Triple negative breast cancer lacks estrogen, progesterone and epidermal growth factor receptors rendering it refractory to available targetedtherapies. TNBC is associated with central fibrosis and necrosis, both indicators of tumor hypoxia. Hypoxia inducible factor 1α is up-regulated under hypoxia and its expression is associated with induction of angiogenesis resulting in proliferation, aggressive tumor phenotype and metastasis. In this study we evaluate the potential use of HIF-1α as aTNBC-specific marker.
62 TNBC, 64 HER2+, and 64 hormone-receptors positive breast cancer cases were evaluated for central fibrosis and necrosis, HIF-1α, HIF-1β, VEGFR3, CD31 expression and microvessel density. RNA extraction from paraffin-embedded samples, followed by quantitative real-time polymerase chain reaction (qRT-PCR) evaluation of HIF-1α and VEGF transcripts was performed on 54 cases (18 from each subtype).
HIF-1α protein was expressed in 35.5% TNBC, 45.3% HER2+and 25.0% ER+/PR+ (p = 0.055; χ2 test). PCRanalysis of subgroup of breast cancers, 84.2% expressed HIF-1α protein and its transcripts, while only 66.7% expressed VEGF transcripts simultaneously with the HIF-1α protein and its transcripts. Central fibrosis and necrosis was highest in TNBC (p = 0.015; χ2 test), while MVD was comparable among all groups (p = 0.928; χ2 test). VEGFR3 was highest in TNBC expressing HIF-1α. HIF-1β protein was expressed in 32.0% of HIF-1α(+), and in (44.3%) of HIF-1α(-) breast cancer cases (p = 0.033; χ2 test). Moreover, HIF-1α expression in cases with central fibrosis and necrosis was highest in the HER2+ followed by the TNBC (p = 0.156; χ2 test).
A proportion of TNBC express HIF-1α but not in a significantly different manner from other breast cancer subtypes. The potential of anti-HIF-1α targeted therapy is therefore not a candidate for exclusive use in TNBC, but should be considered in all breast cancers, especially in the setting of clinically aggressive or refractory disease.
Citation: Yehia L, Boulos F, Jabbour M, Mahfoud Z, Fakhruddin N, El-Sabban M (2015) Expression of HIF-1α and Markers of Angiogenesis Are Not Significantly Different in Triple Negative Breast Cancer Compared to Other Breast Cancer Molecular Subtypes: Implications for Future Therapy. PLoS ONE 10(6): e0129356. doi:10.1371/journal.pone.0129356
Academic Editor: Sonia Rocha, University of Dundee, UNITED KINGDOM
Received: January 23, 2014; Accepted: May 7, 2015; Published: June 5, 2015
Copyright: © 2015 Yehia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Funding: This study has been supported by the Lebanese National Council for Scientific Research (LNCSR) grant #114160/522240. "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."
Competing interests: "The authors have declared that no competing interests exist."
Breast carcinoma exhibits regional hypoxia during its early stages of development. Under hypoxic conditions, the induced “angiogenic switch” causes an elevated expression of Hypoxia inducible factor 1α(HIF-1α) [1–3], followed by “vascular endothelial growth factor (VEGF)-induced angiogenesis”, and consequently tumor vascularization, which promotes tumor progression, invasion and eventually metastasis[5–7]. Although high HIF-1α expression was documented in all breast carcinoma subtypes, a stronger correlation was found with non-heritable and heritable BRCA1 mutation-associated cancers, which in turn are associated with the basal-like molecular subgroup and a triple-negative phenotype[8–10].
Triple negative breast cancer (TNBC), which is defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, accounts for 10–17% of all breast carcinomas[11–20]. Though heterogeneous, TNBCs are most commonly high-grade invasive ductal carcinomas that often affect younger patients[11,13,16,19,21], and pursue an aggressive clinical course[16,19,22,23]. TNBC is regrettably excluded from the effective targeted therapy used in luminal and HER2-positive breast carcinomas due to its lack of hormonal and Human Epidermal Growth Factor receptor expression [20,24–28].
The association between HIF-1α and the frequently triple negative familial breast cancer brings forth the possibility of novel targeted therapy for TNBC, namely anti-HIF-1α chemotherapy and related agents. This is especially plausible given the frequent association of TNBC with central necrosis, a surrogate morphologic marker for hypoxia.
In this study, we assessed the expression of HIF-1α and other markers of hypoxia and angiogenesis including VEGF, vascular endothelial growth factor receptor 3 (VEGFR3), and microvessel density (MVD) in TNBC as compared to HER2+ and luminal-type breast cancers in order to evaluate the practical potential of using anti-HIF-1α as a therapeutic target for TNBC preferentially to other breast cancer subtypes.
Materials and Methods
Institutional review board at the American University of Beirut approved the study with waiver of a written patient informed consent.
