CloneRetriever: An Automated Algorithm to Identify Clonal B and T Cell Gene Rearrangements by Next-Generation Sequencing for the Diagnosis of Lymphoid Malignancies.

BACKGROUND: Clonal immunoglobulin and T-cell receptor rearrangements serve as tumor-specific markers that have become mainstays of the diagnosis and monitoring of lymphoid malignancy. Next-generation sequencing (NGS) techniques targeting these loci have been successfully applied to lymphoblastic leukemia and multiple myeloma for minimal residual disease detection. However, adoption of NGS for primary diagnosis remains limited. METHODS: We addressed the bioinformatics challenges associated with immune cell sequencing and clone detection by designing a novel web tool, CloneRetriever (CR), which uses machine-learning principles to generate clone classification schemes that are customizable, and can be applied to large datasets. CR has 2 applications-a "validation" mode to derive a clonality classifier, and a "live" mode to screen for clones by applying a validated and/or customized classifier. In this study, CR-generated multiple classifiers using 2 datasets comprising 106 annotated patient samples. A custom classifier was then applied to 36 unannotated samples. RESULTS: The optimal classifier for clonality required clonal dominance ≥4.5× above background, read representation ≥8% of all reads, and technical replicate agreement. Depending on the dataset and analysis step, the optimal algorithm yielded sensitivities of 81%-90%, specificities of 97%-100%, areas under the curve of 91%-94%, positive predictive values of 92-100%, and negative predictive values of 88%-98%. Customization of the algorithms yielded 95%-100% concordance with gold-standard clonality determination, including rescue of indeterminate samples. Application to a set of unknowns showed concordance rates of 83%-96%. CONCLUSIONS: CR is an out-of-the-box ready and user-friendly software designed to identify clonal rearrangements in large NGS datasets for the diagnosis of lymphoid malignancies.

Feasibility of Cell-Free DNA Collection and Clonal Immunoglobulin Sequencing in South African Patients With HIV-Associated Lymphoma.

PURPOSE: Diagnosis of AIDS lymphoma in low-resource settings, like South Africa, is often delayed, leaving patients with limited treatment options. In tuberculosis (TB) endemic regions, overlapping signs and symptoms often lead to diagnostic delays. Assessment of plasma cell-free DNA (cfDNA) by next-generation sequencing (NGS) may expedite the diagnosis of lymphoma but requires high-quality cfDNA. METHODS: People living with HIV with newly diagnosed aggressive B-cell lymphoma and those with newly diagnosed TB seeking care at Chris Hani Baragwanath Academic Hospital and its surrounding clinics, in Soweto, South Africa, were enrolled in this study. Each participant provided a whole blood specimen collected in cell-stabilizing tubes. Quantity and quality of plasma cfDNA were assessed. NGS of the immunoglobulin heavy chain was performed. RESULTS: Nine HIV+ patients with untreated lymphoma and eight HIV+ patients with TB, but without lymphoma, were enrolled. All cfDNA quantity and quality metrics were similar between the two groups, except that cfDNA accounted for a larger fraction of recovered plasma DNA in patients with lymphoma. The concentration of cfDNA in plasma also trended higher in patients with lymphoma. NGS of immunoglobulin heavy chain showed robust amplification of DNA, with large amplicons (> 250 bp) being more readily detected in patients with lymphoma. Clonal sequences were detected in five of nine patients with lymphoma, and none of the patients with TB. CONCLUSION: This proof-of-principle study demonstrates that whole blood collected for cfDNA in a low-resource setting is suitable for sophisticated sequencing analyses, including clonal immunoglobulin NGS. The detection of clonal sequences in more than half of patients with lymphoma shows promise as a diagnostic marker that may be explored in future studies.

CREBBP and STAT6 co-mutation and 16p13 and 1p36 loss define the t(14;18)-negative diffuse variant of follicular lymphoma.

