Diagnostic Pathways and Molecular Biomarkers in Colorectal Cancer: Current Evidence and Perspectives in Poland
Abstract
1. Introduction
2. Literature Search
2.1. Methodological Framework
2.2. Screening for Colorectal Cancer
| Method | Mechanism of Action | Sensitivity | Specificity | Remarks |
|---|---|---|---|---|
| gFOBT | Detects heme peroxidase activity | 19.3–44.1% | 65.0–99.0% | Results may be false positives due to diet or medications. |
| FIT | Detects antibodies specific to human hemoglobin | 79–80.4% | 93.5–94% | No need for dietary restrictions, better patient acceptability, preferred method in many countries. |
| Mt-sDNA | Detects occult blood and genetic markers | 74–86% | 85–94% | High sensitivity and specificity, effective tool in CRC diagnostics. |
2.3. CRC Early Detection Recommendations in Poland
- Genetic markers—mutations in specific genes, e.g., KRAS, NRAS, BRAF.
- Epigenetic markers—DNA methylation changes, e.g., SEPT9.
- Protein markers—proteins secreted by tumor cells or their microenvironment, e.g., CEA.
- MicroRNA (miRNA) markers—short RNA molecules regulating gene expression, e.g., miR-21.
- By clinical application, markers are classified as:
- Diagnostic markers—allow detection of an ongoing neoplastic process, e.g., methylated SEPT9 (mSEPT9), a test based on detection of methylated SEPT9 DNA in patient plasma; TAG-72; circulating miRNAs (c-miRNA); p53.
- Prognostic markers—help determine patient prognosis, e.g., BRAF mutation in CRC, associated with worse outcomes; TAG-72; circulating tumor cells (CTCs); circulating tumor DNA (ctDNA); c-miRNA; p53; PTEN.
- Predictive markers—indicate response to specific therapies, e.g., KRAS and NRAS mutations in CRC predict resistance to anti-EGFR therapy; ctDNA; PTEN.
- Monitoring markers—used to assess treatment effectiveness and detect recurrence, e.g., CEA, CA 19-9, TPS, TAG-72, CTCs, ctDNA, c-miRNA.
- By biological material analyzed, markers include:
- Serum markers—present in patient blood, e.g., carbohydrate antigen CEA.
- Tissue markers—present in surgical material, e.g., TP53 and PTEN mutations detected in paraffin-embedded tumor samples.
- Stool markers—present in fecal material, e.g., sDNA-FIT screening tests.
- Urinary markers, e.g., c-miRNA, are detectable in the early stages of CRC.
2.4. Selected Markers of Colorectal Cancer
3. Emerging Multi-Omics and AI-Driven Approaches in CRC Biomarker Discovery
4. Challenges in Clinical Translation and Access to Molecular Diagnostics
5. Conclusions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| CRC | Colorectal cancer |
| FAP | Familial adenomatous polyposis; |
| HMPS | Hereditary mixed polyposis syndrome |
| HNPCC | Hereditary non-polyposis colorectal cancer, Lynch syndrome; associated polyposis |
| MAP | MUTYH-associated polyposis |
| MUTYH | base excision repair gene; biallelic mutations predispose to colorectal cancer. |
| 5-FU | 5-fluorouracil |
| CEA | carcinoembryonic antigen |
| CT | computed tomography |
| MRI | magnetic resonance imaging |
| FOBT | fecal occult blood testing |
| FIT | fecal immunochemical testing |
| sDNA-FIT | stool DNA testing |
| miRNA | MicroRNA |
| mSEPT9 | methylated SEPT9 |
| CTCs | circulating tumor cells |
| ctDNA | circulating tumor DNA |
| CA 19-9 | Carbohydrate antigen 19-9 |
| TPS | Tissue polypeptide-specific antigen |
| TAG-72 | Tumor-associated glycoprotein 72 |
| CA 72-4 | Carbohydrate antigen 72-4 |
| CIN | chromosomal instability |
| MSI | microsatellite instability |
| PTEN | Phosphatase and tensin homolog |
| CIMP | CpG island methylator phenotype |
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| Hereditary Syndrome | Gene(s) Involved | Inheritance Pattern |
|---|---|---|
| FAP | APC | Autosomal dominant |
| MAP | MUTYH | Autosomal recessive |
| Peutz–Jeghers syndrome | STK11 | Autosomal dominant |
| Cowden syndrome | PTEN | Autosomal dominant |
| HMPS | CRAC1 | Autosomal dominant |
| Juvenile polyposis of the colon | BMPR1A, SMAD4 | Autosomal dominant |
| HNPCC | MLH1, MSH2, MSH6, PMS2, EPCAM | Autosomal dominant |
| Method | Sensitivity | Specificity | CRC Risk/Mortality Reduction | Recommended Interval | Advantages/ Disadvantages | Refs. |
