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1.  An International Ki67 Reproducibility Study 
Background
In breast cancer, immunohistochemical assessment of proliferation using the marker Ki67 has potential use in both research and clinical management. However, lack of consistency across laboratories has limited Ki67’s value. A working group was assembled to devise a strategy to harmonize Ki67 analysis and increase scoring concordance. Toward that goal, we conducted a Ki67 reproducibility study.
Methods
Eight laboratories received 100 breast cancer cases arranged into 1-mm core tissue microarrays—one set stained by the participating laboratory and one set stained by the central laboratory, both using antibody MIB-1. Each laboratory scored Ki67 as percentage of positively stained invasive tumor cells using its own method. Six laboratories repeated scoring of 50 locally stained cases on 3 different days. Sources of variation were analyzed using random effects models with log2-transformed measurements. Reproducibility was quantified by intraclass correlation coefficient (ICC), and the approximate two-sided 95% confidence intervals (CIs) for the true intraclass correlation coefficients in these experiments were provided.
Results
Intralaboratory reproducibility was high (ICC = 0.94; 95% CI = 0.93 to 0.97). Interlaboratory reproducibility was only moderate (central staining: ICC = 0.71, 95% CI = 0.47 to 0.78; local staining: ICC = 0.59, 95% CI = 0.37 to 0.68). Geometric mean of Ki67 values for each laboratory across the 100 cases ranged 7.1% to 23.9% with central staining and 6.1% to 30.1% with local staining. Factors contributing to interlaboratory discordance included tumor region selection, counting method, and subjective assessment of staining positivity. Formal counting methods gave more consistent results than visual estimation.
Conclusions
Substantial variability in Ki67 scoring was observed among some of the world’s most experienced laboratories. Ki67 values and cutoffs for clinical decision-making cannot be transferred between laboratories without standardizing scoring methodology because analytical validity is limited.
doi:10.1093/jnci/djt306
PMCID: PMC3888090  PMID: 24203987
2.  Prognostic significance of FOXP3+ tumor-infiltrating lymphocytes in breast cancer depends on estrogen receptor and human epidermal growth factor receptor-2 expression status and concurrent cytotoxic T-cell infiltration 
Introduction
The infiltration of FOXP3+ regulatory T cells into invasive tumors has been reported to be associated with survival in a variety of cancers. The prognostic significance of FOXP3+ tumor-infiltrating lymphocytes (TILs) in breast cancer, however, remains controversial.
Methods
FOXP3+ TILs were assessed by immunohistochemistry on tissue microarrays constructed from a well-defined cohort of 3,992 breast cancer patients linked to detailed demographic, biomarker, treatment and outcome data. Survival analyses were performed using the Kaplan-Meier function and Cox proportional hazards regression models to evaluate the association of FOXP3+ TILs with breast cancer-specific survival, stratified by intrinsic subtype and cytotoxic T-cell infiltration status (as defined by CD8 immunohistochemistry).
Results
The presence of high numbers of FOXP3+ TILs was significantly associated with young age, high grade, estrogen receptor (ER) negativity, concurrent CD8+ cytotoxic T-cell infiltration, and human epidermal growth factor receptor-2 positive (HER2+)/ER− and core basal subtypes. On multivariate survival analysis, a high level of FOXP3+ TILs was significantly associated with poor survival in ER+ breast cancers that lacked CD8+ T-cell infiltrates (hazard ratio (HR) = 1.30, 95% confidence interval (CI) = 1.02 to 1.66). However, in ER− breast cancers, FOXP3+ TILs were strongly associated with improved survival in the HER2+/ER− subgroup, particularly in those with co-existent CD8+ T-cell infiltrates (HR = 0.48, 95% CI = 0.23 to 0.98), for which the presence of high levels of FOXP3+ TILs was independent of standard clinical prognostic factors.
Conclusions
FOXP3+ regulatory TILs are a poor prognostic indicator in ER+ breast cancer, but a favorable prognostic factor in the HER2+/ER− subtype. The prognostic value of FOXP3+ TILs in breast cancer differs depending on ER and HER2 expression status and CD8+ T-cell infiltration.
