Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk of postoperative recurrence in breast cancer.

BACKGROUND: The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer. METHODS: A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves. RESULTS: In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability. CONCLUSION: The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.

Role of ICAM-1 in triple-negative breast cancer.

Intercellular adhesion molecule-1 (ICAM-1) is related to the occurrence and development of a variety of tumors. However, the role of ICAM-1 in the regulation of growth, metastasis, and clinical prognosis of the specific molecular subtypes of breast cancer, triple-negative breast cancer (TNBC), remains to be elucidated. This study explored the role of ICAM-1 in breast cancer and its triple-negative subtypes by systematic bioinformatics methods. The results showed that the expression of ICAM-1 in breast cancer tissues was significantly higher than that in normal tissues, especially in TNBC subtypes. In breast cancer, ICAM-1 mainly activates pathways related to apoptosis and epithelial-mesenchymal transition, while its overexpression in TNBC is associated with inflammatory response, apoptosis, and other processes. TNBC patients displaying higher ICAM-1 expression demonstrate enhanced responses to immunotherapy. High ICAM-1 expression is sensitive to drugs targeting tumor cell proliferation, apoptosis, and angiogenesis. In conclusion, breast cancer is characterized by significantly high expression of ICAM-1, with TNBC subtypes expressing ICAM-1 at much higher levels than other subtypes. The diagnosis, prognosis, development, distant metastases, and immunotherapy of TNBC are correlated with high expression of ICAM-1. This research provides available data for the further study of the diagnosis and treatment of TNBC.

Down-regulation of COL1A1 inhibits tumor-associated fibroblast activation and mediates matrix remodeling in the tumor microenvironment of breast cancer.

We investigated the effects of collagen type I alpha 1 (COL1A1) on tumor-associated fibroblast activation and matrix remodeling in the tumor microenvironment of breast cancer. Cells were divided into the blank control, negative control, and siRNA-COL1A1 groups, or HKF control, HKF + exosomes (EXO), HKF + siRNA negative control-EXO, and HKF + siRNA-COL1A1-EXO co-culture groups. Western blot and quantitative real-time PCR detected gene expressions. COL Ⅰ, COL Ⅲ, and TGF-ß1 were detected by enzyme-linked immunosorbent assay. We found that compared with blank and negative control groups, COL1A1 expression and the secretion of exosomes by breast cancer cells were inhibited in the siRNA-COL1A1 group. Compared with the HKF control group, the COL Ⅰ, COL Ⅲ, TGF-ß1, α-SMA, and fibroblast activation protein (FAP) were increased, while the E-cadherin and CAV-1 were decreased in the HKF + EXO, HKF + siRNA negative control-EXO, and HKF + siRNA-COL1A1-EXO co-culture groups. Compared with HKF + EXO and HKF + siRNA negative control-EXO co-culture groups, the COL Ⅰ, COL Ⅲ, TGF-ß1, α-SMA, and FAP were decreased, and the E-cadherin and CAV-1 were increased in the HKF + siRNA-COL1A1-EXO co-culture group. Collectively, COL1A1 down-regulation may inhibit exosome secretion possibly via inhibiting COL Ⅰ and upregulating CAV-1, thereby inhibiting tumor-associated fibroblast activation and matrix remodeling in the tumor microenvironment.

A Flexible Eddy Current TMR Sensor for Monitoring Internal Fatigue Crack.

This paper proposes a flexible eddy current TMR (FEC-TMR) sensor to monitor the internal crack of metal joint structures. First, the finite element model of the FEC-TMR sensor is established to analyze the influence of the sensor's crack identification sensitivity with internal crack propagation at different depths and determine the optimal location and exciting frequency of the sensor. Then, the optimal longitudinal spacing and exciting frequency of the sensor are tested by experiment. The experimental results are consistent with the simulation results, which verify the correctness of the simulation model. Finally, the experiment is carried out for internal cracks of different depths to verify that the sensor can monitor internal cracks, and the crack identification sensitivity gradually decreases with the increase in the depth of the crack from the surface.

