Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA.

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

Impact of Conditioning Intensity and Genomics on Relapse After Allogeneic Transplantation for Patients With Myelodysplastic Syndrome.

PURPOSE: Patients with myelodysplastic syndrome (MDS) are at risk of relapse after allogeneic hematopoietic cell transplantation. The utility of ultra-deep genomic testing to predict and the impact of conditioning intensity to prevent MDS relapse are unknown. METHODS: Targeted error-corrected DNA sequencing was performed on preconditioning blood samples from patients with MDS (n = 48) from the Blood and Marrow Transplant Clinical Trials Network 0901 phase III randomized clinical trial, which compared outcomes by allogeneic hematopoietic cell transplantation conditioning intensity in adult patients with < 5% marrow myeloblasts and no leukemic myeloblasts in blood on morphological analysis at the time of pretransplant assessment. Clinical end points (53-month median follow-up) included transplant-related mortality (TRM), relapse, relapse-free survival (RFS), and overall survival (OS). Of the 48 patients examined, 14 experienced TRM, 23 are relapse-free, and 11 relapsed, of which 7 died. RESULTS: Using a previously described set of 10 gene regions, 42% of patients (n = 20) had mutations detectable before random assignment to reduced intensity conditioning (RIC) or myeloablative conditioning (MAC). Testing positive was associated with increased rates of relapse (3-year relapse, 40% v 11%; P = .022) and decreased OS (3-year OS, 55% v 79%, P = .045). In those testing positive, relapse rates were higher (3-year relapse, 75% v 17%; P = .003) and RFS was lower (3-year RFS, 13% v 49%; P = .003) in RIC versus MAC arms. Testing additional genes, including those associated with MDS, did not improve prognostication. CONCLUSION: This study provides evidence that targeted DNA sequencing in patients with MDS before transplant can identify those with highest post-transplant relapse rates. In those testing positive, random assignment to MAC lowered but did not eliminate relapse risk.

Simultaneous Identification of Cell of Origin, Translocations, and Hotspot Mutations in Diffuse Large B-Cell Lymphoma Using a Single RNA-Sequencing Assay.

OBJECTIVES: Diffuse large B-cell lymphoma (DLBCL) is an aggressive non-Hodgkin lymphoma with a heterogenous genetic landscape that can require multiple assays to characterize. We reviewed a 1-step RNA-based assay to determine cell of origin (COO), detect translocations, and identify mutations and to assess the role of the assay in diagnosis. METHODS: Using a single custom Archer FusionPlex Lymphoma panel, we performed anchored multiplex polymerase chain reaction-based RNA sequencing on 41 cases of de novo DLBCL. Each case was subclassified by COO, and gene fusions and hotspot mutations were identified. The findings were then compared with COO classification by the Hans immunohistochemical algorithm and NanoString technology, cytogenetics, and fluorescence in situ hybridization results. RESULTS: Concordant COO classification by the FusionPlex panel and NanoString was observed in 35 of 41 cases (85.3%), with NanoString and Hans concordant in 33 of 41 cases (80.5%) and FusionPlex and Hans concordant in 33 of 41 cases (80.5%). The FusionPlex assay also detected 6 of 11 BCL6 translocations (4 cryptic), 2 of 3 BCL2 translocations, and 2 of 4 MYC translocations. Mutations were detected in lymphoma-related genes in 24 of 41 cases. CONCLUSION: This FusionPlex assay offers a single method for COO classification, mutation detection, and identification of important translocations in DLBCL. Although not replacing traditional testing, it could offer useful data when limited tissue is available.

Impact of Conditioning Intensity of Allogeneic Transplantation for Acute Myeloid Leukemia With Genomic Evidence of Residual Disease.

PURPOSE: Patients with acute myeloid leukemia (AML) in remission remain at risk for relapse even after allogeneic hematopoietic cell transplantation (alloHCT). AML measurable residual disease (MRD) status before alloHCT has been shown to be prognostic. Whether modulation of the intensity of the alloHCT conditioning regimen in patients with AML who test positive for MRD can prevent relapse and improve survival is unknown. METHODS: Ultra-deep, error-corrected sequencing for 13 commonly mutated genes in AML was performed on preconditioning blood from patients treated in a phase III clinical trial that randomly assigned adult patients with myeloid malignancy in morphologic complete remission to myeloablative conditioning (MAC) or reduced-intensity conditioning (RIC). RESULTS: No mutations were detected in 32% of MAC and 37% of RIC recipients; these groups had similar survival (3-year overall survival [OS], 56% v 63%; P = .96). In patients with a detectable mutation (next-generation sequencing [NGS] positive), relapse (3-year cumulative incidence, 19% v 67%; P < .001) and survival (3-year OS, 61% v 43%; P = .02) was significantly different between the MAC and RIC arms, respectively. In multivariable analysis for NGS-positive patients, adjusting for disease risk and donor group, RIC was significantly associated with increased relapse (hazard ratio [HR], 6.38; 95% CI, 3.37 to 12.10; P < .001), decreased relapse-free survival (HR, 2.94; 95% CI, 1.84 to 4.69; P < .001), and decreased OS (HR, 1.97; 95% CI, 1.17 to 3.30; P = .01) compared with MAC. Models of AML MRD also showed benefit for MAC over RIC for those who tested positive. CONCLUSION: This study provides evidence that MAC rather than RIC in patients with AML with genomic evidence of MRD before alloHCT can result in improved survival.

SEC31A-ALK Fusion Gene in Lung Adenocarcinoma.

