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

The relationship between carbonic anhydrase IX (CAIX) and patient survival in breast cancer: systematic review and meta-analysis

PURPOSE

Hypoxia is a characteristic of many solid tumours and an adverse prognostic factor for cancer therapy. Hypoxia results in upregulation of carbonic anhydrase IX (CAIX) expression, a pH-regulating enzyme. Many human tissue studies have examined the prognostic value of CAIX expression in breast cancer but have yielded inconsistent results. Therefore, a systematic review and meta-analysis was undertaken to assess the prognostic value of CAIX expression for breast cancer patients.

METHODS

The electronic databases were systematically searched to identify relevant papers. The clinical outcomes included disease-free survival (DFS), recurrence-free survival (RFS) and overall survival (OS) in breast cancer patients. Review Manager version 5.4 was employed to analysis data from 23 eligible studies (containing 8390 patients).

RESULTS

High CAIX expression was associated with poorer RFS [HR = 1.42, 95% CI (1.32-1.51), p < 0.00001], DFS [HR = 1.64, 95% CI (1.34-2.00), p < 0.00001], and OS [HR = 1.48, 95% CI (1.22-1.80), p < 0.0001]. Heterogeneity was observed across the studies. There was an effect of the CAIX antibody employed, scoring methods, and tumour localisation on CAIX expression.

CONCLUSION

CAIX overexpression was significantly associated with poorer RFS, DFS, and OS in breast cancer patients. However, further work in high quantity tissue cohorts is required to define the optimal methodological approach.

Carbonic anhydrase IX-related tumoral hypoxia predicts worse prognosis in breast cancer: A systematic review and meta-analysis

Background

Tumoral hypoxia is associated with aggressiveness in many cancers including breast cancer. However, measuring hypoxia is complicated. Carbonic anhydrase IX (CAIX) is a reliable endogenous marker of hypoxia under the control of the master regulator hypoxia-inducible factor-1α (HIF-1α). The expression of CAIX is associated with poor prognosis in many solid malignancies; however, its role in breast cancer remains controversial.

Methods

The present study performed a meta-analysis to evaluate the correlation between CAIX expression and disease-free survival (DFS) and overall survival (OS) in breast cancer.

Results

A total of 2,120 publications from EMBASE, PubMed, Cochrane, and Scopus were screened. Of these 2,120 publications, 272 full texts were reviewed, and 27 articles were included in the meta-analysis. High CAIX was significantly associated with poor DFS (HR = 1.70, 95% CI = 1.39–2.07, p &lt; 0.00001) and OS (HR = 2.02, 95% CI 1.40–2.91, p = 0.0002) in patients with breast cancer. When stratified by subtype, the high CAIX group was clearly associated with shorter DFS (HR = 2.09, 95% CI =1.11–3.92, p = 0.02) and OS (HR = 2.50, 95% CI =1.53–4.07, p = 0.0002) in TNBC and shorter DFS in ER+ breast cancer (HR = 1.81 95% CI =1.38–2.36, p &lt; 0.0001).

Conclusion

High CAIX expression is a negative prognostic marker of breast cancer regardless of the subtypes.

Identification of a four-long non-coding RNA signature in predicting breast cancer survival

Long non-coding RNAs (lncRNAs) serve key roles in tumorigenesis and are differentially expressed in cancer. Using bioinformatics and statistical methods, the present study aimed to identify an lncRNA signature to predict breast cancer survival. The gene expression data of 768 patients with breast cancer were downloaded from The Cancer Genome Atlas database, and Cox regression, Kaplan-Meier and receiver operating characteristic (ROC) analyses were performed to construct and validate a predictive model. Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis were employed to predict the functions of the indicated lncRNAs. A signature consisting of four lncRNAs, including PVT1, MAPT-AS1, LINC00667 and LINC00938, was identified, and patients were subsequently divided into high- and low-risk groups according to the median risk score. Kaplan-Meier analysis confirmed that patients in the high-risk group exhibited significantly poorer overall survival rate in both the training (P=0.0151) and the validation set (P=0.0016); furthermore, ROC analysis confirmed that the model could predict patient survival with a certain sensitivity and specificity. In conclusion, the four-lncRNA signature presents a potential prognostic biomarker for breast cancer that may be relevant for clinical application.

Clinicopathologic and molecular characteristics of 44 patients with pure secretory breast carcinoma

Objective

Secretory breast carcinoma (SBC) is a rare type of breast malignancy, accounting for less than 0.02% of all infiltrating breast malignancies. The pure SBC, a type of SBC without another type of breast malignant neoplasm, is particularly rare. This study aimed to investigate the clinicopathologic and molecular features of pure SBC.

Methods

The main pathological parameters such as estrogen receptor (ER), progesterone receptor (PR), and human epithelial growth factor receptor 2 (C-erbB-2) were detected by immunohistochemistry (IHC), and the clinicopathologic and prognostic difference were compared with invasive ductal carcinoma (IDC). Fluorescent in situ hybridization (FISH) and reverse transcription polymerase chain reaction (RT-PCR) was performed to identify the ETV6-NTRK3 rearrangement of SBC.

Results

We found that the positivity rates of ER, PR, C-erbB-2, p53, and S-100 were 47.7% (21/44), 52.3% (23/44), 36.4% (16/44), 27.3% (12/44), and 95.5% (42/44), respectively, which were higher than those reported in previous studies. Special periodic acid-Schiff analysis was performed in 36 patients, and the value of the Ki-67 index ranged from 1% to 50% (mean value: 10%). Interestingly, most patients with pure SBC harbored an ETV6-NTRK3 rearrangement with an 88.6% (39/44) expression rate. Compared with IDC, the tumor size of most patients with SBC was larger than 2 cm (P = 0.024). Ultrasound showed benign lesions, and the total misdiagnosis rate was higher (P = 0.020). Although the pathological classification was mostly triple-negative breast cancers (P = 0.036), there was less metastasis (P = 0.029), and the overall prognosis was better than that of the IDC group.

Conclusions

Although axillary lymph node metastasis, local recurrence, or distant metastasis may occur, SBC is also considered an indolent neoplasm with a good prognosis. Once diagnosed, surgical treatment should be performed as soon as possible, followed by appropriate adjuvant chemotherapy, irradiation, and endocrine therapies.

Prognostic value of Ki67 analysed by cytology or histology in primary breast cancer

Aims

The accuracy of biomarker assessment in breast pathology is vital for therapy decisions. The therapy predictive and prognostic biomarkers oestrogen receptor (ER), progesterone receptor, HER2 and Ki67 may act as surrogates to gene expression profiling of breast cancer. The aims of this study were to investigate the concordance of consecutive biomarker assessment by immunocytochemistry on preoperative fine-needle aspiration cytology versus immunohistochemistry (IHC) on the corresponding resected breast tumours. Further, to investigate the concordance with molecular subtype and correlation to stage and outcome.

Methods

Two retrospective cohorts comprising 385 breast tumours with clinicopathological data including gene expression-based subtype and up to 10-year overall survival data were evaluated.

Results

In both cohorts, we identified a substantial variation in Ki67 index between cytology and histology and a switch between low and high proliferation within the same tumour in 121/360 cases. ER evaluations were discordant in only 1.5% of the tumours. From cohort 2, gene expression data with PAM50 subtype were used to correlate surrogate subtypes. IHC-based surrogate classification could identify the correct molecular subtype in 60% and 64% of patients by cytology (n=63) and surgical resections (n=73), respectively. Furthermore, high Ki67 in surgical resections but not in cytology was associated with poor overall survival and higher probability for axillary lymph node metastasis.

