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Meta-analysis of the global gene expression profile of triple-negative breast cancer identifies genes for the prognostication and treatment of aggressive breast cancer.

Al-Ejeh F, Simpson PT, Sanus JM, Klein K, Kalimutho M, Shi W, Miranda M, Kutasovic J, Raghavendra A, Madore J, Reid L, Krause L, Chenevix-Trench G, Lakhani SR, Khanna KK - Oncogenesis (2014)

Bottom Line: Meta-analysis in the Oncomine database identified 206 genes that were recurrently deregulated in TNBC compared with non-TNBC and in tumors that metastasized or led to death within 5 years.Particularly, the inhibition of TTK significantly reduced the survival of TNBC cells and synergized with docetaxel in vitro.Prognostication from these metagenes at the mRNA level was limited to ER-positive tumors.

View Article: PubMed Central - PubMed

Affiliation: Signal Transduction Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

ABSTRACT
Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype lacking expression of estrogen and progesterone receptors (ER/PR) and HER2, thus limiting therapy options. We hypothesized that meta-analysis of TNBC gene expression profiles would illuminate mechanisms underlying the aggressive nature of this disease and identify therapeutic targets. Meta-analysis in the Oncomine database identified 206 genes that were recurrently deregulated in TNBC compared with non-TNBC and in tumors that metastasized or led to death within 5 years. This 'aggressiveness gene list' was enriched for two core functions/metagenes: chromosomal instability (CIN) and ER signaling metagenes. We calculated an 'aggressiveness score' as the ratio of the CIN metagene to the ER metagene, which identified aggressive tumors in breast cancer data sets regardless of subtype or other clinico-pathological indicators. A score calculated from six genes from the CIN metagene and two genes from the ER metagene recapitulated the aggressiveness score. By multivariate survival analysis, we show that our aggressiveness scores (from 206 genes or the 8 representative genes) outperformed several published prognostic signatures. Small interfering RNA screen revealed that the CIN metagene holds therapeutic targets against TNBC. Particularly, the inhibition of TTK significantly reduced the survival of TNBC cells and synergized with docetaxel in vitro. Importantly, mitosis-independent expression of TTK protein was associated with aggressive subgroups, poor survival and further stratified outcome within grade 3, lymph node-positive, HER2-positive and TNBC patients. In conclusion, we identified the core components of CIN and ER metagenes that identify aggressive breast tumors and have therapeutic potential in TNBC and aggressive breast tumors. Prognostication from these metagenes at the mRNA level was limited to ER-positive tumors. However, we provide evidence that mitosis-independent expression of TTK protein was prognostic in TNBC and other aggressive breast cancer subgroups, suggesting that protection of CIN/aneuploidy drives aggressiveness and treatment resistance.

No MeSH data available.


Related in: MedlinePlus

Network analysis of the aggressiveness gene list. (a) Ingenuity Pathway Analysis was performed using direct interactions on the 206 genes in the aggressiveness gene list (red is overexpressed and green is underexpressed). One network of high direct interactions was identified. (b) The genes in the network in A were investigated for their correlation with the aggressiveness score and overall survival (Supplementary Table 2), and eight genes (MAPT, MYB, MELK, MCM10, CENPA, EXO1, TTK and KIF2C) with the highest correlation were still connected in a direct interaction network. (c) The overall survival of patients in the METABRIC data set was analyzed according to the score from the 8 genes in C (upper row: by quartiles; lower row: by median) in all patients, non-TNBC patients and in patients with ER+ Grade 2 tumors.
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fig2: Network analysis of the aggressiveness gene list. (a) Ingenuity Pathway Analysis was performed using direct interactions on the 206 genes in the aggressiveness gene list (red is overexpressed and green is underexpressed). One network of high direct interactions was identified. (b) The genes in the network in A were investigated for their correlation with the aggressiveness score and overall survival (Supplementary Table 2), and eight genes (MAPT, MYB, MELK, MCM10, CENPA, EXO1, TTK and KIF2C) with the highest correlation were still connected in a direct interaction network. (c) The overall survival of patients in the METABRIC data set was analyzed according to the score from the 8 genes in C (upper row: by quartiles; lower row: by median) in all patients, non-TNBC patients and in patients with ER+ Grade 2 tumors.

Mentions: We performed network analysis on the aggressiveness gene list by using the Ingenuity Pathway Analysis and found a network with direct interactions between 97 of the 206 deregulated genes (Figure 2a). To find the minimal genes that represent the aggressiveness genes and this network, the 97 genes in this network were analyzed for their correlation with the CIN or ER metagenes and overall survival in the METABRIC data-set (Supplementary Table 2). We selected genes according to the following criteria: (1) highest correlation with the metagenes (Pearson's correlation coefficient >0.7); (2) association with overall survival (Cox proportional hazards model, P<0.001); and (3) more than two-fold deregulation with least standard deviation of expression between high and low aggressiveness score tumors. These analyses identified two genes from the ER metagene (MAPT and MYB) and six genes from the CIN metagene (MELK, MCM10, CENPA, EXO1, TTK and KIF2C). These eight genes were maintained in a directly connected network (Figure 2b). The classification of tumors (high vs low across the median) from these eight genes, again representing the ratio of CIN and ER metagenes, predicted the classification from the 206 genes with 95% sensitivity and 97% specificity by prediction of microarray (PAM) analysis (data not shown). Importantly, a high score from these eight genes identified poor survival in all patients, non-TNBC patients and ER+ Grade 2 (Figure 2c).


