CYP3A5 unexpectedly regulates glucose metabolism through the AKT-TXNIP-GLUT1 axis in pancreatic cancer.

CYP3A5 is a cytochrome P450 (CYP) enzyme that metabolizes drugs and contributes to drug resistance in cancer. However, it remains unclear whether CYP3A5 directly influences cancer progression. In this report, we demonstrate that CYP3A5 regulates glucose metabolism in pancreatic ductal adenocarcinoma. Multi-omics analysis showed that CYP3A5 knockdown results in a decrease in various glucose-related metabolites through its effect on glucose transport. A mechanistic study revealed that CYP3A5 enriches the glucose transporter GLUT1 at the plasma membrane by restricting the translation of TXNIP, a negative regulator of GLUT1. Notably, CYP3A5-generated reactive oxygen species were proved to be responsible for attenuating the AKT-4EBP1-TXNIP signaling pathway. CYP3A5 contributes to cell migration by maintaining high glucose uptake in pancreatic cancer. Taken together, our results, for the first time, reveal a role of CYP3A5 in glucose metabolism in pancreatic ductal adenocarcinoma and identify a novel mechanism that is a potential therapeutic target.

Single-cell systems pharmacology identifies development-driven drug response and combination therapy in B cell acute lymphoblastic leukemia.

Leukemia can arise at various stages of the hematopoietic differentiation hierarchy, but the impact of developmental arrest on drug sensitivity is unclear. Applying network-based analyses to single-cell transcriptomes of human B cells, we define genome-wide signaling circuitry for each B cell differentiation stage. Using this reference, we comprehensively map the developmental states of B cell acute lymphoblastic leukemia (B-ALL), revealing its strong correlation with sensitivity to asparaginase, a commonly used chemotherapeutic agent. Single-cell multi-omics analyses of primary B-ALL blasts reveal marked intra-leukemia heterogeneity in asparaginase response: resistance is linked to pre-pro-B-like cells, with sensitivity associated with the pro-B-like population. By targeting BCL2, a driver within the pre-pro-B-like cell signaling network, we find that venetoclax significantly potentiates asparaginase efficacy in vitro and in vivo. These findings demonstrate a single-cell systems pharmacology framework to predict effective combination therapies based on intra-leukemia heterogeneity in developmental state, with potentially broad applications beyond B-ALL.

EI-MVSNet: Epipolar-Guided Multi-View Stereo Network With Interval-Aware Label.

Recent learning-based methods demonstrate their strong ability to estimate depth for multi-view stereo reconstruction. However, most of these methods directly extract features via regular or deformable convolutions, and few works consider the alignment of the receptive fields between views while constructing the cost volume. Through analyzing the constraint and inference of previous MVS networks, we find that there are still some shortcomings that hinder the performance. To deal with the above issues, we propose an Epipolar-Guided Multi-View Stereo Network with Interval-Aware Label (EI-MVSNet), which includes an epipolar-guided volume construction module and an interval-aware depth estimation module in a unified architecture for MVS. The proposed EI-MVSNet enjoys several merits. First, in the epipolar-guided volume construction module, we construct cost volume with features from aligned receptive fields between different pairs of reference and source images via epipolar-guided convolutions, which take rotation and scale changes into account. Second, in the interval-aware depth estimation module, we attempt to supervise the cost volume directly and make depth estimation independent of extraneous values by perceiving the upper and lower boundaries, which can achieve fine-grained predictions and enhance the reasoning ability of the network. Extensive experimental results on two standard benchmarks demonstrate that our EI-MVSNet performs favorably against state-of-the-art MVS methods. Specifically, our EI-MVSNet ranks 1st on both intermediate and advanced subsets of the Tanks and Temples benchmark, which verifies the high precision and strong robustness of our model.

Modular chimeric cytokine receptors with leucine zippers enhance the antitumour activity of CAR T cells via JAK/STAT signalling.