Patients and specimens
Pathology reports of patients with breast carcinoma between 2001 and 2011 were accessed from the Pathology Departments at the American University of Beirut Medical Center (AUBMC) and Hammoud Hospital University Medical Center (HHUMC). IRB approval was obtained and no patient consent was required. Patients with no prior chemotherapy, radiotherapy, hormonal therapy, or any form of targeted therapy were selected as follows: all TNBC(64) cases (group 1) were identified and retrieved. They were matched with an equal number of ER-/PR-/HER 2+ (group 2) and ER+/PR+/HER 2- (group 3) breast carcinomas. Cases were then re-evaluated for histologic subtype, grade, central fibrosis and tumor necrosis, as well as adequacy (two TNBC core biopsies were excluded because of minimal (<200) number of tumor cells). For each of the included one hundred and ninety (190) cases, a representative formalin-fixed paraffin-embedded (FFPE) tissue block was selected for immunohistochemical (IHC) and molecular analyses. Negative controls for both techniques were obtained from reduction mammoplasty tissue. ER, PR, and HER2 expression was assessed using immunohistochemistry according to the ASCO-CAP guidelines 2010 and 2007 respectively[29,30]. In addition, presence of central necrosis and fibrosis was considered when we identified a central scar defined as a central, predominantly acellular area of tumor showing sclerosis, myxoidstroma, fibrosis or necrosis.
Three sections (3μm thick) per selected paraffin block were prepared and deparaffinized to be stained for HIF-1α(H1a67,Abcam, San Francisco, CA, USA), HIF-1β (ab54786, Abcam, San Francisco, CA, USA), VEGFR3 (KLT9,Novocastra-Newcastle, UK) and CD31(1A10,Novocastra-Newcastle, UK)by immunohistochemistry for all the 190 cases. All antibodies were used at a 1:100 dilution and endogenous peroxidase activity was blocked for 10 minutes in 5% hydrogen peroxide. Antigen retrieval using pepsin was performed for HIF-1α, HIF-1β, and CD31 staining.Biogenics Super Sensitive polymer detection system and DAB (diaminebenzidine) chromogen was used.The slides were then treated in accordance with the manufacturer’s instructions and counter-stained with hematoxylin.
HIF-1α and HIF-1β expression was considered positive when at least 5% of the tumor cells showed nuclear staining, and VEGFR3 was considered positive when at least 10% of tumor cells showed cytoplasmic staining .
HIF-1α and HIF-1β expression was evaluated by applying the scoring system used by Santos et.al . Each sample was evaluated for intensity of nuclear staining and percentage of positive nuclei. The score for signal intensity is: negative (0), weak (1), moderate (2) and strong (3). The score for percentage of positive nuclei is: (1) when <10% of cells were positive; (2) when 10–50% of cells were positive and (3) when >50% of cells were positive. Then both scores were multiplied, and the HIF1a expression resulting score is designated as negative (<1), weak (1–6) and strong (>6).
Microvessel density evaluation
Four fields were selected randomly at 20x in the CD31 stained slides, photographed and counted. Microvessels were identified as circumscribed patent lumens surrounded by positively staining endothelial cells. The mean vessel count in all four fields was recorded.
Total Nucleic Acid Isolation Kit (Ambion, Applied Biosystems, California, USA) was used to extract RNA from FFPE breast tissues. 80μm thick ribbons were obtained and RNA extracted according to the manufacturer’s recommendations. RNA was quantified using NanoDrop ND-1000 spectrophotometric system.
54 cases were selected from the 3 groups (18 cases per group) for molecular analysis. The selection aimed to obtain 3 equally distributed categories: ≤40 years, 40 to 60 years, and >60 years of age at diagnosis.
cDNA was synthesized from 1μg of extracted RNA using the RevertAid 1st Strand cDNA synthesis kit (Fermentas). iQ SYBR Green Supermix (Bio-Rad) was used in CFX96 real-time PCR system (Bio-Rad). The cycling conditions included aprecycle for 3 minutes at 95°C, followed by 40 cycles of denaturation (15 seconds at 95°C), annealing (1 minute at the specific primer-optimized annealing temperature), and extension (1 minute at 72°C).Final extension was for 5 minutes at 72°C followed by generating the melting curve from 55°C to 95°C in 0.5°C increments.
The primers used were GAPDH (forward: TGGTGCTCAGTGTAGCCCAG, reverse: GGACCTGACCTGCCGTCTAG) with an annealing temperature of55˚C; HIF-1α (forward: AGCCAGATCTCGGCGAAGT, reverse: CAGAGGCCTTATCAAGATGCG) with an annealing temperature of 58°C; and VEGF (forward: AGGCCCACAGGGATTTTCTT, reverse: ATCAAACCTCACCAAGGCCA) with an annealing temperature of 55°C.
