Abstract Accurate deconvolution of cell states from bulk tumor RNA-seq is hindered by heterogeneous malignant cells specifically in cancer applications. We present Statescope, a Bayesian framework that incorporates DNA-derived malignant cell purity to overcome this heterogeneity and explicitly models inter-sample variation to accurately identify cell states. Comprehensive benchmarking shows Statescope outperforms existing methods in both cell fraction and state estimation, and is unique in its ability to identify states entirely absent from single-cell references. In real-data applications, Statescope successfully recapitulates established cell states, including multiple states in neutrophils, a cell type often missed by single-cell methods in lung cancer. Critically, in the POPLAR/OAK clinical trials, Statescope identifies a combinatorial signature of effector CD8 + T cells and conventional dendritic cell states that together predict a striking survival benefit from immunotherapy. Collectively, Statescope transforms deconvolution into a versatile discovery platform, enabling deeper biological and clinical insights from widely available bulk multi-omics data.

This case report describes a rare case of bi-phenotypic gastric cancer with two distinct, but clonally related, histological components. The first component, associated with Epstein-Barr virus (EBV) infection, exhibited the morphological features of gastric carcinoma with lymphoid stroma, suggesting that EBV, as an effective immunogenic factor, may trigger a prominent immune response within the tumour microenvironment. The second component, which was EBV-negative, displayed tubular/papillary morphology and features of increased biological aggressiveness, such as high-grade areas and lymphatic invasion. Immunohistochemical and molecular studies confirmed that, despite the differing morphologies and immunophenotypes, both components were clonally related, with the EBV-negative area showing more complex DNA aberrations, reminiscent of chromosomally instable (CIN) lesions. This case describes clonally related EBV-positive and -negative components within a single gastric cancer, contributing to a better understanding of EBV role in tumour heterogeneity and progression and highlights the impact of EBV loss on tumour behaviour.

Introduction:The incidence of patients presenting with multiple cancers (MCs) and pulmonary involvement is increasing. Although next-generation sequencing mutation panels can discern metastases (clonal) from separate primary cancers (nonclonal), it does not warrant a reliable diagnosis for all patients despite significant therapeutic implications. We evaluated the added value of genome-wide copy number aberrations (CNAs) for clonality diagnosis. Methods:Two cohorts were assembled: 41 clonal and 41 nonclonal pairs from the TRACERx cohort and 21 MC pairs that had sufficient DNA for whole-exome sequencing (WES) from 120 patients diagnosed using CNA analysis in our routine pathology practice between 2016 and 2022. Clonality was determined by comparing tumor pairs using (1) WES mutations as a definitive standard, (2) a conventional mutation panel with an adapted 2024 International Association for the Study of Lung Cancer algorithm, and (3) CNAs with log-likelihood ratio and Pearson correlation metrics. Results:All tumor pairs classified as definite "clonal" or "nonclonal" by mutation analysis (TRACERx: 35 of 82 [43%], MC cohort: 6 of 21 [29%]) were in concordance with WES and CNAs. Of the tumor pairs classified as "probable nonclonal" or "inconclusive" by mutation analysis (TRACERx: 47 of 82 [57%], MC cohort: 15 of 21 [71%]), most could be correctly reclassified by CNAs (TRACERx: 46 of 47 [98%], MC cohort: 15 of 16 [94%]). For each cohort, one tumor pair remained inconclusive. Furthermore, we present a CNA clonality workflow for implementation in molecular diagnostics. Conclusion:Genome-wide CNA analysis provides complementary information to resolve clonality of MCs with ambiguous mutational clonality status, enhancing clinical decision-making.

The evolutionary processes that drive malignant progression of IDH-mutant astrocytomas remain unclear. Here, we performed multiomics on matched initial and recurrent tumor samples from a cohort of 105 patients and overlaid the data with detailed clinical annotation. We identified overlapping features associated with malignant progression that are derived from three molecular mechanisms: cell cycling, tumor cell (de)differentiation and remodeling of the extracellular matrix. Together, they provide a rationale of the underlying biology of tumor malignancy. DNA methylation levels decreased over time, predominantly in tumors with malignant transformation, and co-occurred with poor prognostic genetic events. We identified a DNA methylation-based signature strongly associated with survival, which allows objective, molecular-based grading of IDH-mutant astrocytomas to aid clinical decision making. Our findings were validated on large, independent cohorts of IDH-mutant astrocytoma samples. Lastly, in this retrospective study, we found little effect of radiotherapy or chemotherapy on the molecular features associated with malignant progression. Vallentgoed et al. integrate clinical and multiomic data from persons with matched initial and recurrent IDH-mutant astrocytomas to identify progression-associated mechanisms and report a DNA methylation-based signature associated with survival.

