Alteration of the lipid profile in lymphomas induced by MYC overexpression

Lipid metabolism reprogramming in renal cell carcinomas

This study investigates the intricate mechanisms underlying the correlation between elevated consumption of harmful fats and the onset of kidney malignancies. The rise in global obesity rates has been accompanied by an increased prevalence of renal cancers, prompting an exploration into the molecular pathways and biological processes linking these phenomena. Through an extensive review of current literature and clinical studies, we identify potential key factors contributing to the carcinogenic influence of harmful fats on renal tissues. Our analysis highlights the role of adipose tissue-derived factors, inflammatory mediators, and lipid metabolism dysregulation in fostering a microenvironment conducive to renal tumorigenesis. Furthermore, we delve into the impact of harmful fats on signaling pathways associated with cell proliferation, apoptosis evasion, and angiogenesis within the renal parenchyma. This review underscores the importance of elucidating the molecular intricacies linking lipid metabolism and kidney malignancies, offering a foundation for future research and the development of targeted preventive and therapeutic interventions. The findings discussed herein contribute to our understanding of the complex relationship between lipid mediators and renal cancer, providing a basis for public health strategies aimed at mitigating the impact of harmful fats on kidney health.

Leveraging altered lipid metabolism in treating B cell malignancies

B cell malignancies, comprising over 80 heterogeneous blood cancers, pose significant prognostic challenges due to intricate oncogenic signaling. Emerging evidence emphasizes the pivotal role of disrupted lipid metabolism in the development of these malignancies. Variations in lipid species, such as phospholipids, cholesterol, sphingolipids, and fatty acids, are widespread across B cell malignancies, contributing to uncontrolled cell proliferation and survival. Phospholipids play a crucial role in initial signaling cascades leading to B cell activation and malignant transformation through constitutive B cell receptor (BCR) signaling. Dysregulated cholesterol and sphingolipid homeostasis support lipid raft integrity, crucial for propagating oncogenic signals. Sphingolipids impact malignant B cell stemness, proliferation, and survival, while glycosphingolipids in lipid rafts modulate BCR activation. Additionally, cancer cells enhance fatty acid-related processes to meet heightened metabolic demands. In obese individuals, the obesity-derived lipids and adipokines surrounding adipocytes rewire lipid metabolism in malignant B cells, evading cytotoxic therapies. Genetic drivers such as MYC translocations also intrinsically alter lipid metabolism in malignant B cells. In summary, intrinsic and extrinsic factors converge to reprogram lipid metabolism, fostering aggressive phenotypes in B cell malignancies. Therefore, targeting altered lipid metabolism has translational potential for improving risk stratification and clinical management of diverse B cell malignancy subtypes.

Imaging with mass spectrometry: Which ionization technique is best?

The use of mass spectrometry (MS) to acquire molecular images of biological tissues and other substrates has developed into an indispensable analytical tool over the past 25 years. Imaging mass spectrometry technologies are widely used today to study the in situ spatial distributions for a variety of analytes. Early MS images were acquired using secondary ion mass spectrometry and matrix-assisted laser desorption/ionization. Researchers have also designed and developed other ionization techniques in recent years to probe surfaces and generate MS images, including desorption electrospray ionization (DESI), nanoDESI, laser ablation electrospray ionization, and infrared matrix-assisted laser desorption electrospray ionization. Investigators now have a plethora of ionization techniques to select from when performing imaging mass spectrometry experiments. This brief perspective will highlight the utility and relative figures of merit of these techniques within the context of their use in imaging mass spectrometry.

Construction of a Diagnostic Model for Small Cell Lung Cancer Combining Metabolomics and Integrated Machine Learning

BACKGROUND

To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls.

METHODS

Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138).

RESULTS

Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients.

CONCLUSION

This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.

