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A generic cycling hypoxia-derived prognostic gene signature: application to breast cancer profiling.

Boidot R, Branders S, Helleputte T, Rubio LI, Dupont P, Feron O - Oncotarget (2014)

Bottom Line: The transcriptome associated with cycling hypoxia (CycHyp) could thus represent a prognostic biomarker of cancer progression.The CycHyp signature could also identify ER+HER2 node-negative breast cancer patients at high risk based on clinicopathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based but who presented a negative outcome.The CycHyp signature is prognostic of breast cancer and offers a unique decision making tool to complement anatomopathologic evaluation.

View Article: PubMed Central - PubMed

Affiliation: Institut de Recherche Expérimentale et Clinique (IREC), Pole of Pharmacology and Therapeutics (FATH), Université catholique de Louvain, Brussels, Belgium. These authors contribued equally to this work.

ABSTRACT

Background: Temporal and local fluctuations in O2 in tumors require adaptive mechanisms to support cancer cell survival and proliferation. The transcriptome associated with cycling hypoxia (CycHyp) could thus represent a prognostic biomarker of cancer progression.

Method: We exposed 20 tumor cell lines to repeated periods of hypoxia/reoxygenation to determine a transcriptomic CycHyp signature and used clinical data sets from 2,150 breast cancer patients to estimate a prognostic Cox proportional hazard model to assess its prognostic performance.

Results: The CycHyp prognostic potential was validated in patients independently of the receptor status of the tumors. The discriminating capacity of the CycHyp signature was further increased in the ER+ HER2- patient populations including those with a node negative status under treatment (HR=3.16) or not (HR=5.54). The CycHyp prognostic signature outperformed a signature derived from continuous hypoxia and major prognostic metagenes (P<0.001). The CycHyp signature could also identify ER+HER2 node-negative breast cancer patients at high risk based on clinicopathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based but who presented a negative outcome.

Conclusions: The CycHyp signature is prognostic of breast cancer and offers a unique decision making tool to complement anatomopathologic evaluation.

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Related in: MedlinePlus

Kaplan-Meier survival curves of node-negative, untreated ER+/HER2- patients stratified by using the CycHyp signature to detect(A.) false positive patients among those identified at high risk based on the NPI nomenclature and (B.) false negative patients among those identified at low risk based on the NPI nomenclature (DFS Mantel-Cox comparison).
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Figure 4: Kaplan-Meier survival curves of node-negative, untreated ER+/HER2- patients stratified by using the CycHyp signature to detect(A.) false positive patients among those identified at high risk based on the NPI nomenclature and (B.) false negative patients among those identified at low risk based on the NPI nomenclature (DFS Mantel-Cox comparison).

Mentions: We then aimed to determine whether the CycHyp signature could improve the Nottingham Prognostic Index (NPI) for better predicting the survival of operable breast cancers. The NPI algorithm combines nodal status, tumour size and histological grade and allows to model a continuum of clinical aggressiveness with 3 subsets of patients divided into good, moderate, and poor prognostic groups with 15-year survival [22, 23, 36]. Since few patients were assigned a poor index, we merged here the moderate and poor indices into a high risk group to facilitate the comparison with the CycHyp signature. We found that by integrating the CycHyp signature, an important proportion of patients could be reclassified to another risk group (Figure 4). 44.1% of patients classified at high risk using the NPI algorithm were identified at low risk when using the CycHyp signature and were confirmed to be “false positive” since they actually exhibited a profile of survival closer to the low risk NPI patient (Figure 4A). Inversely, using the CycHyp signature, we also identified in the patients at low risk based on the NPI criteria, 33.1% of patients with a risk profile closer to the patients with a negative outcome (Figure 4B). This increased discriminating potential remained highly relevant when considering all patients or patients with a ER+ HER2- status (and among the latter, those with a node negative status or the untreated ones) (see Suppl. Figure 4).


