MEDICALSCIENCES
`
`Ultra-deep sequencing detects ovarian cancer cells in
`peritoneal fluid and reveals somatic TP53 mutations
`in noncancerous tissues
`
`Jeffrey D. Krimmela, Michael W. Schmitta,b, Maria I. Harrellc, Kathy J. Agnewc, Scott R. Kennedya, Mary J. Emondd,
`Lawrence A. Loeba, Elizabeth M. Swisherc, and Rosa Ana Risquesa,1
`
`aDepartment of Pathology, University of Washington, Seattle, WA 98195; bDivisions of Hematology and Medical Oncology, Department of Medicine,
`University of Washington, Seattle, WA 98195; cDepartment of Obstetrics and Gynecology, University of Washington, Seattle, WA 98195; and dDepartment
`of Statistics, University of Washington, Seattle, WA 98195
`
`Edited by Philip C. Hanawalt, Stanford University, Stanford, CA, and approved March 31, 2016 (received for review January 25, 2016)
`
`Current sequencing methods are error-prone, which precludes the
`identification of low frequency mutations for early cancer detection.
`Duplex sequencing is a sequencing technology that decreases errors
`by scoring mutations present only in both strands of DNA. Our aim
`was to determine whether duplex sequencing could detect extremely
`rare cancer cells present in peritoneal fluid from women with high-
`grade serous ovarian carcinomas (HGSOCs). These aggressive cancers
`are typically diagnosed at a late stage and are characterized by TP53
`mutations and peritoneal dissemination. We used duplex sequencing
`to analyze TP53 mutations in 17 peritoneal fluid samples from women
`with HGSOC and 20 from women without cancer. The tumor TP53
`mutation was detected in 94% (16/17) of peritoneal fluid samples
`from women with HGSOC (frequency as low as 1 mutant per
`24,736 normal genomes). Additionally, we detected extremely low
`frequency TP53 mutations (median mutant fraction 1/13,139) in peri-
`toneal fluid from nearly all patients with and without cancer (35/37).
`These mutations were mostly deleterious, clustered in hotspots, in-
`creased with age, and were more abundant in women with cancer
`than in controls. The total burden of TP53 mutations in peritoneal
`fluid distinguished cancers from controls with 82% sensitivity (14/17)
`and 90% specificity (18/20). Age-associated, low frequency TP53 mu-
`tations were also found in 100% of peripheral blood samples from
`15 women with and without ovarian cancer (none with hemato-
`logic disorder). Our results demonstrate the ability of duplex se-
`quencing to detect rare cancer cells and provide evidence of
`widespread, low frequency, age-associated somatic TP53 mutation
`in noncancerous tissue.
`TP53 mutations | ultra-deep sequencing | ovarian cancer | clonal
`hematopoiesis | premalignant mutations
`The detection of tumor-specific mutations in clinically accessible
`
`samples has enormous potential to transform cancer diagnos-
`tics, monitoring, and screening. However, a major limitation is
`insufficiently accurate sequencing methods. Conventional next-
`generation sequencing (NGS) technologies have a high false pos-
`itive error rate, which precludes reliable detection of mutations at
`frequencies <1/100 (1). “Molecular tagging” of single-stranded
`DNA decreases the rate of false mutations to less than 1 per 10,000
`sequenced nucleotides and has been successfully applied to the
`detection of mutant cancer DNA in a variety of clinical samples (2–
`6). However, this false positive error rate limits the specificity of
`this method in challenging situations in which ultra-deep se-
`quencing is needed to detect extremely low frequency mutant
`molecules (e.g., <1/10,000), as is the case of ovarian cancer DNA in
`Pap smears (5). Because true mutations are indistinguishable from
`artifacts, compromised specificity leads to lower sensitivity and
`overall low diagnostic accuracy. Duplex sequencing is an NGS
`technology that employs molecular tagging of both strands of DNA
`independently. True mutations are defined as mutations that are
`present at the same position in both strands of DNA and that are
`complementary (7). This internal error correction effectively reduces
`
`false positive mutations because PCR and sequencing artifacts are
`very unlikely to occur at both strands of DNA at the same position
`and with complementary nucleotide changes (theoretical false
`positive rate is ∼4 × 10−10) (7). Previous studies have demonstrated
`that duplex sequencing is able to detect a single point mutation
`among >107 sequenced nucleotides (7, 8), an unprecedented ac-
`curacy that holds significant potential for early cancer detection.
