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Glioma, with its heterogeneous microenvironments and genetic subtypes, presents substantial challenges for treatment prediction and development. We integrated 3D bioprinting and multi-algorithm machine learning as a novel approach to enhance the assessment and understanding of glioma treatment responses and microenvironment characteristics. The bioprinted patient-derived glioma tissues successfully recapitulated molecular properties and drug responses of native tumors. We then developed GlioML, a machine learning workflow incorporating nine distinct algorithms and a weighted ensemble model that generated robust gene expression-based predictors, each reflecting the diverse action mechanisms of various compounds and drugs. The ensemble model superseded the performance of all individual algorithms across diverse in vitro systems, including sphere cultures, complex 3D bioprinted multicellular models, and 3D patient-derived tissues. By integrating bioprinting, the evaluative scope of the treatment expanded to T cell-related therapy and anti-angiogenesis targeted therapy. We identified promising compounds and drugs for glioma treatment and revealed distinct immunosuppressive or angiogenic myeloid-infiltrated tumor microenvironments. These insights pave the way for enhanced therapeutic development for glioma and potentially for other cancers, highlighting the broad application potential of this integrative and translational approach.

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Internal N6-methyladenosine (m6A) modifications are among the most abundant modifications of messenger RNA, playing a critical role in diverse biological and pathological processes. However, the functional role and regulatory mechanism of m6A modifications in the immune response to Mycobacterium tuberculosis infection remains unknown. Here, we report that methyltransferase-like 14 (METTL14)-dependent m6A methylation of NAPDH oxidase 2 (Nox2) mRNA was crucial for the host immune defense against M. tuberculosis infection and that M. tuberculosis-secreted antigen EsxB (Rv3874) inhibited METTL14-dependent m6A methylation of Nox2 mRNA. Mechanistically, EsxB interacted with p38 MAP kinase and disrupted the association of TAB1 with p38, thus inhibiting the TAB1-mediated autophosphorylation of p38. Interaction of EsxB with p38 also impeded the binding of p38 with METTL14, thereby inhibiting the p38-mediated phosphorylation of METTL14 at Thr72. Inhibition of p38 by EsxB restrained liquid–liquid phase separation (LLPS) of METTL14 and its subsequent interaction with METTL3, preventing the m6A modification of Nox2 mRNA and its association with the m6A-binding protein IGF2BP1 to destabilize Nox2 mRNA, reduce ROS levels, and increase intracellular survival of M. tuberculosis. Moreover, deletion or mutation of the phosphorylation site on METTL14 impaired the inhibition of ROS level by EsxB and increased bacterial burden or histological damage in the lungs during infection in mice. These findings identify a previously unknown mechanism that M. tuberculosis employs to suppress host immunity, providing insights that may empower the development of effective immunomodulators that target M. tuberculosis.

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Adenine base editors (ABEs) and cytosine base editors (CBEs) enable the single nucleotide editing of targeted DNA sites avoiding generation of double strand breaks, however, the genomic features that influence the outcomes of base editing in vivo still remain to be characterized. High-throughput datasets from lentiviral integrated libraries were used to investigate the sequence features affecting base editing outcomes, but the effects of endogenous factors beyond the DNA sequences are still largely unknown. Here the base editing outcomes of ABE and CBE were evaluated in mammalian cells for 5012 endogenous genomic sites and 11,868 genome-integrated target sequences, with 4654 genomic sites sharing the same target sequences. The comparative analyses revealed that the editing outcomes of ABE and CBE at endogenous sites were substantially different from those obtained using genome-integrated sequences. We found that the base editing efficiency at endogenous target sites of both ABE and CBE was influenced by endogenous factors, including epigenetic modifications and transcriptional activity. A deep-learning algorithm referred as BE_Endo, was developed based on the endogenous factors and sequence information from our genomic datasets, and it yielded unprecedented accuracy in predicting the base editing outcomes. These findings along with the developed computational algorithms may facilitate future application of BEs for scientific research and clinical gene therapy.

Tumor cells are usually considered defective in mitochondrial respiration, but human non-small cell lung cancer (NSCLC) tumor tissues are shown to have enhanced glucose oxidation relative to adjacent benign lung. Here, we reported that oncoprotein cancerous inhibitor of protein phosphatase 2A (CIP2A) inhibited glycolysis and promoted oxidative metabolism in NSCLC cells. CIP2A bound to pyruvate kinase M2 (PKM2) and induced the formation of PKM2 tetramer, with serine 287 as a novel phosphorylation site essential for PKM2 dimer-tetramer switching. CIP2A redirected PKM2 to mitochondrion, leading to upregulation of Bcl2 via phosphorylating Bcl2 at threonine 69. Clinically, CIP2A level in tumor tissues was positively correlated with the level of phosphorylated PKM2 S287. CIP2A-targeting compounds synergized with glycolysis inhibitor in suppressing cell proliferation in vitro and in vivo. These results indicated that CIP2A facilitates oxidative phosphorylation by promoting tetrameric PKM2 formation, and targeting CIP2A and glycolysis exhibits therapeutic potentials in NSCLC.

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