Cancer Biotherapy and Radiopharmaceuticals最新文献

Background: Circular RNAs (circ-RNAs) have been demonstrated to influence initiation, drug resistance, and metastasis of tumors. However, the effects of circular-phosphoglycerate mutase 1 (circ-PGAM1) on matrine resistance in nonsmall cell lung cancer (NSCLC) remain unknown. Materials and Methods: The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to determine gene expression. The terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and cell colony formation assays were used to evaluate NSCLC apoptosis and cell proliferation after indicated treatments, respectively. Results: circ-PGAM1 was upregulated in human NSCLC cell lines (H1299 and A549) compared with the human normal lung epithelial (BEAS-2B) cells. circ-PGAM1 overexpression reversed the matrine treatment-induced inhibition on proliferation of NSCLC cells (A549 and H1299) and rescued the matrine treatment-stimulated apoptosis of these cells. miR-326 was demonstrated to interact with circ-PGAM1. circ-PGAM1 knockdown enhanced the antitumor effect of matrine on NSCLC cell proliferation and apoptosis, which was reversed by miR-326 inhibition. The authors also identified CXCR5 as a key downstream target of miR-326 in A549 cells. Conclusions: circ-PGAM1 enhances matrine resistance of NSCLC cells through the miR-326/CXCR5 axis. The authors' findings provide new insights into NSCLC-targeted therapy.

Malignant peritoneal mesothelioma (MPeM) is a rare primary malignant tumor originating from peritoneal mesothelial cells. Insufficient specificity of the symptoms and their frequent reappearance following surgery make it challenging to diagnose, creating a need for more efficient treatment options. Natural killer cells (NK cells) are part of the innate immune system and are classified as lymphoid cells. Under the regulation of activating and inhibiting receptors, NK cells secrete various cytokines to exert cytotoxic effects and participate in antiforeign body, antiviral, and antitumor activities. This review provides a comprehensive summary of the specific alterations observed in NK cells following MPeM treatment, including changes in cell number, subpopulation distribution, active receptors, and cytotoxicity. In addition, we summarize the impact of various therapeutic interventions, such as chemotherapy, immunotherapy, and targeted therapy, on NK cell function post-MPeM treatment.

Lung adenocarcinoma (ADC) is a common subtype of non-small cell lung cancer. MicroRNAs have been reported to be effective biomarkers for diagnosis and an important target for therapy. MiR-4429 is a newly identified miRNA, which can take part in tumor progression as a tumor inhibitor. Moreover, it is an exosomal miRNA that can be taken by lung ADC cell line A549. Nevertheless, its role in lung ADC has been poorly studied. This research discovered that miR-4429 was low expressed in lung ADC cells. MiR-4429 mimics could alleviate the capacities of cell proliferation and metastasis. The mimics are able to reverse epithelial-mesenchymal transition at the same time. Furthermore, it was verified that miR-4429 could bind to β-catenin and negatively regulate β-catenin expression. Interestingly, SKL2001 can reverse the role of miR-4429 on tumor. Consequently, miR-4429 can inactivate Wnt/β-catenin signaling pathway by targeting β-catenin and prevent oncogene expression in lung ADC cells.

Background: Numerous studies have recorded the function of long noncoding RNAs (lncRNAs) in cancer development, including lung adenocarcinoma (LUAD). Previous studies have reported the crucial role of lncRNA PTPRG antisense RNA 1 (PTPRG-AS1) in various cancers. However, the role of PTPRG-AS1 in LUAD remains unknown. Materials and Methods: Real-time quantitative polymerase chain reaction (RT-qPCR) was applied for detecting PTPRG-AS1 expression in LUAD cell lines. Functional assays and in vivo experiments explored cell proliferation, whereas flow cytometry analysis was used to detect cell cycle. In addition, fluorescent in situ hybridization (FISH) and subcellular fractionation assay measured the localization of PTPRG-AS1 in LUAD cells. RNA pulldown, luciferase reporter, and RNA immunoprecipitation (RIP) assays were used to investigate the interaction of PTPRG-AS1/miR-124-3p/cyclin D1 (CCND1) axis. Results: PTPRG-AS1 expression was notably high in LUAD cell lines. PTPRG-AS1 knockdown suppressed cell proliferation and cycle as well as the level of CCND1. Moreover, miR-124-3p was the mutual target of PTPRG-AS1 and CCND1. In addition, PTPRG-AS1 sponged miR-124-3p to upregulate CCND1 in LUAD cells. Moreover, miR-124-3p depletion reversed the suppression of PTPRG-AS1 silence on LUAD cell behaviors, but then CCND1 knockdown countervailed the promoting influence of downregulated miR-124-3p. Conclusions: PTPRG-AS1 propels cell proliferation and cell cycle of LUAD by targeting miR-124-3p/CCND1 axis.

Background: Breast cancer (BC) in women is the most common malignancy worldwide, but there is still a lack of validated tools to accurately assess patient prognosis and response to available chemotherapy treatment regimens. Method: We collected ultrasound images and transcriptome data of BC from our breast center and public database. Key ultrasound features were then identified by using the support vector machine (SVM) algorithm and correlated with prognostic genes. Long-term survival-related genes were identified through differential expression analysis, and a prognostic evaluation model was established by using Cox regression. In addition, VPS28 from the model was identified as a promising biomarker for BC. Results: Using univariate logistic regression and SVM algorithms, we identified 12 ultrasound features significantly associated with chemotherapy response. Subsequent correlation and differential expression analyses linked 401 genes to these features, from which five key signature genes were derived using Lasso and multivariate Cox regression models. This signature not only facilitates the stratification of patients into risk-specific treatment pathways but also predicts their chemotherapy response, thus supporting personalized medicine in clinical settings. Notably, VPS28, in the signature, emerged as a significant biomarker, strongly associated with poor prognosis, greater tumor invasiveness, and differing expression across demographic groups. Conclusion: In this study, we use ultrasound genomics to reveal a signature that can provide an effective tool for prognostic assessment and predicting chemotherapy response in patients with BC.

Objective: This study aimed to predict therapeutic efficacy among diffuse large B-cell lymphoma (DLBCL) after R-CHOP (-like) therapy using baseline ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) radiomics. Methods: A total of 239 patients with DLBCL were enrolled in this study, with 82 patients having refractory/relapsed disease. The radiomics signatures were developed using a stacking ensemble approach. The efficacy of the radiomics signatures, the National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI), conventional PET parameters model, and their combinations in assessing refractory/relapse risk were evaluated using receiver operating characteristic (ROC) curves, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and decision curve analysis. Results: The stacking model, along with the integrated model that combines stacking with the NCCN-IPI and SDmax (the distance between the two lesions farthest apart, normalized to the patient's body surface area), showed remarkable predictive capabilities with a high area under the curve (AUC), sensitivity, specificity, PPV, NPV, accuracy, and significant net benefit of the AUC (NB-AUC). Although no significant differences were observed between the combined and stacking models in terms of the AUC in either the training cohort (AUC: 0.992 vs. 0.985, p = 0.139) or the testing cohort (AUC: 0.768 vs. 0.781, p = 0.668), the integrated model exhibited higher values for sensitivity, PPV, NPV, accuracy, and NB-AUC than the stacking model. Conclusion: Baseline PET radiomics could predict therapeutic efficacy in DLBCL after R-CHOP (-like) therapy, with improved predictive performance when incorporating clinical features and SDmax.