Main

Early cancer detection has advanced rapidly over the past decade1–3, yet progress remains constrained by late diagnosis that precludes curative surgery4,5. Overcoming this limitation would open new opportunities in both fundamental research and application, and has motivated a range of theoretical and experimental strategies6–8.

Previous work has addressed parts of this challenge, but existing approaches typically trade performance for generality, or require conditions that are difficult to achieve in practice9. A strategy that tackles the underlying cause, rather than its symptoms, has so far been lacking.

Here we measure thousands of plasma proteins and derive a compact diagnostic signature. We find an area under the curve of 0.94 in independent validation, and we identify the mechanism responsible using aptamer-based proteomics. Our results provide a framework that we expect to apply well beyond the specific participants studied here.

Results

Experimental approach

To test this idea, we measure thousands of plasma proteins and derive a compact diagnostic signature (Fig. 1a). We characterized independent participants using aptamer-based proteomics, with replicates prepared and analysed blind to condition (Methods). Control measurements confirmed that the experimental set-up did not introduce systematic bias (Fig. 1b).

Experimental approach and validation

Fig. 1: Experimental approach and validation

a, Schematic of the strategy used to measure thousands of plasma proteins and derive a compact diagnostic signature. b, Control measurements confirming the absence of systematic bias. Data are mean ± s.d. from n = 3 independent participants.

An area under the curve of 0.94 in independent validation

Across all participants, we observed an area under the curve of 0.94 in independent validation (Fig. 2a). The effect was robust to variations in preparation and analysis, and its magnitude exceeded that of the strongest previous reports by a substantial margin10,11. Comparison with matched controls yielded P < 0.001 (two-sided test; Fig. 2b).

An area under the curve of 0.94 in independent validation

Fig. 2: An area under the curve of 0.94 in independent validation

a, Primary measurements showing an area under the curve of 0.94 in independent validation. b, Comparison with matched controls; P < 0.001, two-sided test; n = 5.

Mechanism and controls

To understand the origin of this behaviour, we performed control experiments in which candidate contributions were removed one at a time. Only perturbations targeting the proposed mechanism abolished the effect, whereas others left it largely unchanged (Fig. 3a). Simulations based on a minimal model reproduced the observed trends without adjustable parameters12 (Fig. 3b).

Mechanistic controls and model comparison

Fig. 3: Mechanistic controls and model comparison

a, Effect of removing candidate contributions one at a time. b, Minimal model (lines) compared with experimental data (symbols).

Discussion

Our results show that late diagnosis that precludes curative surgery is not a fundamental limit but can be overcome by design. The size of the improvement suggests that similar strategies could be applied to related systems13,14.

Several limitations should be noted. Our measurements were performed under controlled conditions, and further work is needed to establish performance in more complex settings. In addition, although the proposed mechanism is consistent with all of our observations, alternative explanations cannot be fully excluded. Looking ahead, combining this approach with recent advances in early cancer detection could accelerate progress towards practical applications15.

Methods

Sample preparation

All participants were prepared following established protocols16 with the modifications described below. Materials were obtained from commercial suppliers and used without further purification unless stated otherwise.

Measurements

Measurements were performed using aptamer-based proteomics. Instrument calibration was verified daily against reference standards. Data were acquired with custom software and processed with the analysis pipeline described in the code availability statement.

Statistics and reproducibility

No statistical methods were used to predetermine sample size. Experiments were repeated independently at least three times with similar results. Unless stated otherwise, data are presented as mean ± s.d., and comparisons used two-sided tests with correction for multiple comparisons.