`High-grade serous ovarian carcinoma (HGSOC) is the most
`common and most aggressive type of ovarian cancer, with a dismal
`5-y survival rate of 10–30% (9). A main cause of poor prognosis is
`the absence of effective screening tools to detect early-stage disease.
`HGSOC frequently metastasizes through the peritoneal cavity, the
`anatomic potential space between abdominal and pelvic organs and
`the abdominal walls. The putative premalignant lesion to HGSOC
`is intraepithelial neoplasia in the distal fallopian tube (also known
`as serous tubal intraepithelial carcinoma), which is in direct conti-
`nuity with the peritoneal cavity (10–12). Even in the absence of
`gross metastasis to the peritoneum, ovarian cancer cells can fre-
`quently be found in peritoneal fluid upon cytopathological exami-
`nation, and the presence of these cells has prognostic value in the
`current clinical staging system (13). Thus, peritoneal fluid is rou-
`tinely collected during surgery for women with suspected ovarian
`cancer. We reasoned that peritoneal fluid is an optimal clinical
`biopsy for high-sensitivity early detection of ovarian cancer because
`
`Significance
`
`The detection of rare tumor-specific somatic mutations in “liquid
`biopsies” is limited by the high error rate of DNA sequencing
`technologies. By sequencing peritoneal fluid from women with
`high-grade serous ovarian cancer, we demonstrate that duplex
`sequencing, currently the most accurate sequencing technology, is
`able to detect one cancer cell among tens of thousands of normal
`cells. This unprecedented sensitivity also revealed a striking prev-
`alence of extremely low frequency TP53 mutations in normal tis-
`sue. Women with and without cancer harbored TP53 mutations of
`pathogenic consequences, both in peritoneal fluid and peripheral
`blood. These mutations likely represent a premalignant muta-
`tional background that accumulates in cancer and aging.
`
`Author contributions: J.D.K., L.A.L., E.M.S., and R.A.R. designed research; J.D.K. and M.I.H.
`performed research; M.W.S., K.J.A., and S.R.K. contributed new reagents/analytic tools;
`J.D.K., M.J.E., and R.A.R. analyzed data; and J.D.K., L.A.L., E.M.S., and R.A.R. wrote
`the paper.
`
`Conflict of interest statement: M.W.S. and L.A.L. declare leadership, consulting role, and
`stock ownership at TwinStrand Biosciences, Inc.
`
`This article is a PNAS Direct Submission.
`
`Data deposition: Sequencing data from this paper have been deposited in the Sequence
`Read Archive [accession no. SRP072370 (BioProject ID: PRJNA316476)].
`1To whom correspondence should be addressed. Email: rrisques@uw.edu.
`
`This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
`1073/pnas.1601311113/-/DCSupplemental.
`
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`ycneuqerF elellA tnatuM romuT
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`in Peritoneal Fluid
`
`10 11 12 13 14 15A 15B 16
`9
`8
`7
`6
`5
`4
`3
`2
`1
` ID
`Stage
`IA IC IA IC IIB IIC IIC IIIB IIIB IIIB IIIC IIIC IIIC NA REC REC
`0
`Cytology neg neg pos neg pos neg neg pos neg neg pos neg atyp pos neg pos atyp
`
`Fig. 1. TP53 mutations detected in ovarian tumors are also present in peri-
`toneal fluid. Sample ID, Fédération Internationale de Gynécologie et d’Obsté-
`trique (FIGO) stage, and cytopathological results are indicated in the x axis.