Erratum to "BRCA1 subcellular localization regulated by PI3K signaling pathway in triple-negative breast cancer MDA-MB-231 cells and hormone-sensitive T47D cells".

[This corrects the article DOI: 10.1515/biol-2020-0054.].

NAA20 recruits Rin2 and promotes triple-negative breast cancer progression by regulating Rab5A-mediated activation of EGFR signaling.

Triple-negative breast cancer (TNBC) is the most aggressive subtype with poor prognosis and high mortality. To improve the prognosis and survival of TNBC patients, it is necessary to explore new targets and signaling pathways to develop novel therapies for TNBC treatment. N-α-acetyltransferase 20 (NAA20) is one of the catalytic subunits of N-terminal acetyltransferase (NatB). It has been reported that NAA20 played a critical role in cancer progression. In this study, we found that NAA20 expression was markedly higher in TNBC tissues than in paracancerous normal tissues using The Cancer Genome Atlas (TCGA) analysis. This result was further confirmed by qRT-PCR and immunohistochemistry (IHC). Knockdown of NAA20 significantly inhibited TNBC cell viability by CCK8 and colony formation assays and cell migration and invasion by Transwell assays. Additionally, NAA20 knockdown decreased the expression of EGFR in TNBC cells. Upon stimulation with EGF and knockdown of NAA20, EGFR internalization and degradation were observed by confocal microscopy. The western blot results showed that NAA20 knockdown down-regulated PI3K, AKT, and mTOR phosphorylation. Next, we further explored the underlying molecular mechanisms of NAA20 by co-immunoprecipitation (Co-IP). The results suggested that there was an interacting relationship between NAA20 and Rab5A. Over-expression of NAA20 could potentiate the expression of Rab5A. Furthermore, the knockdown of Rab5A inhibited EGFR expression and the phosphorylation of downstream signaling targets. NAA20 over-expression offset the knockdown effect of Rab5A and activated EGFR signaling. Finally, we constructed a xenograft mouse model transfected TNBC cells to investigate the role of NAA20 in vivo. NAA20 knockdown markedly suppressed tumor growth and decreased tumor volume and weight. In conclusion, our study demonstrated that NAA20, a novel target of TNBC, could promote TNBC progression by regulating Rab5A-mediated activation of EGFR signaling.

Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy.

Objective: The effect of chemotherapy in patients with breast cancer (BC) is uncertain. This study attempted to analyze serum microRNAs (miRNAs) in NAC resistant and sensitive BC patients and develop a miRNA-based nomogram model. To further help clinicians make treatment decisions for hormone receptor-positive patients. Methods: A total of 110 BC patients with NAC were recruited and assigned in sensitive and resistant group, and 4 sensitive patients and 3 resistant patients were subjected to high-throughput sequencing. The functions of their target genes were analyzed by GO and KEGG. Five BC-related reported miRNAs were selected for expression pattern measurement by RT-qPCR and multivariate logistic analysis. The nomogram model was developed using R 4.0.1, and its predictive efficacy, consistency and clinical application value in development and validation groups were evaluated using ROC, calibration and decision curves. Results: There were 44 differentially-expressed miRNAs in resistant BC patients. miR-3646, miR-4741, miR-6730-3p, miR-6831-5p and miR-8485 were candidate for resistance diagnosis in BC. Logistic multiple regression analysis showed that miR-4741 (or = 0.30, 95% CI = 0.08-0.63, P = 0.02) and miR-6831-5p (or = 0.48, 95% CI = 0.24-0.78, P = 0.01) were protective factors of BC resistance. The ROC curves showed a sensitivity of 0.884 and 0.750 for miR-4741 and miR-6831-5P as markers of resistance, suggesting that they can be used as independent risk factors for BC resistance. The other 3 miRNAs can be used as calibration factors to establish the risk prediction model of resistance in BC. In risk model, the prediction accuracy of resistance of BC is about 78%. 5-miRNA signature diagnostic models can help clinicians provide personalized treatment for NAC resistance BC patients to improve patient survival. Conclusion: MiR-4741 and miR-6831-5p are independent risk factors for breast cancer resistance. This study constructed a nomogram model of NAC resistance in BC based on 5 differentially-expressed serum miRNAs.

