Methods and systems for predicting response to anti-TNF therapies
Inventors
Johnson, Keith J. • Ghiassian, Susan Dina
Assignees
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Publication Number
US-11198727-B2
Publication Date
2021-12-14
Expiration Date
Abstract
Methods and systems for administering anti-TNF therapy to subjects who have been determined to display a gene expression response signature established to distinguish between responsive and non-responsive prior subjects who have received the anti-TNF therapy.
Core Innovation
The disclosure addresses a problem in treating subjects suffering from an autoimmune disease, disorder or condition with anti-TNF therapy by improving prediction of non-response. Conventional classifiers based on high fold-change differences are described as inadequate for selecting responders versus non-responders, and the approach instead focuses on identifying genes that show statistically significant differences in expression level between responders and non-responders, including genes with small expression differences.
The method obtains a validated gene expression response signature indicative of non-response to anti-TNF therapy using a validated classifier. Gene expression levels in biological samples from a first cohort of prior subjects who previously received anti-TNF therapy are analyzed to identify signature genes, the signature genes are mapped onto a human interactome to select a subset that maps onto a connected module, and a classifier is trained on expression levels of genes in the candidate gene list to identify prior subjects unlikely to respond.
A validated classifier is obtained by validating the trained classifier on a second cohort that is an independent and blinded group of responders and non-responders, with selection of a cutoff score to meet true negative rate (TNR) and negative predictive value (NPV) thresholds. Subjects predicted as non-responders display the validated gene expression response signature, and subjects not in that group lack the validated gene expression response signature. The disclosure characterizes treating subjects who lack the validated gene expression response signature with anti-TNF therapy, where the anti-TNF therapy is an antibody or a decoy circulating receptor fusion protein.
Claims Coverage
The disclosure includes one independent claim, with multiple dependent claims that refine performance thresholds, cohort composition, disease/agent scope, gene selection, and measurement modalities. The core independent claim covers patient stratification for anti-TNF treatment based on the absence of a validated gene expression response signature indicative of non-response, determined by a specific validated classifier obtained via interactome-connected-module gene selection and blinded independent cohort validation with defined TNR/NPV cutoff performance.
Validated non-response gene expression signature guided anti-TNF treatment selection
A method of treating subjects suffering from an autoimmune disease, disorder or condition with anti-TNF therapy by administering the anti-TNF therapy to subjects assessed to lack a validated gene expression response signature indicative of non-response, wherein absence of the validated gene expression response signature is determined by a validated classifier.
Interactome-connected module signature gene selection
A validated classifier is obtained by analyzing gene expression levels in biological samples from a first cohort of prior subjects previously received anti-TNF therapy and identified as responders or non-responders to identify signature genes with statistically significant differences in expression, mapping the signature genes onto a human interactome, and selecting a subset mapping onto a connected module of the human interactome as a candidate gene list.
Validated classifier training with TNR/NPV cutoff for non-response prediction
Training a classifier on expression levels of genes of the candidate gene list from the first cohort to identify a subset of prior subjects unlikely to respond, obtaining the validated classifier by validating the trained classifier on a second cohort comprising an independent and blinded group of responders and non-responders, and selecting a cutoff score so the validated classifier predicts non-responders with a true negative rate (TNR) of at least 0.5 and a negative predictive value (NPV) of at least 0.9 such that subjects in the predicted non-responders group display the validated gene expression response signature and subjects that do not fall within that group lack the validated gene expression response signature.
Anti-TNF therapy as antibody or decoy circulating receptor fusion protein
The method where the anti-TNF therapy is an antibody or a decoy circulating receptor fusion protein.
Overall claim coverage centers on validated prediction of anti-TNF non-response from a gene expression response signature defined by statistically significant responder/non-responder gene differences, interactome mapping to a connected module, classifier training, and independent blinded cohort validation using TNR and NPV cutoff thresholds; anti-TNF treatment is administered to subjects lacking the validated signature.
Stated Advantages
Predict non-responders with a true negative rate (TNR) of at least 0.5 and negative predictive value (NPV) of at least 0.9 using a validated classifier and selected cutoff score.
Use of a validated gene expression response signature to classify subjects based on whether they lack or display the validated signature indicative of non-response to anti-TNF therapy.
Documented Applications
Treatment stratification for subjects with an autoimmune disease, disorder or condition using anti-TNF therapy based on assessment of whether subjects lack a validated gene expression response signature indicative of non-response.
Performance validation in cohorts including ulcerative colitis (UC) and rheumatoid arthritis (RA) using gene expression response signatures and validated classifiers for responders versus non-responders.
Anti-TNF therapy examples and coverage of treating subjects using specified anti-TNF agents or their biosimilars, including antibodies and a decoy circulating receptor fusion protein.
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