CD61+ and CAF+ were found to be good prognosis factors for invasive breast cancer patients

2017 ◽  
Vol 213 (10) ◽  
pp. 1296-1301 ◽  
Author(s):  
Dongyan Cai ◽  
Xiaohong Wu ◽  
Tingting Hong ◽  
Yong Mao ◽  
Xiaosong Ge ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Good Prognosis ◽  
Breast Cancer Patients ◽  
Prognosis Factors

scholarly journals IL-6 and IL-10 are associated with good prognosis in early stage invasive breast cancer patients

2017 ◽  
Vol 67 (4) ◽  
pp. 537-549 ◽  
Author(s):  
Narmeen Ahmad ◽  
Aula Ammar ◽  
Sarah J. Storr ◽  
Andrew R. Green ◽  
Emad Rakha ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Early Stage ◽  
Good Prognosis ◽  
Breast Cancer Patients

scholarly journals Metformin improves the outcomes in Chinese invasive breast cancer patients with type 2 diabetes mellitus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tianli Hui ◽  
Chao Shang ◽  
Liu Yang ◽  
Meiqi Wang ◽  
Ruoyang Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Breast Cancer Patients ◽  
Diabetes Group ◽  
Metformin Group

AbstractEarly reports indicate that metformin, a clinical drug administered to treat type 2 diabetes mellitus (T2DM), was found to be associated with a better prognosis of cancer. The objective of this study was retrospectively analyzed the effect of metformin on the outcomes of Chinese breast cancer patients with T2DM. A total of 3757 primary invasive breast cancer patients who underwent surgery from January 2010 to December 2013 were enrolled. According to the medication treatment, all the patients were divided as non-diabetes group, metformin group and insulin group. The follow-up data for disease-free survival (DFS) and overall survival (OS) were obtained from 3553 patients (median follow up of 85 months) and estimated with the Kaplan–Meier method followed by a log-rank test. Multivariate Cox proportional hazards regression model was applied. The results showed that there was a significant survival difference among non-diabetes group, metformin group and insulin group, 5-year DFS was 85.8%, 96.1%, 73.0%, and 5-year OS was 87.3%, 97.1%, 73.3% respectively (P < 0.05). Prognostic analysis showed metformin was significantly associated with better DFS and OS. Our results suggested that metformin may have a good effect on the survival of invasive breast cancer patients with T2DM.

scholarly journals Comparing the Prognostic Value of PTEN and Akt Expression with the Mitotic Activity Index in Adjuvant Chemotherapy-Treated Node-Negative Breast Cancer patients aged <55 years

2007 ◽  
Vol 29 (1) ◽  
pp. 25-35
Author(s):  
Emiel A. M. Janssen ◽  
Håvard Søiland ◽  
Ivar Skaland ◽  
Einar Gudlaugson ◽  
Kjell H. Kjellevold ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Cycle ◽  
Cancer Patients ◽  
Mitotic Activity ◽  
Invasive Breast Cancer ◽  
Prognostic Value ◽  
Activity Index ◽  
Breast Cancer Patients ◽  
Node Negative ◽  
Mitotic Activity Index

Background: The prognostic value of the PI3K/Akt/mTOR pathway and PTEN in invasive breast cancer (IBC) is controversial. Cell proliferation, especially the Mitotic Activity Index (MAI), is strongly prognostic in lymph node-negative (LNneg) invasive breast cancer. However, its prognostic value has not been compared with the value of Akt and PTEN expression. Material and Methods: Prognostic comparison of Her2Neu, p110alpha (PIK3CA), Akt, mTOR, PTEN, MAI and cell-cycle regulators in 125 LNneg patients aged <55 years with cyclophosphamide, methotrexate, and 5-fluorouracil (CMF)-based adjuvant systemic chemotherapy. Results: Twenty-one (17%) patients developed distant metastases = DMs (median follow-up: 134 months). p110alpha correlated (p = 0.01) with pAkt but only in PTEN-negatives; pAkt correlated (p = 0.02) with mTOR. PTEN-negativity correlated with high MAI, high grade and ER-negativity (p = 0.009). The MAI was the strongest prognosticator (Hazard Ratio = HR = 2.9, p = 0.01). Her2Neu/p110α/Akt/mTOR features have no additional prognostic value to the MAI. PTEN had additional value but only in MAI < 3 (39/125 = 31%; 8% DMs). 19/39 = 49% of the MAI < 3 patients have combined MAI < 3 / PTEN+ with 0% DMs, contrasting 15% DMs in MAI < 3 / PTEN− (p = 0.03). Conclusions: In T1−3N0M0 adjuvant CMF-treated breast cancer patients aged <55 years, MAI was the strongest survival predictor. The PI3K/Akt/mTOR pathway and cell-cycle regulator characteristics had no additional prognostic value, but PTEN has. Patients with combined MAI < 3 & PTEN-positivity had 100% survival. The small subgroup of MAI < 3 patients that died were PTEN-negative.

