Florian Scherer

Integrated digital error suppression for improved detection of circulating tumor DNA

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by about threefold, and synergize when combined to yield ∼15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to non-small cell lung cancer (NSCLC) patients, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and >99.99% specificity at the variant level, and with 90% sensitivity and 96% specificity at the patient level. In addition, our approach allowed monitoring of NSCLC ctDNA down to 4 in 105 cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings.

Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients

Circulating tumour DNA (ctDNA) analysis facilitates studies of tumour heterogeneity. Here we employ CAPP-Seq ctDNA analysis to study resistance mechanisms in 43 non-small cell lung cancer (NSCLC) patients treated with the third-generation epidermal growth factor receptor (EGFR) inhibitor rociletinib. We observe multiple resistance mechanisms in 46% of patients after treatment with first-line inhibitors, indicating frequent intra-patient heterogeneity. Rociletinib resistance recurrently involves MET, EGFR, PIK3CA, ERRB2, KRAS and RB1. We describe a novel EGFR L798I mutation and find that EGFR C797S, which arises in ∼33% of patients after osimertinib treatment, occurs in <3% after rociletinib. Increased MET copy number is the most frequent rociletinib resistance mechanism in this cohort and patients with multiple pre-existing mechanisms (T790M and MET) experience inferior responses. Similarly, rociletinib-resistant xenografts develop MET amplification that can be overcome with the MET inhibitor crizotinib. These results underscore the importance of tumour heterogeneity in NSCLC and the utility of ctDNA-based resistance mechanism assessment.

Noninvasive monitoring of diffuse large B-cell lymphoma by immunoglobulin high-throughput sequencing

Recent studies have shown limited utility of routine surveillance imaging for diffuse large B-cell lymphoma (DLBCL) patients achieving remission. Detection of molecular disease by immunoglobulin high-throughput sequencing (Ig-HTS) from peripheral blood provides an alternate strategy for surveillance. We prospectively evaluated the utility of Ig-HTS within 311 blood and 105 tumor samples from 75 patients with DLBCL, comparing Ig-HTS from the cellular (circulating leukocytes) and acellular (plasma cell-free DNA) compartments of peripheral blood to clinical outcomes and (18)fluoro-deoxyglucose positron emission tomography combined with computed tomography (PET/CT; n = 173). Clonotypic immunoglobulin rearrangements were detected in 83% of patients with adequate tumor samples to enable subsequent monitoring in peripheral blood. Molecular disease measured from plasma, compared with circulating leukocytes, was more abundant and better correlated with radiographic disease burden. Before treatment, molecular disease was detected in the plasma of 82% of patients compared with 71% in circulating cells (P = .68). However, molecular disease was detected significantly more frequently in the plasma at time of relapse (100% vs 30%; P = .001). Detection of molecular disease in the plasma often preceded PET/CT detection of relapse in patients initially achieving remission. During surveillance time points before relapse, plasma Ig-HTS demonstrated improved specificity (100% vs 56%, P < .0001) and similar sensitivity (31% vs 55%, P = .4) compared with PET/CT. Given its high specificity, Ig-HTS from plasma has potential clinical utility for surveillance after complete remission.

Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA

Circulating tumor DNA reveals patterns of clonal evolution and allows classification of tumor subtypes in lymphoma. The telltale DNA in lymphoma Diffuse large B cell lymphoma is a relatively common type of tumor that can exhibit a wide range of behaviors, from indolent and curable cancers to ones that are very aggressive and difficult to treat. By analyzing DNA in tumor samples and blood of lymphoma patients, Scherer et al. have shown that specific genetic characteristics can determine each tumor’s cell of origin and identify tumors that are going to transform into more aggressive subtypes and may require more intensive treatment. The authors also demonstrated that circulating tumor DNA in the patients’ blood is suitable for this analysis, allowing for periodic monitoring of each patient without repeated invasive biopsies. Patients with diffuse large B cell lymphoma (DLBCL) exhibit marked diversity in tumor behavior and outcomes, yet the identification of poor-risk groups remains challenging. In addition, the biology underlying these differences is incompletely understood. We hypothesized that characterization of mutational heterogeneity and genomic evolution using circulating tumor DNA (ctDNA) profiling could reveal molecular determinants of adverse outcomes. To address this hypothesis, we applied cancer personalized profiling by deep sequencing (CAPP-Seq) analysis to tumor biopsies and cell-free DNA samples from 92 lymphoma patients and 24 healthy subjects. At diagnosis, the amount of ctDNA was found to strongly correlate with clinical indices and was independently predictive of patient outcomes. We demonstrate that ctDNA genotyping can classify transcriptionally defined tumor subtypes, including DLBCL cell of origin, directly from plasma. By simultaneously tracking multiple somatic mutations in ctDNA, our approach outperformed immunoglobulin sequencing and radiographic imaging for the detection of minimal residual disease and facilitated noninvasive identification of emergent resistance mutations to targeted therapies. In addition, we identified distinct patterns of clonal evolution distinguishing indolent follicular lymphomas from those that transformed into DLBCL, allowing for potential noninvasive prediction of histological transformation. Collectively, our results demonstrate that ctDNA analysis reveals biological factors that underlie lymphoma clinical outcomes and could facilitate individualized therapy.

Early detection of molecular residual disease in localized lung cancer by circulating tumor DNA profiling

Identifying molecular residual disease (MRD) after treatment of localized lung cancer could facilitate early intervention and personalization of adjuvant therapies. Here, we apply cancer personalized profiling by deep sequencing (CAPP-seq) circulating tumor DNA (ctDNA) analysis to 255 samples from 40 patients treated with curative intent for stage I-III lung cancer and 54 healthy adults. In 94% of evaluable patients experiencing recurrence, ctDNA was detectable in the first posttreatment blood sample, indicating reliable identification of MRD. Posttreatment ctDNA detection preceded radiographic progression in 72% of patients by a median of 5.2 months, and 53% of patients harbored ctDNA mutation profiles associated with favorable responses to tyrosine kinase inhibitors or immune checkpoint blockade. Collectively, these results indicate that ctDNA MRD in patients with lung cancer can be accurately detected using CAPP-seq and may allow personalized adjuvant treatment while disease burden is lowest.Significance: This study shows that ctDNA analysis can robustly identify posttreatment MRD in patients with localized lung cancer, identifying residual/recurrent disease earlier than standard-of-care radiologic imaging, and thus could facilitate personalized adjuvant treatment at early time points when disease burden is lowest. Cancer Discov; 7(12); 1394-403. ©2017 AACR.See related commentary by Comino-Mendez and Turner, p. 1368This article is highlighted in the In This Issue feature, p. 1355.

Comparative genomics reveals multistep pathogenesis of E2A-PBX1 acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer; however, its genetic diversity limits investigation into the molecular pathogenesis of disease and development of therapeutic strategies. Here, we engineered mice that conditionally express the E2A-PBX1 fusion oncogene, which results from chromosomal translocation t(1;19) and is present in 5% to 7% of pediatric ALL cases. The incidence of leukemia in these mice varied from 5% to 50%, dependent on the Cre-driving promoter (Cd19, Mb1, or Mx1) used to induce E2A-PBX1 expression. Two distinct but highly similar subtypes of B cell precursor ALLs that differed by their pre-B cell receptor (pre-BCR) status were induced and displayed maturation arrest at the pro-B/large pre-B II stages of differentiation, similar to human E2A-PBX1 ALL. Somatic activation of E2A-PBX1 in B cell progenitors enhanced self-renewal and led to acquisition of multiple secondary genomic aberrations, including prominent spontaneous loss of Pax5. In preleukemic mice, conditional Pax5 deletion cooperated with E2A-PBX1 to expand progenitor B cell subpopulations, increasing penetrance and shortening leukemia latency. Recurrent secondary activating mutations were detected in key signaling pathways, most notably JAK/STAT, that leukemia cells require for proliferation. These data support conditional E2A-PBX1 mice as a model of human ALL and suggest targeting pre-BCR signaling and JAK kinases as potential therapeutic strategies.

