Heterogeneity

Instead of hitting a tumour with the maximum dose until it stops working, adjust the dose to keep the tumour small and let drug-sensitive cells suppress resistant ones. Test this properly across several cancers.

When patients who agreed in advance die of cancer, sampling every tumour within hours reveals how the disease evolved and escaped every drug. Few hospitals can do this today.

When a scan shows most tumours shrinking but one growing, that odd lesion holds the escape mechanism. Sampling it, and treating it locally, should be routine.

Resistant cancer cells can become dependent on the drug they resisted, as shown for BRAF-inhibitor-resistant melanoma in mice. Stopping the drug for a defined washout and then rechallenging, while tracking the resistance allele in blood tumour DNA, could make the tumour vulnerable to it once more.

Brain tumours release little DNA into blood because of the blood-brain barrier. Sonobiopsy briefly opens the barrier with focused ultrasound and microbubbles, raising circulating tumour DNA severalfold so a blood sample can replace repeat surgical biopsy for diagnosis and resistance monitoring in glioma and brain metastases.

Personal cancer vaccines target a list of mutations, some present in only part of the tumour, so the tumour can escape by losing them. Restricting vaccines and T-cell products to clonal mutations shared by every tumour cell, identified by multi-region sequencing, should close that escape route.

Some tumours change fast and escape drugs quickly; others are stable. A single validated score for how evolvable a tumour is would tell doctors how aggressively to combine treatments.

When a tumour evolves resistance to one drug, it sometimes becomes weaker against another. Map these trade-offs systematically so doctors can pick the next drug to exploit them.

Aggressive glioblastomas, sarcomas and gastric cancers keep amplified cancer genes such as EGFR, MYC, MDM2 and CDK4 on free-floating DNA circles (ecDNA) whose copy number rises and falls quickly, letting the tumour dial resistance up and down. Cells carrying ecDNA depend on CHK1, giving a first drug target.

Tag every cell in a patient's lab-grown tumour with a unique DNA label, give it a drug, and read the labels to see which cells survive. This predicts which resistant clone will emerge.

Blood tests can already detect tumour DNA. Reporting which sub-populations of the tumour are growing or shrinking, cycle by cycle, would turn the test into an evolution monitor.

Once a year, send the same blinded blood samples to every company selling a tumour-DNA test and publish how each performed.

Dozens of companies sell blood tests for tumour DNA and they report different results on the same sample. Government-issued reference samples with known amounts of tumour DNA would expose the differences.

Rare cancers often share a broken cellular machine even when they arise in different organs. Grouping patients by that shared fault makes trials possible.

Whole regions of tissue carry cancer mutations long before a tumour exists. Detecting and treating the field, not the tumour, could prevent cancers rather than cure them.

Most cancers have the wrong number of chromosomes; normal cells do not. If that difference creates a specific weakness, a drug against it would spare normal tissue by definition.

Current blood tests for leftover cancer track a few dozen mutations and miss low-level disease. Whole-genome and error-corrected methods integrate signal across thousands of tumour-specific sites plus methylation and fragment features, reaching detection near one part per million in research settings; cost, turnaround and reproducibility are the barriers.

Treatment is often chosen from a biopsy taken years earlier from the original tumour. The spread disease may now look different. Test it again before switching drugs.

Chromosomally unstable, often whole-genome-doubled tumours survive constant chromosome mistakes by depending on the motor protein KIF18A, which diploid cells do not need. Blocking it kills unstable cancer cells while sparing normal ones; inhibitors are in early trials in ovarian and other cancers.

Map every state a cancer cell can be in, and how drugs and the surrounding tissue move it between states, into an open computational model anyone can query and improve.