Ph.D. in computational methods for cancer multi-omics
Last modification : Thursday, September 22, 2022
Department of Oncology at KU Leuven accomodates around 400 researchers in 25
research groups and is one of the global leaders in several fields of cancer
research, including gastrointestinal oncology, cancer microenvironment,
vascular oncology, cancer metabolism and other fields. Laboratory for
Computational Cancer Biology and Epigenomics is a new research group focusing
upon computational method development and analysis of high-dimensional
datasets. Our particular interest are epigenetic mechanisms, foremost DNA
methylation and chromatin modifications, and their role in tumorigenesis. The
Ph.D. project will be carried out in close collaboration with the experimental
labs in the Department of Oncology, including the Laboratory for Digestive
Oncology and others.
The prevailing genetic theory of cancerogenesis postulates that malignant
transformations is driven by an accumulation of pathogenic mutations that
gradually increase the fitness and proliferative potential of cells that give
rise to cancer 1. However, recent studies have demonstrated that common
genetic drivers are often mutated in healthy tissues 2, and non-genetic
factors, such as epigenetic heterogeneity, together with the cues from tissue
microenvironment, might be playing a crucial role in cancer initiation 3.
In order to resolve this ambiguity for the benefit of cancer prevention,early
detection and treatment, one would have to recover the earliest gene
regulatory landscapes of cancer cells-of-origin and separate the oncogenically
induced alterations from those that emerged due to intrinsic heterogeneity and
the impact of microenvironment. The project will aim at developing
computational methods to (i) deconvolute tumor,immune and stromal
compartments in bulk, single-cell and spatial omics data of solid cancers,
(ii) reconstruct the transcriptional and gene regulatory states of pre-
malignant and early neoplastic cells, and (iii) disentangle the role and
contributions of the germline genetic backround, somatic mutations and non-
genetic factors to neoplastic transformation. Based on our previous work with
latent factor analysis in epigenomic data 4,5, we will apply
classical(e.g. NMF) and cutting-edge (e.g. deep CNNs, autoencoders)
machine learning approaches to jointly model data of various modalities. We
will combine bulk omicsprofiles from large patient cohorts with time-resolved
single-cell and spatialomics maps to bring together statistical power and high
cellular resolution in selected samples, and integrate gene expression maps
with epigenomic patterns(e.g. chromatin accessibility and DNA methylation)
to pinpoint the gene regulatory mechanisms driving tumorigenesis and develop
novel powerful biomarkers. Through own and our collaboration partners' entity-
focused projects, we will validate our methodology in several cancer types,
including colorectal, pancreatic, prostateand lung cancers, as well as rare
sarcoma entities 6.
Vogelstein et al. Cancer genes and the pathways they control. Nature Medicine , 2004.
Lawson etal. Extensive heterogeneity in somatic mutation and selection in the human bladder. Science , 2020.
Alonso-Curbelo et al. A gene-environment-induced epigenetic program initiates tumorigenesis. Nature , 2021.
Lutsik et al. MeDeCom: discovery and quantification of latent components of heterogeneous methylomes . Genome Biology , 2017.
Sherer et al. Reference-free deconvolution, visualization and interpretation of complexDNA methylation data using DecompPipeline, MeDeCom and FactorViz. Nature Protocols , 2020.
Lutsik et al. Globally altered epigenetic landscape and delayed osteogenic differentiation in H3.3-G34W-mutant giant cell tumor of bone. Nature Communications , 2020.
We are searching for a highly motivated candidate with specialized training
(Masters degree or equivalent) in computational biology, bioinformatics,
computer science or related disciplines. We expect:
- solid knowledge of state-of-the-art machine learning and data science
methodology,combined with a genuine interest to leverage it for solving
important problems in cancer research (previous experience single-cell and/or
spatial omics data is a major advantage);
- excellent programming skills in one of the scripting (Python, R) and/or
core development (C/C++/Java) languages, as well as experience with software
packaging and deployment;
- fluency with Linux-based computational infrastructure and familiarity with
majorHPC enviornments (cluster schedulers, cloud computing etc);
- willingness to gain deep biological understanding of the studied cancer
- well-structured working style and appreciation for reproducible research
practices in computational biology, e.g. proper data management and scientific
- goal-oriented team player attitude and ability to spearhead interactions
with collaboration partners;
- good communication skills and command of English language, both spoken and
We offer a full time PhD position for 48 months,given positive evaluation by
the doctoral committee at the end of the first year. A successful PhD
candidate will be immersed into a vibrant and highly stimulating scientific
environment within the Department of Oncology, VIB-KULeuven Center for Cancer
Biology and beyond, with ample possibilities to interact with researchers from
other groups. For their project the candidate will obtain access to cutting-
edge datasets and computational infrastructure. The offered project is highly
collaborative and will involve participation in the work of global consortia,
such as Pan-Prostate Cancer Group, regular exchange visits with collaboration
partners across Europe, presentations at major conferences and meetings.
Beyond that, you will have access to versatile options for personal growth and
development, advanced qualification courses and mentoring.
For more information please contact Prof. dr. Pavlo Lutsik, mail:
KU Leuven seeks to foster an environment where all talents can flourish,
regardless of gender, age, cultural background, nationality or impairments. If
you have any questions relating to accessibility or support, please contact us