Microvessel area as a predictor of sorafenib response in metastatic renal cell carcinoma.

BACKGROUND: Sorafenib was the first Food and Drug Administration approved anti-angiogenic therapy for renal cell carcinoma (RCC). Currently, there are no validated predictive biomarkers for sorafenib. Our purpose was to determine if sorafenib target expression is predictive of sorafenib sensitivity. METHODS: We used an automated, quantitative immunofluorescence-based method to determine expression levels of sorafenib targets VEGF, VEGF-R1, VEGF-R2, VEGF-R3, c-RAF, B-RAF, c-Kit, and PDGFR-ß in a cohort of 96 patients treated with sorafenib. To measure vasculature in the tumor samples, we measured microvessel area (MVA) by CD-34 staining. RESULTS: Of the markers studied, only high MVA was predictive of response (p = 0.005). High MVA was associated with smaller primary tumors (p = 0.005). None of the biomarkers studied was predictive of overall or progression-free survival. Using the Bonferroni adjustment correcting for 9 variables with an alpha of 0.05, MVA remained significantly associated with sorafenib response. CONCLUSIONS: Our results suggest that high MVA in tumor specimens might be associated with a greater likelihood of response to therapy. Further studies are needed to confirm these results in additional patients and in patients receiving other VEGF-R2 inhibitors, as MVA might be useful to improve patient selection for VEGF-R2 inhibitors.

Vascularity of primary and metastatic renal cell carcinoma specimens.

PURPOSE: Anti-angiogenic therapies are among the most commonly used drugs in renal cell carcinoma. Tumor vascularity, defined by microvessel area, may be associated with response to these drugs. Clinical studies suggest that metastatic sites are more responsive than primary tumors. Our purpose was to characterize microvessel area (MVA) in matched primary and metastatic samples and in samples of different histologies. METHODS: We employed a method of automated, quantitative analysis of in situ tumor components to identify the area of CD-34 staining endothelial cells within renal cell carcinoma tumors. MVA was assessed in corresponding primary and metastatic samples from 34 patients, as well as in 334 primary nephrectomy specimens with variable histologies. RESULTS: MVA measurements from different parts of the same tumor correlated well (R = 0.75), indicating that MVA was fairly uniform within a tumor. While MVA was slightly higher in primary tumors than corresponding metastatic sites, the difference was not statistically significant (P = 0.1). MVA in paired primary and metastatic samples correlated moderately well (R = 0.36). MVA was higher in clear cell than papillary histology and oncocytomas (P < 0.0001 and P = 0.018, respectively). CONCLUSIONS: Lack of significant differences MVA in matched primary and metastatic samples suggests that both types of tumors should respond to anti-angiogenic drugs. This should be confirmed on additional cohorts. Given the small cohort, future predictive biomarker studies entailing MVA measurements should include specimens from both sites. Clear cell carcinomas are more vascular than other histologic subtypes, which may explain the higher response rates to anti-angiogenic therapies in clear cell tumors.

Expression of drug targets in primary and matched metastatic renal cell carcinoma tumors.

BACKGROUND: Targeted therapies in renal cell carcinoma can have different effects on primary and metastatic tumors. To pave the way for predictive biomarker development, we assessed differences in expression of targets of currently approved drugs in matched primary and metastatic specimens from 34 patients. METHODS: Four cores from each site were embedded in tissue microarray blocks. Expression of B-Raf, C-Raf, cKIT, FGF-R1, HIF-2α, mTOR, PDGF-Rß, VEGF-R1, VEGF-R2, VEGF-R3, VEGF, VEGF-B, VEGF-C, VEGF-D, MEK1, and ERK1/2 was studied using a quantitative immunofluorescence method. RESULTS: No significant differences were observed in global expression levels in primary and metastatic renal cell carcinoma tumors, with the exception of MEK, which had higher expression in metastatic than primary specimens. Similarly, more ki67 positive cells were seen in metastatic specimens. Correlations between marker expression in primary and metastatic specimens were variable, with the lowest correlation seen for FGF-R1 and VEGF-D. There were no significant differences in the degree of heterogeneity in primary versus metastatic tumors. CONCLUSIONS: Expression of most of the studied markers was similar in primary and metastatic renal cell carcinoma tumors, suggesting that predictive biomarker testing for these markers can be conducted on either the primary or metastatic tumors for most markers.

