LipidSIM: Inferring mechanistic lipid biosynthesis perturbations from lipidomics with a flexible, low-parameter, Markov modeling framework.

Lipid metabolism is a complex and dynamic system involving numerous enzymes at the junction of multiple metabolic pathways. Disruption of these pathways leads to systematic dyslipidemia, a hallmark of many pathological developments, such as nonalcoholic steatohepatitis and diabetes. Recent advances in computational tools can provide insights into the dysregulation of lipid biosynthesis, but limitations remain due to the complexity of lipidomic data, limited knowledge of interactions among involved enzymes, and technical challenges in standardizing across different lipid types. Here, we present a low-parameter, biologically interpretable framework named Lipid Synthesis Investigative Markov model (LipidSIM), which models and predicts the source of perturbations in lipid biosynthesis from lipidomic data. LipidSIM achieves this by accounting for the interdependency between the lipid species via the lipid biosynthesis network and generates testable hypotheses regarding changes in lipid biosynthetic reactions. This feature allows the integration of lipidomics with other omics types, such as transcriptomics, to elucidate the direct driving mechanisms of altered lipidomes due to treatments or disease progression. To demonstrate the value of LipidSIM, we first applied it to hepatic lipidomics following Keap1 knockdown and found that changes in mRNA expression of the lipid pathways were consistent with the LipidSIM-predicted fluxes. Second, we used it to study lipidomic changes following intraperitoneal injection of CCl4 to induce fast NAFLD/NASH development and the progression of fibrosis and hepatic cancer. Finally, to show the power of LipidSIM for classifying samples with dyslipidemia, we used a Dgat2-knockdown study dataset. Thus, we show that as it demands no a priori knowledge of enzyme kinetics, LipidSIM is a valuable and intuitive framework for extracting biological insights from complex lipidomic data.

Innate and adaptive immune cell interaction drives inflammasome activation and hepatocyte apoptosis in murine liver injury from immune checkpoint inhibitors.

Immune checkpoints (CTLA4 & PD-1) are inhibitory pathways that block aberrant immune activity and maintain self-tolerance. Tumors co-opt these checkpoints to avoid immune destruction. Immune checkpoint inhibitors (ICIs) activate immune cells and restore their tumoricidal potential, making them highly efficacious cancer therapies. However, immunotolerant organs such as the liver depend on these tolerogenic mechanisms, and their disruption with ICI use can trigger the unintended side effect of hepatotoxicity termed immune-mediated liver injury from ICIs (ILICI). Learning how to uncouple ILICI from ICI anti-tumor activity is of paramount clinical importance. We developed a murine model to recapitulate human ILICI using CTLA4+/- mice treated with either combined anti-CTLA4 + anti-PDL1 or IgG1 + IgG2. We tested two forms of antisense oligonucleotides to knockdown caspase-3 in a total liver (parenchymal and non-parenchymal cells) or in a hepatocyte-specific manner. We also employed imaging mass cytometry (IMC), a powerful multiplex modality for immunophenotyping and cell interaction analysis in our model. ICI-treated mice had significant evidence of liver injury. We detected cleaved caspase-3 (cC3), indicating apoptosis was occurring, as well as Nod-like receptor protein 3 (NLRP3) inflammasome activation, but no necroptosis. Total liver knockdown of caspase-3 worsened liver injury, and induced further inflammasome activation, and Gasdermin-D-mediated pyroptosis. Hepatocyte-specific knockdown of caspase-3 reduced liver injury and NLRP3 inflammasome activation. IMC-generated single-cell data for 77,692 cells was used to identify 22 unique phenotypic clusters. Spatial analysis revealed that cC3+ hepatocytes had significantly closer interactions with macrophages, Kupffer cells, and NLRP3hi myeloid cells than other cell types. We also observed zones of three-way interaction between cC3+ hepatocytes, CD8 + T-cells, and macrophages. Our work is the first to identify hepatocyte apoptosis and NLRP3 inflammasome activation as drivers of ILICI. Furthermore, we report that the interplay between adaptive and innate immune cells is critical to hepatocyte apoptosis and ILICI.

