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MicroRNAs (miRNAs) have been confirmed to play pivotal roles in hepatocellular carcinoma (HCC) carcinogenesis. However, the underlying function of microRNA-33b (miR-33b) in HCC remains unclear. Here, we found that miR-33b level was significantly reduced in both HCC tissues and tumor cell lines. Further, luciferase reporter assay and western blot analysis confirmed that Friend leukemia virus integration 1 (Fli-1) was a direct target of miR-33b. Overexpression of miR-33b dramatically suppressed HCC tumor cell proliferation and cell mobility, but facilitated tumor cell apoptosis in vitro. Besides, restoration of Fli-1 partially attenuated miR-33b-mediated inhibition of cell growth and metastasis via activating Notch1 signaling and its downstream effectors. Our findings demonstrate the important role of miR-33b/Fli-1 axis in HCC progression and provide novel therapeutic candidates for HCC clinical treatment.
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Apoptose/genética , Carcinoma Hepatocelular/genética , Movimento Celular/genética , Proliferação de Células/genética , MicroRNAs/genética , Proteínas dos Microfilamentos/genética , Receptor Notch1/genética , Transativadores/genética , Carcinogênese/genética , Carcinogênese/patologia , Carcinoma Hepatocelular/patologia , Linhagem Celular , Linhagem Celular Tumoral , Progressão da Doença , Regulação Neoplásica da Expressão Gênica/genética , Humanos , Fígado/patologia , Transdução de Sinais/genéticaRESUMO
Mammary mucoepidermoid carcinoma (MEC) is a rare entity. The molecular characteristics of breast MEC have not been fully investigated due to its rarity. We performed a retrospective study among 1000 patients with breast carcinomas and identified four cases of breast MEC. Clinical and demographic data were collected. Immunohistochemistry panels which were used to diagnose salivary gland MEC and breast carcinomas were also performed. MAML2 rearrangements were detected by FISH and fusion partners were identified by RNA sequencing. Whole-exome sequencing (WES) was used to reveal the genomes of these four breast MEC. Then, the biological functions and features of breast MEC were further compared with those of invasive breast carcinomas and salivary gland MEC.According to Ellis and Auclair's methods, these four breast MEC could be classified as low-grade breast MEC. All the patients were alive, and disease-free survival (PFS) ranged from 20 months to 67 months. Among these four breast MEC, two cases were triple-negative, and the other two cases were found to be ER positive, with one also showing HER2 equivocal by immunohistochemical staining, but no amplification in FISH. FISH analysis confirmed the presence of the MAML2 translocation in three of four tumors, and CRTC1-MAML2 fusion was confirmed in two of them by RNA-sequencing. The average coverage size of WES for the tumor mutation burden estimation was 32 Mb. MUC4, RP1L1 and QRICH2 mutations were identified in at least three tumors, and these mutation also existed in breast invasive carcinoma databases (TCGA, Cell 2015; TCGA, Nature 2012). The results showed that there were many genes in breast MEC overlapping with the breast invasive carcinoma databases mentioned above, range from 5 to 63 genes (median:21 genes). Next, we assessed immune cell infiltration levels in these tumors. In all these tumors, M2 macrophages and plasma cell were in the high infiltration group. Our breast MEC showed different results from the salivary gland MEC, whose plasma cells were in the low infiltration group. Overall, we first analyzed the genomics and tumor microenvironment of breast mucoepidermoid carcinoma and proposed our hypothesis that although MECs arising in the breast resemble their salivary gland counterparts phenotypically, our findings indicate that breast MECs probably resemble invasive breast carcinomas at the genetic level and immune cell infiltration levels. More cases and in deep research need to be done to further understand this rare carcinoma.