The diffuse variant of follicular lymphoma (dFL) is a rare variant of FL lacking t(14;18) that was first described in 2009. In this study, we use a comprehensive approach to define unifying pathologic and genetic features through gold-standard pathologic review, FISH, SNP-microarray, and next-generation sequencing of 16 cases of dFL. We found unique morphologic features, including interstitial sclerosis, microfollicle formation, and rounded nuclear cytology, confirmed absence of t(14;18) and recurrent deletion of 1p36, and showed a novel association with deletion/CN-LOH of 16p13 (inclusive of CREBBP, CIITA, and SOCS1). Mutational profiling demonstrated near-uniform mutations in CREBBP and STAT6, with clonal dominance of CREBBP, among other mutations typical of germinal-center B-cell lymphomas. Frequent CREBBP and CIITA codeletion/mutation suggested a mechanism for immune evasion, while subclonal STAT6 activating mutations with concurrent SOCS1 loss suggested a mechanism of BCL-xL/BCL2L1 upregulation in the absence of BCL2 rearrangements. A review of the literature showed significant enrichment for 16p13 and 1p36 loss/CN-LOH, STAT6 mutation, and CREBBP and STAT6 comutation in dFL, as compared with conventional FL. With this comprehensive approach, our study demonstrates confirmatory and novel genetic associations that can aid in the diagnosis and subclassification of this rare type of lymphoma.

Circulating Tumor DNA as a Clinical Test in Resected Pancreatic Cancer.

PURPOSE: In research settings, circulating tumor DNA (ctDNA) shows promise as a tumor-specific biomarker for pancreatic ductal adenocarcinoma (PDAC). This study aims to perform analytical and clinical validation of a KRAS ctDNA assay in a Clinical Laboratory Improvement Amendments (CLIA) and College of American Pathology-certified clinical laboratory. EXPERIMENTAL DESIGN: Digital-droplet PCR was used to detect the major PDAC-associated somatic KRAS mutations (G12D, G12V, G12R, and Q61H) in liquid biopsies. For clinical validation, 290 preoperative and longitudinal postoperative plasma samples were collected from 59 patients with PDAC. The utility of ctDNA status to predict PDAC recurrence during follow-up was assessed. RESULTS: ctDNA was detected preoperatively in 29 (49%) patients and was an independent predictor of decreased recurrence-free survival (RFS) and overall survival (OS). Patients who had neoadjuvant chemotherapy were less likely to have preoperative ctDNA than were chemo-naïve patients (21% vs. 69%; P < 0.001). ctDNA levels dropped significantly after tumor resection. Persistence of ctDNA in the immediate postoperative period was associated with a high rate of recurrence and poor median RFS (5 months). ctDNA detected during follow-up predicted clinical recurrence [sensitivity 90% (95% confidence interval (CI), 74%-98%), specificity 88% (95% CI, 62%-98%)] with a median lead time of 84 days (interquartile range, 25-146). Detection of ctDNA during postpancreatectomy follow-up was associated with a median OS of 17 months, while median OS was not yet reached at 30 months for patients without ctDNA (P = 0.011). CONCLUSIONS: Measurement of KRAS ctDNA in a CLIA laboratory setting can be used to predict recurrence and survival in patients with PDAC.

Validation Strategy for Ultrasensitive Mutation Detection.

BACKGROUND: Ultrasensitive detection of low-abundance DNA point mutations is a challenging molecular biology problem, because nearly identical mutant and wild-type molecules exhibit crosstalk. Reliable ultrasensitive point mutation detection will facilitate early detection of cancer and therapeutic monitoring of cancer patients. OBJECTIVE: The objective of this study was to develop a method to correct errors in low-level cell line mixes. MATERIALS AND METHODS: We tested sample mixes with digital-droplet PCR (ddPCR) and next-generation sequencing. RESULTS: We introduced two corrections: baseline variant allele frequency (VAF) in the parental cell line was used to correct for copy number variation; and haplotype counting was used to correct errors in cell counting and pipetting. We found ddPCR to have better correlation for detecting low-level mutations without applying any correction (R2 = 0.80) and be more linear after introducing both corrections (R2 = 0.99). CONCLUSIONS: The VAF correction was found to be more significant than haplotype correction. It is imperative that various technologies be evaluated against each other and laboratories be provided with defined quality control samples for proficiency testing.