Background: Shallow whole genome sequencing (Shallow-seq) is used to determine the copy number aberrations (CNA) in tissue samples and circulating tumor DNA. However, costs of NGS and challenges of small biopsies ask for an alternative to the untargeted NGS approaches. The mFAST-SeqS approach, relying on LINE -1 repeat amplification, showed a good correlation with Shallow-seq to detect CNA in blood samples. In the present study, we evaluated whether mFAST-SeqS is suitable to assess CNA in small formalin-fixed paraffin -embedded (FFPE) tissue specimens, using vulva and anal HPV-related lesions. Methods: Seventy-two FFPE samples, including 36 control samples (19 vulva;17 anal) for threshold setting and 36 samples (24 vulva; 12 anal) for clinical evaluation, were analyzed by mFAST-SeqS. CNA in vulva and anal lesions were determined by calculating genome-wide and chromosome arm -specific z -scores in comparison with the respective control samples. Sixteen samples were also analyzed with the conventional Shallow-seq approach. Results: Genome-wide z -scores increased with the severity of disease, with highest values being found in cancers. In vulva samples median and inter quartile ranges [IQR] were 1[0 -2] in normal tissues ( n = 4), 3[1 -7] in premalignant lesions ( n = 9) and 21[13 -48] in cancers ( n = 10). In anal samples, median [IQR] were 0[0 -1] in normal tissues ( n = 4), 14[6 -38] in premalignant lesions (n = 4) and 18[9 -31] in cancers (n = 4). At threshold 4, all controls were CNA negative, while 8/13 premalignant lesions and 12/14 cancers were CNA positive. CNA captured by mFAST-SeqS were mostly also found by Shallow-seq. Conclusion: mFAST-SeqS is easy to perform, requires less DNA and less sequencing reads reducing costs, thereby providing a good alternative for Shallow-seq to determine CNA in small FFPE samples.

Deconvolution of bulk RNA profiles can identify hidden cell fractions and functional states in the tumor microenvironment. The malignant cells however, are commonly the most abundant cell type and impair deconvolution by profound interpatient heterogeneity. We developed a malignant cell fraction-informed RNA deconvolution method by Bayesian integration of DNA-derived malignant fraction estimates, OncoBLADE. We evaluated OncoBLADE experimentally using bulk RNA profiles with 19 CyTOF determined cell fractions from blood of 46 individuals, and in silico using 180,177 single-cell RNA profiles from 73 lung tumors. Using malignant cell fractions, OncoBLADE achieved improved accuracy in cell fraction and cell type-specific RNA profile estimation. We tested OncoBLADE on real bulk profiles of 50 adeno- and 50 squamous lung cancer samples, revealing hidden RNA profiles of malignant cells and fibroblasts that distinguished two histological subtypes. In conclusion, multimodal deconvolution utilizing bulk DNA and RNA data accurately unveils hidden RNA profiles within the tumor microenvironment.

Supplementary Data from Trifluorothymidine Resistance Is Associated with Decreased Thymidine Kinase and Equilibrative Nucleoside Transporter Expression or Increased Secretory Phospholipase A2

Supplementary Table S1 from Genomic Profiles Associated with Early Micrometastasis in Lung Cancer: Relevance of 4q Deletion

