Molecular profiles of progesterone receptor loss in human breast tumors.
BACKGROUND
Patient prognosis and response to endocrine therapy in breast cancer correlate with protein expression of both estrogen receptor (ER) and progesterone receptor (PR), with poorer outcome in patients with ER+/PR- compared to ER+/PR+ tumors.


METHODS
To better understand the underlying biology of ER+/PR- tumors, we examined RNA expression (n > 1000 tumors) and DNA copy number profiles from five previously published studies of human breast cancers with clinically assigned hormone receptor status (ER+/PR+, ER+/PR-, and ER-/PR-).


RESULTS
We identified an expression "signature" of genes with either elevated or diminished RNA levels specifically in ER+/PR+ compared to ER-/PR- and ER+/PR- tumors. We similarly identified a gene signature specific to ER-/PR- tumors. ER+/PR- tumors, on the other hand, were a mixture of three different subtypes: tumors manifesting the ER+/PR+ signature, tumors manifesting the ER-/PR- signature, and tumors not associating with ER+/PR+ or ER-/PR- tumors (which we considered "true" ER+/PR-). In analyses of both tamoxifen-treated and untreated patients, ER+/PR- breast cancers defined by RNA profiling were associated with poor patient outcome, worse than those with pure ER+/PR+ patterns; these differences were not observed when using clinical assays to assign ER and PR status. ER+/PR- tumors also showed twice as many DNA copy number gains or losses compared to ER+/PR+ and ER-PR- tumors. Targets of transcriptional up-regulation by specific oncogenic pathways, including PI3 K/Akt/mTOR, were enriched in both ER+/PR- and ER-/PR- compared to ER+/PR+ tumors.


CONCLUSIONS
ER+/PR- tumors as defined by RNA profiling represent a distinct subset of breast cancer with aggressive features and poor outcome, despite being clinically ER+. Multigene assays derived from our gene signatures could conceivably provide an improved clinical assay for inferring PR status for prognostic and therapeutic purposes.
Creighton
Chad J
CJ
Dan L Duncan Cancer Center Division of Biostatistics, Baylor College of Medicine, Houston, TX 77030, USA. creighto@bcm.edu
Kent Osborne
C
C
van de Vijver
Marc J
MJ
Foekens
John A
JA
Klijn
Jan G
JG
Horlings
Hugo M
HM
Nuyten
Dimitry
D
Wang
Yixin
Y
Zhang
Yi
Y
Chamness
Gary C
GC
Hilsenbeck
Susan G
SG
Lee
Adrian V
AV
Schiff
Rachel
R
D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D047628:Estrogen Receptor alpha / Q000235:genetics / Q000378:metabolism*; D005260:Female; D018628:Gene Dosage; D020869:Gene Expression Profiling; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D019869:Phosphatidylinositol 3-Kinases / Q000235:genetics / Q000378:metabolism; D011379:Prognosis; D011494:Protein Kinases / Q000235:genetics / Q000378:metabolism; D051057:Proto-Oncogene Proteins c-akt / Q000235:genetics / Q000378:metabolism; D011980:Receptors, Progesterone / Q000235:genetics*; D015398:Signal Transduction; D058570:TOR Serine-Threonine Kinases
D014408:Biomarkers, Tumor; D047628:Estrogen Receptor alpha; D019869:Phosphatidylinositol 3-Kinases; D011494:Protein Kinases; D051057:Proto-Oncogene Proteins c-akt; D011980:Receptors, Progesterone; D058570:TOR Serine-Threonine Kinases; C506487:ESR1 protein, human; C546842:MTOR protein, human