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1.
BMC Cancer ; 24(1): 619, 2024 May 21.
Artículo en Inglés | MEDLINE | ID: mdl-38773471

RESUMEN

BACKGROUND: Breast cancer is one of the common malignancies in women. Evidence has demonstrated that FBXO45 plays a pivotal role in oncogenesis and progression. However, the role of FBXO45 in breast tumorigenesis remains elusive. Exploration of the regulatory mechanisms of FBXO45 in breast cancer development is pivotal for potential therapeutic interventions in patients with breast cancer. METHODS: Hence, we used numerous approaches to explore the functions of FBXO45 and its underlaying mechanisms in breast cancer pathogenesis, including CCK-8 assay, EdU assay, colony formation analysis, apoptosis assay, RT-PCR, Western blotting, immunoprecipitation, ubiquitination assay, and cycloheximide chase assay. RESULTS: We found that downregulation of FBXO45 inhibited cell proliferation, while upregulation of FBXO45 elevated cell proliferation in breast cancer. Silencing of FBXO45 induced cell apoptosis, whereas overexpression of FBXO45 inhibited cell apoptosis in breast cancer. Moreover, FBXO45 interacted with BIM and regulated its ubiquitination and degradation. Furthermore, knockdown of FBXO45 inhibited cell proliferation via regulation of BIM pathway. Notably, overexpression of FBXO45 facilitated tumor growth in mice. Strikingly, FBXO45 expression was associated with poor survival of breast cancer patients. CONCLUSION: Our study could provide the rational for targeting FBXO45 to obtain benefit for breast cancer patients. Altogether, modulating FBXO45/Bim axis could be a promising strategy for breast cancer therapy.


Asunto(s)
Apoptosis , Proteína 11 Similar a Bcl2 , Neoplasias de la Mama , Proliferación Celular , Progresión de la Enfermedad , Proteínas F-Box , Ubiquitinación , Humanos , Neoplasias de la Mama/patología , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/genética , Femenino , Animales , Proteínas F-Box/metabolismo , Proteínas F-Box/genética , Ratones , Proteína 11 Similar a Bcl2/metabolismo , Proteína 11 Similar a Bcl2/genética , Línea Celular Tumoral , Proteolisis , Regulación Neoplásica de la Expresión Génica , Ratones Desnudos
2.
Transl Cancer Res ; 12(4): 949-964, 2023 Apr 28.
Artículo en Inglés | MEDLINE | ID: mdl-37180647

RESUMEN

Background: Breast cancer, a type of tumor associated with high heterogeneity, is top among the common malignancies threatening women's health worldwide. Emerging evidence suggests that competing endogenous RNA (ceRNA) plays a role in the molecular biological mechanisms related to the occurrence and development of cancer. However, the effect of the ceRNA network on breast cancer, especially the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network, has not been fully studied. Methods: To explore potential prognostic markers of breast cancer under ceRNA network, we first extracted the breast cancer expression profiles of lncRNAs, miRNAs and mRNAs and their corresponding clinical data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) database. Next, we selected breast cancer-related candidate genes by intersection of the differential expression analysis and the weighted gene coexpression network analysis (WGCNA). Then, we studied the interactions among lncRNAs, miRNAs, and mRNAs by means of multiMiR and starBase and then constructed a ceRNA network of 9 lncRNAs, 26 miRNAs, and 110 mRNAs. We established a prognostic risk formula by means of multivariable Cox regression analysis. Results: Based on public databases and evaluated via modeling, we identified the HOX antisense intergenic RNA (HOTAIR)-miR-130a-3p-high mobility group-box 3 (HMGB3) axis as a potential prognostic marker in breast cancer through a prognostic risk model we established using multivariable Cox analysis. Conclusions: For the first time, the potential interactions among HOTAIR, miR-130a-3p, and HMGB3 in the tumorigenesis were clarified, and these may provide novel prognostic value for breast cancer treatment.

