Circulating tumor DNA (ctDNA) in precision oncology of ovarian cancer

Non peer reviewe

PerPAS: Topology-Based Single Sample Pathway Analysis Method

Identification of intracellular pathways that play key roles in cancer progression and drug resistance is a prerequisite for developing targeted cancer treatments. The era of personalized medicine calls for computational methods that can function with one sample or very small set of samples. Developing such methods is challenging because standard statistical approaches pose several limiting assumptions, such as number of samples, that prevent their application when n approaches to one. We have developed a novel pathway analysis method called PerPAS to estimate pathway activity at a single sample level by integrating pathway topology and transcriptomics data. In addition, PerPAS is able to identify altered pathways between cancer and control samples as well as to identify key nodes that contribute to the pathway activity. In our case study using breast cancer data, we show that PerPAS can identify highly altered pathways that are associated with patient survival. PerPAS identified four pathways that were associated with patient survival and were successfully validated in three independent breast cancer cohorts. In comparison to two other pathway analysis methods that function at a single sample level, PerPAS had superior performance in both synthetic and breast cancer expression datasets. PerPAS is a free R package (http://csbi.ltdk.helsinki.fi/pub/czliu/perpas/).Peer reviewe

POIBM : batch correction of heterogeneous RNA-seq datasets through latent sample matching

Motivation: RNA sequencing and other high-throughput technologies are essential in understanding complex diseases, such as cancers, but are susceptible to technical factors manifesting as patterns in the measurements. These batch patterns hinder the discovery of biologically relevant patterns. Unbiased batch effect correction in heterogeneous populations currently requires special experimental designs or phenotypic labels, which are not readily available for patient samples in existing datasets. Results: We present POIBM, an RNA-seq batch correction method, which learns virtual reference samples directly from the data. We use a breast cancer cell line dataset to show that POIBM exceeds or matches the performance of previous methods, while being blind to the phenotypes. Further, we analyze The Cancer Genome Atlas RNA-seq data to show that batch effects plague many cancer types; POIBM effectively discovers the true replicates in stomach adenocarcinoma; and integrating the corrected data in endometrial carcinoma improves cancer subtyping.Peer reviewe

Syöpäsolujen lääkeresistenssi ja miten se voitetaan - valokeilassa munasarjasyöpä

Vertaisarvioitu.Lääkeresistenssi on yksi suurimmista haasteista syövän hoidossa. Solunsalpaajat sekä immunologiset ja kohdennetut lääkehoidot menettävät usein tehoaan sairauden edetessä, eikä osa kasvaimista reagoi lääkehoitoon edes diagnoosivaiheessa. Lisäksi yhdelle lääkkeelle vastustuskykyinen kasvain on tyypillisesti vastustuskykyinen useille lääkkeille. Platinayhdisteet ovat yleisesti onkologiassa käytettyjä solunsalpaajia ja kuuluvat usean levinneen syövän, kuten munasarjasyövän, ensilinjan hoitoon. Vaste platinahoitoon on usein aluksi erittäin hyvä mutta heikkenee hoitosyklien aikana. Kehittyvä platinaresistenssi on todellinen ongelma potilaiden hoidossa, eikä platinaresistentille syöpäpotilaalle ole välttämättä mahdollista löytää seuraavaa tehoavaa lääkehoitoa. Tutkimuksessamme keskitymme platinan resistenssimekanismeihin munasarjasyövän yhteydessä. Tavoitteenamme on löytää platinan rinnalle tehokkaita lääkeyhdistelmiä, joita voidaan hyödyntää taudin uusiutuessa.Peer reviewe

Syöpäsolujen lääkeresistenssi ja miten se voitetaan - valokeilassa munasarjasyöpä

Lääkeresistenssi on yksi suurimmista haasteista syövän hoidossa. Solunsalpaajat sekä immunologiset ja kohdennetut lääkehoidot menettävät usein tehoaan sairauden edetessä, eikä osa kasvaimista reagoi lääkehoitoon edes diagnoosivaiheessa. Lisäksi yhdelle lääkkeelle vastustuskykyinen kasvain on tyypillisesti vastustuskykyinen useille lääkkeille. Platinayhdisteet ovat yleisesti onkologiassa käytettyjä solunsalpaajia ja kuuluvat usean levinneen syövän, kuten munasarjasyövän, ensilinjan hoitoon. Vaste platinahoitoon on usein aluksi erittäin hyvä mutta heikkenee hoitosyklien aikana. Kehittyvä platinaresistenssi on todellinen ongelma potilaiden hoidossa, eikä platinaresistentille syöpäpotilaalle ole välttämättä mahdollista löytää seuraavaa tehoavaa lääkehoitoa. Tutkimuksessamme keskitymme platinan resistenssimekanismeihin munasarjasyövän yhteydessä. Tavoitteenamme on löytää platinan rinnalle tehokkaita lääkeyhdistelmiä, joita voidaan hyödyntää taudin uusiutuessa

Fast Gene Ontology based clustering for microarray experiments

Peer reviewe

Editorial : Multi-omic Data Integration in Oncology

Non peer reviewe

Virtual clinical trials identify effective combination therapies in ovarian cancer

A major issue in oncology is the high failure rate of translating preclinical results in successful clinical trials. Using a virtual clinical trial simulations approach, we present a mathematical framework to estimate the added value of combinatorial treatments in ovarian cancer. This approach was applied to identify effective targeted therapies that can be combined with the platinum-taxane regimen and overcome platinum resistance in high-grade serous ovarian cancer. We modeled and evaluated the effectiveness of three drugs that target the main platinum resistance mechanisms, which have shown promising efficacy in vitro, in vivo, and early clinical trials. Our results show that drugs resensitizing chemoresistant cells are superior to those aimed at triggering apoptosis or increasing the bioavailability of platinum. Our results further show that the benefit of using biomarker stratification in clinical trials is dependent on the efficacy of the drug and tumor composition. The mathematical framework presented herein is suitable for systematically testing various drug combinations and clinical trial designs in solid cancers.Peer reviewe

Kinase Inhibitors in the Treatment of Ovarian Cancer: Current State and Future Promises

Ovarian cancer is the deadliest gynecological cancer, the high-grade serous ovarian carcinoma (HGSC) being its most common and most aggressive form. Despite the latest therapeutical advancements following the introduction of vascular endothelial growth factor receptor (VEGFR) targeting angiogenesis inhibitors and poly-ADP-ribose-polymerase (PARP) inhibitors to supplement the standard platinum- and taxane-based chemotherapy, the expected overall survival of HGSC patients has not improved significantly from the five-year rate of 42%. This calls for the development and testing of more efficient treatment options. Many oncogenic kinase-signaling pathways are dysregulated in HGSC. Since small-molecule kinase inhibitors have revolutionized the treatment of many solid cancers due to the generality of the increased activation of protein kinases in carcinomas, it is reasonable to evaluate their potential against HGSC. Here, we present the latest concluded and on-going clinical trials on kinase inhibitors in HGSC, as well as the recent work concerning ovarian cancer patient organoids and xenograft models. We discuss the potential of kinase inhibitors as personalized treatments, which would require comprehensive assessment of the biological mechanisms underlying tumor spread and chemoresistance in individual patients, and their connection to tumor genome and transcriptome to establish identifiable subgroups of patients who are most likely to benefit from a given therapy