Somatic copy number alterations can be detected in cell-free DNA (cfDNA) by shallow whole genome sequencing (sWGS). PCR is typically included in library preparations, but a PCR-free method could serve as a high-throughput alternative. To evaluate a PCR-free method for research and diagnostics, archival peripheral blood or bone marrow plasma samples, collected in EDTA- or lithium-heparin-containing tubes, were collected from patients with non-small-cell lung cancer (n = 10 longitudinal samples; 4 patients), B-cell lymphoma (n = 31), and acute myeloid leukemia (n = 15), or from healthy donors (n = 14). sWGS was performed on PCR-free and PCR library preparations, and the mapping quality, percentage of unique reads, genome coverage, fragment lengths, and copy number profiles were compared. The percentage of unique reads was significantly higher for PCR-free method compared with PCR method, independent of the type of collection tube: EDTA PCR-free method, 96.4% (n = 35); EDTA PCR method, 85.1% (n = 32); heparin PCR-free method, 94.5% (n = 25); and heparin PCR method, 89.4% (n = 10). All other evaluated metrics were highly comparable for PCR-free and PCR library preparations. These results demonstrate the feasibility of somatic copy number alteration detection by PCR-free sWGS using cfDNA from plasma collected in EDTA- or lithium-heparin-containing tubes and pave the way for an automated cfDNA analysis workflow for samples from cancer patients. (J Mol Diagn 2021, 23: 1553-1563; https://doi.org/10.1016/j.jmoldx.2021.08.008)

Large-scale chromosomal deletions are a prevalent and defining feature of cancer. A high degree of tumor-type and subtype specific recurrencies suggest a selective oncogenic advantage. However, due to their large size it has been difficult to pinpoint the oncogenic drivers that confer this advantage. Suitable functional genomics approaches to study the oncogenic driving capacity of large-scale deletions are limited. Here, we present an effective technique to engineer large-scale deletions by CRISPR-Cas9 and create isogenic cell line models. We simultaneously induce double-strand breaks (DSBs) at two ends of a chromosomal arm and select the cells that have lost the intermittent region. Using this technique, we induced large-scale deletions on chromosome 11q (65 Mb) and chromosome 6q (53 Mb) in neuroblastoma cell lines. A high frequency of successful deletions (up to 30% of selected clones) and increased colony forming capacity in the 11q deleted lines suggest an oncogenic advantage of these deletions. Such isogenic models enable further research on the role of large-scale deletions in tumor development and growth, and their possible therapeutic potential.

Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy (CRS-HIPEC) may be curative for colorectal cancer patients with peritoneal metastases (PMs) but it has a high rate of morbidity. Accurate preoperative patient selection is therefore imperative, but is constrained by the limitations of current imaging techniques. In this pilot study, we explored the feasibility of circulating tumor (ct) DNA analysis to select patients for CRS-HIPEC. Thirty patients eligible for CRS-HIPEC provided blood samples preoperatively and during follow-up if the procedure was completed. Targeted Next-Generation Sequencing (NGS) of DNA from PMs was used to identify bespoke mutations that were subsequently tested in corresponding plasma cell-free (cf) DNA samples using droplet digital (dd) PCR. CtDNA was detected preoperatively in cfDNA samples from 33% of patients and was associated with a reduced disease-free survival (DFS) after CRS-HIPEC (median 6.0 months vs median not reached, p = 0.016). This association could indicate the presence of undiagnosed systemic metastases or an increased metastatic potential of the tumors. We demonstrate the feasibility of ctDNA to serve as a preoperative marker of recurrence in patients with PMs of colorectal cancer using a highly sensitive technique. A more appropriate treatment for patients with preoperative ctDNA detection may be systemic chemotherapy in addition to, or instead of, CRS-HIPEC.

Objectives: The majority of patients with locally advanced larynx or hypopharynx squamous cell carcinoma are treated with organ-preserving chemoradiotherapy (CRT). Clinical outcome following CRT varies greatly. We hypothesized that tumor microRNA (miRNA) expression is predictive for outcome following CRT. Methods: Next-generation sequencing (NGS) miRNA profiling was performed on 37 formalin-fixed paraffin-embedded (FFPE) tumor samples. Patients with a recurrence-free survival (RFS) of less than 2 years and patients with late/no recurrence within 2 years were compared by differential expression analysis. Tumor-specific miRNAs were selected based on normal mucosa miRNA expression data from The Cancer Genome Atlas database. A model was constructed to predict outcome using group-regularized penalized logistic ridge regression. Candidate miRNAs were validated by RT-qPCR in the initial sample set as well as in 46 additional samples. Results: Thirteen miRNAs were differentially expressed (p < 0.05, FDR < 0.1) according to outcome group. Initial class prediction in the NGS cohort (n = 37) resulted in a model combining five miRNAs and disease stage, able to predict CRT outcome with an area under the curve (AUC) of 0.82. In the RT-qPCR cohort (n = 83), 25 patients (30%) experienced early recurrence (median RFS 8 months; median follow-up 42 months). Class prediction resulted in a model combining let-7i-5p, miR-192-5p and disease stage, able to discriminate patients with good versus poor clinical outcome (AUC:0.80). Conclusion: The combined miRNA expression and disease stage prediction model for CRT outcome is superior to using either factor alone. This study indicates NGS miRNA profiling using FFPE specimens is feasible, resulting in clinically relevant biomarkers.