`Samples 1–3 correspond to cancers incidentally discovered at prophylactic sur-
`gery in women with hereditary BRCA mutations. Samples 15A and 15B corre-
`spond to primary and recurrence surgeries from the same patient. Sample 15A
`was unstaged because this patient was undergoing chemotherapy for a pre-
`viously diagnosed breast malignancy. Tumor mutant allele frequency was cal-
`culated as the number of Duplex Consensus Sequence (DCS) reads with the
`given mutation divided by the total DCS nucleotides sequenced at the mutation
`coordinate. Tumor 16 was the only one with an indel, and matching peritoneal
`fluid showed the indel mutations in single-strand consensus sequences, but not
`DCS. Errors bars represent the exact/Clopper–Pearson 95% confidence interval.
`atyp, atypical; NA, not available; neg, negative; pos, positive; REC, recurrence.
`
`was, however, significantly associated with positive peritoneal fluid
`cytology (mean ± SD, 0.212 ± 0.30 in positive cytology vs. 0.004 ±
`0.009 in negative or atypical cytology, Mann–Whitney P = 0.009)
`and ascites as opposed to peritoneal washes (mean ± SD, 0.132 ±
`0.27 in ascites vs. 0.048 ± 0.15 in peritoneal washes, Mann–Whitney
`P = 0.009). After adjusting for possible confounding of one variable
`by another in multivariate models, higher TMAF remained asso-
`ciated with ascites but not with positive cytology. In addition to
`ascites, older age also associated with higher TMAF in all models
`(SI Appendix, Table S4).
`
`Low Frequency TP53 Mutations Were Found in Peritoneal Fluid from
`Nearly All Patients. We detected low frequency (<0.001) TP53
`mutations in nearly all of the peritoneal fluid samples from women
`with and without cancer (Fig. 2) (16/17 cancers and 19/20 controls).
`A total of 197 mutations were found (Dataset S2): 97 mutations in
`ovarian cancer patients and 100 mutations in controls. It was pre-
`viously demonstrated that duplex sequencing is able to uniquely
`detect a single mutation among >107 sequenced nucleotides, which
`places the false positive rate of this technology below 10−7 (7).
`Using this figure as a conservative estimate of the false positive
`error rate and given the fact that a total of ∼3.8 × 108 DCS nu-
`cleotides were sequenced in this study, we calculated that poten-
`tially ∼38 mutations could be artifacts. This figure represents only
`20% of all of the mutations found and leaves >150 mutations
`unlikely to be explained as technological error. To distinguish them
`from the tumor mutations, we termed these highly prevalent low
`frequency TP53 mutations “biological background.”
`The mean number of biological background mutations per sample
`was 5.3 (range, 0–14). The number of mutations was directly pro-
`portional to the DCS depth for each sample (i.e., the deeper a sample
`was sequenced, the more mutations were found) (SI Appendix, Fig.
`S2). For cancer patients, the tumor mutation was more abundant
`than biological background mutations in the majority of peritoneal
`fluid samples (11/16) and was at least 10-fold more abundant than
`biological background mutations in 50% (8/16) of samples (Fig. 2A).
`
`Low Frequency TP53 Mutations in Peritoneal Fluid Are Similar to
`Cancer-Specific TP53 Mutations. To explore whether these low
`
`HGSOC disseminates early and preferentially to the peritoneal
`cavity, suggesting that cancer cells may be more abundant in peri-
`toneal fluid than in the relatively distant uterine cavity or cervix, as
`previously attempted by other studies (5, 14).
`An important feature of HGSOC, which may facilitate early de-
`tection by high-sensitivity sequencing, is the high prevalence of tumor
`protein p53 gene (TP53) mutations (>96%) (15, 16), even in pre-
`malignant lesions (17). Moreover, >95% of TP53 mutations cluster in
`exons 4–10 (15), which provides a relatively small target to perform
`cost-efficient ultra-deep sequencing (8). Thus, we used duplex se-
`quencing to sequence TP53 exons 4–10 in peritoneal fluid from pa-
`tients with HGSOC with known TP53 mutations and control patients
`without ovarian cancer. Our goal was to provide proof of principle of
`the ability of duplex sequencing to detect very rare cancer cells, and
`thus the study was enriched for subjects with early stage disease or
`negative peritoneal fluid by traditional cytological evaluation.
