Multi-omics analysis reveals a pericyte-associated gene expression signature for predicting prognosis and therapeutic responses in solid cancers.

The influence of the stroma on cancer progression has been underestimated, particularly the role of vascular pericytes in the tumor microenvironment. Herein, we identified 51 differentially expressed genes in tumor-derived pericytes (TPCs) by analyzing transcriptomic data from TCGA alongside our proteomic data. Using five key TPC-related genes, we constructed a prognostic risk model that accurately predicts prognosis and treatment responses in liver and lung cancers. Enrichment analyses linked these genes to blood vessel remodeling, function, and immune-related pathways. Single-cell RNA sequencing data from the GEO database validated these findings, showing significant upregulation of AKAP12 and RRAS in TPCs. Immunostaining confirmed increased expression of these genes in liver and lung tumors. Depletion of RRAS or AKAP12 in TPCs restored their blood vessel-supporting role. Overall, our findings suggest that TPC-related gene profiles can predict patient outcomes and therapeutic responses in solid cancers, and targeting these profiles could be an improved treatment strategy.

FAT1 as a tumor mutation burden specific gene affects the immunotherapy effect in head and neck squamous cell cancer.

BACKGROUND: Response to immunotherapy is the main challenge of head and neck squamous cancer (HNSCC) treatment. Previous studies have indicated that tumor mutational burden (TMB) is associated with prognosis, but it is not always a precise index. Hence, investigating specific genetic mutations and tumor microenvironment (TME) changes in TMB-high patients is essential for precision therapy of HNSCC. METHODS: A total of 33 HNSCC patients were enrolled in this study. We calculated the TMB score based on next-generation sequencing (NGS) sequencing and grouped these patients based on TMB score. Then, we examined the immune microenvironment of HNSCC using assessments of the bulk transcriptome and the single-cell RNA sequence (scRNA-seq) focusing on the molecular nature of TMB and mutations in HNSCC from our cohort. The association of the mutation pattern and TMB was analyzed in The Cancer Genome Atlas (TCGA) and validated by our cohort. RESULTS: 33 HNSCC patients were divided into three groups (TMB-low, -medium, and -high) based on TMB score. In the result of 520-gene panel sequencing data, we found that FAT1 and LRP1B mutations were highly prevalent in TMB-high patients. FAT1 mutations are associated with resistance to immunotherapy in HNSCC patients. This involves many metabolism-related pathways like RERE, AIRE, HOMER1, etc. In the scRNA-seq data, regulatory T cells (Tregs), monocytes, and DCs were found mainly enriched in TMB-high samples. CONCLUSION: Our analysis unraveled the FAT1 gene as an assistant predictor when we use TMB as a biomarker of drug resistance in HNSCC. Tregs, monocytes, and dendritic cells (DCs) were found mainly enriched in TMB-high samples.

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions. AIM: To construct and evaluate a preoperative diagnostic method to predict OCLNM in early-stage oral and oropharyngeal squamous cell carcinoma (OC and OP SCC) based on deep learning features (DLFs) and radiomics features. METHODS: A total of 319 patients diagnosed with early-stage OC or OP SCC were retrospectively enrolled and divided into training, test and external validation sets. Traditional radiomics features and DLFs were extracted from their MRI images. The least absolute shrinkage and selection operator (LASSO) analysis was employed to identify the most valuable features. Prediction models for OCLNM were developed using radiomics features and DLFs. The effectiveness of the models and their clinical applicability were evaluated using the area under the curve (AUC), decision curve analysis (DCA), and survival analysis. RESULTS: Seventeen prediction models were constructed. The Resnet50 deep learning (DL) model based on the combination of radiomics and DL features achieves the optimal performance, with AUC values of 0.928 (95% CI: 0.881-0.975), 0.878 (95% CI: 0.766-0.990), 0.796 (95% CI: 0.666-0.927), and 0.834 (95% CI: 0.721-0.947) in the training, test, external validation set1, and external validation set2, respectively. Moreover, the Resnet50 model has great prediction value of prognosis in patients with early-stage OC and OP SCC. CONCLUSION: The proposed MRI-based Resnet50 DL model demonstrated high capability in diagnosis of OCLNM and prognosis prediction in the early-stage OC and OP SCC. The Resnet50 model could help refine the clinical diagnosis and treatment of the early-stage OC and OP SCC.

