Multi-model analysis of gallbladder cancer reveals the role of OxLDL-absorbing neutrophils in promoting liver invasion.

BACKGROUND: Gallbladder cancer (GBC) is the most common and lethal malignancy of the biliary tract that lacks effective therapy. In many GBC cases, infiltration into adjacent organs or distant metastasis happened long before the diagnosis, especially the direct liver invasion, which is the most common and unfavorable way of spreading. METHODS: Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), proteomics, and multiplexed immunohistochemistry (mIHC) were performed on GBC across multiple tumor stages to characterize the tumor microenvironment (TME), focusing specifically on the preferential enrichment of neutrophils in GBC liver invasion (GBC-LI). RESULTS: Multi-model Analysis reveals the immunosuppressive TME of GBC-LI that was characterized by the enrichment of neutrophils at the invasive front. We identified the context-dependent transcriptional states of neutrophils, with the Tumor-Modifying state being associated with oxidized low-density lipoprotein (oxLDL) metabolism. In vitro assays showed that the direct cell-cell contact between GBC cells and neutrophils led to the drastic increase in oxLDL uptake of neutrophils, which was primarily mediated by the elevated OLR1 on neutrophils. The oxLDL-absorbing neutrophils displayed a higher potential to promote tumor invasion while demonstrating lower cancer cytotoxicity. Finally, we identified a neutrophil-promoting niche at the invasive front of GBC-LI that constituted of KRT17+ GBC cells, neutrophils, and surrounding fibroblasts, which may help cultivate the oxLDL-absorbing neutrophils. CONCLUSIONS: Our study reveals the existence of a subset of pro-tumoral neutrophils with a unique ability to absorb oxLDL via OLR1, a phenomenon induced through cell-cell contact with KRT17+ GBC cells in GBC-LI.

Neutrophil profiling illuminates anti-tumor antigen-presenting potency.

Neutrophils, the most abundant and efficient defenders against pathogens, exert opposing functions across cancer types. However, given their short half-life, it remains challenging to explore how neutrophils adopt specific fates in cancer. Here, we generated and integrated single-cell neutrophil transcriptomes from 17 cancer types (225 samples from 143 patients). Neutrophils exhibited extraordinary complexity, with 10 distinct states including inflammation, angiogenesis, and antigen presentation. Notably, the antigen-presenting program was associated with favorable survival in most cancers and could be evoked by leucine metabolism and subsequent histone H3K27ac modification. These neutrophils could further invoke both (neo)antigen-specific and antigen-independent T cell responses. Neutrophil delivery or a leucine diet fine-tuned the immune balance to enhance anti-PD-1 therapy in various murine cancer models. In summary, these data not only indicate the neutrophil divergence across cancers but also suggest therapeutic opportunities such as antigen-presenting neutrophil delivery.

Dual Inhibition of CDK4/6 and XPO1 Induces Senescence With Acquired Vulnerability to CRBN-Based PROTAC Drugs.

BACKGROUND & AIMS: Despite the increasing number of treatment options available for liver cancer, only a small proportion of patients achieve long-term clinical benefits. Here, we aim to develop new therapeutic approaches for liver cancer. METHODS: A compound screen was conducted to identify inhibitors that could synergistically induce senescence when combined with cyclin-dependent kinase (CDK) 4/6 inhibitor. The combination effects of CDK4/6 inhibitor and exportin 1 (XPO1) inhibitor on cellular senescence were investigated in a panel of human liver cancer cell lines and multiple liver cancer models. A senolytic drug screen was performed to identify drugs that selectively killed senescent liver cancer cells. RESULTS: The combination of CDK4/6 inhibitor and XPO1 inhibitor synergistically induces senescence of liver cancer cells in vitro and in vivo. The XPO1 inhibitor acts by causing accumulation of RB1 in the nucleus, leading to decreased E2F signaling and promoting senescence induction by the CDK4/6 inhibitor. Through a senolytic drug screen, cereblon (CRBN)-based proteolysis targeting chimera (PROTAC) ARV-825 was identified as an agent that can selectively kill senescent liver cancer cells. Up-regulation of CRBN was a vulnerability of senescent liver cancer cells, making them sensitive to CRBN-based PROTAC drugs. Mechanistically, we find that ubiquitin specific peptidase 2 (USP2) directly interacts with CRBN, leading to the deubiquitination and stabilization of CRBN in senescent liver cancer cells. CONCLUSIONS: Our study demonstrates a striking synergy in senescence induction of liver cancer cells through the combination of CDK4/6 inhibitor and XPO1 inhibitor. These findings also shed light on the molecular processes underlying the vulnerability of senescent liver cancer cells to CRBN-based PROTAC therapy.

