcome. Thus, TCTP may be a potential prognostic marker and therapeutic target in oral cancers.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10343156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Keerthika, Mala Kamboj, Akhil Girdhar, Anjali Narwal, Anju Devi, Rahul Anand, Manish Juneja
Objective
Angiogenesis plays a vital role at the molecular level in various inflammatory lesions, that lead to their chronicity. Oral lichen planus is an immune-mediated chronic inflammatory disorder. The angiogenetic role and exact mechanisms in oral lichen planus are still unclear due to a dearth of studies. Its clinical significance with angiogenesis also requires further elucidation necessitating a thorough review of the studies that have been conducted so far. The present review was designed to identify the dependence of oral lichen planus progression on angiogenesis which could aid in devising metronomic treatments required to halt the progression of this disease.
Materials and Methods
A thorough search was made using MEDLINE by PubMed, Scopus, Google scholar, Cochrane library, and EMBASE databases. Original research articles, that immunohistochemically evaluated angiogenesis in oral lichen planus were included for review. Risk of bias was analysed for each study using Modified Newcastle-Ottawa scale and Review Manager 5.4 was used to output its result.
Results
Twenty-nine published articles were included for data synthesis. The most commonly employed antibody was CD34, however, upregulated VEGF expression was the principal while ICAM-1, VCAM-1, and PECAM-1 were critical angiogenic factors to mediate angiogenesis in oral lichen planus.
Conclusion
The current evidence supports that angiogenesis, a fundamental pathogenetic mechanism of oral lichen planus, leads to its persistence and chronicity. However, studies with a larger sample size, standard evaluation criteria, different subtypes, and adequate follow-up are warranted.
{"title":"An exotic pathogenetic mechanism of angiogenesis in oral lichen planus—A systematic review","authors":"R. Keerthika, Mala Kamboj, Akhil Girdhar, Anjali Narwal, Anju Devi, Rahul Anand, Manish Juneja","doi":"10.1111/jop.13472","DOIUrl":"10.1111/jop.13472","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Angiogenesis plays a vital role at the molecular level in various inflammatory lesions, that lead to their chronicity. Oral lichen planus is an immune-mediated chronic inflammatory disorder. The angiogenetic role and exact mechanisms in oral lichen planus are still unclear due to a dearth of studies. Its clinical significance with angiogenesis also requires further elucidation necessitating a thorough review of the studies that have been conducted so far. The present review was designed to identify the dependence of oral lichen planus progression on angiogenesis which could aid in devising metronomic treatments required to halt the progression of this disease.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>A thorough search was made using MEDLINE by PubMed, Scopus, Google scholar, Cochrane library, and EMBASE databases. Original research articles, that immunohistochemically evaluated angiogenesis in oral lichen planus were included for review. Risk of bias was analysed for each study using Modified Newcastle-Ottawa scale and Review Manager 5.4 was used to output its result.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Twenty-nine published articles were included for data synthesis. The most commonly employed antibody was CD34, however, upregulated VEGF expression was the principal while ICAM-1, VCAM-1, and PECAM-1 were critical angiogenic factors to mediate angiogenesis in oral lichen planus.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The current evidence supports that angiogenesis, a fundamental pathogenetic mechanism of oral lichen planus, leads to its persistence and chronicity. However, studies with a larger sample size, standard evaluation criteria, different subtypes, and adequate follow-up are warranted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":16588,"journal":{"name":"Journal of Oral Pathology & Medicine","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9959887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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