Meta-analysis of the global gene expression profile of triple-negative breast cancer identifies genes for the prognostication and treatment of aggressive breast cancer.

Al-Ejeh F, Simpson PT, Sanus JM, Klein K, Kalimutho M, Shi W, Miranda M, Kutasovic J, Raghavendra A, Madore J, Reid L, Krause L, Chenevix-Trench G, Lakhani SR, Khanna KK - Oncogenesis (2014)

Network analysis of the aggressiveness gene list. (a) Ingenuity Pathway Analysis was performed using direct interactions on the 206 genes in the aggressiveness gene list (red is overexpressed and green is underexpressed). One network of high direct interactions was identified. (b) The genes in the network in A were investigated for their correlation with the aggressiveness score and overall survival (Supplementary Table 2), and eight genes (MAPT, MYB, MELK, MCM10, CENPA, EXO1, TTK and KIF2C) with the highest correlation were still connected in a direct interaction network. (c) The overall survival of patients in the METABRIC data set was analyzed according to the score from the 8 genes in C (upper row: by quartiles; lower row: by median) in all patients, non-TNBC patients and in patients with ER+ Grade 2 tumors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4007196&req=5

fig2: Network analysis of the aggressiveness gene list. (a) Ingenuity Pathway Analysis was performed using direct interactions on the 206 genes in the aggressiveness gene list (red is overexpressed and green is underexpressed). One network of high direct interactions was identified. (b) The genes in the network in A were investigated for their correlation with the aggressiveness score and overall survival (Supplementary Table 2), and eight genes (MAPT, MYB, MELK, MCM10, CENPA, EXO1, TTK and KIF2C) with the highest correlation were still connected in a direct interaction network. (c) The overall survival of patients in the METABRIC data set was analyzed according to the score from the 8 genes in C (upper row: by quartiles; lower row: by median) in all patients, non-TNBC patients and in patients with ER+ Grade 2 tumors.
Mentions: We performed network analysis on the aggressiveness gene list by using the Ingenuity Pathway Analysis and found a network with direct interactions between 97 of the 206 deregulated genes (Figure 2a). To find the minimal genes that represent the aggressiveness genes and this network, the 97 genes in this network were analyzed for their correlation with the CIN or ER metagenes and overall survival in the METABRIC data-set (Supplementary Table 2). We selected genes according to the following criteria: (1) highest correlation with the metagenes (Pearson's correlation coefficient >0.7); (2) association with overall survival (Cox proportional hazards model, P<0.001); and (3) more than two-fold deregulation with least standard deviation of expression between high and low aggressiveness score tumors. These analyses identified two genes from the ER metagene (MAPT and MYB) and six genes from the CIN metagene (MELK, MCM10, CENPA, EXO1, TTK and KIF2C). These eight genes were maintained in a directly connected network (Figure 2b). The classification of tumors (high vs low across the median) from these eight genes, again representing the ratio of CIN and ER metagenes, predicted the classification from the 206 genes with 95% sensitivity and 97% specificity by prediction of microarray (PAM) analysis (data not shown). Importantly, a high score from these eight genes identified poor survival in all patients, non-TNBC patients and ER+ Grade 2 (Figure 2c).

Bottom Line: Meta-analysis in the Oncomine database identified 206 genes that were recurrently deregulated in TNBC compared with non-TNBC and in tumors that metastasized or led to death within 5 years.Particularly, the inhibition of TTK significantly reduced the survival of TNBC cells and synergized with docetaxel in vitro.Prognostication from these metagenes at the mRNA level was limited to ER-positive tumors.

View Article: PubMed Central - PubMed

Affiliation: Signal Transduction Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

ABSTRACT
Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype lacking expression of estrogen and progesterone receptors (ER/PR) and HER2, thus limiting therapy options. We hypothesized that meta-analysis of TNBC gene expression profiles would illuminate mechanisms underlying the aggressive nature of this disease and identify therapeutic targets. Meta-analysis in the Oncomine database identified 206 genes that were recurrently deregulated in TNBC compared with non-TNBC and in tumors that metastasized or led to death within 5 years. This 'aggressiveness gene list' was enriched for two core functions/metagenes: chromosomal instability (CIN) and ER signaling metagenes. We calculated an 'aggressiveness score' as the ratio of the CIN metagene to the ER metagene, which identified aggressive tumors in breast cancer data sets regardless of subtype or other clinico-pathological indicators. A score calculated from six genes from the CIN metagene and two genes from the ER metagene recapitulated the aggressiveness score. By multivariate survival analysis, we show that our aggressiveness scores (from 206 genes or the 8 representative genes) outperformed several published prognostic signatures. Small interfering RNA screen revealed that the CIN metagene holds therapeutic targets against TNBC. Particularly, the inhibition of TTK significantly reduced the survival of TNBC cells and synergized with docetaxel in vitro. Importantly, mitosis-independent expression of TTK protein was associated with aggressive subgroups, poor survival and further stratified outcome within grade 3, lymph node-positive, HER2-positive and TNBC patients. In conclusion, we identified the core components of CIN and ER metagenes that identify aggressive breast tumors and have therapeutic potential in TNBC and aggressive breast tumors. Prognostication from these metagenes at the mRNA level was limited to ER-positive tumors. However, we provide evidence that mitosis-independent expression of TTK protein was prognostic in TNBC and other aggressive breast cancer subgroups, suggesting that protection of CIN/aneuploidy drives aggressiveness and treatment resistance.

No MeSH data available.


Related in: MedlinePlus