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification.

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This limitation hampers the full realization of the potential offered by shotgun phosphoproteomics. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19% to 46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

An Inflammatory Checkpoint Generated by IL1RN Splicing Offers Therapeutic Opportunity for KRAS-Mutant Intrahepatic Cholangiocarcinoma.

KRAS mutations are causally linked to protumor inflammation and are identified as driving factors in tumorigenesis. Here, using multiomics data gathered from a large set of patients, we showed that KRAS mutation was associated with a specific landscape of alternative mRNA splicing that connected to myeloid inflammation in intrahepatic cholangiocarcinoma (iCCA). Then, we identified a negative feedback mechanism in which the upregulation of interleukin 1 receptor antagonist (IL1RN)-201/203 due to alternative splicing confers vital anti-inflammatory effects in KRAS-mutant iCCA. In KRAS-mutant iCCA mice, both IL1RN-201/203 upregulation and anakinra treatment ignited a significant antitumor immune response by altering neutrophil recruitment and phenotypes. Furthermore, anakinra treatment synergistically enhanced anti-PD-1 therapy to activate intratumoral GZMB+ CD8+ T cells in KRAS-mutant iCCA mice. Clinically, we found that high IL1RN-201/203 levels in patients with KRAS-mutant iCCA were significantly associated with superior response to anti-PD-1 immunotherapy. SIGNIFICANCE: This work describes a novel inflammatory checkpoint mediated by IL1RN alternative splicing variants that may serve as a promising basis to develop therapeutic options for KRAS-mutant iCCA and other cancers. This article is featured in Selected Articles from This Issue, p. 2109.

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology.

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification.

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

Genome-Scale CRISPR screen identifies LAPTM5 driving lenvatinib resistance in hepatocellular carcinoma.

ABBREVIATIONS: cld-CASP3: cleaved caspase 3; cld-PARP: cleaved PARP; DTP: drug tolerant persister; GO: Gene Ontology; GTEx: The Genotype-Tissue Expression; HCC: hepatocellular carcinoma; HCQ: hydroxychloroquine; IC50: half maximal inhibitory concentration value; KEGG: Kyoto Encyclopedia of Genes and Genomes; LAPTM5: lysosomal protein transmembrane 5; NT: non-targeting; PDC: patient-derived primary cell lines; PDO: patient-derived primary organoid; TCGA: The Cancer Genome Atlas.

Multimodule characterization of immune subgroups in intrahepatic cholangiocarcinoma reveals distinct therapeutic vulnerabilities.

