Ultra-deep sequencing detects ovarian cancer cells in peritoneal fluid and reveals somatic TP53 mutations in noncancerous tissues

Abstract

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 peritoneal fluid from nearly all patients with and without cancer (35/37). These mutations were mostly deleterious, clustered in hotspots, increased 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 mutations were also found in 100% of peripheral blood samples from 15 women with and without ovarian cancer (none with hematologic disorder). Our results demonstrate the ability of duplex sequencing to detect rare cancer cells and provide evidence of widespread, low frequency, age-associated somatic TP53 mutation in noncancerous tissue.

Keywords: TP53 mutations; clonal hematopoiesis; ovarian cancer; premalignant mutations; ultra-deep sequencing.

Conflict of interest statement

Conflict of interest statement: M.W.S. and L.A.L. declare leadership, consulting role, and stock ownership at TwinStrand Biosciences, Inc.

Figures

Fig. 1.

TP53 mutations detected in ovarian tumors are also present in peritoneal fluid. Sample ID, Fédération Internationale de Gynécologie et d’Obstétrique (FIGO) stage, and cytopathological results are indicated in the x axis. Samples 1–3 correspond to cancers incidentally discovered at prophylactic surgery in women with hereditary BRCA mutations. Samples 15A and 15B correspond to primary and recurrence surgeries from the same patient. Sample 15A was unstaged because this patient was undergoing chemotherapy for a previously diagnosed breast malignancy. Tumor mutant allele frequency was calculated 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.

Fig. 2.

Mutant allele frequency of TP53 mutations (exons 4–10) in peritoneal 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.

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 mutations for B was determined via “MUT-TP53 2.00” (24).

Fig. 4.

Frequency of biological background mutations (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 controls. Women without ovarian cancer showed significant 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 segregated 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).

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).

Fig. 6.

TP53 mutations in peripheral blood. Patient ID is indicated in the x axis. Each bar represents a unique mutation observed 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.