The fluorescence threshold cycle (Ct) value was determined for each gene and normalized with GAPDH. All values were compared and normalized to normal breast tissues.
Sample characteristics were summarized using means for numeric variables for age and MVD. Frequency distributions were used for the categorical variable VEGFR3. Chi-squared test or Fisher’s exact test (when counts fell below 5) were used to compare VEGFR3 expression and HIF-1α in the three breast carcinoma groups. In addition, Chi-squared test was used to compare HIF-1a with HIF-1β in VEGF positive cases. Pair-wise comparisons were also carried when the differences were significant using the Chi-squared test or Fisher’s exact test. Results of pair-wise comparisons were represented by Roman letters. Groups that were not significantly different were denoted with the same letter. Chi-squared test was used to compare central fibrosis and necrosis. This analysis was also repeated adjusting for age by using multivariate logistic regression.
The PCR data was analyzed by summarizing the fold changes using means and standard deviations along with medians and ranges. Since the distribution of the two variables (HIF-1α and VEGF) was skewed, we compared their median using the Kruskal-Wallis test. The Wilcoxon rank sum test was used to compare the fold change in HIF-1α between those that expressed HIF-1α by immunohistochemistry and those that did not express HIF-1α. Analyses were performed using SPSS software (version 19). A p-value of 0.05 or less was considered statistically significant.
Patient age ranged from 26 to 88 years (mean = 52 years, standard deviation = 12.8). Patients younger than 40 years were more prevalent in Groups 1 and 2 (23.3% and 28.1% respectively) (Table 1). More than 80% of TNBC and HER2+ groups were grade 3/3 (Nottingham grading system), as compared to 55% in ER+/PR+ tumors.
Central fibrosis and necrosis in TNBC
15.3% of all tumors showed central fibrosis and tumor necrosis, which differed significantly among the 3 Groups (p = 0.019) (Table 1). TNBC had the highest values among all groups even after adjusting the results for age (no change in the p-values, results not shown in the table).
MVD and VEGF expression
MVD showed no significant variation between the 3 groups (Table 1), although the mean MVD count was higher but not significantly so (p = 0.928) in TNBC cases that expressed HIF-1α. In addition, MVD did not correlate with VEGF fold increase significantly (data not shown).
HIF-1α nuclear expression by immunohistochemistry was highest in the HER2+ group,howeverthereis no statistical significant difference amongthe three different groups [TNBC (35.5%), HER2+(45.3%) and ER+/PR+(25.0%)] (p = 0.055).
VEGFR3 expression differed significantly (p = 0.003) between the three groups with the highest expression in HER2+, while the TNBC group had an intermediate value between HER2+and ER+/PR+. Additionally, VEGFR3 expression was higher among patients expressing HIF-1α as compared to those with negative HIF-1α expression, though not in a statistically significant manner.
Correlation between transcriptional and protein levels of HIF-1α and VEGF
The quantity of extracted RNA ranged from 8 to 1053 ng/μl (mean = 264 ng/μl ± SD = 233 ng/μl, SEM = 32 ng/μl). Only 4 specimens yielded an RNA concentration < 65 ng/μl. These four cases were excluded. The variability in the quantity of extracted RNA may have resulted from the physical dimensions of the embedded tissue (biopsy versus resection) and nature of the specimen (fatty or fibrous tissues resulted in relatively lower RNA yields). All RNA samples gave a 260/280 nm ratio of ~2.0. qRT-PCR analysis results correlated with the immunohistochemical expression profiles of the studied biomarkers. The mean fold changes in the HIF-1α were 2.34,4.56, and 2.66for the TNBC, HER2+, and ER+/PR+respectively. This finding was significantly higher in HER2+(p = 0.043) (Fig 1). The mean fold changes in VEGF were 1.87, 1.37and 1.58 for the respective groups and revealed no significant variation (p = 0.173) (Table 2).
Transcriptional levels of HIF-1α and VEGF, and HIF-1α nuclear expression were correlated in the selected 50 cases. 19cases (38%) showed HIF-1α nuclear expression; 16/19 (84.2%) showed positive transcriptional levels of HIF-1α distributed equally between TNBC and HER2+. Moreover, 9/ 21 (40.9%) expressed both HIF-1α and VEGF transcripts. Of these 9 cases, 6 (66.7%) were TNBC cases and the remaining 3 (33.3%) were HER2+(Fig 2).