BACKGROUND: Immune microenvironment is well recognized as a critical regulator across cancer types, despite its complex roles in different disease conditions. Intrahepatic cholangiocarcinoma (iCCA) is characterized by a tumor-reactive milieu, emphasizing a deep insight into its immunogenomic profile to provide prognostic and therapeutic implications. METHODS: We performed genomic, transcriptomic, and proteomic characterization of 255 paired iCCA and adjacent liver tissues. We validated our findings through H&E staining (n=177), multiplex immunostaining (n=188), single-cell RNA sequencing (scRNA-seq) (n=10), in vitro functional studies, and in vivo transposon-based mouse models. RESULTS: Integrated multimodule data identified three immune subgroups with distinct clinical, genetic, and molecular features, designated as IG1 (immune-suppressive, 25.1%), IG2 (immune-exclusion, 42.7%), and IG3 (immune-activated, 32.2%). IG1 was characterized by excessive infiltration of neutrophils and immature dendritic cells (DCs). The hallmark of IG2 was the relatively higher tumor-proliferative activity and tumor purity. IG3 exhibited an enrichment of adaptive immune cells, natural killer cells, and activated DCs. These immune subgroups were significantly associated with prognosis and validated in two independent cohorts. Tumors with KRAS mutations were enriched in IG1 and associated with myeloid inflammation-dominated immunosuppression. Although tumor mutation burden was relatively higher in IG2, loss of heterozygosity in human leucocyte antigen and defects in antigen presentation undermined the recognition of neoantigens, contributing to immune-exclusion behavior. Pathological analysis confirmed that tumor-infiltrating lymphocytes and tertiary lymphoid structures were both predominant in IG3. Hepatitis B virus (HBV)-related samples tended to be under-represented in IG1, and scRNA-seq analyses implied that HBV infection indeed alleviated myeloid inflammation and reinvigorated antitumor immunity. CONCLUSIONS: Our study elucidates that the immunogenomic traits of iCCA are intrinsically heterogeneous among patients, posing great challenge and opportunity for the application of personalized immunotherapy.

Single-cell transcriptomic analysis suggests two molecularly subtypes of intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous cancer with limited understanding of its classification and tumor microenvironment. Here, by performing single-cell RNA sequencing on 144,878 cells from 14 pairs of iCCA tumors and non-tumor liver tissues, we find that S100P and SPP1 are two markers for iCCA perihilar large duct type (iCCAphl) and peripheral small duct type (iCCApps). S100P + SPP1- iCCAphl has significantly reduced levels of infiltrating CD4+ T cells, CD56+ NK cells, and increased CCL18+ macrophages and PD1+CD8+ T cells compared to S100P-SPP1 + iCCApps. The transcription factor CREB3L1 is identified to regulate the S100P expression and promote tumor cell invasion. S100P-SPP1 + iCCApps has significantly more SPP1+ macrophage infiltration, less aggressiveness and better survival than S100P + SPP1- iCCAphl. Moreover, S100P-SPP1 + iCCApps harbors tumor cells at different status of differentiation, such as ALB + hepatocyte differentiation and ID3+ stemness. Our study extends the understanding of the diversity of tumor cells in iCCA.

Baf60b-mediated ATM-p53 activation blocks cell identity conversion by sensing chromatin opening.

Lineage conversion by expression of lineage-specific transcription factors is a process of epigenetic remodeling that has low efficiency. The mechanism by which a cell resists lineage conversion is largely unknown. Using hepatic-specific transcription factors Foxa3, Hnf1α and Gata4 (3TF) to induce hepatic conversion in mouse fibroblasts, we showed that 3TF induced strong activation of the ATM-p53 pathway, which led to proliferation arrest and cell death, and it further prevented hepatic conversion. Notably, ATM activation, independent of DNA damage, responded to chromatin opening during hepatic conversion. By characterizing the early molecular events during hepatic conversion, we found that Baf60b, a member of the SWI/SNF chromatin remodeling complex, links chromatin opening to ATM activation by facilitating ATM recruitment to the open chromatin regions of a panel of hepatic gene loci. These findings shed light on cellular responses to lineage conversion by revealing a function of the ATM-p53 pathway in sensing chromatin opening.

Optimized Hepatocyte-Like Cells with Functional Drug Transporters Directly-Reprogrammed from Mouse Fibroblasts and their Potential in Drug Disposition and Toxicology.