`
`Results
`Patients and Sequencing Information. Sixteen patients with HGSOC
`(“ovarian cancers”) (SI Appendix, Table S1) and 20 patients without
`detected gynecologic malignancy (“controls”) (SI Appendix, Table
`S2) were included in this study. Seven ovarian cancer patients and
`10 control patients had germline BRCA1 or BRCA2 breast cancer
`genes mutations. Half of the cancers were early stage (0–II). TP53
`mutations were determined by NGS in all primary tumors except
`three occult microscopic cancers, for which Sanger sequencing was
`used due to the limited amount of DNA (SI Appendix, SI Materials
`and Methods) (18–20). A single clonal TP53 mutation was found in
`all tumors (SI Appendix, Table S3). No additional clonal or sub-
`clonal TP53 mutations were found in any of the primary tumors
`(NGS average depth was ∼300×). Peritoneal fluid was centrifuged,
`and DNA was extracted from the cell pellet, obtaining an average
`of 11.9 μg of DNA (range 1.1–112 μg). Duplex sequencing for TP53
`exons 4–10, which cover >95% of mutations in HGSOC (15), was
`performed. Molecular tagging of both strands of DNA allowed us to
`group raw reads sharing the same molecular tag into a single-strand
`consensus sequence (SSCS) and to collapse the two SSCSs with
`complementary tags into a single, highly accurate duplex consensus
`sequence (DCS) (SI Appendix, Fig. S1). The median DCS depth was
`calculated as the median DCS coverage at each genomic position in
`the capture target, and this value essentially corresponds to the total
`number of unique haploid genomes sequenced. The median DCS
`depth for the 37 peritoneal fluid samples ranged from 1,689 to
`36,133. Sequencing information is presented in Dataset S1.
`
`Duplex Sequencing Detected Tumor-Specific TP53 Mutations in
`Almost All Ovarian Cancer Peritoneal Fluid Samples. The TP53 mu-
`tation identified in the primary tumor was detected in 94% (16/
`17) of HGSOC peritoneal fluid samples (Fig. 1), including 9
`peritoneal fluids without malignant cytopathology. In one of the
`cases (case 16), the mutation was not detected in DCS reads but
`was present in two SSCS reads well above background. The only
`cancer missed was an occult stage IA carcinoma with negative
`cytopathology. Importantly, half of the tumor mutations (8/16)
`were found at a frequency at or below 0.001 (3/16 at a frequency
`at or below 0.0001) and would not be reliably discernible from
`technical errors with less accurate sequencing techniques.
`In one patient, peritoneal fluid samples were available from two
`different surgeries: primary surgery and subsequent surgery for
`recurrent disease 2 y later. The exact same tumor-specific TP53
`mutation was found in both. The tumor mutant allele frequency
`(TMAF), which should approximate the fraction of tumor cells in
`the sample, increased dramatically from 0.000039 to 0.685 from the
`initial peritoneal wash to the recurrent ascites.
`In univariate analyses of dependent variables vs. TMAF in
`peritoneal fluid, TMAF was not significantly associated with pre-
`operative CA-125 (Spearman test), germline BRCA status, clinical
`stage, or future recurrence (Mann–Whitney test). Higher TMAF
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`MEDICALSCIENCES
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`abundance of C:G→T:A transitions. Furthermore, 38.6% of C:G→T:A
`mutations occurred at CpG sites, which are known to be highly
`mutable and prone to deamination. These data are consistent with
`known mutational signatures in cancer associated with age, specif-
`ically signatures 1A and 1B reported in Alexandrov et al. (25, 26).
`
`Low Frequency TP53 Mutations Increase with Cancer and with Age.
`Next, we quantified the frequency of biological background TP53
`mutations for each individual as the number of mutations divided by
`the total number of DCS nucleotides. Interestingly, women with
`ovarian cancer had a significantly higher frequency of TP53 muta-
`tions in exons 4–10 than cancer-free women (8.4 × 10−7 in cancers
`vs. 4.23 × 10−7 in controls, Mann–Whitney P = 0.02) (SI Appendix,
`Fig. S8), and this significant difference remained after adjusting for
`age and BRCA status (P = 0.004). Although our study was focused
`on TP53 coding mutations, the sequencing protocol resulted in the
`incidental capture of intronic regions contiguous with TP53 exons
`4–10, which also contain low-frequency biological background mu-
`tations. The frequency of mutations in introns was higher in cancers
`than in controls, but this comparison was not statistically significant
`(SI Appendix, Fig. S8). Notably, in control women, we found that
`the frequency of TP53 biological background mutations increased
`with age for mutations found in exons (Fig. 4A) as well as in introns
`(Fig. 4B). The frequency of mutations increased by 2.2 × 10−7
`for every 10-y increase in age for exons (P = 0.001 after adjusting for
`BRCA status) and by 1.1 × 10−7 for every 10-y increase in age for
`introns (P = 0.01 after adjusting for BRCA status). These regres-
`sions also were done separately for women with and without
`germline BRCA mutations because of the near complete age sep-
`aration between those two groups and were statistically significant
`for mutations in exons and introns regardless of germline muta-
`tional status (Fig. 4 A and B) with near parallel slopes, as assumed
`in the common regression model. In women with ovarian cancer,
`there was no association of exonic TP53 mutations with age, but the
`intronic mutation frequency showed a significant increase of 3.0 ×
`10−7 with every 10-y increase in age after adjusting for BRCA status
`(P = 0.0004) (Fig. 4 C and D).
`
`B
`
`Missense MutaƟons
`FracƟon of TP53
`
`C
`
`FracƟon of TP53 MutaƟons
`
`A
`
`FracƟon of TP53 MutaƟons
`
`Fig. 3. Characterization of “biological background” TP53 mutations found in
`peritoneal fluid of patients with ovarian cancer (97 mutations) and controls (100
`mutations). The fraction of mutations is indicated for categories of mutation
`type (A), pathogenicity (B), and spectrum (C). TP53 activity of missense muta-
`tions for B was determined via “MUT-TP53 2.00” (24).
`
`OVARIAN CANCER PATIENTS
`
`CONTROL PATIENTS
`
`15A 15B
`
`A
`
`Mutant Allele Frequency
`
`in Peritoneal Fluid
`
`B
`
`Mutant Allele Frequency
`
`in Peritoneal Fluid
`
`Fig. 2. Mutant allele frequency of TP53 mutations (exons 4–10) in perito-
`neal fluid from patients with ovarian cancer (A) and controls (B). Each bar
`represents a unique mutation observed at least once. Mutations are ordered
`by descending mutant allele frequency within each patient. Magenta bars
`indicate tumor mutations.
`
`frequency TP53 mutations were biologically relevant, we first ana-
`lyzed their type. Most of the background mutations were missense,
`both in women with (67/97) and without cancer (72/100) (Fig. 3A).
`The prevalence of missense mutations is consistent with clonal
`TP53 mutations most commonly seen in human cancers in general
`and in ovarian cancers in particular, according to the International
`Agency for Research on Cancer (IARC) ovarian cancer database
`(21, 22) (SI Appendix, Fig. S3). Specifically, within exons 5–8, which
`encode the protein’s DNA-binding domain and harbor the majority
`of TP53 mutations found in human cancers, there are 1,567 possible
`single nucleotide substitutions, which are expected to produce
`73.4% missense, 3.7% nonsense, and 22.9% silent mutations (23).
`However, in our study, silent mutations were less than half the
`expected frequency, in both cases and controls (SI Appendix, Fig.