|---|---|---|---|---|---|---|
| Sigmoidoscopy | 95% (adenomas) | 87% | CRC risk ↓ 26%/mortality ↓ 30% | Every 5–10 years (with annual FIT) | Lower complication rate compared with colonoscopy, less invasive Evaluates only the distal colon | [16,17,18,19,20,21,22,23,24] |
| Colonography | Adenomas ≥ 10 mm: 89%; Adenomas ≥ 6 mm: 86% | Adenomas ≥ 10 mm: 94%; Adenomas ≥ 6 mm: 89% | No data on CRC mortality reduction | Every 5 years | Minimally invasive, no anesthesia, safe for patients with comorbidities, detects extracolonic abnormalities Abnormal results require colonoscopy, no evidence of mortality reduction | [16,17,18,19,20,21,22,23,24] |
| Colonoscopy | Gold standard; complete visualization of the colon | CRC incidence ↓ 69% | mortality ↓ up to 88% | Every 10 years (starting age: 45) | Both diagnostic and therapeutic (polyp removal), highest effectiveness More invasive, requires bowel prep and diet/medication adjustments, higher cost, complications < 1% (bleeding 0.146%, perforation 0.031%), low patient adherence | [16,17,18,19,20,21,22,23,24] |
| Target Group | Recommended Test | Remarks | Refs. |
|---|---|---|---|
| Individuals aged 50–65 years without symptoms or with symptoms (GI bleeding, diarrhea, constipation, anemia). | Colonoscopy | First-time examination, repeated every 10 years | [33,34] |
| Individuals aged 40–49 years with a first-degree relative diagnosed with CRC | Colonoscopy | First-time examination, repeated every 10 years | [33,34] |
| Individuals aged 25–49 years with a family history of familial adenomatous polyposis (FAP) | Colonoscopy | Confirmation required in a genetic counseling clinic | [33,34] |
| Individuals who underwent colonoscopy within the last 10 years | Not eligible for repeat colonoscopy | Screening colonoscopy not provided under the program | [33,34] |
| Individuals for whom colonoscopy is not feasible | FOBT | Annual testing | [33,34] |
| Individuals included in the Program 40 Plus | FOBT | Free of charge under the program | [33,34] |
| Biomarker | Clinical Implication | Therapeutic Consequence | Prognostic Significance | Refs. |
|---|---|---|---|---|
| Carcinoembryonic antigen (CEA) | Widely used marker for recurrence surveillance; elevated in ~70% of CRC. | Does not guide therapy; used for monitoring when elevated pre-treatment. | Rising postoperative CEA predicts recurrence; low sensitivity limits standalone use. | [35,36] |
| Carbohydrate antigen 19-9 (CA 19-9) | Low sensitivity in CRC; adjunctive marker when combined with CEA; falsely elevated in benign conditions. | Not recommended for monitoring systemic therapy or guiding treatment. | Higher levels may indicate worse outcomes; non-producers limit use. | [65] |
| Methylated SEPT9 (mSEPT9) | Non-invasive screening test; helpful in recurrence prediction when combined with CEA. | No direct therapeutic implications; supportive diagnostic tool. | Preoperative positivity associated with higher recurrence risk; lower sensitivity vs. colonoscopy. | [37,38,39,40,41] |
| Tissue polypeptide-specific antigen (TPS) | Marker of cell proliferation; useful in monitoring chemotherapy response. | Indicates treatment effect during systemic therapy. | Elevated TPS correlates with aggressive disease. | [42,43,44,45,46] |
| Tumor-associated glycoprotein 72 (TAG-72/CA 72-4) | Complementary diagnostic marker; increases sensitivity when combined with CEA and CA19-9. | Not used for therapy selection; adjunct for long-term follow-up. | Elevated levels associate with tumor burden; sensitivity varies by tumor site. | [47,48,49] |
| Circulating tumor cells (CTCs) | Reflect metastatic potential | Useful for dynamic therapy monitoring | Higher counts link to aggressive disease | [50,51] |
| ctDNA positivity (MRD) | Detects minimal residual disease | Guides adjuvant therapy intensity; early relapse detection | Early rise predicts recurrence months before imaging | [52,53] |
| Circulating microRNAs (c-miRNAs) | Early detection of CRC; stool and plasma assays complement screening; material-dependent sensitivity. | No direct therapeutic impact yet; emerging predictive potential in multi-omics models. | Altered miRNA signatures correlate with tumor stage, invasiveness, and recurrence risk. | [54] |
