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Concept

Expression-Based Prognostic Signatures

5 studiesEvidence last moved Sep 20, 2026

An expression-based prognostic signature is a set of genes whose measured activity is used to predict how a patient's disease will progress. Almost all of them are discovered by mining public expression repositories, which shapes both what they can find and what they can show.

These studies are numerous and easy to produce, and they all end with a survival curve that separates. The question a reader has to ask is whether the separation was discovered or constructed, because the same pipeline — pick genes correlated with outcome, then test that they correlate with outcome — produces a good-looking curve from data with no signal in it.

Studies

5

Findings

4

5 supporting · 0 challenging · 0 qualifying citations

Open tensions

1

Latest change

Concept page published

Expression-Based Prognostic Signatures

Currently

What we know

  1. Both markers track immune infiltration, which is what a single-gene score is often measuring.
  2. The gain came from the combination, which is a stronger claim than a single panel performing well.
  3. Independence from clinical variables is the test that distinguishes a signature from a restatement of stage.
  4. A reversible marker that moves with recovery is a different and harder thing to build than a survival score.

Largest unresolved question

What counts as validation differs sharply across this literature. The immune aging clocks report internal and external validation on independent data, while the single-gene cancer markers are assessed within the same public repositories used to select them — so the reported AUCs and hazard ratios are not measuring the same property.

Common misconceptions

  • A gene that separates survival curves is a driver of the disease.

    Both single-gene markers here correlate strongly with immune infiltration — ITGAL with CD8 T cells at rho = 0.732 and lower tumour purity. A gene expressed by infiltrating immune cells will track outcome without the tumour cells expressing it at all.

  • A high AUC means the signature is ready for clinical use.

    Discrimination measured in the dataset that selected the genes is an upper bound, not an estimate. The studies here that report external validation on independent data are doing a different and harder thing than those reporting performance in the discovery repository.

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