Quantitative assessment of invasive mena isoforms (Menacalc) as an independent prognostic marker in breast cancer.

INTRODUCTION: Mena, an Ena/VASP protein family member, is a key actin regulatory protein. Mena is up-regulated in breast cancers and promotes invasion and motility of tumor cells. Mena has multiple splice variants, including Mena invasive (MenaINV) and Mena11a, which are expressed in invasive or non-invasive tumor cells, respectively. We developed a multiplex quantitative immunofluorescence (MQIF) approach to assess the fraction of Mena lacking 11a sequence as a method to infer the presence of invasive tumor cells represented as total Mena minus Mena11a (called Menacalc) and determined its association with metastasis in breast cancer. METHODS: The MQIF method was applied to two independent primary breast cancer cohorts (Cohort 1 with 501 and Cohort 2 with 296 patients) using antibodies against Mena and its isoform, Mena11a. Menacalc was determined for each patient and assessed for association with risk of disease-specific death. RESULTS: Total Mena or Mena11a isoform expression failed to show any statistically significant association with outcome in either cohort. However, assessment of Menacalc showed that relatively high levels of this biomarker is associated with poor outcome in two independent breast cancer cohorts (log rank P = 0.0004 for Cohort 1 and 0.0321 for Cohort 2). Multivariate analysis on combined cohorts revealed that high Menacalc is associated with poor outcome, independent of age, node status, receptor status and tumor size. CONCLUSIONS: High Menacalc levels identify a subgroup of breast cancer patients with poor disease-specific survival, suggesting that Menacalc may serve as a biomarker for metastasis.

Quantitative assessment shows loss of antigenic epitopes as a function of pre-analytic variables.

Pre-analytic variables, specifically cold ischemic time, have been implicated as key variables in the measurement of proteins by immunohistochemistry. To determine the significance and magnitude of antigenic loss due to pre-analytic variables, we have compared protein antigenicity in core needle biopsies, with essentially no cold ischemic time, with that in routinely processed tumor resection specimens. Two cohorts of matched core needle biopsies and tumor resections were collected with 20 matched pairs and 14 matched pairs, respectively. Both series were analyzed by quantitative immunofluorescence using the AQUA® method. Epitopes phospho-ERK, total ERK, phospho-AKT, total AKT, phospho-S6K1, total S6K1, estrogen receptor (ER), Ki67, cytokeratin and GAPDH were assessed. Detection levels for all phospho-epitopes were significantly decreased in tumor resections compared with biopsies while no significant change was seen in the corresponding total proteins. Of the other four proteins examined, ER and cytokeratin showed significant loss of antigenicity. This data suggest that measurement of phospho-protein antigenicity in formalin-fixed tissue by immunological methods is dramatically affected by pre-analytic variables. This study suggests that core needle biopsies are more accurate for assessment of tissue biomarkers.

Evaluation of prognostic and predictive value of microtubule associated protein tau in two independent cohorts.

INTRODUCTION: Microtubule associated proteins (MAPs) endogenously regulate microtubule stabilization and have been reported as prognostic and predictive markers for taxane response. The microtubule stabilizer, MAP-tau, has shown conflicting results. We quantitatively assessed MAP-tau expression in two independent breast cancer cohorts to determine prognostic and predictive value of this biomarker. METHODS: MAP-tau expression was evaluated in the retrospective Yale University breast cancer cohort (n = 651) using tissue microarrays and also in the TAX 307 cohort, a clinical trial randomized for TAC versus FAC chemotherapy (n = 140), using conventional whole tissue sections. Expression was measured using the AQUA method for quantitative immunofluorescence. Scores were correlated with clinicopathologic variables, survival, and response to therapy. RESULTS: Assessment of the Yale cohort using Cox univariate analysis indicated an improved overall survival (OS) in tumors with a positive correlation between high MAP-tau expression and overall survival (OS) (HR = 0.691, 95% CI = 0.489-0.974; P = 0.004). Kaplan Meier analysis showed 10-year survival for 65% of patients with high MAP-tau expression compared to 52% with low expression (P = .006). In TAX 307, high expression was associated with significantly longer median time to tumor progression (TTP) regardless of treatment arm (33.0 versus 23.4 months, P = 0.010) with mean TTP of 31.2 months. Response rates did not differ by MAP-tau expression (P = 0.518) or by treatment arm (P = 0.584). CONCLUSIONS: Quantitative measurement of MAP-tau expression has prognostic value in both cohorts, with high expression associated with longer TTP and OS. Differences by treatment arm or response rate in low versus high MAP-tau groups were not observed, indicating that MAP-tau is not associated with response to taxanes and is not a useful predictive marker for taxane-based chemotherapy.