The limited availability of cytokines in solid tumours hinders maintenance of the antitumour activity of chimeric antigen receptor (CAR) T cells. Cytokine receptor signalling pathways in CAR T cells can be activated by transgenic expression or injection of cytokines in the tumour, or by engineering the activation of cognate cytokine receptors. However, these strategies are constrained by toxicity arising from the activation of bystander cells, by the suboptimal biodistribution of the cytokines and by downregulation of the cognate receptor. Here we show that replacement of the extracellular domains of heterodimeric cytokine receptors in T cells with two leucine zipper motifs provides optimal Janus kinase/signal transducer and activator of transcription signalling. Such chimeric cytokine receptors, which can be generated for common γ-chain receptors, interleukin-10 and -12 receptors, enabled T cells to survive cytokine starvation without induction of autonomous cell growth, and augmented the effector function of CAR T cells in vitro in the setting of chronic antigen exposure and in human tumour xenografts in mice. As a modular design, leucine zippers can be used to generate constitutively active cytokine receptors in effector immune cells.

Integrome signatures of lentiviral gene therapy for SCID-X1 patients.

Lentiviral vector (LV)-based gene therapy holds promise for a broad range of diseases. Analyzing more than 280,000 vector integration sites (VISs) in 273 samples from 10 patients with X-linked severe combined immunodeficiency (SCID-X1), we discovered shared LV integrome signatures in 9 of 10 patients in relation to the genomics, epigenomics, and 3D structure of the human genome. VISs were enriched in the nuclear subcompartment A1 and integrated into super-enhancers close to nuclear pore complexes. These signatures were validated in T cells transduced with an LV encoding a CD19-specific chimeric antigen receptor. Intriguingly, the one patient whose VISs deviated from the identified integrome signatures had a distinct clinical course. Comparison of LV and gamma retrovirus integromes regarding their 3D genome signatures identified differences that might explain the lower risk of insertional mutagenesis in LV-based gene therapy. Our findings suggest that LV integrome signatures, shaped by common features such as genome organization, may affect the efficacy of LV-based cellular therapies.

CXCR6 orchestrates brain CD8+ T cell residency and limits mouse Alzheimer's disease pathology.

Neurodegenerative diseases, including Alzheimer's disease (AD), are characterized by innate immune-mediated inflammation, but functional and mechanistic effects of the adaptive immune system remain unclear. Here we identify brain-resident CD8+ T cells that coexpress CXCR6 and PD-1 and are in proximity to plaque-associated microglia in human and mouse AD brains. We also establish that CD8+ T cells restrict AD pathologies, including ß-amyloid deposition and cognitive decline. Ligand-receptor interaction analysis identifies CXCL16-CXCR6 intercellular communication between microglia and CD8+ T cells. Further, Cxcr6 deficiency impairs accumulation, tissue residency programming and clonal expansion of brain PD-1+CD8+ T cells. Ablation of Cxcr6 or CD8+ T cells ultimately increases proinflammatory cytokine production from microglia, with CXCR6 orchestrating brain CD8+ T cell-microglia colocalization. Collectively, our study reveals protective roles for brain CD8+ T cells and CXCR6 in mouse AD pathogenesis and highlights that microenvironment-specific, intercellular communication orchestrates tissue homeostasis and protection from neuroinflammation.

Robust capped norm dual hyper-graph regularized non-negative matrix tri-factorization.

Non-negative matrix factorization (NMF) has been widely used in machine learning and data mining fields. As an extension of NMF, non-negative matrix tri-factorization (NMTF) provides more degrees of freedom than NMF. However, standard NMTF algorithm utilizes Frobenius norm to calculate residual error, which can be dramatically affected by noise and outliers. Moreover, the hidden geometric information in feature manifold and sample manifold is rarely learned. Hence, a novel robust capped norm dual hyper-graph regularized non-negative matrix tri-factorization (RCHNMTF) is proposed. First, a robust capped norm is adopted to handle extreme outliers. Second, dual hyper-graph regularization is considered to exploit intrinsic geometric information in feature manifold and sample manifold. Third, orthogonality constraints are added to learn unique data presentation and improve clustering performance. The experiments on seven datasets testify the robustness and superiority of RCHNMTF.

NetBID2 provides comprehensive hidden driver analysis.