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Neoplasias da Mama , Carcinoma Mucoepidermoide , Neoplasias das Glândulas Salivares , Humanos , Feminino , Proteínas de Ligação a DNA/genética , Transativadores/genética , Estudos Retrospectivos , Carcinoma Mucoepidermoide/genética , Carcinoma Mucoepidermoide/patologia , Exoma , Sequenciamento do Exoma , Microambiente Tumoral , Fatores de Transcrição/genética , Neoplasias da Mama/genética , Neoplasias das Glândulas Salivares/genética , Neoplasias das Glândulas Salivares/patologia , Genômica , Análise de Sequência de RNA , Proteínas do Olho/genéticaRESUMO
Background: Chronic kidney disease (CKD) has emerged as a significant challenge to human health and economic stability in aging societies worldwide. Current clinical practice strategies remain insufficient for the early identification of kidney dysfunction, and the differential diagnosis of immunoglobulin A nephropathy (IgAN) predominantly relies on invasive kidney biopsy procedures. Methods: First, we assessed a case-control cohort to obtain urine samples from healthy controls and biopsy-confirmed CKD patients. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) was applied to detect urinary peptide and then these urinary peptide profiles were used to construct diagnostic models to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. Furthermore, we assessed the robustness of the diagnostic models and their reproducibility by applying different algorithms. Results: A rapid and accurate working platform for detecting CKD and its IgAN subtype based on urinary peptide pattern detected by MALDI-TOF MS was established. Naturally occurring urinary peptide profiles were used to construct a diagnostic model to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. The performance of several algorithms was assessed and demonstrated that the robustness of the diagnostic models as well as their reproducibility were satisfactory. Conclusions: The present findings suggest that the CKD-related and IgAN-specific urinary peptides discovered facilitate precise identification of CKD and its IgAN subtype, offering a dependable framework for screening conditions linked to renal dysfunction. This will aid in comprehending the pathogenesis of nephropathy and identifying potential protein targets for the clinical management of nephropathy.
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Biomedical image segmentation and classification are critical components in a computer-aided diagnosis system. However, various deep convolutional neural networks are trained by a single task, ignoring the potential contribution of mutually performing multiple tasks. In this paper, we propose a cascaded unsupervised-based strategy to boost the supervised CNN framework for automated white blood cell (WBC) and skin lesion segmentation and classification, called CUSS-Net. Our proposed CUSS-Net consists of an unsupervised-based strategy (US) module, an enhanced segmentation network named E-SegNet, and a mask-guided classification network called MG-ClsNet. On the one hand, the proposed US module produces coarse masks that provide a prior localization map for the proposed E-SegNet to enhance it in locating and segmenting a target object accurately. On the other hand, the enhanced coarse masks predicted by the proposed E-SegNet are then fed into the proposed MG-ClsNet for accurate classification. Moreover, a novel cascaded dense inception module is presented to capture more high-level information. Meanwhile, we adopt a hybrid loss by combining a dice loss and a cross-entropy loss to alleviate the imbalance training problem. We evaluate our proposed CUSS-Net on three public medical image datasets. Experiments show that our proposed CUSS-Net outperforms representative state-of-the-art approaches.
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Processamento de Imagem Assistida por Computador , Dermatopatias , Humanos , Processamento de Imagem Assistida por Computador/métodos , Redes Neurais de Computação , Diagnóstico por Computador/métodosRESUMO
OBJECTIVE: To study the clinicopathologic and prognostic features of neuroendocrine neoplasm of digestive system with different grades. METHODS: The clinicopathologic features of 139 cases of neuroendocrine neoplasm occurring in digestive system were retrospectively reviewed and graded according to the 2010 World Health Organization classification of tumours of the digestive system. Immunohistochemical study for synaptophysin, chromogranin A and Ki-67 was carried out. The follow-up and survival data were analysed using Kaplan-Meier method. Prognostic factors were tested by Log-rank testing and independent risk factors were analysed using Cox regression model. RESULTS: Amongst the 139 cases studied, there were 88 cases (63.3%) of grade 1 tumors, 9 cases (6.5%) of grade 2 tumors and 42 cases (30.2%) of grade 3 tumors. There was diffusely positive staining for synaptophysin and chromogranin A in most of the grade 1 and grade 2 tumors. The staining in grade 3 tumors however was focal (P < 0.05). The differences in tumor size, depth of invasion, presence of tumor emboli, perineural permeation, nodal involvement, distant metastasis and survival rate amongst the three groups was statistically significant (P < 0.05). CONCLUSIONS: There is significant difference in the clinicopathologic and prognostic features of neuroendocrine neoplasm of digestive system with different grades. It is considered as an independent prognostic factor and represents a useful tool for prognostic evaluation of such tumors, both in clinical practice and research.