[This corrects the article DOI: 10.1371/journal.pone.0223827.].

BackgroundFor patients with locally advanced larynx and hypopharynx cancer, organ preservation chemoradiotherapy (CRT) protocols are frequently applied. However, some tumors are resistant to CRT or will recur within a short time frame. For these patients upfront surgical resection may result in an improved cure rate. Currently, there are no molecular markers that can predict CRT response. In this study, tumor microRNA (miRNA) profiling was performed to predict clinical outcome in patients with locally advanced larynx or hypopharynx cancer treated with CRT.MethodsFirst, matched fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tumor biopsies from 12 patients were profiled by Next Generation Sequencing (NGS) to ensure valid miRNA results from FFPE. Next, miRNA profiles of FFPE tumor biopsies from 37 patients with larynx or hypopharynx cancer, treated with primary CRT, were determined. Clinicopathological data, including response to CRT, tumor stage and nodal stage, was collected of all patients. Differential expression analysis was performed to compare patients with poor clinical outcome, i.e residual tumor after treatment or progression free survival (PFS) < 2 years versus patients with good clinical outcome, i.e. complete response and PFS > 2 years. The median follow up of this cohort was 60 months (range 6 - 118). The Cancer Genome Atlas (TCGA) head and neck miRNA expression data of larynx and hypopharynx tumors and normal squamous cell tissues were used to select tumor specific miRNAs. By group-regularized penalized logistic ridge regression analysis, a model to predict clinical outcome was generated using tumor specific miRNAs combined with clinical covariates.ResultsIn total, 324 novel candidate and 2,262 mature miRNAs were detected. A comparative analysis of miRNA profiles generated using matched FF and FFPE tumor biopsies showed a high correlation (mean r2=0.75). Using only FFPE samples, 13 miRNAs were significantly differentially expressed between patients with good versus poor clinical outcome (p<0.05, FDR<0.1). Class prediction resulted in a model of three miRNAs combined with AJCC stage, able to predict recurrence with an area under the curve of 0.83. Further validation of the model is ongoing in an additional cohort of patients with larynx or hypopharynx cancer treated with CRT.ConclusionNGS miRNA profiling using FFPE tumor biopsies from patients with head and neck cancer is technically feasible, resulting in high quality miRNA expression data comparable to fresh frozen tissue. Based on miRNA expression profiling, candidate miRNAs were identified predictive for clinical outcome following treatment with CRT. A validation study is ongoing.Citation Format: Dennis Poel, Francois Rustenburg, Daoud Sie, Hendrik F. van Essen, Paul P. Eijk, Elisabeth Bloemena, Teresita E. Benites, Bauke Ylstra, Brakenhoff H. Ruud, René C. Leemans, Tineke E. Buffart, Henk M. Verheul, Jens Voortman. MicroRNA expression profiling predicts clinical outcome in patients with locally advanced larynx and hypopharynx cancer treated with chemoradiotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1801.

