Prognostic significance of Ki67 in Chinese women diagnosed with ER+/HER2- breast cancers by the 2015 St. Gallen consensus classification

Ginsenoside Rh3 induces pyroptosis and ferroptosis through the Stat3/p53/NRF2 axis in colorectal cancer cells

Ginsenoside Rh3 (GRh3) is a seminatural product obtained by chemical processing after isolation from Chinese herbal medicine that has strong antitumor activity against human tumors. However, its antitumor role remains to be elucidated. The aim of this study is to explore the mechanisms underlying the tumor suppressive activity of GRh3 from the perspective of pyroptosis and ferroptosis. GRh3 eliminates colorectal cancer (CRC) cells by activating gasdermin D (GSDMD)-dependent pyroptosis and suppressing solute carrier family 7 member 11 (SLC7A11), resulting in ferroptosis activation through the Stat3/p53/NRF2 axis. GRh3 suppresses nuclear factor erythroid 2-related factor 2 (NRF2) entry into the nucleus, leading to the decrease of heme oxygenase 1 (HO-1) expression, which in turn promotes NOD-like receptor thermal protein domain associated protein 3 (NLRP3) and caspase-1 expression. Finally, caspase-1 activates GSDMD-dependent pyroptosis. Furthermore, GRh3 prevents NRF2 from entering the nucleus, which suppresses SLC7A11, causing the depletion of glutathione (GSH) and accumulation of iron, lipid reactive oxygen species (ROS) and malondialdehyde (MDA), and eventually leading to ferroptosis in CRC cells. In addition, GRh3 effectively inhibits the proliferation of CRC cells in vitro and in nude mouse models. Collectively, GRh3 triggers pyroptotic cell death and ferroptotic cell death in CRC cells via the Stat3/p53/NRF2 axis with minimal harm to normal cells, showing great anticancer potential.

Agrimonia pilosa: A Phytochemical and Pharmacological Review

Agrimonia pilosa Ledeb., which belongs to Agrimonia and Rosaceae, is used in traditional Chinese medicine. It exhibits excellent medicinal properties and has been used to treat various diseases, such as tumors, trichomoniasis, vaginitis, diarrhea, and dysentery. Phytochemical studies have revealed that Agrimonia has over 100 secondary metabolites that can be categorized into six classes, i.e., flavonoids, isocoumarins, triterpenes, phloroglucinol derivatives, tannins, and organic acids. This review summarizes recently published literature on the chemical structures of 90 bioactive compounds that have been identified in A. pilosa and examines their pharmacological properties, including their antitumor, anti-inflammatory, antioxidant, antibacterial, and antidiabetic properties, as well as the potential development of parasitic resistance to these chemicals. This review highlights existing knowledge gap and serves as a basis for developing novel preparations of A. pilosa with medicinal value.

Doxorubicin-loaded nanoscale metal–organic framework for tumor-targeting combined chemotherapy and chemodynamic therapy

DMH NPs were prepared and could effectively induce MCF-7 cell death through the combination of chemotherapy and chemodynamic therapy.

Prognostic value of an immunohistochemical signature in patients with esophageal squamous cell carcinoma undergoing radical esophagectomy

Here, we aimed to identify an immunohistochemical (IHC)‐based classifier as a prognostic factor in patients with esophageal squamous cell carcinoma (ESCC). A cohort of 235 patients with ESCC undergoing radical esophagectomy (with complete clinical and pathological information) were enrolled in the study. Using the least absolute shrinkage and selection operator (LASSO) regression model, we extracted six IHC features associated with progression‐free survival (PFS) and then built a classifier in the discovery cohort (n = 141). The prognostic value of this classifier was further confirmed in the validation cohort (n = 94). Additionally, we developed a nomogram integrating the IHC‐based classifier to predict the PFS. We used the IHC‐based classifier to stratify patients into high‐ and low‐risk groups. In the discovery cohort, 5‐year PFS was 22.4% (95% CI: 0.14–0.36) for the high‐risk group and 43.3% (95% CI: 0.32–0.58) for the low‐risk group (P = 0.00064), and in the validation cohort, 5‐year PFS was 20.58% (95% CI: 0.12–0.36) for the high‐risk group and 36.43% (95% CI: 0.22–0.60) for the low‐risk group (P = 0.0082). Multivariable analysis demonstrated that the IHC‐based classifier was an independent prognostic factor for predicting PFS of patients with ESCC. We further developed a nomogram integrating the IHC‐based classifier and clinicopathological risk factors (gender, American Joint Committee on Cancer staging, and vascular invasion status) to predict the 3‐ and 5‐year PFS. The performance of the nomogram was evaluated and proved to be clinically useful. Our 6‐IHC marker‐based classifier is a reliable prognostic tool to facilitate the individual management of patients with ESCC after radical esophagectomy.

Tumor Digital Masking Allows Precise Patient Triaging: A Study Based on Ki-67 Scoring in Gastrointestinal Stromal Tumors

BACKGROUND

Technological advances constantly provide cutting-edge tools that enhance the progress of diagnostic capabilities. Gastrointestinal stromal tumors belong to a family of mesenchymal tumors where patient triaging is still based on traditional criteria such as mitotic count, tumor size, and tumor location. Limitations of the human eye and randomness in choice of area for mitotic figure counting compel us to seek more objective solutions such as digital image analysis. Presently, the labelling of proliferative activity is becoming a routine task amidst many cancers. The purpose of the present study was to compare the traditional method of prediction based on mitotic ratio with digital image analysis of cell cycle-dependent proteins.

METHODS

Fifty-seven eligible cases were enrolled. Furthermore, a digital analysis of previously performed whole tissue section immunohistochemical assays was executed. Digital labelling covered both hotspots and not-hotspots equally.

RESULTS

We noted a significant diversity of proliferative activities, and consequently, the results pointed to 6.5% of Ki-67, counted in hotspots, as the optimal cut-off for low-high-grade GIST. ROC analysis (AUC = 0.913; 95% CI: 0.828-0.997, p < 0.00001) and odds ratio (OR = 40.0, 95% CI: 6.7-237.3, p < 0.0001) pointed to Ki-67 16% as the cut-off for very high-grade (groups 5-6) cases. With help of a tumor digital map, we revealed possible errors resulting from a wrong choice of field for analysis. We confirmed that Ki-67 scores are in line with the level of intracellular metabolism that could be used as the additional biomarker.

CONCLUSIONS

Tumor digital masking is very promising solution for repeatable and objective labelling. Software adjustments of nuclear shape, outlines, size, etc. are helpful to omit other Ki-67-positive cells especially small lymphocytes. Our results pointed to Ki-67 as a good biomarker in GIST, but concurrently, we noted significant differences in used digital approaches which could lead to unequivocal results.