Many signaling and other genes known as "hidden" drivers may not be genetically or epigenetically altered or differentially expressed at the mRNA or protein levels, but, rather, drive a phenotype such as tumorigenesis via post-translational modification or other mechanisms. However, conventional approaches based on genomics or differential expression are limited in exposing such hidden drivers. Here, we present a comprehensive algorithm and toolkit NetBID2 (data-driven network-based Bayesian inference of drivers, version 2), which reverse-engineers context-specific interactomes and integrates network activity inferred from large-scale multi-omics data, empowering the identification of hidden drivers that could not be detected by traditional analyses. NetBID2 has substantially re-engineered the previous prototype version by providing versatile data visualization and sophisticated statistical analyses, which strongly facilitate researchers for result interpretation through end-to-end multi-omics data analysis. We demonstrate the power of NetBID2 using three hidden driver examples. We deploy NetBID2 Viewer, Runner, and Cloud apps with 145 context-specific gene regulatory and signaling networks across normal tissues and paediatric and adult cancers to facilitate end-to-end analysis, real-time interactive visualization and cloud-based data sharing. NetBID2 is freely available at https://jyyulab.github.io/NetBID .

Targeting DNA polymerase ß elicits synthetic lethality with mismatch repair deficiency in acute lymphoblastic leukemia.

Mismatch repair (MMR) deficiency has been linked to thiopurine resistance and hypermutation in relapsed acute lymphoblastic leukemia (ALL). However, the repair mechanism of thiopurine-induced DNA damage in the absence of MMR remains unclear. Here, we provide evidence that DNA polymerase ß (POLB) of base excision repair (BER) pathway plays a critical role in the survival and thiopurine resistance of MMR-deficient ALL cells. In these aggressive resistant ALL cells, POLB depletion and its inhibitor oleanolic acid (OA) treatment result in synthetic lethality with MMR deficiency through increased cellular apurinic/apyrimidinic (AP) sites, DNA strand breaks and apoptosis. POLB depletion increases thiopurine sensitivities of resistant cells, and OA synergizes with thiopurine to kill these cells in ALL cell lines, patient-derived xenograft (PDX) cells and xenograft mouse models. Our findings suggest BER and POLB's roles in the process of repairing thiopurine-induced DNA damage in MMR-deficient ALL cells, and implicate their potentials as therapeutic targets against aggressive ALL progression.

Genomic landscape of Down syndrome-associated acute lymphoblastic leukemia.

Trisomy 21, the genetic cause of Down syndrome (DS), is the most common congenital chromosomal anomaly. It is associated with a 20-fold increased risk of acute lymphoblastic leukemia (ALL) during childhood and results in distinctive leukemia biology. To comprehensively define the genomic landscape of DS-ALL, we performed whole-genome sequencing and whole-transcriptome sequencing (RNA-Seq) on 295 cases. Our integrated genomic analyses identified 15 molecular subtypes of DS-ALL, with marked enrichment of CRLF2-r, IGH::IGF2BP1, and C/EBP altered (C/EBPalt) subtypes compared with 2257 non-DS-ALL cases. We observed abnormal activation of the CEBPD, CEBPA, and CEBPE genes in 10.5% of DS-ALL cases via a variety of genomic mechanisms, including chromosomal rearrangements and noncoding mutations leading to enhancer hijacking. A total of 42.3% of C/EBP-activated DS-ALL also have concomitant FLT3 point mutations or insertions/deletions, compared with 4.1% in other subtypes. CEBPD overexpression enhanced the differentiation of mouse hematopoietic progenitor cells into pro-B cells in vitro, particularly in a DS genetic background. Notably, recombination-activating gene-mediated somatic genomic abnormalities were common in DS-ALL, accounting for a median of 27.5% of structural alterations, compared with 7.7% in non-DS-ALL. Unsupervised hierarchical clustering analyses of CRLF2-rearranged DS-ALL identified substantial heterogeneity within this group, with the BCR::ABL1-like subset linked to an inferior event-free survival, even after adjusting for known clinical risk factors. These results provide important insights into the biology of DS-ALL and point to opportunities for targeted therapy and treatment individualization.

Ribonucleotide reductase subunit switching in hepatoblastoma drug response and relapse.

Prognosis of children with high-risk hepatoblastoma (HB), the most common pediatric liver cancer, remains poor. In this study, we found ribonucleotide reductase (RNR) subunit M2 (RRM2) was one of the key genes supporting cell proliferation in high-risk HB. While standard chemotherapies could effectively suppress RRM2 in HB cells, they induced a significant upregulation of the other RNR M2 subunit, RRM2B. Computational analysis revealed distinct signaling networks RRM2 and RRM2B were involved in HB patient tumors, with RRM2 supporting cell proliferation and RRM2B participating heavily in stress response pathways. Indeed, RRM2B upregulation in chemotherapy-treated HB cells promoted cell survival and subsequent relapse, during which RRM2B was gradually replaced back by RRM2. Combining an RRM2 inhibitor with chemotherapy showed an effective delaying of HB tumor relapse in vivo. Overall, our study revealed the distinct roles of the two RNR M2 subunits and their dynamic switching during HB cell proliferation and stress response.

