Biomarkers and liquid biopsy¶
TL;DR — Colorectal biomarkers have three distinct jobs: classify tumor biology, predict treatment effect and monitor residual/relapsing disease. MMR/MSI, extended RAS, BRAF V600E and HER2 have established treatment utility; CMS and many immune/stromal signatures remain prognostic or exploratory (Morris 2023, PMID 36252154; Guinney 2015, PMID 26457759). CEA is inexpensive but neither sensitive nor specific enough to diagnose recurrence alone; serial trends outperform a single threshold (Shinkins 2018, PMID 29579327). Postoperative ctDNA is one of the strongest recurrence prognosticators: DYNAMIC showed stage II chemotherapy can be reduced using a defined ctDNA strategy, but DYNAMIC-III illustrates that escalation benefit cannot be assumed from prognostic risk (Tie 2022, PMID 35657320; Tie 2025, PMID 41115959). Tumor-informed and tumor-agnostic assays differ in lead time, sensitivity, turnaround and clonal-hematopoiesis control. Blood screening and postoperative MRD are different applications and should never share performance claims (Chung 2024, PMID 38477985).
Biomarker taxonomy¶
| Type | Question | Example | Evidence required |
|---|---|---|---|
| Diagnostic | Is cancer present? | Screening cfDNA, pathology marker | Sensitivity/specificity in intended population |
| Prognostic | What happens regardless of treatment? | Postoperative ctDNA | Outcome association with confounder control |
| Predictive | Does treatment effect differ? | RAS for anti-EGFR | Valid treatment-by-marker interaction |
| Pharmacodynamic | Did biology change on treatment? | Falling ctDNA | Link between change and outcome |
| Surveillance | Has recurrence emerged? | CEA/ctDNA | Lead time plus improved patient outcome |
A strong prognostic biomarker may have no treatment utility. Clinical utility requires that acting on the result improves an outcome.
Established tissue biomarkers¶
| Marker | Assay | Clinical use | Limitation |
|---|---|---|---|
| MMR/MSI | IHC, PCR or NGS | Lynch triage, prognosis, checkpoint therapy | Discordance and incomplete reflex pathways |
| KRAS/NRAS | NGS/PCR | Anti-EGFR resistance | Acquired clones and plasma false negatives |
| BRAF V600E | NGS/PCR/IHC context | BRAF+EGFR therapy, prognosis, MLH1-loss triage | V600E differs from non-V600 alterations |
| HER2 | IHC/ISH/NGS | Dual HER2 therapy | Criteria/platform heterogeneity |
| NTRK fusion | RNA/DNA NGS | TRK inhibitor | Extremely rare; DNA can miss fusions |
| DPYD germline | Germline genotype | Fluoropyrimidine safety | Does not capture all DPD deficiency |
Universal MMR IHC studies show workflow loss: pooled IHC missingness 11.81% and germline completion 76.30% among eligible patients (Eikenboom 2022, PMID 33887476). A biomarker unavailable at decision time is a system failure even if assay performance is high.
Histopathologic biomarkers¶
Tumor budding, lymphovascular/perineural invasion, grade, margins and treatment regression remain practical biomarkers embedded in pathology.
ITBCC standardized tumor budding as single cells/clusters ≤4 in a 0.785-mm² hotspot and judged it prognostic in pT1 and stage II disease (Lugli 2017, PMID 28548122). Its predictive utility for a specific chemotherapy is not established.
Node yield is a quality/prognostic composite, not a molecular marker. More examined nodes correlate with survival, but causality includes stage migration, surgery, pathology and host immunity (Chang 2007, PMID 17374833).
CEA¶
CEA is a glycoprotein shed by many colorectal cancers. Uses include pretreatment baseline, prognosis and post-treatment surveillance.
| Strength | Weakness |
|---|---|
| Low cost and widely available | Normal in a substantial tumor subset |
| Serial personalized trend | Smoking/inflammation can elevate |
| Can precede radiographic recurrence | False positives accumulate with repeated tests |
| Complements CT | Does not localize disease |
FACS analysis found longitudinal CEA trends more informative than single-threshold interpretation, but lowering thresholds increased false alarms (Shinkins 2018, PMID 29579327). Meta-analysis found follow-up-test accuracy heterogeneous and no modality sufficient alone (Liemburg 2021, PMID 33704843).
Older studies established postoperative CEA as a recurrence predictor but used assays and imaging pathways different from current care (McCall 1994, PMID 8076486).
