U.S. patent application number 17/080201 was filed with the patent office on 2021-04-15 for genomic alterations in the tumor and circulation of pancreatic cancer patients.
The applicant listed for this patent is The Johns Hopkins University. Invention is credited to Vilmos Adleff, Jillian A. Phallen, Mark Sausen, Victor E. Velculescu.
Application Number | 20210108256 17/080201 |
Document ID | / |
Family ID | 1000005291758 |
Filed Date | 2021-04-15 |
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United States Patent
Application |
20210108256 |
Kind Code |
A1 |
Velculescu; Victor E. ; et
al. |
April 15, 2021 |
GENOMIC ALTERATIONS IN THE TUMOR AND CIRCULATION OF PANCREATIC
CANCER PATIENTS
Abstract
Pancreatic adenocarcinoma has the worst overall mortality of any
solid tumor, with only 7% of patients surviving after 5 years. To
evaluate the clinical implications of genomic alterations in this
low cellularity tumor type, we deeply sequenced the genomes of 101
enriched pancreatic adenocarcinomas from patients who underwent
potentially curative resections and used non-invasive approaches to
examine tumor specific mutations in the circulation of these
patients. These analyses revealed somatic mutations in chromatin
regulating genes including MLL and ARID1A in 20% of patients that
were associated with improved survival. Liquid biopsy analyses of
cell free plasma DNA revealed that 43% of patients with localized
disease had detectable circulating tumor DNA (ctDNA) in their blood
at the time of diagnosis. Detection of ctDNA after resection
predicted clinical relapse and poor outcome, and disease recurrence
by ctDNA was detected 6.5 months earlier than with standard CT
imaging.
Inventors: |
Velculescu; Victor E.;
(Dayton, MD) ; Sausen; Mark; (Baltimore, MD)
; Adleff; Vilmos; (Baltimore, MD) ; Phallen;
Jillian A.; (Baltimore, MD) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Johns Hopkins University |
Baltimore |
MD |
US |
|
|
Family ID: |
1000005291758 |
Appl. No.: |
17/080201 |
Filed: |
October 26, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15552076 |
Aug 18, 2017 |
10815522 |
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PCT/US2016/018450 |
Feb 18, 2016 |
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17080201 |
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62118604 |
Feb 20, 2015 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C12Q 2600/112 20130101;
C12Q 1/6886 20130101; C12Q 1/6827 20130101; C12Q 2600/106 20130101;
C12Q 2600/118 20130101; C12Q 1/6816 20130101; C12Q 2600/156
20130101 |
International
Class: |
C12Q 1/6827 20060101
C12Q001/6827; C12Q 1/6886 20060101 C12Q001/6886; C12Q 1/6816
20060101 C12Q001/6816 |
Goverment Interests
[0002] This invention was made with government support under
CA12113 and CA62924 awarded by National Institutes of Health. The
government has certain rights in the invention.
Claims
1-11. (canceled)
12. A probe or primer specific for a mutant chromatin regulating
MLL (chromosome 11), MLL2 (chromosome 12), MLL 3 (chromosome 7) or
ARID1A gene, said probe or primer comprising a mutation selected
from the group consisting of: ARID1A mutations: TABLE-US-00003
chr1_26928798- 403Q > X Substitution Nonsense; 26928798_C_T
chr1_26979465- NA Insertion Frameshift; 26979465_C chr1_26978312-
1779E > G Substitution Nonsynonymous 26978312_A_G coding;
chr1_26978589- 1871H > Q Substitution Nonsynonymous 26978589_C_G
coding; chr1_26895595- 38E > EA Insertion In-frame 26895595_GGC
insertion; chr1_26960135- 708Q > X Substitution Nonsense;
26960135_C_T chr1_26973560- 1419A > T Substitution Nonsynonymous
26973560_G_A coding; chr1_26974706- 1682A > E Substitution
Nonsynonymous 26974706_C_A coding; chr1_26972534- 1276R > X
Substitution Nonsense; 26972534_C_T chr1_26978518- NA Deletion
Frameshift; 26978518_G.sub.-- chr1_26979254- NA Insertion
Frameshift; 26979254_TT
and MLL (chromosome 11), MLL2 (chromosome 12), or MLL 3 (chromosome
7) mutations: TABLE-US-00004 chr7_151490485- 3704V > L
Substitution Nonsynonymous 151490485_C_G coding; chr11_117854039-
1161C > S Substitution Nonsynonymous 117854039_G_C coding;
chr11_117847769- 229P > T Substitution Nonsynonymous
117847769_C_A coding; chr12_47718147- 3087R > W Substitution
Nonsynonymous 47718147_G_A coding; chr7_151515732- NA Substitution
Splice site donor; 151515732_C_T chr12_47729834- NA Insertion
Frameshift; 47729834_A chr7_151576224- 743P > L Substitution
Nonsynonymous 151576224_G_A coding; chr7_151476195- 4584R > W
Substitution Nonsynonymous 151476195_G_A coding; chr7_151686622- NA
Insertion Frameshift; 151686622_TC chr12_47711653- NA Insertion
Frameshift; 47711653_T chr12_47731362- NA Deletion Frameshift;
47731362_G.sub.-- chr7_151601824- NA Insertion Frameshift;
151601824_T chr12_47722327- 1974T > M Substitution Nonsynonymous
47722327_G_A coding; and chr7_151510210- 1890R > X Substitution
Nonsense. 151510210_G_A
13. The probe or primer of claim 12 which is labeled with a
radionuclide, a fluorescent label, or a chromophore.