In situ identification of putative cancer stem cells by multiplexing ALDH1, CD44, and cytokeratin identifies breast cancer patients with poor prognosis.

A subset of cells, tentatively called cancer stem cells (CSCs), in breast cancer have been associated with tumor initiation, drug resistance, and tumor persistence or aggressiveness. They are characterized by CD44 positivity, CD24 negativity, and/or ALDH1 positivity in flow cytometric studies. We hypothesized that the frequency or density of these cells may be associated with more aggressive tumor behavior. We borrowed these multiplexed, flow-based methods to develop an in situ method to define CSCs in formalin-fixed paraffin-embedded breast cancer tissue, with the goal of assessing the prognostic value of the presence of CSCs in breast cancer. Using a retrospective collection of 321 node-negative and 318 node-positive patients with a mean follow-up time of 12.6 years, we assessed TMAs using the AQUA method for quantitative immunofluorescence. Using a multiplexed assay for ALDH1, CD44, and cytokeratin to measure the coexpression of these proteins, putative CSCs appear in variable sized clusters and in 27 cases (of 490), which showed significantly worse outcome (log rank P = 0.0003). Multivariate analysis showed that this marker combination is independent of tumor size, histological grade, nodal status, ER-, PR,- and HER2-status. In this cohort, ALDH1 expression alone does not significantly predict outcome. We conclude that the multiplexed method of in situ identification of putative CSCs identifies high risk patients in breast cancer.

Lymph node ratio should be considered for incorporation into staging for breast cancer.

BACKGROUND: We sought to determine whether lymph node ratio (LNR; defined as number of positive nodes/number of nodes dissected) provides additional prognostic information in node-positive breast cancer patients. METHODS: Data from a cohort of 319 node-positive breast cancer patients diagnosed between 1956 and 1982 were analyzed for overall survival (OS) on the basis of current American Joint Committee on Cancer (AJCC) nodal staging versus LNR. RESULTS: In terms of AJCC categorization, 157 patients (49.2%) were pN1 (1-3 positive nodes), 97 (30.4%) were pN2 (4-9 positive nodes), and 65 (20.4%) were pN3 (≥10 positive nodes). In terms of LNR, 90 (28.2%) were low risk (LNR = 0.01-0.20), 119 (38.3%) were intermediate risk (LNR = 0.21-0.65), and 110 (34.5%) were high risk (LNR > 0.65). The median follow-up was 68.7 months. AJCC nodal status correlated with OS (median OS 85.9, 70.4, and 48.4 months for pN1-3, respectively, P = 0.018). LNR also correlated with OS (median OS 105.8, 72.2, and 48.4 months for the low-, intermediate-, and high-risk groups, respectively, P < 0.005). On multivariate analysis, LNR predicted OS independent of pN status (P < 0.001). Stratifying by pN status, LNR could discriminate distinct subpopulations of patients with significantly different OS rates. In a multivariate model controlling for clinicopathologic factors (tumor size, grade, estrogen receptor, progesterone receptor, and her-2-neu status), LNR remained a significant predictor of OS (P < 0.001). CONCLUSIONS: LNR has the ability to discriminate populations with different OS rates within traditional AJCC node classification groups and predicts OS independent of traditional clinicopathologic factors. These results should be validated and considered for future incorporation into the breast cancer staging system.

Automated subcellular localization and quantification of protein expression in tissue microarrays.

The recent development of tissue microarrays-composed of hundreds of tissue sections from different tumors arrayed on a single glass slide-facilitates rapid evaluation of large-scale outcome studies. Realization of this potential depends on the ability to rapidly and precisely quantify the protein expression within each tissue spot. We have developed a set of algorithms that allow the rapid, automated, continuous and quantitative analysis of tissue microarrays, including the separation of tumor from stromal elements and the sub-cellular localization of signals. Validation studies using estrogen receptor in breast carcinoma show that automated analysis matches or exceeds the results of conventional pathologist-based scoring. Automated analysis and sub-cellular localization of beta-catenin in colon cancer identifies two novel, prognostically significant tumor subsets, not detected by traditional pathologist-based scoring. Development of automated analysis technology empowers tissue microarrays for use in discovery-type experiments (more typical of cDNA microarrays), with the added advantage of inclusion of long-term demographic and patient outcome information.

Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models.

INTRODUCTION: Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction. METHODS: We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curve and compared it to nested Cox models obtained by robust backward selection procedures. RESULTS: A prognostic index derived from a multivariate Cox regression model incorporating molecular and clinico-pathological covariates (nodal status, tumor size, nuclear grade, and age) is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model. CONCLUSIONS: Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays.

Expression of sorafenib targets in melanoma patients treated with carboplatin, paclitaxel and sorafenib.

BACKGROUND: Sorafenib, a multitarget kinase inhibitor, inhibits members of the mitogen-activated protein kinase (MAPK) pathway and receptor tyrosine kinases, including vascular endothelial growth factor receptor 2 (VEGF-R2). Sorafenib, carboplatin, and paclitaxel (SCP) has antitumor activity in melanoma patients, but no association was found between response and activating B-Raf V600E mutations. We assessed the expression of sorafenib targets in SCP-treated patient specimens and evaluated the association with response and progression-free survival. EXPERIMENTAL DESIGN: Using automated quantitative analysis, we quantified the expression of VEGF-R1, VEGF-R2, VEGF-R3, fibroblast growth factor receptor 1, platelet-derived growth factor receptor beta, c-Kit, B-Raf, C-Raf, meiosis-specific serine/threonine protein kinase 1, and extracellular regulated kinase 1/2 (ERK1/2) in pretreatment specimens from 46 patients. Furthermore, we assessed ERK1/2 expression in 429 archival melanomas. RESULTS: VEGF-R2 expression was significantly higher in patients with a complete or partial response (P = 0.0435), whereas ERK1/2 was higher in patients who did not respond (P = 0.0417). High ERK1/2 was an independent predictor of poor survival. High ERK1/2 was associated with decreased survival in the archival melanoma cohort, suggesting that high ERK1/2-expressing tumors are biologically more aggressive. All of the six patients with both high VEGF-R2 and low ERK1/2 responded to SCP. CONCLUSIONS: High VEGF-R2 expression is associated with response to SCP in melanoma, whereas high ERK1/2 is associated with resistance. Collection of specimens from SCP-treated melanoma patients in a cooperative group phase III trial comparing this regimen with the chemotherapy alone is ongoing, and confirmation of these findings is necessary. These markers might be useful for predicting response to sorafenib when given with other chemotherapies and in other diseases, resulting in the possible elimination of unnecessary treatment of patients unlikely to respond.

Phosphatidylinositol-3-kinase as a therapeutic target in melanoma.

PURPOSE: Phosphatidylinositol-3 kinases (PI3K) are critical for malignant cellular processes including growth, proliferation, and survival, and are targets of drugs in clinical development. We assessed expression of PI3K in melanomas and nevi, and studied associations between PI3K pathway members and in vitro response to a PI3K inhibitor, LY294002. EXPERIMENTAL DESIGN: Using Automated Quantitative Analysis, we quantified expression of p85 and p110alpha subunits in 540 nevi and 523 melanomas. We determined the IC(50) for LY294002 for 11 melanoma cell lines and, using reverse phase protein arrays, assessed the association between levels of PI3K pathway members and sensitivity to LY294002. RESULTS: p85 and p110alpha tend to be coexpressed (P < 0.0001); expression was higher in melanomas than nevi (P < 0.0001) for both subunits, and higher in metastatic than primary melanomas for p85 (P < 0.0001). Although phospho-Akt (pAkt) levels decreased in all cell lines treated with LY294002, sensitivity was variable. We found no association by t tests between baseline p85, p110alpha, and pAkt levels and sensitivity to LY294002, whereas pS6 Ser(235) and Ser(240) were lower in the more resistant cell lines (P = 0.01 and P = 0.004, respectively). CONCLUSIONS: Expression of p85 and p110alpha subunits is up-regulated in melanoma, indicating that PI3K is a good drug target. Pretreatment pS6 levels correlated with sensitivity to the PI3K inhibitor, LY294002, whereas PI3K and pAkt did not, suggesting that full activation of the PI3K pathway is needed for sensitivity to PI3K inhibition. pS6 should be evaluated as a predictor of response in melanoma patients treated with PI3K inhibitors, as these drugs enter clinical trials.