Screening and Bioinformatics Analysis of MicroRNA Biomarkers in Triple-Negative Breast Cancer.

OBJECTIVE: To identify and evaluate the bioinformatics of microRNA (miRNA) biomarkers in triple-negative breast cancer. METHODS: The MDA-MB-231 cell line with stable and low expression of c-Myc was created, and the expression patterns of messenger RNA (mRNA) and miRNA were investigated by cluster analysis. The genes regulated by c-Myc were then screened by transcriptome sequencing and miRNA sequencing. The negative binomial distribution of the DESeq software package was used to test for and determine the differential expression of genes. RESULTS: In the c-Myc deletion group, 276 differently expressed mRNAs were screened out by transcriptome sequencing, of which 152 mRNAs were considerably upregulated and 124 were significantly downregulated in comparison to the control group. One-hundred-seventeen (117) differentially expressed miRNAs were found using miRNA sequencing, of which 47 showed a substantial upregulation and 70 a significant downregulation. According to the Miranda algorithm, 1803 mRNAs could be targeted by 117 differently expressed miRNAs. Comparing the two sets of data, a total of 5 miRNAs were differentially expressed after targeted binding with 21 mRNAs, which were subjected to GO and KEGG enrichment analysis. The genes regulated by c-Myc were mainly enriched in signaling pathways such as extracellular matrix receptors and Hippo. CONCLUSION: Twenty-one target genes and five differential miRNAs in the mRNA-c-Myc-miRNA regulatory network are potential therapeutic targets for triple-negative breast cancer.

Dual Target of EGFR and mTOR Suppresses Triple-Negative Breast Cancer Cell Growth by Regulating the Phosphorylation of mTOR Downstream Proteins.

Objective: To detect the activation of the EGFR and mTOR signaling pathways in the triple negative breast cancer cell line MDA-MB-468 and investigate the inhibitory effect of gefitinib, an epidermal growth factor receptor inhibitor, and everolimus, a target protein inhibitor of rapamycin, on triple negative breast cancer cells. Methods: Triple negative human breast cancer MDA-MB-468 cells were cultured and blank control group, single EGFR inhibitor gefitinib group, single mTOR inhibitor everolimus group, and two drug combination group were set up respectively to detect the effects of single and combined drugs on cell proliferation activity, cell cycle and apoptosis, and the expression of EGFR and mTOR signal pathway proteins in cell lines after single and combined drug intervention was detected again by Western blot. Results: The level of EGFR and p-mTOR protein in triple negative breast cancer was higher than in non triple negative breast cancer (P<0.05). The level of mTOR, S6K1, p-EGFR, p-S6K1 was significantly increased when treated with EGF (0ng/mL, 10ng/mL, 100ng/mL) for 1h, compared to without EGF stimulation (P<0.05). The level of p-EGFR, p-mTOR, p-S6K1 protein increased significantly when the cells were exposed to EGF for 2h, respectively (P<0.05). EGFR inhibitor gefitinib alone and the mTOR inhibitor everolimus alone could significantly inhibit the proliferation of human triple negative breast cancer MDA-MB-468 cells in a dose-dependent manner (P<0.05). The level of p-4EBP1 protein in EGFR and mTOR signal pathway was significantly increased after the intervention of gefitinib alone, everolimus alone, and the combination of two drugs (P<0.05). Conclusion: EGFR and mTOR signaling pathways can be activated in triple negative breast cancer; Both the EGFR inhibitor gefitinib alone and the mTOR inhibitor everolimus alone can significantly inhibit the proliferation of human triple negative breast cancer MDA-MB-468 cells. The combination of the EGFR inhibitor gefitinib and the mTOR inhibitor everolimus may achieve anti-tumor effect similar to that of single drug by reducing the drug dose.

Exosomal miR-655-3p inhibits growth, and invasion and macrophage M2 polarization through targeting CXCR4 in papillary thyroid carcinoma.

