Antibodies are among the most frequently used tools in basic science research and in clinical assays, but there are no universally accepted guidelines or standardized methods for determining the validity of these reagents. Furthermore, for commercially available antibodies, it is clear that what is on the label does not necessarily correspond to what is in the tube. To validate an antibody, it must be shown to be specific, selective, and reproducible in the context for which it is to be used. In this review, we highlight the common pitfalls when working with antibodies, common practices for validating antibodies, and levels of commercial antibody validation for seven vendors. Finally, we share our algorithm for antibody validation for immunohistochemistry and quantitative immunofluorescence.

We demonstrate an integrated approach to the study of a transcriptional regulatory cascade involved in the progression of breast cancer and we identify a protein associated with disease progression. Using chromatin immunoprecipitation and genome tiling arrays, whole genome mapping of transcription factor-binding sites was combined with gene expression profiling to identify genes involved in the proliferative response to estrogen (E2). Using RNA interference, selected ERa and c-MYC gene targets were knocked down to identify mediators of E2-stimulated cell proliferation. Tissue microarray screening revealed that high expression of an epigenetic factor, the E2-inducible histone variant H2A.Z, is significantly associated with lymph node metastasis and decreased breast cancer survival. Detection of H2A.Z levels independently increased the prognostic power of biomarkers currently in clinical use. This integrated approach has accelerated the identification of a molecule linked to breast cancer progression, has implications for diagnostic and therapeutic interventions, and can be applied to a wide range of cancers.

No abstract

Background Microtubule associated proteins (MAPs) endogenously regulate microtubule stability. Here we assess the prognostic value of stathmin, a destabilizing protein in combination with MAP-tau, a stabilizing protein, in order to assess microtubule stabilization as a potential biomarker. Methods Stathmin and MAP-tau expression levels were measured in a breast cancer cohort (n = 651) using the tissue microarray format and quantitative immunofluorescence (AQUA) technology, then correlated with clinical and pathological characteristics and disease free survival. Results Univariate Cox proportional hazards (PH) models indicated that high stathmin expression predicts worse overall survival (HR = 1.48; 95% CI = 1.119–1.966; P = 0.0061). Survival analysis showed 10-year survival of 53.1% for patients with high stathmin expression versus 67% for low expressers (log rank, P<.003). Cox multivariate analysis showed high stathmin expression was independent of age, menopausal status, nodal status, nuclear grade, tumor size, ER, PR, and HER2 expression (HR = 1.19; 95% CI= 1.03–1.37; P = 0.01). The ratio of MAP-tau to stathmin expression showed a positive correlation to disease free survival (HR = 0.679; 95% CI = 0.517–0.891; P = 0.0053) with a 10-year survival of 65.4% for patients with high MAP-tau to stathmin ratio versus 52.5% survival rate for low ratio (log rank, P = 0.0009). Cox multivariate showed MAP-tau to stathmin ratio was an independent predictor of overall survival (HR = 0.609; 95% CI = 0.422–0.879; P = 0.008). Conclusion Low stathmin and high MAP-tau are associated with increased microtubule stability and better prognosis in breast cancer.

IntroductionMicrotubule 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.MethodsMAP-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.ResultsAssessment 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).ConclusionsQuantitative 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.

IntroductionBiomarkers, such as Estrogen Receptor, are used to determine therapy and prognosis in breast carcinoma. Immunostaining assays of biomarker expression have a high rate of inaccuracy; for example, estimates are as high as 20% for Estrogen Receptor. Biomarkers have been shown to be heterogeneously expressed in breast tumors and this heterogeneity may contribute to the inaccuracy of immunostaining assays. Currently, no evidence-based standards exist for the amount of tumor that must be sampled in order to correct for biomarker heterogeneity. The aim of this study was to determine the optimal number of 20X fields that are necessary to estimate a representative measurement of expression in a whole tissue section for selected biomarkers: ER, HER-2, AKT, ERK, S6K1, GAPDH, Cytokeratin, and MAP-Tau.MethodsTwo collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using the Automated Quantitative Analysis (AQUA) method of quantitative immunofluorescence. Simulated sampling of various numbers of fields (ranging from one to thirty five) was performed for each marker. The optimal number was selected for each marker via resampling techniques and minimization of prediction error over an independent test set.ResultsThe optimal number of 20X fields varied by biomarker, ranging between three to fourteen fields. More heterogeneous markers, such as MAP-Tau protein, required a larger sample of 20X fields to produce representative measurement.ConclusionsThe optimal number of 20X fields that must be sampled to produce a representative measurement of biomarker expression varies by marker with more heterogeneous markers requiring a larger number. The clinical implication of these findings is that breast biopsies consisting of a small number of fields may be inadequate to represent whole tumor biomarker expression for many markers. Additionally, for biomarkers newly introduced into clinical use, especially if therapeutic response is dictated by level of expression, the optimal size of tissue sample must be determined on a marker-by-marker basis.

Bast Jr RC. DIRAS3 regulates the autophagosome initiation complex in dormant ovarian cancer cells.

No abstract