73 Background: Epigenetic alterations have been shown to govern many disease states, including cancer. A key epigenetic mark is the DNA methylation of CpGs. Large studies, like The Cancer Genome Atlas, have shown that DNA methylation can differentiate between cancer status and type. Here, differentially methylated genomic patterns were defined between patients with CRC and healthy individuals by utilizing patterns of co-methylation of adjacent CpG loci. Methods: Deep, whole genome bisulfite sequencing (WGBS) was conducted on DNA samples from 100 healthy individuals (median effective coverage of 352x±38x) and from 75 patients with CRC (median effective coverage of 48x±18x). The two cohorts were chosen to be balanced in terms of age (CRC: 58±11 years; healthy: 57±8 years) and to represent major ethnicities in the USA, and the CRC cohort was chosen to represent all stages, histologies and morphologies, and microsatellite instability (MSI, 23%). A novel machine learning model was developed to discover differentially methylated regions between the healthy and CRC cohorts as well as between subpopulations within the CRC cohort, including age, sex, stage, histology, and MSI vs microsatellite stability (MSS). Results: In total, we discovered 132,911 differentially methylated regions between healthy and CRC cohorts, spanning more than 1.14 million CpGs. 76% of all discovered regions were hypermethylated (70% CpG islands, 1.3% CpG shelves, 21% CpG shores) and the rest were hypomethylated (7.3% CpG islands, 8.6% CpG shelves, 25% CpG shores). We also discovered 220 hypermethylated regions that were differentially methylated between CRC MSI samples and CRC MSS samples and healthy cfDNA samples. Furthermore, we discovered subtype-specific differentially methylated regions, such as 62 hyper-methylated regions that were differentially methylated between mucinous adenocarcinoma samples and the rest of the cohort. Conclusions: Based on deep WGBS data from heterogeneous cohorts, representative of the US population eligible for CRC screening, we identified many differentially methylated regions as strong biomarker candidates for the early detection of cancer. Compared to recurrently mutated driver genes in CRC, we find that differential methylation profiles of CRC samples are generally much more homogenous and are therefore ideal biomarkers for targeted sequencing panels with the purpose of early cancer detection. Further, analysis of these patterns based on clinicopathologic factors enabled discovery of subtype specific markers, which can be incorporated to ensure equivalent performance for underrepresented subtypes or subpopulations.

Standard noninvasive methods for detecting renal allograft rejection and injury have poor sensitivity and specificity. Plasma donor-derived cell-free DNA (dd-cfDNA) has been reported to accurately detect allograft rejection and injury in transplant recipients and shown to discriminate rejection from stable organ function in kidney transplant recipients. This study used a novel single nucleotide polymorphism (SNP)-based massively multiplexed PCR (mmPCR) methodology to measure dd-cfDNA in various types of renal transplant recipients for the detection of allograft rejection/injury without prior knowledge of donor genotypes. A total of 300 plasma samples (217 biopsy-matched: 38 with active rejection (AR), 72 borderline rejection (BL), 82 with stable allografts (STA), and 25 with other injury (OI)) were collected from 193 unique renal transplant patients; dd- cfDNA was processed by mmPCR targeting 13,392 SNPs. Median dd-cfDNA was significantly higher in samples with biopsy-proven AR (2.3%) versus BL (0.6%), OI (0.7%), and STA (0.4%) (p < 0.0001 all comparisons). The SNP-based dd-cfDNA assay discriminated active from non-rejection status with an area under the curve (AUC) of 0.87, 88.7% sensitivity (95% CI, 77.7–99.8%) and 72.6% specificity (95% CI, 65.4–79.8%) at a prespecified cutoff (>1% dd-cfDNA). Of 13 patients with AR findings at a routine protocol biopsy six-months post transplantation, 12 (92%) were detected positive by dd-cfDNA. This SNP-based dd-cfDNA assay detected allograft rejection with superior performance compared with the current standard of care. These data support the feasibility of using this assay to detect disease prior to renal failure and optimize patient management in the case of allograft injury.

The DIR2s RNA aptamer, a second-generation, in-vitro selected binder to dimethylindole red (DIR), activates the fluorescence of cyanine dyes, DIR and oxazole thiazole blue (OTB), allowing detection of two well-resolved emission colors. Using Fab BL3-6 and its cognate hairpin as a crystallization module, we solved the crystal structures of both the apo and OTB-SO 3 bound forms of DIR2s at 2.0 Å and 1.8 Å resolution, respectively. DIR2s adopts a compact, tuning fork-like architecture comprised of a helix and two short stem-loops oriented in parallel to create the ligand binding site through tertiary interactions. The OTB-SO 3 fluorophore binds in a planar conformation to a claw-like structure formed by a purine base-triple, which provides a stacking platform for OTB-SO 3, and an unpaired nucleotide, which partially caps the binding site from the top. The absence of a G-quartet or base tetrad makes the DIR2s aptamer unique among fluorogenic RNAs with known 3D structure.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies.