Integrated Single-cell and Bulk RNA Sequencing Analysis Cross Talk between Ferroptosis-related Genes and Prognosis in Oral Cavity Squamous Cell Carcinoma.

BACKGROUND: Ferroptosis is a new type of programmed apoptosis and plays an important role in tumour inhibition and immunotherapy. OBJECTIVE: In this study, we aimed to explore the potential role of ferroptosis-related genes (FRGs) and the potential therapeutic targets in oral cavity squamous cell carcinoma (OCSCC). METHODS: The transcription data of OCSCC samples were obtained from the Cancer Genome Atlas (TCGA) database as a training dataset. The prognostic FRGs were extracted by univariate Cox regression analysis. Then, we constructed a prognostic model using the least absolute shrinkage and selection operator (LASSO) and Cox analysis to determine the independent prognosis FRGs. Based on this model, risk scores were calculated for the OCSCC samples. The model's capability was further evaluated by the receiver operating characteristic curve (ROC). Then, we used the GSE41613 dataset as an external validation cohort to confirm the model's predictive capability. Next, the immune infiltration and somatic mutation analysis were applied. Lastly, single-cell transcriptomic analysis was used to identify the key cells. RESULTS: A total of 12 prognostic FRGs were identified. Eventually, 6 FRGs were screened as independent predictors and a prognostic model was constructed in the training dataset, which significantly stratified OCSCC samples into high-risk and low-risk groups based on overall survival. The external validation of the model using the GSE41613 dataset demonstrated a satisfactory predictive capability for the prognosis of OCSCC. Further analysis revealed that patients in the highrisk group had distinct immune infiltration and somatic mutation patterns from low-risk patients. Mast cell infiltrations were identified as prognostic immune cells and played a role in OCSCC partly through ferroptosis. CONCLUSION: We successfully constructed a novel 6 FRGs model and identified a prognostic immune cell, which can serve to predict clinical prognoses for OCSCC. Ferroptosis may be a new direction for immunotherapy of OCSCC.

Intratumoral CD103+ CD8+ T cells predict response to neoadjuvant chemoimmunotherapy in advanced head and neck squamous cell carcinoma.

BACKGROUND: Immune cell heterogenicity is known to determine the therapeutic response to cancer progression. Neoadjuvant chemoimmunotherapy (NACI) has shown clinical benefits in some patients with advanced head and neck squamous cell carcinoma (HNSCC), but the underlying mechanism behind this clinical response is unknown. The efficacy of NACI needs to be potentiated by identifying accurate biomarkers to predict clinical responses. Here, we attempted to identify molecules predicting NACI response in advanced HNSCC. METHODS: We performed combined single-cell RNA sequencing (scRNA-seq) and multiplex immunofluorescence (mIHC) staining with tumor samples derived from NACI-treated HNSCC patients to identify a new tumor-infiltrating cell (TIL) subtype, CD103+ CD8+ TILs, associated with clinical response, while both in vitro and in vivo assays were carried out to determine its antitumor efficiency. The regulatory mechanism of the CD103+ CD8+ TILs population was examined by performing cell-cell interaction analysis of the scRNA-seq data and spatial analysis of the mIHC images. RESULTS: We established intratumoral CD103+ CD8+ TILs density as a determinant of NACI efficacy in cancers. Our scRNA-seq results indicated that the population of CD103+ CD8+ TILs was dramatically increased in the responders of NACI-treated HNSCC patients, while mIHC analysis confirmed the correlation between intratumoral CD103+ CD8+ TILs density and NACI efficacy in HNSCC patients. Further receiver operating characteristic curve analysis defined this TIL subset as a potent marker to predict patient response to NACI. Functional assays showed that CD103+ CD8+ TILs were tumor-reactive T cells, while programmed cell death protein-1 (PD-1) blockade enhanced CD103+ CD8+ TILs cytotoxicity against tumor growth in vivo. Mechanistically, targeting the triggering receptor expressed on myeloid cells 2-positive (TREM2+ ) macrophages might enhance the population of CD103+ CD8+ TILs and facilitate antitumor immunity during NACI treatment. CONCLUSIONS: Our study highlights the impact of intratumoral CD103+ CD8+ TILs density on NACI efficacy in different cancers, while the efforts to elevate its population warrant further clinical investigation.