Ligand conjugated antisense oligonucleotide for the treatment of transthyretin amyloidosis: preclinical and phase 1 data.

AIMS: Amyloidogenic transthyretin (ATTR) amyloidosis is a fatal disease characterized by progressive cardiomyopathy and/or polyneuropathy. AKCEA-TTR-LRx (ION-682884) is a ligand-conjugated antisense drug designed for receptor-mediated uptake by hepatocytes, the primary source of circulating transthyretin (TTR). Enhanced delivery of the antisense pharmacophore is expected to increase drug potency and support lower, less frequent dosing in treatment. METHODS AND RESULTS: AKCEA-TTR-LRx demonstrated an approximate 50-fold and 30-fold increase in potency compared with the unconjugated antisense drug, inotersen, in human hepatocyte cell culture and mice expressing a mutated human genomic TTR sequence, respectively. This increase in potency was supported by a preferential distribution of AKCEA-TTR-LRx to liver hepatocytes in the transgenic hTTR mouse model. A randomized, placebo-controlled, phase 1 study was conducted to evaluate AKCEA-TTR-LRx in healthy volunteers (ClinicalTrials.gov: NCT03728634). Eligible participants were assigned to one of three multiple-dose cohorts (45, 60, and 90 mg) or a single-dose cohort (120 mg), and then randomized 10:2 (active : placebo) to receive a total of 4 SC doses (Day 1, 29, 57, and 85) in the multiple-dose cohorts or 1 SC dose in the single-dose cohort. The primary endpoint was safety and tolerability; pharmacokinetics and pharmacodynamics were secondary endpoints. All randomized participants completed treatment. No serious adverse events were reported. In the multiple-dose cohorts, AKCEA-TTR-LRx reduced TTR levels from baseline to 2 weeks after the last dose of 45, 60, or 90 mg by a mean (SD) of -85.7% (8.0), -90.5% (7.4), and -93.8% (3.4), compared with -5.9% (14.0) for pooled placebo (P < 0.001). A maximum mean (SD) reduction in TTR levels of -86.3% (6.5) from baseline was achieved after a single dose of 120 mg AKCEA-TTR-LRx . CONCLUSIONS: These findings suggest an improved safety and tolerability profile with the increase in potency achieved by productive receptor-mediated uptake of AKCEA-TTR-LRx by hepatocytes and supports further development of AKCEA-TTR-LRx for the treatment of ATTR polyneuropathy and cardiomyopathy.

Characterization of target mRNA reduction through in situ RNA hybridization in multiple organ systems following systemic antisense treatment in animals.

Advances in the medicinal chemistry of antisense oligonucleotide drugs have been instrumental in achieving and optimizing antisense activity in cell types other than hepatocytes, the cell type that is most sensitive to antisense effects following systemic treatment. To broadly characterize the effects of antisense drugs on target messenger RNA (mRNA) levels in different organs and cell types in animals, we have developed a sensitive RNA in situ hybridization technique using the noncoding RNA metastasis associated lung adenocarcinoma transcript 1 (MALAT1) as a surrogate target. We have used this technique to evaluate the effects of 2'-O-methoxy ethyl (MOE) and constrained ethyl bicyclic nucleic acid (cEt) gapmer antisense oligonucleotides (ASOs). ASO tissue distribution was also characterized using immunohistochemical techniques, and MALAT1 mRNA reductions were confirmed by quantitative real time-polymerase chain reaction. Our findings demonstrate that systemic antisense drug administration in both mice and non-human primates resulted in marked reductions in MALAT1 RNA in many tissues and cell types other than liver including kidney, muscle, lung, adipose, adrenal gland, and peripheral nerve tissue. As expected, ASOs with cEt chemistry were more efficacious than MOE ASO in all tissues examined.