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cc-study-design

Use when designing or auditing the experimental plan for a Cancer Cell (Cell Press) study — orthogonal validation across in vitro, in vivo, and huma…

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技能内容

Experimental Design (cc-study-design)

When to trigger

  • The mechanism rests on a single system (e.g., cell lines only)
  • Reviewers will ask "is this true in vivo?" or "does it hold in patients?"
  • Controls, replicates, or sample-size logic are unclear
  • Planning mouse / PDX / organoid experiments and unsure about rigor elements

Orthogonal validation ladder

Cancer Cell expects a mechanism corroborated across independent, complementary systems. Build the strongest ladder the biology allows:

| Layer | Systems | Role |

|-------|---------|------|

| In vitro | Cell lines (multiple, authenticated), primary cells, co-cultures, biochemistry | Establish mechanism, gain/loss-of-function, epistasis |

| Functional genetics | CRISPR KO/KI, shRNA/siRNA with rescue, point mutants, degrons | Causality and specificity |

| In vivo | GEMM, syngeneic, xenograft, PDX, orthotopic, metastasis models | Mechanism operates in a tumor in an organism |

| 3D / ex vivo | Tumor organoids, patient-derived organoids, slice cultures, spheroids | Bridge to human, drug response |

| Human | Patient tumor samples, TMAs, scRNA-seq, public cohorts (TCGA), outcome data | Translational anchor / clinical relevance |

A Cancer Cell paper typically spans in vitro + in vivo + a human anchor. Decide early which layers carry the causal claim and which provide corroboration.

Controls (the parts reviewers attack)

  • Genetic perturbation: include rescue / add-back; use ≥2 independent sgRNAs or shRNAs (or rule out off-target); non-targeting / scramble control matched to delivery.
  • Pharmacology: vehicle control, dose-response, on-target genetic phenocopy, and where possible a resistant mutant or analog.
  • In vivo: isotype/vehicle controls, littermate or co-housed controls for GEMMs, tumor-volume and endpoint pre-defined.
  • Antibody / staining: isotype, KO/KD-validated, single-stain compensation for flow.

Replicates: biological vs technical

  • Biological replicates = independent biological units (separate mice, independent cell passages/cultures, distinct patients). These define n.
  • Technical replicates (duplicate wells, repeat measurements) reduce measurement noise but do not increase n.
  • Report both clearly; never inflate n with technical replicates (see cc-statistics).

Sample size, randomization, blinding (especially animals)

  • Power / sample size: justify mouse n (effect size + variance from pilot or literature); state the basis even if informal.
  • Randomization: allocate animals to arms randomly (e.g., when tumors reach a set volume), not by cage convenience.
  • Blinding: blind outcome assessment (tumor measurement, histology scoring, imaging quantification) wherever feasible.
  • Inclusion/exclusion: pre-define humane endpoints and exclusion criteria; report all animals/samples and any exclusions.

Human-sample design

  • Define cohort, inclusion/exclusion, and how samples link to outcomes.
  • Power survival / association analyses; pre-specify primary comparison.
  • Note IRB/consent (route to cc-ethics-registration).

Checklist

  • [ ] Mechanism validated across ≥2 orthogonal systems; causal layer identified
  • [ ] In vivo evidence present (GEMM / xenograft / PDX / orthotopic) where claims require it
  • [ ] Genetic perturbations include rescue and ≥2 independent reagents
  • [ ] Matched controls defined for every perturbation and treatment
  • [ ] Biological vs technical replicates distinguished; n = biological units
  • [ ] Animal sample size justified; randomization and blinding specified
  • [ ] Inclusion/exclusion criteria and humane endpoints pre-defined
  • [ ] Human-sample cohort and primary comparison pre-specified

Anti-patterns

  • Conclusions from a single cell line or a single system
  • shRNA/CRISPR phenotype with no rescue (off-target not excluded)
  • "n=3" that is three wells of one experiment (pseudo-replication)
  • Mouse experiments with no randomization, no blinding, no power basis
  • Therapeutic efficacy claimed without an in vivo tumor model
  • Selecting samples post hoc to fit the hypothesis

Output format

【Causal claim layer】in vitro / in vivo / human
【Orthogonal systems planned】...
【Controls per perturbation】rescue + 2 reagents? vehicle/isotype?
【Replicates】biological n = ... ; technical handled separately
【Animal rigor】power basis / randomization / blinding / endpoints
【Human anchor】cohort + primary comparison
【Gaps to close before submission】...
【Next step】cc-reporting-standards (rigor reporting) or cc-statistics

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