A gene panel to predict response to adjuvant chemotherapy and risk of recurrence in colorectal cancer

Malignancy Spectrum Pub Date : 2025-06-29 DOI:10.1002/msp2.70009

Steffie Urmila Avanthi, Ravikanth Vishnubhotla, Mitnala Sasikala, Guduru Venkat Rao, Rebala Pradeep, Sanjeev Marigowda Patil, Anuradha Sekaran, Jain Aviral, Sonali Mondkar, Nageshwar Reddy Duvvur

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Abstract

Background

Chemotherapy is the mainstay to treat metastatic colorectal cancer (CRC). However, a sizeable proportion of patients do not respond to treatment, which leads to the recurrence of disease. This study was carried out to identify reliable gene expression-based marker(s) to predict the response to chemotherapy and the risk of recurrence.

Methods

This prospective study involved the collection of tumor tissues (n = 100) and normal tissues (n = 10) from CRC patients who primarily underwent surgical treatment. Global gene expression profiles were generated on microarray (Affymetrix; n = 5) and the next-generation sequencing (NGS) (Illumina; n = 20) platforms. Patients were classified as responders (n = 13; complete response with no relapse) or non-responders (n = 12; recurrence of disease leading to death). Common dysregulated genes identified from both platforms were replicated in an independent set (n = 75; quantitative real-time polymerase chain reaction (qRT-PCR)). The area under the curve (AUC) was generated, and a combinatorial analysis was performed.

Results

A total of 193 and 1351 genes were dysregulated in microarray and NGS datasets, respectively. Of the top common genes (PTGIS, LYVE1, C3, C7, CXCL12, CEACAM6, MUC13, and ST14) that were selected for replication, upregulation of five genes (PTGIS, C3, C7, LYVE1, and CXCL12) were associated with the non-responder group in validation set. Combinatorial analysis and comparison of AUC identified a significant increase (p = 0.03) in AUC by 15.2% (95% confidence interval (CI): 0.01−0.29) for two genes (PTGIS and LYVE1). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 88.9%, 100%, 100%, and 95.6%, respectively.

Conclusion

Assessing upregulation of the PTGIS and LYVE1 genes enables identification of individuals who may not respond to adjuvant chemotherapy and the risk of recurrence. The addition of drugs targeting these genes may improve response and benefit the patients.

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预测结直肠癌对辅助化疗的反应和复发风险的基因面板

化疗是治疗转移性结直肠癌（CRC）的主要手段。然而，相当大比例的患者对治疗没有反应，从而导致疾病复发。本研究旨在确定可靠的基于基因表达的标志物，以预测对化疗的反应和复发风险。方法本前瞻性研究收集了主要接受手术治疗的结直肠癌患者的肿瘤组织（n = 100）和正常组织（n = 10）。在微阵列上生成全局基因表达谱(Affymetrix；n = 5)和下一代测序（NGS） (Illumina；N = 20)个平台。将患者分为反应者(n = 13；完全缓解，无复发)或无反应(n = 12；疾病复发导致死亡)。从两个平台中鉴定出的常见失调基因在一个独立的集合中被复制(n = 75；实时定量聚合酶链反应（qRT-PCR）。生成曲线下面积（AUC），并进行组合分析。结果在微阵列和NGS数据集中分别有193个和1351个基因表达异常。在选择复制的最常见基因（PTGIS、LYVE1、C3、C7、CXCL12、CEACAM6、MUC13和ST14）中，验证集中无应答组中有5个基因（PTGIS、C3、C7、LYVE1和CXCL12）表达上调。组合分析和AUC比较发现，两个基因（PTGIS和LYVE1）的AUC显著增加（p = 0.03） 15.2%（95%可信区间（CI）： 0.01 ~ 0.29）。敏感性为88.9%，特异性为100%，阳性预测值为100%，阴性预测值为95.6%。结论评估PTGIS和LYVE1基因的上调有助于识别可能对辅助化疗无反应的个体和复发风险。添加靶向这些基因的药物可能会改善反应并使患者受益。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Malignancy Spectrum

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