Hepatocellular carcinoma (HCC) is the most common lethal form of liver cancer. Apart from surgical removal and transplantation, other treatments have not yet been well established for patients with HCC. In this study, we found that carboxylesterase 1 (CES1) is expressed at various levels in HCC. We further revealed that blockage of CES1 by pharmacological and genetical approaches leads to altered lipid profiles that are directly linked to impaired mitochondrial function. Mechanistically, lipidomic analyses indicated that lipid signaling molecules, including polyunsaturated fatty acids (PUFAs), which activate PPARα/γ, were dramatically reduced upon CES1 inhibition. As a result, the expression of SCD, a PPARα/γ target gene involved in tumor progression and chemoresistance, was significantly downregulated. Clinical analysis demonstrated a strong correlation between the protein levels of CES1 and SCD in HCC. Interference with lipid signaling by targeting the CES1-PPARα/γ-SCD axis sensitized HCC cells to cisplatin treatment. As a result, the growth of HCC xenograft tumors in NU/J mice was potently slowed by coadministration of cisplatin and CES1 inhibition. Our results, thus, suggest that CES1 is a promising therapeutic target for HCC treatment.

African American (AA) women with breast cancer are more likely to have higher inflammation and a stronger overall immune response, which correlate with poorer outcomes. In this report, we applied the nanostring immune panel to identify differences in inflammatory and immune gene expression by race. We observed a higher expression of multiple cytokines in AA patients compared to EA patients, with high expression of CD47, TGFB1, and NFKB1 associated with the transcriptional repressor Kaiso. To investigate the mechanism associated with this expression pattern, we observed that Kaiso depletion results in decreased expression of CD47, and its ligand SIRPA. Furthermore, Kaiso appears to directly bind to the methylated sequences of the THBS1 promotor and repress gene expression. Similarly, Kaiso depletion attenuated tumor formation in athymic nude mice, and these Kaiso-depleted xenograft tissues showed significantly higher phagocytosis and increased infiltration of M1 macrophages. In vitro validation using MCF7 and THP1 macrophages treated with Kaiso-depleted exosomes showed a reduced expression of immune-related markers (CD47 and SIRPA) and macrophage polarization towards the M1 phenotype compared to MCF7 cells treated with exosomes isolated from high-Kaiso cells. Lastly, analysis of TCGA breast cancer patient data demonstrates that this gene signature is most prominent in the basal-like subtype, which is more frequently observed in AA breast cancer patients.

Different software and algorithms are available for peak picking in nontargeted metabolomics and each may have its own strengths and limitations. The choice of pick picking method can significantly influence the results obtained, including the number and identity of metabolites detected, their quantification, and subsequent biomarker analysis. The impact of peak picking by different tools in an untargeted metabolomics-based biomarker study is largely understated. This study compares two popular open-source software tools for peak picking in untargeted metabolomics of cancer cells, tissues, and bio-fluids: XCMS and MZmine 2. The investigation evaluates the impact of these peak-picking algorithms on biomarker identification. We found significant discrepancy between the results obtained from XCMS and MZmine 2, regardless of the sample types, solvent gradient phases, retention time (RT), or mass-to-charge ratio (m/z) tolerances used. Notably, this study revealed significant disagreement between peak picking tools in the context of metabolite-based biomarker study and highlights the importance of carefully evaluating and selecting appropriate peak picking tools to ensure reliable and accurate results in untargeted metabolomics research. Abstract Figure:

Background/Objectives: Uveal melanoma is the most common primary ocular cancer in adults. Patients with metastatic uveal melanoma (mUM) have limited treatment options and poor prognosis. mUM is characterized by high oxidative phosphorylation (OXPHOS), which may be a therapeutic vulnerability for this disease. ONC206 is an imipridone compound that can inhibit OXPHOS indirectly and is currently being evaluated in clinical trials. Thus, we tested the effects of ONC206 on human uveal melanoma cell lines and patient-derived xenografts (PDXs) in vitro and in vivo. Methods: The effects of ONC206 on cell survival, apoptosis, autophagy, oncogenic signaling pathways, and metabolic networks were assessed in vitro using human melanoma cell lines. ONC206 was then tested for safety and anti-tumor activity in vivo using two mUM PDX models. Results: ONC206 treatment produced dose-dependent inhibition of mUM cell growth in vitro, with induction of varying levels of apoptosis and autophagy. ONC206 treatment also downregulated OXPHOS effector proteins and metabolites, thereby impairing mitochondrial OXPHOS. Treatment with ONC206 significantly reduced tumor burden and improved survival in two UM PDX mouse models in vivo. Conclusions: Our findings position ONC206 as a mechanistically distinct agent to target mitochondrial metabolism and to inhibit mUM. As ONC206 is currently being evaluated in multiple clinical studies, our data support further evaluation as a potential new therapeutic strategy for mUM.

Poor therapeutic index is a principal cause of drug attrition during development. A case in point is L-asparaginase (ASNase), an enzyme-drug approved for treatment of pediatric acute lymphoblastic leukemia (ALL) but too toxic for adults. To elucidate potentially targetable mechanisms for mitigation of ASNase toxicity, we performed multi-omic profiling of the response to sub-toxic and toxic doses of ASNase in mice. We collected whole blood samples longitudinally, processed them to plasma, and extracted metabolites, lipids, and proteins from a single 20-µL plasma sample. We analyzed the extracts using multiple reaction monitoring (MRM) of 500+ water soluble metabolites, 750+ lipids, and 375 peptides on a triple quadrupole LC-MS/MS platform. Metabolites, lipids, and peptides that were modulated in a dose-dependent manner appeared to converge on antioxidation, inflammation, autophagy, and cell death pathways, prompting the hypothesis that inhibiting those pathways might decrease ASNase toxicity while preserving anticancer activity. Overall, we provide here a streamlined, three-in-one LC-MS/MS workflow for targeted metabolomics, lipidomics, and proteomics and demonstrate its ability to generate new insights into mechanisms of drug toxicity.