Delineating the transcriptional network of prognostic gene signatures refines treatment recommendations for lymph node negative breast cancer patients
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE62369 | GEO | 2015/09/30
SECONDARY ACCESSION(S): PRJNA263928
REPOSITORIES: GEO
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Project description:We performed Chip-Seq analyses of several DNA binding transcription factors predicted to function as "master transcriptional regulators" (MTRs) of breast cancer prognostic gene signatures in primary human mammary epithelial cells (HMECs). These analyses demonstrated that these factors frequently co–bind the promoters of genes, the expression of which is associated with a proliferative phenotype and poor patient outcome. These data suggest that these predicted MTRs do indeed drive the expression of gene signatures associated with poor patient outcome in breast cancer.
2015-09-30 | GSE62425 | GEO
Project description:Analyses whether, and if so, gene expression can add prognostic information in the subgroups of patients with tumours with low or high proliferative activity. As proliferation measured with MAI and PPH3 has repeatedly been shown to be the best prognosticator in node-negative breast cancer (high sensitivity, little overtreatment). Total RNA were extracted from 94 lymph node negative breast cancer patients
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Project description:IntroductionThe overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. The prognostic value of gene sets from commercial gene-expression assays were compared with proliferation markers.MethodsIllumina WG6 mRNA microarray analysis was used to examine 94 fresh-frozen tumour samples from node-negative breast cancer patients. The patients were divided into low- and high-risk groups for distant metastasis based on the MammaPrint-related genes, and into low-, intermediate- and high-risk groups based on the recurrence score algorithm with genes included in Oncotype DX. These data were then compared to proliferation status, as measured by the mitotic activity index, the expressions of phosphohistone H3 (PPH3), and Ki67.ResultsKaplan-Meier survival analysis for distant-metastasis-free survival revealed that patients with weak and strong PPH3 expressions had 14-year survival rates of 87% (n=45), and 65% (n=49, p=0.014), respectively. Analysis of the MammaPrint classification resulted in 14-year survival rates of 80% (n=45) and 71% (n=49, p=0.287) for patients with low and high risks of recurrence, respectively. The Oncotype DX categorization yielded 14-year survival rates of 83% (n=18), 79% (n=42) and 68% (n=34) for those in the low-, intermediate- and high-risk groups, respectively (p=0.52). Supervised hierarchical cluster analysis for distant-metastasis-free survival in the subgroup of patients with strong PPH3 expression revealed that the genes involved in Notch signalling and cell adhesion were expressed at higher levels in those patients with distant metastasis.ConclusionThis pilot study indicates that proliferation has greater prognostic value than the expressions of either MammaPrint- or Oncotype-DX-related genes. Furthermore, in the subgroup of patients with high proliferation, Notch signalling pathway genes appear to be expressed at higher levels in patients who develop distant metastasis.
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Project description:Analyses whether, and if so, gene expression can add prognostic information in the subgroups of patients with tumours with low or high proliferative activity. As proliferation measured with MAI and PPH3 has repeatedly been shown to be the best prognosticator in node-negative breast cancer (high sensitivity, little overtreatment).
2014-03-05 | GSE46563 | GEO
Project description:Analyses whether, and if so, gene expression can add prognostic information in the subgroups of patients with tumours with low or high proliferative activity. As proliferation measured with MAI and PPH3 has repeatedly been shown to be the best prognosticator in node-negative breast cancer (high sensitivity, little overtreatment). Total RNA were extracted from 94 lymph node negative breast cancer patients
2014-03-05 | E-GEOD-46563 | biostudies-arrayexpress
Project description:BackgroundWe aimed to evaluate the prognostic value of the lymph node ratio (LNR) in patients with axillary lymph node-positive triple-negative breast cancer (TNBC).MethodsThe prognostic efficacy was investigated in the first cohort from the Surveillance, Epidemiology, and End Results (SEER) dataset (n=4114) and was further validated in an independent cohort from Fudan University Shanghai Cancer Center (n=417). Patients were classified into low-, medium- and high-risk LNR groups.ResultsMultivariate analysis revealed that the LNR was an independent predictor of overall survival (hazard ratio (HR) for high-risk LNR: 3.24; 95% confidence interval (CI): 2.56 to 4.09) and breast cancer-specific survival (HR for high-risk LNR: 3.57; 95% CI: 2.76 to 4.62) in the SEER population and also for disease-free survival (HR for high-risk LNR: 4.29; 95% CI: 2.24-8.21) in the validation population. Subgroup analysis revealed that patient classification according to the LNR could discriminate among groups of patients with different survival rates based on pathological nodal (pN) staging.ConclusionThe LNR shows potential for use as an additional prognostic factor for TNBC patients with positive lymph node involvement. Considering the heterogeneity of TNBC, use of the LNR might allow for optimization of the pN staging system and should be considered when making treatment decisions.
