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Background: In the Phase III LUX-Lung 3/6 (LL3/LL6) trials in epidermal growth factor receptor ( EGFR ) mutation-positive lung adenocarcinoma patients, we evaluated feasibility of EGFR mutation detection using circulating cell-free DNA (cfDNA) and prognostic and predictive utility of cfDNA positivity (cfDNA+). Methods: Paired tumour and blood samples were prospectively collected from randomised patients. Mutations were detected using cfDNA from serum (LL3) or plasma (LL6) by a validated allele-specific quantitative real-time PCR kit. Results: EGFR mutation detection rates in cfDNA were 28.6% (serum) and 60.5% (plasma). Mutation detection in blood was associated with advanced disease characteristics, including higher performance score, number of metastatic sites and bone/liver metastases, and poorer prognosis. In patients with common EGFR mutations, afatinib improved progression-free survival vs chemotherapy in cfDNA+ (LL3: HR, 0.35; P =0.0009; LL6: HR, 0.25; P <0.0001) and cfDNA− (LL3: HR, 0.46; P <0.0001; LL6: HR, 0.12; P <0.0001) cohorts. A trend towards overall survival benefit with afatinib was observed in cfDNA+ patients. Conclusions: Plasma cfDNA is a promising alternative to biopsy for EGFR testing. Detectable mutation in blood was associated with more advanced disease and poorer prognosis. Afatinib improved outcomes in EGFR mutation-positive patients regardless of blood mutation status.

Cell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes. It is possible to call single-nucleotide variant (SNV) in cell-free DNA (cfDNA), but the accuracy of detection is often affected by low tumour cfDNA content. Here, the authors develop a method, cfSNV, and show that it can be used even for medium-coverage whole exome sequencing of cfDNA.

Background Circulating cell-free DNA (cfDNA) is emerging as a surrogate sample type for mutation analyses. To improve the clinical utility of cfDNA, we developed a sensitive peptide nucleic acid (PNA)-based method for analyzing EGFR and KRAS mutations in the plasma cfDNA of patients with advanced non-small cell lung cancer (NSCLC). Methods Baseline tissue and plasma samples were collected from treatment-naïve advanced NSCLC patients participated in a randomized phase II study, which was registered with ClinicalTrials.gov at Feb. 2009 (NCT01003964). EGFR and KRAS mutations in the plasma cfDNA were analyzed retrospectively using a PNA clamping-assisted fluorescence melting curve analysis. The results were compared with those obtained from tissue analysis performed using the direct sequencing. Exploratory analyses were performed to determine survival predicted by the plasma and tissue mutation status. Results Mutation analyses in matched tissue and plasma samples were available for 194 patients for EGFR and 135 patients for KRAS . The mutation concordance rates were 82.0 % (95 % confidence interval [CI], 76.5–87.4) for EGFR and 85.9 % (95 % CI, 80.1–91.8) for KRAS . The plasma EGFR mutation test sensitivity and specificity were 66.7 % (95 % CI, 60.0–73.3) and 87.4 % (95 % CI, 82.7–92.1), respectively, and the plasma KRAS mutation test sensitivity and specificity were 50.0 % (95 % CI, 41.6–58.4) and 89.4 % (95 % CI, 84.2–94.6), respectively. The predictive value of the plasma EGFR and KRAS mutation status with respect to survival was comparable with that of the tissue mutation status. Conclusions These data suggest that plasma EGFR and KRAS mutations can be analyzed using PNA-based real-time PCR methods and used as an alternative to tumor genotyping for NSCLC patients when tumor tissue is not available.

Leber congenital amaurosis (LCA) is a heterogeneous, early‐onset inherited retinal dystrophy, which is associated with severe visual impairment. We aimed to determine the disease‐causing variants in Iranian LCA and evaluate the clinical implications. Clinically, a possible LCA disease was found through diagnostic imaging, such as fundus photography, autofluorescence and optical coherence tomography. All affected patients showed typical eye symptoms associated with LCA including narrow arterioles, blindness, pigmentary changes and nystagmus. Target exome sequencing was performed to analyse the proband DNA. A homozygous novel c. 2889delT  (p.P963 fs) mutation in the RPGRIP1 gene was identified, which was likely the deleterious and pathogenic mutation in the proband. Structurally, this mutation lost a retinitis pigmentosa GTPase regulator (RPGR)‐interacting domain at the C‐terminus which most likely impaired stability in the RPGRIP1 with the distribution of polarised proteins in the cilium connecting process. Sanger sequencing showed complete co‐segregation  in this pedigree. This study provides compelling evidence that the c. 2889delT  (p.P963 fs) mutation in the RPGRIP1 gene works as a pathogenic mutation that contributes to the progression of LCA.

Pre-surgical studies allow study of the relationship between mutations and response of oestrogen receptor-positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 controls). In poor responders (based on Ki67 change), we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores occur in ∼30% of tumours. In phase II, we combine targeted sequencing on another 28 treated patients with phase I. We find six genes frequently mutated: PIK3CA , TP53 , CDH1 , MLL3 , ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy. Aromatase inhibitors are used to treat oestrogen receptor positive breast cancers but the molecular basis for the response of patients is unclear. Here, the authors use samples from an aromatase inhibitor clinical trial and show that tumours from poor responders have more mutations than good responders and also more frequently harbour p53 mutations.

