Colorectal cancer is frequently diagnosed in advanced stages, highlighting the need for developing approaches for early detection. Liquid biopsy using cell-free DNA (cfDNA) fragmentomics is a promising approach, but the clinical application is hindered by complexity and cost. This study aimed to develop an integrated model using cfDNA fragmentomics for accurate, cost-effective early-stage colorectal cancer detection. Plasma cfDNA was extracted and sequenced from a training cohort of 360 participants, including 176 patients with colorectal cancer and 184 healthy controls. An ensemble stacked model comprising five machine learning models was employed to distinguish patients with colorectal cancer from healthy controls using five cfDNA fragmentomic features. The model was validated in an independent cohort of 236 participants (117 patients with colorectal cancer and 119 controls) and a prospective cohort of 242 participants (129 patients with colorectal cancer and 113 controls). The ensemble stacked model showed remarkable discriminatory power between patients with colorectal cancer and controls, outperforming all base models and achieving a high area under the receiver operating characteristic curve of 0.986 in the validation cohort. It reached 94.88% sensitivity and 98% specificity for detecting colorectal cancer in the validation cohort, with sensitivity increasing as the cancer progressed. The model also demonstrated consistently high accuracy in within-run and between-run tests and across various conditions in healthy individuals. In the prospective cohort, it achieved 91.47% sensitivity and 95.58% specificity. This integrated model capitalizes on the multiplex nature of cfDNA fragmentomics to achieve high sensitivity and robustness, offering significant promise for early colorectal cancer detection and broad patient benefit. Significance: The development of a minimally invasive, efficient approach for early colorectal cancer detection using advanced machine learning to analyze cfDNA fragment patterns could expedite diagnosis and improve treatment outcomes for patients. See related commentary by Rolfo and Russo, p. 3128

Despite recent improvements in the comprehensive therapy of malignancy, metastatic colorectal cancer (mCRC) continues to have a poor prognosis. Notably, 5% of mCRC cases harbor Erb-B2 receptor tyrosine kinase 2 (ERBB2) alterations. ERBB2, commonly referred to as human epidermal growth factor receptor 2, is a member of the human epidermal growth factor receptor family of protein tyrosine kinases. In addition to being a recognized therapeutic target in the treatment of gastric and breast malignancies, it is considered crucial in the management of CRC. In this review, we describe the molecular biology of ERBB2 from the perspective of biomarkers for mCRC-targeted therapy, including receptor structures, signaling pathways, gene alterations, and their detection methods. We also discuss the relationship between ERBB2 aberrations and the underlying mechanisms of resistance to anti-EGFR therapy and immunotherapy tolerance in these patients with a focus on novel targeted therapeutics and ongoing clinical trials. This may aid the development of a new standard of care in patients with ERBB2-positive mCRC.

Essential membrane components and metabolites with a wide range of biological roles are both produced by cholesterol metabolism. Cell-intrinsic and cell-extrinsic stimuli alter cholesterol metabolism in the tumor microenvironment (TME), which in turn encourages colorectal carcinogenesis. Metabolites produced from cholesterol play intricate roles in promoting the development of colorectal cancer (CRC) and stifling immunological responses. By altering the extracellular matrix of the main tumor, redesigning its immunological environment, and altering its mechanical stiffness, cholesterol can encourage the epithelial-mesenchymal transition of the primary tumor, opening up a pathway for tumor metastasis. Its functions in TME remodeling and tumor prevention have been recently identified. In this review we address the function of cholesterol in TME remodeling and therapeutic techniques designed to block cholesterol metabolism, and discuss how combining these strategies with already available anti-CRC medicines can have combined effects and open up new therapeutic avenues.

Introduction: Reports of rectal neuroendocrine tumor (R-NET) are relatively rare. There is a lack of experience in how to accurately locate and resect metastatic lateral lymph nodes. Case presentation: We present a challenging case. The patient was diagnosed with rectal neuroendocrine tumor. After endoscopic submucosal dissection (ESD), this patient came to hospital for reexamination. The imaging results indicated the presence of left lateral lymph node metastasis, so total mesorectal excision (TME) plus lateral lymph node dissection(LLND) was performed. One year later, PET-CT was reexamined again, using a contrast agent targeted at somatostatin receptor. The result showed residual metastatic lymph nodes. We used nanocarbon combined with coil to accurately locate the metastatic lymph nodes and finally successfully resected the lymph node. The patient recovered and was discharged 5 days after the operation. Discussion: Surgery is the most effective method for treating rectal neuroendocrine tumors. However, it is still challenging to accurately detect and locate metastatic lymph nodes after surgery. 68Ga-DOTA-NOC is a special contrast agent that targets somatostatin receptors, and somatostatin receptors are highly expressed in NETs. Using it can clearly trace whether the lateral lymph nodes are metastasized. Nanocarbon localization has been used for the localization of various tumors. We combined it with coils and effectively located the metastatic lymph nodes. This localization method has great potential. Conclusion: Surgical resection is the most effective way to treat rectal neuroendocrine tumors. Nanocarbon combined with coils can effectively locate metastatic lymph nodes, which is helpful for accurate resection later. And 68Ga-DOTA-NOC can assist in detection of metastatic lymph nodes. Highlights: