Predictive value of topoisomerase II alpha protein for clinicopathological characteristics and prognosis in early breast cancer

Hsa_circ_0072088 promotes non-small cell lung cancer progression through modulating miR-1270/TOP2A axis

According to the data released by the International Agency for Research on Cancer (IARC) in 2020, lung cancer ranks second among newly diagnosed malignant tumors globally. As a special class of non-coding RNA, circRNA has become a new hotspot in the field of biomarker research. With the continuous deepening of molecular-level investigations, the underlying mechanisms of circRNA are being gradually unveiled. The more widely studied mechanism is the competitive endogenous RNA mechanism of circRNA. Studies related to circRNA expression were searched in GEO database and statistically analyzed using the "limma" package and weighted gene co-expression network analysis. The expression of circRNA, microRNA and mRNA in cells and tissues were examined via qRT-PCR. MTS assay was used to measure cell proliferation, Transwell assay was used to measure cell migration, and apoptosis assay was carried out to detect cell apoptosis. Additionally, a dual-luciferase reporter assay was further executed to explore the targeted binding relationships between circRNA-microRNA and microRNA-mRNA. It was discovered that hsa_circRNA_103809 was differentially highly expressed in non-small cell lung cancer cells, whereas miR-1270 was differentially lowly expressed. The knockdown of circ_0072088 inhibited the cell proliferation and migration, while promoting cell apoptosis. The same biological function was found with the overexpression of miR-1270. The rescue experiment further validated that circ_0072088 could regulate the biological function of cells by influencing miR-1270. Finally, the targeted binding relationship was verified by dual luciferase reporting experiment. In conclusion, circ_0072088 is differentially highly expressed in non-small cell lung cancer and can affect the progression of non-small cell lung cancer through the circ_0072088/miR-1270/TOP2A axis.

Design, synthesis, and in vitro and in vivo biological evaluation of triazolopyrimidine hybrids as multitarget directed anticancer agents

In response to the urgent need for new anti-proliferative agents, four novel series of triazolopyrimidine compounds (7a-e, 9a-d, 11a-f, and 13a-e) were synthesized and evaluated for in vitro anticancer efficacy against HCT116, HeLa, and MCF-7 cell lines. Compound 13c emerged as the most potent, with IC50 values of 6.10, 10.33, and 2.42 μM respectively, while 11e and 7c also showed strong activity. In multi-target suppression tests, 13c exhibited the highest inhibition against EGFR, TOP-II, HER-2, and ARO (IC50: 0.087, 31.56, 0.078, and 0.156 μM, respectively). Flow cytometry revealed 13c's ability to suppress the S-phase cell population in MCF-7 cells. In vivo studies of 13c demonstrated significant tumor growth inhibition, comparable to the positive control. Molecular docking studies supported the experimental findings, confirming the binding of the novel motifs to the target enzymes' active sites. This comprehensive evaluation highlights the potential of these triazolopyrimidine compounds, particularly 13c, as promising anticancer agents, warranting further investigation.

Refining breast cancer biomarker discovery and drug targeting through an advanced data-driven approach

Breast cancer remains a major public health challenge worldwide. The identification of accurate biomarkers is critical for the early detection and effective treatment of breast cancer. This study utilizes an integrative machine learning approach to analyze breast cancer gene expression data for superior biomarker and drug target discovery. Gene expression datasets, obtained from the GEO database, were merged post-preprocessing. From the merged dataset, differential expression analysis between breast cancer and normal samples revealed 164 differentially expressed genes. Meanwhile, a separate gene expression dataset revealed 350 differentially expressed genes. Additionally, the BGWO_SA_Ens algorithm, integrating binary grey wolf optimization and simulated annealing with an ensemble classifier, was employed on gene expression datasets to identify predictive genes including TOP2A, AKR1C3, EZH2, MMP1, EDNRB, S100B, and SPP1. From over 10,000 genes, BGWO_SA_Ens identified 1404 in the merged dataset (F1 score: 0.981, PR-AUC: 0.998, ROC-AUC: 0.995) and 1710 in the GSE45827 dataset (F1 score: 0.965, PR-AUC: 0.986, ROC-AUC: 0.972). The intersection of DEGs and BGWO_SA_Ens selected genes revealed 35 superior genes that were consistently significant across methods. Enrichment analyses uncovered the involvement of these superior genes in key pathways such as AMPK, Adipocytokine, and PPAR signaling. Protein-protein interaction network analysis highlighted subnetworks and central nodes. Finally, a drug-gene interaction investigation revealed connections between superior genes and anticancer drugs. Collectively, the machine learning workflow identified a robust gene signature for breast cancer, illuminated their biological roles, interactions and therapeutic associations, and underscored the potential of computational approaches in biomarker discovery and precision oncology.

Neoadjuvant Chemotherapy of Taxanes With or Without Anthracyclines in Different Molecular Subtypes of Breast Cancer: A Propensity Score Matching Study

PURPOSE

To compare the efficacy of taxane (T) based neoadjuvant chemotherapy (NAC) with T and anthracycline (A) based NAC in different molecular types of breast cancer (BC).

METHODS

We retrospectively analyzed the date of NAC for BC from 20 hospitals in China from January 2010 to December 2020, 7870 cases were enrolled. The propensity score matching was used to equalize the baseline characteristics. Pathological complete response (pCR) rate, clinical response rate and breast-conserving rate were analyzed.

RESULTS

The efficacy of 2 regimens were similar in luminal A subtype. The breast-conserving rate was higher in T-based NAC in luminal B subtype (17.9% vs. 10.2%, P = .043).The pCR (T0/isN0M0) and tpCR (T0N0M0) rates in T-based NAC were higher than those in TA-based NAC for triple-negative subtype (pCR: 34.5% vs. 25.8%, P = .041, tpCR: 26.9% vs. 17.1%, P = .008). For HER2+(HR-) subtype, the pCR, and tpCR rates were higher in T-based NAC in insufficient anti-HER2 therapy (P < .05), and those were higher in TA-based NAC in dual-target anti-HER2 therapy (pCR: 69.2% vs. 53.8%, P = .254, tpCR: 61.5% vs. 42.3%, P = .165). For HER2+(HR+) breast cancer, both pCR and tpCR rates were higher in TA group, regardless of the adequacy of anti-HER2 treatment.

CONCLUSIONS

T-based NAC could replace TA-based NAC for luminal A, luminal B, and triple-negative early-stage BC, but anthracyclines cannot be abandoned in HER2+ breast cancer. The development of anthracyclines with lower adverse reactions is one of the directions for the treatment of HER2+ breast cancer.

A comprehensive atlas of epigenetic regulators reveals tissue-specific epigenetic regulation patterns

Epigenetic machinery contributes to gene regulation in eukaryotic species. However, the machinery including more than 600 epigenetic regulator (ER) genes responsible for reading, writing, and erasing histone modifications and DNA modifications remains largely uncharacterized across species. We compile a comprehensive list of ERs based on an evolutionary analysis across 23 species, which is the most comprehensive ER list in various species until recently. We further perform comparative transcriptomic analyses across different tissues in humans, mice, as well as other amniote species. We observe a consistent tissue-of-origin expression specificity pattern of duplicated ER genes across species and suggest links between expression specificity and ER gene evolution as well as ER function. Additional analyses further suggest that ER duplication can generate tissue-specific ER genes with the same epigenetic substrates, which may be closely related to their regulatory specificity in tissue development. Our work can serve as a foundation to better comprehend the tissue-specific expression patterns of ER genes from an evolutionary perspective and also the functional implications of ERs in tissue-specific epigenetic regulation.

Topoisomerase IIα immunoexpression in feline mammary carcinomas: A correlation with Ki67 immunoexpression and the mitotic count

The aim of the study was to compare the immunohistochemical expression of topoisomerase IIα protein (Topo IIα) with Ki67 expression and mitotic count in feline mammary carcinomas (FMCs). Topo IIα is considered as a proliferation indicator as well as a molecular target of anthracycline chemotherapy. The studied material included 70 FMCs from female cats treated with mastectomy. Primary mouse monoclonal antibodies directed against Topo IIα and Ki67 were used in immunohistochemical reactions. The number of mitotic figures was counted at 400× magnification in a field of 2.37 mm2. Immunohistochemical reaction for Topo IIα occurred in cell nuclei. The Topo IIα index ranged from 6.12% to 54.60% and was positively correlated with the values of the Ki67 index (r = 0.7193) and the mitotic count (r = 0. 2858). This indicates the potential possibility of use of the immunohistochemical expression of Topo IIα to assess the rate of proliferation in FMCs. The wide range of expression of Topo IIα in individual tumorus found in the conducted studies allows us to hypothesize that its assessment could be used as a predictive marker in chemotherapy of FMCs with the use of anthracyclines. However, this requires confirmation in clinical trials.