Cancer-associated fibroblasts in the invasive tumour front promote the metastasis of oral squamous cell carcinoma through MFAP5 upregulation.

Cancer-associated fibroblasts (CAFs) are widely involved in the development and progression of tumours. As a direct junction between tumour and normal host tissue, the invasive tumour front can remodel host tissue to generate a microenvironment more suitable for tumour invasion. However, whether CAFs derived from the invasive front (CAFs-F) have a greater ability to promote tumour invasion than CAFs derived from the superficial tumour (CAFs-S) is unclear. In this study, we characterized primary CAFs from different spatial locations of tumours. We demonstrated that CAFs-F had an increased ability to promote oral squamous cell carcinoma (OSCC) proliferation and invasion in vitro and significantly enhanced tumour growth in vivo compared to CAFs-S. Mechanistically, transcriptome profiling analysis revealed that the expression of MFAP5, encoding microfibril associated protein 5, was dramatically increased in CAFs-F compared to CAFs-S, which further confirmed that the MFAP5 protein level was elevated in head and neck squamous cell carcinoma (HNSCC) and that this increase was correlated with poor survival. Genetic ablation of MFAP5 impaired the preinvasive capabilities of CAFs-F. Together, our findings demonstrated that CAFs-F had a greater ability to promote tumour invasion than CAFs-S and that MFAP5 might be involved in this process.

Bibliometric Analysis of Chimeric Antigen Receptor-Based Immunotherapy in Cancers From 2001 to 2021.

Background: Chimeric antigen receptor (CAR)-based immunotherapy has shown great potential for the treatment of both hematopoietic malignancies and solid tumors. Nevertheless, multiple obstacles still block the development of CAR-based immunotherapy in the clinical setting. In this study, we aimed to summarize the research landscape and highlight the front lines and trends of this field. Methods: Literature published from 2001 to 2021 was searched in the Web of Science Core Collection database. Full records and cited references of all the documents were extracted and screened. Bibliometric analysis and visualization were conducted using CiteSpace, Microsoft Excel 2019, VOSviewer and R software. Results: A total of 5981 articles and reviews were included. The publication and citation results exhibited increasing trends in the last 20 years. Frontiers in Immunology and Blood were the most productive and most co-cited journals, respectively. The United States was the country with the most productive organizations and publications in the comprehensive worldwide cooperation network, followed by China and Germany. June, C.H. published the most papers with the most citations, while Maude, S.L. ranked first among the co-cited authors. The hotspots in CAR-based therapy research were multiple myeloma, safety and toxicity, solid tumors, CAR-engineered immune cells beyond T cells, and gene editing. Conclusion: CAR-based immunotherapy is a promising treatment for cancer patients, and there is an emerging movement toward using advanced gene modification technologies to overcome therapeutic challenges, especially in solid tumors, and to generate safer and more effective universal CAR-engineered cell products.

Correlation Between TCF7+ T Cells and Prognosis of Patients With Oral Squamous Cell Carcinoma.