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Project description:Protein expression of Myristoylated alanine-rich C kinase substrate like-1 (MARCKSL1) has been identified as a prognostic factor in lymph-node negative (LN-) breast cancer patients. We aim to validate MARCKSL1 protein expression as a prognostic marker for distant metastasis-free survival (DMFS) in a new cohort of LN- breast cancer patients. MARCKSL1 expression was evaluated in 151 operable T1,2N0M0 LN- breast cancer patients by immunohistochemistry. Median follow-up time was 152 months, range 11-189 months. Results were compared with classical prognosticators (age, tumor diameter, grade, estrogen receptor, and proliferation) using single (Kaplan-Meier) and multivariate (Cox model) survival analysis. Thirteen patients (9%) developed distant metastases. With both single and multiple analysis of all features, MARCKSL1 did not show a significant prognostic value for DMFS (p = 0.498). Of the assessed classical prognosticators, only tumor diameter showed prognostic value (hazard ratio 9.3, 95% confidence interval 2.8-31.0, p <0.001). MARCKSL1 expression could not be confirmed as a prognostic factor in this cohort. Possible reasons include changes in diagnostic and treatment guidelines between the discovery and validation cohorts. Further studies are needed to reveal the potential biological role of this protein in breast cancer.
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Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with no targeted treatment available. Our previous study identified 38 TNBC-specific genes with altered expression comparing tumour to normal samples. This study aimed to establish whether DNA methylation contributed to these expression changes in the same cohort as well as disease progression from primary breast tumour to lymph node metastasis associated with changes in the epigenome. We obtained DNA from 23 primary TNBC samples, 12 matched lymph node metastases, and 11 matched normal adjacent tissues and assayed for differential methylation profiles using Illumina HumanMethylation450 BeadChips. The results were validated in an independent cohort of 70 primary TNBC samples. The expression of 16/38 TNBC-specific genes was associated with alteration in DNA methylation. Novel methylation changes between primary tumours and lymph node metastases, as well as those associated with survival were identified. Altered methylation of 18 genes associated with lymph node metastasis were identified and validated. This study reveals the important role DNA methylation plays in altered gene expression of TNBC-specific genes and lymph node metastases. The novel insights into progression of TNBC to secondary disease may provide potential prognostic indicators for this hard-to-treat breast cancer subtype.
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Project description:BackgroundThe prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment.MethodsWe analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model.ResultsA clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size.ConclusionsThe proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.
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Project description:BackgroundDual-targeted therapy is currently the standard adjuvant treatment for human epidermal growth factor receptor 2-positive (HER2+) and lymph node-positive (LN+) breast cancer. However, the optimal therapeutic strategy for patients with HER2+ and lymph node-negative (LN-) breast cancer remains unclear. This population-based study aimed to explore the factors associated with survival in patients with HER2+ and LN- breast cancer, and develop a survival-predicting nomogram in the era of trastuzumab-based single-targeted therapy.MethodsWe collected the clinicopathological information of HER2+ and LN- breast cancer patients who underwent chemotherapy and surgery from The Surveillance, Epidemiology, and End Results (SEER) database (2010-2016, the Trastuzumab-based single-targeted therapy era). We subsequently explored the risk factors for breast cancer-specific survival (BCSS) and overall survival (OS) using a Cox proportional hazards regression model, aiming to identify subgroups with worse prognosis, which would indicate potential demand for dual-targeted therapy. Three- and 5-year survival probability-predictive nomograms were established and subjected to bootstrap internal validation. The concordance index (C-index) and calibration curve were applied to evaluate the performance of the model.ResultsAfter data cleansing, a total of 13,755 patients were included in the current analysis. Using univariate and multivariate Cox proportional hazards regression, higher clinical T stage, hormone receptors-negative (HR-), and partial mastectomy without radiotherapy were identified as independent risk factors for BCSS and OS in patients with HER2+ and LN- breast cancer. Nomograms for 3- and 5-year BCSS and OS incorporating the selected prognostic factors were established. Calibration curves verified good consistency between the actual and nomogram-predicted survival probability. The C-index values of the BCSS and OS predictions and 95% confidence interval (CI) were 0.773 (0.740-0.806) and 0.764 (0.737-0.791), respectively.ConclusionsHigher clinical T stage, HR-, and partial mastectomy without radiotherapy predicted worse prognosis in patients with HER2+ and LN- breast cancer. In clinical practice, patients can be recommended for single-targeted or dual-targeted therapy according to the individualized factors.
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