Resistance to immunotherapy poses a significant challenge in the treatment of colorectal cancer (CRC), and the underlying mechanisms are not fully understood. Recent studies have implicated PFKFB3, a crucial glycolytic enzyme, in shaping the tumor microenvironment in CRC. Our study aimed to systematically study the role of PFKFB3 in CRC. Bioinformatic analysis revealed that PFKFB3 expression is notably elevated in CRC tissues compared to normal counterparts. In vivo experiments confirmed that suppressing PFKFB3 reduces the tumorigenesis of CRC. We identified multiple cancer-associated pathways positively correlated with high expression of PFKFB3, such as epithelial-mesenchymal transition (EMT), hypoxia, KRAS signaling, angiogenesis, PI3K/AKT/mTOR, Hedgehog, and Notch pathways. Additionally, PFKFB3 exhibited significant correlations with various immune-related pathways, including complement, IL-2/STAT5, IL-6/JAK/STAT3, IFN-α/IFN-γ, TGF-β, and TNF-α/NF-κB, as well as several immunosuppressive cell markers found in regulatory T cells (CCR8, TGFB1, STAT5B, FOXP3), M2 macrophages (CD163, VSIG4, MS4A4A), T cell exhaustion markers (CTLA-4, PDCD1, LAG3), and PD-L1. Intriguingly, increased PFKFB3 expression was observed in PD-L1 blockade-resistant patients and was associated with shorter overall survival. In a nutshell, PFKFB3 plays an important role in CRC tumorigenesis and resistance to immunotherapy. Targeting PFKFB3 inhibits tumor formation and enhances the efficacy of immunotherapy. Our findings underscore the functions of PFKFB3 in CRC, shedding light on both cancer-related and immunosuppressive pathways.

Colitis-associated cancer (CAC) is closely related to chronic inflammation, whose underlying molecular mechanism, however, has not been elaborated comprehensively. In the current study, an investigation was conducted on the role of autophagy in the initiation and progression of azoxymethane (AOM)/dextran sulfate sodium (DSS)-induced colon tumors, a mouse model for CAC in humans. Mice with the intestinal epithelial cell (IEC)-specific deletion of the autophagy-related gene 7 (Atg7) saw a significant decrease in tumor number, burden, and risk of high-grade dysplasia. The autophagy deficiency of IECs resulted in the accumulation of T cells, especially CD8⁺ T lymphocytes in colon lamina propria. Furthermore, it was found that autophagy protects against DSS-induced intestinal injury through maintaining epithelial barrier function and promoting the survival and proliferation of IECs. Mechanistically, autophagy in IECs enhanced the activation of epithelial STAT3/ERK to promote the survival and proliferation of colonic epithelial cells during the development of CAC. Therefore, the findings unveil the essential role of autophagy in activating the processes of colonic protection, regeneration, and tumorigenesis.

Cancer is a global health threat, with its treatment modalities transitioning from single therapies to integrated treatments. This paper systematically explores the key technological systems in modern cancer treatment and their application value. Modern cancer treatment relies on four core technological pillars: omics, bioinformatics, network pharmacology (NP), and molecular dynamics (MD) simulation. Omics technologies integrate various biological molecular information, such as genomics, proteomics and metabolomics, providing foundational data support for drug research. But the differences in data and the challenges of integrating it often lead to biased predictions, and that’s a big limitation for this technology. Bioinformatics utilizes computer science and statistical methods to process and analyze biological data, aiding in the identification of drug targets and the elucidation of mechanisms of action. It is important to note that the prediction accuracy largely depends on the algorithm chosen. Consequently, this dependence may affect the reliability of the research results. NP, based on systems biology, studies drug-target-disease networks, revealing the potential for multitargeted therapies. That said, this method may overlook important aspects of biological complexity, such as variations in protein expression. This oversight can lead to overestimating the effectiveness of multi-targeted therapies, resulting in false positives in efficacy assessments, which somewhat limits its practical usefulness. MD simulation examines how drugs interact with target proteins by tracking atomic movements, thus enhancing the precision of drug design and optimization. Nevertheless, this technology faces practical challenges, such as high computational costs and sensitivity of model accuracy to the parameters of the force field. The synergistic application of these technologies significantly shortens the drug development cycle and promotes precision and personalization in cancer therapy, bringing new hope to patients for successful treatment. However, researchers still face challenges like the variability of data. Future efforts need to use Artificial Intelligence (AI) to establish standardized data integration platforms, develop multimodal analysis algorithms, and strengthen preclinical-clinical translational research to drive breakthrough advancements in cancer treatment. With the ongoing technological improvements, the vision of personalized medicine—tailored treatments based on individual patient characteristics—will gradually be realized, significantly enhancing treatment efficacy and improving patients’ quality of life.

