Author

J. Oikkonen

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Cancer Biology· 7

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Organism:human· 7 Research Focus:differential expression· 5 Assay:bulk RNA-seq· 4 Research Focus:drug response / drug discovery· 4 Research Focus:gene regulatory network inference· 4 Approach:statistical model· 4 Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1

Frequent Co-Authors

J. Hynninen· 7 shared S. Hautaniemi· 7 shared Y. Li· 6 shared K. Lavikka· 5 shared A. Virtanen· 4 shared S. Hietanen· 4 shared A. Farkkila· 3 shared E. P. Erkan· 3 shared

Activity by Year

2021-2024 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

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7 shared papersCancer Biology

J. Hynninen

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7 papers

Recent·Most cited

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

D. Afenteva, R. Yu, A. Rajavuori, M. Salvadores, I.-M. Launonen, K. Lavikka, K. Zhang, G. Marchi, S. Jamalzadeh, V.-M. Isoviita, Y. Li, G. Micoli, E. P. Erkan, M. M. Falco, D. Ungureanu, , S. Hautaniemi

The paper identifies reduced IFN-I pathway activity as a driver of chemo-refractory ovarian cancer using multi-omics analysis in a clinical trial cohort.

bioRxiv · Mar 28, 2024Cancer Biology

Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

I.-M. P. Launonen, E. P. Erkan, I. Niemiec, A. Junquera, M. Hincapie-Otero, D. Afenteva, Z. Liang, M. Salko, A. Szabo, F. Perez-Villatoro, M. M. Falco, Y. Li, G. Micoli, A. Nagaraj, U.-M. Haltia, , A. Farkkila

This study shows chemotherapy causes myeloid-driven spatial T-cell exhaustion in ovarian cancer by altering immune cell states and interactions, suggesting new immunotherapy approaches.

bioRxiv · Mar 19, 2024 · PreprintCancer Biology

A synthetic lethal dependency on casein kinase 2 in response to replication-perturbing drugs in RB1-deficient ovarian and breast cancer cells

D. Bulanova, Y. Akimov, W. Senkowski, J. Oikkonen, L. Gall-Mas, S. Timonen, M. Elmadani, J. Hynninen, S. Hautaniemi, T. Aittokallio, K. Wennerberg

This study identifies CK2 inhibition as a sensitizing strategy for RB1-deficient ovarian and breast cancer cells to replication-perturbing drugs, showing enhanced efficacy when combined with existing therapies.

bioRxiv · Nov 14, 2022 · PreprintCancer Biology

L1 retrotransposition is regulated post-transcriptionally In High-Grade Serous Ovarian Cancer

B. Pradhan, K. Zhang, Y. Li, K. Lavikka, T. Muranen, K. Huhtinen, R. M. Badge, K. Burns, J. Hynninen, S. Hietanen, J. Oikkonen, S. Hautaniemi, L. Kauppi

The paper investigates L1 retrotransposition in HGSC, finding that despite high L1 mRNA expression, only a third of tumors show somatic insertions, with variability in retrotransposition frequency and patterns.

bioRxiv · Sep 27, 2022 · PreprintCancer Biology

Evolutionary states and trajectories characterized by distinct pathways stratify ovarian high-grade serous carcinoma patients

A. Lahtinen, K. Lavikka, Y. Li, A. Virtanen, S. Jamalzadeh, K. Huhtinen, O. Carpen, S. Hietanen, A. Häkkinen, J. Hynninen, J. Oikkonen, S. Hautaniemi

This study identifies three evolutionary states of ovarian high-grade serous carcinoma using whole-genome sequencing and links them to distinct therapeutic targets.

bioRxiv · Aug 30, 2022Cancer Biology

A platform for efficient establishment, expansion and drug response profiling of high-grade serous ovarian cancer organoids

W. Senkowski, L. Gall-Mas, M. M. Falco, Y. Li, K. Lavikka, M. C. Kriegbaum, J. Oikkonen, D. Bulanova, E. J. Pietras, K. Vossgröne, Y.-J. Chen, E. P. Erkan, M. K. Gronning Hog, I. M. Larsen, T. Lamminen, , K. Wennerberg

This paper describes a method to generate and expand high-grade serous ovarian cancer organoids with improved success rates and reports their drug response correlation with clinical outcomes.

bioRxiv · Apr 21, 2022Cancer Biology

Optimized detection of allelic imbalances specific for homologous recombination deficiency improves the prediction of clinical outcomes in cancer

F. Perez-Villatoro, J. Oikkonen, J. Casado, A. Chernenko, D. C. Gulhan, M. Tumiati, Y. Li, K. Lavikka, S. Hietanen, J. Hynninen, U.-M. Haltia, J. S. Tyrmi, H. Laivuori, P. Konstantinopoulos, S. Hautaniemi, , A. Farkkila

The paper develops a tumor-specific method to detect allelic imbalances for HRD prediction, showing improved clinical outcome prediction in ovarian and breast cancers.

bioRxiv · Aug 19, 2021Cancer Biology