International Journal of Inflammation, Cancer and Integrative Therapy
Open Access

Gastroesophageal cancer, encompassing both gastric (stomach) cancer and esophageal cancer, is a significant global health challenge due to its high incidence and poor prognosis. Early detection and personalized treatment strategies are critical to improving outcomes for patients. Biomarkers, which are biological molecules indicative of disease presence, progression, or response to treatment, play a crucial role in advancing the management of gastroesophageal cancer. This article explores current biomarkers, their clinical implications, and recent innovations in this field [1].

Understanding gastroesophageal cancer

Gastroesophageal cancer includes two main types:

Gastric cancer: Originates in the stomach lining.

Esophageal cancer: Develops in the esophagus, the tube connecting the throat to the stomach.

These cancers are often diagnosed at an advanced stage, contributing to their poor prognosis. Therefore, identifying reliable biomarkers for early detection, prognosis, and treatment response is essential.

Current biomarkers in gastroesophageal cancer

1. HER2 (Human epidermal growth factor receptor 2): HER2 is a protein that promotes cell growth. Overexpression of HER2 is found in approximately 20% of gastric cancers and a smaller percentage of esophageal cancers. HER2 status is determined using immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). HER2-positive tumors can be treated with trastuzumab, an anti-HER2 monoclonal antibody, improving survival rates in these patients [2].
2. PD-L1 (Programmed death-ligand 1): PD-L1 is a protein that helps cancer cells evade the immune system. High PD-L1 expression in tumor cells or the tumor microenvironment is associated with a better response to immune checkpoint inhibitors, such as pembrolizumab and nivolumab. Testing for PD-L1 expression helps identify patients who may benefit from immunotherapy.
3. VEGF (Vascular endothelial growth factor): VEGF promotes blood vessel formation, supporting tumor growth and metastasis. High levels of VEGF are associated with poor prognosis in gastroesophageal cancer. Anti-VEGF therapies, such as bevacizumab, target this pathway to inhibit tumor angiogenesis [3].
4. Microsatellite instability (msi) and mismatch repair (mmr) deficiency: MSI and MMR deficiency occur due to errors in the DNA repair system. Tumors with high MSI or MMR deficiency are more likely to respond to immunotherapy. Testing for MSI/MMR status helps guide treatment decisions and identify patients who may benefit from immune checkpoint inhibitors.
5. CEA (Carcinoembryonic antigen): CEA is a protein that can be elevated in various cancers, including gastroesophageal cancer. Elevated CEA levels are associated with advanced disease and poorer prognosis. CEA is primarily used to monitor treatment response and detect recurrence.
6. CA 19-9 (Carbohydrate antigen 19-9): CA 19-9 is another tumor marker that can be elevated in gastroesophageal cancer. Like CEA, it is used for monitoring disease progression and treatment response, rather than for early diagnosis.

Diagnostic and prognostic implications

1. Early detection: Early detection of gastroesophageal cancer significantly improves outcomes. Biomarkers like HER2, PD-L1, MSI/MMR, CEA, and CA 19-9 provide valuable information that can aid in the early diagnosis and stratification of patients. HER2 status, for example, can guide targeted therapy decisions, while MSI/MMR testing can identify candidates for immunotherapy [4].
2. Prognosis: Biomarkers offer insights into disease aggressiveness and likely clinical outcomes. High levels of VEGF, CEA, and CA 19-9, as well as MSI/MMR status, can provide prognostic information, helping clinicians develop personalized treatment plans and predict patient survival.
3. Treatment selection and monitoring: Biomarkers guide the selection of appropriate therapies and allow for monitoring of treatment efficacy. HER2-positive patients can benefit from targeted therapies like trastuzumab, while high PD-L1 expression indicates a potential response to immune checkpoint inhibitors. Monitoring biomarker levels, such as CEA and CA 19-9, during treatment can provide real-time feedback on therapeutic effectiveness.