Conclusions

This study shows considerable differences in the prognostic value of Ki67 but not ER in breast cancer depending on the diagnostic method. Furthermore, our findings show that both methods are insufficient in predicting true molecular subtypes.

Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival

Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan–Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC = 0.752, 95% confidence intervals (CI): 0.651–0.854) and the microarray dataset (AUC = 0.714, 95%CI: 0.615–0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs.

Serum total hCGβ level is an independent prognostic factor in transitional cell carcinoma of the urothelial tract

Background:

Serum total human chorionic gonadotrophin β subunit (hCGβ) level might have prognostic value in urothelial transitional cell carcinoma (TCC) but has not been investigated for independence from other prognostic variables.

Methods:

We utilised a clinical database of patients receiving chemotherapy between 2005 and 2011 for urothelial TCC and an independent cohort of radical cystectomy patients for validation purposes. Prognostic variables were tested by univariate Kaplan–Meier analyses and log-rank tests. Statistically significant variables were then assessed by multivariate Cox regression. Total hCGβ level was dichotomised at < vs ⩾2 IU l⁻¹.

Results:

A total of 235 chemotherapy patients were eligible. For neoadjuvant chemotherapy, established prognostic factors including low ECOG performance status, normal haemoglobin, lower T stage and suitability for cisplatin-based chemotherapy were associated with favourable survival in univariate analyses. In addition, low hCGβ level was favourable when assessed either before (median survival not reached vs 1.86 years, P=0.001) or on completion of chemotherapy (4.27 vs 0.42 years, P=0.000002). This was confirmed in multivariate analyses and in patients receiving first- and second-line palliative chemotherapy, and in a radical cystectomy validation set.

Conclusions:

Serum total hCGβ level is an independent prognostic factor in patients receiving chemotherapy for urothelial TCC in both curative and palliative settings.

Prognostic value of Ki-67 in breast cancer patients with positive axillary lymph nodes: a retrospective cohort study

Introduction

Ki-67 expression is a biomarker for proliferation. Its prognostic value is recognized in breast cancer (BC) patients with negative axillary nodes, but is less clear in BC patients with positive axillary lymph nodes.

Methods

We retrospectively reviewed the medical records of 1131 Chinese BC patients treated from January 2002 to June 2007 and 450 patients met the inclusion criteria: positive nodes, adjuvant therapy, and complete biomarker profile (estrogen receptor (ER), progesterone receptor (PR), HER2, p53, Ki-67). Univariate and multivariate regression analysis were used to correlate biomarkers and tumor characteristics with metastasis free survival (MFS) and overall survival (OS).

Results

Median follow-up time was 46 months (range 5–76 months). The Ki-67 expression was associated significantly with histological grade, ER, PR, HER2, and P53 status (P<0.05). Tumor stage, nodal stage, and ER status were independent prognostic factors for MFS. Ki-67 status was associated significantly with OS but not MFS. To determine whether the extent of LN involvement in the BC patients influenced the role of Ki-67 in survival rates, we compared these variables in patients with 1–3 positive lymph nodes (N1) to those of patients with ≥4 positive lymph nodes. Ki-67 status was an independent prognostic factor for MFS (Hazard Ratio, 3.27, P = 0.026) and overall survival (HR, 10.64, P = 0.007) in patients with 1–3 positive nodes (N1).

Conclusions

The possibility that Ki-67 expression together with clinical factors can improve prediction of the prognosis of BC patients with 1∼3 positive axillary lymph nodes warrants further studies.

The potential of hypoxia markers as target for breast molecular imaging--a systematic review and meta-analysis of human marker expression

Background

Molecular imaging of breast cancer is a promising emerging technology, potentially able to improve clinical care. Valid imaging targets for molecular imaging tracer development are membrane-bound hypoxia-related proteins, expressed when tumor growth outpaces neo-angiogenesis. We performed a systematic literature review and meta-analysis of such hypoxia marker expression rates in human breast cancer to evaluate their potential as clinically relevant molecular imaging targets.

