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1.
Front Oncol ; 14: 1419710, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-39114303

RESUMO

Large Cell Neuroendocrine Carcinoma (LCNEC) of the cervix is an extremely rare but highly aggressive type of cervical cancer and it requires multimodal therapy to improve their quality of life. At present, there are no established, standardized treatment protocols for managing large cell neuroendocrine carcinoma of the cervix. In this report, we present a case of a patient with cervical LCNEC, Who was a 39-year-old woman who presented with irregular vaginal bleeding accompanied by lower abdominal distension for over a month. Examination revealed a cauliflower-like cervical mass approximately 4cm in diameter, with the normal cervical architecture distorted and partially fused to the vaginal wall. Following further investigations, the stage assigned was IVB, and who was started on neoadjuvant chemotherapy with the TC (paclitaxel + carboplatin) regimen but during neoadjuvant chemotherapy, The patient developed a vaginal urinary leakage. Then, The patient underwent a comprehensive treatment regimen that included pelvic exenteration, urinary system reconstruction, pelvic floor reconstruction, and chemotherapy. Given the patient's positive immunohistochemistry for EGFR, the treatment was combined with the anti-angiogenic drug, bevacizumab. The patient achieved complete remission following the comprehensive treatment. Through this case to explore individualized treatment for cervical LCNEC.

2.
Front Oncol ; 14: 1298109, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38515573

RESUMO

Multiple primary malignant neoplasms are a rare gynecologic malignancy; particularly, cases originating from the heterologous organs, such as the ovary and cervix. Here, we report a case of two primary malignant neoplasms in a patient who had undergone laparoscopic radical hysterectomy + bilateral salpingo-oophorectomy + pelvic lymph node dissection + para-aortic lymphadenectomy + appendectomy + omentectomy + metastasectomy under general anesthesia. The patient experienced complete remission after six courses of postoperative chemotherapy with a standard Taxol and Carboplatin regimen. Genetic testing was performed to detect BRCA2 mutations, and poly (ADP-ribose) polymerase (PARP) inhibitors were used for maintenance therapy.

3.
Gene ; 710: 122-130, 2019 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-31075415

RESUMO

PURPOSE: Coronary artery disease (CAD) is one of the most common causes of morbidity and mortality globally. This work aimed to investigate the specific modules and feature genes associated with CAD. METHODS: Three microarray datasets were downloaded from the Gene Expression Omnibus database, which included CAD and healthy samples. WGCNA was applied to identify highly preserved modules across the three datasets. MetaDE method was used to select differentially expressed genes (DEGs) with significant consistency. Protein-protein interaction (PPI) network was constructed using the overlapping genes amongst the DEGs with significant consistency and in the preserved modules. Moreover, a combined machine learning of support vector machine and recursive feature elimination was used to further investigate the feature genes and pathways. RESULTS: Nine highly preserved modules were detected in the WGCNA network, and 961 DEGs with significant consistency across the three datasets were selected using the metaDE method. A PPI network was constructed with the 158 overlapping genes. Ten genes were found to be involved in these KEGG pathways directly, including genes CD22, CD79B, CD81, CR1, IKBKE, MAP3K3, MAPK14, MMP9, NCF4, and SPP1. CONCLUSIONS: The present work might provide novel insight into the underlying molecular mechanism of CAD.


Assuntos
Biologia Computacional/métodos , Doença da Artéria Coronariana/genética , Perfilação da Expressão Gênica/métodos , Redes Reguladoras de Genes , Regulação da Expressão Gênica , Predisposição Genética para Doença , Humanos , Análise de Sequência com Séries de Oligonucleotídeos , Mapas de Interação de Proteínas , Máquina de Vetores de Suporte
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