Electronic supplementary material
The online version of this article (doi:10.1186/s13058-014-0432-8) contains supplementary material, which is available to authorized users.
doi:10.1186/s13058-014-0432-8
PMCID: PMC4303113  PMID: 25193543
3.  A functional proteogenomic analysis of endometrioid and clear cell carcinomas using reverse phase protein array and mutation analysis: protein expression is histotype-specific and loss of ARID1A/BAF250a is associated with AKT phosphorylation 
BMC Cancer  2014;14:120.
Background
Ovarian cancer is now recognized as a number of distinct diseases primarily defined by histological subtype. Both clear cell ovarian carcinomas (CCC) and ovarian endometrioid carcinomas (EC) may arise from endometriosis and frequently harbor mutations in the ARID1A tumor suppressor gene. We studied the influence of histological subtype on protein expression with reverse phase protein array (RPPA) and assessed proteomic changes associated with ARID1A mutation/BAF250a expression in EC and CCC.
Methods
Immunohistochemistry (IHC) for BAF250a expression was performed on 127 chemotherapy-naive ovarian carcinomas (33 CCC, 29 EC, and 65 high-grade serous ovarian carcinomas (HGSC)). Whole tumor lysates were prepared from frozen banked tumor samples and profiled by RPPA using 116 antibodies. ARID1A mutations were identified by exome sequencing, and PIK3CA mutations were characterized by MALDI-TOF mass spectrometry. SAM (Significance Analysis of Microarrays) was performed to determine differential protein expression by histological subtype and ARID1A mutation status. Multivariate logistic regression was used to assess the impact of ARID1A mutation status/BAF250a expression on AKT phosphorylation (pAKT). PIK3CA mutation type and PTEN expression were included in the model. BAF250a knockdown was performed in 3 clear cell lines using siRNA to ARID1A.
Results
Marked differences in protein expression were observed that are driven by histotype. Compared to HGSC, SAM identified over 50 proteins that are differentially expressed in CCC and EC. These included PI3K/AKT pathway proteins, those regulating the cell cycle, apoptosis, transcription, and other signaling pathways including steroid hormone signaling. Multivariate models showed that tumors with loss of BAF250a expression showed significantly higher levels of AKT-Thr308 and AKT-Ser473 phosphorylation (p < 0.05). In 31 CCC cases, pAKT was similarly significantly increased in tumors with BAF250a loss on IHC. Knockdown of BAF250a by siRNA in three CCC cell lines wild type for ARID1A showed no increase in either pAKT-Thr308 or pAKT-S473 suggesting that pAKT in tumor tissues is indirectly regulated by BAF250a expression.
Conclusions
Proteomic assessment of CCC and EC demonstrates remarkable differences in protein expression that are dependent on histotype, thereby further characterizing these cancers. AKT phosphorylation is associated with ARID1A/BAF250a deficient tumors, however in ovarian cancers the mechanism remains to be elucidated.
doi:10.1186/1471-2407-14-120
PMCID: PMC3941949  PMID: 24559118
Ovarian cancer; Proteomics; ARID1A/BAF250a; PIK3CA mutation; AKT; Phosphorylation
4.  Cyclin D1 as a diagnostic immunomarker for endometrial stromal sarcoma with YWHAE-FAM22 rearrangement 
Endometrial stromal sarcoma (ESS) characterized by YWHAE-FAM22 genetic fusion is histologically higher-grade and clinically more aggressive than ESS with JAZF1-SUZ12 or equivalent genetic rearrangements, hence it is clinically important to recognize this subset of ESS. To identify diagnostic immunomarkers for this biologically-defined ESS subset, we compared gene expression profiles from YWHAE-FAM22 ESS, JAZF1-rearranged ESS and uterine leiomyosarcomas. These studies showed consistent upregulation of cyclin D1 in YWHAE-FAM22 ESS compared to JAZF1-SUZ12 ESS. Immunohistochemically, the high-grade round cell component of all 12 YWHAE-FAM22 ESS demonstrated diffuse (≥70%) moderate-to-strong nuclear cyclin D1 staining and this diffuse positivity was not seen in 34 ESS with JAZF1 and equivalent genetic rearrangements or in 21 low-grade ESS with no demonstrable genetic rearrangements. In a series of 243 non-ESS pure uterine mesenchymal and mixed epithelial-mesenchymal tumors, only 2 of 8 undifferentiated endometrial sarcomas with nuclear uniformity and 1 of 80 uterine leiomyosarcomas demonstrate diffuse cyclin D1 immunoreactivity. Both cyclin D1-positive undifferentiated endometrial sarcomas showed diffuse strong CD10 staining, which is consistently absent in the high-grade round cell component of YWHAE-FAM22 ESS. The low-grade spindle cell component of YWHAE-FAM22 ESS showed a spatially heterogeneous cyclin D1 staining pattern that was weaker and less diffuse overall. Our findings indicate that cyclin D1 is a sensitive and specific diagnostic immunomarker for YWHAE-FAM22 ESS. When evaluating high-grade uterine sarcomas, cyclin D1 can be included in the immunohistochemical panel as an indicator of YWHAE-FAM22 ESS.
