Alok Jaiswal’s dissertation demonstrates the impact of computational approaches on data integration in cancer research
M.Sc. Alok Jaiswal’s thesis entitled "Integrative bioinformatics of functional and genomic profiles for cancer systems medicine” will be publically examined on Friday, 8 June, with the permission of the Faculty of Medicine of the University of Helsinki. The thesis has focused on developing novel computational models and approaches for data analysis to facilitate extracting reproducible and meaningful information from the genomic and functional cancer datasets.
A number of large-scale studies focusing on genetic background of different cancers have been performed and the related genomic profiling data have been made available to the scientific community. Lately, also functional profiling datasets based on RNA interference and drug sensitivity screens have become increasingly available. Genetic and functional data provide complementary and valuable information for better understanding of the functional relevance of genes related to cancer.
The main aim of M.Sc. Alok Jaiswal’s thesis entitled "Integrative bioinformatics of functional and genomic profiles for cancer systems medicine” was to develop novel computational models for integrating genomic and functional data types and to implement them on cancer research data.
Alok Jaiswal graduated from Jamia Hamdard University in Delhi in 2009, specialising in biotechnology. He received a highly competitive FIMM-EMBL PhD student position and started at the rotation programme in 2012. After the rotation period, he decided to start his PhD project in the computational research group of FIMM-EMBL Group Leader Tero Aittokallio. The thesis has been co-supervised by FIMM Group Leader Jing Tang.
Making the jump from biotechnology to computational field was a bit hard in the beginning but it has definitely paid off. The combination of biological knowledge and computational modelling skills is valued in the scientific community and I have been fortunate to be able to develop a completely new skill set during the project.
- Alok Jaiswal
In his thesis, Alok concentrated on developing novel computational models and approaches for data analysis to facilitate extracting reproducible and meaningful information from the genomic and functional cancer datasets. The ultimate goal was to provide information about the genes driving cancer that could be utilised in identifying promising cancer drug candidates and predictive biomarkers.
Undesired off-target effects often complicate the interpretation of RNA interference results, and the consistency of these screens have been questioned. We wanted to develop methods that are able to account for the complex biological mechanisms involved and thus increase the reliability of the results.
His thesis consists of three publications, all of which have already been published.
In the first paper of the thesis, Alok developed an approach to remove noise from genome-wide RNAi screens. Furthermore, he integrated genomic profiles with the RNAi screen data to be able to predict major cancer driver genes and their synthetic lethal partners. These results were then experimentally validated by CRISPR/Cas9 technology.
As part of the thesis work, Alok participated in a crowd-based competition “Broad-DREAM Gene Essentiality Prediction Challenge”. Their team won one of the sub-challenges where the task was to identify the most predictive features for gene essentiality values of a prioritised list of genes. The results are described in the second publication of the thesis.
In the third study, Alok focused on identifying a gene expression signature associated with a property called cancer stemness (stem cell like characteristics). This property and the identified gene expression signature can be used to predict the sensitivity of the cancers to certain inhibitor drugs and to identify patient sub-groups that will most likely benefit from this therapy.
Overall, my thesis work demonstrates that computational approaches to integrate functional and genomic datasets of cancer cell lines can be useful in understanding cancer biology and guide further translational efforts for cancer therapy under the precision medicine paradigm.
During the PhD project, I have grown to face my fears and to turn the uncertainty in research into positivity. FIMM has been a great place for me to develop my own intellectual path in a supportive and collaborative environment.
Alok will stay at FIMM for a few more months and is currently looking for a post-doc position where he could combine his data mining skills with an applied research project.
The public examination of Alok Jaiswal’s doctoral dissertation will take place on 8 June at 12 o'clock noon in the Lecture hall 2 at Biomedicum Helsinki 1, Haartmaninkatu 8. The thesis has been supervised by FIMM-EMBL Group Leader, Professor Tero Aittokallio and FIMM Group Leader, Dr. Jing Tang. Associate Professor Benjamin Haibe-Kains (University of Toronto) will serve as the opponent and Professor Jaakko Kaprio as the custos.
The dissertation is also available in an electronic form