`S4). Nonsynonymous mutations, which include missense and non-
`sense, represented 89.8% (53/59) and 90.0% (63/70) of all single
`nucleotide substitutions in these exons in cases and controls, re-
`spectively, significantly above the 77.1% expected in the absence of
`selection (P = 0.027 in cancers; P = 0.013 in controls, by Fisher’s
`exact test). Approximately 80% of these missense mutations were
`projected to generate an inactive or partially inactive p53 protein
`(Fig. 3B) as determined by TP53-MUT 2.00, an online tool that
`predicts the biological activity of known TP53 mutations (24). In
`addition, missense mutations were enriched in the 9 most com-
`monly mutated “hotspot” TP53 codons (175, 179, 195, 220, 237,
`245, 248, 273, and 282) in ovarian carcinomas according to the
`IARC database (21, 22). These codons represent only 2.7% of the
`codons in our capture set; however, 10/67 missense mutations in
`cancers (14.9%) and 13/72 missense mutations in controls (18.1%)
`clustered in those codons (P = 2 × 10−4 and P < 1 × 10−5, re-
`spectively, by Fisher’s exact test). Importantly, when cancers and
`controls were subdivided by BRCA germline status, the distribu-
`tion of mutation type and the functional impact of missense mu-
`tations remained very similar for each of the groups (SI Appendix,
`Fig. S5). To demonstrate that the findings were not driven by
`outlier individuals, we also plotted the distribution of mutation type
`(SI Appendix, Fig. S6) and predicted functional impact of missense
`mutations (SI Appendix, Fig. S7) for each patient in the study. The
`overwhelming majority of patients (including 19/20 controls) harbored
`at least one deleterious mutation. Next, we analyzed the mutational
`spectra of TP53 mutations found in ovarian cancers and controls
`(Fig. 3C). The spectrum was similar in both groups and showed an
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`Fig. 4. Frequency of biological background muta-
`tions (number of mutations divided by total number
`of DCS nucleotides) detected in TP53 exons 4–10
`and corresponding introns in peritoneal fluid of
`women with and without ovarian cancer. Patients’
`age is indicated in the x axis, and germline BRCA
`status is color-coded for ovarian cancers and con-
`trols. Women without ovarian cancer showed sig-
`nificant associations between the frequency of
`biological background TP53 mutations and age,
`both for mutations found in TP53 exons (A) and
`introns (B). Because control women were segre-
`gated into young age and old age depending on
`germline BRCA status, the correlations with age
`(regression lines and Spearman’s test P values) are
`presented separately for women with and without
`BRCA germline mutations. Women with cancer did
`not show a significant association between the
`frequency of biological background TP53 mutations
`in exons and age (C). For introns, the association
`was significant after adjusting for BRCA status (D).
`
`A
`
`CONTROLS- TP53 exons
`
`B
`
`CONTROLS- TP53 introns
`
`p=0.008
`
`p=0.05
`
`p=0.003
`
`p=0.05
`
`C
`
`OVARIAN CANCERS- TP53 exons
`
`D
`
`OVARIAN CANCERS- TP53 introns
`
`p=0.0004
`
`Frequency of TP53 Biological
`
`Background MutaƟons
`
`Frequency of TP53 Biological
`
`Background MutaƟons
`
`peritoneal fluid sample from the same patient, further proving the
`validity of these mutations. Leukocytes are common in peritoneal
`fluid (34), and, thus, overlap of mutations between matched blood
`and peritoneal fluid is expected. In one patient with ovarian cancer,
`the primary tumor TP53 mutation was identified in blood DNA,
`consistent with the presence of circulating tumor cells or cell free
`tumor DNA in whole blood. In the other six ovarian cancer pa-
`tients, the tumor-specific TP53 mutation was not found in blood.
`The type, pathogenicity, and spectrum of the TP53 mutations
`found in blood were very similar to mutations found in perito-
`neal fluid (SI Appendix, Fig. S9). In addition, similar to perito-
`neal fluid, 21.6% (8/37) of the nontumor missense mutations
`were present at one of the nine previously mentioned TP53
`hotspot codons although these codons represent only 2.7% of
`the total codons in TP53 exons 4–10 (P = 6 × 10−5). Further-
`more, consistent with our findings in peritoneal fluid and
`reported age-related clonal hematopoiesis (28–30, 32, 33), the
`frequency of TP53 biological background mutations in periph-
`eral blood increased significantly with patient age (P = 0.011).