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Neoplasias do Sistema Digestório/patologia , Gradação de Tumores , Tumores Neuroendócrinos/patologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Cromogranina A/metabolismo , Neoplasias do Sistema Digestório/metabolismo , Feminino , Seguimentos , Humanos , Antígeno Ki-67/metabolismo , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica , Metástase Neoplásica , Células Neoplásicas Circulantes , Tumores Neuroendócrinos/metabolismo , Modelos de Riscos Proporcionais , Estudos Retrospectivos , Taxa de Sobrevida , Sinaptofisina/metabolismo , Carga Tumoral , Adulto JovemRESUMO
Background: Primary common bile duct (CBD) stones can be treated with laparoscopic CBD exploration (LCBDE), during which cholecystectomy is routinely performed. For patients without gallstones, we have developed a new procedure, LCBDE with gallbladder preservation. The purpose of this study was to evaluate the management of LCBDE with gallbladder preservation at our institution. Methods: Retrospective analysis the clinical data of 105 patients with primary CBD stones. Demographic data, clinical characteristics, preoperative risk factors, and postoperative complications were evaluated. Results: All patients were divided into two groups depending on the presence of gallstones: the primary CBD stone coexistence gallstones group (Group A, n = 15) and the primary CBD stones absence gallstones group (Group B, n = 90). Complete stones clearance was achieved in all patients. There were no significant differences in postoperative complications rates and mortality between the two groups. The mean postoperative hospital stay was 3.2 days for Group A and 4.1 days for Group B (P = .03). Conclusion: This study found that LCBDE with gallbladder preservation can effectively and safely treat primary CBD stones without gallbladder stones.
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Colecistectomia Laparoscópica , Coledocolitíase , Cálculos Biliares , Laparoscopia , Colangiopancreatografia Retrógrada Endoscópica/métodos , Colecistectomia Laparoscópica/métodos , Coledocolitíase/complicações , Coledocolitíase/cirurgia , Ducto Colédoco/cirurgia , Cálculos Biliares/complicações , Cálculos Biliares/cirurgia , Humanos , Laparoscopia/métodos , Tempo de Internação , Complicações Pós-Operatórias/cirurgia , Estudos RetrospectivosRESUMO
Medical image segmentation is an essential component of computer-aided diagnosis (CAD) systems. Thyroid nodule segmentation using ultrasound images is a necessary step for the early diagnosis of thyroid diseases. An encoder-decoder based deep convolutional neural network (DCNN), like U-Net architecture and its variants, has been extensively used to deal with medical image segmentation tasks. In this article, we propose a novel N-shape dense fully convolutional neural network for medical image segmentation, referred to as N-Net. The proposed framework is composed of three major components: a multi-scale input layer, an attention guidance module, and an innovative stackable dilated convolution (SDC) block. First, we apply the multi-scale input layer to construct an image pyramid, which achieves multi-level receiver field sizes and obtains rich feature representation. After that, the U-shape convolutional network is employed as the backbone structure. Moreover, we use the attention guidance module to filter the features before several skip connections, which can transfer structural information from previous feature maps to the following layers. This module can also remove noise and reduce the negative impact of the background. Finally, we propose a stackable dilated convolution (SDC) block, which is able to capture deep semantic features that may be lost in bilinear upsampling. We have evaluated the proposed N-Net framework on a thyroid nodule ultrasound image dataset (called the TNUI-2021 dataset) and the DDTI publicly available dataset. The experimental results show that our N-Net model outperforms several state-of-the-art methods in the thyroid nodule segmentation tasks.
