Development and Application of a Microfluidics-Based Panel in the Basal/Luminal Transcriptional Characterization of Archival Bladder Cancers.

In the age of personalized medicine stratifying tumors into molecularly defined subtypes associated with distinctive clinical behaviors and predictable responses to therapies holds tremendous value. Towards this end, we developed a custom microfluidics-based bladder cancer gene expression panel for characterization of archival clinical samples. In silico analysis indicated that the content of our panel was capable of accurately segregating bladder cancers from several public datasets into the clinically relevant basal and luminal subtypes. On a technical level, our bladder cancer panel yielded robust and reproducible results when analyzing formalin-fixed, paraffin-embedded (FFPE) tissues. We applied our panel in the analysis of a novel set of 204 FFPE samples that included non-muscle invasive bladder cancers (NMIBCs), muscle invasive disease (MIBCs), and bladder cancer metastases (METs). We found NMIBCs to be mostly luminal-like, MIBCs to include both luminal- and basal-like types, and METs to be predominantly of a basal-like transcriptional profile. Mutational analysis confirmed the expected enrichment of FGFR3 mutations in luminal samples, and, consistently, FGFR3 IHC showed high protein expression levels of the receptor in these tumors. Our bladder cancer panel enables basal/luminal characterization of FFPE tissues and with further development could be used for stratification of bladder cancer samples in the clinic.

Targeted biomarker profiling of matched primary and metastatic estrogen receptor positive breast cancers.

Patients with newly diagnosed, early stage estrogen receptor positive (ER+) breast cancer often show disease free survival in excess of five years following surgery and systemic adjuvant therapy. An important question is whether diagnostic tumor tissue from the primary lesion offers an accurate molecular portrait of the cancer post recurrence and thus may be used for predictive diagnostic purposes for patients with relapsed, metastatic disease. As the class I phosphatidylinositol 3' kinase (PI3K) pathway is frequently activated in ER+ breast cancer and has been linked to acquired resistance to hormonal therapy, we hypothesized pathway status could evolve over time and treatment. Biomarker analyses were conducted on matched, asynchronous primary and metastatic tumors from 77 patients with ER+ breast cancer. We examined whether PIK3CA and AKT1 alterations or PTEN and Ki67 levels showed differences between primary and metastatic samples. We also sought to look more broadly at gene expression markers reflective of proliferation, molecular subtype, and key receptors and signaling pathways using an mRNA analysis platform developed on the Fluidigm BioMark™ microfluidics system to measure the relative expression of 90 breast cancer related genes in formalin-fixed paraffin-embedded (FFPE) tissue. Application of this panel of biomarker assays to matched tumor pairs showed a high concordance between primary and metastatic tissue, with generally few changes in mutation status, proliferative markers, or gene expression between matched samples. The collection of assays described here has been optimized for FFPE tissue and may have utility in exploratory analyses to identify patient subsets responsive to targeted therapies.

Identification and analysis of in vivo VEGF downstream markers link VEGF pathway activity with efficacy of anti-VEGF therapies.

PURPOSE: The aim of this study was to identify conserved pharmacodynamic and potential predictive biomarkers of response to anti-VEGF therapy using gene expression profiling in preclinical tumor models and in patients. EXPERIMENTAL DESIGN: Surrogate markers of VEGF inhibition [VEGF-dependent genes or VEGF-dependent vasculature (VDV)] were identified by profiling gene expression changes induced in response to VEGF blockade in preclinical tumor models and in human biopsies from patients treated with anti-VEGF monoclonal antibodies. The potential value of VDV genes as candidate predictive biomarkers was tested by correlating high or low VDV gene expression levels in pretreatment clinical samples with the subsequent clinical efficacy of bevacizumab (anti-VEGF)-containing therapy. RESULTS: We show that VDV genes, including direct and more distal VEGF downstream endothelial targets, enable detection of VEGF signaling inhibition in mouse tumor models and human tumor biopsies. Retrospective analyses of clinical trial data indicate that patients with higher VDV expression in pretreatment tumor samples exhibited improved clinical outcome when treated with bevacizumab-containing therapies. CONCLUSIONS: In this work, we identified surrogate markers (VDV genes) for in vivo VEGF signaling in tumors and showed clinical data supporting a correlation between pretreatment VEGF bioactivity and the subsequent efficacy of anti-VEGF therapy. We propose that VDV genes are candidate biomarkers with the potential to aid the selection of novel indications as well as patients likely to respond to anti-VEGF therapy. The data presented here define a diagnostic biomarker hypothesis based on translational research that warrants further evaluation in additional retrospective and prospective trials.