BACKGROUND/AIMS: To develop a suitable hepatocyte-like cell model that could be a substitute for primary hepatocytes with essential transporter expression and functions. Induced hepatocyte-like (iHep) cells directly reprogrammed from mice fibroblast cells were fully characterized. METHODS: Naïve iHep cells were transfected with nuclear hepatocyte factor 4 alpha (Hnf4α) and treated with selected small molecules. Sandwich cultured configuration was applied. The mRNA and protein expression of transporters were determined by Real Time PCR and confocal. The functional transporters were estimated by drug biliary excretion measurement. The inhibition of bile acid efflux transporters by cholestatic drugs were assessed. RESULTS: The expression and function of p-glycoprotein (P-gp), bile salt efflux pump (Bsep), multidrug resistance-associated protein 2 (Mrp2), Na+-dependent taurocholate cotransporting polypeptide (Ntcp), and organic anion transporter polypedtides (Oatps) in iHep cells were significantly improved after transfection of hepatocyte nuclear factor 4 alpha (Hnf4α) and treatment with selected inducers. In vitro intrinsic biliary clearances (CLb,int) of optimized iHep cells for rosuvastatin, methotrexate, d8-TCA (deuterium-labeled sodium taurocholate acid) and DPDPE ([D-Pen2,5] enkephalin hydrate) correlated well with that of sandwich-cultured primary mouse hepatocytes (SCMHs) (r2 = 0.984). Cholestatic drugs were evaluated and the results were compared well with primary mice hepatocytes. CONCLUSION: The optimized iHep cells expressed functional drug transporters and were comparable to primary mice hepatocytes. This study suggested direct reprogramming could provide a potential alternative to primary hepatocytes for drug candidate hepatobiliary disposition and hepatotoxicity screening.

Cell fate conversion: direct induction of hepatocyte-like cells from fibroblasts.

One of the essential features of stem cells is their cellular plasticity to differentiate into daughter cells with defined functions. Recently, induction of pluripotent stem cells from somatic cells by defined transcription factors led to the focus on cellular plasticity of terminally differentiated cells. This approach is adopted by other studies to demonstrate the cell fate conversion between different lineages of terminally differentiated cells. We and others showed that induced hepatocyte-like (iHep) cells are directly converted from mouse fibroblasts by overexpression of liver-enriched transcription factors. iHep cells as well as pluripotent stem cell- or mesenchymal stem cell-derived hepatocyte-like cells provide potential cell sources for disease modeling, transplantation, and tissue engineering independent of donor organs. Here, we review the latest advances in generating hepatocyte-like cells and summarize general criteria for evaluating these cells. In addition, we propose a possible role of the p19(Arf) /p53 pathway in cell fate maintenance, which apparently limits the formation of induced pluripotent stem (iPS) cells and iHep cells.

Induction of functional hepatocyte-like cells from mouse fibroblasts by defined factors.

The generation of functional hepatocytes independent of donor liver organs is of great therapeutic interest with regard to regenerative medicine and possible cures for liver disease. Induced hepatic differentiation has been achieved previously using embryonic stem cells or induced pluripotent stem cells. Particularly, hepatocytes generated from a patient's own induced pluripotent stem cells could theoretically avoid immunological rejection. However, the induction of hepatocytes from induced pluripotent stem cells is a complicated process that would probably be replaced with the arrival of improved technology. Overexpression of lineage-specific transcription factors directly converts terminally differentiated cells into some other lineages, including neurons, cardiomyocytes and blood progenitors; however, it remains unclear whether these lineage-converted cells could repair damaged tissues in vivo. Here we demonstrate the direct induction of functional hepatocyte-like (iHep) cells from mouse tail-tip fibroblasts by transduction of Gata4, Hnf1α and Foxa3, and inactivation of p19(Arf). iHep cells show typical epithelial morphology, express hepatic genes and acquire hepatocyte functions. Notably, transplanted iHep cells repopulate the livers of fumarylacetoacetate-hydrolase-deficient (Fah(-/-)) mice and rescue almost half of recipients from death by restoring liver functions. Our study provides a novel strategy to generate functional hepatocyte-like cells for the purpose of liver engineering and regenerative medicine.