scholarly journals Combined genomic and phenotype screening reveals secretory factor SPINK1 as an invasion and survival factor associated with patient prognosis in breast cancer

2011 ◽  
Vol 3 (8) ◽  
pp. 451-464 ◽  
Author(s):  
Wendy WeiJia Soon ◽  
Lance David Miller ◽  
Michael A. Black ◽  
Cyril Dalmasso ◽  
Xiu Bin Chan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Factor ◽  
Phenotype Screening ◽  
Patient Prognosis

scholarly journals Cytotoxic T-lymphocyte infiltration and chemokine predict long-term patient survival independently of tumor mutational burden in triple-negative breast cancer

2021 ◽  
Vol 13 ◽  
pp. 175883592110066
Author(s):  
Eriko Katsuta ◽  
Li Yan ◽  
Mateusz Opyrchal ◽  
Pawel Kalinski ◽  
Kazuaki Takabe
Keyword(s):  
Breast Cancer ◽  
Triple Negative ◽  
Patient Survival ◽  
Cytotoxic T Lymphocyte ◽  
Breast Cancer Patients ◽  
Mutational Burden ◽  
Cancer Immunity ◽  
Anti Cancer ◽  
Tumor Mutational Burden ◽  
Patient Prognosis

Background: Cytotoxic T-lymphocyte (CTL) infiltration into tumor is a positive prognostic factor in breast cancer. High tumor mutational burden (TMB) is also considered as a predictor of tumor immunogenicity and response to immunotherapy. However, it is unclear whether the infiltration of functional CTL simply reflects the TMB or represents an independent prognostic value. Methods: Utilizing The Cancer Genome Atlas (TCGA) breast cancer cohort, we established the Functional Hotness Score (FHS). The associations of FHS and breast cancer patient prognosis as well as distinct immunity markers were analyzed in a total of 3011 breast cancer patients using TCGA, METABRIC and metastatic breast cancer (MBC) cohort GSE110590. Results: We established FHS, based on CD8A, GZMB and CXCL10 gene expression levels of bulk tumors, which delivered the best prognostic value among some gene combinations. Breast cancer patients with the high-FHS tumors showed significantly better survival. FHS was lower in the MBCs. Triple-negative breast cancer (TNBC) showed the highest FHS among subtypes. FHS predicted patient survival in hormone receptor (HR)-negative, especially in TNBC, but not in HR-positive breast cancer. FHS predicted patient prognosis independently in TNBC. The high-FHS TNBCs showed not only higher CD8+ T cell infiltration, but also enhanced broader type-1 anti-cancer immunity. The patients with the high-FHS tumors showed better prognosis not only in high-TMB tumors but also in low-TMB TNBCs. The combination of high-TMB with high-FHS identified a unique subset of patients who do not recur over time in TNBC. Conclusion: TNBCs with high FHS based on the expression levels of CD8A, GZMB and CXCL10 showed improved prognosis with enhanced anti-cancer immunity regardless of TMB. FHS constitutes an independent prognostic marker of survival, particularly robustly when combined with TMB in TNBC.

HBXIP expression predicts patient prognosis in breast cancer

2014 ◽  
Vol 31 (10) ◽  
Author(s):  
Daye Cheng ◽  
Bin Liang ◽  
Yunhui Li
Keyword(s):  
Breast Cancer ◽  
Patient Prognosis

P01-18 IGFBP-2 acts as a survival factor for breast cancer cells: Role of ER-α

2012 ◽  
Vol 22 ◽  
pp. S38
Author(s):  
L. Zeng ◽  
E. Foulstone ◽  
J. Holly ◽  
C. Perks
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Survival Factor

scholarly journals Mutant p53 and Twist1 Co-Expression Predicts Poor Prognosis and Is an Independent Prognostic Factor in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yong-Qu Zhang ◽  
Fan Zhang ◽  
Yun-Zhu Zeng ◽  
Min Chen ◽  
Wen-He Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Clinical Stage ◽  
Lymph Node Involvement ◽  
Mutant P53 ◽  
Breast Cancer Patients ◽  
P53 Expression ◽  
Free Survival ◽  
Node Involvement ◽  
Patient Prognosis

