Hercules Project


Raivola J, Dini A, Karvonen H, Piki E, Salokas K, Niininen W, Kaleva L, Zhang K, Arjama M, Gudoityte G, Seashore-Ludlow B, Varjosalo M, Kallioniemi O, Hautaniemi S, Murumägi A, Ungureanu D.
Multiomics characterization implicates PTK7 in ovarian cancer EMT and cell plasticity and offers strategies for therapeutic intervention.
Cell Death and Disease. 2022, 13:714. Open access.

Carroll MJ, Kaipio K, Hynninen J, Carpén O, Hautaniemi S, Page D, Kreeger PK.
A Subset of Secreted Proteins in Ascites Can Predict Platinum-Free Interval in Ovarian Cancer.
Cancers. 2022, 14(17), 4291. Open access.

Firoozbakht F, Yousefi B, Schwikowski B.
An overview of machine learning methods for monotherapy drug response prediction.
Briefings in Bioinformatics. 2022, 23(1), 1–18. Open access.

Holmström S, Hautaniemi S, Häkkinen A.
POIBM: Batch correction of heterogeneous RNA-seq datasets through latent sample matching.
Bioinformatics. 2022, btac124. Open access.

Zhang K, Erkan EP, Jamalzadeh S, Dai J, Andersson N, Kaipio K, Lamminen T, Mansuri N, Huhtinen K, Carpén O, Hietanen S, Oikkonen J, Hynninen J, Virtanen A, Häkkinen A, Hautaniemi S, Vähärautio A.
Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer.
Science Advances. 2022, 8, eabm1831. Open access.

Jamalzadeh S, Häkkinen A, Andersson N, Huhtinen K, Laury A, Hietanen S, Hynninen J, Oikkonen J, Carpén O, Virtanen A, Hautaniemi S.
QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability.
Laboratory Investigation. 2022. Open access.

Laury A, Blom S, Ropponen T, Virtanen A, Carpén O.
Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.
Nature Scientific Reports. 2021, 11:19165. Open access.

Hippen AA, Falco MM, Weber LM, Erkan EP, Zhang K, Doherty JA, Vaharautio A, Greene CS, Hicks SC.
miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data.
PLoS Comput Biol. 2021, 17(8):e1009290. Open access.

Azzalini E, Abdurakhmanova N, Parisse P, Bartoletti M, Canzonieri V, Stanta G, Casalis L, Bonin S.
Cell-stiffness and morphological architectural patterns in clinical samples of high grade serous ovarian cancers.
Nanomedicine. 2021, 37:102452. Open access.

He L, Bulanova D, Oikkonen J, Hakkinen A, Zhang K, Zheng S, Wang W, Erkan EP, Carpen O, Joutsiniemi T, Hietanen S, Hynninen J, Huhtinen K, Hautaniemi S, Vaharautio A, Tang J, Wennerberg K, Aittokallio T.
Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer.
Briefings in Bioinformatics, 2021, bbab272. Open access.

Sahu B, Pihlajamaa P, Zhang K, Palin K, Ahonen S, Cervera A, Ristimaki A, Aaltonen LA, Hautaniemi S, Taipale J.
Human cell transformation by combined lineage conversion and oncogene expression.
Oncogene, 2021. Open access.

Pietila EA, Gonzalez-Molina J, Moyano-Galceran L, Jamalzadeh S, Zhang Z, Lehtinen L, Turunen SP, Martins TA, Gultekin O, Lamminen T, Kaipio K, Joneborg U, Hynninen H, Hietanen H, Grenman S, Lehtonen R, Hautaniemi S, Carpen O, Carlson JW, Lehti K.
Co-evolution of matrisome and adaptive adhesion dynamics drives ovarian cancer chemoresistance.
Nature Communications. 2021, 12:3904. Open access.

Jukonen J, Moyano-Galceran L, Hopfner K, Pietila EA, Lehtinen L, Huhtinen K, Gucciardo E, Hynninen J, Hietanen S, Grenman S, Ojala PM, Carpen O, Lehti K.
Aggressive and recurrent ovarian cancers upregulate ephrinA5, a non-canonical effector of EphA2 signaling duality.
Scientific Reports, 2021, 11:8856. Open access.