14-34. (canceled)
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a National Stage application under 35
U.S.C. .sctn. 371 of International Application No.
PCT/US2016/018450, filed Feb. 18, 2016, which claims the benefit of
U.S. Provisional Application No. 62/118,604, filed Feb. 20, 2015.
The disclosures of the prior applications are hereby incorporated
by reference in their entirety.
TECHNICAL FIELD OF THE INVENTION
[0003] This invention is related to the area of cancer. In
particular, it relates to pancreatic cancer.
BACKGROUND OF THE INVENTION
[0004] Worldwide, over 250,000 patients develop pancreatic ductal
adenocarcinoma every year and the vast majority die of their
disease.sup.1. Several genetic alterations have been identified in
pancreatic cancers, including those in the CDKN2A, SMAD4 and TP53
tumor suppressor genes, and in the KRAS oncogene.sup.2,3. Although
the discoveries of these genes and their pathways have provided
important insights into the natural history of pancreatic cancer
and have spurred efforts to develop improved diagnostic and
therapeutic agents, few genetic alterations discovered to date in
pancreatic cancer have been used to directly affect clinical
care.sup.4,5.
[0005] There is a continuing need in the art to develop tools for
detecting disease, assessing disease, and effectively treating
disease, particularly highly lethal disease such as pancreatic
cancers.
SUMMARY OF THE INVENTION
[0006] According to one aspect of the invention a method is
provided for characterizing a pancreatic adenocarcinoma. A sample
of nucleic acids from a pancreatic adenocarcinoma of a human is
tested to identify a somatic mutation in a chromatin regulating
gene selected from the group consisting of MLL, MLL2, MLL3, and
ARID1A.
[0007] Another aspect of the invention is a method for testing a
human. Plasma of a human collected at the time of diagnosis of a
pancreatic adenocarcinoma is tested for the presence of cell-free
tumor DNA. The cell-free tumor DNA contains a somatic mutation
present in the pancreatic adenocarcinoma but not present in tissues
that are not pancreatic adenocarcinoma.
[0008] An additional aspect of the invention is a method for
testing a human. Plasma of a human collected after surgical
resection of a pancreatic adenocarcinoma is tested for the presence
of cell-free tumor DNA. The cell-free tumor DNA contains a somatic
mutation present in the pancreatic adenocarcinoma but not present
in tissues that are not pancreatic adenocarcinoma.
[0009] One aspect of the invention is a probe or primer specific
for a mutant chromatin regulating MLL (chromosome 11), MLL2
(chromosome 12), MLL 3 (chromosome 7) or ARID1A gene, said probe or
primer comprising a mutation selected from the group consisting
of:
[0010] ARID1A mutations:
TABLE-US-00001 chr1_26928798- 403Q > X Substitution Nonsense;
26928798_C_T chr1_26979465- NA Insertion Frameshift; 26979465_C
chr1_26978312- 1779E > G Substitution Nonsynonymous 26978312_A_G
coding; chr1_26978589- 1871H > Q Substitution Nonsynonymous
26978589_C_G coding; chr1_26895595- 38E > EA Insertion In-frame
insertion; 26895595_GGC chr1_26960135- 708Q > X Substitution
Nonsense; 26960135_C_T chr1_26973560- 1419A > T Substitution
Nonsynonymous 26973560_G_A coding; chr1_26974706- 1682A > E
Substitution Nonsynonymous 26974706_C_A coding; chr1_26972534-
1276R > X Substitution Nonsense; 26972534_C_T chr1_26978518- NA
Deletion Frameshift; and 26978518_G.sub.-- chr1_26979254- NA
Insertion Frameshift; 26979254_TT
and MLL (chromosome 11), MLL2 (chromosome 12), or MLL 3 (chromosome
7) mutations:
TABLE-US-00002 chr7_151490485- 3704V > L Substitution
Nonsynonymous 151490485_C_G coding; chr11_117854039- 1161C > S
Substitution Nonsynonymous 117854039_G_C coding; chr11_117847769-
229P > T Substitution Nonsynonymous 117847769_C_A coding;
chr12_47718147- 3087R > W Substitution Nonsynonymous
47718147_G_A coding; chr7_151515732- NA Substitution Splice site
donor; 151515732_C_T chr12_47729834- NA Insertion Frameshift;
47729834_A chr7_151576224- 743P > L Substitution Nonsynonymous
151576224_G_A coding; chr7_151476195- 4584R > W Substitution
Nonsynonymous 151476195_G_A coding; chr7_l51686622- NA Insertion
Frameshift; 151686622_TC chr12_47711653- NA Insertion Frameshift;
47711653_T chr12_47731362- NA Deletion Frameshift;
47731362_G.sub.-- chr7_151601824- NA Insertion Frameshift;
151601824_T chr12_47722327- 1974T > M Substitution Nonsynonymous
47722327_G_A coding; and chr7_151510210- 1890R > X Substitution
Nonsense. 151510210_G_A
[0011] These and other embodiments which will be apparent to those
of skill in the art upon reading the specification provide the art
with
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] FIG. 1. Schematic of next-generation sequencing and
circulating tumor DNA analyses.