Papillary thyroid cancer (PTC) is an endocrine malignancy whose incidence has increased rapidly worldwide. Exosome-miR-655-3p was down-regulated in patients with PTC. However, the effect and molecular mechanism of exosome-miR-655-3p in PTC was indistinct until now. Our study found that exosome-miR-655-3p was decreased in serum of PTC patients. Overexpression of miR-655-3p with mimics significantly shrunk the cell viability, reduced the number of chemotactic and invasive PTC cells. Besides, the proportion of CD163 positive cells and the expression of markers of M2 subtype macrophages was markedly decreased when mononuclear macrophage THP-1 was cultured with exosomes of miR-655-3p mimics. Oppositely, the inhibitor of miR-655-3p exacerbated growth, chemotaxis and invasion of PTC cells, and enhanced the M2 subtype macrophages. Structurally, miR-655-3p could target the 3' untranslated region (3'UTR) of CXCR4 and restrict the expression of CXCR4. In Xenograft tumor experiment, upregulated exosome-miR-655-3p effectively inhibited the growth of tumor and reduced the expression of CXCR4, Ki67 and CD163 in vivo. In summary, exosomal miR-655-3p inhibited growth, invasion and macrophage M2 polarization through targeting CXCR4 in papillary thyroid carcinoma. Regulating exosome-miR-655-3p/CXCR4 may be a potential treatment strategy for PTC.

The Involvement of Insulin-Like Growth Factor 2 Messenger Ribonucleic Acid-Binding Protein 2 in the Regulation of the Expression of Breast Cancer-Related Genes.

Aim: This study investigated the role and mechanism of insulin-like growth factor 2-IGF2BP2 in breast cancer. Methods: IGF2BP2 is overexpressed in MDA-MB-231 human breast cancer cells. Thus, RNA sequencing was used to analyze the differentially expressed genes, Cell Counting Kit-8 was used to detect cell proliferation, and a Transwell assay was used to assess cell invasion. Following on from the RNA sequencing results, Interferon-induced protein with tetratricopeptide repeats 2 (IFIT2), chemokine C-C motif ligand 20 (CCL20), chemokine C-C motif ligand 5 (CCL5), and chemokine C-X-C motif ligand 10 (CXCL10) regulated by IGF2BP2 were subjected to real-time reverse transcriptase-polymerase chain reaction verification. Results: After IGF2BP2 overexpression, 67 genes were up-regulated, and 87 genes were down-regulated. The gene with the most significant up-regulation was homeobox protein 1 (PROX1), and the gene with the most significant down-regulation was Acidic ß-crystallin 4 (CRYBA4). The most enriched gene ontology (GO) terms of up-regulated differentially expressed genes are protein binding and cell membrane and of down-regulated differentially expressed genes they are ion binding, cytoplasm, and response to virus. Kyoto Encyclopedia of Genes and Genomes analysis showed that the up-regulated differential genes were mainly enriched in protein processing, the endoplasmic reticulum, and the regulation of actin cytoskeleton, while down-regulated differential genes were mainly enriched in rheumatoid arthritis, chemokine signaling pathways, toll-like receptor signaling pathways, tumor necrosis factor signaling pathways, cytokine-cytokine receptor interaction, and Notch signaling pathways. IGF2BP2 overexpression significantly promoted the proliferation and invasion of breast cancer cells (P < 0.01). Compared with the control group, the IGF2BP2 overexpression group had significantly increased expressions of IFIT2, CCL20, and CXCL10 (P < 0.05). Conclusion: IGF2BP2 may promote the invasion and proliferation of human breast cancer cells by up-regulating breast cancer-related genes, such as IFIT2, CCL20, and CXCL10.

Serum Raman spectroscopy combined with multiple classification models for rapid diagnosis of breast cancer.

Breast cancer is a malignant tumor with the highest incidence rate in women. Current diagnostic methods are time-consuming, costly, and dependent on physician experience. In this study, we used serum Raman spectroscopy combined with multiple classification algorithms to implement an auxiliary diagnosis method for breast cancer, which will help in the early diagnosis of breast cancer patients. We analyzed the serum Raman spectra of 171 invasive ductal carcinoma (IDC) and 100 healthy volunteers; The analysis showed differences in nucleic acids, carotenoids, amino acids, and lipid concentrations in their blood. These differences provide a theoretical basis for this experiment. First, we used adaptive iteratively reweighted penalized least squares (airPLS) and Savitzky-Golay (SG) for baseline correction and smoothing denoising to remove the effect of noise on the experiment. Then, the Principal component analysis (PCA) algorithm was used to extract features. Finally, we built four classification models: support vector machine (SVM), decision tree (DT), linear discriminant analysis (LDA), and Neural Network Language Model (NNLM). The LDA, SVM, and NNLM achieve 100% accuracy. As supplementary, we added the classification experiment of the raw data. By comparing the experimental results of the two groups, We concluded that the NNLM was the best model. The results show the reliability of the combination of serum Raman spectroscopy and classification models under large sample conditions.

Grouped-sampling technique to deal with unbalance in Raman spectral data modeling.

Due to limitations in disease prevalence and hospital specificity, spectral data are often collected with unbalanced sample size. To solve this problem, a new sampling method - grouped-sampling was proposed in this research, which is shown to be effective for unbalanced data. It avoids over-fitting of over-sampling and overcomes under-sampling utilization of under-sampling. In this study, we applied grouped-sampling to two unbalanced datasets where the sample proportions are 199:40 and 75:225. And then verified from two classic models: PCA-SVM (Principal Component Analysis-Support Vector Machine) and the deep learning algorithm GoogLeNet. The accuracy of these two datasets were 85.11% and 96.15% in PCA-SVM and 85.10% and 84.61% on GoogLeNet. Also, the F1-score were evaluated to measure the classification balance of sampling method, and result shows that F1-score of grouped-sampling is always the highest compared to over-sampling and under-sampling. In summary, compared to traditional sampling methods, grouped-sampling performs better on prediction for classes with smaller sample size, which means grouped-sampling can improve the balance of classification results and the potential of practical application. Therefore, we develop a group sampling method that distinguishes between under- and over-sampling, which greatly improves the accuracy and balance of predictions for unbalanced samples.

Thyroidectomy Using the Lateral Cervical Small Incision Approach for Early Thyroid Cancer.

Objective: Surgical resection is the main treatment for thyroid cancer, but while traditional open thyroidectomy improves prognosis, it also results in poor cosmetic outcomes. Therefore, we devised the lateral cervical small incision approach to thyroidectomy and will evaluate its efficacy. Methods: The clinicopathological data of 191 patients who underwent unilateral thyroidectomy and isthmusectomy for early thyroid cancer were collected retrospectively. Of these, 100 patients underwent a traditional thyroidectomy using the median cervical approach (control group), and 91 patients underwent a thyroidectomy using the lateral cervical small incision approach (experimental group). The differences in perioperative prognosis, postoperative complications, and cosmetic outcomes between the two groups were evaluated. Results: There was no significant difference in sex, age, tumor size, lymph node dissection, number of metastases, or postoperative complications between the experimental group and the control group (P > 0.05). There were significant differences in the duration of the operation; postoperative blood loss, drainage, and hospital stay; and scar color, blood circulation, hardness, and thickness between the groups (P < 0.05). The cosmetic outcomes of the incisions in the experimental group were more satisfactory than in the control group (P < 0.05). Conclusion: When compared with traditional open thyroidectomy, the lateral cervical small incision approach has a lower incidence of complications, a better perioperative prognosis, and an improved cosmetic outcome.

The role of microRNA-4723-5p regulated by c-myc in triple-negative breast cancer.