Estrogen receptor co-activator (AIB1) protein expression by automated quantitative analysis (AQUA) in a breast cancer tissue microarray and association with patient outcome.

PURPOSE: Amplified in breast cancer (AIB1 or SRC-3) is an estrogen receptor coregulatory protein that together with other co-activators like transcription intermediary factor 2 (TIF2) and nuclear receptor co-repressor (NCoR), is implicated in estrogen signaling pathway and estrogen regulated tumor progression. We investigated the prognostic significance of AIB1, TIF2 & NCoR protein expression breast tissue microarray (TMA), and studied the relationship of coregulatory proteins to prognostic biomarkers like estrogen (ER), progesterone (PR) & HER2/neu and between coregulatory proteins. METHODS: AIBI, TIF2 & NCoR were studied by fluorescent immunohistochemical staining of a TMA with 670 breast cancer specimens, using AQUA software. RESULT: Using Cox univariate survival analyses, high AIB1 expression was associated with poor patient outcome (P = 0.002), while no association was noted for TIF2 (P = 0.376) & NCoR (P = 0.12). When subclassified by nodal or ER status, AIB1 was not prognostic in the node positive and ER positive subsets. However, in the ER negative and node negative subsets, high AIB1 expression was associated with poor patient outcome (P = 0.02 and P = 0.007 respectively). AIB1 retained its independent association with survival by multivariate analyses (P = 0.028). There was significant positive correlation between AIB1 and ER and PR status and with other cofators (TIF2 and NCoR) but not with HER2/neu status. CONCLUSION: High AIB1 expression was predictive of worse overall survival in our study, suggesting that AIB1 may be critical in breast carcinogenesis.

Expression and prognostic significance of kallikrein-related peptidase 8 protein levels in advanced ovarian cancer by using automated quantitative analysis.

Kallikrein-related peptidases, a subgroup of the serine protease enzyme family, are considered to be important prognostic biomarkers in cancer. In this study we sought to determine the prognostic value of kallikrein-related peptidase 8 (KLK8, hK8, KLK-8) in ovarian cancer using a novel method of compartmentalised in situ protein analysis. A tissue array composed of 150 advanced stage ovarian cancers, uniformly treated with surgical debulking followed by platinum-paclitaxel combination chemotherapy, was constructed. For the evaluation of kallikrein-related peptidase 8 protein expression, we used an immunofluorescence-based method of automated in situ quantitative protein analysis (AQUA). Mean follow-up time of the cohort was 34.35 months. One hundred twenty-six of 150 cases had sufficient tissue for AQUA analysis. There were significant correlations between tumour mask KLK8 protein expression levels and clinicopathological variables, including grade (p = 0.0011), residual disease (p = 0.0063) and clinical response to chemotherapy(p = 0.0346). In univariate survival analysis there was a significant correlation between KLK8 tumour mask expression and five years progression-free survival, meanwhile it was not associated with five-year overall survival (p = 0.0694). Specifically, low KLK8 expression correlated with better outcome (top vs. bottom quartile, p = 0.0319). In multivariate survival analysis, adjusting for well-characterised prognostic variables, tumour KLK8 expression level retained its prognostic significance for progression-free survival (95%CI: 0.341-1.027, p = 0.045). The possibility that KLK8 may be a suitable candidate as a diagnostic and prognostic marker warrants further investigation.

Expression of Aurora A (but not Aurora B) is predictive of survival in breast cancer.

PURPOSE: The cell cycle mediators Aurora A and B are targets of drugs currently in clinical development. As with other targeted therapies in breast cancer, response to therapy might be associated with target expression in tumors. We therefore assessed expression of Aurora A and B in breast tumors and studied associations with clinical/pathologic variables. EXPERIMENTAL DESIGN: Tissue microarrays containing primary specimens from 638 patients with 15-year follow-up were employed to assess expression of Aurora A and B using our automated quantitative analysis method; we used cytokeratin to define pixels as breast cancer (tumor mask) within the array spot and measured Aurora A and B expression within the mask using Cy5-conjugated antibodies. RESULTS: Aurora A and B expression was variable in primary breast tumors. High Aurora A expression was strongly associated with decreased survival (P = 0.0005). On multivariable analysis, it remained an independent prognostic marker. High Aurora A expression was associated with high nuclear grade and high HER-2/neu and progesterone receptor expression. Aurora B expression was not associated with survival. CONCLUSIONS: Aurora A expression defines a population of patients with decreased survival, whereas Aurora B expression does not, suggesting that Aurora A might be the preferred drug target in breast cancer. Aurora A expression in early-stage breast cancer may identify a subset of patients requiring more aggressive or pathway-targeted treatment. Prospective studies are needed to confirm the prognostic role of Aurora A as well as the predictive role of Aurora A expression in patients treated with Aurora A inhibitors.

