Quantification of tumor‐specific variants (TSVs) in cell‐free DNA is rapidly evolving as a prognostic and predictive tool in patients with cancer. Currently, both variant allele frequency (VAF) and number of mutant molecules per mL plasma are used as units of measurement to report those TSVs. However, it is unknown to what extent both units of measurement agree and what are the factors underlying an existing disagreement. To study the agreement between VAF and mutant molecules in current clinical studies, we analyzed 1116 TSVs from 338 patients identified with next‐generation sequencing (NGS) or digital droplet PCR (ddPCR). On different study cohorts, a Deming regression analysis was performed and its 95% prediction interval was used as surrogate for the limits of agreement between VAF and number of mutant molecules per mL and to identify outliers. VAF and number of mutant molecules per mL plasma yielded greater agreement when using ddPCR than NGS. In case of discordance between VAF and number of mutant molecules per mL, insufficient molecular coverage in NGS and high cell‐free DNA concentration were the main responsible factors. We propose several optimization steps needed to bring monitoring of TSVs in cell‐free DNA to its full potential.

Molecular profiling of tumor derived cell free DNA (cfDNA) is gaining ground as a prognostic and predictive biomarker. However to what extent cfDNA reflects the full metastatic landscape as currently determined by tumor tissue analysis remains controversial. Though technically challenging, whole exome sequencing (WES) of cfDNA enables thorough evaluation of somatic alterations. Here, we review the feasibility of WES of cfDNA and determine the sensitivity of WES-detected single nucleotide variants (SNVs) in cfDNA on individual patient data level using paired tumor tissue as reference (sharedSNVsAlltissueSNVs×100%). The pooled sensitivity was 50% (95% credible interval (CI): 29-72%). The tissue mutant allele frequency (MAF) of variants exclusively identified in tissue was significantly lower (12.5%, range: 0.5-18%) than the tissue MAF of variants identified in both tissue and cfDNA (23.9%, range: 17-38%), p = 0.004. The overall agreement (sharedSNVsAllSNVs×100%)between SNVs in cfDNA and tumor tissue was 31% (95% CI: 15-49%). The number of detected SNVs was positively correlated with circulating tumor DNA (ctDNA) fraction (p = 0.016). A sub analysis of samples with ctDNA fractions ≥ 25% improved the sensitivity to 69% (95% CI: 46-89%) and agreement to 46% (95% CI: 36-59%), suggesting that WES is mainly feasible for patients with high ctDNA fractions. Pre- and post-analytical procedures were highly variable between studies rendering comparisons problematic. In conclusion, various aspects of WES of cfDNA are largely in its investigative phase, standardization of methodologies is highly needed to bring this promising technique to its clinical potential.

ESR1 methylation was proposed as mechanism for endocrine resistance in metastatic breast cancer patients. To evaluate its potential as a minimally invasive biomarker, we investigated the feasibility of measuring ESR1 methylation in cell-free DNA (cfDNA) and its association with endocrine resistance. First, we provided evidence that demethylation in vitro restores ER expression. Subsequently, we found that ESR1 methylation in cfDNA was not enriched in endocrine-resistant versus endocrine-sensitive patients. Interestingly, we found a correlation between ESR1 methylation and age. Publicly available data confirm an age-related increase in ESR1 methylation in leukocytes, confounding the determination of the ESR1 methylation status of tumors using cfDNA.

According to the current guidelines, watchful waiting (WW) is a feasible option for patients with good or intermediate prognosis renal-cell carcinoma (RCC). However, some patients rapidly progress during WW, requiring the initiation of treatment. Here, we explore whether we can identify those patients using circulating cell-free DNA (cfDNA) methylation. We first defined a panel of RCC-specific circulating methylation markers by intersecting differentially methylated regions from a publicly available dataset with known RCC methylation markers from the literature. The resulting RCC-specific methylation marker panel of 22 markers was subsequently evaluated for an association with rapid progression by methylated DNA sequencing (MeD-seq) in serum from 10 HBDs and 34 RCC patients with a good or intermediate prognosis starting WW in the IMPACT-RCC study. Patients with an elevated RCC-specific methylation score compared to HBDs had a shorter progression-free survival (PFS, p = 0.018), but not a shorter WW-time (p = 0.15). Cox proportional hazards regression showed that only the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria were significantly associated with WW time (HR 2.01, p = 0.01), whereas only our RCC-specific methylation score (HR 4.45, p = 0.02) was significantly associated with PFS. The results of this study suggest that cfDNA methylation is predictive of PFS but not WW.

PURPOSE: Apolipoprotein B mRNA-Editing Catalytic Polypeptide-like (APOBEC) enzymes are mutagenic factors contributing to tumor progression and therapy resistance. However, the effects of APOBEC-induced protein changes have not been systematically assessed. Here, we describe the effects of APOBEC on the coding sequence in primary and metastatic estrogen receptor–positive (ER+)/human epidermal growth factor receptor 2–negative (HER2–) breast cancer (BC).METHODS: We determined the enrichment of amino acid (AA) changes resulting from APOBEC mutagenesis in 323 primary BC tumors and 424 metastatic breast cancer (mBC) lesions via comparison with a simulated mutational genomic landscape not under selection pressure. We subsequently explored genes with recurrent APOBEC-associated AA changes and investigated the clonality of individual APOBEC-associated mutations. Using public sequencing data from an independent primary BC and mBC cohort, we further confirm our findings by reporting genes having these enriched AA changes in an APOBEC context.RESULTS: Our analysis demonstrated that several APOBEC-derived AA changes are significantly enriched compared with a simulated AA change distribution drawn at random. Among the enriched AA changes, Glutamate(E)>Lysine(K) and Glutamate(E)>Glutamine(Q) were mostly found at hotspots in oncogenes, whereas termination codons (Glutamine[Q]>STOP[X] and Serine[S]>STOP[X]) occurred in tumor suppressor genes and, mostly, not at hotspot locations. These mutations are found in genes contributing to BC initiation, eg, introduction of termination codons in TP53, MAP3K1, and CDH1 (in lobular BC) and two oncogenic hotspots in PIK3CA (p.E542K and p.E545K). In endocrine-resistant BC, we observed APOBEC-induced termination codons at ER-modulating genes, KMT2C, ARID1A, NF1, and ZFHX3. Finally, in mBC, compared with single PIK3CA mutations, dual PIK3CA mutations occurred more frequently in an APOBEC context (Fisher's exact P < .001).CONCLUSION: Our results show that APOBEC mutagenesis recurrently targets various known drivers of BC initiation, progression, and endocrine resistance.