What ctDNA measures¶
ctDNA is the tumor-derived fraction of cell-free DNA. Concentration depends on tumor burden, vascularity, site, cell death and clearance.
| Context | Typical shedding |
|---|---|
| Bulky liver metastases | High |
| Lung-only small metastases | Lower |
| Peritoneal-only disease | Often lower |
| Immediately after surgery | Confounded by high non-tumor cfDNA |
| Microscopic residual disease | Near assay detection limit |
Negative ctDNA means “not detected by this assay at this time,” not “no cancer.”
Tumor-informed versus tumor-agnostic¶
| Feature | Tumor-informed | Tumor-agnostic/plasma-only |
|---|---|---|
| Design | Tracks patient-specific tumor variants | Fixed panel, methylation/fragment or genomic features |
| Sensitivity | Can aggregate multiple variants | May capture evolution without tissue |
| Turnaround | Requires tissue sequencing/design | Often faster |
| Clonal hematopoiesis | Tumor matching helps | Paired white-cell filtering important |
| Failure | Insufficient tissue/delay | Lower specificity or variant attribution |
Reviews stress that assay classes are not interchangeable and that lead-time, immortal-time and sampling biases can exaggerate apparent performance (Martínez-Castedo 2025, PMID 39675560; Hlauschek 2026, PMID 42508231).
Postoperative MRD¶
ctDNA after curative-intent surgery strongly stratifies recurrence. The critical question is whether treatment can change the poor outcome of a positive test.
DYNAMIC stage II¶
DYNAMIC randomized 455 stage II patients to ctDNA-guided or clinicopathologic management. Chemotherapy use fell from 28% to 15%; 2-year recurrence-free survival was 93.5% versus 92.4%, meeting noninferiority (Tie 2022, PMID 35657320).
At 5 years, recurrence-free and overall survival remained consistent with safe de-escalation within the trial algorithm (Tie 2025, PMID 40055522).
| DYNAMIC proves | DYNAMIC does not prove |
|---|---|
| A defined stage II strategy reduced chemotherapy | Every commercial assay is equivalent |
| Noninferior RFS in that trial | ctDNA-negative risk is zero |
| Positive patients received treatment | Escalation beyond standard improves survival |
Stage III and escalation¶
DYNAMIC-III randomized ctDNA-informed escalation/de-escalation. De-escalation reduced treatment, but intensifying therapy in ctDNA-positive disease did not automatically overcome risk (Tie 2025, PMID 41115959).
Post hoc IDEA-France analysis found postoperative ctDNA prognostic in stage III and related it to duration, but biomarker subgroup analysis cannot substitute for a prospective action trial (Taieb 2021, PMID 34083233).
CIRCULATE-Japan¶
CIRCULATE-Japan links the GALAXY observational registry with VEGA de-escalation and ALTAIR escalation trials (Taniguchi 2021, PMID 33931919). Large resectable-disease analyses confirm strong molecular-residual-disease prognostic separation (Nakamura 2024, PMID 39284954).
Timing¶
| Time point | Use | Caveat |
|---|---|---|
| Preoperative | Assay design and shedding baseline | Not MRD |
| ~2–4 weeks postoperative | Early MRD | Surgical cfDNA may dilute signal |
| Before adjuvant therapy | Treatment allocation | Delay versus turnaround |
| During therapy | Molecular clearance | Clearance may be temporary |
| End of therapy | Residual risk | Requires serial confirmation |
| Surveillance | Molecular recurrence | Action pathway unproven |
Serial sampling improves sensitivity but increases cost and false-positive opportunity. Landmark/time-dependent analysis is required.
ctDNA after metastasis-directed therapy¶
After liver resection/ablation, detectable ctDNA predicts recurrence, but liver-metastasis cohorts vary by assay and treatment. A systematic review/meta-analysis supports prognostic value while emphasizing small cohorts and heterogeneity (Khan 2026, PMID 41723037).
The low shedding of lung/peritoneal recurrence can make plasma falsely negative. Organ-specific sensitivity should be reported.
Metastatic disease monitoring¶
Plasma NGS can identify baseline targets and acquired resistance. Under anti-EGFR therapy, serial ctDNA detects emergent RAS/BRAF/MAP2K1/EGFR alterations across lesions (Topham 2023, PMID 36007218).
CALGB/SWOG 80405 plasma analysis demonstrated that first-line cetuximab can select multiple acquired genomic alterations rather than one dominant universal mechanism (Raghav 2023, PMID 36067452).
