Hub metastatic gene signature and risk score of breast cancer patients with small tumor sizes using WGCNA.

BACKGROUND: Breast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices. METHODS: We integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression. RESULTS: ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72-0.76. The enriched pathways were immune regulation and cell-cell signaling. EGFR serves as the hub gene for the protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3. CONCLUSION: Prognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms.

Advancing breast cancer subtyping: optimizing immunohistochemical staining classification with insights from real-world Taiwanese data.

Gene expression signatures provide valuable information to guide postoperative treatment in breast cancer (BC) patients. However, genetic tests are prohibitively expensive for the majority of BC patients. Immunohistochemical staining (IHC) subtype classification system has been widely used for treatment guideline and is affordable to most BC patients. We aimed to revise immunohistochemical staining (IHC) subtyping to better match gene expression-based Prediction Analysis of Microarray 50 (PAM50) subtyping. Real world data of 372 BC patients were recruited in the Tri-Service General Hospital between Jan 2019 and Dec 2021. Clinical pathological information, blood, twelve pathological tissue slide samples, and fresh surgical tumor specimens were collected to examine IHC and PAM50. Current IHC subtyping (cIHC) tends to misclassify PAM50-based luminal A (lum A) to luminal B (lum B) by 35.81%, PAM50-lum B to PAM50-lum A by 9.09%, PAM50-Her2-enriched to lum B by 61.11%, PAM50-based Her2-enriched to lum B by 61.11%, and PAM50-based basal-like to lum B by 33.33%. We used random forest to identify estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her2), and Ki-67 status as the best indicators for revised IHC subtyping (rIHC4) and revised the classification rules by stratified analysis and prediction efficacy. rIHC4 increased the concordance rate for PAM50 subtypes from 68.3% to 74.7%. Both sensitivity and precision increased in most rIHC4 subtypes. Sensitivity increased from 33.3% to 87.4% in the Her2-enriched subtype; precision increased more evidently in the basal-like and lum B subtypes, from 71.4% to 83.3% and 57% to 65.1%, respectively. Our rIHC4 subtyping improved consistency with the PAM50 subtype, which could improve clinical management of BC patients without increasing medical expense.

The Risk of Breast Cancer between Western and Mediterranean Dietary Patterns.

Breast cancer is a significant public health problem globally and prevention strategies have become of great interest as its incidence rises. Exploring the connection between dietary patterns and the reduction of breast cancer risk is considered a promising approach. High levels of fiber, phytochemicals, a good antioxidant profile, and a composition of advantageous fatty acids are characteristics of healthy dietary programs such as the Mediterranean diet. This review summarized and discussed the active compounds that are considered important in preventing breast cancer, including dietary components from recent related reports. These include polyunsaturated fatty acids, fiber, phytochemicals, and alcohol. Although the exact mechanism for preventing breast cancer using these dietary factors is not well understood, the combination of all the elements in a healthy diet plays a role in reducing breast cancer risk. Considering the elevated probability of breast cancer relapse and mortality, it is crucial to investigate the correlation between a nutritious dietary pattern and breast cancer, while identifying bioactive components that have the potential to mitigate the risk of breast cancer incidence.

The impact of frailty on breast cancer outcomes: evidence from analysis of the Nationwide Inpatient Sample, 2005-2018.

The aims of the present study were to examine whether and how frailty impacts the outcomes of breast cancer. Data of women with breast cancer hospitalized during 2005 and 2018 were extracted from the US Nationwide Inpatient Sample (NIS) database. Frailty was identified using a novel algorithm, Hospital Frailty Risk Score (HFRS). Propensity-score (PS) matching was utilized to balance the baseline characteristics between frail and non-frail groups. In-hospital mortality, unfavorable discharge, prolonged length of stay (LOS), and total hospital cost were compared using univariate and multivariable logistic regression analyses. A total of 19,522 patients with metastatic (frailty n = 9,906; no frailty n = 9,716) and 135,200 with non-metastatic breast cancer (frailty n = 30,235; no frailty n = 104,965) were included. After adjustment, frailty was significantly and independently associated with higher risk for in-hospital mortality, unfavorable discharge, prolonged LOS, and greater hospital cost in both metastatic and non-metastatic diseases, in which the impacts of frailty was greater in women with non-metastatic disease. In stratified analysis, frailty had the greatest impact on in-hospital mortality among women had had non-metastatic disease and aged <50 years (aOR = 3.88; 95% CI: 1.95-7.73). In conclusion, frailty is associated with worse outcomes in women with breast cancer, and the effects are greater in non-metastatic disease and younger patients.