RESEARCH

 

 

Validation in clinical samples

Key mechanisms and pathways will be studied further in large numbers of clinical samples using high-throughput technologies, both at the genomic level and at the protein level. The main steps in the clinical validation process are:

  1. Creation of a bank of biological resources for large scale clinical validation. An initial repository inventory of retrospective biological resources will be followed by a complementing prospective collection. In total, we aim to obtain the following material for the validation studies:
    • Lung cancer biopsies before treatment (NSCLS 85%, SCLC15%): 500 - 1,000 frozen biopsies, 1,000 serum samples, 1,000 blood leukocyte DNA samples and 1,000  formalin fixed paraffin embedded tumour samples.
    • Melanoma: 300 frozen biopsies of metastases, 800 sera before treatment with DTIC/TMZ, 800 blood leukocyte DNA samples, 1,000 formalin fixed sequential tumour samples and serum samples from over 3,000 patients in randomized trials of IFN therapy.
  1. Generation of validation tools (for both the clinical and preclinical validation).
    • Antibodies. An inventory of commercially available antibodies for the 100 key selected genes will be performed. For genes with missing antibodies, we will generate polyclonal antibodies.
    • siRNA tools. The consortium will generate siRNA tools for 20 to 40 key genes from the 100 candidate gene list. siRNA tools and protocols will be dispatched to all teams involved in preclinical model validations
    • Transfection vectors. The consortium will generate tools for transfection of 20 candidates from the 100 genes list. Tools will be dispatched to teams involved in preclinical model validations.
  1. Validation studies using antibodies
    • Immunohistochemistry studies using tissue microarrays (TMA). Investigations using 30 antibodies each will be performed on lung cancer and melanoma TMA (800 to 1,600 cases of each tumor type).
    • Enzyme-Linked ImmunoSorbent Assay (ELISA) studies using sera. ELISA assays will be optimised for 10 candidate serum biomarkers. A first study will be performed on the discovery cohort using sera before and after treatment for all lung cancer and melanoma patients. If relevant, a predictive model will be established and we will validate prospectively in a large cohort of samples 1,000 patients with lung cancer and 1,000 patients with melanoma using sera before and after treatment.
  1. Validation studies using quantitative RT-PCR. A panel of 96 key genes will be used to generate a gene card. We will profile these candidates for all the patients from the initial cohort using RNAs obtained before and after treatment and build a predictive model on matched pairs, and another using only results obtained with the biopsy before treatment. If the predictor using one biopsy is significant we will perform a large scale validation using 500 to 1000 RNAs from lung cancer and 300 RNAs from melanoma. If the predictor works only by comparing two biopsies, before and after treatment, this will lead to a new standard of biopsy collection.

  1. Promoter methylation investigations to build a predictive model of chemoresistance. If a predictive model is found based on investigations of promoter methylation status in the initial cohort of patients, we plan to perform a validation study  of 500 - 1,000 patients with lung cancer and 300 patients with melanoma.

Page updated by Chemores June 12, 2007
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