Jaana Oikkonen

This study maps the spatio-temporal DNA methylation patterns in ovarian cancer using longitudinal data from the DECIDER trial, showing early establishment of regulatory methylomes and their stability through treatment.

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.

The paper identifies nine transcriptional programs driving metastasis in ovarian cancer using multi-modal data from 350 tumor samples, highlighting intra-patient heterogeneity and therapeutic implications.

This study identifies molecular drivers of ctDNA variability in ovarian cancer by analyzing genomic and transcriptomic data from 118 patients, linking ctDNA levels to proliferation and immune activity.

SegmentQTL improves molQTL analysis in copy number-driven cancers by incorporating breakpoint information to reduce false discoveries and refine associations.

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.

GenomeSpy is a grammar-based visualization toolkit for genomic data analysis that enables interactive exploration of large datasets, demonstrated on ovarian cancer samples.

The paper identifies a stress-related transcriptional profile in ovarian cancer linked to chemotherapy resistance and poor survival, suggesting MEK1/2 inhibitors as a potential treatment.