Long non-coding RNA gene expression signatures in disease monitoring and treatment
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Publication Number
US-10982259-B2
Publication Date
2021-04-20
Expiration Date
Abstract
Differential expression of long non-coding RNAs (lncRNAs) and enhancer RNAs (eRNAs) are used to monitor diseases and determine therapeutic efficacy in, for example, neurological diseases, inflammatory diseases, rheumatic diseases, and autoimmune diseases. Machine learning systems are used to identify lncRNAs or eRNAs having differential expression correlated with responsiveness to various therapies.
Core Innovation
The disclosed invention relates to monitoring disease progression of multiple sclerosis in a subject by conducting an assay on a first sample and a second sample collected at a later point in time than the first sample. The assay measures expression levels of one or more long non-coding RNA (lncRNA) species and compares the measured expression levels to a reference expression level to determine differential expression in the first and second samples. Disease progression of multiple sclerosis is determined based on an increase or decrease in differential expression between the first and second samples.
The method is performed in a clinical context where the patient receives a treatment for multiple sclerosis between collection of the first and second samples. Based on the determined disease progression, therapeutic efficacy of the treatment is determined, linking changes in differential lncRNA expression over time to treatment-related outcomes.
In the broader disclosure, differential expression of long non-coding RNAs (lncRNAs) and enhancer RNAs (eRNAs) is assessed in patient sample series over time to monitor disease progression and therapeutic efficacy. The disclosure includes options for normalization using housekeeping genes and supports classification-based workflows using machine learning classifiers to identify therapeutic response biomarkers and to support monitoring and prediction.
Claims Coverage
The independent claim recites one core inventive method with multiple claim refinements. The main inventive features involve longitudinal comparison of lncRNA differential expression using a reference expression level, inferring multiple sclerosis disease progression from an increase or decrease in that differential expression, and associating the inferred progression with treatment administered between sample collections. Dependent claims further narrow the assay modality, interpretation of directionality, and normalization approach using housekeeping genes.
Longitudinal lncRNA differential expression comparison to a reference level
Conduct an assay on a first sample and a second sample collected from a patient at a later point in time than the first sample to measure expression levels of one or more lncRNA species; comparing the expression levels to a reference expression level to determine differential expression of the lncRNA gene in the first and second samples.
Multiple sclerosis progression determined from increase or decrease in differential expression
Determine disease progression of multiple sclerosis based on an increase or decrease in differential expression between the lncRNA gene in the first and second samples.
Treatment administered between sample collections linked to progression determination
Provide that the patient receives a treatment for the disease in between collection of the first and second samples.
Disease progression direction interpreted as lower disease burden when differential expression decreases
Determine that a decrease in differential expression between the first and second samples indicates a lower disease burden.
Therapeutic efficacy determined based on the determined disease progression
Determine the therapeutic efficacy of the treatment based on the determined disease progression.
RT-PCR assay of lncRNA expression in the first and second samples
Characterize the method such that the assay uses reverse transcription polymerase chain reaction (RT-PCR).
Normalization of lncRNA expression using housekeeping gene expression from the samples
Use RNA from the first and second samples to measure housekeeping gene expression and normalize lncRNA gene expression to the housekeeping gene expression.
Housekeeping gene selected from a defined set
Select the housekeeping gene from GAPDH, ACTB, B2M, 18S, or 28S.
Across the independent claim and its dependents, the inventive coverage centers on longitudinal lncRNA differential expression measured relative to a reference level and used to infer multiple sclerosis disease progression from an increase or decrease. Additional coverage ties the progression determination to treatment administered between sample collections, with dependent claims narrowing the assay to RT-PCR and adding housekeeping-gene normalization using a defined housekeeping gene set.
Stated Advantages
Enables monitoring of multiple sclerosis disease progression based on changes in lncRNA differential expression between a first and a later sample.
Provides a basis for determining therapeutic efficacy of treatment based on the determined disease progression.
Documented Applications
Monitoring multiple sclerosis disease progression in a subject using assays on patient samples collected at two time points.
Assessing therapeutic efficacy of a treatment for multiple sclerosis using progression determined from differential lncRNA expression.
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