Methods

We searched MEDLINE and EMBASE for articles describing membrane-bound proteins that are related to hypoxia inducible factor 1α (HIF-1α), the key regulator of the hypoxia response. We extracted expression rates of carbonic anhydrase-IX (CAIX), glucose transporter-1 (GLUT1), C-X-C chemokine receptor type-4 (CXCR4), or insulin-like growth factor-1 receptor (IGF1R) in human breast disease, evaluated by immunohistochemistry. We pooled study results using random-effects models and applied meta-regression to identify associations with clinicopathological variables.

Results

Of 1,705 identified articles, 117 matched our selection criteria, totaling 30,216 immunohistochemistry results. We found substantial between-study variability in expression rates. Invasive cancer showed pooled expression rates of 35% for CAIX (95% confidence interval (CI): 26-46%), 51% for GLUT1 (CI: 40-61%), 46% for CXCR4 (CI: 33-59%), and 46% for IGF1R (CI: 35-70%). Expression rates increased with tumor grade for GLUT1, CAIX, and CXCR4 (all p < 0.001), but decreased for IGF1R (p < 0.001). GLUT1 showed the highest expression rate in grade III cancers with 58% (45-69%). CXCR4 showed the highest expression rate in small T1 tumors with 48% (CI: 28-69%), but associations with size were only significant for CAIX (p < 0.001; positive association) and IGF1R (p = 0.047; negative association). Although based on few studies, CAIX, GLUT1, and CXCR4 showed profound lower expression rates in normal breast tissue and benign breast disease (p < 0.001), and high rates in carcinoma in situ. Invasive lobular carcinoma consistently showed lower expression rates (p < 0.001).

Conclusions

Our results support the potential of hypoxia-related markers as breast cancer molecular imaging targets. Although specificity is promising, combining targets would be necessary for optimal sensitivity. These data could help guide the choice of imaging targets for tracer development depending on the envisioned clinical application.

Axillary dissection can be avoided in the majority of clinically node-negative patients undergoing breast-conserving therapy

BACKGROUND

The extent to which ACOSOG Z0011 findings are applicable to patients undergoing breast-conserving therapy (BCT) is uncertain. We prospectively assessed how often axillary dissection (ALND) was avoided in an unselected, consecutive patient cohort meeting Z0011 eligibility criteria and whether subgroups requiring ALND could be identified preoperatively.

METHODS

Patients with cT1,2cN0 breast cancer undergoing BCT were managed without ALND for metastases in <3 sentinel nodes (SNs) and no gross extracapsular extension (ECE). Patients with and without indications for ALND were compared using Fisher's exact and Wilcoxon rank sum tests.

RESULTS

From August 2010 to November 2012, 2,157 invasive cancer patients had BCT. A total of 380 had histologic nodal metastasis; 93 did not meet Z0011 criteria. Of 287 with ≥1 H&E-positive SN (209 macrometastases), 242 (84 %) had indications for SN only. ALND was indicated in 45 for ≥3 positive SNs (n = 29) or ECE (n = 16). The median number of SNs removed in the SN group was 3 versus 5 in the ALND group (p < 0.0001). Age, hormone receptor and HER2 status, and grade did not differ between groups; tumors were larger in the ALND group (p < 0.0001). Of ALND patients, 72 % had additional positive nodes (median = 1; range 1-19). No axillary recurrences have occurred (median follow-up, 13 months).

CONCLUSIONS

ALND was avoided in 84 % of a consecutive series of patients having BCT, suggesting that most patients meeting ACOSOG Z0011 eligibility have a low axillary tumor burden. Age, ER, and HER2 status were not predictive of ALND, and the criteria used for ALND (≥3 SNs, ECE) reliably identified patients at high risk for residual axillary disease.