BackgroundHigh resolution genome-wide copy number analysis, routinely used in clinical diagnosis for several years, retrieves new and extremely rare copy number variations (CNVs) that provide novel candidate genes contributing to disease etiology. The aim of this work was to identify novel genetic causes of neurodevelopmental disease, inferred from CNVs detected by array comparative hybridization (aCGH), in a cohort of 325 Portuguese patients with intellectual disability (ID).ResultsWe have detected CNVs in 30.1% of the patients, of which 5.2% corresponded to novel likely pathogenic CNVs. For these 11 rare CNVs (which encompass novel ID candidate genes), we identified those most likely to be relevant, and established genotype-phenotype correlations based on detailed clinical assessment. In the case of duplications, we performed expression analysis to assess the impact of the rearrangement. Interestingly, these novel candidate genes belong to known ID-related pathways. Within the 8% of patients with CNVs in known pathogenic loci, the majority had a clinical presentation fitting the phenotype(s) described in the literature, with a few interesting exceptions that are discussed.ConclusionsIdentification of such rare CNVs (some of which reported for the first time in ID patients/families) contributes to our understanding of the etiology of ID and for the ever-improving diagnosis of this group of patients.

Background First line chemotherapy is effective in 75 to 80% of patients with metastatic colorectal cancer (mCRC). We studied whether microRNA (miR) expression profiles can predict treatment outcome for first line fluoropyrimidine containing systemic therapy in patients with mCRC. Methods MiR expression levels were determined by next generation sequencing from snap frozen tumor samples of 88 patients with mCRC. Predictive miRs were selected with penalized logistic regression and posterior forward selection. The prediction co-efficients of the miRs were re-estimated and validated by real-time quantitative PCR in an independent cohort of 81 patients with mCRC. Results Expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miR signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with stable disease (SD) from 0.79 to 0.90. The increase for predicting treatment response versus progressive disease (PD) and for patients with SD versus those with PD was not significant. in the validation cohort. MiR-17-5p, miR-20a-5p and miR-92a-3p were significantly upregulated in patients with treatment response in both the training and validation cohorts. Conclusion A six miR expression signature was identified that predicted treatment response to fluoropyrimidine containing first line systemic treatment in patients with mCRC when combined with four clinicopathological factors. Independent validation demonstrated added predictive value of this miR-signature for predicting treatment response versus SD. However, added predicted value for separating patients with PD could not be validated. The clinical relevance of the identified miRs for predicting treatment response has to be further explored.

Purpose Patients with metastatic colorectal cancer (mCRC) have limited benefit from the addition of bevacizumab to standard chemotherapy. However, a subset probably benefits substantially, highlighting an unmet clinical need for a biomarker of response to bevacizumab. Previously, we demonstrated that losses of chromosomes 5q34, 17q12, and 18q11.2-q12.1 had a significant correlation with progression-free survival (PFS) in patients with mCRC treated with bevacizumab in the CAIRO2 clinical trial but not in patients who did not receive bevacizumab in the CAIRO trial. This study was designed to validate these findings. Materials and Methods Primary mCRC samples were analyzed from two cohorts of patients who received bevacizumab as first-line treatment; 96 samples from the European multicenter study Angiopredict (APD) and 81 samples from the Italian multicenter study, MOMA. A third cohort of 90 samples from patients with mCRC who did not receive bevacizumab was analyzed. Copy number aberrations of tumor biopsy specimens were measured by shallow whole-genome sequencing and were correlated with PFS, overall survival (OS), and response. Results Loss of chromosome 18q11.2-q12.1 was associated with prolonged PFS most significantly in both the cohorts that received bevacizumab (APD: hazard ratio, 0.54; P = .01; PFS difference, 65 days; MOMA: hazard ratio, 0.55; P = .019; PFS difference, 49 days). A similar association was found for OS and overall response rate in these two cohorts, which became significant when combined with the CAIRO2 cohort. Median PFS in the cohort of patients with mCRC who did not receive bevacizumab and in the CAIRO cohort was similar to that of the APD, MOMA, and CAIRO2 patients without an 18q11.2-q12.1 loss. Conclusion We conclude that the loss of chromosome 18q11.2-q12.1 is consistently predictive for prolonged PFS in patients receiving bevacizumab. The predictive value of this loss is substantiated by a significant gain in OS and overall response rate.