The aim of this study was to investigate the expression of miRNA regulated by c-myc and its mechanism in three negative breast cancer (TNBC). We constructed MDA-MB-231 cell line with low expression of c-myc by lentivirus short hairpin RNA (shRNA), analyzed the miRNA expression profile of MDA-MB-231 cell line with different expression levels of c-myc by high-throughput sequencing technology, obtained differential miRNA by bioinformatics analysis and statistical analysis, and verified hsa-mir-4723-5p by Quantitative Real-time polymerase chain reaction(QRT-PCR). The target gene of hsa-mir-4723-5p was analyzed by miRDB and miRWalk database. The results showed that there were significant differences in 126 miRNAs in c-myc knockdown cell lines compared with the control group, of which 84 were significantly up-regulated and 42 were significantly down regulated. According to the results of miRNA sequencing, the miRNA closely related to the expression of c-myc was hsa-mir-4723-5p. QRT PCR showed that the expression of hsa-mir-4723-5p was down regulated in TNBC cell line MDA-MB-231 with low expression of c-myc, which was positively correlated with the expression. The target genes of hsa-mir-4723-5p were predicted according to mirdb and mirwalk database. A total of 112 target genes were obtained, and 107 target genes were related to hsa-mir-4723-5p. Through mirdb and mirwalk databases, it was found that the target gene TRAF4 of hsa-mir-4723-5p may be related to cancer pathway and affect tumor metastasis. In conclusion, the hsa-miR-4723-5p regulated by c-myc may be involved.

Mutations in exon region of BRCA1-related RING domain 1 gene and risk of breast cancer.

BACKGROUND: BRCA1-associated RING Domain 1 (BARD1) is an important gene related to breast cancer development. However, the role of BARD1 mutations in breast cancer remains inconclusive. This study is to investigate the relationship between exon mutations of BARD1 gene and the risk of early-onset breast cancer. METHODS: Totally, 60 cases of early-onset breast cancer patients (age 30-40 years) and 240 healthy women (age 30-40 years) were enrolled. Exon mutations of BARD1 were detected and analyzed by direct sequencing and SNaPshot. RESULTS: The risk of breast cancer was increased by 3.475 times in carriers with deletion mutation at rs28997575 site of BARD1 (aOR1  = 3.475, 95%CI = 1.302-9.276) (p = 0.013). The risk of breast cancer in carriers with GC genotype at rs2229571 site of BARD1 was reduced by 72.6% (aOR1  = 0.274, 95%CI = 0.134-0.562) (p = 0.001), and that in carriers with CC genotype was reduced by 82.8% (aOR1  = 0.172, 95%CI = 0.076-0.392) (p = 0.001). After stratification with family history, the difference of rs2229571 site mutation genotype was statistically significant (OR = -2.169, 95%CI = 0.016-0.828, p = 0.032). Additionally, the frequency distribution of breast cancer family history in the case group (15%) was significantly more than that in the control group (6.7%) (p = 0.037). CONCLUSION: The deletion mutation at rs28997575 locus of the BARD1 gene can significantly increase the risk of breast cancer. The mutation genotype of rs2229571 locus can significantly reduce the risk of breast cancer. Family history is associated with BARD1 gene polymorphism. A family history of breast cancer may be a risk factor for breast cancer.

UBE2T promotes proliferation, invasion and glycolysis of breast cancer cells by regualting the PI3K/AKT signaling pathway.

PURPOSE: Breast cancer (BCa) is one of the most common gynecological malignancies. Ubiquitin-coupled enzyme E2T (UBE2T) has been demonstrated to play crucial roles in various tumors. METHODS: UBE2T levels were detected using quantitative real time PCR and western blot. CCK-8 and colony formation assays were used to evaluate cell proliferation. A xenograft model was used to evaluate the effects of UBE2T on tumor growth in mice, and immunohistochemistry (IHC) assay was performed to detect the expression of UBE2T and Ki-67. Transwell assay was performed to determine cell migration and invasion. The ATP level, glucose consumption and lactate production were measured using the corresponding commercial kits. Western blot assay was used to detect the levels of epithelial-mesenchymal transformation (EMT), glycolytic and the PI3K/AKT pathway related proteins regulated by UBE2T. RESULTS: Upregulation of UBE2T expression in human BCa tissues was found in human clinical BCa tissues and The Cancer Genome Atlas (TCGA) dataset. The expression of UBE2T was confirmed to be up-regulated in BCa cells compared to normal breast epithelial cell line (MCF-10A). Overexpression of UBE2T promoted proliferation, migration, invasion and glycolysis in BCa cells, while UBE2T knockdown showed the opposite results. Moreover, UBE2T knockdown suppressed tumor growth in mice. Further mechanism analysis shows that UBE2T participated in the regulation of BCa progression through affecting the PI3K/AKT signaling pathway. CONCLUSION: UBE2T promoted proliferation, invasion and glycolysis through modulating PI3K/AKT signaling pathway in BCa, implying that UBE2T may provide a promising therapeutic target for the therapy of BCa.

Rapid identification of papillary thyroid carcinoma and papillary microcarcinoma based on serum Raman spectroscopy combined with machine learning models.

Thyroid carcinoma is with the highest diagnosis rate in the endocrine system, and its main histological subtype is papillary thyroid carcinoma (PTC) accounting for 80% of thyroid malignancies. In recent years, the incidence of thyroid cancer has increased exponentially, and its substantial increase was closely related to the overdiagnosis of papillary microcarcinoma (PMC). Therefore, early and accurate identification of PTC and PMC can prevent patients from over treatment. This study aimed to identify PTC and PMC using Raman spectroscopy. We collected serum Raman spectra from 16 patients with PTC and 31 patients with PMC. Firstly, the collected imbalance data were preprocessed using the synthetic minority over-sampling technique (SMOTE). Then, the equalized data were dimensionality reduced by principal component analysis (PCA). Finally, the processed data were fed into the single decision tree (DT) classifier, as well as the random forest (RF) built on the idea of Boosting ensemble and the Adaptive Boosting (Adaboost) model built on the idea of Bagging ensemble for classification. The classification accuracy of the three models in the testing set were 75.38%, 81.54%, and 84.61%, respectively. Compared with the DT classifier, the accuracy of the models introducing the idea of ensemble learning was enhanced by 6.16% and 9.23%, respectively. The best model was the Adaboost. This result demonstrates that serum Raman spectroscopy combined with an ensemble learning algorithm was feasible in rapidly identifying PTC and PMC. At the same time, the method has great potential for application in the field of clinical diagnosis.

Targeting a novel LncRNA SNHG15/miR-451/c-Myc signaling cascade is effective to hamper the pathogenesis of breast cancer (BC) in vitro and in vivo.

BACKGROUND: To our knowledge, LncRNA SNHG15 exerted its tumor-promoting effects to facilitate the development of breast cancer (BC), but there still needed more data to elucidate the potential underlying mechanisms. METHODS: We examined genes expression status by performing Real-Time qPCR and Western Blot analysis, and cellular functions, including cell proliferation, viability, apoptosis, mobility, were measured by using the CCK-8 assay, colony formation assay, trypan blue staining assay, flow cytometer (FCM), transwell assay and wound scratch assay, respectively. The predicted targeting sites in LncRNA SNHG15, miR-451 and c-Myc 3'UTR were validated by dual-luciferase reporter gene system assay. Finally, we established the tumor-bearing mice models, and the expression status, including its enrichment and cellular localization were examined by immunohistochemistry (IHC) assay. RESULTS: Our data indicated LncRNA SNHG15 upregulated c-Myc to facilitate BC progression by sponging miR-451 in a competing endogenous RNA (ceRNA)-dependent manner in vitro and in vivo. Specifically, LncRNA SNHG15 and c-Myc were upregulated, while miR-451 was downregulated in BC cells and clinical tissues, compared to their normal counterparts. In addition, miR-451 negatively correlated with LncRNA SNHG15 and c-Myc, and LncRNA SNHG15 was positively relevant to c-Myc in BC tissues. Next, we validated that LncRNA SNHG15 sponged miR-451 to upregulate c-Myc in BC cells. Further gain- and loss-of-function experiments evidenced that LncRNA SNHG15 promoted, while miR-451 inhibited malignant phenotypes, including cell proliferation, viability, migration, invasion and epithelial-mesenchymal transition (EMT) in BC cells. Interestingly, the inhibiting effects of LncRNA SNHG15 ablation on BC progression were abrogated by both silencing miR-451 and overexpressing c-Myc. CONCLUSIONS: We concluded that targeting the LncRNA SNHG15/miR-451/c-Myc signaling cascade was novel to hamper BC progression, which broadened our knowledge in this field, and provided potential biomarkers for BC diagnosis and treatment.