Resistant clones decay off anti-EGFR with estimated half-life around 4.4 months, supporting molecular rechallenge selection (Parseghian 2019, PMID 30462160). Clinical utility depends on whether plasma-guided sequence improves survival, not just response (Patelli 2023, PMID 37436743).
Screening cfDNA is a separate use case¶
ECLIPSE reported 83.1% CRC sensitivity, 89.6% specificity for advanced neoplasia and 13.2% advanced-precursor sensitivity (Chung 2024, PMID 38477985). Screening performance in asymptomatic average-risk people cannot be inferred from high-shedding metastatic disease.
Cell-free DNA diagnostic reviews show large variation by methylation, fragmentation, mutation panel and case-control design (Petit 2019, PMID 30694754). Methylated-region panels can detect cancer but require prospective screening denominators (Young 2021, PMID 33478584).
Meta-analysis and bias¶
A network meta-analysis found ctDNA MRD strongly associated with recurrence and compared assay/timing strategies, but indirect comparisons inherit study and treatment differences (Hoang 2025, PMID 40293388).
| Bias | How it inflates performance |
|---|---|
| Lead time | Earlier detection appears longer survival without changing death |
| Immortal time | Patient must survive to later sample |
| Treatment confounding | Positive patients receive more therapy |
| Case-control spectrum | Advanced cases versus healthy controls overstates screening accuracy |
| Selective sampling | Missing samples from sicker patients |
| Publication bias | Negative assays less visible |
Analytical standards¶
- Predefine limit of detection and report plasma volume.
- Report tumor fraction and number of tracked variants.
- Filter clonal hematopoiesis, preferably with paired leukocytes.
- State timing from surgery and treatment.
- Report failure/no-result rates.
- Blind outcome assessment to exploratory biomarker where feasible.
- Lock threshold before validation.
- Validate externally and prospectively.
Clinical-utility scoreboard¶
| Application | Status |
|---|---|
| Metastatic RAS/BRAF target testing | Established |
| Anti-EGFR resistance mapping | Clinically useful in selected rechallenge; evolving |
| Stage II de-escalation | Randomized DYNAMIC evidence |
| Stage III escalation | Not established merely by prognostic positivity |
| Routine surveillance replacing CT/CEA | Not established |
| Blood screening replacing established strategies | Outcome evidence immature |
| Rectal complete-response prediction | Investigational |
Open questions¶
- Which assay/timing combination maximizes MRD sensitivity without unacceptable false positives? (Hoang 2025, PMID 40293388)
- What treatment clears ctDNA and improves survival in positive stage III disease? (Tie 2025, PMID 41115959)
- Can serial ctDNA safely reduce CT imaging in any surveillance group? (Liemburg 2021, PMID 33704843)
- How should low-shedding lung and peritoneal recurrence be handled? (Khan 2026, PMID 41723037)
- Will blood screening’s participation gain compensate for 13.2% advanced-precursor sensitivity? (Chung 2024, PMID 38477985)
Related pages¶
- Precision oncology — treatment-predictive targets.
- Localized colon cancer — adjuvant ctDNA decisions.
- Localized rectal cancer — response assessment.
- Metastatic systemic therapy — resistance and rechallenge.
- Clinical trials landscape — ongoing biomarker-action trials.