Objective: To investigate whether TCF7+ T cells constitute an important factor to improve the existing postoperative prediction model for patients with oral squamous cell carcinoma. Method: TCF7+ T cells were detected in the tissues of 167 OSCC patients by multiplex immunofluorescence. The percentage of TCF7+ T cells was transformed into a dichotomous variable, combined with the clinicopathological data for the OSCC patients, and then subjected to univariate and multivariate analyses. The derived independent predictors were then incorporated into risk models to analyze their relationship with the prognosis of patients. Results: The high TCF7+ group had a better prognosis than the low TCF7+ group (OS: p<0.001; RFS: p<0.001). Univariate and multivariate analyses showed that TCF7+ T cells serve as an independent predictor of OSCC (univariate/multivariate analysis: p<0.001). In Cox risk progression models, inclusion of the TCF7+ T cell percentage improved the predictive accuracy of Grade and TNM stage (Grade-OS/RFS: p<0.001; TNM-OS/RFS: p<0.001; TNM+Grade-OS: p<0.001, TNM+Grade-RFS: p=0.004). Inclusion of the TCF7+ T cell percentage improved the clinical utility. Conclusions: TCF7+ T cells can act as an independent predictor for postoperative OSCC patients. The inclusion of TCF7+ T cells improved the predictive accuracy and clinical utility of the nomograms to different degrees.

Identification and validation of seven RNA binding protein genes as a prognostic signature in oral cavity squamous cell carcinoma.

RNA binding proteins (RBPs) play a pivotal role in various biological processes, and aberrant expression of RBPs is closely associated with tumorigenesis and progression. However, the role of RBPs in oral cavity squamous cell carcinoma (OCSCC) is yet unveiled. In this study, RNA sequences and clinical information of OCSCC samples were acquired from The Cancer Genome Atlas (TCGA) database. A total of 650 RBPs, with significantly different expression between healthy and OCSCC samples, were identified using the limma package. A prognostic model was constructed by Lasso-Cox analysis, resulting in the determination of 7 prognosis-related RBPs: ERMP1, RNASE3, ARL4D, CSRP2, ULK1, ZC3H12D, and RPS28. Based on the prognostic model, the risk scores of the OCSCC samples were calculated. The capability of the prognostic model was further evaluated using the receiver operating characteristic curve (ROC). The areas under ROC were 0.764, 0.771, and 0.809 at 1, 3 and 5-year respectively in the TCGA dataset. Internal and external validation showed satisfactory predictive capability for prognosis in OCSCC. In addition, a nomogram was created to graphically present the model. To further validate the analytical data, qRT-PCR was performed on normal and OCSCC cell lines. The mRNA expression of the 7 prognostic genes was in accordance with the analytical results. Functional analysis and gene connection networks were used to describe the biological functions and underlying interactions among the 7 prognostic genes Overall, 7 prognosis-related RBPs were identified, which could be used to predict clinical prognosis and to identify potential therapeutic targets for OCSCC.

Primary clinical study of radiomics for diagnosing simple bone cyst of the jaw.

OBJECTIVE: To screen the radiomic features of simple bone cysts of the jaws and explore the potential application of radiomics in pre-operative diagnosis of jaw simple bone cysts. METHODS: The investigators designed and implemented a case-control study. 19 patients with simple bone cysts who were admitted to the Department of Maxillofacial Surgery, Sun Yat-sen University Affiliated Stomatology Hospital from 2013 to 2019 were included in this study. Their clinical data and cone-beam computed tomography (CBCT) images were examined. The control group consisted of patients with odontogenic keratocyst. CBCT imaging features were analyzed and compared between the patient and control groups. RESULTS: Overall, 10,323 image features were extracted through feature analysis. A subset of 25 radiomic features obtained after feature selection were analyzed further. These 25 features were significantly different between the 2 groups (p < 0.05). The absolute value of correlation coefficient was 0.487-0.775. Gray-level co-occurrence matrix (GLCM) contrast, neighborhood gray tone difference matrix (NGTDM) contrast, and GLCM variance were the features with the highest correlation coefficients. CONCLUSIONS: Pre-operative radiomics analysis showed the differences between simple bone cysts and odontogenic keratocysts, can help to diagnose simple bone cysts. Three specific texture features-GLCM contrast, NGTDM contrast, and GLCM variance-may be the characteristic imaging features of simple bone cysts of the jaw.