Gasdermin D as a potential prognosis and treatment response prediction biomarker for invasive breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12548-e12548
Author(s):  
Xianghou Xia ◽  
Wenjuan Yin ◽  
Jiefei Mao ◽  
Jiejie Hu ◽  
Dehong Zou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Response Prediction ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter ◽  
Treatment Response Prediction

e12548 Background: Pyroptosis is a type of inflammatory cell death mediated by gasdermins. Pyroptosis is critical for macrophage against pathogen infection. Recently growing evidences show that pyroptosis may affect development and progression of many cancers. We aim to explore the expression and related function of pyroptosis executioner Gasdermin D (GSDMD) in breast cancer. Methods: We investigated the expression level of GSDMD using TNM plotter and Breast Cancer landscape proteome with TCGA, GTEx and TARGET databases, and the prognostic value of GSDMD in invasive breast cancer using Kaplan-Meier plotter with TCGA, GEO and EGA databases. The treatment response prediction values of GSDMD in invasive breast were calculated using ROC-plotter with GEO database. Further validation of the prognostic value and chemotherapy response prediction value of GSDMD were carried out with immunohistochemical staining on tissues from 165 cases of breast cancer patients receiving neoadjuvant chemotherapy in our cancer center. Results: TNM plotter and breast cancer landscape proteome portal analysis shows that overall expression level of GSDMD in invasive breast cancer tissue is 1.67 folds higher than it is in breast normal tissues ( p=1.05*e-06). Expression of GSDMD in LuminalB subtype (p=0.019) and Her2 subtype(p=0.04) is significantly higher than it is in TNBC subtype. Calculations with Kaplan-Meier plotter show expression of GSDMD is negatively correlated with overall survival(OS), HR=0.61(0.4−0.95) p=0.027 and relapse free survival (RFS), HR =0.65(0.58−0.63), p=8.7*e-14 and distant metastasis free survival (DMFS) HR =0.75(0.61−0.91), p=0.0038 in breast cancer patients. ROC-plotter calculations show high GSDMD expression is a powerful endocrine therapy (AUC=0.731 p=6*e-09 ) and chemotherapy response (AUC=0.64 p=8*e-05 ) predictor based on 5-year RFS in overall breast cancer patients. Our IHC staining analysis shows consistent prognostic and chemotherapy prediction value of GSDMD expression in TNBC patients. Conclusions: In conclusion, our findings suggest that high expression of GSDMD is positively correlated with prognosis and therapeutic response in breast cancer. GSDMD is a promising prognostic marker and therapeutic response predictor in invasive breast cancer.

Micropallet Technology for Investigating Tumor Cellular Profiles and Analysis of Rare Cell Subsets

2008 ◽  
Author(s):  
Nicholas M. Gunn ◽  
Mark Bachman ◽  
Edward L. Nelson ◽  
G.-P. Li
Keyword(s):  
Breast Cancer ◽  
United States ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Breast Tumor ◽  
The United States ◽  
Therapeutic Strategies ◽  
Cellular Heterogeneity ◽  
Breast Cancer Patients ◽  
Critical Limits

Rationally designed, individualized therapeutic strategies have long been a desired objective for breast cancer patients and clinicians as an estimated 178,480 new cases of invasive breast cancer will be diagnosed among women in the United States this year and over 40,000 women are expected to die from the disease. [1] The increasing appreciation of breast tumor cellular heterogeneity raises fundamental questions as to the relative contributions of cellular subsets to the biologic behavior of an individual patient’s tumor. [2] As such, it has become increasingly clear that in many cases, an individualized strategy for the treatment of breast cancer would be of great benefit, and that the ability to isolate relevant cellular subsets from the main tumor population is one of the critical limits to accomplishing this goal.

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