Changes in tumor DNA mutation status during chemotherapy can provide insights into tumor biology and drug resistance. The purpose of this study is to analyse the presence or absence of mutations in cancer-related genes using baseline breast tumor samples and those obtained after exposure to one cycle of chemotherapy to determine if any differences exist, and to correlate these differences with clinical and pathological features. Paired breast tumor core biopsies obtained pre- and post-first cycle doxorubicin (n = 18) or docetaxel (n = 22) in treatment-naïve breast cancer patients were analysed for 238 mutations in 19 cancer-related genes by the Sequenom Oncocarta assay. Median age of patients was 48 years (range 32-64); 55% had estrogen receptor-positive tumors, and 60% had tumor reduction ≥25% after cycle 1. Mutations were detected in 10/40 (25%) pre-treatment and 11/40 (28%) post-treatment samples. Four mutation pattern categories were identified based on tumor mutation status pre- → post-treatment: wildtype (WT)→WT, n = 24; mutant (MT)→MT, n = 5; MT→WT, n = 5; WT→MT, n = 6. Overall, the majority of tumors were WT at baseline (30/40, 75%), of which 6/30 (20%) acquired new mutations after chemotherapy. Pre-treatment mutations were predominantly in PIK3CA (8/10, 80%), while post-treatment mutations were distributed in PIK3CA, EGFR, PDGFRA, ABL1 and MET. All 6 WT→MT cases were treated with docetaxel. Higher mutant allele frequency in baseline MT tumors (n = 10; PIK3CA mutations n = 8) correlated with less tumor reduction after cycle 1 chemotherapy (R = -0.667, p = 0.035). No other associations were observed between mutation pattern category with treatment, clinicopathological features, and tumor response or survival. Tumor mutational profiles can change as quickly as after one cycle of chemotherapy in breast cancer. Understanding of these changes can provide insights on potential therapeutic options in residual resistant tumors. ClinicalTrials.gov NCT00212082.

An early genetic change in the pathway to colorectal cancer is a mutation in the adenomatous polyposis coli ( APC ) gene. On the basis of the premise that cells with mutant APC genes are shed into the feces, these investigators devised a powerful molecular method to find such genes in feces from patients with colorectal cancer. Whereas feces from normal subjects had no detectable mutant APC genes, stools from over half the patients with colorectal cancer or colonic polyps contained such genes. Stools from over half the patients with colorectal cancer or colonic polyps contained mutant APC genes. Several strategies for the early detection of colorectal tumors have been devised. Colonoscopy, sigmoidoscopy, and barium enemas are highly specific and sensitive tests for neoplasia, 1 – 4 but they are invasive and limited by the availability of experts in the procedures and patient compliance. 5 , 6 Testing for occult blood in the stool has been shown in some studies to reduce the incidence of and morbidity and mortality from colorectal cancer. 7 – 11 These fecal occult-blood tests are noninvasive and extremely useful but not sufficiently sensitive or specific for neoplasia. 12 – 15 Furthermore, some fecal occult-blood tests require patients to change their diet before . . .

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings.

Cytosine and adenine base editors (CBEs and ABEs) are promising new tools for achieving the precise genetic changes required for disease treatment and trait improvement. However, genome-wide and unbiased analyses of their off-target effects in vivo are still lacking. Our whole-genome sequencing analysis of rice plants treated with the third-generation base editor (BE3), high-fidelity BE3 (HF1-BE3), or ABE revealed that BE3 and HF1-BE3, but not ABE, induce substantial genome-wide off-target mutations, which are mostly the C→T type of single-nucleotide variants (SNVs) and appear to be enriched in genic regions. Notably, treatment of rice with BE3 or HF1-BE3 in the absence of single-guide RNA also results in the rise of genome-wide SNVs. Thus, the base-editing unit of BE3 or HF1-BE3 needs to be optimized in order to attain high fidelity.

Clinical tests that rely on next-generation sequencing to evaluate large numbers of cancer genes can be validated using pooled cell lines with known mutations. As more clinically relevant cancer genes are identified, comprehensive diagnostic approaches are needed to match patients to therapies, raising the challenge of optimization and analytical validation of assays that interrogate millions of bases of cancer genomes altered by multiple mechanisms. Here we describe a test based on massively parallel DNA sequencing to characterize base substitutions, short insertions and deletions (indels), copy number alterations and selected fusions across 287 cancer-related genes from routine formalin-fixed and paraffin-embedded (FFPE) clinical specimens. We implemented a practical validation strategy with reference samples of pooled cell lines that model key determinants of accuracy, including mutant allele frequency, indel length and amplitude of copy change. Test sensitivity achieved was 95–99% across alteration types, with high specificity (positive predictive value >99%). We confirmed accuracy using 249 FFPE cancer specimens characterized by established assays. Application of the test to 2,221 clinical cases revealed clinically actionable alterations in 76% of tumors, three times the number of actionable alterations detected by current diagnostic tests.