Single-cell profiling of tumor-infiltrating TCF1/TCF7+ T cells reveals a T lymphocyte subset associated with tertiary lymphoid structures/organs and a superior prognosis in oral cancer.

OBJECTIVES: Despite substantial advances in treatment, clinical outcomes for oral squamous cell carcinoma (OSCC) remain unsatisfactory. Tumor-infiltrating lymphocytes (TILs) are an important prognostic factor for patients and are heterogeneous. Some studies have suggested that TCF1/TCF7+ T cells and tertiary lymphatic structure/organ (TLS) play an important role in tumor immunity. However, how they affect tumor immunity and whether they are related to prognosis in OSCC have not been reported in detail. MATERIALS AND METHODS: We isolated OSCC cells and performed single-cell RNA sequencing (scRNA-seq). We used immunohistochemistry (IHC) to analyze the relationship between TLSs and prognosis. Multiplex immunohistochemistry (MIHC), flow cytometry (FCM) and spatial analysis were performed to verify the characteristics of TCF1/TCF7+ T cells. The prognostic significance and upstream regulatory network of the TCF1/TCF7+ T cell subpopulation were determined by multivariate analysis and Scenic software. RESULTS: We found a strong association between TCF1/TCF7+ T cell subsets, TLSs and prognosis. The results suggested that TCF1/TCF7+ T cells express high levels of TLS-related genes and low levels of immune checkpoint molecules. Finally, we found that TCF1/TCF7+ T cells were significantly associated with favorable outcomes. We also describe the upstream drivers that these cells rely on. CONCLUSIONS: TCF1/TCF7+ T cells could be used as a new therapeutic target to regulate the immune response of OSCC and are expected to be a new prognostic marker.

Integrative Bioinformatics Analysis Demonstrates the Prognostic Value of Chromatin Accessibility Biomarkers in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) accounts for 75%-85% of renal cell carcinoma (RCC) and has a poor 5-year survival rate. In recent years, medical advancement has promoted the understanding of the histopathological and molecular characterization of ccRCC; however, the carcinogenesis and molecular mechanisms of ccRCC remain unclear. Chromatin accessibility is an essential determinant of cellular phenotype. This study aimed to explore the potential role of chromatin accessibility in the development and progression of ccRCC. By the combination of open-access genome-wide chromatin accessibility profiles and gene expression profiles in ccRCC, we obtained a total of 13,474 crucial peaks, corresponding to 5,120 crucial genes and 9,185 differentially expressed genes. Moreover, two potential function modules (P2 and G4) that contained 129 upregulated genes were identified via the weighted gene co-expression network analysis (WGCNA). Furthermore, we obtained five independent predictors (FSCN1, SLC17A9, ANKRD13B, ADCY2, and MAPT), and a prognostic model was established based on these genes through the least absolute shrinkage and selection operator-proportional hazards model (LASSO-Cox) analysis. This model can stratify the ccRCC samples into a high-risk and a low-risk group, from which the patients have distinct prognosis. Further analysis demonstrated a completely different immune cell infiltration pattern between these two risk groups. This study also suggested that mast cell resting is associated with the prognosis of ccRCC and could be a target of immunotherapy. Overall, this study indicated that chromatin accessibility plays an essential role in ccRCC. The five prognostic chromatin accessibility biomarkers and the prognostic immune cells can provide a new direction for the treatment of ccRCC.

Self-adaptive weighted level set evolution based on local intensity difference for parotid ducts segmentation.

