Analyzing copy number variation in the detection of cancer
The invention provides a method for determining copy number variations (CNV) of a sequence of interest in a test sample that comprises a mixture of nucleic acids that are known or are suspected to differ in the amount of one or more sequence of interest. The method comprises a statistical approach that accounts for accrued variability stemming from process-related, interchromosomal and inter-sequencing variability. The method is applicable to determining CNV of any fetal aneuploidy, and CNVs known or suspected to be associated with a variety of medical conditions. CNV that can be determined according to the method include trisomies and monosomies of any one or more of chromosomes 1-22, X and Y, other chromosomal polysomies, and deletions and/or duplications of segments of any one or more of the chromosomes, which can be detected by sequencing only once the nucleic acids of a test sample.
1. A method, implemented using a computer system comprising one or more processors and system memory, for identifying the presence of a cancer and/or an increased risk of a cancer in a mammal, said method comprising:
(a) providing, to the computer system, sequence reads of nucleic acids in a test sample from said mammal, wherein said test sample comprises both genomic nucleic acids from cancerous or precancerous cells and genomic nucleic acids from constitutive cells, and wherein the sequence reads are provided in an electronic format;
(b) aligning, by the one or more processors, the sequence reads to one or more chromosome reference sequences, thereby providing sequence tags corresponding to the sequence reads;
(c) identifying, by the one or more processors, a number of sequence tags from the nucleic acids for one or more sequences of interest amplification of which or deletions of which are associated with cancers, wherein said one or more sequences of interest are on chromosomes 1-22, X, or Y, and identifying, by the one or more processors, a number of sequence tags for at least one normalizing sequence for each of the one or more sequences of interest;
(d) calculating, by the one or more processors and using said number of sequence tags identified for each of said one or more sequences of interest and said number of sequence tags identified for each said normalizing sequence, a single sequence dose for each of said one or more sequences of interest,
wherein the at least one normalizing sequence is a sequence that yields sequence doses for a sequence of interest having: (a) the smallest variability among unaffected samples, (b) the greatest differentiability between affected and unaffected samples, (c) the smallest variability and the greatest differentiability, or (d) an optimal combination of small variability and large differentiability; and
(e) evaluating, using the one or more processors, each of said single sequence doses for each of one or more sequences of interest, and thereby determining the presence or absence of copy number variations (CNVs) of the one or more sequences of interest in said test sample, where the presence of said CNVs is an indicator of the presence and/or increased risk of a cancer.
2. The method of claim 1 , wherein said CNVs comprise one or more microdeletions, microinsertions, or microduplications.
3. The method of claim 1 , wherein said one or more sequences of interest are sequences containing one or more oncogenes and/or one or more tumor suppressor genes.
4. The method of claim 3 , wherein said CNVs comprise an amplification of one or more regions comprising a gene selected from the group consisting of MYC, ERBB2 (EFGR), CCND1 (Cyclin D1), FGFRJ, FGFR2, HRAS, KRAS, MYB, MDM2, CCNE, KRAS, MET, ERBBJ, CDK4, MYCB, ERBB2, AKT2, MDM2 and CDK4.
5. The method of claim 3 , wherein said cancer is a cancer selected from the group consisting of leukemia, ALL, brain cancer, breast cancer, colorectal cancer, dedifferentiated liposarcoma, esophageal adenocarcinoma, esophageal squamous cell cancer, GIST, glioma, HCC, hepatocellular cancer, lung cancer, lung NSC, lung SC, medulloblastoma, melanoma, MPD, myeloproliferative disorder, cervical cancer, ovarian cancer, prostate cancer, and renal cancer.
6. The method of claim 1 , further comprising sequencing cell free DNA from the test sample to provide the sequence read.
7. The method of claim 1 , wherein the determination of the presence or absence of said CNVs is a component in a differential diagnosis for cancer.
8. The method according to claim 1 , wherein detection of CNVs indicates a positive result and said method further comprises prescribing, initiating, and/or altering treatment of a human subject from whom the test sample was taken.
9. The method of claim 8 , wherein said prescribing, initiating, and/or altering treatment of a human subject from whom the test sample was taken comprises prescribing and/or performing further diagnostics to determine the presence and/or severity of a cancer.
10. The method of claim 9 , wherein said further diagnostics comprise screening a sample from said human subject for a biomarker of a cancer, and/or imaging said human subject for a cancer.
11. The method of claim 8 , wherein when said method indicates the presence of neoplastic cells in said mammal, treating said mammal, or causing said mammal to be treated, to remove and/or to inhibit the growth or proliferation of said neoplastic cells.
