Long-term survival after neoadjuvant therapy for triple-negative breast cancer under different treatment regimens: a systematic review and network meta-analysis.

BACKGROUND: Triple-negative breast cancer (TNBC) is a life-threatening subtype of breast cancer with limited treatment options. Therefore, this network meta-analysis (NMA) aimed to evaluate and compare the effect of various neoadjuvant chemotherapy (NCT) options on the long-term survival of patients with TNBC. METHODS: PubMed, Embase, Medline, Cochrane Library, Web of Science, and major international conference databases were systematically searched for randomized controlled trials (RCTs) on the efficacy of various NCT options in patients with TNBC. Searches were performed from January 2000 to June 2023. Study heterogeneity was assessed using the I2 statistic. Hazard ratios (HRs) and 95% confidence intervals (CIs) were used to evaluate disease-free survival (DFS) and overall survival (OS). Odds ratios (ORs) and 95% CIs were used to evaluate the pathologic complete response (pCR). The primary outcome was DFS. RESULTS: We conducted an NMA of 21 RCTs involving 8873 patients with TNBC. Our study defined the combination of anthracyclines and taxanes as the preferred treatment option. On this basis, the addition of any of the following new drugs is considered a new treatment option: bevacizumab (B), platinum (P), poly-ADP-ribose polymerase inhibitors (PARPi), and immune checkpoint inhibitor (ICI). Based on the surface under the cumulative ranking curve (SUCRA) values, the top three SUCRA area values of DFS were taxanes, anthracycline, and cyclophosphamide (TAC; 89.23%); CT (84.53%); and B (81.06%). The top three SUCRA area values of OS were CT (83.70%), TAC (62.02%), and B-containing regimens (60.06%). The top three SUCRA area values of pCR were B + P-containing regimens (82.7%), ICI + P-containing regimens (80.2%), and ICI-containing regimens (61.8%). CONCLUSIONS: This NMA showed that standard chemotherapy is a good choice with respect to long-term survival. Moreover, B associated with P-containing regimens is likely to be the optimal treatment option for neoadjuvant TNBC in terms of pCR.

The construction and analysis of a prognostic assessment model based on P53-related multi-genes in breast carcinoma.

BACKGROUND: Breast cancer ranks second in female tumor mortality, with an estimation of 2 million new cases diagnosed each year worldwide. METHODS: In our current study, we screened 13 genes highly distributed on the P53 phenotype which were significantly expressed and had a strong correlation with survival in the Cancer Genome Atlas breast cancer dataset. Least absolute shrinkage and selection operator Cox regression was conducted to construct the risk assessment model. Based on bioinformatics and statistical methods, we confirmed the credibility and validity of the model by training set and testing set. RESULTS: The result of comparing the other two previous hypoxia models was also satisfying. We also verified the model on one of the Gene Expression Omnibus datasets-GSE20685. Using clinical data from patients in the Cancer Genome Atlas, we acknowledged the risk score as an independent influence on breast cancer survival prognosis, and strong relevance was suggested between risk signature and age, lymphatic metastasis, tumor size and clinical stage by performing univariate and multivariate analysis. Immunology analysis demonstrated that the macrophages subset was positively associated with a risk score and other immune cell types had a negative effect with the risk score increases. The risk score was also emerging as a valuable prognostic factor for the prediction of chemotherapy drug curative effect because Gemcitabine, vinorelbine, paclitaxel and cisplatin known as a generic drug for breast cancer had more pleasing sensitivity in high-scored patients than low-scored patients. CONCLUSION: The P53-related risk assessment model is promising to be a potential predictor for the prognosis of patients with breast cancer and a powerful guide for the selection of therapeutic strategies.

Novel LncRNA AK023507 inhibits cell metastasis and proliferation in Papillary Thyroid Cancer through ß-catenin/Wnt Signaling Pathway.

INTRODUCTION: Papillary Thyroid Cancer (PTC) represents a commonly encountered type of thyroid malignancy whose occurrence and development is influenced by long non-coding RNA (LncRNA). A novel lncRNA (LncRNA AK023507), known to have tumor suppressive functions, was shown to prevent breast cancer cells from proliferating and metastasizing, but its mechanism in PTC is unclear. METHODS: Using PTC tissues and cell lines, the expression of LncRNA AK023507 was investigated by quantitative Real-time Polymerase Chain Reaction (qRT-PCR). The effects of knockdown or overexpression of LncRNA AK023507 on cell growth and movement were investigated through various cell experiments in vitro. The presence of important functional proteins was determined by Western blotting, with the recovery experiment used for verification. RESULTS: LncRNA AK023507 was found to have low expression in both the PTC cell lines and tissue samples. Knockdown of LncRNA AK023507 in PTC cells significantly promoted cell proliferation, migration, and invasion, while overexpression of LncRNA AK023507 resulted in the opposite effects. Furthermore, LncRNA AK023507 could regulate the expression of ß-catenin/Wnt signaling pathway as confirmed by recovery experiment. CONCLUSION: By acting through the ß-catenin/Wnt signaling pathway, LncRNA AK023507 prevented PTC cells from proliferating and metastasizing. These novel findings indicate that LncRNA AK023507 could be of prognostic and diagnostic value as a potential biomarker of PTC.

A Review of the Release Profiles and Efficacies of Chemotherapy Drug-Loaded Electrospun Membranes.

Electrospun fibrous membranes loaded with chemotherapy drugs have been broadly studied, many of which have had promising data demonstrating therapeutic effects on cancer cell inhibition, tumor size reduction, the life extension of tumor-bearing animals, and more. Nevertheless, their drug release profiles are difficult to predict since their degradation pattern varies with crystalline polymers. In addition, there is room for improving their release performances, optimizing the release patterns, and achieving better therapeutic outcomes. In this review, the key factors affecting electrospun membrane drug release profiles have been systematically reviewed. Case studies of the release profiles of typical chemotherapy drugs are carried out to determine the preferred polymer choices and techniques to achieve the expected prolonged or enhanced release profiles. The therapeutic effects of these electrospun, chemo-drug-loaded membranes are also discussed. This review aims to assist in the design of future drug-loaded electrospun materials to achieve preferred release profiles with enhanced therapeutic efficacies.

Mechanisms Affecting Physical Aging and Swelling by Blending an Amphiphilic Component.

Polymer blending is a promising method to overcome stability obstacles induced by physical aging and swelling of implant scaffolds prepared from amorphous polymers in biomedical application, since it will not bring potential toxicity compared with chemical modification. However, the mechanism of polymer blending still remains unclearly explained in existing studies that fail to provide theoretical references in material R&D processes for stability improvement of the scaffold during ethylene oxide (EtO) sterilization, long-term storage, and clinical application. In this study, amphiphilic poly(ethylene glycol)-co-poly(lactic acid) (PELA) was blended with amorphous poly(lactic-co-glycolic acid) (PLGA) because of its good miscibility so as to adjust the glass transition temperature (Tg) and hydrophilicity of electrospun PLGA membranes. By characterizing the morphological stability and mechanical performance, the chain movement and the glass transition behavior of the polymer during the physical aging and swelling process were studied. This study revealed the modification mechanism of polymer blending at the molecular chain level, which will contribute to stability improvement and performance adjustment of implant scaffolds in biomedical application.