Topics to be covered:

• CTC specific biomarkers and clinical applications
• Advanced CTC and Cancer Stem Cell enrichment, detection and downstream analyses technologies
• Stem Cell technologies

Course Instructors:
John Park, M.D., Associate Clinical Professor, Hematology & Oncology, University of California, San Francisco
Glenn Deng, Ph.D., Senior Scientist, Circulating Tumor Cells, Genetix
Katharina Effenberger, Ph.D., Institute of Tumor Biology, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf
Amir Ali Talasaz, Ph.D., Research Associate, Stanford Genome Technology Center, Stanford University
Ying Liu, Ph.D., M.D., Stem Cells and Regenerative Medicine, Invitrogen
Massimo Cristofanilli, M.D., The University of Texas, MD Anderson Cancer Center

9:00 Chairperson’s Remarks 

BIOMARKERS FOR EARLY DETECTION OF CANCER

9:05 Efficient Diagnosis of Smaller Hepatocellular Carcinoma by Methylated Gene Markers and Classical Tumor Markers in Blood
Toyoki Moribe, Ph.D., Technical Support Team Leader, Array Group, Applied Science Business Unit, Roche Diagnostics K.K.
We have identified novel methylated gene markers specific for hepatocellular carcinoma (HCC) by genome-wide search. We have established new, original algorithms (classifiers) for discriminating HCC from non-HCC patients (chronic hepatitis and liver cirrhosis) in blood. We have efficiently diagnosed HCC of 2cm or smaller using 4 markers combination of 2 methylated gene markers, AFP and PIVKA-II. Early HCC detection by blood-based diagnostics with methylation specific PCR (MSP) would be promising.

9:35 Septin 9, A Novel DNA Methylation Biomarker as a Blood Test for the Early Detection of Colorectal Cancer
Cathy Lofton-Day, Ph.D., Vice President, Molecular Biology & Diagnostics, Epigenomics, Inc.
Disease associated DNA methylation is proving to be a rich source of robust biomarkers for diagnosis, prognosis and drug response prediction, particularly for oncology applications. These tumor and organ specific DNA methylation patterns can be detected in body fluids providing valuable information regarding disease state. A highly sensitive real-time PCR assay that amplifies methylated Septin 9 DNA from the blood of individuals with colorectal cancer (CRC) has been recently shown to be an effective plasma biomarker for CRC detection in several large case control studies and is now in development as an in vitro diagnostic. A prospective clinical trial is ongoing to describe the clinical performance of the Septin 9 biomarker in the colorectal screening population. Non-invasive and minimally invasive tests, particularly those that utilize a blood sample are more likely to improve patient compliance to routine screening. This and other body fluid biomarkers currently in development may offer the opportunity to introduce convenient cancer screening tests that drive screening compliance and thereby reduce cancer mortality.

10:05 Protein Biomarkers for Oral SCC and MALT Lymphoma
Shen Hu, Ph.D., Assistant Professor, Proteomics and Oral Biology, UCLA School of Dentistry
I will talk about the protein biomarkers for oral squamous cell carcinoma and mucosa-associated lymphoid tissue lymphoma that we recently discovered using proteomics approaches. These biomarkers have been successfully validated using immunoassays, and may allow for early detection of these disease conditions in dental clinics.

10:35 Networking Break

11:00 Discovery of miRNA-Based Biomarkers for Cancer 
Søren Møller, Ph.D., Vice President Research & Development, Exiqon A/S 
Abnormal expression of microRNAs (miRNAs) in cancer implies that these small ~22-nucleotide molecules play a role in oncogenesis. Therefore miRNAs may comprise a novel class of diagnostic and prognostic signatures. This talk will focus on examples of using microRNA for cancer classification, prognosis and treatment selection.

11:30 A miRNA qRT-PCR Assay that Differentiates Pancreatic Ductal Adenocarcinoma from Chronic Pancreatitis 
Anna Szafranska-Schwarzbach, Ph.D., CLIA Laboratory Supervisor, Pharmacogenomics Services, Asuragen
Using microarray and qRT-PCR platforms we identified miR-196a and miR-217 as the top biomarker candidates that distinguish pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis. The qRT-PCR assay developed using this microRNA (miRNA) signature was validated using formalin-fixed, paraffin embedded (FFPE) pancreatic blocks and achieved 95.24% sensitivity and 94.87% specificity. Early feasibility experiments showed that the assay can also be successfully used to identify PDAC in low tissue yielding clinical specimens, such as fine needle aspirate biopsies. In addition, interrogation of microdissected populations of normal, pre-malignant and malignant cells revealed that miR-196a is specific to PDAC cells and can be detected as early as in PanIn-2 precursor lesions. Our ongoing efforts will assess whether elevated expression of miR-196a in pancreatic tissue may enable earlier identification of patients at high risk to develop PDAC in the future.

