Non-apoptotic regulatory cell death scoring system to predict the clinical outcome and drug choices in breast cancer.

Background: Breast cancer (BC), the most common cancer among women globally, has been shown by numerous studies to significantly involve non-apoptotic regulatory cell death (RCD) in its pathogenesis and progression. Methods: We obtained the RNA sequences and clinical data of BC patients from The Cancer Genome Atlas (TCGA) database for the training set, while datasets GSE96058, GSE86166, and GSE20685 from The Gene Expression Omnibus (GEO) database were utilized as validation cohorts. Initially, we performed non-negative matrix factorization (NMF) clustering analysis on the BC samples from the TCGA database to discern non-apoptotic RCD-related molecular subtypes. To identify prognostically-relevant non-apoptotic RCD genes (NRGs) and construct a prognostic model, we implemented three machine learning algorithms: lasso regression, random forest, and XGBoost analysis. The expression of selected genes was verified using real-time quantitative polymerase chain reaction (RT-qPCR), single-cell RNA-sequencing (scRNA-seq) analysis, and The Human Protein Atlas (HPA) database. The risk signature was evaluated concerning clinical characteristics and drug sensitivity. Furthermore, we developed a nomogram to predict BC patient survival. Results: The NMF method successfully compartmentalized patients from the TCGA database into three distinct non-apoptotic RCD-related subtypes, with significant variations observed in immune characteristics and prognostic stratification across these subtypes. We identified 5 differentially expressed NRGs used in establishing the risk signature. Patients with different risk groups exhibited distinct clinicopathological features, drug sensitivity, and prognostic outcomes. A nomogram was subsequently developed, incorporating the NRGs-related risk signature, age, T stage, and N stage, to aid clinical decision-making. Conclusion: We identified a novel NRGs-related risk signature, which was expected to become a potential prognostic marker in BC.

Synthesis, optical properties, and application of novel chalcone skeleton as pH fluorescent probe: Based AIE + ESIPT strategy.

A series of "turn off" pH fluorescence probes with chalcone skeleton for basic system have been developed. The molecules emitted bright yellow fluorescence under acidic condition, resulting AIE coupled ESIPT characteristic and ICT process. What's more, the compounds exhibited excellent sensitivity and selectivity for detecting pH as a facile "On-Off" fluorescence probe, and the fluorescence of them were quenched with the ESIPT process interrupted under alkaline condition. Theoretical calculation for the related compounds also performed to verify the electron effect on photophysical properties and confirm the rational speculation on the mechanism.

Metastasis, characteristic, and treatment of breast cancer in young women and older women: A study from the Surveillance, Epidemiology, and End Results registration database.

BACKGROUND: Younger age is an independent risk factor for breast cancer (BC) prognosis, and BC in young women is often considered more aggressive. BC patients with different age and molecular subtypes have different metastasis patterns and survival. Herein, we aim to explore the metastasis patterns, characteristics and treatment methods of young patients with BC, and to compare them with older patients. METHODS: Data of young patients (aged ≤40 years old) and older patients (aged >40 years old) with BC were extracted from the Surveillance, Epidemiology, and End Results (SEER) registration database in 2010-2019 in this retrospective cohort study. Univariate and multivariate competing risk models and proportional hazard models were used to explore the association between different metastasis patterns and treatments and BC prognoses in young and older patients. Kaplan-Meier (KM) curves were drawn to reflect the survival probability of patients with BC who have different metastasis patterns. Also, we performed subgroup analysis of different metastasis patterns to explore the association between different treatments and overall survival (OS)/cancer specific survival (CSS) in patients with BC. The evaluation index was hazard ratios (HRs) with 95% confidence intervals (CIs). RESULTS: Totally, 5,984 patients died, and 92.56% of them died from BC. There were respectively 1,089 young patients and 9,105 older patients, and we found some differences of characteristics and metastasis patterns between them. After adjusting for covariates, young patients who had brain metastasis and multiple sites metastasis seemed to have high risk of both lower OS and CSS. Among older patients with BC, brain metastasis, liver metastasis, and multiple sites metastasis were all positively associated with both lower OS and CSS. In young and older patients, those who not receive radiotherapy or surgery, or received non-surgery combined with radiotherapy seemed to have high risk of both lower OS and CSS. Breast-conserving surgery (BCS) and surgery combined with radiotherapy were associated with higher OS and CSS in young patients, while only older patients received surgery combined with radiotherapy had higher OS and CSS. Results of subgroup analysis indicated that for patients with different metastasis patterns, developing a personalized treatment plan is necessary. CONCLUSIONS: Characteristics of BC between young patients and older patients were different. Clinicians should focus on different metastasis sites and choose appropriate treatments in patients with different ages, which may improve the prognoses.

Fate decisions of breast cancer stem cells in cancer progression.

Breast cancer has a marked recurrence and metastatic trait and is one of the most prevalent malignancies affecting women's health worldwide. Tumor initiation and progression begin after the cell goes from a quiescent to an activated state and requires different mechanisms to act in concert to regulate t a specific set of spectral genes for expression. Cancer stem cells (CSCs) have been proven to initiate and drive tumorigenesis due to their capability of self-renew and differentiate. In addition, CSCs are believed to be capable of causing resistance to anti-tumor drugs, recurrence and metastasis. Therefore, exploring the origin, regulatory mechanisms and ultimate fate decision of CSCs in breast cancer outcomes has far-reaching clinical implications for the development of breast cancer stem cell (BCSC)-targeted therapeutic strategies. In this review, we will highlight the contribution of BCSCs to breast cancer and explore the internal and external factors that regulate the fate of BCSCs.