Tapahtumakalenteri (vanha)
kesäkuu
16
Dissertation: Feiyi Wang
Feiyi Wang, University of Helsinki, Faculty of Medicine, Doctoral Programme in Clinical Research
Familial and genetic risk factors for autoimmune diseases
Opponent: Professor Ingrid Kockum, Karolinska Institutet
Aloitusaika: 16.06.2025 13:00
Lopetusaika: 16.06.2025 15:00
Kesto: 2 hours
Sijainti: Biomedicum1, lecture hall 2, Haartmaninkatu 8, 00290 Helsinki
Tyyppi: Dissertation
Organisaatio: UH, Faculty of Medicine
Yhteyshenkilö: feiyi.wang@helsinki.fi
Online-kokouslinkki:
https://video.helsinki.fi/unitube/live-stream.html?room=l43
kesäkuu
17
iCAN Science Seminar on Bridging the radiology-pathology gap for prostate cancer characterization with Mirabela Rusu
Welcome to the iCAN science
seminar with Assistant Professor Mirabela Rusu (Stanford University) on on Bridging the radiology-pathology gap for prostate
cancer characterization!
Radiology imaging is an essential non-invasive tool for cancer care, facilitating diagnosis and treatment planning. Yet, despite technological advancements in imaging, radiologists still miss 12-36% of aggressive prostate cancers due to their subtle radiologic features. Some patients undergo surgery as cancer treatment and thus have rich data comprised of high-resolution pathology images showing the extent, heterogeneity, and aggressiveness of cancer. In this context, Prof. Rusu’s team develops advanced deep learning methods to assist radiologists in their image interpretation. The approaches are split between two categories. First, the team developed registration methods that align radiology and pathology images, e.g., in the prostate or breast, using both traditional and deep-learning based registration methods. Second, they developed radiology-pathology fusion strategies by constructing pathology-derived radiology (rad-pathomic) biomarkers. When included in deep learning models, these biomarkers improved by 7% the detection of aggressive vs indolent cancers on prostate MRI or kidney CT. While this cancer detection methods are trained when both radiology and pathology images are available, they only use radiology images at inference time in new unseen patients, rendering then useful to guide biopsy or local treatment procedures.
Radiology imaging is an essential non-invasive tool for cancer care, facilitating diagnosis and treatment planning. Yet, despite technological advancements in imaging, radiologists still miss 12-36% of aggressive prostate cancers due to their subtle radiologic features. Some patients undergo surgery as cancer treatment and thus have rich data comprised of high-resolution pathology images showing the extent, heterogeneity, and aggressiveness of cancer. In this context, Prof. Rusu’s team develops advanced deep learning methods to assist radiologists in their image interpretation. The approaches are split between two categories. First, the team developed registration methods that align radiology and pathology images, e.g., in the prostate or breast, using both traditional and deep-learning based registration methods. Second, they developed radiology-pathology fusion strategies by constructing pathology-derived radiology (rad-pathomic) biomarkers. When included in deep learning models, these biomarkers improved by 7% the detection of aggressive vs indolent cancers on prostate MRI or kidney CT. While this cancer detection methods are trained when both radiology and pathology images are available, they only use radiology images at inference time in new unseen patients, rendering then useful to guide biopsy or local treatment procedures.
Hosts: Prof. Tuomas Mirtti and Doctoral Researcher Tolou Shabdah
Bio: Dr. Rusu is an Assistant Professor, in the Department of Radiology, and, by courtesy, Department of Urology and Biomedical Data Science, at Stanford University, California, where she leads the Personalized Integrative Medicine Laboratory (PIMed). The PIMed Laboratory has a multi-disciplinary direction and focuses on developing analytic methods for biomedical data integration, with a particular interest in multimodal fusion, e.g., radiology-pathology fusion to facilitate radiology image labeling, or MRI-ultrasound for guiding procedure. These fusion approaches allow the downstream training of advanced multimodal machine learning for cancer detection and subtype identification at pixel-level. Our approaches have been applied in oncologic applications (prostate, breast, kidney).Aloitusaika: 17.06.2025 11:45
Lopetusaika: 17.06.2025 12:45
Kesto:
Sijainti: HUS Siltasairaala, Ullanlinnasali, Haartmaninkatu 4
Tyyppi: Seminar
Organisaatio: iCAN Flagship Team
Yhteyshenkilö: ican-comms@helsinki.fi
Online-kokouslinkki:
https://helsinki.zoom.us/j/69887400500
kesäkuu
17
Dissertation: Jani Haukka
Jani Haukka, University of Helsinki, Faculty of Medicine, Doctoral Programme in Clinical Research
Genetic and metabolomic factors of type 1 diabetes and diabetic kidney disease
Opponent: Professor Marju Orho-Melander, University of LundAloitusaika: 17.06.2025 13:00
Lopetusaika: 17.06.2025 15:00
Kesto: 2 hours
Sijainti: Biomedicum1, lecture hall 2, Haartmaninkatu 8, 00290 Helsinki
Tyyppi: Dissertation
Organisaatio: UH, Faculty of Medicine
Yhteyshenkilö: jani.haukka@helsinki.fi
Online-kokouslinkki:
kesäkuu
18
Special seminar by Dr. Gabri van der Pluijm
Welcome to the special seminar by Dr. Gabri van der Pluijm
Title: Potentiating Immunotherapy of Urological Cancers with Oncolytic Viruses in ‘Near-Patient” Models
Dr. Gabri van der Pluijm is a Graduate in Molecular Cell Biology of the University of Leiden, with a PhD in Bone Biology from the University of Leiden.