Defining molecular phenotypes of human papillomavirus-associated oropharyngeal squamous cell carcinoma: validation of three-class hypothesis.

OBJECTIVE: The purpose of this study was to determine if oropharyngeal squamous cell carcinoma (OSCC) classified into three groups based on human papillomavirus (HPV) 16 DNA presence and p16 expression display different protein expression patterns. STUDY DESIGN: Cross-sectional study. SETTING: A laboratory-based study of patients with OSCC treated at a tertiary care academic medical center. SUBJECTS AND METHODS: Paraffin-embedded OSCC specimens from 77 patients classified into the three-class model (HPV negative, HPV inactive [HPV16+/p16-], and HPV active [HPV16+/p16+]) were queried for the expression of 14 tumor progression proteins using AQUA (HistoRx, New Haven CT). Protein expression between groups was assessed by analysis of variance. Global expression patterns were determined by unsupervised hierarchical clustering. RESULTS: There were significant differences in expression of beta-catenin (P = 0.009), epidermal growth factor receptor (P = 0.009), and vascular endothelial growth factor (P = 0.028) between groups. HPV-active tumors had overexpression of beta-catenin. Hierarchical clustering showed HPV-negative and HPV-inactive tumors displayed association patterns distinct from HPV-active tumors. CONCLUSIONS: Tumors classified by HPV DNA presence and p16 expression have different molecular phenotypes. This is the first demonstration of overexpression of beta-catenin (also found in HPV-caused cervical cancer) in HPV-active OSCC. HPV-active OSCC may share a similar ontogeny to HPV-caused cervical cancer.

High HSP90 expression is associated with decreased survival in breast cancer.

The heat shock protein HSP90 chaperones proteins implicated in breast cancer progression, including Her2/neu. HSP90-targeting agents are in clinical trials for breast cancer. HSP90 expression is high in breast cancer cell lines, yet no large studies have been conducted on expression in human tumors and the association with clinical/pathologic variables. Tissue microarrays containing 10 cell lines and primary specimens from 655 patients with 10-year follow-up were assessed using our automated quantitative analysis (AQUA) method; we used cytokeratin to define pixels as breast cancer (tumor mask) within the array spot and measured HSP90 expression within the mask using Cy5-conjugated antibodies. We similarly assessed estrogen receptor, progesterone receptor, and Her2/neu expression. HSP90 expression was more variable in human tumors than in cell lines (P < 0.0001). High HSP90 expression was associated with decreased survival (P = 0.0024). On multivariable analysis, high HSP90 expression remained an independent prognostic marker. High HSP90 expression was associated with high Her2/neu and estrogen receptor, large tumors, high nuclear grade, and lymph node involvement. Although HSP90 levels were high in all our cell lines, expression in tumors was more variable. High HSP90 expression in primary breast cancer defines a population of patients with decreased survival. Evaluation of HSP90 expression in early-stage breast cancer may identify a subset of patients requiring more aggressive or pathway-targeted treatment. Prospective studies are needed to confirm the prognostic role of HSP90, as well as the predictive role of HSP90 expression in patients treated with HSP90 inhibitors.

Expression patterns and prognostic value of Bag-1 and Bcl-2 in breast cancer.

