The Addario Lung Cancer Medical Institute (ALCMI)

Collaborative Advanced Stage Tissue Lung Cancer (CASTLE) Network

Scientific Leadership Team
• David P. Carbone, MD, PhD, Vanderbilt University, Nashville, TN
• David Gandara, MD, University of California, Davis, CA
• David Jablons, MD, University of California, San Francisco, CA
• Pasi Jänne, MD, PhD, Dana-Farber Cancer Institute, MA
• Ite Laird-Offringa, PhD, University of Southern California, CA
• Harvey Pass, MD, New York University, NY
• Rafael Rosell, MD, PhD, Catalan Institute of Oncology, Spain
  

   

Specific Aims:

1. To collect, process, store, and distribute tumor-related and normal biospecimens from advanced stage lung cancer patients in support of ALCMI-approved research projects.
2. To maintain a centralized, computerized database of all specimens with uniform and complete demographic, pathologic, and clinical information
3. To facilitate integration of molecular assays and other laboratory studies with demographic data and clinical outcomes.

Inclusion Criteria:

• M1A or B NSCLC or any stage Small cell Lung Cancer (SCLC) with any number of prior therapies.
• Planned systemic therapy.
• Provision of written informed consent for biospecimen storage, broad genetic and proteomic analysis of tumor and normal tissues, without restrictions, AND correlation with outcome data.
• Aged 18 years and over.
• Measurable or evaluable disease.
• ECOG performance status of 0-2 (see Appendix A) with expected survival of at least 3 months.
• serum:  EGFR-TKI predictive response
• tumor: EGFR exon 19 and 21 mutations, KRAS codon 12 mutations, ALK fusions, and TS, ERCC1, and RRM1 expression
• Tumor specimens:
• First Priority: availability of a minimum of a 1 X 10 mm core fresh frozen tumor and normal tissues from clinically indicated interventional procedures, with no intervening treatment between collection of the biopsy and entry into the study.
       or
• Second Priority: availability of paraffin-embedded tumor and adjacent normal tissue (when available) at least 5 X 5 mm cross-sectional tumor area, with no intervening treatment between collection of the biopsy and entry into the study.
• Willingness to undergo all study collection procedures and sample analyses.

Exclusion Criteria: 

• Other co-existing malignancies except for basal cell carcinoma or cervical cancer in situ.
• Compromise of patient diagnosis or staging if tissue is harvested for research.

Study Schema:

	Pre-study	CASTLE Enrollment	At disease progression	Survival follow-up every 3 months
Informed consent		X
Data Set		X	X	X
Tumor	X		X*
Plasma		X	X
Serum		X	X
PAXgene DNA		X
PAXgene RNA		X

* when available from remainder of diagnostic sample

Summary:

In response to systematic barriers to progress against lung cancer, the Addario Lung Cancer Medical Institute (ALCMI) has developed, and will soon publically launch, a targeted, multi-institutional tissue and data repository. The first biospecimens and data will be collected under the CASTLE Network, with future projects including correlative studies in parallel with clinical trials.The CASTLE Network will be the only resource of its kind in lung cancer that facilitates the collection of biospecimens from advanced lung cancer patients and routine determination of a panel of documented clinically significant biomarkers.  In addition, it will go beyond this to centrally integrate and standardize research tissue samples with corresponding proteomic, genomic, molecular and clinical data across a multitude of institutions and oncology networks. This kind of transformative research resource, defined as a large, well-annotated, uniformly collected, fresh flash-frozen collection of advanced stage lung cancer tissues, simply does not exist anywhere and it is our intention to rapidly develop and implement this in concert with the lung cancer clinical research and therapeutic communities.  These unique resources will then be applied to identify and validate optimal molecular targets for lung cancer and drugs active against biologic and molecular targets, as well as enable correlative studies to determine patients’ responses to standard of care and emerging therapies.  The ALCMI CASTLE Network will help lead the way as the lung cancer research community’s premier, open access source for high quality proteomics, genomics, target validation, and correlative science analyses.In addition to the leading academic lung cancer centers of excellence, a central facet of ALCMI’s strategic plan is to integrate community-based investigators and clinicians into these translational research efforts. The resultant ALCMI Biorepository will be comprised of high-quality, standardized, annotated tumor and normal tissue samples, and serve as an open resource to academic and community researchers in the United States. It will also form a foundation for collaboration with the National Institutes of Health and the biopharmaceutical industry for target/agent discovery and validation, genomics and proteomics—thus bringing new and improved treatment options to lung cancer patients in need.The ALCMI Data Bank will enable centralized biological specimen tracking from “cradle to grave”  to comply with regulations, satisfy study subject consent requirements, enhance scientific accuracy, and improve development efficiency.

Molecular Analyses:

The biospecimens collected in CASTLE will be analyzed for a panel of biomarkers chosen by ALCMI’s Scientific Leadership Board (SLB) with the greatest level of evidence connecting them to clinical management decisions.  The current panel of analytes includes:These diagnostic/prognostic screenings are to be performed in CLIA-compliant laboratory settings utilizing documented, clinically-significant biomarkers and algorithms with test reports directly returned to the submitting physicians/institutions by the testing laboratories.These panels, which have been shown in multiple studies to have prognostic importance and/or be associated with benefit from specific interventions as described in the NCCN 2009 Clinical Practice Guidelines in Oncology, may be updated in response to generally accepted new scientific findings.