`
`Discussion
`This study demonstrates that duplex sequencing—the most accu-
`rate NGS technique currently available—is able to identify tumor
`DNA at mutant allele frequencies as low as ∼1/25,000, which is
`
`TP53 MutaƟon Burden
`
`in Peritoneal Fluid
`
`OVARIAN CANCER PATIENTS
`
`CONTROL PATIENTS
`
`Fig. 5. TP53 mutation burden in peritoneal fluid distinguishes women with
`ovarian cancer from controls. Within each group, patients are sorted by
`ascending age, indicated in the x axis. For each sample, the mutation burden
`was calculated as the total number of mutant TP53 molecules (exons 4–10)
`divided by total DCS nucleotides sequenced. A threshold of 10−6 (red line,
`corresponding to one mutation for one million nucleotides) distinguishes
`cancers and controls with 82% (14/17) sensitivity and 90% specificity (18/20).
`
`TP53 Mutation Burden in Peritoneal Fluid Distinguishes Individuals
`With and Without Ovarian Cancer. We sought to assess whether
`the TP53 mutations detected in peritoneal fluid samples could
`distinguish individuals with ovarian cancer from controls without
`knowledge of the primary tumor TP53 mutation. As previously
`shown, almost all cancer samples harbor the tumor mutation (some
`at relatively high allele frequency) (Fig. 1), and most cancer samples
`carry more TP53 biological background mutations than controls
`(Fig. 4C vs. Fig. 4A). Thus, we reasoned that the total burden of
`mutated TP53 molecules found in a sample could be a useful bio-
`marker to distinguish individuals with and without cancer. For each
`sample, the mutation burden was calculated as the total number of
`mutant TP53 molecules in exons 4–10 divided by the total number
`of DCS nucleotides sequenced. Fourteen out of 17 peritoneal fluid
`samples from cancer patients had a TP53 mutation burden >10−6
`(Fig. 5). In contrast, only 2 out of 20 controls reached that
`threshold, and, interestingly, they were among the oldest controls in
`the study (Fig. 5). These frequencies correspond to 82% sensitivity
`and 90% specificity for distinguishing cancer patients from controls.
`
`Low Frequency TP53 Mutations Are also Found in Peripheral Blood.
`The observation that TP53 biological background mutations are
`present in the peritoneal fluid of essentially all patients (with and
`without ovarian cancer) provides evidence for the emerging concept
`that somatic mutation in classically cancer-associated “driver” genes
`may occur in “normal” tissues (27). However, because peritoneal
`fluid consists of a heterogeneous mixture of cell types, we sought to
`assess whether rare TP53-mutated subclones were present in a dif-
`ferent sample source. We chose peripheral blood because multiple
`studies have demonstrated that clonal hematopoiesis with mutations
`in driver genes occurs in a subset of normal individuals (28–33).
`We applied duplex sequencing to whole blood samples from 15
`women in our study (7 with ovarian cancer and 8 without cancer).
`No patients had known history of hematologic disease, and all but
`one were chemotherapy-naive at sample collection. We identified
`at least one low frequency TP53 mutation in all patients (15/15),
`with a range of 1–8 mutations per sample (Fig. 6). A comprehen-
`sive list of these mutations can be found in Dataset S2. Similar to
`the findings in peritoneal fluid, these mutant clones were exclu-
`sively present at extremely low mutant allele frequency (≤0.001),
`and, thus, they are undetectable by less accurate sequencing
`methods. Importantly, 22% (13/58) of the biological background
`mutations in peripheral blood were also detected in the matched
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`OVARIAN CANCER PATIENTS
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`Fig. 6. TP53 mutations in peripheral blood. Patient ID is in-
`dicated in the x axis. Each bar represents a unique mutation ob-
`served in at least one DCS. Mutations are ordered by descending
`mutant allele frequency within each sample. The tumor TP53
`mutation was detected in peripheral blood of case 9 but was not
`found in any other cases.
