Proteomics enables systematic, context-dependent characterization of the proteome, and has emerged as a cornerstone of precision cancer medicine. Although the systematical analysis of molecular profiling has transformed oncology over the past two decades, substantial heterogeneity in therapeutic responses still persists among patients with similar genetic alterations, highlighting the limitations of static genomic information. By directly interrogating signaling pathways and regulatory networks of proteins and post-translational modifications (PTMs) that drive tumor initiation, progression, and therapy resistance, proteomics bridges the gap between genomic alterations and phenotypic outcomes. Recent advances in mass spectrometry have enabled low-cost, high-throughput, and high-resolution proteomics from bulk to single cells, providing unprecedented insights into tumor heterogeneity. Integrative analysis of multi-omics, including genomics, transcriptomics and proteomics data, facilitates the construction of multidimensional molecular landscapes that reveal novel biomarkers and therapeutic targets. In this review, we summarize recent advances in proteomics-based biomarker discovery, highlight emerging single-cell and spatial proteomics technologies, and discuss future directions for integrating multi-omics, clinical information, and artificial intelligence to accelerate clinical translation.

The development of oncology therapeutics is currently impeded by exorbitant costs, protracted timelines, and high clinical attrition rates stemming from the inherent complexity of tumor biology. Artificial Intelligence (AI) is transforming oncology drug discovery, shifting the paradigm from trial-and-error experimentation to one of data-driven rational design. In this paper, we review recent AI advances in four key areas. First, regarding Target Identification, we examine how multi-omics integration and deep learning uncover novel vulnerabilities, such as synthetic lethal pairs and immune checkpoints. Second, we analyze the evolution of Virtual Screening, moving from classical docking to graph neural networks that efficiently explore vast chemical spaces. Third, we highlight the shift toward Generative Molecular Design, where AI models create de novo small molecules, protein binders, and nucleic acid therapeutics with tailored functional properties. Fourth, we discuss AI applications in Preclinical Evaluation for predicting toxicity and efficacy. Finally, we critically assess current challenges—including data standardization deficits and the “black box” nature of deep learning—and propose emerging strategies, such as automated design-make-test workflows, to bridge the gap between computational prediction and clinical reality.

Colorectal cancer (CRC) ranks among the leading malignancies globally in both incidence and mortality. Treatment failure and disease recurrence are largely attributable to significant heterogeneity and acquired resistance to current therapies. Recent studies have extensively demonstrated that the initiation, progression, and recurrence of CRC are closely associated with the malignancy of intestinal stem cells (ISCs) and their derived cancer stem cells (CSCs). CSCs possess the characteristics of sustained self-renewal and multi-potent differentiation, constituting a key cellular population that sustains tumor growth, metastasis and drug resistance. Concurrently, CSCs evade the host immune system by reducing tumor antigen presentation, secreting immunosuppressive factors, and remodeling tumor microenvironment, thereby significantly limiting the clinical efficacy of immunotherapy. Consequently, immunotherapeutic strategies targeting ISCs and CSCs have emerged as a pivotal research direction for precision treatment of CRC. This paper systematically reviews recent advances in this field, discussing vaccine strategies based on CSC-specific antigens, bispecific antibodies (BsAbs) and antibody-drug conjugates (ADCs), CAR-T cells, and multimodal therapeutic approaches. Further, this paper summarizes the application of multi-omics technologies, spatial biology, and organoid models in elucidating the plasticity and drug resistance mechanisms of CSCs. We also discuss the potential role of gut microbial regulation in enhancing immunotherapy response. In summary, comprehensive immunotherapy strategies targeting ISCs and their ecological niches hold promise for overcoming current treatment bottlenecks in CRC, providing new theoretical foundations and practical pathways towards achieving long-term disease control.