Predictive Value of CD3, CD8, CD45RO Expression in Stage II/III Colorectal Cancer

Theodoros Argyropoulos, P. Foukas, Effrosyni Karakitsou, Stefanos Konstantoudakis, M. Kefala, Nektarios Koufopoulos, N. Machairas, I. Panayiotides, K. Triantafyllou
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Abstract

This article describes how colorectal carcinomas (CRC) are the fourth most frequently diagnosed cancer. However, despite advances in specific treatment, approximately 40% to 50% of patients have disease recurrence following potentially curative surgery, highlighting the demand for improvement of staging, treatment and prognosis. Inflammatory infiltration composed of lymphocytes is a common feature found in neoplasms and studies have indicated an association between tumor immune infiltrates and favorable disease outcomes. The aim of this article is to assess the association of tumor infiltrating lymphocytes and DNA damage response expression levels with disease outcome and survival in stage II and III CRC. The authors examined the prognostic value of immunological biomarkers using 5-year follow-up data to train an Artificial Neural Network (ANN) designed for the prediction of personalized risk. Data for three biomarkers which were found significant were subsequently used to train the ANN which predicted 5-year survival with 72.9% sensitivity and 68.8% specificity.
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CD3、CD8、CD45RO表达对Ⅱ/Ⅲ期癌症结直肠癌的预测价值
这篇文章描述了结直肠癌(CRC)如何成为第四大最常诊断的癌症。然而,尽管在特异性治疗方面取得了进展,但大约40%至50%的患者在可能治愈的手术后出现疾病复发,这突出了对改善分期、治疗和预后的需求。由淋巴细胞组成的炎症浸润是肿瘤的共同特征,研究表明肿瘤免疫浸润与良好的疾病预后之间存在关联。本文的目的是评估肿瘤浸润淋巴细胞和DNA损伤反应表达水平与II期和III期CRC的疾病结局和生存的关系。作者使用5年随访数据来训练用于预测个性化风险的人工神经网络(ANN),研究了免疫生物标志物的预后价值。随后,将发现具有显著意义的三个生物标志物的数据用于训练人工神经网络,该人工神经网络预测5年生存率的灵敏度为72.9%,特异性为68.8%。
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