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`doolB ni ycneuqerF elellA tnatuM
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`MEDICALSCIENCES
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`beyond the capabilities of other sequencing technologies. Ultra-
`deep sequencing of TP53 by duplex sequencing enabled the de-
`tection of tumor DNA in peritoneal fluid from women with ovarian
`cancer with 94% sensitivity, despite enriching cases for early stage
`and negative peritoneal cytology. Tumor DNA was present in some
`cases that would otherwise challenge clinical detection, in particular
`two cancers that were microscopic and identified only at risk-
`reducing surgery. These results provide evidence that ovarian can-
`cer cells are present in the peritoneum even at the earliest de-
`tectable stages of disease and before clinically apparent metastasis.
`The high resolution afforded by duplex sequencing uncovered the
`presence of extremely low frequency, cancer-like TP53 mutations in
`peritoneal fluid and peripheral blood from nearly all patients with and
`without ovarian cancer. We termed these mutations “biological
`background” to distinguish them from tumor-specific TP53 muta-
`tions. Previous studies have reported somatic mutation of cancer-
`associated genes in normal tissue (blood and skin), but generally in
`relatively small subsets of older individuals (27–33, 35). Here, we
`show that low frequency, cancer-like TP53 mutations in noncancerous
`tissue are very common, but almost exclusively occur at allele fre-
`quencies <0.001, which is below the limit of detection of conventional
`sequencing methods. Remarkably, the only biological background
`mutation at frequency >0.001 was found in the oldest woman in the
`control group. Thus, our results demonstrate widespread, low fre-
`quency TP53 mutagenesis, in nearly all individuals, that increases with
`aging and cancer. These mutations are likely present in both the
`mesothelial lining of the peritoneal cavity (the dominant cell type in
`peritoneal fluid samples) as well as in leukocytes. We speculate that
`biological background mutation may be a phenomenon common to
`all healthy replicative tissues, but larger studies including multiple
`tissue samples from healthy individuals across a wide range of ages
`will be necessary to fully explore this concept.
`Several lines of evidence confirm that the majority of these bi-
`ological background mutations are functional and not technical ar-
`tifacts. First, they closely resemble TP53 mutations in cancers: nearly
`all of them are predicted to partially or completely inactivate TP53,
`they are predominantly C:G→T:A transitions, and they cluster in
`TP53 hotspot codons. Second, they are more abundant in women with
`cancer than in women cancer-free, and, in the latter, they increase
`with age. The age effect was observed for mutations detected in both
`exons and introns, and independently in the analysis of peritoneal fluid
`and peripheral blood. This age dependency is in concordance with
`prior studies of somatic mutations in noncancerous tissues (28–30, 32,
`33) and supports the notion that “clock-like mutations” commonly
`found in cancers accumulate in normal cells with aging before the
`development of cancer (25). Third, a proportion (13/58) of the low
`frequency mutations found in blood were also detected in peritoneal
`fluid from the same patient. Because peritoneal fluid is known to
`contain a variable number of leukocytes (34), this overlapping is
`expected and demonstrates the reproducibility of our approach.
`Our results indicate that noncancerous tissue carries clones with
`positively selected driver TP53 mutations. This finding is in agree-
`ment with a recent report of somatic cancer mutations in normal
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`human skin (36). Multiple cancer-associated driver genes, including
`TP53, seemed to be mutated and clonally expanded in large patches
`of morphologically normal skin cells. Although the high prevalence
`of these clones was surprising, it is consistent with the concept that
`cancer is the result of clonal evolution over the lifespan of an in-
`dividual. It is conceivable for multiple competing clones with cancer
`driver mutations to coexist and remain untransformed within nor-
`mal tissue, and it is expected that the number and size of these
`clones would increase with age. It is also expected that the indi-
`viduals that harbor more of these clones have higher probability of
`developing cancer. Indeed, individuals in previous studies carrying
`detectable somatic mutations in blood were at increased risk of
`developing hematopoietic malignancies (28–31, 33). Elevated mu-
`tagenesis is thought to be a characteristic feature of premalignant
`and malignant tissues (37), and our finding that women with
`HGSOC have a significantly higher burden of TP53 mutations in
`peritoneal fluid is cons