Systems and methods for expression-based classification of thyroid tissue

Inventors

Davicioni, Elai • Wiseman, Sam Michael

Assignees

Madryn Health Partners Lp • Veracyte Inc

Abstract

A system for classifying thyroid nodule tissue as malignant or benign is provided that is based on the identification of sets of gene transcripts, which are characterized in that changes in expression of each gene transcript within a set of gene transcripts can be correlated to with either malignant or benign thyroid nodule disease. The thyroid classification system provides for sets of “thyroid classifying” target sequences and further provides for combinations of polynucleotide probes and primers derived there from. These combinations of polynucleotide probes can be provided in solution or as an array. The combination of probes and the arrays can be used for diagnosis. The invention further provides further methods of classifying thyroid nodule tissue.

Core Innovation

The invention relates to expression-based classification of a thyroid nodule using a fine needle aspirate test sample from a subject. It assays the expression level of a first group of transcripts and a second group of transcripts, where the groups correspond to transcript target sequences provided as SEQ ID No. 1-659, by sequencing, array hybridization, or nucleic acid amplification. The classification is performed by comparing measured expression levels to reference expression levels for transcripts corresponding to SEQ ID No. 1 to 659.

The method specifies malignant and benign classification rules based on the direction of expression changes between the two transcript groups. A thyroid nodule is classified as malignant if there is an increase in expression level for the first group or a decrease in expression level for the second group. A thyroid nodule is classified as benign if there is an increase in expression level for the second group or a decrease in expression level for the first group.

The invention uses distinct thyroid classification sets and related transcript target definitions derived from a thyroid classification library. It uses polynucleotide probe and primer sets aligned to sequences in SEQ ID No. 1 to 659 and correlates expression patterns with malignant versus benign disease. The specification further includes approaches for constructing minimal expression signatures and performing comparison to reference patterns using programmed computation.

Claims Coverage

Independent claim clm-00001 covers a computerized method for classifying a thyroid nodule as malignant or benign by comparing assayed expression levels of two transcript groups against reference expression levels corresponding to SEQ ID No. 1 to 659, using directionality rules for expression changes. The claim set includes 2 inventive features, with dependent claims refining the assaying and classification implementation by constraining target sequence membership, restricting expression measurement approaches, and tying classification to treatment modality selections.

Across the independent claim, the core inventive concept is to measure transcript expression from two defined transcript groups in a fine needle aspirate sample and to classify the nodule by programmed comparison to reference expression levels with specified directionality criteria. The dependent claims further narrow which SEQ ID sequences are required in each group, limit expression measurement approaches, and include enumerated treatment modality options.

Stated Advantages

Documented Applications