Jornal de Patologia Médica e Cirúrgica

Jornal de Patologia Médica e Cirúrgica
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ISSN: 2472-4971

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Stroma-High Lymph Node Involvement Predicts Poor Survival More Accurately for Patients with Stage III Colon Cancer

Gabi W van Pelt, Torben F Hansen, Esther Bastiaannet, Sanne Kjær-Frifeldt, J Han JM van Krieken, Rob AEM Tollenaar, Flemming B Sørensen, Wilma E Mesker

Objective: The tumor microenvironment has ample impact on the behavior of the malignant process in colon cancer (CC). Patients with a high percentage of stroma within the primary tumor, determined by the tumor-stroma ratio (TSR), have a poor prognosis. In metastatic lymph nodes from patients with stage III CC, the TSR is heterogeneous, but the impact on patients’ prognosis is unknown.
Methods: Haematoxylin and eosin stained tissue slides of primary tumor (PT) and associated lymph nodes (LNs) metastases from 102 patients with stage III CC were analyzed for the TSR. Stroma-high (>50% stroma) and stromalow (≤ 50% stroma) groups were evaluated with respect to disease free survival (DFS).
Results: Of 102 analyzed primary tumors, 47 (46.1%) scored as stroma-high and 55 (53.9%) as stroma-low. In total, 33 patients had at least one stroma-high LN and 69 patients had one or more stroma-low LNs. Interestingly, 28 patients (27.5%) had both stroma-high and stroma-low LNs, but in another 44 cases the TSR between PT and LNs differed: 29 patients had a stroma-high PT with stroma-low LNs, while 15 patients displayed the opposite. As a result of the combination of the TSR analysis of the PT and the involved metastatic LNs, 62 patients (60.8%) were classified as stroma-high and 40 (39.2%) as stroma-low, restaging 14.7% of the patients to stroma-high with a significantly worse 5-year DFS compared to stroma-low patients (59% vs. 82%, HR=2.83 (95%CI 1.34–5.97), P=0.006). In multivariate analysis, the TSR retained its independent prognostic impact (HR=2.85 (95%CI 1.33-6.10), P=0.007).
Conclusion: The presence of abundant stroma in metastatic LNs from patients with stage III CC adds to the prognostic information learned from the primary tumor independently, and supports selective patient treatment.

Isenção de responsabilidade: Este resumo foi traduzido com recurso a ferramentas de inteligência artificial e ainda não foi revisto ou verificado.
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