Locus-specific LINE-1 expression in clinical ovarian cancer specimens at the single-cell level

Autor: Anna Perkiö, Barun Pradhan, Fatih Genc, Anna Pirttikoski, Sanna Pikkusaari, Erdogan Pekcan Erkan, Matias Marin Falco, Kaisa Huhtinen, Sara Narva, Johanna Hynninen, Liisa Kauppi, Anna Vähärautio

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)

Abstract Long interspersed nuclear elements (LINE-1s/L1s) are a group of retrotransposons that can copy themselves within a genome. In humans, it is the most successful transposon in nucleotide content. L1 expression is generally mild in normal human

Externí odkaz: https://doaj.org/article/7262afbd946940dbacc468c1107b3ada

Circulating Tumor Biomarkers in Meningiomas Reveal a Signature of Equilibrium Between Tumor Growth and Immune Modulation

Autor: Erdogan Pekcan Erkan, Thomas Ströbel, Christian Dorfer, Markus Sonntagbauer, Andreas Weinhäusel, Nurten Saydam, Okay Saydam

Publikováno v: Frontiers in Oncology, Vol 9 (2019)

Meningiomas are primary central nervous system (CNS) tumors that originate from the arachnoid cells of the meninges. Recurrence occurs in higher grade meningiomas and a small subset of Grade I meningiomas with benign histology. Currently, there are n

Externí odkaz: https://doaj.org/article/935e2e7ee9c04686a4441282268f3975

PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples

Autor: Olli Carpén, Katja Kaipio, Kaisa Huhtinen, Antti Häkkinen, Erdogan Pekcan Erkan, Noora Andersson, Naziha Mansuri, Sampsa Hautaniemi, Anna Vähärautio, Johanna Hynninen, Tarja Lamminen, Amjad Alkodsi, Rainer Lehtonen, Kaiyang Zhang, Jun Dai, Sakari Hietanen

Publikováno v: Bioinformatics

Motivation A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample comp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8bdc90ea0a8336db5a512e998ee118f7
https://doi.org/10.1093/bioinformatics/btab178

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

Autor: Krister Wennerberg, Anna Vähärautio, Liye He, Jaana Oikkonen, Antti Häkkinen, Sampsa Hautaniemi, Shuyu Zheng, Olli Carpén, Daria Bulanova, Erdogan Pekcan Erkan, Tero Aittokallio, Wenyu Wang, Titta Joutsiniemi, Kaiyang Zhang, Johanna Hynninen, Sakari Hietanen, Kaisa Huhtinen, Jing Tang

Publikováno v: He, L, Bulanova, D, Oikkonen, J, Häkkinen, A, Zhang, K, Zheng, S, Wang, W, Erkan, E P, Carpén, O, Joutsiniemi, T, Hietanen, S, Hynninen, J, Huhtinen, K, Hautaniemi, S, Vähärautio, A, Tang, J, Wennerberg, K & Aittokallio, T 2021, ' Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer ', Briefings in Bioinformatics, vol. 22, no. 6 . https://doi.org/10.1093/bib/bbab272
Briefings in Bioinformatics

Each patient’s cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoprot

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57447d3207204c3e89faac0491283adb
https://doi.org/10.1093/bib/bbab272

Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile with chemotherapy resistance

Autor: Jun Dai, Kaisa Huhtinen, Antti Häkkinen, Johanna Hynninen, Anna Vähärautio, Kaiyang Zhang, Olli Carpén, Katja Kaipio, Sampsa Hautaniemi, Sakari Hietanen, Jaana Oikkonen, Naziha Mansuri, Erdogan Pekcan Erkan, Tarja Lamminen, Noora Andersson

Chemotherapy resistance is the greatest contributor to cancer mortality and the most urgent unmet challenge in oncology. In order to reveal transcriptomics changes due to platinum-based chemotherapy we analyzed single-cell RNA-seq data from fresh tis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ba6ea84cec7ea7d16b48d7c70b0f98ad
https://doi.org/10.1101/2020.06.06.138362