| TP53 mutation | Associated with impaired DNA damage response | Reduced sensitivity to 5-FU, cisplatin, oxaliplatin | Worse overall survival | [57,58,59] |
| PTEN loss | Activates PI3K/AKT pathway; induces treatment resistance | Reduced efficacy of EGFR inhibitors; potential candidate for PI3K pathway-targeted trials | Associated with deeper invasion, nodal metastases, and poor survival | [60,61,62,63] |
| Approach | What It Measures | Clinical Use | Advantages | Limitations | Refs. |
|---|---|---|---|---|---|
| Genomics (NGS) | Mutations, CNVs, MSI/MMR | Therapy selection | Actionable targets | Cost; limited early detection | [64,66,67,68,69,70,71,72,73] |
| Epigenomics | DNA methylation | Screening; recurrence | Liquid biopsy-friendly | Lower sensitivity; variability | [64,66,67,68,69,70,71,72,73] |
| Transcriptomics | Gene-expression | Prognosis; immunotherapy prediction | Immune contexture captured | Needs high-quality tissue | [64,66,67,68,69,70,71,72,73] |
| Proteomics | Protein pathways | Target discovery | Functional insight | Low standardization | [64,66,67,68,69,70,71,72,73] |
| Metabolomics | Metabolic markers | Early detection | Non-invasive | High variability | [64,66,67,68,69,70,71,72,73] |
| Microbiome | Gut bacteria, metabolites | Risk; immune modulation | Non-invasive | Inter-individual variation | [64,66,67,68,69,70,71,72,73] |
| Multi-Omics Liquid Biopsy | cfDNA mutations + methylation + fragmentomics | Early detection; MRD | High accuracy | Complex analytics; cost | [64,66,67,68,69,70,71,72,73] |
| scRNA-seq | Single-cell TME mapping | Resistant clones; immune profiling | Highest resolution | Only research use | [64,66,67,68,69,70,71,72,73] |
| Spatial Transcriptomics | Spatial gene maps | TME architecture | Preserves tissue context | Very high cost | [64,66,67,68,69,70,71,72,73] |
| AI/ML | Integrated clinical + omics | Predicting risk/outcomes | High accuracy | Needs large datasets | [64,66,67,68,69,70,71,72,73] |
| Deep Learning Multi-Omics | Multi-layer biomarker fusion | Early detection | Outperforms single tests | Limited validation | [64,66,67,68,69,70,71,72,73] |
| Barrier | Core Problem | Clinical Impact | Essential Solution | Refs. |
|---|---|---|---|---|
| Cost and Reimbursement | High cost; limited coverage | Unequal access; restricted testing | Reimbursement reform; cost-effectiveness data | [68,74,75,76,77] |
| Standardization Issues | Variable NGS/ctDNA workflows | Inconsistent results | Harmonized protocols; QC programs | [68,74,75,76,77] |
| Infrastructure Limits | Lack of sequencing/bioinformatics capacity | Limited implementation outside major centers | Investment in labs; centralized testing | [68,74,75,76,77] |
| Clinical Workflow Gaps | Complex reports; lack of clear pathways | Misinterpretation; underuse | Decision-support tools; MDT involvement | [68,74,75,76,77] |
| Evidence Gaps | Few prospective trials for new biomarkers | Conservative guidelines; low reimbursement | Large-scale validation studies | [68,74,75,76,77] |
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Bichalski, B.; Bichalska-Lach, M.; Waniczek, D. Diagnostic Pathways and Molecular Biomarkers in Colorectal Cancer: Current Evidence and Perspectives in Poland. Curr. Issues Mol. Biol. 2025, 47, 1047. https://doi.org/10.3390/cimb47121047
Bichalski B, Bichalska-Lach M, Waniczek D. Diagnostic Pathways and Molecular Biomarkers in Colorectal Cancer: Current Evidence and Perspectives in Poland. Current Issues in Molecular Biology. 2025; 47(12):1047. https://doi.org/10.3390/cimb47121047
Chicago/Turabian StyleBichalski, Bartosz, Magda Bichalska-Lach, and Dariusz Waniczek. 2025. "Diagnostic Pathways and Molecular Biomarkers in Colorectal Cancer: Current Evidence and Perspectives in Poland" Current Issues in Molecular Biology 47, no. 12: 1047. https://doi.org/10.3390/cimb47121047
APA StyleBichalski, B., Bichalska-Lach, M., & Waniczek, D. (2025). Diagnostic Pathways and Molecular Biomarkers in Colorectal Cancer: Current Evidence and Perspectives in Poland. Current Issues in Molecular Biology, 47(12), 1047. https://doi.org/10.3390/cimb47121047