Loss of mitochondrial pyruvate carrier 1 supports proline-dependent proliferation and collagen biosynthesis in ovarian cancer

The pyruvate transporter MPC1 (mitochondrial pyruvate carrier 1) acts as a tumour-suppressor, loss of which correlates with a pro-tumorigenic phenotype and poor survival in several tumour types. In high-grade serous ovarian cancers (HGSOC), patients display copy number loss of MPC1 in around 78% of cases and reduced MPC1 mRNA expression. To explore the metabolic effect of reduced expression, we demonstrate that depleting MPC1 in HGSOC cell lines drives expression of key proline biosynthetic genes; PYCR1, PYCR2 and PYCR3, and biosynthesis of proline. We show that altered proline metabolism underpins cancer cell proliferation, reactive oxygen species (ROS) production, and type I and type VI collagen formation in ovarian cancer cells. Furthermore, exploring The Cancer Genome Atlas, we discovered the PYCR3 isozyme to be highly expressed in a third of HGSOC patients, which was associated with more aggressive disease and diagnosis at a younger age. Taken together, our study highlights that targeting proline metabolism is a potential therapeutic avenue for the treatment of HGSOC.

Targeting MYC at the intersection between cancer metabolism and oncoimmunology

MYC activation is a known hallmark of cancer as it governs the gene targets involved in various facets of cancer progression. Of interest, MYC governs oncometabolism through the interactions with its partners and cofactors, as well as cancer immunity via its gene targets. Recent investigations have taken interest in characterizing these interactions through multi-Omic approaches, to better understand the vastness of the MYC network. Of the several gene targets of MYC involved in either oncometabolism or oncoimmunology, few of them overlap in function. Prominent interactions have been observed with MYC and HIF-1α, in promoting glucose and glutamine metabolism and activation of antigen presentation on regulatory T cells, and its subsequent metabolic reprogramming. This review explores existing knowledge of the role of MYC in oncometabolism and oncoimmunology. It also unravels how MYC governs transcription and influences cellular metabolism to facilitate the induction of pro- or anti-tumoral immunity. Moreover, considering the significant roles MYC holds in cancer development, the present study discusses effective direct or indirect therapeutic strategies to combat MYC-driven cancer progression.

Inhibition of choline metabolism in an angioimmunoblastic T-cell lymphoma preclinical model reveals a new metabolic vulnerability as possible target for treatment

BACKGROUND

Angioimmunoblastic T-cell lymphoma (AITL) is a malignancy with very poor survival outcome, in urgent need of more specific therapeutic strategies. The drivers of malignancy in this disease are CD4+ follicular helper T cells (Tfh). The metabolism of these malignant Tfh cells was not yet elucidated. Therefore, we decided to identify their metabolic requirements with the objective to propose a novel therapeutic option.

METHODS

To reveal the prominent metabolic pathways used by the AITL lymphoma cells, we relied on metabolomic and proteomic analysis of murine AITL (mAITL) T cells isolated from our established mAITL model. We confirmed these results using AITL patient and healthy T cell expression data.

RESULTS

Strikingly, the mAITL Tfh cells were highly dependent on the second branch of the Kennedy pathway, the choline lipid pathway, responsible for the production of the major membrane constituent phosphatidylcholine. Moreover, gene expression data from Tfh cells isolated from AITL patient tumors, confirmed the upregulation of the choline lipid pathway. Several enzymes involved in this pathway such as choline kinase, catalyzing the first step in the phosphatidylcholine pathway, are upregulated in multiple tumors other than AITL. Here we showed that treatment of our mAITL preclinical mouse model with a fatty acid oxydation inhibitor, significantly increased their survival and even reverted the exhausted CD8 T cells in the tumor into potent cytotoxic anti-tumor cells. Specific inhibition of Chokα confirmed the importance of the phosphatidylcholine production pathway in neoplastic CD4 + T cells, nearly eradicating mAITL Tfh cells from the tumors. Finally, the same inhibitor induced in human AITL lymphoma biopsies cell death of the majority of the hAITL PD-1high neoplastic cells.

CONCLUSION

Our results suggest that interfering with choline metabolism in AITL reveals a specific metabolic vulnerability and might represent a new therapeutic strategy for these patients.