[0013] FIG. 2A-2C. Recurrent genetic alterations in pancreatic
cancer and their effect on disease outcome. FIG. 2A: Representation
of the mutations identified in chromatin modifying and other
recurrently mutated genes. Each patient sample is indicated as a
grey box with mutations indicated in green or black. FIG. 2B:
Analyses of overall survival revealed that patients wild type for
MLL gene alterations (n=87) had a significantly lower median
survival compared with those with mutated MLL genes (n=14; median
survival 15.3 months vs not reached respectively, p=0.0063,
log-rank test). FIG. 2C: Similar analyses revealed significantly
improved survival in patients with mutations in either MLL or
ARID1A genes (n=20) compared with those that were wild-type for any
of these genes (n=81).
[0014] FIG. 3A-3B. Detection of residual disease using CT imaging
and ctDNA analyses. FIG. 3A: Patients with detectable circulating
tumor DNA (ctDNA) after surgical resection were more likely to
relapse and die from disease compared to those with undetectable
ctDNA. The median time to recurrence was 9.9 months for individuals
with detectable ctDNA and was not reached for those without
detectable ctDNA. FIG. 3B: Comparison between the time to detection
of recurrence using ctDNA and standard-of-care CT imaging revealed
that the median time to recurrence was 71 days for individuals with
detectable ctDNA and 289 days for those patients with positive
imaging results (p=0.0004, paired t-test).
[0015] FIG. 4 (Table 1) Clinical Actionability of Genetic
Alterations in Pancreatic Cancer
[0016] FIG. 5. (Supplementary FIG. 1.) Schematic of Mutations in
MLL and ARID1A Proteins. Domains indicated in the schematic
represent PHD, plant homeo domain finger, HMG, high mobility group
box, FYRN, FY-rich N-terminal domain, FY-rich C-terminal domain,
SET, Su (var)3-9 Enhancer-of-zeste Trithorax methyltransferase
domain, BROM, bromodomain, ARID, ARID/BRIGHT DNA binding domain,
DUF3518, and Domain of unknown function (DUF3518). Mutations were
assessed for conservation by phyloP across 44 vetebrate species and
those highlighted in green were predicted to be conserved. Black
arrows indicate missense alterations and red arrows indicate
truncating alterations.
[0017] FIG. 6A-6B. (Supplementary FIG. 2.) Kaplan Meier
Progression-Free Survival Analysis of MLL and Chromatin Regulator
Mutations. FIG. 6A: The hazard ratio for tumor recurrence among
individuals with mutant MLL, MLL2, or MLL3 genes compared to those
with wild-type MLL, MLL2, or MLL3 genes (WT) was 0.54 (95%
CI=0.30-0.98). The median time to recurrence was 10.2 months for
individuals wild-type for MLL gene alterations and 24.9 months for
those with mutated MLL genes. FIG. 6B: The hazard ratio for tumor
recurrence among individuals with mutant chromatin regulator genes
compared to those with wild-type (WT) chromatin regulator genes was
0.47 (95% CI=0.27-0.82). The median time to recurrence was 8.2
months for individuals wild-type for chromatin regulator gene
alterations and 24.9 months for those with mutated chromatin
regulator genes.
[0018] FIG. 7. (Supplementary FIG. 3.) Prediction of Recurrence
using ctDNA Detected at Baseline. The hazard ratio for tumor
recurrence among individuals with detectable circulating tumor DNA
(ctDNA) compared to those without detectable ctDNA was 2.39 (95%
CI=1.18-4.81). The median time to recurrence was 15.2 months for
individuals without detectable ctDNA and 7.9 months for those with
detectable ctDNA.
[0019] FIG. 8 (Supplemental Table 1)
[0020] FIG. 9 (Supplemental Table 4 (ARID1A, MLL, MLL2, AND
MLL3)
[0021] FIG. 10 (Supplemental Table 5)
[0022] FIG. 11 (Supplemental Table 7)
[0023] FIG. 12 (Supplemental Table 8)
DETAILED DESCRIPTION OF THE INVENTION
[0024] Through integrated genomic analyses we have identified MLL
and ARID1A genes as markers of improved prognosis, and highlighted
clinically actionable alterations in genes not typically evaluated
during clinical care of pancreatic cancer patients. We have also
shown that cell-free DNA in the circulation of pancreatic cancer
patients may provide a marker of early detection of sub-clinical,
residual or recurrent disease. These analyses suggest more
intensive therapies for pancreatic cancer patients without MLL or
ARID1A alterations or with detectable cell-free DNA at the time of
diagnosis or after surgical resection.
[0025] Testing for mutations in nucleic acids from plasma, other
body fluids, or from tumor tissue can be performed by any means
known in the art. Hybridization methods using probes may be used in
any assay format desired, including but not limited to Southern or
Northern blots, and microarrays. The probes may be double or single
stranded. They may hybridize to the sense strand of the gene or the
anti-sense strand. Mutations may also be detected using an
amplification method, whether linear or exponential. The
amplification may utilize one or more primers. The primers may be
contain a mutant nucleotide or be adjacent to it. A primer pair may
surround a mutant nucleotide and the detection of the mutant may
rely on hybridization to a probe after amplification. Other means
for identifying mutations include nucleic acid sequencing
techniques. Probes and primers may be labeled with any detectable
label known in the art, including but not limited to radionuclides,
fluorescent labels, chromophores, enzymes. Probes or primers may
contain non-naturally occurring components, for example, to limit
degradation. Artificial nucleic acids may include peptide nucleic
acid, morpholino and locked nucleic acid, glycol nucleic acid, and
threose nucleic acid (TNA). Each of these is distinguished from
naturally occurring DNA or RNA by changes to the backbone of the
molecule.
[0026] Nucleic acids from pancreatic adenocarcinomas may be
obtained from biopsies or from surgical samples. Nucleic acids
found in the plasma of a patient with a tumor are believed to be
shed into the circulation or other body fluids, perhaps by cells
which are undergoing apoptosis or necrosis. The presence of a
somatic mutation that is identical to one found in the tumor
indicates that the nucleic acid ultimately derived from the
tumor.
[0027] Control nucleic acids for determining a somatic mutation may
be taken from any normal tissue, including normal portions of the
patient's pancreas, or other organs. If a mutation is a germline
mutation, it will be found in all of a patient's tissues. In the
case of circulating tumor DNA found in the plasma, this DNA
typically forms a minority of the DNA found in the plasma.
[0028] Mutations that affect a coding sequence include
substitutions, insertions, and deletions. These may cause nonsense,
frameshifts, splice site donor, or non-synonymous coding mutations.
Other than the latter type, these mutation types will typically
lead to truncation of an encoded message or product.
[0029] Plasma, other body fluid, and/or tissue samples can be
collected for testing at the time of diagnosis, before surgical
resections, or after surgical resections. The findings of mutations
or no mutations can inform subsequent treatment options. In some
cases, surgery may be averted if a good prognosis is determined. In
other cases more intensive therapies may be used to counter a bad
prognostic finding. In other cases less intensive therapies may be
used when a favorable prognostic indication is found. Therapies may
be more or less intensive in kind, dosage, or duration.
[0030] The finding of mutations in the chromatin regulation genes
is a positive prognostic indicator. Finding of tumor-specific,
cell-free DNA is a negative prognostic indicator. Conversely,
finding of no tumor-specific, cell-free DNA can be considered a
positive prognostic indicator and finding of no chromatin
regulation gene mutations may be considered a negative prognostic
indicator. These factors affect both disease-free progression time
as well as overall survival time. Prognoses can be delivered to a
patient in a written or electronic form. They can be delivered from
a clinical laboratory to a practicing physician.
[0031] Cell-free tumor DNA can be tested for mutations in any genes
that are known to be associated with cancers. Often a single
patient will have many somatic mutations in his tumor. Any of these
can be detected and followed in the cell-free DNA of the plasma or
other body fluid. Frequently mutated genes in pancreatic
adenocarcinomas include KRAS, BRAF, and PIK3CA. Other frequently
mutated genes may be monitored.
[0032] Plasma or other body fluids may be tested for the presence
of cell-free DNA. Suitable body fluids include serum, blood,
pancreatic juice, pus, stool, etc. Drainage of pancreatic lesions
into the stomach or jejunum may lead to increased cell-free
pancreatic DNA in the stool.
[0033] The above disclosure generally describes the present
invention. All references disclosed herein are expressly
incorporated by reference. A more complete understanding can be
obtained by reference to the following specific examples which are
provided herein for purposes of illustration only, and are not
intended to limit the scope of the invention.
Example 1--Materials and Methods
Samples Obtained for Sequencing Analyses
[0034] Pancreatic ductal adenocarcinoma tumor specimens and matched
germline specimens (from peripheral blood) from 101 patients were
used for genomic analyses. Plasma samples were obtained at the time
of diagnosis from 44 of these patients as well as 7 additional
patients. Informed consent for research use was obtained from all
patients at the enrolling institution prior to tissue banking and
study approval was obtained. Primary tumor samples for genomic
analyses were selected from patients with resectable stage II
disease, verified to have .gtoreq.10% viable tumor cell content by
histopathological assessment, and demonstrated to be wild-type for
the DAXX/ATRX loci, which have been shown to be associated with
improved outcome in patients with pancreatic neuroendocrine
tumors.sup.20. For a subset of cases, plasma samples were obtained
at multiple time points after surgery.
