4 results on '"Bunkum A."'
Search Results
2. CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction.
- Author
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Grigoriadis K, Huebner A, Bunkum A, Colliver E, Frankell AM, Hill MS, Thol K, Birkbak NJ, Swanton C, Zaccaria S, and McGranahan N
- Subjects
- Humans, Phylogeny, Computational Biology methods, Sequence Analysis, DNA, Mutation, Algorithms, Neoplasms genetics, Neoplasms pathology
- Abstract
Intratumor heterogeneity provides the fuel for the evolution and selection of subclonal tumor cell populations. However, accurate inference of tumor subclonal architecture and reconstruction of tumor evolutionary histories from bulk DNA sequencing data remains challenging. Frequently, sequencing and alignment artifacts are not fully filtered out from cancer somatic mutations, and errors in the identification of copy number alterations or complex evolutionary events (e.g., mutation losses) affect the estimated cellular prevalence of mutations. Together, such errors propagate into the analysis of mutation clustering and phylogenetic reconstruction. In this Protocol, we present a new computational framework, CONIPHER (COrrecting Noise In PHylogenetic Evaluation and Reconstruction), that accurately infers subclonal structure and phylogenetic relationships from multisample tumor sequencing, accounting for both copy number alterations and mutation errors. CONIPHER has been used to reconstruct subclonal architecture and tumor phylogeny from multisample tumors with high-depth whole-exome sequencing from the TRACERx421 dataset, as well as matched primary-metastatic cases. CONIPHER outperforms similar methods on simulated datasets, and in particular scales to a large number of tumor samples and clones, while completing in under 1.5 h on average. CONIPHER enables automated phylogenetic analysis that can be effectively applied to large sequencing datasets generated with different technologies. CONIPHER can be run with a basic knowledge of bioinformatics and R and bash scripting languages., (© 2023. Springer Nature Limited.)
- Published
- 2024
- Full Text
- View/download PDF
3. The evolution of non-small cell lung cancer metastases in TRACERx.
- Author
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Al Bakir M, Huebner A, Martínez-Ruiz C, Grigoriadis K, Watkins TBK, Pich O, Moore DA, Veeriah S, Ward S, Laycock J, Johnson D, Rowan A, Razaq M, Akther M, Naceur-Lombardelli C, Prymas P, Toncheva A, Hessey S, Dietzen M, Colliver E, Frankell AM, Bunkum A, Lim EL, Karasaki T, Abbosh C, Hiley CT, Hill MS, Cook DE, Wilson GA, Salgado R, Nye E, Stone RK, Fennell DA, Price G, Kerr KM, Naidu B, Middleton G, Summers Y, Lindsay CR, Blackhall FH, Cave J, Blyth KG, Nair A, Ahmed A, Taylor MN, Procter AJ, Falzon M, Lawrence D, Navani N, Thakrar RM, Janes SM, Papadatos-Pastos D, Forster MD, Lee SM, Ahmad T, Quezada SA, Peggs KS, Van Loo P, Dive C, Hackshaw A, Birkbak NJ, Zaccaria S, Jamal-Hanjani M, McGranahan N, and Swanton C
- Subjects
- Humans, Cohort Studies, Disease Progression, Neoplasm Recurrence, Local, Carcinoma, Non-Small-Cell Lung pathology, Clonal Evolution, Clone Cells pathology, Evolution, Molecular, Lung Neoplasms pathology, Neoplasm Metastasis diagnosis, Neoplasm Metastasis pathology
- Abstract
Metastatic disease is responsible for the majority of cancer-related deaths
1 . We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse., (© 2023. The Author(s).)- Published
- 2023
- Full Text
- View/download PDF
4. The evolution of lung cancer and impact of subclonal selection in TRACERx.
- Author
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Frankell AM, Dietzen M, Al Bakir M, Lim EL, Karasaki T, Ward S, Veeriah S, Colliver E, Huebner A, Bunkum A, Hill MS, Grigoriadis K, Moore DA, Black JRM, Liu WK, Thol K, Pich O, Watkins TBK, Naceur-Lombardelli C, Cook DE, Salgado R, Wilson GA, Bailey C, Angelova M, Bentham R, Martínez-Ruiz C, Abbosh C, Nicholson AG, Le Quesne J, Biswas D, Rosenthal R, Puttick C, Hessey S, Lee C, Prymas P, Toncheva A, Smith J, Xing W, Nicod J, Price G, Kerr KM, Naidu B, Middleton G, Blyth KG, Fennell DA, Forster MD, Lee SM, Falzon M, Hewish M, Shackcloth MJ, Lim E, Benafif S, Russell P, Boleti E, Krebs MG, Lester JF, Papadatos-Pastos D, Ahmad T, Thakrar RM, Lawrence D, Navani N, Janes SM, Dive C, Blackhall FH, Summers Y, Cave J, Marafioti T, Herrero J, Quezada SA, Peggs KS, Schwarz RF, Van Loo P, Miedema DM, Birkbak NJ, Hiley CT, Hackshaw A, Zaccaria S, Jamal-Hanjani M, McGranahan N, and Swanton C
- Subjects
- Humans, Adenocarcinoma of Lung etiology, Adenocarcinoma of Lung genetics, Adenocarcinoma of Lung pathology, Mutation, Neoplasm Recurrence, Local genetics, Phylogeny, Treatment Outcome, Smoking genetics, Smoking physiopathology, Mutagenesis, DNA Copy Number Variations, Carcinoma, Non-Small-Cell Lung etiology, Carcinoma, Non-Small-Cell Lung genetics, Carcinoma, Non-Small-Cell Lung pathology, Lung Neoplasms etiology, Lung Neoplasms genetics, Lung Neoplasms pathology
- Abstract
Lung cancer is the leading cause of cancer-associated mortality worldwide
1 . Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource., (© 2023. The Author(s).)- Published
- 2023
- Full Text
- View/download PDF
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