Recent studies have highlighted the potential benefits of neoadjuvant chemotherapy (NAC) in colon cancer; however, its indication is generally limited to cases corresponding to pathological stage IIB or higher. Accurately identifying such high-risk cases before surgery remains challenging using conventional clinical diagnostics alone. Therefore, we hypothesized that integrating molecular biomarkers with preoperative clinical assessment could provide a more precise and sensitive evaluation of tumor aggressiveness. In this context, we focused on exosomal microRNAs, which are actively secreted from tumor cells and remain stable in circulation, and aimed to develop a machine learning-based biomarker panel. To achieve this, we initiated a multicenter study utilizing preoperative plasma samples to establish a reliable biomarker model for risk stratification and treatment decision-making in colon cancer.

Colon cancer remains one of the leading causes of cancer-related mortality worldwide, and despite advances in screening and surgical techniques, a substantial proportion of patients continue to experience disease recurrence after curative resection. For patients with pathological stage IIB or higher disease, adjuvant chemotherapy is routinely recommended due to their elevated recurrence risk. However, accurately identifying these biologically aggressive cases before surgery remains a major clinical challenge, as current imaging-based staging often underestimates tumor burden and fails to capture underlying malignant potential. This diagnostic gap has hindered the optimal implementation of neoadjuvant chemotherapy (NAC) in colon cancer.

To address this issue, the investigators established the EXPOSE study (Exosomal microRNA Signature for Pre-Operative Stage and Eligibility Evaluation), a multicenter translational research initiative aiming to develop and validate a noninvasive, biologically informed diagnostic assay capable of identifying patients with high-risk colon cancer-equivalent to pathological stage IIB or higher-who may benefit from NAC.

The EXPOSE study will proceed through three structured phases.

1. In the discovery phase, exosomal microRNAs will be profiled using comprehensive small RNA sequencing to identify key biomarkers reflecting tumor aggressiveness.
2. In the training phase, the investigators will quantify candidate microRNAs using RT-qPCR and integrate their expression patterns via machine-learning algorithms to construct a predictive model for high-risk disease.
3. Finally, in the validation phase, the model's reproducibility, diagnostic accuracy, and generalizability will be tested in an independent clinical cohort.

The final EXPOSE assay is expected to serve as a liquid biopsy-based tool for preoperative staging, enabling more precise identification of biologically advanced colon cancer cases. Upon completion, this study will deliver a rigorously validated diagnostic model that combines molecular and clinical data to guide neoadjuvant treatment decisions and enhance personalized care in colon cancer management.

Inclusion Criteria:

• Pathologically confirmed colon cancer (Stage I-IV, UICC TNM 8th edition)
• Underwent curative-intent resection (with or without perioperative therapy)
• Preoperative plasma (or serum) samples available
• Clinical and prognostic data available

Exclusion Criteria:

• No written informed consent
• Missing preoperative blood samples
• Missing survival/recurrence data
• Duplicate cases
• Non-adenocarcinoma histology

Colon cancer patients (Stage I-IV) from multiple institutions with preoperative serum or plasma samples and complete pathological staging.

Data collected for the study will be made available to others, including de-identified participant data, at publication, via a signed data access agreement and at the discretion of the investigators' approval of the proposed use of such data