doi:10.1097/PAS.0b013e31825fa931
PMCID: PMC3444748  PMID: 22982899
Endometrial stromal sarcoma; round cell; YWHAE-FAM22; cyclin D1; JAZF1-SUZ12
5.  Effect of continuous statistically standardized measures of estrogen and progesterone receptors on disease-free survival in NCIC CTG MA.12 Trial and BC Cohort 
Introduction
We hypothesized improved inter-laboratory comparability of estrogen receptor (ER) and progesterone receptor (PgR) across different assay methodologies with adjunctive statistical standardization, akin to bone mineral density (BMD) z-scores. We examined statistical standardization in MA.12, a placebo-controlled pre-menopausal trial of adjuvant tamoxifen with locally assessed hormone receptor +/- tumours, and in a cohort of post-menopausal British Columbia (BC) tamoxifen-treated patients.
Methods
ER and PgR were centrally assessed for both patient groups with real time quantitative reverse transcription polymerase chain reaction (qPCR) and immunohistochemistry (IHC). Effects on disease-free survival (DFS) were investigated separately for 345 MA.12 and 673 BC patients who had both qPCR and IHC assessments. Comparisons utilized continuous laboratory units and statistically standardized z-scores. Univariate categorization of ER/PgR was by number of standard deviations (SD) above or below the mean (z-score ≥1.0 SD below mean; z-score <1.0 SD below mean; z-score ≤1.0 SD above mean; z-score >1.0 SD above mean). Exploratory multivariate examinations utilized step-wise Cox regression.
Results
Median follow-up for MA.12 was 9.7 years; for BC patients, 11.8 years. For MA.12, 101 of 345 (29%) patients were IHC ER-PgR-. ER was not univariately associated with DFS (qPCR, P = 0.19; IHC, P = 0.08), while PgR was (qPCR, P = 0.09; IHC, P = 0.04). For BC patients, neither receptor was univariately associated with DFS: for ER, PCR, P = 0.36, IHC, P = 0.24; while for PgR, qPCR, P = 0.17, IHC, P = 0.31. Multivariately, MA.12 patients randomized to tamoxifen had significantly better DFS (P = 0.002 to 0.005) than placebo. Meanwhile, jointly ER and PgR were not associated with DFS whether assessed by qPCR or by IHC in all patients, or in the subgroup of patients with IHC positive stain, for pooled or separate treatment arms. Different results by type of continuous unit supported the concept of ER level being relevant for medical decision-making. For postmenopausal BC tamoxifen patients, higher qPCR PgR was weakly associated with better DFS (P = 0.06).
Conclusions
MA.12 pre-menopausal patients in a placebo-controlled tamoxifen trial had similar multivariate prognostic effects with statistically standardized hormone receptors when tumours were assayed by qPCR or IHC, for hormone receptor +/- and + tumours. The BC post-menopausal tamoxifen cohort did not exhibit a significant prognostic association of ER or PgR with DFS. Adjunctive statistical standardization is currently under investigation in other NCIC CTG endocrine trials.
doi:10.1186/bcr3465
PMCID: PMC3978444  PMID: 23972025
6.  Responsiveness of Intrinsic Subtypes to Adjuvant Anthracycline Substitution in the NCIC.CTG MA.5 Randomized Trial 
Purpose
Recent studies suggest that intrinsic breast cancer subtypes may differ in their responsiveness to specific chemotherapy regimens. We examined this hypothesis on NCIC.CTG MA.5, a clinical trial randomizing premenopausal women with node-positive breast cancer to adjuvant CMF (cyclophosphamide-methotrexate-fluorouracil) versus CEF (cyclophosphamide-epirubicin-fluorouracil) chemotherapy.
