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name: cc-figures-tables description: Use when building or auditing multi-panel mechanistic figures and tables for a Cancer Cell (Cell Press) manuscript — quantification of images, panel logic, image integrity, and legends. It shapes display items; it does not choose statistical tests or write the abstract.

Figures & Tables (cc-figures-tables)

When to trigger

• Representative images (blots, IHC, micrographs) shown without quantification
• A multi-panel figure has no clear narrative logic
• Worried about image-integrity standards (splicing, over-processing)
• Building a graphical abstract or supplemental display items

Cancer Cell figure logic

Each main figure should advance one step of the mechanistic argument and be readable on its own:

• Panels flow left-to-right / top-to-bottom as a mini-narrative (perturbation → readout → mechanism → consequence).
• Mechanistic figures typically combine schematic + functional data + in vivo and/or human validation.
• A figure usually carries discovery, validation, and a control panel together.
• Keep one main message per figure; push orthogonal corroboration to supplement.

Quantify everything representative

The signature Cancer Cell requirement: a representative image must be paired with quantification across biological replicates.

Representative image	Required quantification
Western blot	Densitometry across n independent blots (normalized to loading)
IHC / IF micrograph	Scored / counted across multiple fields and tumors (e.g., QuPath)
Flow plot	Summary bar/dot plot of % or MFI across replicates
Tumor photo	Tumor volume/weight curves with n, stats
Migration/invasion image	Quantified across fields/replicates
Single-cell UMAP	Proportions / DE stats, not just a colored embedding

Show data points (superplots) for small n; never imply quantity from one picture.

Image integrity (Cell Press enforces)

• Keep uncropped, unprocessed raw blots/gels; include full-length blots in supplement with MW markers.
• No splicing of lanes without a clear dividing line and disclosure.
• Adjustments (brightness/contrast) must be linear and applied to the entire image, including controls.
• Do not duplicate, mirror, or reuse panels across figures.
• Disclose any grouping of images from different parts of the same gel.

Tables and the Key Resources Table

• The Key Resources Table (STAR Methods) is mandatory — see cc-reporting-standards.
• Data tables (cohorts, mutation lists, screen hits) go to supplement; keep main tables minimal.
• Define every abbreviation and unit in legends.

Legends

• State n, what one replicate is, the statistical test, the error-bar definition, and scale bars.
• Each panel letter referenced; magnification/scale bar on all micrographs.
• Antibodies / markers / treatments named in the legend.

Worked micro-example: fixing a "representative blot" panel

Before: Figure 2C is a single Western blot showing MARK7 down and cleaved-PARP up after treatment, captioned "representative of independent experiments."

Why a Cancer Cell reviewer rejects it as evidence: one image cannot support a quantitative claim; the reader cannot see variance, n, or whether the effect is consistent.

After: Figure 2C keeps the representative blot but adds 2C′ — densitometry normalized to loading control across four independent lysates, plotted as a superplot (individual points + mean), with the test and exact p in the legend. The uncropped full-length blot with MW markers moves to Figure S2. Now the panel carries a claim, not an anecdote.

Panel-order sanity check (per main figure)

Read each figure left-to-right and ask whether it narrates one mechanistic step:

1. Perturbation — what was changed (knockdown/knockout/inhibitor), with the validation of that perturbation.
2. Readout — the phenotype or molecular consequence, quantified across replicates.
3. Mechanism — the intermediate that connects perturbation to readout (binding, flux, signaling).
4. Orthogonal confirmation — in vivo and/or human panel that the claim in the figure title needs.

If a panel does not serve the figure's one-sentence title, move it to the supplement.

Cancer Cell figure failure modes reviewers cite

• A migration/invasion or IHC figure with beautiful images but no per-field, per-tumor quantification.
• Tumor-growth curves without n per arm, without the test, or truncated before humane endpoints.
• Flow plots shown as gated dot-plots only, with no summary statistic across mice/donors.
• A graphical abstract that asserts an axis (arrows implying causality) the main figures never establish.
• Kaplan-Meier survival curves with no numbers-at-risk and no censoring shown.
• Contrast/brightness pushed non-linearly, or a loading-control band reused across panels.

Checklist

• Every figure advances one mechanistic step; panel order tells a story
• Each representative image is paired with replicate-level quantification
• Data points shown for small-n panels (superplots)
• Blots uncropped in supplement, MW markers visible, no undisclosed splicing
• Image adjustments linear and whole-image; no duplicated panels
• Scale bars on all micrographs; channels/markers labeled
• Legends give n, test, error-bar definition
• In vivo / human validation panels present where claims need them
• Graphical abstract (if used) conveys the mechanism at a glance

Anti-patterns

• One representative blot/image as the entire evidence (no quantification)
• Bar charts hiding tiny n; undefined error bars
• Spliced or over-contrasted blots; reused/duplicated panels
• Overcrowded figures mixing several unrelated messages
• Missing scale bars or unlabeled axes
• Beautiful schematic with no supporting data

Output format

【Per-figure message】Fig1: ... Fig2: ...
【Representative-without-quantification】flagged panels: [...]
【Image integrity】raw blots? linear adj? duplication check
【Legends】n / test / error bar / scale bar present? Y/N
【Validation panels】in vivo / human present where needed?
【Next step】cc-structured-abstract