New perspectives on predictive biomarkers of tumor response and their clinical application in preoperative chemoradiation therapy for rectal cancer

Nam Kyu Kim, Hyuk Hur

Research output: Contribution to journalReview article

21 Citations (Scopus)

Abstract

Preoperative chemoradiation therapy (CRT) is the standard treatment for patients with locally advanced rectal cancer (LARC) and can improve local control and survival outcomes. However, the responses of individual tumors to CRT are not uniform and vary widely, from complete response to disease progression. Patients with resistant tumors can be exposed to irradiation and chemotherapy that are both expensive and at times toxic without benefit. In contrast, about 60% of tumors show tumor regression and T and N down-staging. Furthermore, a pathologic complete response (pCR), which is characterized by sterilization of all tumor cells, leads to an excellent prognosis and is observed in approximately 10–30% of cases. This variety in tumor response has lead to an increased need to develop a model predictive of responses to CRT in order to identify patients who will benefit from this multimodal treatment. Endoscopy, magnetic resonance imaging, positron emission tomography, serum carcinoembryonic antigen, and molecular biomarkers analyzed using immunohistochemistry and gene expression profiling are the most commonly used predictive models in preoperative CRT. Such modalities guide clinicians in choosing the best possible treatment options and the extent of surgery for each individual patient. However, there are still controversies regarding study outcomes, and a nomogram of combined models of future trends is needed to better predict patient response. The aim of this article was to review currently available tools for predicting tumor response after preoperative CRT in rectal cancer and to explore their applicability in clinical practice for tailored treatment.

Original languageEnglish
Pages (from-to)1461-1477
Number of pages17
JournalYonsei medical journal
Volume56
Issue number6
DOIs
Publication statusPublished - 2015 Nov

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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