Flow-Sorting of Aneuploid Nuclei
[0035] Flow sorting of tumor nuclei: Individual biopsies were
minced with scalpel blades in a petri dish (35.times.100 mm) in NST
buffer (146 mM NaCl, 10 mM Tris-HCl, pH 7.5, 1 mM CaCl2, 0.5 mM
MgSO4, 21 mM MgCl2, 0.05% bovine serum albumin, 0.2% Nonidet P40
(Sigma)) with 4,6-diamindino-2-phenylindole (DAPI; 10 .mu.g/ml;
Boehringer) according to published protocols (Ruiz, Lenkiewicz et
al. 2011). The nuclei were then disaggregated with a 25-gauge
needle, and subsequently filtered through a 40-.mu.m mesh filter
immediately before analyses on an Influx cytometer
(Becton-Dickinson, San Jose Calif.), with ultraviolet excitation
and DAPI emission collected at >450 nm. We sorted all diploid,
aneuploid, and tetraploid fractions from each sample. DNA content
and cell cycle were analyzed using the software program MultiCycle
(Phoenix Flow Systems, San Diego, Calif.).
Sample Preparation and Next-Generation Sequencing
[0036] Sample preparation, library construction, exome and targeted
capture, next generation sequencing, and bioinformatics analyses of
tumor and normal samples were performed as previously described. In
brief, DNA was extracted from frozen or formalin-fixed paraffin
embedded (FFPE) tissue, along with matched blood or saliva samples
using the Qiagen DNA FFPE tissue kit or Qiagen DNA blood mini kit
(Qiagen, Calif.). Genomic DNA from tumor and normal samples were
fragmented and used for Illumina TruSeq library construction
(Illumina, San Diego, Calif.) according to the manufacturer's
instructions or as previously described 17. Briefly, 50 nanograms
(ng)-3 micrograms (.mu.g) of genomic DNA in 100 microliters (.mu.l)
of TE was fragmented in a Covaris sonicator (Covaris, Woburn,
Mass.) to a size of 150-450 bp. To remove fragments smaller than
150 bp, DNA was purified using Agencourt AMPure XP beads (Beckman
Coulter, Ind.) in a ratio of 1.0 to 0.9 of PCR product to beads
twice and washed using 70% ethanol per the manufacturer's
instructions. Purified, fragmented DNA was mixed with 36 .mu.l of
H2O, 10 .mu.l of End Repair Reaction Buffer, 5 .mu.l of End Repair
Enzyme Mix (cat #E6050, NEB, Ipswich, Mass.). The 100 .mu.l
end-repair mixture was incubated at 20.degree. C. for 30 min, and
purified using Agencourt AMPure XP beads (Beckman Coulter, Ind.) in
a ratio of 1.0 to 1.25 of PCR product to beads and washed using 70%
ethanol per the manufacturer's instructions. To A-tail, 42 .mu.l of
end-repaired DNA was mixed with 5 .mu.l of 10.times. dA Tailing
Reaction Buffer and 3 .mu.l of Klenow (exo-)(cat #E6053, NEB,
Ipswich, Mass.). The 50 .mu.l mixture was incubated at 37.degree.
C. for 30 min and purified using Agencourt AMPure XP beads (Beckman
Coulter, Ind.) in a ratio of 1.0 to 1.0 of PCR product to beads and
washed using 70% ethanol per the manufacturer's instructions. For
adaptor ligation, 25 .mu.l of A-tailed DNA was mixed with 6.7 .mu.l
of H2O, 3.3 .mu.l of PE-adaptor (Illumina), 10 .mu.l of 5.times.
Ligation buffer and 5 .mu.l of Quick T4 DNA ligase (cat #E6056,
NEB, Ipswich, Mass.). The ligation mixture was incubated at
20.degree. C. for 15 min and purified using Agencourt AMPure XP
beads (Beckman Coulter, Ind.) in a ratio of 1.0 to 0.95 and 1.0 of
PCR product to beads twice and washed using 70% ethanol per the
manufacturer's instructions. To obtain an amplified library, twelve
PCRs of 25 .mu.l each were set up, each including 15.5 .mu.l of
H2O, 5 .mu.l of 5.times. Phusion HF buffer, 0.5 .mu.l of a dNTP mix
containing 10 mM of each dNTP, 1.25 .mu.l of DMSO, 0.25 .mu.l of
Illumina PE primer #1, 0.25 .mu.l of Illumina PE primer #2, 0.25
.mu.l of Hotstart Phusion polymerase, and 2 .mu.l of the DNA. The
PCR program used was: 98.degree. C. for 2 minutes; 12 cycles of
98.degree. C. for 15 seconds, 65.degree. C. for 30 seconds,
72.degree. C. for 30 seconds; and 72.degree. C. for 5 min. DNA was
purified using Agencourt AMPure XP beads (Beckman Coulter, Ind.) in
a ratio of 1.0 to 1.0 of PCR product to beads and washed using 70%
ethanol per the manufacturer's instructions. Exonic or targeted
regions were captured in solution using the Agilent SureSelect v.4
kit or a custom targeted panel for the 111 genes of interest
according to the manufacturer's instructions (Agilent, Santa Clara,
Calif.). The captured library was then purified with a Qiagen
MinElute column purification kit and eluted in 17 .mu.l of
70.degree. C. EB to obtain 15 .mu.l of captured DNA library. (5)
The captured DNA library was amplified in the following way: Eight
30 uL PCR reactions each containing 19 .mu.l of H2O, 6 .mu.l of
5.times. Phusion HF buffer, 0.6 .mu.l of 10 mM dNTP, 1.5 .mu.l of
DMSO, 0.30 .mu.l of Illumina PE primer #1, 0.30 .mu.l of Illumina
PE primer #2, 0.30 .mu.l of Hotstart Phusion polymerase, and 2
.mu.l of captured exome library were set up. The PCR program used
was: 98.degree. C. for 30 seconds; 14 cycles (exome) or 16 cycles
(targeted) of 98.degree. C. for 10 seconds, 65.degree. C. for 30
seconds, 72.degree. C. for 30 seconds; and 72.degree. C. for 5 min.