Experimental Design
Intrinsic subtype was determined for 476 tumors using the quantitative reverse transcriptase PCR PAM50 gene expression test. Luminal A, luminal B, HER2-enriched (HER2-E), and basal-like subtypes were correlated with relapse-free survival (RFS) and overall survival (OS), estimated using Kaplan-Meier plots and log-rank testing. Multivariable Cox regression analyses determined significance of interaction between treatment and intrinsic subtypes.
Results
Intrinsic subtypes were associated with RFS (P = 0005) and OS (P < 0.0001) on the combined cohort. The HER2-E showed the greatest benefit from CEF versus CMF, with absolute 5-year RFS and OS differences exceeding 20%, whereas there was a less than 2% difference for non-HER2-E tumors (interaction test P = 0.03 for RFS and 0.03 for OS). Within clinically defined Her2+ tumors, 79% (72 of 91) were classified as the HER2-E subtype by gene expression and this subset was strongly associated with better response to CEF versus CMF (62% vs. 22%, P = 0.0006). There was no significant difference in benefit between CEF and CMF in basal-like tumors [n = 94; HR, 1.1; 95% confidence interval (CI), 0.6−.1 for RFS and HR, 1.3; 95% CI, 0.7−2.5 for OS].
Conclusion
HER2-E strongly predicted anthracycline sensitivity. The chemotherapy-sensitive basal- like tumors showed no added benefit for CEF over CMF, suggesting that nonanthracycline regimens may be adequate in this subtype although further investigation is required.
doi:10.1158/1078-0432.CCR-11-2956
PMCID: PMC3743660  PMID: 22351696
7.  A 50-Gene Intrinsic Subtype Classifier for Prognosis and Prediction of Benefit from Adjuvant Tamoxifen 
Purpose
Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry.
Experimental Design
Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2–enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes.
Results
Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32–0.86 vs. HR, 0.80; 95% CI, 0.50–1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease.
Conclusions
In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen.
doi:10.1158/1078-0432.CCR-12-0286
PMCID: PMC3743663  PMID: 22711706
8.  CD8+ lymphocyte infiltration is an independent favorable prognostic indicator in basal-like breast cancer 
Introduction
Tumor infiltrating lymphocytes may indicate an immune response to cancer development, but their significance remains controversial in breast cancer. We conducted this study to assess CD8+ (cytotoxic T) lymphocyte infiltration in a large cohort of invasive early stage breast cancers, and to evaluate its prognostic effect in different breast cancer intrinsic subtypes.
Methods
Immunohistochemistry for CD8 staining was performed on tissue microarrays from 3992 breast cancer patients. CD8+ tumor infiltrating lymphocytes were counted as intratumoral when in direct contact with tumor cells, and as stromal in adjacent locations. Kaplan-Meier functions and Cox proportional hazards regression models were applied to examine the associations between tumor infiltrating lymphocytes and breast cancer specific survival.
Results
Among 3403 cases for which immunohistochemical results were obtained, CD8+ tumor infiltrating lymphocytes were identified in an intratumoral pattern in 32% and stromal pattern in 61% of the cases. In the whole cohort, the presence of intratumoral tumor-infiltrating lymphocytes was significantly correlated with young age, high grade, estrogen receptor negativity, human epidermal growth factor receptor-2 positivity and core basal intrinsic subtype, and was associated with superior breast cancer specific survival. Multivariate analysis indicated that the favorable prognostic effect of CD8+ tumor infiltrating lymphocytes was significant only in the core basal intrinsic subgroup (Hazard ratio, HR = 0.35, 95% CI = 0.23-0.54). No association with improved survival was present in those triple negative breast cancers that lack expression of basal markers (HR = 0.99, 95% CI = 0.48-2.04) nor in the other intrinsic subtypes.
Conclusions
CD8+ tumor infiltrating lymphocytes are an independent prognostic factor associated with better patient survival in basal-like breast cancer, but not in non-basal triple negative breast cancers nor in other intrinsic molecular subtypes.
doi:10.1186/bcr3148
PMCID: PMC3446382  PMID: 22420471
9.  A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor positive breast cancer 
Purpose
To compare clinical, immunohistochemical and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor positive breast cancers, from patients uniformly treated with adjuvant tamoxifen.