BACKGROUND: Parotid ducts (PDs) play an important role in the diagnosis and treatment of parotid lesions. Segmentation of PDs from Cone beam computed tomography (CBCT) images has a significant impact to the pathological analysis of the parotid gland. Although level set methods (LSMs) have achieved considerable success in medical imaging segmentation, it is still a challenging task for existing LSMs to precisely and self-adaptively segment PDs from parotid duct (PD) images with both noise, intensity inhomogeneity, and vague boundary. In this paper, we propose a novel Self-adaptive Weighted level set method via Local intensity Difference (SWLD) to comprehensively solve the above issues. METHOD: Firstly, a new adaptive weighted operator based on local intensity variance difference has been proposed to overcome the limitations of previous LSMs that are sensitive to parameters, which achieves the aim of automatic segmentation. Secondly, we introduce local intensity mean difference into the energy function to improve the curve evolution efficiency. Thirdly, we eliminate the effects of intensity inhomogeneity, noise, and boundary blur in the parotid image through a local similarity factor with two different neighborhood sizes. RESULTS: Using the same dataset, segmentation of PDs is performed using the proposed SWLD algorithm and existing LSM algorithms. The mean Dice score for the proposed algorithm is 91.3%, and the corresponding mean Hausdorff distance (HD) is 1.746. CONCLUSION: Experimental results demonstrate that the proposed algorithm is superior to many existing level set segmentation algorithms, and it can accurately and automatically segment the PDs even in complex gradient boundaries.

Osteochondroma of the coronoid process: A case report and review of the literature.

Osteochondroma (OC) is considered the most common tumor of the axial skeleton, although it is relatively uncommon in the craniofacial region. The present study describes an atypical case of OC of the coronoid process. A 34-year-old woman presented with severely limited mouth opening (5 mm) and swelling of the right zygoma. Cone-beam computed tomography (CBCT) revealed a mushroom-shaped outgrowth from the coronoid process to the inner surface of the zygomatic arch, forming a pseudojoint. The patient was treated with coronoidectomy via an intraoral approach. Histopathological examination revealed features suggestive of OC. Subsequently, the patient was able to open their mouth, and there was no evidence of recurrence or post-operative complications in the 21-month follow-up. A review of the literature revealed only 38 histologically proven cases of coronoid OC in the past 30 years (1989-2018). The incidence of the disease was higher in men compared with that in women (male:female, 2.17:1), and the median age at onset was 28.7 years, with a range of 5-57 years. Gradual limitation of mouth opening and facial asymmetry are the most noticeable symptoms. Water's view and submentovertex projection of the zygomatic arch may be useful in identifying the tumor and its association with the zygoma, while CT and CBCT permit a detailed visualization of the location and density of the tumor. Coronoidectomy is the preferred treatment option, and the prognosis is excellent, with no evidence of recurrence or malignant transformation.

Upregulation of interleukin-8 and activin A induces osteoclastogenesis in ameloblastoma.

Ameloblastoma is a common odontogenic benign tumor located in the jaws and is characterized by severe local bone destruction. The current study aimed to investigate the effect of interactions between tumor cells and bone marrow stromal cells (BMSCs) on osteoclast formation in ameloblastoma. The impact of ameloblastoma/BMSC interactions on cytokine production, gene expression and osteoclastogenesis was examined using an immortalized ameloblastoma cell line that the authors' previously established. The results demonstrated that interactions between ameloblastoma cells and BMSCs increased interleukin (IL)­8 and activin A secretion by BMSCs. IL­8 expression in BMSCs was modulated by tumor­derived tumor necrosis factor­α and IL­8 contributed to osteoclast formation not only directly but also by stimulating receptor activator of NF­κB ligand (RANKL) expression in BMSCs. Activin A secretion in BMSCs was stimulated by ameloblastoma cells via cell­to­cell­mediated activation of c­Jun N­terminal kinase activation, acting as a cofactor of RANKL to induce osteoclast formation and function. The present study highlights the critical role of communication between BMSCs and ameloblastoma cells in bone resorption in ameloblastoma.

Role of Salivary Duct Morphology in the Etiology of Chronic Obstructive Parotitis: Statistical Analysis of Sialographic Features and Computational Fluid Dynamics Analysis of Salivary Flow.