To purify PCR products, a NucleoSpin Extract II purification kit
(Macherey-Nagel, Pa.) was used following the manufacturer's
instructions. Paired-end sequencing, resulting in 100 bases from
each end of the fragments for exome libraries and 150 bases from
each end of the fragment for targeted libraries, was performed
using Illumina HiSeq 2000/2500 and Illumina MiSeq instrumentation
(Illumina, San Diego, Calif.).
Primary Processing of Next-Generation Sequencing Data and
Identification of Putative Somatic Mutations
[0037] Somatic mutations were identified using VariantDx custom
software for identifying mutations in matched tumor and normal
samples through Personal Genome Diagnostics (Baltimore, Md.). Prior
to mutation calling, primary processing of sequence data for both
tumor and normal samples were performed using Illumina CASAVA
software (v1.8), including masking of adapter sequences. Sequence
reads were aligned against the human reference genome (version
hg18) using ELAND with additional realignment of select regions
using the Needleman-Wunsch method 18. Candidate somatic mutations,
consisting of point mutations, insertions, and deletions were then
identified using VariantDx across the either the whole exome or
regions of interest. VariantDx examines sequence alignments of
tumor samples against a matched normal while applying filters to
exclude alignment and sequencing artifacts. In brief, an alignment
filter was applied to exclude quality failed reads, unpaired reads,
and poorly mapped reads in the tumor. A base quality filter was
applied to limit inclusion of bases with reported phred quality
score >30 for the tumor and >20 for the normal. A mutation in
the tumor was identified as a candidate somatic mutation only when
(i) distinct paired reads contained the mutation in the tumor; (ii)
the number of distinct paired reads containing a particular
mutation in the tumor was at least 2% of the total distinct read
pairs for targeted analyses and 10% of read pairs for exome and
(iii) the mismatched base was not present in >1% of the reads in
the matched normal sample as well as not present in a custom
database of common germline variants derived from dbSNP and (iv)
the position was covered in both the tumor and normal. Mutations
arising from misplaced genome alignments, including paralogous
sequences, were identified and excluded by searching the reference
genome. Candidate somatic mutations were further filtered based on
gene annotation to identify those occurring in protein coding
regions. Functional consequences were predicted using snpEff and a
custom database of CCDS, RefSeq and Ensembl annotations using the
latest transcript versions available on hg18 from UCSC
(https://genome.ucsc.edu/). Predictions were ordered to prefer
transcripts with canonical start and stop codons and CCDS or Refseq
transcripts over Ensembl when available. Finally mutations were
filtered to exclude intronic and silent changes, while retaining
mutations resulting in missense mutations, nonsense mutations,
frameshifts, or splice site alterations. A manual visual inspection
step was used to further remove artifactual changes.
Identification of Putative Somatic Mutations without Matched Normal
Sample
[0038] For the identification of putative somatic mutations without
a matched normal, additional filters were applied. Firstly,
mutations present in an unmatched normal sample, sequenced to a
similar coverage and on the same platform as the matched normal,
were removed. Second, alterations reported in the 1000 Genomes
project, present in >1% of the population or listed as Common in
dbSNP138 were filtered.
Clinical Actionability Analyses
[0039] We selected 200 well characterized genes with potential
clinical significance and assessed the level of evidence for
clinical actionability in three ways. Firstly, we determined which
of the genes were associated with FDA-approved therapies (see URL
www.fda.gov/Drugs/). Secondly, we carried out a literature search
to identify published prospective clinical studies pertaining to
genomic alterations of each gene and their association with outcome
for cancer patients. Genes that served as targets for specific
agents or were predictors of response or resistance to cancer
therapies when mutated were considered actionable. Thirdly, we
identified clinical trials (see URL www.clinicaltrials.gov) that
specified altered genes within the inclusion criteria and were
actively recruiting patients in August 2014. In all cases, the
tumor type relevant to the FDA approval or studied in the clinical
trials was determined to allow the clinical information to be
matched to the mutational data by both gene and cancer type.
Statistical Analyses for Clinical and Genetic Data
[0040] Unpaired T-test and chi-square were employed to compare
mutation status of MLL genes among different groups with different
clinical and pathological characteristics. Curves for overall
survival and progression free survival (calculated as the time from
diagnosis to disease progression) were constructed using the
Kaplan-Meier method and compared between groups using the log-rank
test. Cox proportional hazards regression analysis was used to
determine which independent factors jointly had a significant
impact on overall survival. All p values were based on 2-sided
testing and differences were considered significant at p<0.05.
