Trans-omic approach to colorectal cancer: an integrative computational and clinical perspective
Auf einen Blick
- Projektleiter/in : Dr. Maria Anisimova
- Projektteam : Inbar Leaf, Max Verbiest, Huifang You
- Projektvolumen : CHF 2'900'000
- Projektstatus : laufend
- Drittmittelgeber : SNF (Sinergia / Projekt Nr. 193832)
- Projektpartner : IBM Research GmbH, Universität Bern, Eidgenössische Technische Hochschule Zürich ETH
- Kontaktperson : Maria Anisimova
Beschreibung
Colorectal Cancer (CRC) is an important cause of cancer-related
mortality world-wide. The Consensus Molecular Subtypes represent
the first comprehensive molecular classification with clinical
implications, but many aspects are still missing. We use a
transomic approach to improve the stratification, prognosis, and
treatment prediction of CRC patients.
What is the novelty of the proposed approach?
Precision medicine is a reality in some tumor types, yet this
cannot be said for CRC, where predictive biomarkers are scarce and
are more effective at identifying non-responders than patients who
may benefit from treatment. Here, we aim to provide insights into
CRC and therapy responsiveness by combining different omics
approaches, such as genomics, histomics, and
pharmacogenomics, and integrating these by means of an AI-driven
multimodal classifier. To improve the current understanding of the
molecular basis of CRC we work on characterizing the relationship
between morphology and molecular cancer variants in genotype,
transcriptome, proteome and single-cell image data. In particular,
variations in short tandem repeats of human genomes are associated
with gene expression changes in samples from CRC patients. Here, we
will systematically search for tandem repeat variations in tumors,
annotating and cataloguing those variants that lead to
tumorigenesis of colorectal cancer.
Weiterführende Informationen
Publikationen
-
Nguyen, Huu-Giao; Lundström, Oxana; Blank, Annika; Dawson, Heather; Lugli, Alessandro; Anisimova, Maria; Zlobec, Inti,
2021.
Modern Pathology.
35, S. 240-248.
Verfügbar unter: https://doi.org/10.1038/s41379-021-00894-8
-
Delucchi, Matteo; Näf, Paulina; Bliven, Spencer; Anisimova, Maria,
2021.
Frontiers in Bioinformatics.
1(691865).
Verfügbar unter: https://doi.org/10.3389/fbinf.2021.691865
-
Verbiest, Max; Delucchi, Matteo; Bilgin Sonay, Tugce; Anisimova, Maria,
2021.
Frontiers in Bioinformatics.
1(685844).
Verfügbar unter: https://doi.org/10.3389/fbinf.2021.685844