What Is Biomarker Identification?
Biomarker identification is the process of finding biological signs (like certain molecules, genes, or proteins in the body) that tell us:
- If someone has a disease,
- How serious it is,
- If a treatment is working,
- Or even if someone is likely to get the disease in the future.
These biomarkers are essential for:
- Diagnosing diseases early,xปxปxป
- Predicting how a disease might progress,
- Choosing the right treatment for each person (personalized medicine),
- And developing new drugs.
Types of Biomarkers (What They Tell Us)
| Type | Purpose |
|---|---|
| Diagnostic | Confirms if a disease is present (e.g., PSA for prostate cancer) |
| Prognostic | Shows how a disease might progress (e.g., risk of cancer coming back) |
| Predictive | Helps choose the right treatment (e.g., HER2 for breast cancer treatment) |
| Monitoring | Tracks how well treatment is working (e.g., CA-125 in ovarian cancer) |
| Risk | Indicates if you are more likely to develop a disease |
How Are Cancer Biomarkers Identified?
1. Collect Samples
Get body materials like blood, urine, or tissue from both healthy people and patients.
2. Scan for Differences
Use advanced tools to look at:
- DNA (genomics)
- RNA (transcriptomics)
- Proteins (proteomics)
- Metabolites (metabolomics)
- Epigenetic changes (epigenomics)
These tools include things like gene sequencing, mass spectrometry, and chemical analysis.
3. Clean the Data
Make sure the results are accurate by removing errors or background noise.
4. Analyze the Data
Use statistics and AI (machine learning) to find patterns or differences linked to disease.
5. Validate the Findings
Double-check the results with:
- More data
- Lab tests (like ELISA or qPCR)
- Clinical trials with real patients
6. Understand the Biology
See how these biomarkers fit into body systems and disease processes, using known research and biological databases.
Common Challenges
- Small study sizes
- Different results in different people
- Difficulty repeating results
- Regulatory and ethical hurdles
Cancer Biomarker Discovery: A Closer Look
1. Start with a Goal
Are we looking to:
- Catch cancer early?
- Predict survival chances?
- See if a drug will work?
- Track if cancer comes back?
2. Get the Right Samples
Use:
- Tumor and normal tissues
- Blood or saliva (liquid biopsy)
- Other fluids (urine, spinal fluid)
3. Use “Omics” Tech to Scan
Examples:
- DNA changes (mutations)
- Gene activity (like HER2 in breast cancer)
- Protein levels (like PSA in prostate cancer)
- Metabolic changes
- DNA methylation (epigenetic markers)
4. Clean and Normalize Data
Remove technical noise and check for reliable patterns.
5. Pick Out Key Features
Use tools and models to find what’s important:
- Statistical tests
- Machine learning (e.g., random forests, SVMs)
- Survival models (Kaplan-Meier, Cox regression)
6. Understand What It Means
Look at:
- Biological pathways (e.g., cancer growth pathways like p53 or MAPK)
- Gene/protein networks
7. Cancer Biomarkers
| Biomarker | Cancer Type | Type | Clinical Use |
|---|---|---|---|
| HER2 | Breast, gastric | Protein | Targeted therapy (trastuzumab) |
| EGFR mutation | Lung (NSCLC) | Gene mutation | Predicts response to EGFR inhibitors |
| BRAF V600E | Melanoma, colorectal | Gene mutation | Targeted therapy (vemurafenib) |
| PD-L1 | Multiple (e.g., lung) | Protein | Predicts immunotherapy response |
| BRCA1/2 | Breast, ovarian | Germline mutation | Risk assessment, PARP inhibitors |
| MSI-H/dMMR | Colorectal, endometrial | Genomic instability | Immunotherapy predictor |
| ctDNA | Various | Circulating DNA | Non-invasive monitoring, MRD |
Remember:
Biomarkers help your doctor understand your cancer better—so they can treat YOU, not just the disease.