INTRODUCTION: Bcl-2 antanogene-1 (Bag-1) binds the anti-apoptotic mediator Bcl-2, and enhances its activity. Bcl-2 and Bag-1 are associated with chemotherapy resistance in cancer cells. Drugs that target Bcl-2 are currently in clinical development. The purpose of the present study was to examine expression patterns of Bag-1 in a large cohort of breast tumors and to assess the association with Bcl-2, estrogen receptor, progesterone receptor and Her2/neu, and other clinical/pathological variables. METHODS: Tissue microarrays containing primary specimens from 638 patients with 10-year follow-up were employed, and the expression of Bag-1, Bcl-2, estrogen receptor, progesterone receptor and Her2/neu was assessed using our automated quantitative analysis method. We used cytokeratin to define pixels as breast cancer (tumor mask) within the array spot, and we measured biomarker expression within the mask using Cy5 conjugated antibodies. RESULTS: High Bcl-2 expression was associated with improved survival in the entire cohort and in the node-positive subset (P = 0.008 and P = 0.002, respectively). High Bag-1 expression was associated with improved survival in the node-positive subset (P = 0.006). On multivariable analysis, neither Bcl-2 nor Bag-1 retained their independence as prognostic markers. Strong associations were found between Bag-1, Bcl-2, estrogen receptor and progesterone receptor. CONCLUSION: Bag-1 and Bcl-2 expression in breast tumors is associated with improved outcome and steroid receptor positivity. Evaluation of Bcl-2 and Bag-1 expression in breast cancer may identify a subset of patients with a favorable prognosis, who might not benefit from chemotherapy or who might benefit from Bcl-2 targeting agents in addition to antihormonal therapy.

Classification of renal cell carcinoma based on expression of VEGF and VEGF receptors in both tumor cells and endothelial cells.

Recent development of antiangiogenic therapy for renal cell carcinoma (RCC) has significantly improved the treatment of these often refractory tumors. However, not all patients respond to therapy and assays for predicting outcome are needed. As a first step, we analyzed a retrospective cohort of tumors and assessed the ability of VEGF and VEGF receptors (VEGF-R1, -R2 and -R3) to classify tumors. We analyzed tissue microarrays containing 330 RCCs using a novel method of automated quantitative analysis of VEGF and VEGF-R expression by fluorescent immunohistochemistry. Expression of markers was separately quantified within three tissue components: tumor cells, endothelial cells and adjacent normal epithelium. VEGF and VEGF receptors were tightly coexpressed both within tumors and within adjacent normal cells (all P-values <0.001). Tumor cell expression of VEGF-R1 and -R2 was strongly and inversely correlated with vessel area (P<0.0001). Unsupervised hierarchical clustering classified tumors by coordinated expression of VEGF and VEGF-Rs. The distribution of clear cell and papillary tumors was not significantly different between clusters. Clusters with high expression of VEGF and VEGF-Rs in the tumor cells exhibited poor survival when compared with the other clusters on uni- and multivariable analysis. VEGF and VEGF receptors exhibit a complex pattern of coordinated expression in RCC. Clustering tumors by VEGF and VEGF-R in tissue components demonstrates distinct tumor phenotypes with different outcomes, and may provide a means for determining which tumors will respond to what antiangiogenic therapies.

Quantitative in situ analysis of beta-catenin expression in breast cancer shows decreased expression is associated with poor outcome.

The role of beta-catenin in breast cancer and its prognostic value is controversial. The prognostic value had been assessed previously in a series of nonquantitative immunohistochemical studies with conflicting results. In efforts to clarify the relationship between beta-catenin protein expression and breast cancer prognosis, we have assessed a retrospective 600 case cohort of breast cancer tumors from the Yale Pathology archives on tissue microarrays. They were assessed using automated quantitative analysis (AQUA) with a series of array-embedded cell lines for which the beta-catenin concentration was standardized by an ELISA assay. The expression levels of the standard clinical markers HER2, estrogen receptor (ER), progesterone receptor (PR), and Ki-67 were also assessed on the same cohort. X-tile software was used to select optimal protein concentration cutpoints and to evaluate the outcome using a training set and a validation set. We found that low-level expression of membranous beta-catenin is associated with significantly worse outcome (38% versus 76%, 10-year survival, validation set log-rank P = 0.0016). Multivariate analysis of this marker, assessed in a proportional hazards model with tumor size, age, node status, nuclear grade, ER, PR, HER2, and Ki-67, is still highly significant with a hazard ratio of 6.8 (P < 0.0001, 95% confidence interval, 3.1-15.1). These results suggest that loss of beta-catenin expression at the membrane, as assessed by objective quantitative analysis methods, may be useful as a prognostic marker or may be part of a useful algorithm for prognosis in breast cancer.