Organocatalytic removal of formaldehyde adducts from RNA and DNA bases

Formaldehyde is universally employed to fix tissue specimens, where it forms hemiaminal and aminal adducts with biomolecules, hindering the ability to retrieve molecular information. Common methods for removing these adducts involve extended heating, which can cause extensive degradation of nucleic acids, particularly RNA. Here we show that water-soluble bifunctional catalysts (anthranilates and phosphanilates) speed the reversal of formaldehyde adducts of mononucleotides over standard buffers. Studies with formaldehyde-treated RNA oligonucleotides show that the catalysts enhance adduct removal, restoring unmodified RNA at 37 °C even when extensively modified, and avoiding high temperatures that promote RNA degradation. Experiments with formalin-fixed, paraffin-embedded cell samples show that the catalysis is compatible with common RNA extraction protocols, with detectable RNA yields increased by 1.5–2.4 fold using a catalyst under optimized conditions, and by 7–25 fold compared to a commercial kit. Such catalytic strategies show promise for general use in reversing formaldehyde adducts in clinical specimens.

Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma

PURPOSE Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes. PATIENTS AND METHODS We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans. RESULTS Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival. CONCLUSION Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.

Corrigendum: Organocatalytic removal of formaldehyde adducts from RNA and DNA bases.

Nature Chemistry 7, 752–758 (2015); published online 3 August 2015; corrected after print 27 October 2015. In the original version of this Article a contributing author, Florian Scherer, was mistakenly omitted. Florian Scherer is in the Divisions of Oncology and of Hematology, Stanford School of Medicine, Stanford, California 94305, USA.

Noninvasive Cancer Classification Using Diverse Genomic Features in Circulating Tumor DNA

Circulating tumor DNA (ctDNA) has the potential to revolutionize cancer care, through detection of somatic lesions over time, as relevant for therapy selection, response monitoring, and early detection. Our group previously described cancer personalized profiling with deep sequencing (CAPP-Seq) [2], a ctDNA detection method targeting recurrent point mutations and structural variations within a given tumor. However, two unmet challenges for ctDNA are its utility for noninvasive histology classification and for copy number variation (CNV) at low ctDNA levels. Here, we tackle both challenges as related problems. We describe a simple CNV detection algorithm for ctDNA. To correct for systematic/biological noise, we map depth data into corresponding z-statistics in healthy subjects. Then, we estimate parameters of a multivariate Gaussian governing z-statistics of the contributing regions. Finally, we employ a polished signal to assign a score to each gene. CNVs are then called based on predetermined performance metrics. We benchmarked performance via synthetic and empirical CAPP-Seq data, achieving 95% sensitivity/specificity for ctDNA levels 3-5% in actionable CNVs involving ERBB2, MET, and EGFR. We also successfully detected CNVs for ctDNA level as low as 3% in patients with non-small cell lung cancer or diffuse large B-cell lymphoma (DLBCL). We separately describe a Bayesian tumor histology classifier using prior probabilities from existing knowledge regarding CNVs, single nucleotide variants, and gene fusions in public tumor sequencing data. Prior probabilities were constructed within an optimization framework using maximum entropy. When applied to noninvasive classification of DLBCL subtypes (i.e. germinal center B-cell like (GCB) and activated B-cell like (ABC) [1]) using pretreatment plasma, this method showed ~ 80% concordance with routine clinical classification (Hans Algorithm). We conclude that tumor subtype classification and CNV detection with ctDNA is feasible and robust using CAPP-Seq.