Welcome to computational cancer genomics lab!

Unraveling the genetic code of cancer


Welcome to the Computational Cancer Genomics Lab at the Princess Margaret Cancer Center at the University Health Network. We study role of genomic variations in driving tumor progression.

Our lab studies cancer biology by building computational tools with state-of-the art genomics, biophysics, and machine learning techniques. We are looking for enthusiastic researchers and students interested in computational biology to JOIN US!

Rapid declines in sequencing costs have enabled large-scale genome and exome sequencing for various cancer cohorts. A critical shared objective among such studies has been to understand how genomic variants affect tumor etiology. How may we develop robust quantitative models to predict the impact of somatic mutations on gene expression and protein function? Furthermore, how may we leverage these quantitative models to prioritize genomic variants and utilize this knowledge to develop new cancer therapeutics? Our lab is interested in developing integrative methods that use multiple data resources and cross-disciplinary approaches to address questions of this nature.

Previously, we have developed methods that integrate protein structure and protein motion information to evaluate the molecular impact of cancer mutations and identify putative cancer driver genes. Currently, we are building machine learning methods integrating protein structure, cancer genomics, and clinical data to identify novel drug targets and predict drugs' efficacy & side effects among cancer patients.

The canonical model of cancer progression dichotomizes cancer mutations as drivers and passengers. However, our recent analysis of thousands of cancer genomes indicates the presence of a continuum where strong and weak drivers can contribute to cancer progression via epistatic interactions or their aggregated/additive effects. As a follow-up to this work, we are currently developing novel methods to investigate the role of cooperative genetic and cellular level interactions in driving tumor growth and metastases.

The overwhelming majority of cancer mutations fall within non-coding regions of the genome. Clear insights into how non-coding mutations play causal roles in various cancer types remain limited. Similar to non-coding mutations, we have little understanding of how SVs influence cancer progression. My group is interested in building methodologies for understanding the role of non-coding mutations and SVs in different cancer cohorts.

Recent Publications

Unified views on variant impact across many diseases,Sushant Kumar**and Mark Gerstein. Trends in Genetics (2023)

Whole-genome sequencing of phenotypically distinct inflammatory breast cancers reveals similar genomic alterations to the more commonplace non-inflammatory breast cancers, Xiaotong Li; Sushant Kumar; Arif Harmanci; …. Naoto T. Ueno; Savitri Krishnamurthy; Lajos Pusztai; and Mark Gerstein. Genome Medicine (2021)

Haplotype-resolved diverse human genomes and integrated analysis of structural variation, Peter Ebert; Peter Audano; Qihui Zhu; Bernardo Rodriguez-Martin; …. Sushant Kumar; …... Tobias Marschall; and Evan E. Eichler Science (2021)

SVFX: a machine learning framework to quantify the pathogenicity of structural variants, Sushant Kumar*; Arif Harmanci*; Jagath Vytheeswaran; and Mark Gerstein Genome Biology (2020)

Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences, Sushant Kumar*; Jonathan Warrell*; Shantao Li; Patrick McGillivray; William Meyerson; Leonidas Salichos;….. Ekta Khurana; and Mark Gerstein. Cell (2020)

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes, Esther Rhienbay; Morten Nielsen; Federico Abascal; Jermiah Wala;….. Sushant Kumar; …... Jakob Pedersen; and Gad Getz. Nature (2020)

Leveraging protein dynamics to identify cancer mutational hotspots in 3D-structures, Sushant Kumar; Declan Clarke; and Mark Gerstein. PNAS (2019)

For full publication list please check our google scholar page


Sushant Kumar is the Canada Research Chair (Tier 2) in Genomic Medicine and an Assistant Professor in the Department of Medical Biophysics at the University of Toronto. He is also a scientist at the Princess Margaret Cancer Center. His expertise and research interests are in computational biology/bioinformatics, cancer biology, genomics, machine learning, and biophysics. Outside of work, he likes to watch sports documentaries and spend time with family.

Nirvana Nursimulu is a postdoctoral researcher in the lab. She completed her undergraduate degree in Bioinformatics and Computational Biology at the University of Toronto, after which she embarked on a journey through graduate school at the University of Toronto studying Computer Science under the supervision of Dr Parkinson and Dr Moses. From her previous work, she remains fascinated by how mathematics can be used to capture biological phenomena and model the growth of parasites. In her free time, she enjoys reading and writing fiction, running, and has occasionally engaged in improvisational theatre.

Saman Bazmi is a postdoctoral researcher in the lab. He completed his PhD in Computational Biophysics at Memorial University of Newfoundland. His research interests are computational biology, molecular dynamics, and cancer genomics. In his free time, he likes to watch criminal tv series, hiking, and cooking.

Yosef received his Ph.D. in Bioinformatics in 2019 from the University of Tehran and completed a year-long postdoctoral program. Before moving to UHN, Yosef held a faculty teaching position at the Tabriz University of Medical Sciences and then completed a two-year-long postdoctoral course at Queen's University. Yosef has over a decade of teaching experience (from undergraduate to Ph.D. level) in Bioinformatics. He is interested in introducing novel algorithms, developing machine learning methods, and designing efficient data structures for biological applications.

Nadejda Boev is a graduate student in the Department of Medical Biophysics at the University of Toronto. She completed her undergraduate degree in Biology & Mathematics at Queen's University. In her free time, she enjoys going on walks and listening to podcasts.

Nour Hanafi is a PhD student in the Department of Medical Biophysics at the University of Toronto (U of T). She completed her undergraduate degree in Molecular Biology with a Chemistry minor at U of T Mississauga, an MHSc in Medical Genomics at U of T, and worked as an analyst at the SickKids’ Centre for Computational Medicine. In her free time, she enjoys long walks, trying out new iced drinks, and watching her favorite sports teams, Atletico Madrid and the Toronto Raptors.