Methods
qRT-PCR assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median followup 11.7 years) and immunohistochemical (ER, PR, HER2, Ki67) data. Performance of predefined intrinsic subtype and Risk-Of-Relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell’s C index was used to compare fixed models trained in independent data sets, including proliferation signatures.
Results
Despite clinical ER positivity, 10% of cases were assigned to non-Luminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease specific survival over the first 5 years of followup, relative to the most common Luminal A subtype, are 1.99 (95% CI: 1.09–3.64) for Luminal B, 3.65 (1.64–8.16) for HER2-enriched and 17.71 (1.71–183.33) for the basal like subtype. For node-negative disease, PAM50 qRT-PCR based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10 yr survival without chemotherapy. In node positive disease, PAM50-based prognostic models were also superior.
Conclusion
The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and immunohistochemistry using standard cutpoints.
doi:10.1158/1078-0432.CCR-10-1282
PMCID: PMC2970720  PMID: 20837693
11.  Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes 
Journal of Clinical Oncology  2009;27(8):1160-1167.
Purpose
To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression–based “intrinsic” subtypes luminal A, luminal B, HER2-enriched, and basal-like.
Methods
A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen.
Results
The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%.
Conclusion
Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.
doi:10.1200/JCO.2008.18.1370
PMCID: PMC2667820  PMID: 19204204
12.  Type I gamma phosphatidylinositol phosphate kinase modulates invasion and proliferation and its expression correlates with poor prognosis in breast cancer 
Introduction
The loss of E-cadherin based cell-cell contacts and tumor cell migration to the vasculature and lymphatic system are hallmarks of metastasis of epithelial cancers. Type I gamma phosphatidylinositol phosphate kinase (PIPKIγ), an enzyme that generates phosphatidylinositol 4,5-bisphosphate (PI4,5P2) a lipid messenger and precursor to many additional second messengers, was found to regulate E-cadherin cell-cell contacts and growth factor-stimulated directional cell migration, indicating that PIPKIγ regulates key steps in metastasis. Here, we assess the expression of PIPKIγ in breast cancers and have shown that expression correlated with disease progression and outcome.
Methods
Using a tissue microarray, we analyzed 438 breast carcinomas for the levels of PIPKIγ and investigated the correlation of PIPKIγ expression with patient survival via Kaplan-Meier survival analysis. Moreover, via knockdown of the expression of PIPKIγ in cultured breast cancer cells with siRNA, the roles of PIPKIγ in breast cancer migration, invasion, and proliferation were examined.
Results
Tissue microarray data shows that ~18% of the cohort immunostained showed high expression of PIPKIγ. The Kaplan-Meier survival analysis revealed a significant inverse correlation between strong PIPKIγ expression and overall patient survival. Expression of PIPKIγ correlated positively with epidermal growth factor receptor (EGFR) expression, which regulates breast cancer progression and metastasis. In cultured breast cancer cells, PIPKIγ is required for growth factor stimulated migration, invasion, and proliferation of cells.
Conclusions
The results reveal a significant correlation between PIPKIγ expression and the progression of breast cancer. This is consistent with PIPKIγ 's role in breast cancer cell migration, invasion, and proliferation.
doi:10.1186/bcr2471
PMCID: PMC2880426  PMID: 20074374
13.  Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis 
BMC Cancer  2009;9:165.
Background
In breast cancer patients, HER2 overexpression is routinely assessed by immunohistochemistry (IHC) and equivocal cases are subject to fluorescent in situ hybridization (FISH). Our study compares HER2 scoring by histopathologists with automated quantitation of staining, and determines the concordance of IHC scores with FISH results.
Methods
A tissue microarray was constructed from 1,212 invasive breast carcinoma cases with linked treatment and outcome information. IHC slides were semi-quantitatively scored by two independent pathologists on a range of 0 to 3+, and also analyzed with an Ariol automated system by two operators. 616 cases were scorable by both IHC and FISH.