Correlation of HIF-1β with HIF-1α expression in breast carcinoma cases
HIF-1α immunoexpression was noted to be mostly weak staining (1+ and 2+) in 35/97 (36.1%) cases (Fig 3). This indicates that HIF-1α is not the sole contributor to the hypoxia driven angiogenesis. Therefore HIF-1β was assessed in order to determine whether the difference in HIF-1α positive cases is due to a difference in HIF-1β expression. Immunohistochemistry for HIF-1β protein was evaluated revealing that 31/97 (32.0%) cases were HIF-1β(+)/HIF-1α(+), 43/97 (44.3%) HIF-1β(-)/HIF-1α(+), 4/97 (4.1%) HIF-1β(+)/HIF-1α(-) and 19/97 (19.6%) HIF-1β(-)/HIF1α(-). When comparing HIF-1α expression with HIF-1β expression, the findings indicated a statistical difference between the status of HIF-1α expression and corresponding HIF-1β immunoexpression (p = 0.033; χ2 test).
Furthermore, HIF-1α expression is known to stimulateVEGF expression. The question is whether the difference in HIF-1α immunoexpression and VEGF mRNA expression correlates with HIF-1β immunoexpression (Fig 4, Table 3). In HIF-1β positive cases 13/42 (31.0%) VEGF tested cases were HIF-1α(+)/VEGF(+), 12/42 (28.6%) HIF-1α(-)/VEGF(+), 2/42 (4.8%) HIF-1α(+)/VEGF (-) and 4/42 (9.5%) HIF-1α (-)/VEGF (-). In HIF-1β negative cases, the status of HIF-1α and VEGF were as follows; 1/42 (2.4%) HIF-1α(+)/VEGF(+), 8/42 (19.1%) HIF-1α(-)/VEGF (+), 0/42 HIF-1α (+)/VEGF(-) and 6/42 (14.3%) HIF-1α(-)/VEGF(-) Table 4.Therefore, following correlation of HIF-1β status with HIF-1α in VEGF positive breast cancer revealed a statistically significant difference (p = 0.033; χ2 test). This implies that VEGF expression correlates with HIF-1α and HIF-1β expression. However, the question was whether a low VEGF expression correlates with a low HIF-1β and HIF-1α expression. The results were nonstatistically significant (p>0.05; χ2 test) implying that the findings are not reciprocal; note that the number of cases was low in VEGF negative cases (n = 8).
HIF-1α and HIF-1β were expressed in cases with central fibrosis and necrosis. Thehighest expression for HIF-1αwasin HER2+ followed by TNBC, while HIF-1β was expressed in 77% of TNBC; however no statistical significant correlation was observed and sample size was relatively small to draw a definite conclusion (Table 5).
Hypoxia is a complex process associated with aggressive phenotype in many solid tumors including breast cancer[1,2]. A major regulator of hypoxia is the transcription factor HIF-1α. HIF-1α is a part of a heterodimeric protein that undergoes, under normoxicconditions, post-translational ubiquitination followed by proteosomal degradation. During hypoxia, this reaction is inhibited and HIF-1α is stabilized and dimerizes with its constitutive counterpart HIF-1β, forming a complex that translocates to the nucleus, and binds to the hypoxia response elements. This complex activates the transcription of genes involved in cell growth, cell survival, and angiogenesis, consequently facilitating tumor progression and metastasis[4,37]. Identifying potential targets for anti-HIF-1α treatment among breast tumors is an appealing goal, especially for tumors such as TNBC which, as of yet, have no available targeted therapy. We therefore investigated the relative expression of HIF-1α and related angiogenic factors among the three main groups of breast cancer listed above. Our results revealed that TNBC, contrary to expectation, differed only slightly and with little to no statistical significance from the other subgroups, and that HER2 positive tumors showed the highest levels of expression for all studied parameters.
The initial expectation that HIF-1α should be increased in TNBC comes from its high documented levels in hereditary BRCA1 mutated carcinomas (up to 90% of cases). Given that BRCA1-associated breast cancers often belong to the TNBC subtype, and both frequently show morphologic evidence of hypoxia (central fibrosis and necrosis)[9,27,28,38], an augmented expression of HIF-1α in tumors with a triple-negative phenotype was anticipated. In fact, this had been elegantly demonstrated through the preferential expression of HIF-1α in peri-necrotic/peri-fibrotic tumor cells in TNBC and BRCA1 mutated breast cancers[10,39]. In contrast Tan etal. and Choi et al demonstrated an increase in TNBC of CAIX (carbonic anhydrase IX), a downstream product of the hypoxic pathway, rather than an increase in HIF-1α per se[40,41]. The authors did not dispute the likely contribution of hypoxia to the tumors’ aggressive phenotype, however. Our findings seem to be in line with the latter authors’ findings.