Systematic antibody generation and validation via tissue microarray technology leading to identification of a novel protein prognostic panel in breast cancer

BACKGROUND

Although omic-based discovery approaches can provide powerful tools for biomarker identification, several reservations have been raised regarding the clinical applicability of gene expression studies, such as their prohibitive cost. However, the limited availability of antibodies is a key barrier to the development of a lower cost alternative, namely a discrete collection of immunohistochemistry (IHC)-based biomarkers. The aim of this study was to use a systematic approach to generate and screen affinity-purified, mono-specific antibodies targeting progression-related biomarkers, with a view towards developing a clinically applicable IHC-based prognostic biomarker panel for breast cancer.

METHODS

We examined both in-house and publicly available breast cancer DNA microarray datasets relating to invasion and metastasis, thus identifying a cohort of candidate progression-associated biomarkers. Of these, 18 antibodies were released for extended analysis. Validated antibodies were screened against a tissue microarray (TMA) constructed from a cohort of consecutive breast cancer cases (n = 512) to test the immunohistochemical surrogate signature.

RESULTS

Antibody screening revealed 3 candidate prognostic markers: the cell cycle regulator, Anillin (ANLN); the mitogen-activated protein kinase, PDZ-Binding Kinase (PBK); and the estrogen response gene, PDZ-Domain Containing 1 (PDZK1). Increased expression of ANLN and PBK was associated with poor prognosis, whilst increased expression of PDZK1 was associated with good prognosis. A 3-marker signature comprised of high PBK, high ANLN and low PDZK1 expression was associated with decreased recurrence-free survival (p < 0.001) and breast cancer-specific survival (BCSS) (p < 0.001). This novel signature was associated with high tumour grade (p < 0.001), positive nodal status (p = 0.029), ER-negativity (p = 0.006), Her2-positivity (p = 0.036) and high Ki67 status (p < 0.001). However, multivariate Cox regression demonstrated that the signature was not a significant predictor of BCSS (HR = 6.38; 95% CI = 0.79-51.26, p = 0.082).

CONCLUSIONS

We have developed a comprehensive biomarker pathway that extends from discovery through to validation on a TMA platform. This proof-of-concept study has resulted in the identification of a novel 3-protein prognostic panel. Additional biochemical markers, interrogated using this high-throughput platform, may further augment the prognostic accuracy of this panel to a point that may allow implementation into routine clinical practice.

Protein analytical assays for diagnosing, monitoring, and choosing treatment for cancer patients

Cancer treatment is often hindered by inadequate methods for diagnosing the disease or insufficient predictive capacity regarding therapeutic efficacy. Targeted cancer treatments, including Bcr-Abl and EGFR kinase inhibitors, have increased survival for some cancer patients but are ineffective in other patients. In addition, many patients who initially respond to targeted inhibitor therapy develop resistance during the course of treatment. Molecular analysis of cancer cells has emerged as a means to tailor treatment to particular patients. While DNA analysis can provide important diagnostic information, protein analysis is particularly valuable because proteins are more direct mediators of normal and diseased cellular processes. In this review article, we discuss current and emerging protein assays for improving cancer treatment, including trends toward assay miniaturization and measurement of protein activity.

Extending the tissue microarray data exchange specification for inclusion of data analysis results

Background:

The Tissue Microarray Data Exchange Specification (TMA DES) is an eXtensible Markup Language (XML) specification for encoding TMA experiment data in a machine-readable format that is also human readable. TMA DES defines Common Data Elements (CDEs) that form a basic vocabulary for describing TMA data. TMA data are routinely subjected to univariate and multivariate statistical analysis to determine differences or similarities between pathologically distinct groups of tumors for one or more markers or between markers for different groups. Such statistical analysis tests include the t-test, ANOVA, Chi-square, Mann-Whitney U, and Kruskal-Wallis tests. All these generate output that needs to be recorded and stored with TMA data.