Results
Using data from unequivocal positive (3+) or negative (0, 1+) results, both visual and automated scores were highly consistent: there was excellent concordance between two pathologists (kappa = 1.000, 95% CI: 1-1), between two machines (kappa = 1.000, 95% CI: 1-1), and between both visual and both machine scores (kappa = 0.898, 95% CI: 0.775–0.979). Two pathologists successfully distinguished negative, positive and equivocal cases (kappa = 0.929, 95% CI: 0.909–0.946), with excellent agreement with machine 1 scores (kappa = 0.835, 95% CI: 0.806–0.862; kappa = 0.837, 95% CI: 0.81–0.862), and good agreement with machine 2 scores (kappa = 0.698, 95% CI: 0.6723–0.723; kappa = 0.709, 95% CI: 0.684–0.732), whereas the two machines showed good agreement (kappa = 0.806, 95% CI: 0.785–0.826). When comparing categorized IHC scores and FISH results, the agreement was excellent for visual 1 (kappa = 0.814, 95% CI: 0.768–0.856), good for visual 2 (kappa = 0.763, 95% CI: 0.712–0.81) and machine 1 (kappa = 0.665, 95% CI: 0.609–0.718), and moderate for machine 2 (kappa = 0.535, 95% CI: 0.485–0.584).
Conclusion
A fully automated image analysis system run by an experienced operator can provide results consistent with visual HER2 scoring. Further development of such systems will likely improve the accuracy of detection and categorization of membranous staining, making this technique suitable for use in quality assurance programs and eventually in clinical practice.
doi:10.1186/1471-2407-9-165
PMCID: PMC2698924  PMID: 19476653
14.  Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer 
Background
Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival.
Methods
Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan–Meier curves and multivariable Cox regression.
Results
Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor–positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal–HER2 positive. Luminal B and luminal–HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer–specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal–HER2 subtypes.
Conclusion
Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.
doi:10.1093/jnci/djp082
PMCID: PMC2684553  PMID: 19436038
15.  Ovarian Carcinoma Subtypes Are Different Diseases: Implications for Biomarker Studies 
PLoS Medicine  2008;5(12):e232.
Background
Although it has long been appreciated that ovarian carcinoma subtypes (serous, clear cell, endometrioid, and mucinous) are associated with different natural histories, most ovarian carcinoma biomarker studies and current treatment protocols for women with this disease are not subtype specific. With the emergence of high-throughput molecular techniques, distinct pathogenetic pathways have been identified in these subtypes. We examined variation in biomarker expression rates between subtypes, and how this influences correlations between biomarker expression and stage at diagnosis or prognosis.
Methods and Findings
In this retrospective study we assessed the protein expression of 21 candidate tissue-based biomarkers (CA125, CRABP-II, EpCam, ER, F-Spondin, HE4, IGF2, K-Cadherin, Ki-67, KISS1, Matriptase, Mesothelin, MIF, MMP7, p21, p53, PAX8, PR, SLPI, TROP2, WT1) in a population-based cohort of 500 ovarian carcinomas that was collected over the period from 1984 to 2000. The expression of 20 of the 21 biomarkers differs significantly between subtypes, but does not vary across stage within each subtype. Survival analyses show that nine of the 21 biomarkers are prognostic indicators in the entire cohort but when analyzed by subtype only three remain prognostic indicators in the high-grade serous and none in the clear cell subtype. For example, tumor proliferation, as assessed by Ki-67 staining, varies markedly between different subtypes and is an unfavourable prognostic marker in the entire cohort (risk ratio [RR] 1.7, 95% confidence interval [CI] 1.2%–2.4%) but is not of prognostic significance within any subtype. Prognostic associations can even show an inverse correlation within the entire cohort, when compared to a specific subtype. For example, WT1 is more frequently expressed in high-grade serous carcinomas, an aggressive subtype, and is an unfavourable prognostic marker within the entire cohort of ovarian carcinomas (RR 1.7, 95% CI 1.2%–2.3%), but is a favourable prognostic marker within the high-grade serous subtype (RR 0.5, 95% CI 0.3%–0.8%).
Conclusions
The association of biomarker expression with survival varies substantially between subtypes, and can easily be overlooked in whole cohort analyses. To avoid this effect, each subtype within a cohort should be analyzed discretely. Ovarian carcinoma subtypes are different diseases, and these differences should be reflected in clinical research study design and ultimately in the management of ovarian carcinoma.
David Huntsman and colleagues describe the associations between biomarker expression patterns and survival in different ovarian cancer subtypes. They suggest that the management of ovarian cancer should reflect differences between these subtypes.
Editors' Summary
Background.