Cervera A, Rausio H, Kahkonen T, Andersson N, Partel G, Rantanen V, Paciello G, Ficarra E, Hynninen J, Hietanen S, Carpen Olli, Lehtonen R, Hautaniemi S, Huhtinen K.
FUNGI: FUsioN Gene Integration toolset.
Bioinformatics, 2021, btab206. Online publication before print. Open access.

Hakkinen A, Zhang K, Alkodsi A, Andersson N, Pekcan Erkan E, Dai J, Kaipio K, Lamminen T, Mansuri N, Huhtinen K, Vaharautio A, Carpen O, Hynninen J, Hietanen S, Lehtonen R, Hautaniemi S.
PRISM: Recovering cell type specific expression profiles from individual composite RNA-seq samples.
Bioinformatics. 2021, btab178. Online publication before print. Open access.

Iyer S, Zhang S, Yucel S, Horn H, Smith SG, Reinhardt F, Hoefsmit E, Assatova B, Casado J, Meinsohn MC, Barrasa MI, Bell GW, Perez-Villatoro F, Huhtinen K, Hynninen J, Oikkonen J, Galhenage PM, Pathania S, Hammond PT, Neel BG, Farkkila A, Pepin D, Weinberg RA.
Genetically defined syngeneic mouse models of ovarian cancer as tools for the discovery of combination immunotherapy.
Cancer Discovery, 2021 11(2):384-407. Open access.

Casado J, Lehtonen O, Rantanen V, Kaipio K, Pasquini L, Hakkinen A, Petrucci E, Hynninen J, Hietanen S, Carpen O, Biffoni M, Farkkila A, Hautaniemi S.
Agile workflow for interactive analysis of mass cytometry data.
Bioinformatics. 37(9):1263-1268. Open access.

Salminen L, Gidwani K, Grenman S, Carpen O, Hietanen S, Pettersson K, Huhtinen K Hynninen J.
HE4 in the evaluation of tumor load and prognostic stratification of high grade serous ovarian carcinoma.
Acta Oncologica, 2020, 59:12, 1461-1468. Open access.

Laasik M, Hynninen J, Forsback S, Noponen T, Seppanen M, Hietanen S.
The feasibility of [18F]EF5-PET/CT to image hypoxia in ovarian tumors: a clinical study.
EJNMMI Research, 2020, 10, 103. Open access.

Salminen L, Nadeem N, Jain S, Grenman S, Carpen O, Hietanen S, Oksa S, Lamminmaki U, Pettersson K, Gidwani K, Huhtinen K, Hynninen J.
A longitudinal analysis of CA125 glycoforms in the monitoring and follow up of high grade serous ovarian cancer.
Gynecol Oncol. 2020, 156(3):689-694. Open access.

Balduit A, Agostinis C, Mangogna A, Maggi V, Zito G, Romano F, Romano A, Ceccherini R, Grassi G, Bonin S, Bonazza D, Zanconati F, Ricci G, Bulla R.
The Extracellular matrix influences ovarian carcinoma cells' sensitivity to cisplatinum: A first step towards personalized medicine.
Cancers (Basel). 2020, 12(5):1175. Open access.

Hakkinen A, Koiranen J, Casado J, Kaipio K, Lehtonen O, Petrucci E, Hynninen J, Hietanen S, Carpen O, Pasquini L, Biffoni M, Lehtonen R, Hautaniemi S.
qSNE: Quadratic rate t-SNE optimizer with automatic parameter tuning for large data sets.
Bioinformatics, 2020. Online publication before print. Open access.

Akimov Y, Bulanova D, Timonen S, Wennerberg K, Aittokallio T.
Improved detection of differentially represented DNA barcodes for high-throughput clonal phenomics.
Molecular Systems Biology, 2020, 16:e9195. Open access.

Kaipio K, Chen P, Roering P, Huhtinen K, Mikkonen P, Ostling P, Lehtinen L, Mansuri N, Korpela T, Potdar S, Hynninen J, Auranen A, Grenman S, Wennerberg K, Hautaniemi S, Carpen O.
ALDH1A1-related stemness in high-grade serous ovarian cancer is a negative prognostic indicator but potentially targetable by EGFR/mTOR-PI3K/aurora kinase inhibitors.
Journal of Pathology, 2020, 250(2):159-169.

Azzalini E, De Martino E, Fattorini P, Canzonieri V, Stanta G, Bonin S.
Reliability of miRNA Analysis from Fixed and Paraffin-Embedded Tissues.
International Journal of Molecular Sciences. 2019;20(19):4819. Open access.

