Cancer signaling beyond the genes

Cancer is still largely interpreted through the lens of genetic mutations, which continues to shape most therapeutic strategies. Yet single cell analyses reveal limits to this view: phenotypic heterogeneity is pervasive even among genetically identical cancer cells, and many canonical driver mutations are also present in non-malignant tissues. These paradoxes can be reconciled by viewing cancer as a new tissue state characterized by aberrant cellular information processing, where mutations act as context-dependent modifiers of the signaling codes. We advance a framework in which input-specific signaling dynamics determine phenotypic outcomes, while oncogenic mutations bias and blur these dynamics rather than acting as simple "on-off" switches. In this view, therapeutic success depends on restoring the fidelity of dynamic signal encoding and decoding rather than merely inhibiting isolated pathway components.

Authors

Institutions

Publication Details

Journal
Current Opinion in Cell Biology
Published
2026-04-17
DOI
https://doi.org/10.1016/j.ceb.2026.102643
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cancer signaling beyond the genes

Andre Levchenko, Ralitsa Radostinova Madsen
Current Opinion in Cell Biology
Cancer Genomics and Diagnostics
article

Cancer signaling beyond the genes

Andre Levchenko, Ralitsa Radostinova Madsen
article en

Abstract

Cancer is still largely interpreted through the lens of genetic mutations, which continues to shape most therapeutic strategies. Yet single cell analyses reveal limits to this view: phenotypic heterogeneity is pervasive even among genetically identical cancer cells, and many canonical driver mutations are also present in non-malignant tissues. These paradoxes can be reconciled by viewing cancer as a new tissue state characterized by aberrant cellular information processing, where mutations act as context-dependent modifiers of the signaling codes. We advance a framework in which input-specific signaling dynamics determine phenotypic outcomes, while oncogenic mutations bias and blur these dynamics rather than acting as simple "on-off" switches. In this view, therapeutic success depends on restoring the fidelity of dynamic signal encoding and decoding rather than merely inhibiting isolated pathway components.

Current Opinion in Cell BiologyVol. 100
Yale University (US), MRC Protein Phosphorylation and Ubiquitylation Unit (GB), Systems Biology Institute (JP), University of Glasgow (GB)
National Science Foundation, UK Research and Innovation, National Institutes of Health
Openalex Percentile: Top 17%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.