12. The method of claim 11 , wherein said treating said mammal comprises surgically removing said neoplastic cells.
13. The method of claim 11 , wherein said treating said mammal comprises performing radiotherapy or causing radiotherapy to be performed on said mammal to kill said neoplastic cells.
14. The method of claim 11 , wherein said treating said mammal comprises administering or causing to be administered to said mammal an anti-cancer drug.
15. The method of claim 14 , wherein said anti-cancer drug is a drug selected from the group consisting of matuzumab, erbitux, vectibix, nimotuzumab, matuzumab, panitumumab, flourouracil, capecitabine, 5-trifluoromethyl-2′-deoxyuridine, methotrexate, raltitrexed, pemetrexed, cytosine arabinoside, 6-mercaptopurine, azathioprine, 6-thioguanine, pentostatin, fludarabine, cladribine, floxuridine, cyclophosphamide, neosar, ifosfamide, thiotepa, 1,3-bis(2-chloroethyl)-1-nitosourea, 1-(2-chloroethyl)-3-cyclohexyl-lnitrosourea, hexamethylmelamine, busulfan, procarbazine, dacarbazine, chlorambucil, melphalan, cisplatin, carboplatin, oxaliplatin, bendamustine, carmustine, chloromethine, dacarbazine, fotemustine, lomustine, mannosulfan, nedaplatin, nimustine, prednimustine, ranimustine, satraplatin, semustine, streptozocin, tem ozol omi de, treosulfan, triaziquone, tri ethyl ene melamine, thiotepa, triplatin tetranitrate, trofosfamide, uramustine, doxorubicin, daunorubicin, mitoxantrone, etoposide, topotecan, teniposide, irinotecan, camptosar, camptothecin, belotecan, rubitecan, vincristine, vinblastine, vinorelbine, vindesine, paclitaxel, docetaxel, abraxane, ixabepilone, larotaxel, ortataxel, tesetaxel, vinflunine, imatinib mesylate, sunitinib malate, sorafenib tosylate, nilotinib hydrochloride monohydrate, tasigna, semaxanib, vandetanib, vatalanib, retinoic acid, and a retinoic acid derivative.
16. A computer program product for use in determining the presence of a cancer and/or an increased risk of a cancer in a mammal, said computer program product comprising:
(a) code for providing sequence reads of nucleic acids in a test sample from said mammal, wherein said test sample comprises both genomic nucleic acids from cancerous or precancerous cells and genomic nucleic acids from constitutive cells, and wherein the sequence reads are provided in an electronic format;
(b) code for aligning the sequence reads to one or more chromosome reference sequences and thereby providing sequence tags corresponding to the sequence reads;
(c) code for identifying a number of sequence tags from nucleic acids for one or more sequences of interest amplification of which or deletions of which are associated with cancers, wherein said one or more sequences of interest are on chromosomes 1-22, X, or Y, and identifying a number of sequence tags for at least one normalizing sequence for each of the one or more sequences of interest;
(d) code for calculating, using said number of sequence tags identified for each of said one or more sequences of interest and said number of sequence tags identified for each said at least one normalizing sequence, a single sequence dose for each of said one or more sequences of interest,
wherein the at least one normalizing sequence is a sequence that yields sequence doses for a sequence of interest having: (a) the smallest variability among unaffected samples, (b) the greatest differentiability between affected and unaffected samples, (c) the smallest variability and the greatest differentiability, or (d) an optimal combination of small variability and large differentiability; and
(e) code for evaluating each of said single sequence doses for each of one or more sequences of interest, and thereby determining the presence or absence of copy number variations (CNVs) of the one or more sequences of interest in said test sample, where the presence of said CNVs is an indicator of the presence and/or increased risk of a cancer.
17. A method of monitoring a treatment of a subject for a cancer, said method comprising:
performing the method according to claim 1 on a sample from said subject or receiving results of such a method performed on said sample before or during said treatment to obtain a first measurement of the sequence of interest; and
performing the method according to claim 1 on a second sample from said subject or receiving the results of such a method performed on said second sample at a later time during or after said treatment to obtain a second measurement of the sequence of interest; where a reduced number or severity of aneuploidy in said second measurement is an indicator of a positive course of treatment and the same or increased number or severity of aneuploidy in said second measurement is an indicator of a negative course of treatment and when said indicator is negative adjusting said treatment to a more aggressive treatment regimen or a palliative treatment regimen.