METHODS FOR ANALYSIS OF TARGET MOLECULES IN BIOLOGICAL FLUIDS
Methods for measuring subpopulations of target molecules (e.g., polypeptides and/or cell-free ribonucleic acid) are provided. In some embodiments, methods of generating a sequencing library from a plurality of RNA molecules in a test sample obtained from a subject are provided, as well as methods for analyzing the sequencing library to detect, e.g., the presence or absence of a disease.
1 . A method of detecting cancer in a subject, the method comprising:
(a) measuring a plurality of target molecules in a biological fluid of the subject, wherein the plurality of target molecules are selected from polypeptides of Table 11; and
(b) detecting the cancer, wherein detecting the cancer comprises detecting one or more of the target molecules above a threshold level.
2 . The method of claim 1 , wherein the plurality of target molecules are selected from polypeptides of one or more of Tables 8 or 12-19.
3 . The method of claim 1 , wherein the plurality of target molecules are selected from at least 5, 10, 15, or 20 polypeptides of Tables 8, 11-14 or 17-19.
4 . The method of claim 1 , wherein the plurality of target molecules comprises a plurality of polypeptides from (i) Table 11; (ii) each of Tables 2, 5, and 12, (iii) each of Tables 3, 4, 6, and 13, (iv) Table 14, (v) Table 8, or (vi) Tables 18 and 19.
5 . (canceled)
6 . (canceled)
7 . The method of claim 1 , wherein the plurality of target molecules detected above a threshold are polypeptides selected from the group consisting of: ADAMTS15, AFP, AGR2, AIF1, ALPP, BPIFB2, CEACAM5, CGA, CHGA, CWC15, CXCL17, DXO, ERBB2, ERBB4, F7, FGFBP1, FGFR2, FKBPL, FOLR1, GDF15, GFRA1, GP2, INSL4, LAMA4, LEP, MIA, MMP12, PRSS8, SFRP1, SFTPA2, SPON1, TFF1, VTCN1, and WFDC2.
8 . (canceled)
9 . The method of claim 1 , wherein the plurality of target molecules detected above a threshold are polypeptides selected from the group consisting of: CEACAM5, RHOV, SFTA2, SCGB1D2, IGF2BP1, SFTPA1, CA12, SFTPB, CDH3, MUC6, SLC6A14, HOXC9, AGR3, TMEM125, TFAP2B, IRX2, POTEKP, ARHGEF38, GPR87, LMX1B, ATP10B, NELL1, MUC21, SOX9, LINC00993, STMND1, ERVH48-1, SCTR, MAGEA3, MB, LEMD1, SIX4, and NXNL2.
10 . The method of claim 1 , wherein the plurality of target molecules comprise (a) polypeptides of one or more of Tables 11-14, and (b) one or more polypeptides of Tables 1-6.
11 . (canceled)
12 . The method of claim 1 , wherein (i) the cancer is lung cancer, and (ii) the plurality of target molecules detected above a threshold are selected from polypeptides of Table 18, and optionally (iii) the plurality of target molecules detected above a threshold are selected polypeptides of one or more of WFDC2, CXCL17, MMP12, GDF15, or CEACAM5.
13 . (canceled)
14 . The method of claim 1 , wherein (i) the cancer is breast cancer, and (ii) the plurality of target molecules detected above a threshold are selected from polypeptides of Table 19, and optionally (iii) the plurality of target molecules detected above a threshold are selected from polypeptides of one or more of ADAMTS15, LEP, ERBB2, ERBB4, or CGA.
15 . (canceled)
16 . The method of claim 1 , wherein the plurality of target molecules comprises polypeptides of Table 16A or Table 16B
17 . The method of claim 16 , wherein the plurality of target molecules comprises: (a) polypeptides of Table 17, or (b) polypeptides selected from AGR3, CA12, CEACAM5, CXCL17, GP2, IL20, MMP7, TFF1, VTCN1.