Abstract Background and aim: Patients with advanced colorectal cancer (mCRC) are commonly treated with systemic treatment consisting of fluoropyrimidine-based regimens being ineffective in 20-25% of the patients. Currently, selection criteria for patients to predict who will respond to this treatment is lacking. The aim of this study is to identify which patients will respond to first line fluoropyrimidine-based treatment based using microRNA (miR) expression profiles in order to avoid ineffective treatment. Material and methods: Total RNA was isolated from 88 fresh frozen colorectal cancer tissue samples consisting of ≥ 70% tumor cells, collected from patients with mCRC. MiR expression profiles were generated by next generation sequencing using the Illumina High Seq 2000 platform. Of all patients clinical and pathological data, including treatment response based on RECIST criteria, were collected. Class prediction and miR selection were performed using the GRidge package in R. Penalized selection and internal cross validation were used to select miRs predictive for treatment response. RESULTS: Next generation sequencing resulted in a mean of 10.087.107 (range 6.114.932 to 74.313.067) reads per sample corresponding to 2567 unique mature miR sequences, including 457 novel candidate and 2110 known miRs sequences (miRbase version 19). Penalized regression analysis on tumor specific miRs identified an expression profile which was predictive for clinical benefit (defined as response and stable disease) from first line treatment. Conclusion: With miR profiling of CRC tissue samples response prediction to first line fluoropyrimidine-based treatment in patients with mCRC is possible. We foresee that selection of treatment using miR expression profiling will avoid unnecessary treatment related toxicity and improve outcome for patients with mCRC Citation Format: Dennis Poel, Maarten Neerincx, Daoud L.S. Sie, Nicole C.T. van Grieken, R Shankaraiah, F. S.W. van der Wolf, J. H.T.M van Waesberghe, J. D. Burggraaf, Paul P. Eijk, Bauke Ylstra, Cees Verhoef, Mark A. van de Wiel, Henk M.W. Verheul, Tineke E. Buffart. MiR expression profiles can predict response to systemic treatment in patients with advanced colorectal cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4928.

e14682 Background: MicroRNAs (miRs) have been recognized as promising biomarkers because of their role in cancer biology while being protected from degradation in tissue and blood samples. It is unknown to what extent tumor derived miRs are differentially expressed between primary colorectal cancers (CRCs) and metastatic lesions and between tumor and the surrounding normal tissue. We analyzed and compared miR expression profiles of novel and known miRs in primary CRC tissue and metastases as well as their surrounding normal tissue. Methods: Total RNA was isolated from 125 snap-frozen resection specimens including 40 primary CRC, 45 metastases, 23 normal colorectal en 17 normal extracolonic tissues corresponding to paired primary tumor samples and metastases from 38 patients. MiR expression profiles were obtained by next generation sequencing (NGS) using the Illumina Highseq 2000 platform. Sequence data were aligned to miRBase (release 19). Prediction of novel candidate miRs was based on specific folding characteristics of the precursor sequences using miRdeep2. Cluster analysis and differential expression for known miR sequences was performed using the R statistical software package in a paired manner. Results: 1714 different miRs were identified of which only 8 (0.5%) were differentially expressed between metastases and primary tumors (BFDR < 0.1), including five known and three novel candidate miRs. 212 miRs were significantly different expressed between CRC and normal colorectal tissue samples (BFDR < 0.05). Unsupervised clustering did not separate primary tumor tissue from their paired metastases, while tumor tissues and normal colorectal mucosae were completely separated. Conclusions: MiR expression profiles of primary or secondary origin of CRC tissues may be of similar value for their potential prognostic or predictive value.

Despite developments in targeted gene sequencing and whole-genome analysis techniques, the robust detection of all genetic variation, including structural variants, in and around genes of interest and in an allele-specific manner remains a challenge. Here we present targeted locus amplification (TLA), a strategy to selectively amplify and sequence entire genes on the basis of the crosslinking of physically proximal sequences. We show that, unlike other targeted re-sequencing methods, TLA works without detailed prior locus information, as one or a few primer pairs are sufficient for sequencing tens to hundreds of kilobases of surrounding DNA. This enables robust detection of single nucleotide variants, structural variants and gene fusions in clinically relevant genes, including BRCA1 and BRCA2, and enables haplotyping. We show that TLA can also be used to uncover insertion sites and sequences of integrated transgenes and viruses. TLA therefore promises to be a useful method in genetic research and diagnostics when comprehensive or allele-specific genetic information is needed.