	US 12,215,388 B2
	Theranostic tools for management of pancreatic cancer and its precursors
Jennifer Permuth, Tampa, FL (US); Daniel Jeong, Tampa, FL (US); Jung Choi, Wesley Chapel, FL (US); Yoganand Balagurunathan, Tampa, FL (US); Dung-Tsa Chen, Tampa, FL (US); and Mokenge Malafa, Tampa, FL (US)
Assigned to Lee Moffitt Cancer Center and Research Institute, Inc., Tampa, FL (US)
Appl. No. 16/610,001
Filed by H. LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE, INC., Tampa, FL (US)
PCT Filed May 3, 2018, PCT No. PCT/US2018/030994 § 371(c)(1), (2) Date Oct. 31, 2019, PCT Pub. No. WO2018/204725, PCT Pub. Date Nov. 8, 2018.
Claims priority of provisional application 62/501,040, filed on May 3, 2017.
Prior Publication US 2020/0063215 A1, Feb. 27, 2020
This patent is subject to a terminal disclaimer.
Int. Cl. C12Q 1/6886 (2018.01)

CPC C12Q 1/6886 (2013.01) [C12Q 2600/112 (2013.01); C12Q 2600/158 (2013.01); C12Q 2600/178 (2013.01)]

15 Claims

1. A method for detecting microRNAs (miRNA) and long non-coding RNAs (IncRNAs) in human blood and assessing radiomic features, from a human subject having an intraductal papillary mucinous neoplasm (IPMN) comprising:

detecting a level of each of the following miRNAs in a blood sample from the human subject: miR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-4p, and miR-663b; wherein said detecting is carried out using a method selected from among hybridization assay, RNA sequencing, or amplification assay;

detecting a level of each of the following lncRNAs in the blood sample from the human subject: ADARB2-AS1, ANRIL, GLIS3-AS1, LINC00472, MEG3, PANDA, PVT1, and UCA1; and

extracting quantitative radiomic features from an image of abdominal visceral fat from the human subject; wherein the quantitative radiomic features comprise one or more of the following: Fourier Descriptor Layer 1, Histogram Energy Layer 1, Histogram Entropy Layer 1, Co-occurrence matrix features OF1G1 CONTRAST Layer 1, Run-length features G1 DO HGRE Layer 1, Run-length features G1 DO LGRE Layer 1, Laws features E5 E5 Energy Layer 1, Laws features L5 S5 Energy Layer 1, Laws features R5 E5 Energy Layer 1, Wavelet decomposition P1 L3 C1 Layer 1, Wavelet decomposition P1 L3 C2 Layer 1, Border length (Pxl), Width (Pxl), and Radius of largest enclosed ellipse.