Isotope-Coded On-Tissue Derivatization for Quantitative Mass Spectrometry Imaging of Short-Chain Fatty Acids in Biological Tissues

Short-chain fatty acids (SCFAs), as the main metabolites of gut microbiota, are recognized as crucial players in the host's inflammatory response and metabolic disease. Imaging the spatial distributions and calculating the accurate contents of SCFAs in the heterogeneous intestinal tissue are critical to reveal their biological functions. Here, we develop an isotope-coded on-tissue derivatization method combined with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to map the spatial expressions of SCFAs in the colon tissue based on pair-labeled N,N,N-trimethyl-2-(piperazin-1-yl)ethan-1-aminium iodide (TMPA) and D3-TMPA. A noticeable increase in the MALDI-MSI sensitivity of SCFAs was achieved after on-tissue derivatization, which enables the visualization of acetic acid, propionic acid, butyric acid, valeric acid, hexanoic acid, hydroxy acetic acid, and hydroxy propionic acid in the colon tissue. Moreover, the introduction of D3-TMPA-tagged SCFAs as internal standards can significantly reduce quantitation deviation from the matrix effects, ensuring the quantitative MALDI-MSI of SCFAs. We further used this method to characterize the spatial alterations of SCFAs in the colon tissues of mice with enterocolitis. The development of this strategy provides a reliable approach to image the spatial expressions of SCFAs in tissues and paves an insight way to study the roles of SCFAs in the gut microbiota and disease.

Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview

Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.

An integrated analysis of dysregulated SCD1 in human cancers and functional verification of miR-181a-5p/SCD1 axis in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC), one of the most lethal cancers, has become a global health issue. Stearoyl-coA desaturase 1 (SCD1) has been demonstrated to play a crucial role in human cancers. However, pan-cancer analysis has revealed little evidence to date. In the current study, we systematically inspected the expression patterns and potential clinical outcomes of SCD1 in multiple human cancers. SCD1 was dysregulated in several types of cancers, and its aberrant expression acted as a diagnostic biomarker, indicating that SCD1 may play a role in tumorigenesis. We used ESCC as an example to demonstrate that SCD1 was dramatically upregulated in tumor tissues of ESCC and was associated with clinicopathological characteristics in ESCC patients. Furthermore, Kaplan-Meier analysis showed that high SCD1 expression was correlated with poor progression-free survival (PFS) and disease-free survival (DFS) in ESCC patients. The protein-protein interaction (PPI) network and module analysis by PINA database and Gephi were performed to identify the hub targets. Meanwhile, the functional annotation analysis of these hubs was constructed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Functionally, the gain-of-function of SCD1 in ESCC cells promoted cell proliferation, migration, and invasion; in contrast, loss-of-function of SCD1 in ESCC cells had opposite effects. Bioinformatic, QPCR, Western blotting and luciferase assays indicated that SCD1 was a direct target of miR-181a-5p in ESCC cells. In addition, gain-of-function of miR-181a-5p in ESCC cells reduced the cell growth, migratory, and invasive abilities. Conversely, inhibition of miR-181a-5p expression by its inhibitor in ESCC cells had opposite biological effects. Importantly, reinforced SCD1 in miR-181a-5p mimic ESCC transfectants reversed miR-181a-5p mimic-prevented malignant phenotypes of ESCC cells. Taken together, these results indicate that SCD1 expression influences tumor progression in a variety of cancers, and the miR-181a-5p/SCD1 axis may be a potential therapeutic target for ESCC treatment.

Disturbed Plasma Lipidomic Profiles in Females with Diffuse Large B-Cell Lymphoma: A Pilot Study

