Ranking patients by best tumor change, then reusing the same visual grammar for molecular measurements.
In oncology, a waterfall plot usually means one bar per patient, sorted by best percent change in target-lesion burden. Negative values mean shrinkage. Positive values mean growth. The plot is popular because it keeps the individual patients visible instead of collapsing them into a single response rate.
The same ranked-bar grammar also works for molecular quantities such as expression or mutation burden. The important habit is to name the quantity being ranked, because a RECIST response waterfall and a molecular waterfall answer different questions.
Figure 1. RECIST-style waterfall for 60 synthetic patients. Bars show best percent change from baseline in the sum of target-lesion diameters. The -30% line marks the target-lesion threshold for partial response; the +20% line is a progression reference, but overall progression can also come from non-target lesions or new lesions. A bar crossing -30% is therefore a candidate response, not an ORR by itself.
Now reuse the ranking idea for the TP53–CDKN1A relationship. Sorting by one variable and coloring by another exposes associations: a genotype that clusters at one end of the phenotypic spectrum is visible immediately.
Figure 2. CDKN1A expression waterfall for the same 60 patients. The bars are sorted descending. TP53 mutant samples (red) cluster toward the low-expression end, as TP53 is a transcriptional activator of CDKN1A.
CDKN1A (p21) is a cell cycle inhibitor. Mutated TP53 cannot activate CDKN1A, decreasing expression and allowing faster cell division.
A cohort can be reordered by different measures. Tumor mutation burden (TMB) is often elevated in mutant tumors due to impaired DNA repair — a second axis that tells a different story on the same patients.
Figure 3. Reshuffling the cohort. TP53 mutants cluster low on CDKN1A but high on TMB.
Dragging a threshold classifies patients (e.g., CDKN1A-low) and computes mutation enrichment in that group, bridging visual pattern recognition and formal testing.
Figure 4. Interactive thresholding. Drag the dashed line to classify patients; statistics update to show the association with TP53 status. This is exploratory, so the p-value should be treated as descriptive unless the cutoff was pre-specified or validated elsewhere.