3.
Front Endocrinol (Lausanne) ; 13: 888072, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36313748

RESUMEN

Background: Papillary thyroid microcarcinoma (PTMC) is defined as a papillary carcinoma measuring ≤ 10 mm. The current management of PTMC has become more conservative; however, there are high-risk tumor features that can be revealed only postoperatively. For thyroid cancer, BRAF mutations and somatic copy number variation (CNV) are the most common genetic events. Molecular testing may contribute to clinical decision-making by molecular risk stratification, for example predicting lymph node (LN) metastasis. Here, we build a risk stratification model based on molecular profiling of thyroid fine needle aspiration (FNA) washout DNA (wDNA) for the differential diagnosis of thyroid nodules. Methods: Fifty-eight patients were recruited, FNA wDNA samples were analyzed using CNV profiling through low-coverage whole genome sequencing (LC-WGS) and BRAF mutation was analyzed using quantitative PCR. FNA pathology was reported as a Bethesda System for Reporting Thyroid Cytopathology (BSRTC) score. Ultrasound examination produced a Thyroid Imaging Reporting and Data System (TIRADS) score. Results: In total, 37 (63.8%) patients with a TIRADS score of 4A, 13 (22.4%) patients with a TIRADS score of 4B, and 8 (13.8%) patients with a TIRADS score of 4C were recruited after ultrasound examination. All patients underwent FNA with wDNA profiling. CNVs were identified in 17 (29.3%) patients. CNVs were frequent in patients with a BSRTC score of V or VI, including eight (47.1%) patients with a score of VI and five (29.4%) with a score of V, but not in patients with a score of III, II, or I (0%). BRAF mutation was not significantly correlated with BSRTC score. LN metastasis was found more frequently in CNV-positive (CNV+) than in CNV-negative (CNV-) patients (85.7% vs. 34.6%, odds ratio = 11.33, p = 0.002). In total, three molecular subtypes of thyroid nodules were identified in this study: 1) CNV+, 2) CNV- and BRAF positive (BRAF+), and 3) CNV- and BRAF negative (BRAF-). For the CNV+ subtype, 10 (83.3%) lesions with LN metastasis were found, including four (100%) small lesions (i.e. ≤ 5 mm). For the CNV- and BRAF+ nodules, LN metastases were detected in only seven (60.0%) larger tumors (i.e. > 5 mm). For CNV- and BRAF- tumors, LN metastasis was also frequently found in larger tumors only. Conclusions: It is feasible to identify high-risk LN metastasis thyroid cancer from FNA washout samples preoperatively using wDNA CNV profiling using LC-WGS.


Asunto(s)
Neoplasias de la Tiroides , Nódulo Tiroideo , Humanos , Nódulo Tiroideo/diagnóstico , Nódulo Tiroideo/genética , Nódulo Tiroideo/patología , Proteínas Proto-Oncogénicas B-raf/genética , Variaciones en el Número de Copia de ADN , Análisis Mutacional de ADN , Neoplasias de la Tiroides/diagnóstico , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/patología , Metástasis Linfática , Secuenciación Completa del Genoma , ADN
4.
Front Oncol ; 11: 756246, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-35141140

RESUMEN

OBJECTIVE: Since there are few studies exploring genes associated with lymphatic metastasis of thyroid carcinoma (THCA), this study was conducted to explore genes associated with lymphatic metastasis of THCA and to investigate the relationship with immune infiltration. METHODS: Differentially expressed genes associated with THCA lymphatic metastasis were analyzed based on The Cancer Genome Atlas Program (TCGA) database; a protein-protein interaction(PPI)network was constructed to screen for pivotal genes. Based on the identified hub genes, their expression in THCA with and without lymphatic metastasis were determined. Functional enrichment analysis was performed. The correlation between the identified genes and immune cell infiltration was explored. LASSO logistic regression analysis was performed to determine the risk score of the most relevant gene constructs and multifactor COX regression analysis based on genes in the risk score formula. RESULTS: A total of 115 genes were differentially expressed in THCA with and without lymphatic metastasis, including 28 upregulated genes and 87 downregulated genes. The PPI network identified seven hub genes (EVA1A, TIMP1, SERPINA1, FAM20A, FN1, TNC, MXRA8); the expression of all seven genes was upregulated in the group with lymphatic metastasis; Immuno-infiltration analysis showed that all seven genes were significantly positively correlated with macrophage M1 and NK cells and negatively correlated with T-cell CD4+ and myeloid dendritic cells. LASSO logistic regression analysis identified the five most relevant genes (EVA1A, SERPINA1, FN1, TNC, MXRA8), and multi-factor COX regression analysis showed EVA1A, SERPINA1 and FN1 as independent prognostic factors. CONCLUSION: Seven genes were associated with lymphatic metastasis of THCA and with tumor immune cell infiltration.

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