In the case of HER2 amplified tumors where hypoxia is not a prominent histologic feature, HIF-1α appears to act in concert with HER2, contributing to aggressive tumor biology. HER2 is a transmembrane tyrosine kinase receptor whose overexpression in breast carcinoma is a major contributor to tumor progression and metastasis[42,43]. HER2 appears to stabilize HIF-1α under normoxic conditions through tyrosine kinase receptor activation, consequently promoting VEGF secretion[44,45]. Recently, Whelan et al. showed that HIF-1α plays a role in HER2 over-expression and oncogenesis by regulating anoikis. Thus the increase in HIF-1α expression and HER2 over-expression may be synergistic rather than necessarily an end product of hypoxic conditions. Nevertheless, the presence of HIF-1α seems likely to contribute to the aggressive tumor phenotype, regardless of the mechanism of its increased expression.
The lack of significant difference between TNBC and the ER+ group is also surprising. ER+/PR+/HER2- breast carcinomas are less aggressive when compared to the TNBC and HER2 amplified groups. ER expression, although known to contribute to breast cancer proliferation, is primarily a marker of better differentiation and renders the tumor responsive to Tamoxifen therapy. In this setting, HIF-1α tends to downregulate ERα[48–51]thus contributing to resistance to Tamoxifen treatment and worsening prognosis.
Our results did reveal that the protein as well as the mRNA expression for HIF-1α were the lowest in this subgroup even when corrected for tumor grade (data not shown), as reported in the literature, but the difference from TNBC failed to meet statistical significance[53,54].
Irrespective of breast cancer subgroup, we similarly did not establish any correlation between HIF-1α expression and age, grade, lymph node status, or MVD, which, when elevated in breast cancer, is thought to indicate an aggressive phenotype. In the TNBC group, the detected mean MVD count was higher in cases that expressed HIF-1α, but not significantly, and showed no correlation with VEGF transcript fold increase. We could show a marginal correlation with VEGFR3 expression (p = 0.083), but with no special selectivity to TNBC.
However, HIF-1α expression appears to correlate with HIF-1β expression when positive. Similarly this is in conjunction with VEGF mRNA expression. Conversely, the absence of HIF-1α expression is inversely correlated with HIF-1β expression. With respect to VEGF expression, HIF1α positivity correlates with a HIF-1β expression. In addition, HIF-1β expression appears to correlate with VEGF status as expected. Finally, HIF-1α and HIF-1β were mainly expressed in HER2 + and TNBC in cases with central fibrosis and necrosis without any statistical difference. Similar findings were demonstrated by Bos et al. that showed a higher expression of HIF1α, with the presence of necrosis in invasive breast cancer.
Based on these findings, the prospects of using anti-HIF-1α therapy is not likely to favor TNBC over other tumor groups, however, targeting HIF-1α may still prove beneficial given its definite expression in a significant portion of all studied breast cancer subtypes. This may be especially important in tumors that manifest aggressive clinical behavior. HIF-1α inhibitors are currently available but they do not exclusively target the HIF-1 pathway; and their efficacy in cancer therapy has not yet been established. One clinical trial is currently recruiting patients with breast cancer to receive digoxin prior to surgery to block HIF-1α and potentially thwart cancer cell growth. Large prospective trials with more specific agents will have to be undertaken to study the potential clinical use of this group of therapeutic agents in all breast cancer categories, not just TNBC.
This study is limited by the number of cases of each group, particularly in determining the mRNA expression of HIF-1α and VEGF (n = 18). Moreover, 85% of the TNBC while only 55% of ER+/PR+ of the cases o were grade 3, this factor may be have influence the results, however up to 95% of ER+/PR+ are less than grade 3 .
In summary, this study demonstrates that a proportion of TNBC is associated with hypoxia-related markers, that this association is not exclusive to TNBC but equally, if not more prominently, present in other breast cancer subtypes such as the HER2+ tumors, and finally that the presence of central fibrosis and necrosis correlate with higher HIF-1α expression levels in the studied cases. Although these findings do not identify a target that is specific for TNBC over other breast cancer subtypes, they do confirm the expression of high levels of HIF-1α at the transcriptional and protein levels in a variety of breast tumors, which may benefit from such targeted therapy, especially in the setting of clinically aggressive and drug resistant disease.
This study has been supported by the Lebanese National Council for Scientific Research (LNCSR) grant #114160/522240. The authors also acknowledge Dr. Ghazi Zaatari, Chair of the Department of Pathology and Laboratory Medicine at the American University of Beirut Medical Center for funding the histological aspect of the study.
Conceived and designed the experiments: LY NF MES. Performed the experiments: LY FB NF. Analyzed the data: LY FB NF MES ZM. Contributed reagents/materials/analysis tools: FB ZM NF MES. Wrote the paper: LY FB MJ NF.