Spatiotemporal regulation of cholangiocarcinoma growth and dissemination by peritumoral myofibroblasts in a Vcam1-dependent manner.

Intrahepatic cholangiocarcinoma (iCCA) is characterized by its highly desmoplastic stroma. Myofibroblasts (MFs) are present both within the tumor mass (intratumoral MFs, iMFs) and at the tumor border (peritumoral MFs, pMFs). Using a spheroid-based coculture system, we show that the initial iCCA-pMF contact is growth suppressive to the tumor cells. However, prolonged iCCA-pMF interaction elicits significant tumor cell invasion and dissemination. We find that vascular cell adhesion molecule-1 (Vcam1) level is elevated in tumor cells in contact with pMFs but low in disseminated tumor cells both in vitro and in vivo. A gene regulatory network analysis of mouse and patient iCCA tumors and Vcam1 knockout (Vcam1KO) demonstrate a heavy involvement of Vcam1 in epithelial-to-mesenchymal transition. While Vcam1KO has only a limited impact on tumor cell growth in their monoculture, Vcam1KO spheroids exhibit instant dissemination and a severe growth defect when cocultured with pMFs. When transplanted into the liver, Vcam1KO iCCA cells show a similar increase in dissemination but a significant defect in establishing primary and metastatic tumors. Incomplete blocking of Vcam1 in vivo reduces the size but increase the number of metastatic lesions. Overall, our study shows a spatiotemporal regulation of iCCA growth and dissemination by pMFs in a Vcam1-dependent manner.

Ribonucleotide Reductase Subunit Switching in Hepatoblastoma Drug Response and Relapse.

Prognosis of children with high-risk hepatoblastoma (HB), the most common pediatric liver cancer, remains poor. In this study, we found ribonucleotide reductase (RNR) subunit M2 ( RRM2 ) was one of the key genes supporting cell proliferation in high-risk HB. While standard chemotherapies could effectively suppress RRM2 in HB cells, they induced a significant upregulation of the other RNR M2 subunit, RRM2B . Computational analysis revealed distinct signaling networks RRM2 and RRM2B were involved in HB patient tumors, with RRM2 supporting cell proliferation and RRM2B participating heavily in stress response pathways. Indeed, RRM2B upregulation in chemotherapy-treated HB cells promoted cell survival and subsequent relapse, during which RRM2B was gradually replaced back by RRM2. Combining an RRM2 inhibitor with chemotherapy showed an effective delaying of HB tumor relapse in vivo. Overall, our study revealed the distinct roles of the two RNR M2 subunits and their dynamic switching during HB cell proliferation and stress response.

scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data.

The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.

scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data.

The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.

Loss of phosphatase CTDNEP1 potentiates aggressive medulloblastoma by triggering MYC amplification and genomic instability.

MYC-driven medulloblastomas are highly aggressive childhood brain tumors, however, the molecular and genetic events triggering MYC amplification and malignant transformation remain elusive. Here we report that mutations in CTDNEP1, a CTD nuclear-envelope-phosphatase, are the most significantly enriched recurrent alterations in MYC-driven medulloblastomas, and define high-risk subsets with poorer prognosis. Ctdnep1 ablation promotes the transformation of murine cerebellar progenitors into Myc-amplified medulloblastomas, resembling their human counterparts. CTDNEP1 deficiency stabilizes and activates MYC activity by elevating MYC serine-62 phosphorylation, and triggers chromosomal instability to induce p53 loss and Myc amplifications. Further, phosphoproteomics reveals that CTDNEP1 post-translationally modulates the activities of key regulators for chromosome segregation and mitotic checkpoint regulators including topoisomerase TOP2A and checkpoint kinase CHEK1. Co-targeting MYC and CHEK1 activities synergistically inhibits CTDNEP1-deficient MYC-amplified tumor growth and prolongs animal survival. Together, our studies demonstrate that CTDNEP1 is a tumor suppressor in highly aggressive MYC-driven medulloblastomas by controlling MYC activity and mitotic fidelity, pointing to a CTDNEP1-dependent targetable therapeutic vulnerability.

