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Review
. 2018 Feb;472(2):175-186.
doi: 10.1007/s00428-017-2232-x. Epub 2017 Sep 16.

Tumor regression grading of gastrointestinal cancers after neoadjuvant therapy

Rupert Langer  1 , Karen Becker  2
Affiliations
Free article
Review

Tumor regression grading of gastrointestinal cancers after neoadjuvant therapy

Rupert Langer et al. Virchows Arch. 2018 Feb.
Free article

Abstract

Neoadjuvant therapy has been successfully introduced in the treatment of locally advanced gastrointestinal malignancies, particularly esophageal, gastric, and rectal cancers. The effects of preoperative chemo- or radiochemotherapy can be determined by histopathological investigation of the resection specimen following this treatment. Frequent histological findings after neoadjuvant therapy include various amounts of residual tumor, inflammation, resorptive changes with infiltrates of foamy histiocytes, foreign body reactions, and scarry fibrosis. Several tumor regression grading (TRG) systems, which aim to categorize the amount of regressive changes after cytotoxic treatment in primary tumor sites, have been proposed for gastroesophageal and rectal carcinomas. These systems primarily refer to the amount of therapy-induced fibrosis in relation to the residual tumor (e.g., the Mandard, Dworak, or AJCC systems) or the estimated percentage of residual tumor in relation to the previous tumor site (e.g., the Becker, Rödel, or Rectal Cancer Regression Grading systems). TRGs provide valuable prognostic information, as in most cases, complete or subtotal tumor regression after neoadjuvant treatment is associated with better patient outcomes. This review describes the typical histopathological findings after neoadjuvant treatment, discusses the most commonly used TRG systems for gastroesophageal and rectal carcinomas, addresses the limitations and critical issues of tumor regression grading in these tumors, and describes the clinical impact of TRG.

Keywords: Esophageal cancer; Gastric cancer; Histopathology; Neoadjuvant therapy; Rectal cancer; Tumor regression grading.

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