PurposeThe basic helix-loop-helix transcription factor (bHLH) transcription factor Twist1 plays a key role in embryonic development and tumorigenesis. p53 is a frequently mutated tumor suppressor in cancer. Both proteins play a key and significant role in breast cancer tumorigenesis. However, the regulatory mechanism and clinical significance of their co-expression in this disease remain unclear. The purpose of this study was to analyze the expression patterns of p53 and Twist1 and determine their association with patient prognosis in breast cancer. We also investigated whether their co-expression could be a potential marker for predicting patient prognosis in this disease.MethodsTwist1 and mutant p53 expression in 408 breast cancer patient samples were evaluated by immunohistochemistry. Kaplan-Meier Plotter was used to analyze the correlation between co-expression of Twist1 and wild-type or mutant p53 and prognosis for recurrence-free survival (RFS) and overall survival (OS). Univariate analysis, multivariate analysis, and nomograms were used to explore the independent prognostic factors in disease-free survival (DFS) and OS in this cohort.ResultsOf the 408 patients enrolled, 237 (58%) had high mutant p53 expression. Two-hundred twenty patients (53.9%) stained positive for Twist1, and 188 cases were Twist1-negative. Furthermore, patients that co-expressed Twist1 and mutant p53 (T+P+) had significantly advanced-stage breast cancer [stage III, 61/89 T+P+ (68.5%) vs. 28/89 T-P- (31.5%); stage II, 63/104 T+P+ (60.6%)vs. 41/104 T-P- (39.4%)]. Co-expression was negatively related to early clinical stage (i.e., stages 0 and I; P = 0.039). T+P+ breast cancer patients also had worse DFS (95% CI = 1.217–7.499, P = 0.017) and OS (95% CI = 1.009–9.272, P = 0.048). Elevated Twist1 and mutant p53 expression predicted shorter RFS in basal-like patients. Univariate and multivariate analysis identified three variables (i.e., lymph node involvement, larger tumor, and T+P+) as independent prognostic factors for DFS. Lymph node involvement and T+P+ were also independent factors for OS in this cohort. The total risk scores and nomograms were reliable for predicting DFS and OS in breast cancer patients.ConclusionsOur results revealed that co-expression of mutant p53 and Twist1 was associated with advanced clinical stage, triple negative breast cancer (TNBC) subtype, distant metastasis, and shorter DFS and OS in breast cancer patients. Furthermore, lymph nodes status and co-expression of Twist1 and mutant p53 were classified as independent factors for DFS and OS in this cohort. Co-evaluation of mutant p53 and Twist1 might be an appropriate tool for predicting breast cancer patient outcome.

scholarly journals Nomogram Models Based on Gene Expression in Prediction of Breast Cancer Bone Metastasis

2021 ◽  
Author(s):  
Teng-di Fan ◽  
Di-kai Bei ◽  
Song-wei Li
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Bone Metastasis ◽  
Gene Signature ◽  
Functional Enrichment ◽  
Training Set ◽  
Hub Genes ◽  
Kaplan Meier ◽  
Patient Prognosis ◽  
Kaplan Meier Plotter

Abstract Objective: To design a weighted co-expression network and build gene expression signature-based nomogram (GESBN) models for predicting the likelihood of bone metastasis in breast cancer (BC) patients. Methods: Dataset GSE124647 was used as a training set, and GSE14020 was taken as a validation set. In the training cohort, limma package in R was adopted to obtain differentially expressed genes (DEGs) between BC non-bone metastasis and bone metastasis patients, which were used for functional enrichment analysis. After weighted co-expression network analysis (WGCNA), univariate Cox regression and Kaplan-Meier plotter analyses were performed to screen potential prognosis-related genes. Then, GESBN models were constructed and evaluated. Further, the expression levels of genes in the models were explored in the training set, which was validated in GSE14020. Finally, the prognostic value of hub genes in BC was explored. Results: A total of 1858 DEGs were obtained. WGCNA result showed that the blue module was most significantly related to bone metastasis and prognosis. After survival analyses, GAJ1, SLC24A3, ITGBL1, and SLC44A1 were subjected to construct a GESBN model for overall survival. While GJA1, IGFBP6, MDFI, ITGFBI, ANXA2, and SLC24A3 were subjected to build a GESBN model for progression-free survival. Kaplan-Meier plotter and receiver operating characteristic analyses presented the reliable prediction ability of the models. Besides, GJA1, IGFBP6, ITGBL1, SLC44A1, and TGFBI expressions were significantly different between the two groups in GSE124647 and GSE14020. The hub genes had a significant impact on patient prognosis. Conclusion: Both the four-gene signature and six-gene signature could accurately predict patient prognosis, which may provide novel treatment insights for BC bone metastasis.

scholarly journals Expression of RUNX1 Correlates with Poor Patient Prognosis in Triple Negative Breast Cancer

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e100759 ◽  
Author(s):  
Nicola Ferrari ◽  
Zahra M. A. Mohammed ◽  
Colin Nixon ◽  
Susan M. Mason ◽  
Elizabeth Mallon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Poor Patient ◽  
Patient Prognosis

P70 IGFBP-2 acts as a survival factor in breast cancer cells

2010 ◽  
Vol 20 ◽  
pp. S63-S64
Author(s):  
E. Foulstone ◽  
J.M.P. Holly ◽  
L. Zeng ◽  
Z.E. Winters ◽  
C.M. Perks
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Survival Factor

scholarly journals Expression of γ‐H2AX and patient prognosis in breast cancer cohort

2019 ◽  
Vol 120 (8) ◽  
pp. 12958-12965 ◽  
Author(s):  
Beili Wang ◽  
Zheng Zhang ◽  
Shi’an Xia ◽  
Mawei Jiang ◽  
Yajie Wang
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Cohort ◽  
Patient Prognosis
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