Gastrointestinal (GI) tumors represent a significant global health burden and are among the leading causes of cancer-related mortality worldwide. their drug resistance is one of the major challenges in cancer therapy. In recent years, epigenetic modifications, especially N6-methyladenosine (m6A) RNA modifications, have become a hot research topic. m6A modification plays an important role in gene expression and cancer progression by regulating RNA splicing, translation, stability, and degradation, which are regulated by “writers,” “erasers” and “readers.” In GI tumors, resistance to chemotherapy, targeted therapy, and immunotherapy is closely associated with m6A RNA modification. Therefore, the molecular mechanism of m6A modification and its targeted drug development provide new therapeutic strategies for overcoming drug resistance and therapeutic efficacy in GI tumors. In this review, the biological functions of m6A were explored, the specific resistance mechanisms of m6A in different types of GI tumors were explored, new ideas and targets for future treatment resistance were identified, and the limitations of this field were highlighted.

Background In locally advanced rectal cancer (LARC), the optimal sequence of neoadjuvant chemotherapy in relation to neoadjuvant chemoradiotherapy and before total mesorectal excision is unknown. Methods A total of 426 LARC patients, treated with neoadjuvant chemoradiotherapy followed by total mesorectal excision, between January 2010 and December 2018, were studied retrospectively. Patients were divided into induction and consolidation chemotherapy groups. Overall, disease-free, locoregional relapse-free, and distant metastasis-free survival rates for the 2 groups were compared. Multivariate analysis hazard ratios (HR) with 95% confidence intervals (CI) to identify survival predictors. Results Median follow-up was 37 (range, 7–162) months. The 3-year overall, disease-free, locoregional relapse-free, and distant metastasis-free survival rates were 93.8%, 71.6%, 93.5%, and 74.4%, respectively. For those receiving either induction or consolidation chemotherapy, 3-year disease-free survival rates were 82.5% and 67.7%, respectively (P = 0.021), distant metastasis-free rates were 85.4% and 70.8%, respectively (P = 0.024), and both overall and locoregional relapse-free survival rates did not differ significantly. Absence of neural invasion was an independent predictor of disease-free (HR = 0.49, 95% CI 0.25–0.97, P = 0.04) and distant metastasis-free (HR = 0.49, 95% CI 0.25–0.98, P = 0.04) survival. Both ypTN stage III (vs.0-II) and consolidation (vs. induction) chemotherapy were independent predictors of disease relapse (HR = 1.95, 95% CI 1.47–2.58, P < 0.001; HR = 1.68, 95% CI 1.01–2.79, P = 0.046; respectively) and distant metastasis (HR = 2.04, 95% CI 1.51–2.76, P < 0.001; HR = 1.75, 95% CI 1.03–2.99, P = 0.04; respectively). Conclusions LARC patients receiving neoadjuvant chemoradiotherapy and total mesorectal excision had better disease-free and distant metastasis-free survival, with induction rather than consolidation neoadjuvant chemotherapy.

The YTH domain family protein 1 (YTHDF1), a key N1-methyladenosine (m¹A) modification reader protein, has been significantly associated with the proliferation and invasion of various malignant cells. However, knowledge of the precise role of YTHDF1 in hepatocellular carcinoma (HCC) and the molecular mechanisms involving RNA m¹A modification remains incomplete. This study integrated HCC data from The Cancer Genome Atlas (TCGA), tissue microarray (TMA), in vitro functional experiments, and in vivo xenograft models to explore the regulatory role of YTHDF1-mediated RNA m¹A modification in HCC. Bioinformation analysis and TMA revealed that YTHDF1 expression is significantly upregulated in HCC tissues and correlated with poor prognosis of HCC patients. Functional experiments demonstrated that YTHDF1 knockdown markedly suppresses the proliferation and invasion of HCC cells, which was further confirmed by in vivo xenograft models. Integrated m¹A methylated RNA immunoprecipitation sequencing (MeRIP-seq), MeRIP-qPCR, transcriptome-sequencing (RNA-seq) and RNA immunoprecipitation-qPCR (RIP-qPCR) showed the distribution change of m¹A modifications after YTHDF1 knockdown, identified LRP5 as the downstream target of YTHDF1, and confirmed the direct binding of YTHDF1 to LRP5 mRNA. The Actinomycin D and dual-luciferase reporter assays confirmed that YTHDF1 can affect the stability of LRP5 mRNA. Further in vitro experiments indicated that YTHDF1 knockdown reduces the protein levels of key Wnt pathway components and inhibits the cell malignant phenotype, while LRP5 overexpression reverses the effects induced by YTHDF1 knockdown. In conclusion, YTHDF1-mediated RNA m¹A modifications facilitate the malignant progression of HCC by modulating the LRP5/Wnt/β-catenin signaling pathway.