Materials and Methods:

We propose extending the TMA DES to include syntactic and semantic definitions of CDEs for describing the results of statistical analyses performed upon TMA DES data. These CDEs are described in this paper and it is illustrated how they can be added to the TMA DES. We created a Document Type Definition (DTD) file defining the syntax for these CDEs, and a set of ISO 11179 entries providing semantic definitions for them. We describe how we wrote a program in R that read TMA DES data from an XML file, performed statistical analyses on that data, and created a new XML file containing both the original XML data and CDEs representing the results of our analyses. This XML file was submitted to XML parsers in order to confirm that they conformed to the syntax defined in our extended DTD file. TMA DES XML files with deliberately introduced errors were also parsed in order to verify that our new DTD file could perform error checking. Finally, we also validated an existing TMA DES XML file against our DTD file in order to demonstrate the backward compatibility of our DTD.

Results:

Our experiments demonstrated the encoding of analysis results using our proposed CDEs. We used XML parsers to confirm that these XML data were syntactically correct and conformed to the rules specified in our extended TMA DES DTD. We also demonstrated that this extended DTD was capable of being used to successfully perform error checking, and was backward compatible with pre-existing TMA DES data which did not use our new CDEs.

Conclusions:

The TMA DES allows Tissue Microarray data to be shared. A variety of statistical tests are used to analyze such data. We have proposed a set of CDEs as an extension to the TMA DES which can be used to annotate TMA DES data with the results of statistical analyses performed on that data. We performed experiments which demonstrated the usage of TMA DES data containing our proposed CDEs.

Toponostics of invasive ductal breast carcinoma: combination of spatial protein expression imaging and quantitative proteome signature analysis

Due to enormous advances in quantitative proteomics and in immunohistochemistry (pathology), the two research areas have now reached the state to be successfully interwoven in order to tackle challenges in toponostics and to open tumor-targeted systems pathology approaches. In this study the differential expressions of candidate proteins nucleophosmin, nucleoside diphosphate kinase A/B (NDKA/B), osteoinducive factor (mimecan), and pyru-vate kinase M2 from a quantitative proteome signature for invasive ductal breast cancer were determined by immunohistochemistry on 53 tissue slices from formalin-fixed and paraffin-embedded tumor and control tissue samples from ten patients and fourteen controls. In addition, 87 images from the Human Protein Atlas representing seven tumor and nine normal breast tissue samples were investigated by computer-assisted semi-quantitative density measurements on nucleophosmin, nucleoside diphosphate kinase A/B (NDKA/B), osteoinducive factor (mimecan), pyruvate kinase M2, glyceraldehyde-3-phosphate dehydro-genase (GAP-DH), and mimecan (osteoinductive factor). Both IHC data sets match well to each other and support the quantitative proteome analysis data. Determining spatial distribution of signature protein expressions by protein imaging on morphologically intact tissue samples at the sub-cellular level and, hence, keeping all topological information, presents an added value to quantitative proteome data. Such comprehensive data sets are needed for both, pathway analyses and for "next generation clinical diagnostics" approaches.

Targeting tumor hypoxia: suppression of breast tumor growth and metastasis by novel carbonic anhydrase IX inhibitors

Carbonic anhydrase IX (CAIX) is a hypoxia and HIF-1-inducible protein that regulates intra- and extracellular pH under hypoxic conditions and promotes tumor cell survival and invasion in hypoxic microenvironments. Interrogation of 3,630 human breast cancers provided definitive evidence of CAIX as an independent poor prognostic biomarker for distant metastases and survival. shRNA-mediated depletion of CAIX expression in 4T1 mouse metastatic breast cancer cells capable of inducing CAIX in hypoxia resulted in regression of orthotopic mammary tumors and inhibition of spontaneous lung metastasis formation. Stable depletion of CAIX in MDA-MB-231 human breast cancer xenografts also resulted in attenuation of primary tumor growth. CAIX depletion in the 4T1 cells led to caspase-independent cell death and reversal of extracellular acidosis under hypoxic conditions in vitro. Treatment of mice harboring CAIX-positive 4T1 mammary tumors with novel CAIX-specific small molecule inhibitors that mimicked the effects of CAIX depletion in vitro resulted in significant inhibition of tumor growth and metastasis formation in both spontaneous and experimental models of metastasis, without inhibitory effects on CAIX-negative tumors. Similar inhibitory effects on primary tumor growth were observed in mice harboring orthotopic tumors comprised of lung metatstatic MDA-MB-231 LM2-4(Luc+) cells. Our findings show that CAIX is vital for growth and metastasis of hypoxic breast tumors and is a specific, targetable biomarker for breast cancer metastasis.