18 . (canceled)
19 . The method of claim 1 , wherein:
(a) the plurality of target molecules further comprises cell-free polynucleotides comprising (i) cell-free DNA (cfDNA) from genes encoding the polypeptides, and/or (ii) cell-free RNA (cfRNA) transcripts of the genes encoding the polypeptides; and
(b) detecting one or more of the target molecules above a threshold level comprises (i) detecting one or more of the polypeptides above a first threshold level, and (ii) for each of the polypeptides detected above the first threshold level, detecting a corresponding cell-free polynucleotide above a second threshold level.
20 . The method of claim 19 , wherein the cell-free polynucleotides comprise cfRNA or cfDNA.
21 . (canceled)
22 . The method of claim 20 , wherein the cfDNA is methylated cfDNA.
23 . (canceled)
24 . The method of claim 19 , wherein the measuring comprises sequencing the cell-free polynucleotides to produce sequence reads.
25 . The method of claim 24 , wherein the sequencing comprises: (i) whole transcriptome sequencing, (ii) sequencing cDNA molecules reverse transcribed from the cfRNA, or (iii) sequencing an enriched population of cfRNA or cfDNA.
26 . (canceled)
27 . (canceled)
28 . (canceled)
29 . (canceled)
30 . The method of claim 1 , wherein detecting one or more of the target molecules above a threshold level comprises (i) detection, (ii) detection above background, or (iii) detection at a level that is greater than a level of the one or more target molecules in subjects that do not have the cancer.
31 . (canceled)
32 . (canceled)
33 . The method of claim 19 , wherein the cell-free polynucleotides comprise cfRNA transcripts, and detecting one or more of the cfRNA transcripts above the second threshold level comprises:
(a) determining an indicator score for cfRNA transcript by comparing the expression level of each of the cfRNA transcript to an RNA tissue score matrix;
(b) aggregating the indicator scores for each cfRNA transcript; and,
(c) detecting the cancer when the indicator score exceeds a threshold value.
34 . The method of claim 24 , wherein detecting one or more of the cell-free polynucleotides above a threshold level comprises inputting the sequence reads into a machine learning or deep learning model.
35 . The method of claim 34 , wherein:
(a) the machine learning or deep learning model comprises logistic regression, random forest, gradient boosting machine, Näive Bayes, neural network, or multinomial regression; or
(b) the machine learning or deep learning model transforms the values of the one or more features to the disease state prediction for the subject through a function comprising learned weights.
36 . (canceled)
37 . The method of claim 1 , wherein the cancer comprises:
(i) a carcinoma, a sarcoma, a myeloma, a leukemia, a lymphoma, a blastoma, a germ cell tumor, or any combination thereof;
(ii) a carcinoma selected from the group consisting of adenocarcinoma, squamous cell carcinoma, small cell lung cancer, non-small-cell lung cancer, nasopharyngeal, colorectal, anal, liver, urinary bladder, testicular, cervical, ovarian, gastric, esophageal, head-and-neck, pancreatic, prostate, renal, thyroid, melanoma, and breast carcinoma;
(iii) hormone receptor negative breast carcinoma or triple negative breast carcinoma;
(iv) a sarcoma selected from the group consisting of: osteosarcoma, chondrosarcoma, leiomyosarcoma, rhabdomyosarcoma, mesothelial sarcoma (mesothelioma), fibrosarcoma, angiosarcoma, liposarcoma, glioma, and astrocytoma;
(v) a leukemia selected from the group consisting of myelogenous, granulocytic, lymphatic, lymphocytic, and lymphoblastic leukemia; or
(vi) a lymphoma selected from the group consisting of: Hodgkin's lymphoma and Non-Hodgkin's lymphoma.
38 . The method of claim 1 , wherein detecting the cancer comprises determining a cancer stage, determining cancer progression, determining a cancer type, determining cancer tissue of origin, or a combination thereof.
39 . The method of claim 1 , further comprising selecting a treatment based on the cancer detected, and treating the subject with the selected treatment.
40 . The method of claim 39 , wherein the treatment comprises surgical resection, radiation therapy, or administering an anti-cancer agent.
41 . (canceled)
42 . A computer system for implementing one or more steps in the method of claim 1 .
43 . A non-transitory, computer-readable medium, having stored thereon computer-readable instructions for implementing one or more steps in the method of claim 1 .