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Layer 1 of 21 · Six shared core layers

CloneTrace Clonality and tumour evolution.

A tumour is rarely one uniform population of cells. It usually contains related subpopulations (subclones) that share some alterations and differ in others. CloneTrace is intended to describe what the available data suggest about that structure: which alterations appear to be carried by most tumour cells, and which may be present in only a fraction of them.

Why it's needed

What tumour subpopulations or evolutionary patterns may be represented in the available molecular evidence?

Context on whether an alteration of interest appears truncal or subclonal, with the sample and purity constraints stated.

What it draws on

2 of 8 evidence domains.

Molecular & genomicTumour biologyVariant allele fractions, copy-number profile and an estimate of tumour fraction from the selected testing pathway.

What it produces

Potentially relevant genomic findings and a structured summary of the clonality or evolutionary interpretation.

Describe the relationship between relevant alterations and patterns of clonal structure and evolution, where the data support that analysis.

Why it's essential

Layer 1 of 21.

Gives context to every other molecular layer. Whether a targetable alteration appears broadly shared or limited to a subpopulation is relevant when AccessMatch and ResistMap findings are weighed, and the baseline picture is what later updates are compared against.

1 · What it does

What CloneTrace does

A tumour is rarely one uniform population of cells. It usually contains related subpopulations (subclones) that share some alterations and differ in others. CloneTrace is intended to describe what the available data suggest about that structure: which alterations appear to be carried by most tumour cells, and which may be present in only a fraction of them.

2 · Scientific question

The question it addresses

What tumour subpopulations or evolutionary patterns may be represented in the available molecular evidence?

Intended function

Describe the relationship between relevant alterations and patterns of clonal structure and evolution, where the data support that analysis.

3 · Data inputs and required context

What it draws on

  • 01 Molecular & genomic
  • 02 Tumour biology

Variant allele fractions, copy-number profile and an estimate of tumour fraction from the selected testing pathway.

4 · Scientific basis

The science behind it

Scientific basis

In the field, clonality is usually estimated from each variant's allele fraction, corrected for tumour purity, ploidy and local copy number to give a cancer-cell fraction. Variants with similar fractions are then grouped into putative subclones. With several samples over time or space, phylogenetic relationships can be reconstructed; from a single sample, resolution is limited.

5 · Output and evidence sources

What it produces

Main output

Potentially relevant genomic findings and a structured summary of the clonality or evolutionary interpretation.

Output type

  • Computational inference. Estimated by analysis of available data rather than measured directly.

6 · Why it\u2019s essential

How it powers the Twin

Gives context to every other molecular layer. Whether a targetable alteration appears broadly shared or limited to a subpopulation is relevant when AccessMatch and ResistMap findings are weighed, and the baseline picture is what later updates are compared against.

Report section

Capability

Understand

Bring molecular findings and relevant clinical context into a structured view.

7 · Why it\u2019s needed

What it changes — for doctors, patients and researchers

Clinicians

Context on whether an alteration of interest appears truncal or subclonal, with the sample and purity constraints stated.

Doctor & Clinical Team

Patients & caregivers

Helps explain why a cancer can change over time, and why a single test is a snapshot rather than the whole story.

Patient & Caregiver

Researchers

A structured hypothesis about tumour evolution that can be compared against later samples.

Industry & Research

8 · Dependencies and limitations

Limitations

  • Longitudinal clone tracking cannot be claimed from a single baseline sample unless the methodology supports it.
  • Accuracy depends on tumour purity, sequencing depth and the breadth of the assay: a targeted panel offers fewer variants for clustering than whole-exome data.
  • A single biopsy may not capture spatial heterogeneity; plasma reflects only the tumour DNA that is shed into the blood.

9 · Review and uncertainty

How the output is handled

Output status

An AI-assisted analytical output presented as structured findings for clinician review. It becomes part of a report only after the treating oncologist has reviewed and signed it.

How uncertainty is communicated

Clonal assignments are expressed with qualifiers (for example, likely clonal or possibly subclonal), alongside the purity and coverage that limit them.

10 · Claim boundary

What this layer does not establish

It does not establish the complete clonal architecture of the tumour, and it does not predict how the tumour will evolve.

The treating oncologist owns every decision. Every Twin report is reviewed and signed by the treating oncologist, then taken to KPCIRC's Molecular Tumour Board.

KPCIRC sign-off process

Continue the journey

Longitudinal monitoring

Every change goes in.

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