Anaplastic lymphoma kinase (ALK) fusion is a common mechanism underlying pathogenesis of non-small cell lung carcinoma (NSCLC) where these rearrangements represent important diagnostic and therapeutic targets. In this study, we found a new ALK fusion gene, SEC31A-ALK, in lung carcinoma from a 53-year-old Korean man. The conjoined region in the fusion transcript was generated by the fusion of SEC31A exon 21 and ALK exon 20 by genomic rearrangement, which contributed to generation of an intact, in-frame open reading frame. SEC31A-ALK encodes a predicted fusion protein of 1,438 amino acids comprising the WD40 domain of SEC31A at the N-terminus and ALK kinase domain at the C-terminus. Fluorescence in situ hybridization studies suggested that SEC31A-ALK was generated by an unbalanced genomic rearrangement associated with loss of the 3'-end of SEC31A. This is the first report of SEC31A-ALK fusion transcript in clinical NSCLC, which could be a novel diagnostic and therapeutic target for patients with NSCLC.

The Power Decoder Simulator for the Evaluation of Pooled shRNA Screen Performance.

RNA interference screening using pooled, short hairpin RNA (shRNA) is a powerful, high-throughput tool for determining the biological relevance of genes for a phenotype. Assessing an shRNA pooled screen's performance is difficult in practice; one can estimate the performance only by using reproducibility as a proxy for power or by employing a large number of validated positive and negative controls. Here, we develop an open-source software tool, the Power Decoder simulator, for generating shRNA pooled screening experiments in silico that can be used to estimate a screen's statistical power. Using the negative binomial distribution, it models both the relative abundance of multiple shRNAs within a single screening replicate and the biological noise between replicates for each individual shRNA. We demonstrate that this simulator can successfully model the data from an actual laboratory experiment. We then use it to evaluate the effects of biological replicates and sequencing counts on the performance of a pooled screen, without the necessity of gathering additional data. The Power Decoder simulator is written in R and Python and is available for download under the GNU General Public License v3.0.

Optimized PCR conditions and increased shRNA fold representation improve reproducibility of pooled shRNA screens.

RNAi screening using pooled shRNA libraries is a valuable tool for identifying genetic regulators of biological processes. However, for a successful pooled shRNA screen, it is imperative to thoroughly optimize experimental conditions to obtain reproducible data. Here we performed viability screens with a library of ∼10,000 shRNAs at two different fold representations (100- and 500-fold at transduction) and report the reproducibility of shRNA abundance changes between screening replicates determined by microarray and next generation sequencing analyses. We show that the technical reproducibility between PCR replicates from a pooled screen can be drastically improved by ensuring that PCR amplification steps are kept within the exponential phase and by using an amount of genomic DNA input in the reaction that maintains the average template copies per shRNA used during library transduction. Using these optimized PCR conditions, we then show that higher reproducibility of biological replicates is obtained by both microarray and next generation sequencing when screening with higher average shRNA fold representation. shRNAs that change abundance reproducibly in biological replicates (primary hits) are identified from screens performed with both 100- and 500-fold shRNA representation, however a higher percentage of primary hit overlap between screening replicates is obtained from 500-fold shRNA representation screens. While strong hits with larger changes in relative abundance were generally identified in both screens, hits with smaller changes were identified only in the screens performed with the higher shRNA fold representation at transduction.

A Dynamic Programming Algorithm for Finding the Optimal Segmentation of an RNA Sequence in Secondary Structure Predictions.

In this paper, we present a dynamic programming algorithm that runs in polynomial time and allows us to achieve the optimal, non-overlapping segmentation of a long RNA sequence into segments (chunks). The secondary structure of each chunk is predicted independently, then combined with the structures predicted for the other chunks, to generate a complete secondary structure prediction that is thus a combination of local energy minima. The proposed approach not only is more efficient and accurate than other traditionally used methods that are based on global energy minimizations, but it also allows scientists to overcome computing and storage constraints when trying to predict the secondary structure of long RNA sequences.

PseudoBase++: an extension of PseudoBase for easy searching, formatting and visualization of pseudoknots.

Pseudoknots have been recognized to be an important type of RNA secondary structures responsible for many biological functions. PseudoBase, a widely used database of pseudoknot secondary structures developed at Leiden University, contains over 250 records of pseudoknots obtained in the past 25 years through crystallography, NMR, mutational experiments and sequence comparisons. To promptly address the growing analysis requests of the researchers on RNA structures and bring together information from multiple sources across the Internet to a single platform, we designed and implemented PseudoBase++, an extension of PseudoBase for easy searching, formatting and visualization of pseudoknots. PseudoBase++ (http://pseudobaseplusplus.utep.edu) maps the PseudoBase dataset into a searchable relational database including additional functionalities such as pseudoknot type. PseudoBase++ links each pseudoknot in PseudoBase to the GenBank record of the corresponding nucleotide sequence and allows scientists to automatically visualize RNA secondary structures with PseudoViewer. It also includes the capabilities of fine-grained reference searching and collecting new pseudoknot information.

RNAVLab: A virtual laboratory for studying RNA secondary structures based on grid computing technology.

As ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation, their secondary structures have been the focus of many recent studies. Despite the computing power of supercomputers, computationally predicting secondary structures with thermodynamic methods is still not feasible when the RNA molecules have long nucleotide sequences and include complex motifs such as pseudoknots. This paper presents RNAVLab (RNA Virtual Laboratory), a virtual laboratory for studying RNA secondary structures including pseudoknots that allows scientists to address this challenge. Two important case studies show the versatility and functionalities of RNAVLab. The first study quantifies its capability to rebuild longer secondary structures from motifs found in systematically sampled nucleotide segments. The extensive sampling and predictions are made feasible in a short turnaround time because of the grid technology used. The second study shows how RNAVLab allows scientists to study the viral RNA genome replication mechanisms used by members of the virus family Nodaviridae.