Dr. Bingxin Lu

Dr. Bingxin Lu

Surrey Future Fellow

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

portfolio

posters

preprints

Cell-cycle dependent DNA repair and replication unifies patterns of chromosome instability

Published:

Abstract

Chromosomal instability (CIN) is pervasive in human tumours and often leads to structural or numerical chromosomal aberrations. Somatic structural variants (SVs) are intimately related to copy number alterations but the two types of variant are often studied independently. In addition, despite numerous studies on detecting various SV patterns, there are still no general quantitative models of SV generation. To address this issue, we develop a computational cell-cycle model for the generation of SVs from end-joining repair and replication after double strand break formation. Our model provides quantitative information on the relationship between breakage fusion bridge cycle, chromothripsis, seismic amplification, and extra-chromosomal circular DNA. Given single-cell whole-genome sequencing data, the model also allows us to infer important parameters in SV generation with Bayesian inference. Our quantitative framework unifies disparate genomic patterns resulted from CIN, provides a null mutational model for SV, and reveals new insights into the impact of genome rearrangement on tumour evolution.

Recommended citation: Bingxin Lu, Samuel Winnall, William Cross, Chris P. Barnes (2023). Cell-cycle dependent DNA repair and replication unifies patterns of chromosome instability. bioRxiv: 2024.01.03.574048. https://www.biorxiv.org/content/10.1101/2024.01.03.574048v1

publications

Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns

Published in Nature Genetics, 2021

Recommended citation: Yannik Bollen, Ellen Stelloo, Petra van Leenen, Myrna van den Bos, Bas Ponsioen, Bingxin Lu, Markus J. van Roosmalen, Ana C. F. Bolhaqueiro, Christopher Kimberley, Maximilian Mossner, William C. H. Cross, Nicolle J. M. Besselink, Bastiaan van der Roest, Sander Boymans, Koen C. Oost, Sippe G. de Vries, Holger Rehmann, Edwin Cuppen, Susanne M. A. Lens, Geert J. P. L. Kops, Wigard P. Kloosterman, Leon W. M. M. Terstappen, Chris P. Barnes, Andrea Sottoriva, Trevor A. Graham, Hugo J. G. Snippert. Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns. Nat Genet 53, 1187–1195 (2021). https://doi.org/10.1038/s41588-021-00891-2 https://www.nature.com/articles/s41588-021-00891-2

Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma: the PLANET study

Published in National Science Review, 2022

Recommended citation: Weiwei Zhai, Hannah Lai, Neslihan Arife Kaya, Jianbin Chen, Hechuan Yang, Bingxin Lu, Jia Qi Lim, Siming Ma, Sin Chi Chew, Khi Pin Chua, Jacob Josiah Santiago Alvarez, Pauline Jieqi Chen, Mei Mei Chang, Lingyan Wu, Brian K P Goh, Alexander Yaw-Fui Chung, Chung Yip Chan, Peng Chung Cheow, Ser Yee Lee, Juinn Huar Kam, Alfred Wei-Chieh Kow, Iyer Shridhar Ganpathi, Rawisak Chanwat, Jidapa Thammasiri, Boon Koon Yoong, Diana Bee-Lan Ong, Vanessa H de Villa, Rouchelle D Dela Cruz, Tracy Jiezhen Loh, Wei Keat Wan, Zeng Zeng, Anders Jacobsen Skanderup, Yin Huei Pang, Krishnakumar Madhavan, Tony Kiat-Hon Lim, Glenn Bonney, Wei Qiang Leow, Valerie Chew, Yock Young Dan, Wai Leong Tam, Han Chong Toh, Roger Sik-Yin Foo, Pierce Kah-Hoe Chow, Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma: the PLANET study, National Science Review, Volume 9, Issue 3, March 2022, nwab192, https://doi.org/10.1093/nsr/nwab192 https://academic.oup.com/nsr/article/9/3/nwab192/6414014

CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples

Published in Genome Biology, 2023

Abstract

Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, and mutation rates from total copy numbers of longitudinal samples. Our extensive simulations suggest CNETML performs well on copy numbers relative to ploidy and under slight violation of model assumptions. The application of CNETML to real data generates results consistent with previous discoveries and provides novel early copy number events for further investigation.

Recommended citation: Bingxin Lu, Kit Curtius, Trevor A. Graham, Ziheng Yang, Chris P. Barnes. CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples. Genome Biol 24, 144 (2023). https://doi.org/10.1186/s13059-023-02983-0 https://doi.org/10.1186/s13059-023-02983-0

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