BACKGROUND:The aim of this pilot study was to assess whether both ubiquitous and heterogeneous somatic mutations could be detected in cell-free DNA (cfDNA) from patients with early-stage non-small-cell lung cancer (NSCLC). PATIENTS AND METHODS:Three stage I and one stage II primary NSCLC tumors were subjected to multiregion whole-exome sequencing (WES) and validated with AmpliSeq. A subset of ubiquitous and heterogeneous single-nucleotide variants (SNVs) were chosen. Multiplexed PCR using custom-designed primers, coupled with next-generation sequencing (mPCR-NGS), was used to detect these SNVs in both tumor DNA and cfDNA isolated from plasma obtained before surgical resection of the tumors. The limit of detection for each assay was determined using cfDNA from 48 presumed-normal healthy volunteers. RESULTS:Tumor DNA and plasma-derived cfDNA was successfully amplified and sequenced for 37/50 (74%) SNVs using the mPCR-NGS method. Twenty-five (68%) were ubiquitous and 12 (32%) were heterogeneous SNVs. Variant detection by mPCR-NGS and WES-AmpliSeq in tumor tissue was well correlated (R(2) = 0.8722, P < 0.0001). Sixteen (43%) out of 37 SNVs were detected in cfDNA. Twelve of these were ubiquitous SNVs with a variant allele frequency (VAF) range of 0.15-23.25%, and four of these were heterogeneous SNVs with a VAF range of 0.28-1.71%. There was a statistically significant linear relationship between the VAFs for tumor and cfDNA (R(2) = 0.5144; P = 0.0018). For all four patients, at least two variants were detected in plasma. The estimated number of copies of variant DNA present in each sample ranged from 5 to 524. The average number of variant copies required for detection (VCRD) was 3.16 (range: 0.2-7.6 copies). CONCLUSIONS:The mPCR-NGS method revealed intratumor heterogeneity in early-stage NSCLC tumors, and was able to detect both ubiquitous and heterogeneous SNVs in cfDNA. Further validation of mPCR-NGS in cfDNA is required to define its potential use in clinical practice.

We demonstrate proof-of-concept for the use of massively multiplexed PCR and next-generation sequencing (mmPCR-NGS) to identify both clonal and subclonal copy-number variants (CNVs) in circulating tumor DNA. This is the first report of a targeted methodology for detection of CNVs in plasma. Using an in vitro model of cell-free DNA, we show that mmPCR-NGS can accurately detect CNVs with average allelic imbalances as low as 0.5%, an improvement over previously reported whole-genome sequencing approaches. Our method revealed differences in the spectrum of CNVs detected in tumor tissue subsections and matching plasma samples from 11 patients with stage II breast cancer. Moreover, we showed that liquid biopsies are able to detect subclonal mutations that may be missed in tumor tissue biopsies. We anticipate that this mmPCR-NGS methodology will have broad applicability for the characterization, diagnosis, and therapeutic monitoring of CNV-enriched cancers, such as breast, ovarian, and lung cancer.

Abstract Genomic instability, the hallmark of cancer, presents with a variety of mutation types, most commonly single nucleotide variations (SNVs) and copy number variations (CNVs), which traditionally have required different methods for identification. It has proven challenging to simultaneously achieve sufficient breadth to detect CNVs and depth to detect SNVs on samples of limited input amount. The objective of this study was to validate a new methodology for detection of SNVs and CNVs in a single assay. We used a massively multiplex PCR/NGS approach combining an SNV panel covering 585 point mutation hotspots in breast cancer (Cosmic) and a CNV panel targeting 28,000 SNPs designed to detect copy number at chromosomes 1, 2, 13, 18, 21, and X, and focal regions 4p16, 5p15, 7q11, 15q, 17p, 22q11, and 22q13. We applied these panels to breast cancer cell lines and fresh frozen (FF) breast tumor samples; the presence of CNVs in circulating cell-free tumor DNA (ctDNA) in the plasma of breast cancer patients was also investigated. The CNV assay methodology was validated using genomic DNA isolated from 96 human samples with known karyotype; sensitivity to single region deletions or duplications was 100% (71/71) and specificity was 100% for normal regions in the same samples. Single-molecule sensitivity for the detection of CNVs was established by analyzing isolated single cells. Performance of the mutation assay was demonstrated with the analysis of 5 matched tumor and normal cell lines, with 24 out of 27 SNVs known to be present in these cell lines detected. The 3 undetected SNVs were determined to be a result of assay design failure. Also, multiple somatic CNVs (median: 13) were detected in all 5 tumor cell lines. Analysis of the normal cell lines found no cancer related SNVs or CNVs. In 32 FF tumor samples, 78.1% (25/32) had SNVs detected; of samples with SNVs, 88% (22/25) had SNVs in TP53 or PIK3CA. Of the same 32 FF breast tumor samples, 96.9% (31/32) showed full or partial CNVs in at least 1 and up to 15 regions; of the 31 samples with detected CNVs, 93.5% had a CNV of either 1q or 17p, two of the three most prevalent breast cancer CNVs (the 16q region was not represented in this panel). Overall, a combination of SNV and CNV testing allowed identification of genetic changes in 100% of the breast tumor samples, a significant improvement in diagnostic yield than using SNV detection alone. Of the 12 breast cancer patients with matched tumor tissue and plasma samples, 83.3% (10/12) had CNVs detected in tissue. The CNVs present in each primary tumor sample were identified in corresponding plasma ctDNA samples (1 stage IIa, 7 stage IIb, and 2 stage III). The ctDNA fractions in these samples ranged from 0.58 to 4.33%; detection required as few as 86 heterozygous SNPs per CNV. Analysis of ctDNA for cancer-associated mutations may allow earlier, safer and more accurate profiling and monitoring of breast cancer. Thus, this targeted PCR approach offers the promise of an assay able to detect both cancer-associated SNVs and CNVs in the same sample with good sensitivity and specificity, and improved detection rates compared to assays that only detect SNVs. Citation Format: Robert J Pelham, Bernhard G Zimmermann, Eser Kirkizlar, Ryan K Swenerton, Bin Hoang, Onur Sakarya, Joshua E Babiarz, Nicholas Wayham, Tudor Constantin, Styrmir Sigurjonsson, Matthew Rabinowitz, Matthew Hill. Detection of single nucleotide variations and copy number variations in breast cancer tissue and ctDNA samples using single-nucleotide polymorphism-targeted massively multiplexed PCR [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-02-03.