Every year, about 200,000 women develop ovarian cancer and more than 100,000 die from the disease. Ovarian epithelial cancer (carcinoma) occurs when epithelial cells from the ovary or fallopian tube acquire mutations or equivalent changes that allow them to grow uncontrollably within one of the ovaries (two small organs in the pelvis that produce eggs) and acquire the potential to spread around the body (metastasize). While the cancer is confined to the ovaries, cancer specialists call this stage I disease; 70%–80% of women diagnosed with stage I ovarian cancer survive for at least 5 y. However, only a fifth of ovarian cancers are diagnosed at this stage; in the majority of patients the cancer has spread into the pelvis (stage II disease), into the peritoneal cavity (the space around the gut, stomach, and liver; stage III disease), or metastasized to distant organs such as brain (stage IV disease). This peritoneal spread might be associated with often only vague abdominal pain and mild digestive disturbances. Patients with advanced-stage ovarian carcinoma are treated with a combination of surgery and chemotherapy but, despite recent advances in treatment, only 15% of women diagnosed with stage IV disease survive for 5 y.
Why Was This Study Done?
Although it is usually regarded as a single disease, there are actually several distinct subtypes of ovarian carcinoma. These are classified according to their microscopic appearance as high-grade serous, low-grade serous, clear cell, endometrioid, and mucinous ovarian carcinomas. These subtypes develop differently and respond differently to chemotherapy. Yet scientists studying ovarian carcinoma usually regard this cancer as a single entity, and current treatment protocols for the disease are not subtype specific. Might better progress be made toward understanding ovarian carcinoma and toward improving its treatment if each subtype were treated as a separate disease? Why are some tumors confined to the ovary, whereas the majority spread beyond the ovary at time of diagnosis? In this study, the researchers address these questions by asking whether correlations between the expression of “biomarkers” (molecules made by cancer cells that can be used to detect tumors and to monitor treatment effectiveness) and the stage at diagnosis or length of survival can be explained by differential biomarker expression between different subtypes of ovarian carcinoma. They also address the question of whether early stage and late stage ovarian carcinomas are fundamentally different.
What Did the Researchers Do and Find?
The researchers measured the expression of 21 candidate protein biomarkers in 500 ovarian carcinoma samples collected in British Columbia, Canada, between 1984 and 2000. For 20 of the biomarkers, the fraction of tumors expressing the biomarker varied significantly between ovarian carcinoma subtypes. Considering all the tumors together, ten biomarkers had different expression levels in early and late stage tumors. However, when each subtype was considered separately, the expression of none of the biomarkers varied with stage. When the researchers asked whether the expression of any of the biomarkers correlated with survival times, they found that nine biomarkers were unfavorable indicators of outcome when all the tumors were considered together. That is, women whose tumors expressed any of these biomarkers had a higher risk of dying from ovarian cancer than women whose tumors did not express these biomarkers. However, only three biomarkers were unfavorable indicators for high-grade serous carcinomas considered alone and the expression of a biomarker called WT1 in this subtype of ovarian carcinoma is associated with a lower risk of dying. Similarly, expression of the biomarker Ki-67 was an unfavorable prognostic indicator when all the tumors were considered, but was not a prognostic indicator for any individual subtype.
What Do These Findings Mean?
These and other findings indicate that biomarker expression is more strongly associated with ovarian carcinoma subtype than with stage. In other words, biomarker expression is constant from early to late stage, but only within a given subtype. Second, the association of biomarker expression with survival varies between subtypes, hence lumping all subtypes together can yield misleading results. Although these findings need confirming in more tumor samples, they support the view that ovarian carcinoma subtypes are different diseases. In practical terms, therefore, these findings suggest that better ways to detect and treat ovarian cancer are more likely to be found if future biomarker studies and clinical research studies investigate each subtype of ovarian carcinoma separately rather than grouping them all together.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050232.