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BACKGROUND AND OBJECTIVE: A thyroid nodule is an abnormal lump that grows in the thyroid gland, which is the early symptom of thyroid cancer. In order to diagnose and treat thyroid cancer at the earliest stage, it is desired to characterize the nodule accurately. Ultrasound thyroid nodules segmentation is a challenging task due to the speckle noise, intensity heterogeneity, low contrast and low resolution. In this paper, we propose a novel framework to improve the accuracy of thyroid nodules segmentation. METHODS: Different from previous work, a super-resolution reconstruction network is firstly constructed to upscale the resolution of the input ultrasound image. After that, our proposed N-shape network is utilized to perform the segmentation task. The guidance of super-resolution reconstruction network can make the high-frequency information of the input thyroid ultrasound image richer and more comprehensive than the original image. Our N-shape network consists of several atrous spatial pyramid pooling blocks, a multi-scale input layer, a U-shape convolutional network with attention blocks and a proposed parallel atrous convolution(PAC) module. These modules are conducive to capture context information at multiple scales so that semantic features can be fully utilized for lesion segmentation. Especially, our proposed PAC module is beneficial to further improve the segmentation by extracting high-level semantic features from different receptive fields. We use the UTNI-2021 dataset for model training, validating and testing. RESULTS: The experimental results show that our proposed method achieve a Dice value of 91.9%, a mIoU value of 87.0%, a Precision value of 88.0%, a Recall value 83.7% and a F1-score value of 84.3%, which outperforms most state-of-the-art methods. CONCLUSIONS: Our method achieves the best performance on the UTNI-2021 dataset and provides a new way of ultrasound image segmentation. We believe that our method can provide doctors with reliable auxiliary diagnosis information in clinical practice.
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Neoplasias da Glândula Tireoide , Nódulo da Glândula Tireoide , Humanos , Nódulo da Glândula Tireoide/diagnóstico por imagem , Redes Neurais de Computação , Processamento de Imagem Assistida por Computador/métodos , Ultrassonografia/métodosRESUMO
[This corrects the article DOI: 10.3389/fnins.2022.872601.].
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Automated thyroid nodule classification in ultrasound images is an important way to detect thyroid nodules and to make a more accurate diagnosis. In this paper, we propose a novel deep convolutional neural network (CNN) model, called n-ClsNet, for thyroid nodule classification. Our model consists of a multi-scale classification layer, multiple skip blocks, and a hybrid atrous convolution (HAC) block. The multi-scale classification layer first obtains multi-scale feature maps in order to make full use of image features. After that, each skip-block propagates information at different scales to learn multi-scale features for image classification. Finally, the HAC block is used to replace the downpooling layer so that the spatial information can be fully learned. We have evaluated our n-ClsNet model on the TNUI-2021 dataset. The proposed n-ClsNet achieves an average accuracy (ACC) score of 93.8% in the thyroid nodule classification task, which outperforms several representative state-of-the-art classification methods.
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OBJECTIVE: To evaluate the epidemiological status of HER2 protein expression in Chinese patients with gastric carcinoma, and to study its clinical and prognostic significance and the association with the clinicopathological features. METHODS: The clinical data were reviewed in 860 patients with gastric carcinoma admitted to Guangdong General Hospital from 2003 to 2010. The HER2 status was evaluated using immunohistochemistry (IHC). The modified HercepTest scoring criterion was used to assess HER2 protein expression. The association between HER2 expression and clinicopathological features was analyzed by χ(2) test. Kaplan-Meier analysis, log-rank test and Cox regression model were used for the survival analysis. RESULTS: The median age of the patients was 59 years, and the male-to-female ratio was 2.06:1. Positive expression of HER2 protein (3+) was found in 77 (9.0%) cases of gastric carcinoma, and in 69 (8.9%) advanced gastric cancers. There was significantly positive association between HER2 over-expression and tumor differentiation, Lauren classification and WHO classification. No significant association was observed between HER2 protein expression and patients' age, gender, tumor location and clinical stage. There was no statistically significant difference in survival rate between patients with positive HER2 expression and negative ones. CONCLUSION: Though there was significantly positive association between HER2 expression status and tumor differentiation, histological type, it may be of limited prognostic value in gastric cancer patients.