12:00 Lunch on your own

BIOMARKERS FOR CANCER PROGNOSIS AND THERAPY SELECTION 

2:00 Evaluating Risk for Future Tumor Formation
Thea D. Tlsty, Ph.D., Professor, Department of Pathology, University of California, San Francisco
Our ability to determine future tumor formation in women diagnosed with ductal carcinoma in situ (DCIS) is currently limited. Here we describe distinct subsets of molecular markers that identify women that have an increased risk or decreased risk of developing subsequent tumor events after diagnosis of DCIS. The markers for increased risk also characterize a subset of invasive tumors known as the "basal-like" subtype and provide a biological rationale for the aggressive malignant phenotypes associated with this sub-classification of tumors. This information could be used in the clinic to determine which women should receive more or less aggressive therapy.

2:30 Development of Clinically Relevant Gene Expression Profiles for Prognosis of Early Stage Breast Cancer
Richard Bender, M.D., F.A.C.P., Chief Medical Officer, Agendia, Inc.
Gene Expression Profiling is rapidly becoming the new frontier for the development of biomarkers for the diagnosis of disease, for the assessment of prognosis and for the prediction of the likelihood of responding to a particular drug or class of drugs. The ability to analyze patient groups with multi-gene profiles using either RT-PCR or microarray oftentimes belies the complexity of the clinical question and is subject to over-fitting the data as many genes are used to discriminate between 2 groups of patients , oftentimes simply responders or non-responders, "low" risk or "high" risk or disease present or absent groups. As such, meticulous attention to all experimental details from extraction of genomic material from patient specimens to interpretation of gene expression, experimental details must be rigidly controlled. As interpretation of the multi-gene readout is not "intuitive" to the ordering physician (unlike a single analyte assay, such as CA 27-29) requiring a "black box" mathematical algorithm to generate or risk profile or result, the FDA has issued IVDMIA Guidance for the Industry, suggesting how these assays need to be regulated. The presentation will discuss the process of assay development for breast cancer prognosis as a way of illustrating the key steps in this process and will review the latest developments in governmental oversight.

3:00 in vivo Discovery and Validation of Biomarkers of Human Drug Response and Resistance
Joerg Heyer, Ph.D., Principal Scientist, Group Leader, Genetic Models, AVEO Pharmaceuticals, Inc.
With the emerging elucidation and understanding of the human genome, the complexities of genetic changes in cancer have become apparent. Traditional models of preclinical research and development have generally not recapitulated the dynamics of the genome found in cancer. New approaches to genetically engineered models, i.e. exploiting the natural diversity of signaling pathways in genetically engineered cancer model, or generating spontaneous human tumors in tissue transplantation models, have shown great promise to faithfully capture the complexity of genomic changes seen in cancer. We have generated a Human Response Prediction approach, based on natural occurring variation in our genetically defined models of cancer, which allows to us identify genetic biomarkers of therapeutic response.

3:30 Networking Break

4:00 Industrialized Proteomics for the Discovery and Validation of Oncology Biomarkers
Joanna Hunter, Ph.D., Director, Protein Analysis, Caprion
The success of many investigational drugs is dependent on matching treatments with the appropriate target populations. Variability in response to therapy, both with regards to efficacy and to adverse events, is leading the pharmaceutical industry down the path of personalized medicine. Further pushing the process along are government and private insurance payors who are faced with very expensive treatments that can help some but provide little benefit and possible harm to others. One promising solution to the problem is to identify predictive biomarkers of drug efficacy; circulating proteins that stratify patients into populations of likely responders and non-responders to a proposed therapy. Finding such biomarkers has been challenging due to the complexity of human plasma, the sample of choice, and to the available technologies for detection and quantification of thousands of proteins. Based on the experience of over two dozen preclinical and clinical proteomic studies with pharmaceutical partners, an “industrialized” and very productive approach to biomarker discovery and validation has been developed. Results from multiple oncology biomarker discovery studies will be presented that make the case for accelerating the move to personalized medicine.

4:30 Metabolite Biomarkers of Prostate Cancer Aggressivity
Jeffrey Shuster, Ph.D., Director, Diagnostic Development, Metabolon, Inc.
Even with all diagnostics methods in use today, it is difficult to determine with surety which prostate cancers are indolent, and which are aggressive and have the potential to metastasize. Diagnostic tests that distinguish indolent from aggressive tumors have the potential to reduce the number of unnecessary biopsies and prostatectomies. Prostate cancer aggressivity was investigated at the biochemical level using metabolomics with urine from men at-risk for prostate cancer, and from post-surgical prostate tissue. The results identified sets of mechanism-based biomarkers correlated with prostate cancer aggressivity. In this talk, we will briefly describe the metabolomics platform and its utility for developing cancer diagnostics.

5:00 Close of Day