P-cadherin expression as a prognostic biomarker in a 3992 case tissue microarray series of breast cancer

P-cadherin is a calcium-dependent cell-cell adhesion glycoprotein. P-cadherin expression is restricted to the myoepithelial cells in normal breast tissue, and aberrant staining has also been described in invasive tumors. Several small studies have reported P-cadherin as a marker of poor outcome in breast cancer patients but its prognostic significance in relation to other variables has not been established in a large series of breast cancers. A tissue microarray was constructed from 3992 cases of invasive breast carcinoma, and P-cadherin expression was evaluated using immunohistochemistry. Median follow-up was 12.5 years. The immunohistochemistry-based definitions of cancer subtypes were luminal (ER+ or PR+/HER2-), luminal/HER2+ (ER+ or PR+/HER2+), HER2+ (ER-/PR-/HER2+), and basal (ER-/PR-/HER2-/CK5/6+ or EGFR+). Clinical covariate and biomarker associations were assessed using contingency tables, and Pearson's χ(2) or Fisher's exact test. Survival associations were assessed using Kaplan-Meier plots, logrank and Breslow tests, and Cox proportional hazards regression analysis. P-cadherin was expressed in 34.8% (1290/3710, 50% cut point) of cases. P-cadherin staining was strongly associated with HER2+ and basal carcinoma subtypes (P<0.0005). P-cadherin-positive patients showed significantly poorer short-term (0-10 years) overall survival, disease-specific survival, distant relapse-free interval, and locoregional relapse-free interval in univariable models (P<0.05). In multivariable Cox models containing standard clinical covariates and cancer subtypes, P-cadherin did not show independent prognostic value. P-cadherin expression was positively associated with histological grade, chemotherapy, Ki-67, EGFR, CK5/6, p53, YB-1, and HER2 expression (P<0.002), and negatively associated with age at diagnosis, ER, PR, and Bcl-2 expression (P<0.0005). This study shows the value of P-cadherin as a marker of poor prognosis. The large sample size of this series clarifies contradictory findings of many smaller studies. P-cadherin positivity is associated with high-grade tumor subtypes and well-established markers of poor prognosis, and may represent a promising antibody therapeutic target.

Antibody-based proteomics: fast-tracking molecular diagnostics in oncology

The effective implementation of personalized cancer therapeutic regimens depends on the successful identification and translation of informative biomarkers to aid clinical decision making. Antibody-based proteomics occupies a pivotal space in the cancer biomarker discovery and validation pipeline, facilitating the high-throughput evaluation of candidate markers. Although the clinical utility of these emerging technologies remains to be established, the traditional use of antibodies as affinity reagents in clinical diagnostic and predictive assays suggests that the rapid translation of such approaches is an achievable goal. Furthermore, in combination with, or as alternatives to, genomic and transcriptomic methods for patient stratification, antibody-based proteomics approaches offer the promise of additional insight into cancer disease states. In this Review, we discuss the current status of antibody-based proteomics and its contribution to the development of new assays that are crucial for the realization of individualized cancer therapy.

Tissue biomarker development in a multicentre trial context: a feasibility study on the PETACC3 stage II and III colon cancer adjuvant treatment trial

PURPOSE

We evaluated the feasibility of biomarker development in the context of multicenter clinical trials.