Passenger probabilities were calculated using the binomial test
adjusted for gene sizes and corrected for multiple comparisons.
Genes which were recurrently mutated within the comprehensive exome
analysis (>2 cases) were considered. Statistical analyses of
clinical and genetic features were performed with SPSS version 22
for windows, while conservation of specific genomic positions were
evaluated using phyloP software.sup.23.
Digital PCR Analyses
[0041] KRAS, BRAF, or PIK3CA somatic point mutations were
identified through sequencing analysis of tumor tissues. In cases
with matched plasma samples, point mutations were detected in the
plasma using droplet digital PCR (ddPCR) using the BioRad QX200.TM.
Droplet Digital.TM. PCR System (Hercules, Calif.). Briefly,
specific ddPCR assays for each point mutation were obtained from
BioRad (Hercules, Calif.) and applied to assess the mutant allele
fraction (mutant genomic equivalents/total genomic equivalents).
Prior to analysis of each point mutation in the patient plasma
sample, a panel of at least 160 normal control analyses were used
to confirm the mutation specificity of the assay. Additionally,
control samples of wild-type DNA were included in each
analysis.
Example 2
[0042] In order to identify genetic alterations that may be related
to patient outcome and other clinical characteristics, we performed
large-scale genomic analyses of pancreatic adenocarcinomas using
two prospectively collected clinical cohorts.
[0043] We used next generation sequencing to examine the entire
exomes of matched tumor-normal specimens from 24 patients and
targeted sequencing to analyze an additional 77 patient tumors.
These approaches allowed us to identify sequence changes, including
single base and small insertion or deletion mutations, as well as
copy number alterations in >20,000 genes in the whole-exome
analyses and in 116 specific genes in the targeted analyses
(Supplementary Table 1). The pancreatic cancers analyzed were stage
II tumors in patients who underwent potentially curative
resections. Given the low neoplastic cellularity of pancreatic
cancers, we enriched for neoplastic cells either by macrodissecting
primary tumors or by flow-sorting tumor nuclei (example 1), and
performed high-coverage sequencing of these enriched samples. We
obtained a per-base sequencing coverage of 234-fold for each tumor
analyzed by whole-exome sequencing and 754-fold for each tumor
analyzed by targeted cancer gene sequencing (Example 1).
[0044] We detected an average of 114 tumor-specific (somatic)
non-synonymous sequence alterations in the cancers analyzed by
whole exome sequencing, similar to previous studies of this tumor
type.sup.2,3, and 4.7 non-synonymous sequence alterations per
cancer in the targeted analyses (Supplementary Table 4). Among
known recurrent sequence alterations in the cancers analyzed we
identified mutations in the known pancreatic cancer driver genes:
KRAS (88%), TP53 (77%), SMAD4 (29%), CDKN2A (18%), and TGFBR2 (7%)
(Supplementary Tables 4 and 5).sup.2,3. Homozygous deletions were
difficult to assess given the low purity of the samples, but such
alterations were identified in CDKN2A in an additional 5% of
cases.
[0045] We also identified recurrent somatic alterations in genes
involved in chromatin regulation or modification, primarily
involving the AT-rich interactive domain-containing ARID1A gene (9%
of cases) and the histone methyltransferase MLL3 gene (7%)
(Supplementary FIG. 1, Supplementary Tables 4 and 5).sup.6. Six of
the alterations in ARID1A were either nonsense or frameshift
alterations which were predicted to truncate the protein
(Supplementary Table 4, Supplementary FIG. 1). Mutations in the
MLL3 gene included a combination of nonsynonymous, nonsense,
frameshift and splice-site mutations which occurred in amino acids
predicted to be evolutionarily conserved (Supplementary Table 4,
Supplementary FIG. 1). We found somatic frameshift and
nonsynonymous sequence alterations in the related
methyltransferases MLL or MLL2 in eight additional cases.
Interestingly, no tumor had more than one gene mutated among the
MLL genes suggesting that mutation in any one may be sufficient to
confer a selective advantage in neoplastic cells.
Example 3
[0046] Given the global cellular changes regulated by chromatin
regulators.sup.7,8, we examined the survival characteristics of
patients with mutations in either the MLL or ARID1A genes and found
that patients with MLL alterations had a prolonged survival
compared to those that were wild-type at these loci. Over three
quarters (79%) of patients with mutations in MLL, MLL2 or MLL3 were
still alive at the time of the analysis (median follow-up of 32
months), while the median survival in patients with wild-type
sequences of these genes was 15.3 months (p=0.0063; log-rank test,
FIGS. 2A-2C and Supplementary FIG. 2). MLL mutation status was
independent of clinical characteristics (Supplementary Table 7,
p>0.05 for all comparisons by chi-square and unpaired t-test)
and was found to be an independent prognostic factor (Supplementary
Table 8, p=0.015, Cox multivariate regression analysis). Patients
with alterations in ARID1A had improved survival (p<0.05,
log-rank test) but this observation was limited by a shorter
follow-up time in affected individuals. Patients with mutations in
any of the chromatin regulating genes identified had prolonged
overall and progression-free survival and these observations were
independent of other clinical variables (p<0.01 for all
analyses, FIG. 2A-2C, Supplementary FIG. 2, and Supplementary Table
8). Genomic analyses in other tumor types have shown that somatic
mutations of epigenetic regulators can have important clinical
consequences, including improved outcome in patients with DAXX/ATRX
alterations in pancreatic neuroendocrine tumors.sup.9, and a
decreased survival in patients with ARID1A and ARID1B mutations in
neuroblastome.sup.10.
