Omics · study · 2026
ATHENA: Augmenting Therapeutic Effectiveness through Novel Analytics
Listed in NCBI GEO
With a yearly incidence of about 2500 new cases in Belgium, bladder cancer (BC) is a commonly-diagnosed cancer type.
Description
Furthermore, it is accompanied with high mortality rates, with ca. 70% of patients not surviving past five years (Richters et al., 2020). In order to reduce the risk of recurrence and progression, patients with non-muscle invasive bladder cancer (NMIBC) are monitored frequently, undergoing cystoscopy examination and cytology.
The costs accompanying these types of diagnostics are very high (Babjuk et al., 2019). Due to the high variability in BC development at the molecular level, it is hard to differentiate between patients who are more or less at risk for disease progression, simply based on clinical and pathological features. No accurate markers exist to differentiate between these patients in an early stage.
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Recently developed techniques based on next-generation sequencing have shown that there are different molecular subtypes of bladder cancer and that patients with different types also respond differently to treatment (Weinstein et al., 2014; Robertson et al., 2017; Lerner et al., 2016).
Project
ATHENA aims to set up a multicenter platform to integrate relevant data from patients with NMIBC. Information will include clinical and -omics data, both collected preserving the patients’ privacy. Through state-of-the-art machine learning processes, our researchers will be able to link disease outcome and treatment response to certain biomarkers, which can then be used to improve early diagnosis and personalized treatment strategies.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE327nnn/GSE327922 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE327922 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1452998 ncbi.nlm.nih.gov/bioproject/PRJNA1452998 ↗
project · from NCBI GEO
- PubMed 42141426 pubmed.ncbi.nlm.nih.gov/42141426 ↗
publication · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Cancer 75% · Disease 75% · Sequencing 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE327922 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:sequencing | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |