These FIMM PhD students defended their thesis during 2018. Congratulations!
FIMM Dissertations 2018
Unravelling Lung Cancer Heterogeneity and Associated Therapeutic Responses Using In Vivo and Ex Vivo Model Systems
December 7th, 2018
The thesis work of M.Sc. Ashwini Nagaraj focused on investigating the role of tumor cell of origin in establishing lung cancer phenotypic and functional heterogeneity using genetically engineered lung cancer mouse models. The thesis was supervised by Dr. Emmy Vershuren and Dr. Denis Kainov.
Ashwini's thesis demonstrate that the tumor cell of origin is crucial in determining survival, lung cancer subtype, and associated immune microenvironment in the mouse model used. In addition, it ighlights that beyond understanding lung cancer at the genetic level, investigation of histotype-specific etiology, and spatially distributed functions including oncogenic signaling activities is important for designing effective therapies.
Seven shades of tamoxifen resistance - Molecular mechanisms of drug resistance in breast cancer
October 23rd, 2018
M.Sc. Susanne Hultsch's thesis work focuses on the cellular events that precede the development of resistance to one the most important breast cancer treatments, tamoxifen. The thesis was supervised by Sara Kangaspeska, Olli Kallioniemi and Vilja Pietiäinen.
The overall goal of Susanne’s thesis was to create and utilize breast cancer cell line models to explore the resistance mechanisms of breast cancer and find potential prognostic markers as well as drug vulnerabilities. Susanne says that even after "70 years of research, drug resistance is still a problem and we need to learn more about mechanisms of it and vulnerabilities associated with these mechanisms to be able to treat drug-resistant cancers".
Improving Precision in Therapies for Hematological Malignancies
October 12th, 2018
M.Sc. Muntasir Mamun Majumder's thesis focused on accelerating the adoption of precision medicine practices in myeloma and other hematological cancers. The thesis was supervised by Caroline Heckman and Krister Wennerberg.
The main goal of Mamun's thesis was to identify individualised treatment decisions and to facilitate drug discovery efforts for multiple myeloma. The research covered all the key aspects of precision medicine from method development, patient stratification and biomarker identification to validating the clinical utility of the findings.
Machine Learning for Systems Pharmacology
October 5th, 2018
M.Sc. Anna Cichonska's thesis work was supervised by Tero Aittokallio and Matti Pirinen (FIMM) and Professor Juho Rousu (Aalto University). Anna received an "Aalto Univeristy dissertation award 2019" on her thesis.
Targeting Key Survival Signaling Pathways for The Treatment of Leukemia
September 28th, 2018
M.Sc. Heikki Kuusanmäki's thesis approached the challenges of transforming the new knowledge on leukemia genetics into clinically actionable strategies by combining genetic profiling with high-throughput drug sensitivity testing in patient derived leukemia cells. The thesis work was supervised by Caroline Heckman and Satu Mustjoki.
The main objective of Heikki's thesis was to identify novel driver mutations in two rare leukemia types, large granular lymphocyte (LGL) leukemia and T-cell acute lymphoblastic leukemia (T-ALL). Furthermore, he wanted to develop a new flow cytometry-based drug screening assay to assess cell population specific drug responses in heterogenous leukemia samples.
Clonal evolution and heterogeneity of cancer in the context of individualized medicine
August 24th, 2018
M.Sc. Poojitha Ojamies' thesis work focused on developing sequencing and bioinformatics methods to study spatial and temporal tumor heterogeneity and evolution of cancer subclones. The thesis was supervised by Prof. Olli Kallioniemi and Dr. Maija Wolff.
The goal of Poojitha’s thesis was to comprehensively investigate cancer evolution and heterogeneity as well as understand drug responses at a subclone level in the context of individualised cancer treatment. Her thesis project is part of FIMM’s “Individualised systems medicine in cancer” Grand Challenge programme.
Computer vision for tissue characterization and outcome prediction in cancer
August 24th, 2018
M.Sc. (Tech) Riku Turkki's thesis focused on investigating the use of computer vision for tissue characterisation and patient outcome prediction in cancer. The thesis work was supervised by Johan Lundin and Nina Linder.