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Adenocarcinoma/patologia , Receptor ErbB-2/metabolismo , Neoplasias Gástricas/patologia , Adenocarcinoma/metabolismo , Adenocarcinoma/cirurgia , Adenocarcinoma Mucinoso/metabolismo , Adenocarcinoma Mucinoso/patologia , Adenocarcinoma Mucinoso/cirurgia , Adenocarcinoma Papilar/metabolismo , Adenocarcinoma Papilar/patologia , Adenocarcinoma Papilar/cirurgia , Adulto , Idoso , Idoso de 80 Anos ou mais , Povo Asiático , Carcinoma de Células em Anel de Sinete/metabolismo , Carcinoma de Células em Anel de Sinete/patologia , Carcinoma de Células em Anel de Sinete/cirurgia , Feminino , Seguimentos , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Modelos de Riscos Proporcionais , Neoplasias Gástricas/metabolismo , Neoplasias Gástricas/cirurgia , Taxa de Sobrevida , Adulto JovemRESUMO
BACKGROUND: Renal cell carcinoma (RCC) associated with Xp11.2 translocation/TFE3 gene fusion is a rare and new subtype of RCC and was classified by the WHO in 2004. Since then, multiple 5' fusion partners for TFE3 have been reported; however, the impact of individual fusion variant on specific clinicopathologic features of Xp11.2 RCCs has not been well defined. METHODS: Four Xp11.2 translocation RCCs were identified by morphological, immunostaining, and fluorescence in situ hybridization (FISH) assays from 200 patients who attended Guangdong General Hospital between January 2017 and January 2020. All these four cases were further analyzed by RNA sequencing to explore their TFE3 gene fusion partners. The clinicopathologic features, including clinical manifestations, pathological findings, treatment strategies, clinical outcomes, and follow-up information on Xp11.2 translocation RCCs, were recorded and evaluated. RESULTS: These four cases affected one male and three females. The median age was 13 years at the time of diagnosis (range = 4-20 years). All the examined tumors were unilateral and unifocal. The largest diameter of these tumors ranged from 2.0 to 10.0 cm, and the average was 5.55 cm. Regional lymph node or distant metastasis developed in two patients. Three cases demonstrated known fusions: ASPCR1-TFE3 (two cases) and PRCC-TFE3 (one case). However, one case showed an unreported VCP-TFE3 fusion gene in Xp11.2 translocation RCCs. Immunohistochemistry results revealed tumor cells diffusely positive for TFE3, but have no consistency in other markers. Moreover, there were different clinical prognoses among the different variant TFE3 rearrangements; RCC patients with VCP-TFE3 translocation had worse prognosis compared to those with other fusion types. Follow-up were available for all the patients and ranged from 3 to 36 months. Three patients were without evidence of disease progression, while that with VCP-TFE3 fusion died of the disease 3 months after the diagnosis. CONCLUSION: In conclusion, our data expand the list of TFE3 gene fusion partners and the clinicopathologic features of Xp11.2 RCCs with specific TFE3 gene fusions. We identified a novel VCP-TFE3 fusion in Xp11.2 translocation RCCs for the first time, which has unique morphology and worse prognosis than those with other variant TFE3 rearrangements. Integration of morphological, immunohistochemical, and molecular methods is often necessary for the precise diagnosis and optimal clinical management of malignant tumors.