A generic cycling hypoxia-derived prognostic gene signature: application to breast cancer profiling.

Boidot R, Branders S, Helleputte T, Rubio LI, Dupont P, Feron O - Oncotarget (2014)

Kaplan-Meier survival curves of node-negative, untreated ER+/HER2- patients stratified by using the CycHyp signature to detect(A.) false positive patients among those identified at high risk based on the NPI nomenclature and (B.) false negative patients among those identified at low risk based on the NPI nomenclature (DFS Mantel-Cox comparison).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4196175&req=5

Figure 4: Kaplan-Meier survival curves of node-negative, untreated ER+/HER2- patients stratified by using the CycHyp signature to detect(A.) false positive patients among those identified at high risk based on the NPI nomenclature and (B.) false negative patients among those identified at low risk based on the NPI nomenclature (DFS Mantel-Cox comparison).
Mentions: We then aimed to determine whether the CycHyp signature could improve the Nottingham Prognostic Index (NPI) for better predicting the survival of operable breast cancers. The NPI algorithm combines nodal status, tumour size and histological grade and allows to model a continuum of clinical aggressiveness with 3 subsets of patients divided into good, moderate, and poor prognostic groups with 15-year survival [22, 23, 36]. Since few patients were assigned a poor index, we merged here the moderate and poor indices into a high risk group to facilitate the comparison with the CycHyp signature. We found that by integrating the CycHyp signature, an important proportion of patients could be reclassified to another risk group (Figure 4). 44.1% of patients classified at high risk using the NPI algorithm were identified at low risk when using the CycHyp signature and were confirmed to be “false positive” since they actually exhibited a profile of survival closer to the low risk NPI patient (Figure 4A). Inversely, using the CycHyp signature, we also identified in the patients at low risk based on the NPI criteria, 33.1% of patients with a risk profile closer to the patients with a negative outcome (Figure 4B). This increased discriminating potential remained highly relevant when considering all patients or patients with a ER+ HER2- status (and among the latter, those with a node negative status or the untreated ones) (see Suppl. Figure 4).

Bottom Line: The transcriptome associated with cycling hypoxia (CycHyp) could thus represent a prognostic biomarker of cancer progression.The CycHyp signature could also identify ER+HER2 node-negative breast cancer patients at high risk based on clinicopathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based but who presented a negative outcome.The CycHyp signature is prognostic of breast cancer and offers a unique decision making tool to complement anatomopathologic evaluation.

View Article: PubMed Central - PubMed

Affiliation: Institut de Recherche Expérimentale et Clinique (IREC), Pole of Pharmacology and Therapeutics (FATH), Université catholique de Louvain, Brussels, Belgium. These authors contribued equally to this work.

ABSTRACT

Background: Temporal and local fluctuations in O2 in tumors require adaptive mechanisms to support cancer cell survival and proliferation. The transcriptome associated with cycling hypoxia (CycHyp) could thus represent a prognostic biomarker of cancer progression.

Method: We exposed 20 tumor cell lines to repeated periods of hypoxia/reoxygenation to determine a transcriptomic CycHyp signature and used clinical data sets from 2,150 breast cancer patients to estimate a prognostic Cox proportional hazard model to assess its prognostic performance.

Results: The CycHyp prognostic potential was validated in patients independently of the receptor status of the tumors. The discriminating capacity of the CycHyp signature was further increased in the ER+ HER2- patient populations including those with a node negative status under treatment (HR=3.16) or not (HR=5.54). The CycHyp prognostic signature outperformed a signature derived from continuous hypoxia and major prognostic metagenes (P<0.001). The CycHyp signature could also identify ER+HER2 node-negative breast cancer patients at high risk based on clinicopathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based but who presented a negative outcome.

Conclusions: The CycHyp signature is prognostic of breast cancer and offers a unique decision making tool to complement anatomopathologic evaluation.

Show MeSH
Related in: MedlinePlus