Example 4
[0047] In parallel to the sequencing analyses of neoplastic
tissues, we evaluated the utility of using somatic mutations in
circulating tumor DNA (ctDNA) to identify patients likely to recur
after surgical intervention. Through sequencing analyses of tumor
samples we identified somatic mutations that could be used to
detect ctDNA in 51 patients from whom plasma was available, largely
focusing on alterations in the KRAS, BRAF and PIK3CA genes (Online
Methods). Using digital polymerase chain reaction (dPCR)
approaches, we were able to demonstrate that these alterations were
detectable in the plasma of 22 patients (43%) at the time of
diagnosis, with a specificity of >99.9% (Example 1). Consistent
with recent reports.sup.11,12, these results suggest that a
significant fraction of early stage pancreatic cancers could be
diagnosed non-invasively using approaches that focus on a few
specific genetic alterations.
Example 5
[0048] dPCR analyses were performed using plasma samples obtained
at various time points after surgical resection. These analyses
revealed that patients with detectable ctDNA in their plasma were
more likely to relapse than those with undetectable alterations
(p=0.02, log-rank test, FIG. 3a). Disease progression using ctDNA
was detected at an average of 3.1 months after surgery compared to
9.6 months using standard CT imaging (p=0.0004, paired t-test, FIG.
3b). The presence of ctDNA at the time of diagnosis also provided a
predictor of disease recurrence (p=0.015, log-rank test,
Supplementary FIG. 3). These analyses suggest that tests to detect
sequence alterations in cell free DNA may provide a highly specific
approach for early detection of residual or recurrent disease after
surgical resection.
Example 6
[0049] Given the poor outcome and limited therapeutic options for
patients with pancreatic cancer, we investigated whether mutations
observed in individual cases may be clinically actionable using
existing or investigational therapies. We examined genetic
alterations that were associated with 1) FDA-approved therapies for
oncologic indications, 2) therapies in published prospective
clinical studies, and 3) ongoing clinical trials for patients with
pancreatic cancer or other tumor types. We also evaluated
alterations in five genes in the patients' germline that may affect
cancer predisposition as detection of such changes have important
implications for early detection and intervention.sup.13.
[0050] Through these analyses we were able to identify somatic
alterations with potentially actionable consequences in 98 of the
101 patients (97%) (Table 1, Supplementary Table 10). Even if one
excludes clinical trials related to alterations in KRAS and TP53,
over a third (38%) of patients had clinically actionable mutations
(Table 1). These alterations included amplification of the
HER-2/neu tyrosine kinase ERBB2, the serine and threonine kinases
AKT1 and AKT2 genes, the cyclin dependent kinase CDK4 gene, and the
E3 ubiquitin ligase MDM2 gene. We also observed nonsynonymous
somatic mutations in the catalytic domains of the
phosphatidylinositol-4,5-bisphosphate 3-kinase, PIK3CA, and the
v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog, KIT
(Supplementary Table 4). These alterations were at or nearby
previously identified somatic mutations in other human
cancers.sup.14. In addition, we identified three patients with
truncating somatic alterations in BRCA2: two with heterozygous
somatic nonsense alterations, a patient with a frameshift
alteration, and a fourth patient with a germline frameshift in
BRCA2 together with a loss of heterozygosity (LOH) in the
matched-tumor sample (Supplementary Table 4).
[0051] These alterations represent potential targets of clinical
intervention in pancreatic cancer. Poly(adenosine diphosphate
[ADP]-ribose) polymerase (PARP) inhibitors and DNA damaging agents
such as cisplatin and mitomycin C have been shown to provide a
synthetic lethal therapeutic strategy for treatment of cancers with
defects in components of the homologous recombination repair
pathway, such as BRCA1/2.sup.15-18. Trastuzumab has demonstrated
therapeutic efficacy against GI tumors with ERBB2
amplification.sup.19 and is currently being evaluated in clinical
trials for patients with metastatic colorectal cancer.sup.20. Small
molecule inhibitors have been reported that target proteins or the
pathways encoded by the altered genes identified, including PIK3CA,
BRAF, AKT1/AKT2, and MDM2, but these not been evaluated in
pancreatic cancer.
[0052] This study highlights information that may be obtained
through the integration of large-scale genomic and clinical
analyses in pancreatic cancer. Although careful measures were taken
to increase sensitivity of detecting genetic changes in the tumors
and in the circulation of these patients, some alterations may not
have been detected due to low tumor purity, limited plasma amounts,
and low mutant allele frequency. Despite these limitations, these
data add to our growing understanding of pancreatic cancer.
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