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Background: Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.
Methodology/Principal Findings: We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).
Conclusions/Significance: Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures.
Introduction: Lymphocyte infiltration (LI) is often seen in breast cancer but its importance remains controversial. A positive correlation of human epidermal growth factor receptor 2 (HER2) amplification and LI has been described, which was associated with a more favorable outcome. However, specific lymphocytes might also promote tumor progression by shifting the cytokine milieu in the tumor.
Methods: Affymetrix HG-U133A microarray data of 1,781 primary breast cancer samples from 12 datasets were included. The correlation of immune system-related metagenes with different immune cells, clinical parameters, and survival was analyzed.
Results: A large cluster of nearly 600 genes with functions in immune cells was consistently obtained in all datasets. Seven robust metagenes from this cluster can act as surrogate markers for the amount of different immune cell types in the breast cancer sample. An IgG metagene as a marker for B cells had no significant prognostic value. In contrast, a strong positive prognostic value for the T-cell surrogate marker (lymphocyte-specific kinase (LCK) metagene) was observed among all estrogen receptor (ER)-negative tumors and those ER-positive tumors with a HER2 overexpression. Moreover ER-negative tumors with high expression of both IgG and LCK metagenes seem to respond better to neoadjuvant chemotherapy.
Conclusions: Precise definitions of the specific subtypes of immune cells in the tumor can be accomplished from microarray data. These surrogate markers define subgroups of tumors with different prognosis. Importantly, all known prognostic gene signatures uniformly assign poor prognosis to all ER-negative tumors. In contrast, the LCK metagene actually separates the ER-negative group into better or worse prognosis.
Background The proto-oncogene pituitary tumor-transforming gene (PTTG) has been shown to be abundantly overexpressed in a large variety of neoplasms likely promoting neo-vascularization and tumor invasiveness. In this study, we investigated a potential role for PTTG mRNA expression as a marker to evaluate the future clinical outcome of patients diagnosed with primary cancer of the head and neck. Methods Tumor samples derived from primary tumors of 89 patients suffering from a squamous cell carcinoma were analyzed for PTTG mRNA-expression and compared to corresponding unaffected tissue. Expression levels were correlated to standard clinico-pathological parameters based on a five year observation period. Results In almost all 89 tumor samples PTTG was found to be overexpressed (median fold increase: 2.1) when compared to the unaffected tissue specimens derived from the same patient. The nodal stage correlated with PTTG transcript levels with significant differences between pN0 (median expression: 1.32) and pN+ (median expression: 2.12; P = 0.016). In patients who developed a tumor recurrence we detected a significantly higher PTTG expression in primary tumors (median expression: 2.63) when compared to patients who did not develop a tumor recurrence (median expression: 1.29; P = 0.009). Since the median expression of PTTG in patients with tumor stage T1/2N0M0 that received surgery alone without tumor recurrence was 0.94 versus 3.82 in patients suffering from a tumor recurrence (P = 0.006), PTTG expression might provide a feasible mean of predicting tumor recurrence. Conclusion Elevated PTTG transcript levels might be used as a prognostic biomarker for future clinical outcome (i.e. recurrence) in primary squamous cell carcinomas of the head and neck, especially in early stages of tumor development.