After 10 years as post-doc at the National Institutes of Health (Bethesda, MD, USA) and the department of Endocrinology of Leiden University Medical Center (the Netherlands), he was appointed as staff scientist (Associate Professor) at the department of Urology and is now heading the Urology Research Laboratory at LUMC.
During his post-doctoral research and later as head of the Urology research lab, his group developed 2D and 3D co-culture models in vitro and preclinical/‘near-patient’ models for the study of the pathogenesis of tumor progression and treatment of urological cancers (prostate bladder and renal cancer) molecular imaging.
His group is engaged in the development of ‘near-patient’ tumor models, the identification of molecular and cellular mechanisms of prostate and bladder cancer progression, therapy resistance, drug repurposing and the application of oncolytic virotherapy for the treatment of urological malignancies.
Dr. van der Pluijm is a mentor for several PhD students and postdocs. He has served as a co-promotor on different PhD committees. He is tutor of Medical and Biomedical Science students.
References
van de Merbel AF, van der Horst G, van der Mark MH, Bots STF, van den Wollenberg DJM, de Ridder CMA, Stuurman D, Aalders T, Erkens-Schulz S, van Montfoort N, Karthaus WR, Mehra N, Smits M, Schalken JA, van Weerden WM, Hoeben RC, van der Pluijm G. Reovirus mutant jin-3 exhibits lytic and immune-stimulatory effects in preclinical human prostate cancer models. Cancer Gene Ther. 2022 Jun;29(6):793-802.
Bots STF, Kemp V, Cramer SJ, van den Wollenberg DJM, Hornsveld M, Lamfers MLM, van der Pluijm G, Hoeben RC. Nonhuman Primate Adenoviruses of the Human Adenovirus B Species Are Potent and Broadly Acting Oncolytic Vector Candidates. Hum Gene Ther. 2022 Mar;33(5-6):275-289.
van der Horst G, van de Merbel AF, Ruigrok E, van der Mark MH, Ploeg E, Appelman L, Tvingsholm S, Jäättelä M, van Uhm J, Kruithof-de Julio M, Thalmann GN, Pelger RCM, Bangma CH, Boormans JL, van der Pluijm G, Zwarthoff EC. Cationic amphiphilic drugs as potential anticancer therapy for bladder cancer. Mol Oncol. 2020 Dec;14(12):3121-3134.
van de Merbel AF, van der Horst G, van der Pluijm G. Patient-derived tumour models for personalized therapeutics in urological cancers. Nat Rev Urol. 2021 Jan;18(1):33-45.
Baart VM, van der Horst G, Deken MM, Bhairosingh SS, Schomann T, Sier VQ, van der Mark MH, Iamele L, de Jonge H, Resnati M, Mazar AP, Pelger RCM, van der Pluijm G, Kuppen PJK, Vahrmeijer AL, Sier CFM. A multimodal molecular imaging approach targeting urokinase plasminogen activator receptor for the diagnosis, resection and surveillance of urothelial cell carcinoma. Eur J Cancer. 2021 Mar;146:11-20.
van de Merbel AF, van Hooij O, van der Horst G, van Rijt-van de Westerlo CCM, van der Mark MH, Cheung H, Kroon J, Verhaegh GW, Tijhuis J, Wellink A, Maas P, Viëtor H, Schalken JA, van der Pluijm G. The Identification of Small Molecule Inhibitors That Reduce Invasion and Metastasis of Aggressive Cancers. Int J Mol Sci. 2021 Feb 8;22(4):1688.
Aloitusaika: 18.06.2025 09:00
Lopetusaika: 18.06.2025 10:00
Kesto:
Sijainti: Biomedicum 1, meeting room 8-9
Tyyppi: Seminar
Organisaatio: UH, Faculty of Medicine
Yhteyshenkilö: tatiana.kudling@helsinki.fi
Lisätiedot:
Online-kokouslinkki:
kesäkuu
18
Dissertation: Tatiana Kudling
Tatiana Kudling, University of Helsinki, Faculty of Medicine, Doctoral Programme in Clinical Research
Advancing cancer immunotherapy with armed oncolytic adenoviruses: translational and clinical perspectives
Opponent: Associate professor Gabriel van der Pluijm, University of Leiden, Leiden University Medical Center
Aloitusaika: 18.06.2025 13:00
Lopetusaika: 18.06.2025 15:00
Kesto: 2 hours
Sijainti: Biomedicum1, lecture hall 2, Haartmaninkatu 8, 00290 Helsinki
Tyyppi: Dissertation
Organisaatio: UH, Faculty of Medicine
Yhteyshenkilö: tatiana.kudling@helsinki.fi
Online-kokouslinkki:
https://video.helsinki.fi/unitube/live-stream.html?room=l43