Description

Innovative approaches and future directions

1. Liquid biopsies: Liquid biopsies involve the analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and other tumor-derived materials in blood samples. This non-invasive approach offers a promising method for early detection, monitoring of minimal residual disease, and assessing treatment response. Liquid biopsies can detect genetic alterations and mutations, providing insights into tumor dynamics and resistance mechanisms.
2. Multi-omics approaches: Combining genomics, proteomics, and metabolomics data can reveal comprehensive biomarker signatures that provide a deeper understanding of gastroesophageal cancer biology. Multi-omics approaches can identify novel biomarkers and therapeutic targets, facilitating the development of personalized treatment strategies [5].
3. Artificial intelligence and machine learning: AI and ML technologies can analyze large datasets to identify complex biomarker patterns and correlations that traditional analysis methods may miss. These technologies can enhance biomarker discovery, improve diagnostic accuracy, and optimize treatment plans, ultimately leading to better patient outcomes.
4. Tumor microenvironment markers: The tumor microenvironment (TME) plays a crucial role in cancer progression and response to therapy. Biomarkers derived from the TME, including immune cell infiltration profiles and stromal markers, are being investigated to better understand their impact on gastroesophageal cancer and identify new therapeutic targets [6].
5. Personalized medicine: The integration of biomarker testing into clinical practice enables personalized medicine, tailoring treatment to the individual’s genetic profile and disease characteristics [7]. This approach increases the likelihood of treatment success and minimizes unnecessary side effects, leading to improved patient outcomes.

Conclusion

Biomarkers have revolutionized the diagnosis and treatment of gastroesophageal cancer, offering new opportunities for early detection, personalized therapy, and improved patient outcomes. Current biomarkers such as HER2, PD-L1, VEGF, MSI/MMR, CEA, and CA 19-9 provide valuable insights into disease biology and guide clinical decision-making. Emerging technologies, including liquid biopsies, multi-omics approaches, and AI/ML, hold great promise for advancing biomarker research and enhancing clinical care. Continued research and collaboration are essential to fully realize the potential of biomarkers in gastroesophageal cancer, ultimately leading to better clinical outcomes and prolonged survival for patients.

Acknowledgement

None

Conflict of Interest

None

References

1. Ay C, Vormittag R, Dunkler D, Simanek R, Chiriac AL, et al. (2009) D-dimer and prothrombin fragment 1+2 predict venous thromboembolism in patients with cancer: results from the Vienna Cancer and Thrombosis Study. J Clin Oncol 27: 4124-4129.

Indexed at, Google Scholar, Crossref

2. Kirwan CC, McDowell G, McCollum CN, Kumar S, Byrne GJ (2008) Early changes in the haemostatic and procoagulant systems after chemotherapy for breast cancer. British journal of cancer 99: 1000-1006.

Indexed at, Google Scholar, Crossref

3. Khorana AA, Kuderer NM, Culakova E, Lyman GH, Francis CW (2008) Development and validation of a predictive model for chemotherapy-associated thrombosis. Blood 111: 4902-4907.

Indexed at, Google Scholar, Crossref

4. Khorana AA (2007) The NCCN Clinical Practice Guidelines on Venous Thromboembolic Disease: strategies for improving VTE prophylaxis in hospitalized cancer patients. Oncologist 12: 1361-1370.

Indexed at, Google Scholar, Crossref

5. Mulder FI, Candeloro M, Kamphuisen PW, Di Nisio M, Bossuyt PM, et al. (2019) The Khorana score for prediction of venous thromboembolism in cancer patients: a systematic review and meta-analysis. Haematologica 104: 1277.

Indexed at, Google Scholar, Crossref

6. Ashrani AA, Gullerud RE, Petterson TM, Marks RS, Bailey KR et al. (2016) Risk factors for incident venous thromboembolism in active cancer patients: a population based case–control study. Thromb res 139: 29-37.

Indexed at, Google Scholar, Crossref

7. Aslan JE (2021) Platelet proteomes, pathways, and phenotypes as informants of vascular wellness and disease. Arteriosclerosis, thrombosis, and vascular biology 41: 999-1011.

Indexed at, Google Scholar, Crossref