References¶
- Morris VK, et al. Treatment of Metastatic Colorectal Cancer: ASCO Guideline. J Clin Oncol. 2023;41(3):678-700. PMID 36252154
- Guinney J, et al. The consensus molecular subtypes of colorectal cancer. Nat Med. 2015;21(11):1350-6. PMID 26457759
- Shinkins B, et al. Serum carcinoembryonic antigen trends for diagnosing colorectal cancer recurrence in the FACS randomized clinical trial. Br J Surg. 2018;105(6):658-662. PMID 29579327
- Tie J, et al. Circulating Tumor DNA Analysis Guiding Adjuvant Therapy in Stage II Colon Cancer. N Engl J Med. 2022;386(24):2261-2272. PMID 35657320
- Tie J, et al. Circulating tumor DNA-guided adjuvant therapy in locally advanced colon cancer: the randomized phase 2/3 DYNAMIC-III trial. Nat Med. 2025;31(12):4291-4300. PMID 41115959
- Chung DC, et al. A Cell-free DNA Blood-Based Test for Colorectal Cancer Screening. N Engl J Med. 2024;390(11):973-983. PMID 38477985
- Eikenboom EL, et al. Universal Immunohistochemistry for Lynch Syndrome: A Systematic Review and Meta-analysis of 58,580 Colorectal Carcinomas. Clin Gastroenterol Hepatol. 2022;20(3):e496-e507. PMID 33887476
- Lugli A, et al. Recommendations for reporting tumor budding in colorectal cancer based on the International Tumor Budding Consensus Conference (ITBCC) 2016. Mod Pathol. 2017;30(9):1299-1311. PMID 28548122
- Chang GJ, et al. Lymph node evaluation and survival after curative resection of colon cancer: systematic review. J Natl Cancer Inst. 2007;99(6):433-41. PMID 17374833
- Liemburg GB, et al. Diagnostic accuracy of follow-up tests for detecting colorectal cancer recurrences in primary care: A systematic review and meta-analysis. Eur J Cancer Care (Engl). 2021;30(5):e13432. PMID 33704843
- McCall JL, et al. The value of serum carcinoembryonic antigen in predicting recurrent disease following curative resection of colorectal cancer. Dis Colon Rectum. 1994;37(9):875-81. PMID 8076486
- Martínez-Castedo B, et al. Minimal residual disease in colorectal cancer. Tumor-informed versus tumor-agnostic approaches: unraveling the optimal strategy. Ann Oncol. 2025;36(3):263-276. PMID 39675560
- Hlauschek D, et al. Common analysis pitfalls in longitudinal ctDNA studies: lead time, sensitivity and immortal time bias. EBioMedicine. 2026;130:106407. PMID 42508231
- Tie J, et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer: 5-year outcomes of the randomized DYNAMIC trial. Nat Med. 2025;31(5):1509-1518. PMID 40055522
- Taieb J, et al. Prognostic Value and Relation with Adjuvant Treatment Duration of ctDNA in Stage III Colon Cancer: a Post Hoc Analysis of the PRODIGE-GERCOR IDEA-France Trial. Clin Cancer Res. 2021;27(20):5638-5646. PMID 34083233
- Taniguchi H, et al. CIRCULATE-Japan: Circulating tumor DNA-guided adaptive platform trials to refine adjuvant therapy for colorectal cancer. Cancer Sci. 2021;112(7):2915-2920. PMID 33931919
- Nakamura Y, et al. ctDNA-based molecular residual disease and survival in resectable colorectal cancer. Nat Med. 2024;30(11):3272-3283. PMID 39284954
- Khan AU, et al. Circulating Tumor DNA as a Biomarker for Recurrence After Curative Resection of Colorectal Cancer Liver Metastases: A Systematic Review and Meta-Analysis. Clin Colorectal Cancer. 2026;25(2):181-190.e1. PMID 41723037
- Topham JT, et al. Circulating Tumor DNA Identifies Diverse Landscape of Acquired Resistance to Anti-Epidermal Growth Factor Receptor Therapy in Metastatic Colorectal Cancer. J Clin Oncol. 2023;41(3):485-496. PMID 36007218
- Raghav K, et al. Acquired Genomic Alterations on First-Line Chemotherapy With Cetuximab in Advanced Colorectal Cancer: Circulating Tumor DNA Analysis of the CALGB/SWOG-80405 Trial (Alliance). J Clin Oncol. 2023;41(3):472-478. PMID 36067452
- Parseghian CM, et al. Anti-EGFR-resistant clones decay exponentially after progression: implications for anti-EGFR re-challenge. Ann Oncol. 2019;30(2):243-249. PMID 30462160
- Patelli G, et al. Circulating Tumor DNA to Drive Treatment in Metastatic Colorectal Cancer. Clin Cancer Res. 2023;29(22):4530-4539. PMID 37436743
- Petit J, et al. Cell-Free DNA as a Diagnostic Blood-Based Biomarker for Colorectal Cancer: A Systematic Review. J Surg Res. 2019;236:184-197. PMID 30694754
- Young GP, et al. Evaluation of a panel of tumor-specific differentially-methylated DNA regions in IRF4, IKZF1 and BCAT1 for blood-based detection of colorectal cancer. Clin Epigenetics. 2021;13(1):14. PMID 33478584
- Hoang T, et al. Utility of circulating tumor DNA to detect minimal residual disease in colorectal cancer: A systematic review and network meta-analysis. Int J Cancer. 2025;157(4):722-740. PMID 40293388