Transcriptomic Marker Set for Plasma Cell Leukemia Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods fail to reliably and specifically identify aggressive forms of plasma cell dyscrasias, such as primary plasma cell leukemia (pPCL), and poorly understand molecular determinants of disease aggressiveness in multiple myeloma, leading to inadequate diagnostic accuracy and treatment outcomes.
Innovation Solution
A marker set based on transcriptomic profiling is developed, comprising coding and non-coding genes associated with biological pathways, which identifies a PCL-like transcriptomic status indicative of high-risk diseases, including pPCL and PCL-like multiple myeloma, using a combination of markers like SDC1, IGLV3-19, and others, and a method involving RNA isolation, expression profile determination, and scoring to classify samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If circulating tumor cell (CTC) levels are used to identify pPCL, then diagnostic simplicity is maintained, but diagnostic accuracy deteriorates (only 2% of patients meet the threshold)
Solution Approach 1:
The diagnostic approach segments the assessment into multiple independent components: conventional CTC counting and a separate transcriptomic profiling system. The transcriptomic system further segments analysis into specific gene marker evaluation (e.g., SDC1, IGLV3-19, PPAPDC1B) and scoring algorithms, allowing each component to be optimized independently for its specific diagnostic purpose.
Solution Approach 2:
The patent introduces transcriptomic profiling as an intermediary diagnostic layer between conventional CTC counting and final disease classification. This intermediary system uses gene expression markers as mediators to identify PCL-like status, providing more accurate classification without requiring direct measurement of circulating tumor cells alone.
2Measurement precision
If conventional risk markers (t(4;14), t(14;16), del17p) are used, then ease of testing is maintained, but diagnostic specificity deteriorates (detectable only in subset of pPCL tumors)
Solution Approach 1:
The transcriptomic marker set provides universal applicability across different pPCL subtypes and disease stages. The gene markers (SDC1, IGLV3-19, PPAPDC1B, etc.) and scoring system can identify PCL-like status in primary pPCL, secondary pPCL, and PCL-like MM patients regardless of specific cytogenetic abnormalities, making the test universally applicable to all plasma cell leukemia variants.
Solution Approach 2:
The diagnostic system uses a composite approach combining multiple gene markers (both coding and non-coding genes) with specific scoring algorithms. This composite transcriptomic profile provides more precise disease identification than single markers or conventional cytogenetic tests, achieving high measurement precision through integration of multiple molecular signals.
3Reliability
If CTC levels ≥20% are used as threshold for pPCL diagnosis, then diagnostic clarity is improved, but sensitivity deteriorates (misses many aggressive cases)
Solution Approach 1:
The patent changes the diagnostic parameter from absolute CTC concentration thresholds to relative transcriptomic expression profiles. By using normalized gene expression scores and comparing them against reference ranges rather than absolute cell counts, the system can detect PCL-like status across the full spectrum of disease severity, from early stages to advanced leukemia, improving both reliability and detection coverage.
Solution Approach 2:
The diagnostic approach transitions from a single-dimensional CTC count measurement to a multi-dimensional transcriptomic profile assessment. By evaluating multiple gene markers simultaneously (SDC1, IGLV3-19, PPAPDC1B, WDR11, ALG14, PHF19, TSC22D1, FAM174A, TSPAN3, CALU, TPM1, VCAM1, IDH2, P2RY6, ASAH1, IGHV1-69, FUCA1, STRN, CYSTM1, APH1B, SLAMF7, YIPF5, APOE, SPATS2, PRKCA, PSME4, SLFN11, RMDN3, CHID1, TMEM45A, TARSL2, DCLRE1C, TCTN3, DAP, DCK, SMOC1, EMC7, LINC00582, KDELR1, APOBEC3B, CRTAP, BRSK1, MZB1, ERI3, DERL3, CENPM, GDE1, FLNA, NCF4, DNASE1L3, ITGA8, SELENOM, AL159169.2, AC092620.1) and calculating composite scores, the system gains additional diagnostic dimensions that capture disease aggressiveness beyond what CTC counts alone can detect.
Data Source
AI summary
The present invention refers to a marker set for determining a PCL-like transcriptomic status in a sample which is indicative for a disease. Further, a method for determining a PCL-like transcriptomic status in a sample is provided by the present invention. In addition, the marker set and/or the method of the present invention is used for selecting an active agent for use in the treatment and/or prevention of a disease. In addition, the present invention refers to kits comprising means for determining the PCL-like transcriptomic status based on the marker set in a sample.