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Kumar Eriksson posted an update 6 months ago
The objective of this study is to summarize the clinical and pathologic characteristics of malignant struma ovarii to facilitate the early diagnosis and treatment of this disease. All 144 patients were females from 27 countries. The mean age of the patients at diagnosis was 42.6 years. Overall, 35.71% of the patients underwent unilateral oophorectomy, 58.57% of the patients underwent bilateral oophorectomy, 5.72% of the patients were not ovariectomized, and 38.57% of the patients received radioactive iodine treatment with an average dose of 158.22 mCI each time. “Impure” types accounted for 70.19% of the cases, while pure types accounted for 29.81% of the cases. Among these cases, papillary thyroid carcinoma accounted for 50.00%, follicular thyroid carcinoma accounted for 26.47%, follicular variant of papillary thyroid carcinoma accounted for 18.63%, papillary and follicular mixed thyroid carcinoma accounted for 2.94%, anaplastic carcinoma accounted for 0.98%, and medullary carcinoma accounted for 0.98%. In total, 21 patients (51.22%) had elevated CA125. More than half of the patients (51.94%) had metastasis outside the ovary. The most common metastatic site was the pelvic cavity. The misdiagnosis rate was 17.27%. Mortality was related to metastasis and the cancer type. Gene mutations were found in the NRAS, KRAS, BRAF, and KIT genes and were similar to those in thyroid carcinoma, but some patients (37.5%) did not exhibit any gene mutations. Regardless of the treatment received, the survival rate is high. Treatment could initially include ovariectomy; however, in cases with metastasis and iodine uptake of the metastatic tumor, thyroidectomy, radioactive iodine therapy, and thyroid hormone inhibiting therapy are indicated.
Hepatocellular carcinoma (HCC) remains a major global health burden due to its high prevalence and mortality. Emerging evidence reveals that microRNA (miRNA) plays a vital role in cancer pathogenesis and is widely involved in the regulation of signaling pathways
their targeting of downstream genes. MiR-21-3p, a liver-enriched miRNA, and SMAD7, the negative regulator of the TGF-
signaling pathway, likely exert a vital influence on HCC progression.
Here, we explore the role of the miR-21-3p-SMAD7/YAP1 axis on HCC pathogenesis.
MiRNA microarray analysis was performed for miRNA screening. The dual-luciferase assay was adopted for target verification. Expression of miRNA and related genes were quantified
qRT-PCR, western blotting, and immunohistochemical staining. Flow cytometry and the transwell migration assay were used to detail cell apoptosis, invasion and metastases. Rat models were established to explore the role of the miR-21-3p-SMAD7/YAP1 axis in hepatocarcinogenesis. Bioinformatics analysis AD7 were significantly associated with the TGF-β signaling pathway in HCC.
MiR-21-3p promotes migration and invasion of HCC cells and upregulation of YAP1 expression
direct inhibition of SMAD7, underscoring a major epigenetic mechanism in the pathogenesis of HCC.
MiR-21-3p promotes migration and invasion of HCC cells and upregulation of YAP1 expression via direct inhibition of SMAD7, underscoring a major epigenetic mechanism in the pathogenesis of HCC.
Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies in urinary system, and radiomics has been adopted in tumor staging and prognostic evaluation in renal carcinomas. This study aimed to integrate image features of contrast-enhanced CT and underlying genomics features to predict the overall survival (OS) of ccRCC patients.
We extracted 107 radiomics features out of 205 patients with available CT images obtained from TCIA database and corresponding clinical and genetic information from TCGA database. LASSO-COX and SVM-RFE were employed independently as machine-learning algorithms to select prognosis-related imaging features (PRIF). Afterwards, we identified prognosis-related gene signature through WGCNA. selleck chemical The random forest (RF) algorithm was then applied to integrate PRIF and the genes into a combined imaging-genomics prognostic factors (IGPF) model. Furthermore, we constructed a nomogram incorporating IGPF and clinical predictors as the integrative prognostic model for ccRCC patiets.Glioblastoma (GBM) remains one of the most lethal primary brain tumors in both adult and pediatric patients. Targeting tumor metabolism has emerged as a promising-targeted therapeutic strategy for GBM and characteristically resistant GBM stem-like cells (GSCs). Neoplastic cells, especially those with high proliferative potential such as GSCs, have been shown to upregulate UCP2 as a cytoprotective mechanism in response to chronic increased reactive oxygen species (ROS) exposure. This upregulation plays a central role in the induction of the highly glycolytic phenotype associated with many tumors. In addition to shifting metabolism away from oxidative phosphorylation, UCP2 has also been implicated in increased mitochondrial Ca2+ sequestration, apoptotic evasion, dampened immune response, and chemotherapeutic resistance. A query of the CGGA RNA-seq and the TCGA GBMLGG database demonstrated that UCP2 expression increases with increased WHO tumor-grade and is associated with much poorer prognosis across a cohort of brain tumors. UCP2 expression could potentially serve as a biomarker to stratify patients for adjunctive anti-tumor metabolic therapies, such as glycolytic inhibition alongside current standard of care, particularly in adult and pediatric gliomas. Additionally, because UCP2 correlates with tumor grade, monitoring serum protein levels in the future may allow clinicians a relatively minimally invasive marker to correlate with disease progression. Further investigation of UCP2’s role in metabolic reprogramming is warranted to fully appreciate its clinical translatability and utility.
Colon adenocarcinoma (COAD) can be divided into left-sided and right-sided COAD (LCCs and RCCs, respectively). They have unique characteristics in various biological aspects, particularly immune invasion and prognosis. The purpose of our study was to develop a prognostic risk scoring model (PRSM) based on differentially expressed immune-related genes (IRGs) between LCCs and RCCs, therefore the prognostic key IRGs could be identified.
The gene sets and clinical information of COAD patients were derived from TCGA and GEO databases. The comparison of differentially expressed genes (DEGs) of LCCs and RCCs were conducted with appliance of “Limma” analysis. The establishment about co-expression modules of DEGs related with immune score was conducted by weighted gene co-expression network analysis (WGCNA). Furthermore, we screened the module genes and completed construction of gene pairs. The analysis of the prognosis and the establishment of PRSM were performed with univariate- and lasso-Cox regression. We employed the PRSM in the model group and verification group for the purpose of risk group assignment and PRSM accuracy verification.