Breast cancer screening involves mammography, which has high false positive rates and misses some cancers1-4. Analysis of tumor-derived circulating cell-free DNA (ctDNA) for cancer-associated copy number variations (CNVs) may allow for earlier, safer, and more accurate screening. Here, we employed a single-nucleotide polymorphism (SNP)-based massively multiplex PCR (mmPCR) approach to screen for CNVs in ctDNA isolated from the plasma of breast cancer patients. The mmPCR assay targeted 3,168 SNPs on chromosomes 1, 2, and 22q, which often have CNVs in cancer (e.g., 49% of breast cancer samples have a 22q deletion5). Here, we present case studies of six breast cancer patients: one stage IIa, four stage IIb, and one stage IIIb, with ctDNA fractions of 0.58-4.33%. Each tumor sample had CNVs on one or more of the targeted chromosomes. CNVs were identified in the corresponding plasma samples, including in one stage IIb sample with a ctDNA fraction of 0.58%; detection only required 86 heterozygous SNPs. This demonstrates that focal or whole chromosome arm CNVs, both common in cancer, can be readily detected. To further evaluate sensitivity, we generated 22 artificial mixtures containing a 3Mb 22q CNV, with ctDNA fractions of 0.85-14.7%. The method correctly detected CNVs in 100% of these samples with under $100 sequencing cost per sample. In numerous cancers, such as breast and ovarian, a significant proportion of tumors may only be detectable by CNVs instead of point mutations. Together, this supports that this SNP-based mmPCR approach offers a cost-effective, non-invasive method for detecting these cancers.

Evaluation of copy number variation (CNV) in tumor tissues typically involves SNP microarray or aCGH. These methods have high whole-genome resolution, but require large amounts of input material, have high fixed costs, and falter on FFPE samples. Here, we employ a 28,000-plex SNP-targeted PCR with NGS, targeting chromosomes 1, 2, 13, 18, 21 and X, and regions 4p16, 5p15, 7q11, 15q, 17p, 22q11, and 22q13, to detect CNVs from fresh and FFPE samples. An accuracy of 100% was demonstrated on 96 samples: 25 unaffected and 71 affected (minimum 3 samples per region). Single-molecule sensitivity was established by analyzing single cells. Among five matched tumor and normal cell lines all five tumor samples had multiple amplifications and deletions (median: 13), whereas CNVs were absent in the matched controls. Of 15 fresh frozen and 2 FFPE breast tumors samples, 14 fresh and both FFPEs showed full or partial CNVs in at least one and up to 15 regions (median: 7); all had a CNV of either 1q or 17p, the two most common breast cancer CNVs represented on this panel. Evidence of tumor heterogeneity was also observed. Although not investigated here, the very low input requirements will allow this assay to analyze tumor heterogeneity. A similar assay targeting all chromosome arms would result in a sequencing cost of approximately $5 per sample. Thus, this method offers a powerful, efficient, and scalable approach for investigating large numbers of fresh frozen or FFPE samples.

A new fluorogenic cyanine dye was synthesized and found to have low fluorescence quantum yield in fluid solution and in the presence of double-stranded DNA but 80-fold enhanced fluorescence in viscous glycerol solution. An RNA aptamer selected for binding to the new dye exhibits K-d = 87 nM and 60-fold fluorescence enhancement. The dye-aptamer pair is a fluoromodule that can be incorporated into fluorescent sensors and labels.