Combination of Ribociclib with BET-Bromodomain and PI3K/mTOR Inhibitors for Medulloblastoma Treatment In Vitro and In Vivo.

Despite improvement in the treatment of medulloblastoma over the last years, numerous patients with MYC- and MYCN-driven tumors still fail current therapies. Medulloblastomas have an intact retinoblastoma protein RB, suggesting that CDK4/6 inhibition might represent a therapeutic strategy for which drug combination remains understudied. We conducted high-throughput drug combination screens in a Group3 (G3) medulloblastoma line using the CDK4/6 inhibitor (CDK4/6i) ribociclib at IC20, referred to as an anchor, and 87 oncology drugs approved by FDA or in clinical trials. Bromodomain and extra terminal (BET) and PI3K/mTOR inhibitors potentiated ribociclib inhibition of proliferation in an established cell line and freshly dissociated tumor cells from intracranial xenografts of G3 and Sonic hedgehog (SHH) medulloblastomas in vitro. A reverse combination screen using the BET inhibitor JQ1 as anchor, revealed CDK4/6i as the most potentiating drugs. In vivo, ribociclib showed single-agent activity in medulloblastoma models whereas JQ1 failed to show efficacy due to high clearance and insufficient free brain concentration. Despite in vitro synergy, combination of ribociclib with the PI3K/mTOR inhibitor paxalisib did not significantly improve the survival of G3 and SHH medulloblastoma-bearing mice compared with ribociclib alone. Molecular analysis of ribociclib and paxalisib-treated tumors revealed that E2F targets and PI3K/AKT/MTORC1 signaling genes were depleted, as expected. Importantly, in one untreated G3MB model HD-MB03, the PI3K/AKT/MTORC1 gene set was enriched in vitro compared with in vivo suggesting that the pathway displayed increased activity in vitro. Our data illustrate the difficulty in translating in vitro findings in vivo. See related article in Mol Cancer Ther (2022) 21(8):1306-1317.

Network-based assessment of HDAC6 activity predicts preclinical and clinical responses to the HDAC6 inhibitor ricolinostat in breast cancer.

Inhibiting individual histone deacetylase (HDAC) is emerging as well-tolerated anticancer strategy compared with pan-HDAC inhibitors. Through preclinical studies, we demonstrated that the sensitivity to the leading HDAC6 inhibitor (HDAC6i) ricolinstat can be predicted by a computational network-based algorithm (HDAC6 score). Analysis of ~3,000 human breast cancers (BCs) showed that ~30% of them could benefice from HDAC6i therapy. Thus, we designed a phase 1b dose-escalation clinical trial to evaluate the activity of ricolinostat plus nab-paclitaxel in patients with metastatic BC (MBC) (NCT02632071). Study results showed that the two agents can be safely combined, that clinical activity is identified in patients with HR+/HER2- disease and that the HDAC6 score has potential as predictive biomarker. Analysis of other tumor types also identified multiple cohorts with predicted sensitivity to HDAC6i's. Mechanistically, we have linked the anticancer activity of HDAC6i's to their ability to induce c-Myc hyperacetylation (ac-K148) promoting its proteasome-mediated degradation in sensitive cancer cells.

PAX5 epigenetically orchestrates CD58 transcription and modulates blinatumomab response in acute lymphoblastic leukemia.

Blinatumomab is an efficacious immunotherapeutic agent in B cell acute lymphoblastic leukemia (B-ALL). However, the pharmacogenomic basis of leukemia response to blinatumomab is unclear. Using genome-wide CRISPR, we comprehensively identified leukemia intrinsic factors of blinatumomab sensitivity, i.e., the loss of CD58 as a top driver for resistance, in addition to CD19. Screening 1639 transcription factor genes, we then identified PAX5 as the key activator of CD58. ALL with the PAX5 P80R mutation also expressed the lowest level of CD58 among 20 ALL molecular subtypes in 1988 patients. Genome editing confirmed the effects of this mutation on CD58 expression and blinatumomab sensitivity in B-ALL, with validation in patient leukemic blasts. We described a PAX5-driven enhancer at the CD58 locus, which was disrupted by PAX5 P80R, and the loss of CD58 abolished blinatumomab-induced T cell activation with global changes in transcriptomic/epigenomic program. In conclusion, we identified previously unidentified genetic mechanisms of blinatumomab resistance in B-ALL, suggesting strategies for genomics-guided treatment individualization.