Jean Charle Yaacoub is a research analyst in the lab. Jean completed his Bachelor of Computing at Queen's University and Master of Science in Applied Computing from the University of Toronto. In his free time, he enjoys powerlifting, hiking with his dog, and watching anime

Yumika Shiba is a bioinformatics analyst in the lab. Yumkia studied Computer science and Biology at McGill University. Her past research revolves around UK Biobank and genotyping transposable elements. She is deeply touched when she hears whispers of data. Aside from research, she loves birds, playing the piano and the ukulele, and biking.

Alexander Turco is a research assistant in the lab. He completed his undergraduate study in biology with a focus on bioinformatics from McMaster University. Outside of the lab, Alexander enjoys travelling, Rubik’s cubes, snowboarding, and Star Wars.

Yukai Wang is a summer student in the lab. Yukai completed his Bachelor of Computer Science at University of Waterloo and Master of Science in Applied Computing from the University of Toronto. In his free time, he enjoys playing basketball, snowboarding and playing video games.

Lekshmi Mohan is a Master of Health Sciences candidate in the Medical Genomics program at the Temerty Faculty of Medicine, University of Toronto and is currently a summer student in the lab. She completed her undergraduate degree in Biotechnology and a certification in Regulatory Affairs. In her free time, she enjoys drawing, walking out in nature, travelling, and listening to podcasts.

Hayden is a research volunteer in the lab and is also a MSc student in Applied Computing at University of Toronto. Before that, he completed his undergraduate degree in Computer Science and Mathematics in Hong Kong. His interest surrounds computer vision and enhancing machine learning pipelines for industry uses. In leisure time, he likes hiking, bouldering, and snowboarding.

Victoria Valeeva is a summer student in the lab. She is completing her undergraduate degree in mathematics and statistics at the University of Toronto. Her interests include molecular dynamics, statistical mechanics, and computational biology. Outside of the lab, Victoria enjoys hiking and cooking. Her favourite band is Death Grips.

Jackson Howe is a undergraduate student in the lab. He is completing his undergraduate degree in computer science from the University of Waterloo. Jackson is passionate about designing efficient bioinformatics applications and user-friendly tools for researchers and clinical applications. When not working, Jackson enjoys long-distance running, going to concerts, and watching the Blue Jays.

Lucy Fuccillo is the research administrative assistant of the lab. Lucy was born and raised in Niagara Falls, Ontario. Subsequently, she moved to Toronto in 1999 to attend George Brown College to study Business Management. She has 30+ years of experience working as a research administrative assistant for various research and clinical organizations. Away from work, Lucy enjoys cycling, working out, and taking long walks with her buddy Watson!

We are looking for enthusiastic researchers and students interested in computational biology and cancer research to JOIN US!


Shaoshi Zhang   (Current Position: Graduate Student at the University of Western Ontario)

Grace Hu   (Current Position: MD Student at the University of Toronto)

Luke Zhang   (Current Position: PhD Student at the University of Toronto)


Postdoctoral Associate

Job description: Applications are invited for postdoctoral positions in the computational cancer genomics laboratory at the Princess Margaret Cancer Center. We are interested in working with highly motivated people interested in building tools and analyzing large-scale cancer multi-omics data. They will have opportunities to collaborate with a diverse group of experimental and computational biologists at the Princess Margaret Cancer Centre and the University of Toronto. We are looking for candidates with prior experience in computational biology

Eligibility requirement: A Ph.D. in computational biology, bioinformatics, genomics, computer science, or a related field is required. A strong computational background, proficiency in at least one programming language, knowledge of machine learning and statistics are also needed.

How to Apply: Interested candidates should send a cover letter, CV, link to their GitHub/another codebase, and names of three references to Dr. Kumar (sushantDotkumarAtuhnresearchDotCA).

Graduate and Undergraduate Students

Interested students should send an email to Dr. Kumar (sushantDotkumarAtuhnresearchDotca) to discuss potential projects in the lab.


Fall 2023 -- Nour Hanafi joins the lab to pursue her PhD at MBP. Welcome, Nour!

Fall 2023 -- Nirvana Nursimulu joins the lab as the inaugural CBMP Postdoctoral Fellow. Welcome Nirvana!

Fall 2023 -- Saman Bazmi joins our group as postdoctoral associate. Welcome Saman!

Summer 2023 -- Alexander Turco joined our group for the summer as an undergraduate student researcher. Welcome Alex!

Summer 2023 -- Jackson Howe joined our group for the summer as a UofT Data Science Institute SUDS scholar. Welcome Jackson!

Summer 2023 -- Jean Yaacoub joined the lab for his coop internship as part of his graduate study in the MScAC program at UofT. Welcome Jean!

Spring 2023 -- Sushant attended the annual V summit in Virginia and presented our efforts toward cancer prevention and early detection.

Spring 2023 -- Nad received a Canada Graduate Scholarship award from CIHR to pursue her graduate thesis. Many congratulations, Nad!

Spring 2023 -- Our lab received funding from NSERC to study the evolution of the gene regulation process. We are very grateful for the support.

Winter 2022 -- Nadejda Boev joined the lab for her graduate studies. Welcome, Nad!

Fall 2022 -- Our lab received funding support from the Canada Research Chair Program. We are immensely thankful to CIHR.

Fall 2022 -- Our lab received funding from the V Foundation for Cancer Research as part of the V scholar program. We are very grateful.


Computational Cancer Genomics Lab
Princess Margaret Cancer Research Tower
University Health Network, University of Toronto
101 College Street Toronto, ON M5G 0A3