Laasik M, Kemppainen J, Auranen A, Hietanen S, Grenman S, Seppanen M, Hynninen J.
Behavior of FDG-avid supradiaphragmatic lymph nodes in PET/CT throughout primary therapy in advanced serous epithelial ovarian cancer: a prospective study.
Cancer Imaging, 2019, 29;19(1):27. Open access.

Kozlowska E, Vallius T, Hynninen J, Hietanen S, Farkkila A, Hautaniemi S.
Virtual clinical trials identify effective combination therapies in ovarian cancer.
Science Reports, 2019, 9(1):18678. Open access.

Isoviita V-M, Salminen L, Azar J, Lehtonen R, Roering P, Carpen O, Hietanen S, Grenman S, Hynninen J, Farkkila A, Hautaniemi S.
Open source infrastructure for healthcare data integration and machine learning analyses.
JCO Clinical Cancer Informatics, 2019, 3:1-16. Author manuscript can be downloaded from here.

Oikkonen J, Zhang K, Salminen L, Schulman I, Lavikka K, Andersson N, Ojanpera E, Hietanen S, Grenman S, Lehtonen R, Huhtinen K, Carpen O, Hynninen J, Farkkila A, Hautaniemi S.
Prospective longitudinal ctDNA workflow reveals clinically actionable alterations in ovarian cancer.
JCO Precision Oncology, 2019, 3:1-12. Open access.

Cervera A, Rantanen V, Ovaska K, Laakso M, Nunez-Fontarnau J, Alkodsi A, Casado J, Facciotto C, Hakkinen A, Louhimo R, Karinen S, Zhang K, Lavikka K, Lyly L, Pal Singh M, Hautaniemi S.
Anduril 2: Upgraded large-scale data integration framework.
Bioinformatics, 2019, pii: btz133, Epub ahead of print. Author manuscript can be downloaded from here.

Tumiati M, Hietanen S, Hynninen J, Pietila E, Farkkila A, Kaipio K, Roering P, Huhtinen K, Alkodsi A, Li Y, Lehtonen R, Erkan EP, Tuominen MM, Lehti K, Hautaniemi SK, Vaharautio A, Grenman S, Carpen O, Kauppi L.
A Functional homologous recombination assay predicts primary chemotherapy response and long-term survival in ovarian cancer patients.
Clinical Cancer Research, 2018, 24(18):4482-4493. Open access.

Hynninen J, Laasik M, Vallius T, Kemppainen J, Gronroos S, Virtanen J, Casado J, Hautaniemi S, Grenman S, Seppanen M, Auranen A.
Clinical value of 18 F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in response evaluation after primary treatment of advanced epithelial ovarian cancer.
Clinical Oncology, 2018, 30(8):507-514. Open access.

Kozlowska E, Farkkila A, Vallius T, Carpen O, Kemppainen J, Grenman S, Lehtonen R, Hynninen J, Hietanen S, Hautaniemi S.
Mathematical modeling predicts response to chemotherapy and drug combinations in ovarian cancer.
Cancer Research, 2018, 78(14):4036-4044. Author manuscript can be downloaded from here.

Hakkinen A, Alkodsi A, Facciotto C, Zhang K, Kaipio K, Leppa S, Carpen O, Grenman S, Hynninen J, Hietanen S, Lehtonen R, Hautaniemi S.
Identifying differentially methylated sites in samples with varying tumor purity
Bioinformatics, 2018, 34(18):3078-3085. Link to pre-print in BiorXivs.

Nikolayeva I, Guitart Pla O, Schwikowski B.
Network module identification - A widespread theoretical bias and best practices
Methods. 2017 Sep 21. pii: S1046-2023(17)30037-3. Open access.

Doctoral theses

Facciotto, C. In vitro and in silico methods to investigate and overcome drug resistance in cancer. University of Helsinki, 2021.

Casado, J. Proteogenomics methods for translational cancer research. University of Helsinki, 2021.

Azzalini, E. Comprehensive characterization and effective combinatorial targeting of high-grade serous ovarian cancer via single-cell analysis. Universita degli Studi di Trieste, 2020.

Cervera Taboada, A. Transcriptomics analysis and its applications in cancer. University of Helsinki, 2020.

Salminen, L. Clinical application of novel circulatory biomarkers in epithelial ovarian cancer. University of Turku, 2020.