BACKGROUND: The basement membrane (BM), an omnipresent extracellular matrix, plays a pivotal role as a physiological element in the process of tumor metastasis. However, given the heterogeneity of colorectal cancer (CRC), prognosis is challengingly predictive. Therefore, we aim to construct a prognostic model using BM-associated genes to assess patient prognosis and clinical drug treatment effects. METHOD: The Non-negative Matrix Factorization (NMF) algorithm leverages the characteristics or categories of matrix rows and columns to achieve BMAG molecular classification and further develop a model for predicting patient prognosis. ssGSEA quantified the relatively abundance of 13 immune functionalities and 16 immune cell typologies. To predict the efficacy of immunotherapy, a comprehensive investigation was conducted on the correlations between riskScores and key factors such as TME, immune checkpoints, and MMR-related genes. The CCK8 method, plate cloning method and Cell Apoptosis Assessment were used to evaluate the ability of NELL2 to affect the proliferation. RESULT: We developed a powerful riskScore to predict colorectal cancer prognosis and effectively differentiate the tumor microenvironment. In clinical practice, this riskScore can also be utilized to further assess patient prognosis, thereby facilitating personalized treatment strategies. In addition, downregulation of NELL2 expression inhibits CRC cell proliferation. CONCLUSION: In summary, we constructed a novel riskScore using BMAG for predicting prognosis in patients with CRC and explored the efficacy of this riskScore in predicting patient response to clinical drug therapy. Most importantly, we have identified the oncogenic role of NELL2 in CRC. By inhibiting NELL2, we can further suppress the initiation and progression of CRC.