- 1. Hockel M, Schlenger K, Aral B, Mitze M, Schaffer U, Vaupel P (1996) Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. Cancer Res 56: 4509–4515. pmid:8813149
- 2. Hockel M, Schlenger K, Hockel S, Aral B, Schaffer U, Vaupel P (1998) Tumor hypoxia in pelvic recurrences of cervical cancer. Int J Cancer 79: 365–369. pmid:9699528
- 3. Brizel DM, Scully SP, Harrelson JM, Layfield LJ, Bean JM, Prosnitz LR, et al. (1996) Tumor oxygenation predicts for the likelihood of distant metastases in human soft tissue sarcoma. Cancer Res 56: 941–943. pmid:8640781
- 4. Semenza GL (2000) HIF-1: using two hands to flip the angiogenic switch. Cancer Metastasis Rev 19: 59–65. pmid:11191064
- 5. Bos R, van Diest PJ, de Jong JS, van der Groep P, van der Valk P, van der Wall E, et al. (2005) Hypoxia-inducible factor-1alpha is associated with angiogenesis, and expression of bFGF, PDGF-BB, and EGFR in invasive breast cancer. Histopathology 46: 31–36. pmid:15656883
- 6. Wong CC, Gilkes DM, Zhang H, Chen J, Wei H, Chaturvedi P, et al. (2011) Hypoxia-inducible factor 1 is a master regulator of breast cancer metastatic niche formation. Proc Natl Acad Sci U S A 108: 16369–16374. doi: 10.1073/pnas.1113483108. pmid:21911388
- 7. Mimeault M, Batra SK (2013) Hypoxia-inducing factors as master regulators of stemness properties and altered metabolism of cancer- and metastasis-initiating cells. J Cell Mol Med 17: 30–54. doi: 10.1111/jcmm.12004. pmid:23301832
- 8. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 98: 10869–10874. pmid:11553815
- 9. Turner NC, Reis-Filho JS (2006) Basal-like breast cancer and the BRCA1 phenotype. Oncogene 25: 5846–5853. pmid:16998499
- 10. van der Groep P, Bouter A, Menko FH, van der Wall E, van Diest PJ (2008) High frequency of HIF-1alpha overexpression in BRCA1 related breast cancer. Breast Cancer Res Treat 111: 475–480. pmid:18030615
- 11. Haffty BG, Yang Q, Reiss M, Kearney T, Higgins SA, Weidhaas J, et al. (2006) Locoregional relapse and distant metastasis in conservatively managed triple negative early-stage breast cancer. J Clin Oncol 24: 5652–5657. pmid:17116942
- 12. Harris LN, Broadwater G, Lin NU, Miron A, Schnitt SJ, Cowan D, et al. (2006) Molecular subtypes of breast cancer in relation to paclitaxel response and outcomes in women with metastatic disease: results from CALGB 9342. Breast Cancer Res 8: R66. pmid:17129383
- 13. Bauer KR, Brown M, Cress RD, Parise CA, Caggiano V (2007) Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California cancer Registry. Cancer 109: 1721–1728. pmid:17387718
- 14. Brown NS, Bicknell R (2001) Hypoxia and oxidative stress in breast cancer. Oxidative stress: its effects on the growth, metastatic potential and response to therapy of breast cancer. Breast Cancer Res 3: 323–327. pmid:11597322
- 15. Carey LA, Dees EC, Sawyer L, Gatti L, Moore DT, Collichio F, et al. (2007) The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res 13: 2329–2334. pmid:17438091
- 16. Dent R, Trudeau M, Pritchard KI, Hanna WM, Kahn HK, Sawka CA, et al. (2007) Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 13: 4429–4434. pmid:17671126
- 17. Morris GJ, Naidu S, Topham AK, Guiles F, Xu Y, MacCue P, et al. (2007) Differences in breast carcinoma characteristics in newly diagnosed African-American and Caucasian patients: a single-institution compilation compared with the National Cancer Institute's Surveillance, Epidemiology, and End Results database. Cancer 110: 876–884. pmid:17620276
- 18. Rakha EA, El-Sayed ME, Green AR, Lee AH, Robertson JF, Ellis IO (2007) Prognostic markers in triple-negative breast cancer. Cancer 109: 25–32. pmid:17146782
- 19. Tischkowitz M, Brunet JS, Begin LR, Huntsman DG, Cheang MC, et al. (2007) Use of immunohistochemical markers can refine prognosis in triple negative breast cancer. BMC Cancer 7: 134. pmid:17650314
- 20. Reis-Filho JS, Tutt AN (2008) Triple negative tumours: a critical review. Histopathology 52: 108–118. doi: 10.1111/j.1365-2559.2007.02889.x. pmid:18171422
- 21. Carvalho FM, Bacchi LM, Santos PP, Bacchi CE (2010) Triple-negative breast carcinomas are a heterogeneous entity that differs between young and old patients. Clinics (Sao Paulo) 65: 1033–1036. pmid:21120307
- 22. Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z, et al. (2004) Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 10: 5367–5374. pmid:15328174
- 23. Ishihara A, Tsuda H, Kitagawa K, Yoneda M, Shiraishi T (2009) Morphological characteristics of basal-like subtype of breast carcinoma with special reference to cytopathological features. Breast Cancer 16: 179–185. doi: 10.1007/s12282-009-0108-x. pmid:19466513
- 24. Tsuda H, Takarabe T, Hasegawa T, Murata T, Hirohashi S (1999) Myoepithelial differentiation in high-grade invasive ductal carcinomas with large central acellular zones. Hum Pathol 30: 1134–1139. pmid:10534158
- 25. Tsuda H, Takarabe T, Hasegawa F, Fukutomi T, Hirohashi S (2000) Large, central acellular zones indicating myoepithelial tumor differentiation in high-grade invasive ductal carcinomas as markers of predisposition to lung and brain metastases. Am J Surg Pathol 24: 197–202. pmid:10680887
- 26. Lakhani SR, Reis-Filho JS, Fulford L, Penault-Llorca F, van der Vijver M, Parry S, et al. (2005) Prediction of BRCA1 status in patients with breast cancer using estrogen receptor and basal phenotype. Clin Cancer Res 11: 5175–5180. pmid:16033833
- 27. Livasy CA, Karaca G, Nanda R, Tretiakova MS, Olopade OI, Moore DT, et al. (2006) Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol 19: 264–271. pmid:16341146
- 28. Fulford LG, Easton DF, Reis-Filho JS, Sofronis A, Gillett CE, Lakhani SR, et al. (2006) Specific morphological features predictive for the basal phenotype in grade 3 invasive ductal carcinoma of breast. Histopathology 49: 22–34. pmid:16842243
- 29. Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, et al. (2010) American Society of Clinical Oncology/College Of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol 28: 2784–2795. doi: 10.1200/JCO.2009.25.6529. pmid:20404251
- 30. Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, et al. (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 25: 118–145. pmid:17159189
- 31. Bos R, van der Groep P, Greijer AE, Shvarts A, Meijer S, Pinedo HM, et al. (2003) Levels of hypoxia-inducible factor-1alpha independently predict prognosis in patients with lymph node negative breast carcinoma. Cancer 97: 1573–1581. pmid:12627523
- 32. Mouawad R, Spano JP, Comperat E, Capron F, Khayat D (2009) Tumoural expression and circulating level of VEGFR-3 (Flt-4) in metastatic melanoma patients: correlation with clinical parameters and outcome. Eur J Cancer 45: 1407–1414. doi: 10.1016/j.ejca.2008.12.015. pmid:19157860
- 33. dos Santos M, Mercante AM, Louro ID, Goncalves AJ, de Carvalho MB, da Silva EH, et al. (2012) HIF1-alpha expression predicts survival of patients with squamous cell carcinoma of the oral cavity. PLoS One 7: e45228. doi: 10.1371/journal.pone.0045228. pmid:23028863
- 34. Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19: 403–410. pmid:1757079
- 35. De Francesco EM, Lappano R, Santolla MF, Marsico S, Caruso A, Magiolini M (2013) HIF-1alpha/GPER signaling mediates the expression of VEGF induced by hypoxia in breast cancer associated fibroblasts (CAFs). Breast Cancer Res 15: R64. pmid:23947803
- 36. Huang LE, Gu J, Schau M, Bunn HF (1998) Regulation of hypoxia-inducible factor 1alpha is mediated by an O2-dependent degradation domain via the ubiquitin-proteasome pathway. Proc Natl Acad Sci U S A 95: 7987–7992. pmid:9653127
- 37. Forsythe JA, Jiang BH, Iyer NV, Agani F, Leung SW, Koos RD, et al. (1996) Activation of vascular endothelial growth factor gene transcription by hypoxia-inducible factor 1. Mol Cell Biol 16: 4604–4613. pmid:8756616
- 38. Chappuis PO, Nethercot V, Foulkes WD (2000) Clinico-pathological characteristics of BRCA1- and BRCA2-related breast cancer. Semin Surg Oncol 18: 287–295. pmid:10805950
- 39. Yan M, Rayoo M, Takano EA, Investigators KC, Fox SB (2009) BRCA1 tumours correlate with a HIF-1alpha phenotype and have a poor prognosis through modulation of hydroxylase enzyme profile expression. Br J Cancer 101: 1168–1174. doi: 10.1038/sj.bjc.6605287. pmid:19724277