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In this study, UiO-66 was selected as sorbent media packed in the tube to selectively enrich trace levels of benzene homologues such as benzene, toluene, and xylene (BTX) in ambient air prior to thermal desorption (TD)-GC-MS determination. A series of experiments were conducted to obtain the optimal TD conditions. The results indicated that the optimal TD parameters were as follows: desorption temperature of 180°C, desorption flow rate of 50 mL min-1, and desorption time of 30 min. Furthermore, the method based on UiO-66 enrichment integrated with TD-GC-MS for trace levels of BTX was successfully developed. It exhibited a good linearity (R 2 > 0.99) in the range of 50-1000 ng, except for p, m-xylene in the range of 100-2000 ng, and achieved the recovery of 69.4-101.3%, and the relative standard deviation of 3.8-6.4%. The detection limits of BTX were 1.6-4.0 ng; according to 10 L of sampling volume, the method detection limits would be in the range of 0.16-0.40 µg m-3. Additionally, the method was successfully applied to determine BTX in indoor air and showed good selectivity and sensitivity. In summary, the findings in this work revealed that UiO-66 was an attractive adsorbent for selective enrichment trace levels of BTX compounds in ambient air, which was favorable for the subsequent detection by TD-GC-MS.
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Background: Programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC) is considered as a predictive biomarker of anti-PD-1/PD-L1 cancer therapies. However, the correlation of PD-L1 expression status between the primary and paired metastatic NSCLC is still not clear. The current study aims to address this specific issue. Materials and Methods: The PD-L1 expression of the primary and paired metastatic lesions from 110 patients with NSCLC was retrospectively evaluated by immunohistochemical assay using Anti-PD-L1 antibody, Clone 22C3. The results were assessed by the Tumor Proportion Score (TPS) using cutoff values of <1%, 1%-49% and ≥50%. Meanwhile, the Cohen's kappa coefficient (k) of agreement was calculated. Results: An overall concordance rate of the PD-L1 expression between the primary and metastatic lesions was 61% (63/103) (k = 0.39, and P < 0.001). If using TPS considering 1% and 50% as a threshold, the inconsistent rate was 28/103 (27.2%) paired specimens (k = 0.46, and P < 0.001) and 14/103 (13.6%) paired specimens (k = 0.53, and P < 0.001), respectively. Moreover, the concordance of the PD-L1 expression between primary and metastatic tumor was also analyzed according to the clinical stages within the untreated group of patients. We observed that for patients with stage I-III NSCLC, the concordance rate of the PD-L1 expression between primary and metastatic lesions was 81.3% and 100% when using 1% and 50% as threshold, respectively. While in stage IV patients, the concordance rate of the PD-L1 expression between the primary and metastatic lesions drops to 71.4% and 85.7%, respectively. Conclusion: The PD-L1 expression was dynamic as tumor developed, which was valuable in selecting the proper type of sample for accurately evaluating the prognosis of using pembrolizumab as first or second line treatment.
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AIMS: Pseudomyogenic hemangioendothelioma (PHE)/epithelioid sarcoma-like hemangioendothelioma (ES-H) is a rare vascular tumor of intermediate malignancy that commonly occurs in soft tissue of distal extremities of young adults. PHE typically has a multifocal presentation and can involve several tissue planes, including the dermis, subcutis, muscle and bone. METHODS AND RESULTS: We present here a unique case of PHE/ESH that arose in the breast as well as a review of the published literature. The initial biopsy was interpreted as a metaplastic carcinoma. However, complete resection largely revealed plump epithelioid cells, and a more spindled cell component was also noted. The cells displayed abundant eosinophilic cytoplasm and central vesicular nuclei arranged in loose fascicles, with a mild, mixed acute and chronic inflammatory infiltrate. Overall, linear membranous staining of CD31 and lack of CD34 expression were highly suggestive of PHE. At the same time, FOSB immunoreactivity was observed, which supported PHE/ESH instead of metaplastic carcinoma. The patient has not shown recurrence in the half year follow up after total mastectomy. CONCLUSION: To our knowledge, this is the first report of breast involvement in this neoplasm. Recognition of its histopathological features and immunohistochemical reactivity will prevent misdiagnosis of breast lesions.