EXPERIMENTAL DESIGN

Formalin-fixed, paraffin-embedded (FFPE) tissue samples were collected from a prospective adjuvant colon cancer trial (PETACC3). DNA was isolated from tumor as well as normal tissue and used for analysis of microsatellite instability, KRAS and BRAF genotyping, UGT1A1 genotyping, and loss of heterozygosity of 18 q loci. Immunohistochemistry was used to test expression of TERT, SMAD4, p53, and TYMS. Messenger RNA was retrieved and tested for use in expression profiling experiments.

RESULTS

Of the 3,278 patients entered in the study, FFPE blocks were obtained from 1,564 patients coming from 368 different centers in 31 countries. In over 95% of the samples, genomic DNA tests yielded a reliable result. Of the immmunohistochemical tests, p53 and SMAD4 staining did best with reliable results in over 85% of the cases. TERT was the most problematic test with 46% of failures, mostly due to insufficient tissue processing quality. Good quality mRNA was obtained, usable in expression profiling experiments.

CONCLUSIONS

Prospective clinical trials can be used as framework for biomarker development using routinely processed FFPE tissues. Our results support the notion that as a rule, translational studies based on FFPE should be included in prospective clinical trials.

Novel image analysis approach for quantifying expression of nuclear proteins assessed by immunohistochemistry: application to measurement of oestrogen and progesterone receptor levels in breast cancer

Introduction

Manual interpretation of immunohistochemistry (IHC) is a subjective, time-consuming and variable process, with an inherent intra-observer and inter-observer variability. Automated image analysis approaches offer the possibility of developing rapid, uniform indicators of IHC staining. In the present article we describe the development of a novel approach for automatically quantifying oestrogen receptor (ER) and progesterone receptor (PR) protein expression assessed by IHC in primary breast cancer.

Methods

Two cohorts of breast cancer patients (n = 743) were used in the study. Digital images of breast cancer tissue microarrays were captured using the Aperio ScanScope XT slide scanner (Aperio Technologies, Vista, CA, USA). Image analysis algorithms were developed using MatLab 7 (MathWorks, Apple Hill Drive, MA, USA). A fully automated nuclear algorithm was developed to discriminate tumour from normal tissue and to quantify ER and PR expression in both cohorts. Random forest clustering was employed to identify optimum thresholds for survival analysis.

Results

The accuracy of the nuclear algorithm was initially confirmed by a histopathologist, who validated the output in 18 representative images. In these 18 samples, an excellent correlation was evident between the results obtained by manual and automated analysis (Spearman's ρ = 0.9, P < 0.001). Optimum thresholds for survival analysis were identified using random forest clustering. This revealed 7% positive tumour cells as the optimum threshold for the ER and 5% positive tumour cells for the PR. Moreover, a 7% cutoff level for the ER predicted a better response to tamoxifen than the currently used 10% threshold. Finally, linear regression was employed to demonstrate a more homogeneous pattern of expression for the ER (R = 0.860) than for the PR (R = 0.681).

Conclusions

In summary, we present data on the automated quantification of the ER and the PR in 743 primary breast tumours using a novel unsupervised image analysis algorithm. This novel approach provides a useful tool for the quantification of biomarkers on tissue specimens, as well as for objective identification of appropriate cutoff thresholds for biomarker positivity. It also offers the potential to identify proteins with a homogeneous pattern of expression.

Prognostic ability of a panel of immunohistochemistry markers - retailoring of an 'old solution'

An urgent requirement exists for new prognostic and predictive assays in breast cancer. Despite the development of high-throughput technologies such as DNA microarrays, it would now appear that immunohistochemistry (IHC) may play an increasingly important role in the clinical management of breast cancer. In this editorial, the authors discuss the potential prognostic ability of a panel of IHC markers, and question whether this well-established assay technology may in fact allow for improved prognostic and predictive tests in breast cancer.