Although a lot of progress is made in cancer diagnostics and outcome prediction, histological analysis of tumour tissue still has a key role. Manual histological evaluation is time-consuming and prone to subjective assessment. In his thesis, Riku tackled this challenge by developing computer vision aided processes and testing their applicability for clinical purposes. The main aim of his dissertation was to investigate the use of computer vision for tissue characterisation and patient outcome prediction in cancer.
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Functional testing of urological cancer models by RNAi and drug libraries
August 13th, 2018
M.Sc. Khalid Saeed’s thesis work focused on identifying novel future treatment strategies for prostate, renal and kidney cancer. His thesis was supervised by Olli Kallioniemi, Päivi Östling and Taija af Hällström.
In his thsesis, Khalid’s was aimed to generate molecular profile and drug testing data using patient-derived cancer cells. His proof-of-concept studies show that this kind of data can be used to help clinicians in treatment decision and to facilitate the early selection of the best drug candidates for clinical development.
Molecular Effects of Obesity and Related Metabolic Risk Factors – A Transcriptomics and Metabolomics Approach
June 8th, 2018
M.Sc., MBA Maheswary Muniandy’s thesis focused on studying obesity using omics data and bioinformatics tools. The thesis work was supervised by Dr. Miina Ollikainen and Prof. Kirsi Pietiläinen.
The global obesity epidemic is worsening in most parts of the world and the implications of obesity regarding both personal health and health-economics are enormous. Understanding the molecular mechanisms leading to and caused by obesity could help in designing personalised treatment to support weight-loss. In her thesis Maheswary tried to gain understanding of the complex, multifactorial biology behind obesity using bioinformatics tools.
Integrative bioinformatics of functional and genomic profiles for cancer systems medicine
June 8th, 2018
M.Sc. Alok Jaiswal’s thesis 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. The thesis work was supervised by Tero Aittokallio and Jing Tang.
The goal of Alok's thesis was to provide information about the genes driving cancer that could be utilised in identifying promising cancer drug candidates and predictive biomarkers. He developed an approach to remove noise from genome-wide RNAi screens and also integrated genomic profiles with the RNAi screen data to be able to predict major cancer driver genes and their synthetic lethal partners.
Analysis of somatic mutations in leukemias
May 21st, 2018
M.Sc. Samuli Eldfors' thesis focused on identifying clinically important somatic mutations contributing to the development and treatment response of different leukemias. The thesis work was supervised by Dr. Caroline Heckman and Prof. Olli Kallioniemi.
In his thesis, Samuli has identified somatic mutations in three leukemia types and analyzed the biological and clinical significance of these mutations. A major part of the work has been the development of a computational workflow and the application of bioinformatics approaches to detect mutations based on whole exome sequencing data.
In Search of Improved Outcome Prediction of Prostate Cancer – A Biological and Clinical Approach
May 11th, 2018
The thesis of M.Sc. Andrew Erickson focused on identifying novel biological and clinical factors that could be utilized in the outcome prediction of prostate cancer. The thesis was supervised by Tuomas Mirtti and Antti Rannikko.
In the first part his thesis work, Andrew focused on outcomes of low-risk active surveillance patients. And in the second part of the thesis, the focus was on the long-term outcome of primarily treated patients.
Association and interplay of genetic and epigenetic variants in smoking behavior
April 20th, 2018
The thesis of M.Sc. Richa Gupta focused on studying the links between the smoking behaviour and genetic as well as epigenetic variation. The thesis work was supervised by Jaakko Kaprio and Miina Ollikainen.
Smoking is the single greatest preventable cause of death in the world today. In her thesis, Richa utilised several different omics data, including genetics (assessed by single nucleotide polymorphisms), epigenetics (assessed by DNA methylation), as well as transcriptomics data to identify novel associations and validating the involvement of known candidate genes in smoking behaviour.
Bioinformatic identification of disease driver networks using functional profiling data
March 23rd, 2018
The thesis of M.Sc. Agnieszka Szwajda was supervised my FIMM-EMBL Group Leaders Tero Aittokallio and Krister Wennerberg.