In the Cancer Stress Biology research we study the molecular, cellular and tissue mechanisms that contribute to the increased ability of cancer cells to tolerate stress. We focus on the molecular mechanisms behind the different capacities of cancer and neuronal cells to deal with protein and RNA aggregates, and the ability of cancer cells to form resistance to drugs. We also query the cancer growth patterns in tissue combining this to molecular information in order to better understand the mechanisms behind cancer cells’ ability to survive in the crossfire of different stress types. In our tissue analysis collaboration projects we search for better ways to image, visualise and quantitatively analyse histology with development of digital pathology, machine learning and AI tools.
Understanding the molecular mechanisms behind detrimental tissue effects in disease are key to find more efficient treatments for patients. Better understanding of cellular stress responses enables identification of novel drug targets. If we can inhibit the increased ability of cancer cells to bypass toxic amounts of stress, we can identify ways to destroy cancer cells. On the other hand, by activating the stress responses in cells that are unable to buffer out toxic effects, we can prevent the damage on cells and tissues in diseases such as neurodegeneration.
Please visit our research group website:
https://sites.uef.fi/cancer-stress-biology-latonen/
Research groups
Publications
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A PEG-assisted membrane coating to prepare biomimetic mesoporous silicon for PET/CT imaging of triple-negative breast cancer
Wen, Huang; Martínez, María Gómez; Happonen, Emilia; Qian, Jing; Vallejo, Vanessa Gómez; Mendazona, Helena Jorge; Jokivarsi, Kimmo; Scaravilli, Mauro; Latonen, Leena; Llop, Jordi; Lehto, Vesa-Pekka; Xu, Wujun. 2024. International journal of pharmaceutics. 652: A1 Journal article (refereed), original research -
Long noncoding RNA EPCART regulates translation through PI3K/AKT/mTOR pathway and PDCD4 in prostate cancer
Kohvakka, Annika; Sattari, Mina; Nättinen, Janika; Aapola, Ulla; Gregorová, Pavlína; Tammela, Teuvo LJ; Uusitalo, Hannu; Sarin, L Peter; Visakorpi, Tapio; Latonen, Leena. 2024. Cancer gene therapy. 31: 1536-1546 A1 Journal article (refereed), original research -
Platinum-based drugs induce phenotypic alterations in nucleoli and Cajal bodies in prostate cancer cells
Batnasan, Enkhzaya; Kärkkäinen, Minttu; Koivukoski, Sonja; Sadeesh, Nithin; Tollis, Sylvain; Ruusuvuori, Pekka; Scaravilli, Mauro; Latonen, Leena. 2024. Cancer cell international. 24: . 29 A1 Journal article (refereed), original research -
RNA:han sitoutuvat proteiinit syövän lääkehoidossa ja -resistenssissä
Latonen, Leena. 2024. Duodecim. 140: 281-287 A2 Review article, Literature review, Systematic review -
Single cell and spatial transcriptomics highlight the interaction of club-like cells with immunosuppressive myeloid cells in prostate cancer
Kiviaho, Antti; Eerola, Sini K.; Kallio, Heini M. L.; Andersen, Maria K.; Hoikka, Miina; Tiihonen, Aliisa M.; Salonen, Iida; Spotbeen, Xander; Giesen, Alexander; Parker, Charles T. A.; Taavitsainen, Sinja; Hantula, Olli; Marttinen, Mikael; Hermelo, Ismaïl; Ismail, Mazlina; Midtbust, Elise; Wess, Maximilian; Devlies, Wout; Sharma, Abhibhav; Krossa, Sebastian; Häkkinen, Tomi; Afyounian, Ebrahim; Vandereyken, Katy; Kint, Sam; Kesseli, Juha; Tolonen, Teemu; Tammela, Teuvo L. J.; Viset, Trond; Størke. 2024. Nature communications. 15: . 9949 A1 Journal article (refereed), original research -
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Weitz, Philippe; Valkonen, Masi; Solorzano, Leslie; Carr, Circe; Kartasalo, Kimmo; Boissin, Constance; Koivukoski, Sonja; Kuusela, Aino; Rasic, Dusan; Feng, Yanbo; Pouplier, Sandra Sinius; Sharma, Abhinav; Eriksson, Kajsa Ledesma; Robertson, Stephanie; Marzahl, Christian; Gatenbee, Chandler D; Anderson, Alexander RA; Wodzinski, Marek; Jurgas, Artur; Marini, Niccolò; Atzori, Manfredo; Müller, Henning; Budelmann, Daniel; Weiss, Nick; Heldmann, Stefan; Lotz, Johannes; Wolterink, Jelmer M; De Santi,. 2024. Medical image analysis. 97: A1 Journal article (refereed), original research -
Virtuaalimaailma histologian oppimisen tukena
Mairinoja, Laura; Liimatainen, Kaisa; Koivukoski, Sonja; Latonen, Leena; Strauss, Leena; Ruusuvuori, Pekka. 2024. Yliopistopedagogiikka. 31: . B1 Non-refereed journal articles -
Virtuaalivärjäys mahdollistaa ympäristöystävällisempää histologiaa kemikaaleja vähentämällä
Koivukoski, Sonja; Ruusuvuori, Pekka; Latonen, Leena. 2024. Duodecim. 140: 1071-1078 A2 Review article, Literature review, Systematic review -
Virtual staining for histology by deep learning
Latonen, Leena; Koivukoski, Sonja; Khan, Umair; Ruusuvuori, Pekka. 2024. Trends in biotechnology. 42: 1177-1191 A2 Review article, Literature review, Systematic review -
A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics
Weitz, Philippe; Valkonen, Masi; Solorzano, Leslie; Carr, Circe; Kartasalo, Kimmo; Boissin, Constance; Koivukoski, Sonja; Kuusela, Aino; Rasic, Dusan; Feng, Yanbo; Sinius Pouplier, Sandra; Sharma, Abhinav; Ledesma Eriksson, Kajsa; Latonen, Leena; Laenkholm, Anne-Vibeke; Hartman, Johan; Ruusuvuori, Pekka; Rantalainen, Mattias. 2023. Scientific data. 10: . 562 A1 Journal article (refereed), original research