Genotypic tumor progression classifier and predictor

摘要

Actively dividing tumors appear to progress to a life threatening condition more rapidly than slowly dividing tumors. Assessing actively dividing tumors currently involves a manual assessment of the number of mitotic cells in a histological slide prepared from the tumor and assessed by a trained pathologist. Disclosed is a method for using cumulative information from a series of expressed genes to determine tumor prognosis. This cumulative information can be used to categorize tumor samples into high mitotic states or low mitotic states using a mathematical algorithm and gene expression data derived from microarrays or quantitative-Polymerase Chain Reaction (Q-PCR) data. The specific mathematical description outlines how the algorithm assesses the most informative subset of genes from the full list of genes during the assessment of each sample.

主权项

1. A method of predicting clinical tumor outcome in patients diagnosed with Stage I-III Lung Carcinoma comprising the steps of:
establishing a plurality of gene expression values in a tumor sample wherein the plurality of gene expression values are a plurality of genes identified in Table 1; normalizing the plurality of gene expression values in the tumor sample to a reference expression; defining at least one threshold value for the plurality of gene expressions; establishing a vote of single-gene classifiers further comprising the steps of:
determining individual classifiers, further comprising:
comparing the gene expressions to the at least one threshold value;selecting genes with expression levels above the at least one threshold value;selecting genes with expression levels below the at least one threshold value;assigning a positive value to the selected genes with expression levels above the at least one threshold value and assigning a negative value to the selected genes with expression levels below the at least one threshold value to form probeset data;summing the probeset data to form a risk score; andcomparing the risk score to a sum of the al number of genes tested to form the majority vote classifier;wherein the majority classifier is indicative of tumor outcome, such that the risk ratio above 0.15 is indicative of poor outcome and a risk ratio below 0.15 is indicative of good outcome; administering treatment based on the outcome,
where patients with good prognosis are treated by resection and adjuvant chemotherapy, curative radiation therapy, or curative chemotherapy; andwhere patients with poor prognosis are treated with palliative treatment.