A Review on Biomarkers for Early Detection of Liver Cancer

Liver cancer, particularly hepatocellular carcinoma (HCC), is one of the leading causes of cancer- related mortality worldwide. The major challenge in its management lies in the fact that symptoms often appear only at advanced stages, limiting treatment options and survival rates. Therefore, early detection is critical for improving prognosis and reducing mortality. Biomarkers, measurable biological indicators found in blood, tissues, or other body fluids, offer a promising approach for early diagnosis. [1] The application of biomarkers enables clinicians to detect molecular changes preceding clinical symptoms, thereby identifying liver cancer at its initial stages.  Recent advancements in proteomics, genomics, and metabolomics have accelerated the discovery of specific biomarkers, such as alpha-fetoprotein (AFP), des-gamma-carboxy prothrombin (DCP), and Golgi protein-73 (GP73). These markers hold significant diagnostic, prognostic, and therapeutic potential. [2]

History of Biomarker:

Liver cancer, primarily hepatocellular carcinoma (HCC), is one of the most prevalent and deadly malignancies worldwide. Its strong association with chronic hepatitis B and C infections, alcohol consumption, and non-alcoholic fatty liver disease (NAFLD) has made early diagnosis a major focus of research for decades. Historically, diagnosis relied mainly on imaging and clinical symptoms, which often appear only in the advanced stages of the disease. To improve early detection and patient outcomes, scientists began exploring biochemical and molecular markers, known as biomarkers, in the mid-20th century. [3] The first biomarker used clinically for liver cancer detection was Alpha-Fetoprotein (AFP), discovered in the 1960s by Abelev and colleagues in the serum of hepatoma patients. AFP became the gold standard biomarker for HCC screening for several decades due to its easy detection in blood. However, its diagnostic accuracy was limited, as elevated AFP levels were also found in benign liver diseases and pregnancy. [4] To overcome these limitations, new biomarkers such as Des-gamma-carboxy prothrombin (DCP or PIVKA-II) were introduced in the 1980s, offering improved specificity for HCC. Later, in the early 2000s, Golgi protein 73 (GP73) and glypican-3 (GPC3) emerged as promising candidates, showing better performance for early-stage detection compared to AFP alone. [5-6] Advancements in molecular biology and omics technologies (genomics, proteomics, and metabolomics) during the 2010s revolutionized biomarker discovery. [7] Researchers identified novel molecular markers such as microRNAs (miR-21, miR-122), circulating tumor DNA (ctDNA), and exosomal proteins, which provided non-invasive options for liquid biopsy-based detection. [8] These modern biomarkers reflect tumor biology and genetic alterations, offering superior diagnostic, prognostic, and therapeutic insights. [9] Currently, the trend has shifted toward multi-marker panels and integrated diagnostic systems that combine protein, gene, and metabolic biomarkers with advanced imaging and artificial intelligence (AI) tools. [10] This holistic approach aims to enhance sensitivity, specificity, and early detection accuracy, ultimately enabling timely treatment and improved survival rates. [11]..

Background For Selection Of Topic:

5-Year Survival Rate   

When cancer is detected at stage 1

90%

5-Year Survival Rate

When cancer is detected at stage 4

15%    

Liver cancer, especially hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths due to late diagnosis and limited treatment options. [13] Early detection using biomarkers such as alpha- fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP) offers a non-invasive and reliable approach to identify the disease at an earlier stage. [14] This improves prognosis, enables timely treatment, and enhances overall patient survival.[15]

Table no 1 Types of biomarkers: [36]

1. Multi-biomarker Panels:

Instead of relying on a single biomarker like AFP (Alpha-fetoprotein), researchers are combining multiple markers (e.g., AFP-L3, DCP, GP73, GPC3) to improve accuracy.

These panels increase sensitivity and specificity for early-stage hepatocellular carcinoma (HCC).[16]

2. Liquid Biopsy:

A non-invasive technique using blood, urine, or saliva to detect tumor-derived materials such as:

1. 1. Circulating tumor DNA (ctDNA)
   2. Circulating tumor cells (CTCs)
   3. Exosomes and microRNAs (miRNAs)
   4. Liquid biopsy allows real-time tumor monitoring and early diagnosis. [17]

a. MicroRNA (miRNA) and Long Non-coding RNA (lncRNA) Biomarkers:

Specific RNAs (e.g., miR-122, miR-21, HULC, and MALAT1) are emerging as sensitive biomarkers. They reflect early molecular changes in liver cells before visible tumors appear. [18]

3. Proteomic and Metabolomic Profiling:

Advanced mass spectrometry and metabolomics help identify unique protein and metabolite patterns in early liver cancer. This approach provides comprehensive molecular signatures of tumor development [19].