- 40. Tan EY, Yan M, Campo L, Han C, Takano E, Turley H, et al. (2009) The key hypoxia regulated gene CAIX is upregulated in basal-like breast tumours and is associated with resistance to chemotherapy. Br J Cancer 100: 405–411. doi: 10.1038/sj.bjc.6604844. pmid:19165203
- 41. Choi J, Jung WH, Koo JS (2013) Metabolism-related proteins are differentially expressed according to the molecular subtype of invasive breast cancer defined by surrogate immunohistochemistry. Pathobiology 80: 41–52. doi: 10.1159/000339513. pmid:22832328
- 42. Toikkanen S, Helin H, Isola J, Joensuu H (1992) Prognostic significance of HER-2 oncoprotein expression in breast cancer: a 30-year follow-up. J Clin Oncol 10: 1044–1048. pmid:1351537
- 43. Giatromanolaki A, Koukourakis MI, Simopoulos C, Polychronidis A, Gatter KC, Harris AL, et al. (2004) c-erbB-2 related aggressiveness in breast cancer is hypoxia inducible factor-1alpha dependent. Clin Cancer Res 10: 7972–7977. pmid:15585632
- 44. Laughner E, Taghavi P, Chiles K, Mahon PC, Semenza GL (2001) HER2 (neu) signaling increases the rate of hypoxia-inducible factor 1alpha (HIF-1alpha) synthesis: novel mechanism for HIF-1-mediated vascular endothelial growth factor expression. Mol Cell Biol 21: 3995–4004. pmid:11359907
- 45. Konecny GE, Meng YG, Untch M, Wang HJ, Bauerfeind I, Epstein M, et al. (2004) Association between HER-2/neu and vascular endothelial growth factor expression predicts clinical outcome in primary breast cancer patients. Clin Cancer Res 10: 1706–1716. pmid:15014023
- 46. Whelan KA, Schwab LP, Karakashev SV, Franchetti L, Johannes GJ, Seagroves TN, et al. (2013) The oncogene HER2/neu (ERBB2) requires the hypoxia-inducible factor HIF-1 for mammary tumor growth and anoikis resistance. J Biol Chem 288: 15865–15877. doi: 10.1074/jbc.M112.426999. pmid:23585570
- 47. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, et al. (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A 100: 10393–10398. pmid:12917485
- 48. Bos R, Zhong H, Hanrahan CF, Mommers EC, Semenza GL, Pinedo HM, et al. (2001) Levels of hypoxia-inducible factor-1 alpha during breast carcinogenesis. J Natl Cancer Inst 93: 309–314. pmid:11181778
- 49. Kurebayashi J, Otsuki T, Moriya T, Sonoo H (2001) Hypoxia reduces hormone responsiveness of human breast cancer cells. Jpn J Cancer Res 92: 1093–1101. pmid:11676860
- 50. Stoner M, Saville B, Wormke M, Dean D, Burghardt R, Safe S (2002) Hypoxia induces proteasome-dependent degradation of estrogen receptor alpha in ZR-75 breast cancer cells. Mol Endocrinol 16: 2231–2242. pmid:12351689
- 51. Kronblad A, Hedenfalk I, Nilsson E, Pahlman S, Landberg G (2005) ERK1/2 inhibition increases antiestrogen treatment efficacy by interfering with hypoxia-induced downregulation of ERalpha: a combination therapy potentially targeting hypoxic and dormant tumor cells. Oncogene 24: 6835–6841. pmid:16007158
- 52. Tredan O, Galmarini CM, Patel K, Tannock IF (2007) Drug resistance and the solid tumor microenvironment. J Natl Cancer Inst 99: 1441–1454. pmid:17895480
- 53. Yamamoto Y, Ibusuki M, Okumura Y, Kawasoe T, Kai K, Iyama K, et al. (2008) Hypoxia-inducible factor 1alpha is closely linked to an aggressive phenotype in breast cancer. Breast Cancer Res Treat 110: 465–475. pmid:17805961
- 54. Cho J, Bahn JJ, Park M, Ahn W, Lee YJ (2006) Hypoxic activation of unoccupied estrogen-receptor-alpha is mediated by hypoxia-inducible factor-1 alpha. J Steroid Biochem Mol Biol 100: 18–23. pmid:16797973
- 55. Uzzan B, Nicolas P, Cucherat M, Perret GY (2004) Microvessel density as a prognostic factor in women with breast cancer: a systematic review of the literature and meta-analysis. Cancer Res 64: 2941–2955. pmid:15126324
- 56. Xia Y, Choi HK, Lee K (2012) Recent advances in hypoxia-inducible factor (HIF)-1 inhibitors. Eur J Med Chem 49: 24–40. doi: 10.1016/j.ejmech.2012.01.033. pmid:22305612
- 57. http://clinicaltrials.gov/ct2/show/NCT01763931?term=%22breast+cancer%22+AND+%22HIF%22&rank=1. DIG-HIF1 Pharmacodynamic Trial in Newly Diagnosed Operable Breast Cancer.
- 58. Onitilo AA, Engel JM, Greenlee RT, Mukesh BN (2009) Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival. Clin Med Res 7: 4–13. doi: 10.3121/cmr.2009.825. pmid:19574486