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Surgical resection remains the cornerstone of treatment for many solid tumors, offering the best chance for cure. However, despite successful surgery, cancer recurrence remains a significant challenge, with many patients experiencing relapse even after achieving apparent remission. Predicting which patients are at high risk for recurrence after surgery is crucial for optimizing post-surgical management and tailoring individualized follow-up protocols. Historically, cancer recurrence was assessed through clinical monitoring, imaging studies, and serum tumor markers. While these approaches are valuable, they often lack sensitivity and specificity. In recent years, there has been increasing interest in identifying molecular biomarkers that can more accurately predict recurrence and guide decisions regarding adjuvant therapy or extended surveillance. This article explores the different types of post-surgical biomarkers used to predict cancer recurrence and examines their clinical applications and limitations [1].

Types of Post-Surgical Biomarkers

Biomarkers can be classified into several categories based on the type of molecular information they provide. Genetic biomarkers, such as mutations, amplifications, and deletions in oncogenes and tumor suppressor genes, are among the most studied post-surgical markers. For example, in colorectal cancer, the presence of KRAS mutations has been shown to correlate with recurrence risk, influencing decisions regarding chemotherapy [2]. Similarly, mutations in TP53 and microsatellite instability (MSI) have been associated with poor prognosis in various cancers [3]. Proteomic biomarkers involve the identification of proteins or protein signatures that are indicative of residual disease or potential recurrence. Circulating tumor cells (CTCs) and tumor-derived extracellular vesicles (TEVs) are examples of proteomic biomarkers that can provide real-time insights into the metastatic potential of tumors after surgery. Elevated levels of CTCs after surgery have been shown to correlate with higher recurrence rates in cancers such as breast and prostate cancer [4]. Epigenetic biomarkers refer to modifications in DNA, such as DNA methylation and histone modifications that can alter gene expression without changing the underlying genetic code. In cancers such as gastric and lung cancer, changes in DNA methylation patterns have been linked to a higher risk of recurrence after surgery. These epigenetic changes can be detected in blood or tissue samples, providing a non-invasive means of monitoring patients post-surgically [5].

The Role of Circulating Tumor DNA (ctDNA)

Circulating tumor DNA (ctDNA) is one of the most promising post-surgical biomarkers for detecting minimal residual disease and predicting recurrence. ctDNA consists of small fragments of DNA released into the bloodstream by tumor cells. It has gained significant attention due to its ability to detect genetic mutations and other alterations associated with the tumor. In cancers like colorectal, breast, and lung cancer, ctDNA levels measured after surgery have been shown to correlate with the risk of recurrence. For instance, studies have demonstrated that patients with detectable ctDNA after surgery for colorectal cancer have a significantly higher risk of recurrence compared to those without detectable ctDNA. As ctDNA can be assessed using liquid biopsy, it offers a non-invasive and real-time method for monitoring recurrence risk without the need for invasive tissue biopsies [6]. The potential of ctDNA in predicting recurrence is further supported by its ability to detect minimal residual disease (MRD), which refers to the presence of small numbers of cancer cells that are below the detection threshold of conventional imaging or histopathology. Monitoring ctDNA levels post-surgery allows for early detection of recurrence, enabling more timely intervention and potentially improving survival rates [7].

Proteomics and Tumor Markers in Post-Surgical Surveillance

Proteomics involves the analysis of the entire set of proteins present in a sample, providing valuable insights into the biological processes underlying cancer recurrence. Proteomic biomarkers, such as carcinoembryonic antigen (CEA) and cancer antigen 125 (CA-125), have been used for monitoring recurrence in cancers like colorectal and ovarian cancer, respectively. However, these biomarkers are not always reliable on their own, as they can be influenced by a variety of factors such as inflammation and benign conditions. In addition to traditional tumor markers, advancements in mass spectrometry and other proteomic technologies have enabled the discovery of new protein signatures that may be more specific for recurrence. For example, research has identified panels of proteins in the blood or urine that can predict recurrence in bladder cancer, helping to identify patients at higher risk of relapse after surgery [8].

Challenges in Implementing Biomarker-Based Recurrence Prediction

Despite the promising potential of post-surgical biomarkers, several challenges remain in their clinical application. One major issue is the lack of standardized assays for many of these biomarkers, which can result in variability in detection and interpretation. Additionally, many biomarkers, particularly ctDNA and proteomic markers, are still in the research phase and have not yet been fully validated for routine clinical use [9]. Another challenge is the heterogeneity of cancer and its biological processes. A single biomarker may not be sufficient to predict recurrence across all patients or cancer types, and combining multiple biomarkers may be necessary for more accurate predictions. The development of multi-biomarker panels that integrate genetic, proteomic, and epigenetic information may improve the predictive accuracy and clinical utility of these tests [10].

Conclusion

Post-surgical biomarkers hold great promise in predicting cancer recurrence, enabling more personalized and timely treatment decisions. By integrating genetic, proteomic, and epigenetic markers into clinical practice, healthcare providers can identify patients at higher risk of recurrence, tailor surveillance strategies, and optimize adjuvant treatments. However, further research and validation are needed to standardize these biomarkers and overcome the challenges of implementation. As the field of molecular oncology continues to evolve, the integration of post-surgical biomarkers into routine clinical practice will likely become a cornerstone of personalized cancer care.

1. Vennix S, Pelzers L, Bouvy N, Beets GL, Pierie JP, et al. (2014). Cochrane Database Syst 005200.

, ,

2. Nunobe S, Hiki N, Fukunaga T, Tokunaga M, Ohyama S, et al. (2008)World J Surg32: 1466-1472.

, ,

3. Osborne MP (2007). Lancet Oncol 8: 256-265.

, ,

4. Fisher B (1977). World J Surg 1: 327-330.

, ,

5. Heald RJ, Husband EM, Ryall RD (1982).Br J Surg 69: 613-616.

, ,

6. S酶ndenaa K, Quirke P, Hohenberger W, Sugihara K, Kobayashi H, et al. ( 2014). Int J Colorectal Dis 29: 419-428.

, ,

7. Dogan NU, Dogan S, Favero G, K枚hler C, Dursun P, et al. (2019). J Oncol 3415630.

, ,

8. Deijen CL, Vasmel JE, de Lange-de Klerk ESM, Cuesta MA, Coene PLO, et al. ( 2017). Surg Endosc. 31: 2607-2615.

, ,

9. Dewys WD, Begg C, Lavin PT, Band PR, Bennett JM, et al. (1980)Am J Med 69: 491-497.

, ,

10. Correia MI, Waitzberg DL (2003)Clin Nutr22: 235-239.

, ,