4. Epigenetic Biomarkers

DNA methylation patterns (like methylated SEPT9, RASSF1A) are being explored for early detection.These markers are detectable in circulating free DNA (cfDNA) from blood samples.[20]

a. Artificial Intelligence (AI) and Machine Learning

AI models analyze large biomarker datasets to detect hidden patterns. Integration of clinical data + imaging + biomarkers leads to more accurate risk prediction.[21]

5. Integration with Imaging Biomarkers

Combining molecular biomarkers with advanced imaging (MRI, CT, PET) improves detection and reduces false negatives. [22]

1. Sample Collection:

Blood, urine, or tissue samples are collected from the patient. Blood samples are most commonly used because they are easy to obtain and less invasive. [23]

2. Biomarker Identification:
   • Specific biomarkers (molecules that indicate liver cancer) are targeted for detection.
   • Common liver cancer biomarkers include:
     1. AFP (Alpha-fetoprotein)
     2. DCP (Des-gamma-carboxy prothrombin)
     3. GPC3 (Glypican-3)
     4. microRNAs (miR-21, miR-122)
     5. AFP-L3 (a specific type of AFP) [24]
3. Laboratory Testing:

• The collected samples are analyzed in the lab using advanced techniques such as:
• ELISA (Enzyme-Linked Immunosorbent Assay) – measures protein biomarkers like AFP.
• PCR (Polymerase Chain Reaction) – detects genetic biomarkers such as microRNAs.
• Mass spectrometry or immunoassays – for detailed biomarker profiling. [25]

4. Data Analysis:
   • The biomarker levels are compared with normal reference values.
   • High or abnormal levels of certain biomarkers (e.g., AFP > 400 ng/mL) may indicate liver cancer. [26]
5. Diagnosis Confirmation:
   • If biomarker tests suggest liver cancer, imaging tests such as ultrasound, CT scan, or MRI are performed for confirmation. Sometimes, a biopsy (tissue sample) is also taken to confirm cancerous cells. [27]

Future Scope of Biomarker-Based Early Detection of Liver Cancer:

1. Early Diagnosis:

Biomarkers can detect liver cancer at very early stages before appearing improving survival rate

2. Risk Stratification:

Identify high-risk individuals (e.g., hepatitis or cirrhosis patients) for targeted screening.

3. Non-Invasive Testing:

Blood-based biomarkers and liquid biopsies reduce the need for invasive procedures like liver biopsy.

4. Multi-Biomarker Panels:

Combining multiple biomarkers increases sensitivity and specificity compared to single markers.

5. Integration with AI:

Machine learning can analyze complex biomarker patterns for more accurate early detection.

6. Personalized Surveillance:

Biomarker profiles can guide individualized monitoring schedules.

7. Recurrence Monitoring:

Detect tumor recurrence earlier after treatment through serial biomarker assessment.

8. Therapy Response Assessment:

Biomarkers can indicate how well a patient responds to treatments.

9. Development of Novel Biomarkers:

Research will continue to identify new molecular, protein, or genetic markers for HCC.

10. Point-of-Care Testing:

Portable biomarker assays could enable rapid screening in remote or low-resource areas.

11. Integration with Imaging:

Biomarkers combined with imaging modalities improve diagnostic accuracy.

1. Cost-Effective Screening:

Biomarkers may reduce the need for expensive imaging for routine surveillance.

2. Population-Based Screening Programs:

High-risk populations can be systematically monitored using biomarker-based tests.

3. Multi-Omics Approaches:

Combining genomics, proteomics, and metabolomics will enhance early detection capabilities.

4. Predictive Modeling:

Biomarkers can be used in algorithms to predict liver cancer risk before onset.

5. Reducing Late-Stage Diagnosis:

Early detection through biomarkers decreases the proportion of patients diagnosed at advanced stages.

6. Global Health Impact:

Accessible biomarker tests can significantly reduce liver cancer mortality worldwide.

7. Targeted Therapies Development:

Biomarkers can identify molecular pathways for novel drug targets.

8. Integration with Wearable Tech:

Future biosensors may allow continuous monitoring of biomarker levels.

9. Standardization and Validation:

Future research will establish standardized biomarker protocols for clinical use. [28]