The US National Cancer Institute provides a brief description of what cancer is and how it develops and information on all aspects of ovarian cancer for patients and professionals. It also provides a fact sheet on tumor markers (in English and Spanish)
The UK charity Cancerbackup provides general information about cancer and more specific information about ovarian cancer, including tumor staging
doi:10.1371/journal.pmed.0050232
PMCID: PMC2592352  PMID: 19053170
16.  Redefining prognostic factors for breast cancer: YB-1 is a stronger predictor of relapse and disease-specific survival than estrogen receptor or HER-2 across all tumor subtypes 
Introduction
Gene expression analysis is used to subtype breast cancers such that the most aggressive tumors are identified, but translating this into clinical practice can be cumbersome. Our goal is to develop a universal biomarker that distinguishes patients at high risk across all breast cancer subtypes. We previously reported that Y-box binding protein-1 (YB-1), a transcription/translation factor, was a marker of poor prognosis in a cohort of 490 patients with breast cancer, but the study was not large enough to subtype the cancers. We therefore investigated whether YB-1 identifies patients at risk for either reduced relapse free survival or decreased r breast cancer specific survival (BCSS) across all tumor subtypes by evaluating 4,049 cases.
Methods
Tumor tissue microarrays, representing 4,049 cases of invasive breast cancers with 20 years of follow up, were subtyped by the expression profiles of estrogen receptor, progesterone receptor, or HER-2. We then addressed whether YB-1 expression identified patients at higher risk for relapse and/or lower BCSS.
Results
We found YB-1 to be a highly predictive biomarker of relapse (P < 2.5 × 10-20) and poor survival (P < 7.3 × 10-26) in the entire cohort and across all breast cancer subtypes. Patients with node-positive or node-negative cancer were more likely to die from the disease if YB-1 was expressed. This was further substantiated using a Cox regression model, which revealed that it was significantly associated with relapse and poor survival in a subtype independent manner (relapse patients, hazard ratio = 1.28, P < 8 × 10-3; all patients, hazard ratio = 1.45, P < 6.7 × 10-7). Moreover, YB-1 was superior to estrogen receptor and HER-2 as a prognostic marker for relapse and survival. For a subset of patients who were originally considered low risk and were therefore not given chemotherapy, YB-1 was indicative of poor survival (P < 7.1 × 10 -17). Likewise, YB-1 was predictive of decreased BCSS in tamoxifen-treated patients (P = 0.001); in this setting a Cox regression model once again demonstrated it to be an independent biomarker indicating poor survival (hazard ratio = 1.70, P = 0.022).
Conclusions
Expression of YB-1 universally identifies patients at high risk across all breast cancer subtypes and in situations where more aggressive treatment may be needed. We therefore propose that YB-1 may re-define high-risk breast cancer and thereby create opportunities for individualized therapy.
doi:10.1186/bcr2156
PMCID: PMC2614522  PMID: 18925950
17.  Can clinically relevant prognostic subsets of breast cancer patients with four or more involved axillary lymph nodes be identified through immunohistochemical biomarkers? A tissue microarray feasibility study 
Introduction
Primary breast cancer involving four or more axillary lymph nodes carries a poor prognosis. We hypothesized that use of an immunohistochemical biomarker scoring system could allow for identification of variable risk subgroups.
Methods
Patients with four or more positive axillary nodes were identified from a clinically annotated tissue microarray of formalin-fixed paraffin-embedded primary breast cancers and randomized into a 'test set' and a 'validation set'. A prospectively defined prognostic scoring model was developed in the test set and was further assessed in the validation set combining expression for eight biomarkers by immunohistochemistry, including estrogen receptor, human epidermal growth factor receptors 1 and 2, carbonic anhydrase IX, cytokeratin 5/6, progesterone receptor, p53 and Ki-67. Survival outcomes were analyzed by the Kaplan–Meier method, log rank tests and Cox proportional-hazards models.
Results
A total of 313 eligible patients were identified in the test set for whom 10-year relapse-free survival was 38.3% (SEM 2.9%), with complete immunohistochemical data available for 227. Tumor size, percentage of positive axillary nodes and expression status for the progesterone receptor, Ki-67 and carbonic anhydrase IX demonstrated independent prognostic significance with respect to relapse-free survival. Our combined biomarker scoring system defined three subgroups in the test set with mean 10-year relapse-free survivals of 75.4% (SEM 7.0%), 35.3% (SEM 4.1%) and 19.3% (SEM 7.0%). In the validation set, differences in relapse-free survival for these subgroups remained statistically significant but less marked.
Conclusion
Biomarkers assessed here carry independent prognostic value for breast cancer with four or more positive axillary nodes and identified clinically relevant prognostic subgroups. This approach requires refinement and validation of methodology.
doi:10.1186/bcr1847
PMCID: PMC2374957  PMID: 18194560

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