Methods for melanoma detection

Inactive Publication Date: 2018-11-29
LIQUID BIOPSY RES LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The patent text describes a tool that can help detect melanoma with high levels of accuracy. This tool can tell the difference between aggressive melanoma that has not been treated and stable melanoma that has been treated.

Problems solved by technology

Melanoma, however, lacks a clinically useful non-invasive e.g., blood-based biomarker of disease activity to help guide patient management by providing predictive or prognostic information.
Mutations in target genes, like BRAF, can be detected in the blood in ctDNA but its utility as an indicator of therapeutic efficacy is limited e.g., 45-70% accurate.
Circulating microNAs (miRNA) have been detected but there is no evidence yet for clinical usefulness.
A biomarker that can be used to monitor the efficacy of surgery or drug therapy in melanomas is currently lacking.

Method used

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  • Methods for melanoma detection
  • Methods for melanoma detection
  • Methods for melanoma detection

Examples

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example 1

[0080]Derivation of a 28-Marker Gene Panel

[0081]Raw probe intensities (n=6,892,960 features) from n=49 whole blood samples were used to identify genes that best discriminated between different types of melanoma samples e.g., treated versus untreated, simultaneously. A total of 28 transcripts were identified in an unbiased manner as potential markers of melanoma behavior (Table 2).

[0082]An artificial intelligence model of melanoma disease dynamics was built using normalized gene expression of these 28 markers in whole blood from Controls (n=90), Responders / Stable (n=68), and Progressive (n=66) samples. The dataset was randomly split into training (n=169) and testing (n=55) partitions for model creation and validation respectively. Five algorithms (XGB, RF, TreeBag, SVM, NNET) were identified that best predicted the training data. In the test set, each algorithm produced probability scores that predicted the sample. Each probability score reflects the “certainty” of an algorithm that ...

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Abstract

The present invention is directed to methods for detecting a melanoma, methods for determining whether a melanoma is stable or progressive, methods for evaluating the extent of surgery resection in a subject having a melanoma, and methods for determining a response by a subject having a melanoma to a therapy.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of and priority to U.S. Provisional Application No. 62 / 511,058, filed on May 25, 2017, the contents of which are hereby incorporated by reference.INCORPORATION BY REFERENCE OF SEQUENCE LISTING[0002]The contents of the text file named “LBIO-001_001US_SEQ LISTING.txt”, which was created on May 12, 2018 and is 265 kB in size, are hereby incorporated by reference in their entireties.FIELD OF THE INVENTION[0003]The present invention relates to melanoma detection.BACKGROUND OF THE INVENTION[0004]Melanoma is a common (˜24-35 / 100,000 incidence—US), highly aggressive, skin cancer with an incidence that continues to rise. The most common, cutaneous melanomas, are associated with UV exposure and immune dysregulation. As a group, melanoma is known to carry the highest mutational burden (>10 mutations / Mb). Major mutations include BRAF (˜50%), N-Ras (˜20%) and NF-1 (˜5%), which together, comprise 75% of all mutati...

Claims

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Application Information

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IPC IPC(8): G01N33/574G01N33/53G01N33/58
CPCG01N33/5743G01N33/5308G01N33/582G01N2800/7028G01N2800/52G01N2800/56G01N2800/60A61P17/00A61P35/00A61K39/3955C12Q1/6886C12Q2600/106C12Q2600/118C12Q2600/158C12Q2563/107
InventorMODLIN, IRVIN MARKKIDD, MARKDROZDOV, IGNAT
OwnerLIQUID BIOPSY RES LLC