PURPOSE: The causes of some cases of chronic obstructive parotitis (COP) without obstructive factors are still unclear. The authors hypothesized that some morphologic features of salivary ducts might contribute to the development of COP. This study investigated the role of salivary duct morphology in the etiology of COP. MATERIALS AND METHODS: The authors designed and implemented a case-and-control study. Cases were defined as patients with COP, diagnosed from September 2014 to May 2017 at the Affiliated Hospital of Stomatology of the Sun Yat-sen University (Guangzhou, China), and controls were healthy participants. The primary predictor variables were the occurrence of an accessory duct (AD), the number of branches uniting to form the Stensen duct (SD), the angle between the AD and the SD, and the angle between branches identified on sialographic computed tomograms. Data from the 2 groups were compared to investigate the association between these variables and COP. The χ2 test, Student t test, and logistic regression were computed, with significance set at a P value less than .05. Fluid dynamics analysis was used to analyze salivary flow field in models of salivary ducts with different morphologic features reconstructed from sialographic computed tomograms. RESULTS: The sample was composed of 39 patients with COP and 18 controls without COP. The 2 groups were not similar for incidences of an AD (71.8 vs 38.9%) and the angle between branches (96.5 ± 26.0° vs 71.5 ± 21.2°). There was no relevant difference between groups in the number of branches and the angle between the AD and the SD. The area of low velocity was larger in the model with the wider angle between branches. CONCLUSIONS: The results suggest that the presence of an AD and a wider angle between duct branches are associated with COP.

Detection of salivary protein biomarkers of saliva secretion disorder in a primary Sjögren syndrome murine model.

Saliva secretion disorder is one of the most common symptoms in primary Sjögren syndrome (pSS). Salivary biomarkers related to saliva secretion disorder were identified in a pSS murine model, NOD/ShiLtJ mouse, using differential proteomic analysis. Candidate biomarkers were screened with Kyoto Encyclopedia of Genes and Genomes pathway analysis and validated in saliva and salivary glands by western blotting and immunohistochemistry (IHC). Biological functions were detected using ingenuity pathway analysis (IPA). We identified 1101 salivary proteins from NOD/ShiLtJ mice and BALB/c mice (control). Catenin alpha-3 (CTNNA3), tyrosine-protein phosphatase non-receptor type 6 (PTPN6), Ras-related C3 botulinum toxin substrate (RAC2), and intermediate conductance calcium-activated potassium channel protein 4 (KCNN4) were screened as candidate biomarkers from 225 significantly dysregulated salivary proteins. These proteins participated in adherens junction or saliva secretion pathway and may be related to saliva secretion disorder. Proteomic analysis revealed that CTNNA3, PTPN6, and RAC2 were dysregulated in saliva and salivary glands and showed satisfactory sensitivity and specificity in receiver-operating characteristic curve; KCNN4 showed no statistical difference. IHC and IPA indicated that CTNNA3 may regulate acinar cell morphology, while PTPN6 and RAC2 promoted lymphocyte adhesion in salivary glands. Thus, CTNNA3, PTPN6, and RAC2 may be related to saliva secretion disorder in pSS.

[A fast adaptive active contour model based on local gray difference for parotid duct].

OBJECTIVE: To establish a fast adaptive active contour model based on local gray difference for parotid duct image segmentation. METHODS: On the basis of the LBF model, we added the mean difference of the local gray scale inside and outside the contour as the energy term of the driving evolution curve, and the local gray-scale variance difference was used to replaceλ1 and λ2 as the control term of the energy parameter value. Two local similarity factors of different neighborhood sizes were introduced to correct the effects of image gray unevenness and boundary blur to improve the segmentation efficiency. RESULTS: During image segmentation, this algorithm allowed for adaptive adjustment of the evolution direction, velocity and the energy weight of the internal and external regions according to the difference of gray mean and variance between the internal and external regions. This algorithm was also capable of detecting the actual boundary in a complex gradient boundary region, thus enabling the evolution curve to approach the target boundary quickly and accurately. CONCLUSIONS: The proposed algorithm is superior to the existing segmentation algorithms and allows fast and accurate segmentation of the parotid duct with well-preserved image details.