Lipidome dysregulation is a hallmark of cancer and inflammation. The global plasma lipidome and sub-lipidome of inflammatory pathways have not been reported in diffuse large B-cell lymphoma (DLBCL). In a pilot study of plasma lipid variation in female DLBCL patients and BMI-matched disease-free controls, we performed targeted lipidomics using LC-MRM to quantify lipid mediators of inflammation and immunity, and those known or hypothesised to be involved in cancer progression: sphingolipids, resolvin D1, arachidonic acid (AA)-derived oxylipins, such as hydroxyeicosatetraenoic acids (HETEs) and dihydroxyeicosatrienoic acids, along with their membrane structural precursors. We report on the role of the eicosanoids in the separation of DLBCL from controls, along with lysophosphatidylinositol LPI 20:4, implying notable changes in lipid metabolic and/or signalling pathways, particularly pertaining to AA lipoxygenase pathway and glycerophospholipid remodelling in the cell membrane. We suggest here the set of S1P, SM 36:1, SM 34:1 and PI 34:1 as DLBCL lipid signatures which could serve as a basis for the prospective validation in larger DLBCL cohorts. Additionally, untargeted lipidomics indicates a substantial change in the overall lipid metabolism in DLBCL. The plasma lipid profiling of DLBCL patients helps to better understand the specific lipid dysregulations and pathways in this cancer.

Spatially resolved multi-omics highlights cell-specific metabolic remodeling and interactions in gastric cancer

Mapping tumor metabolic remodeling and their spatial crosstalk with surrounding non-tumor cells can fundamentally improve our understanding of tumor biology, facilitates the designing of advanced therapeutic strategies. Here, we present an integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics to hierarchically visualize the intratumor metabolic heterogeneity and cell metabolic interactions in same gastric cancer sample. Tumor-associated metabolic reprogramming is imaged at metabolic-transcriptional levels, and maker metabolites, lipids, genes are connected in metabolic pathways and colocalized in the heterogeneous cancer tissues. Integrated data from spatial multi-omics approaches coherently identify cell types and distributions within the complex tumor microenvironment, and an immune cell-dominated "tumor-normal interface" region where tumor cells contact adjacent tissues are characterized with distinct transcriptional signatures and significant immunometabolic alterations. Our approach for mapping tissue molecular architecture provides highly integrated picture of intratumor heterogeneity, and transform the understanding of cancer metabolism at systemic level.

MYC-driven synthesis of Siglec ligands is a glycoimmune checkpoint

The Siglecs (sialic acid-binding immunoglobulin-like lectins) are glycoimmune checkpoint receptors that suppress immune cell activation upon engagement of cognate sialoglycan ligands. The cellular drivers underlying Siglec ligand production on cancer cells are poorly understood. We find the MYC oncogene causally regulates Siglec ligand production to enable tumor immune evasion. A combination of glycomics and RNA-sequencing of mouse tumors revealed the MYC oncogene controls expression of the sialyltransferase St6galnac4 and induces a glycan known as disialyl-T. Using in vivo models and primary human leukemias, we find that disialyl-T functions as a "don't eat me" signal by engaging macrophage Siglec-E in mice or the human ortholog Siglec-7, thereby preventing cancer cell clearance. Combined high expression of MYC and ST6GALNAC4 identifies patients with high-risk cancers and reduced tumor myeloid infiltration. MYC therefore regulates glycosylation to enable tumor immune evasion. We conclude that disialyl-T is a glycoimmune checkpoint ligand. Thus, disialyl-T is a candidate for antibody-based checkpoint blockade, and the disialyl-T synthase ST6GALNAC4 is a potential enzyme target for small molecule-mediated immune therapy.

Metabolic Reprogramming and Potential Therapeutic Targets in Lymphoma

Lymphoma is a heterogeneous group of diseases that often require their metabolism program to fulfill the demand of cell proliferation. Features of metabolism in lymphoma cells include high glucose uptake, deregulated expression of enzymes related to glycolysis, dual capacity for glycolytic and oxidative metabolism, elevated glutamine metabolism, and fatty acid synthesis. These aberrant metabolic changes lead to tumorigenesis, disease progression, and resistance to lymphoma chemotherapy. This metabolic reprogramming, including glucose, nucleic acid, fatty acid, and amino acid metabolism, is a dynamic process caused not only by genetic and epigenetic changes, but also by changes in the microenvironment affected by viral infections. Notably, some critical metabolic enzymes and metabolites may play vital roles in lymphomagenesis and progression. Recent studies have uncovered that metabolic pathways might have clinical impacts on the diagnosis, characterization, and treatment of lymphoma subtypes. However, determining the clinical relevance of biomarkers and therapeutic targets related to lymphoma metabolism is still challenging. In this review, we systematically summarize current studies on metabolism reprogramming in lymphoma, and we mainly focus on disorders of glucose, amino acids, and lipid metabolisms, as well as dysregulation of molecules in metabolic pathways, oncometabolites, and potential metabolic biomarkers. We then discuss strategies directly or indirectly for those potential therapeutic targets. Finally, we prospect the future directions of lymphoma treatment on metabolic reprogramming.

Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is one of the least specimen destructive ambient ionization mass spectrometry tissue imaging methods. It enables rapid simultaneous mapping, measurement, and identification of hundreds of molecules from an unmodified tissue sample. Over the years, since its first introduction as an imaging technique in 2005, DESI-MSI has been extensively developed as a tool for separating tissue regions of various histopathologic classes for diagnostic applications. Recently, DESI-MSI has also emerged as a versatile technique that enables drug discovery and can guide the efficient development of drug delivery systems. For example, it has been increasingly employed for uncovering unique patterns of in vivo drug distribution, the discovery of potentially treatable biochemical pathways, revealing novel druggable targets, predicting therapeutic sensitivity of diseased tissues, and identifying early tissue response to pharmacological treatment. These and other recent advances in implementing DESI-MSI as the tool for the development of novel therapies are highlighted in this review.

Gene expression profiling and FDG-PET radiomics uncover radiometabolic signatures associated with outcome in DLBCL

Emerging evidence indicates that chemoresistance is closely related to altered metabolism in cancer. Here, we hypothesized that distinct metabolic gene expression profiling (GEP) signatures might be correlated with outcome and with specific fluorodeoxyglucose positron emission tomography (FDG-PET) radiomic profiles in diffuse large B-cell lymphoma (DLBCL). We retrospectively analyzed a discovery cohort of 48 consecutive patients with DLBCL treated at our center with standard first-line chemoimmunotherapy by performing targeted GEP (T-GEP)- and FDG-PET radiomic analyses on the same target lesions at baseline. T-GEP-based metabolic profiling identified a 6-gene signature independently associated with outcomes in univariate and multivariate analyses. This signature included genes regulating mitochondrial oxidative metabolism (SCL25A1, PDK4, PDPR) that were upregulated and was inversely associated with genes involved in hypoxia and glycolysis (MAP2K1, HIF1A, GBE1) that were downregulated. These data were validated in 2 large publicly available cohorts. By integrating FDG-PET radiomics and T-GEP, we identified a radiometabolic signature (RadSig) including 4 radiomic features (histo kurtosis, histo energy, shape sphericity, and neighboring gray level dependence matrix contrast), significantly associated with the metabolic GEP-based signature (r = 0.43, P = .0027) and with progression-free survival (P = .028). These results were confirmed using different target lesions, an alternative segmentation method, and were validated in an independent cohort of 64 patients. RadSig retained independent prognostic value in relation to the International Prognostic Index score and metabolic tumor volume (MTV). Integration of RadSig and MTV further refined prognostic stratification. This study provides the proof of principle for the use of FDG-PET radiomics as a tool for noninvasive assessment of cancer metabolism and prognostic stratification in DLBCL.

COX-2/PGE2 upregulation contributes to the chromosome 17p-deleted lymphoma

Deletions of chromosome 17p, where TP53 gene locates, are the most frequent chromosome alterations in human cancers and associated with poor outcomes in patients. Our previous work suggested that there were p53-independent mechanisms involved in chromosome 17p deletions-driven cancers. Here, we report that altered arachidonate metabolism, due to the deficiency of mouse Alox8 on chromosome 11B3 (homologous to human ALOX15B on chromosome 17p), contributes to the B cell malignancy. While the metabolites produced from lipoxygenase pathway reduced, chromosome 11B3 deletions or Alox8 loss, lead to upregulating its paralleling cyclooxygenase pathway, indicated by the increased levels of oncometabolite prostaglandin E2. Ectopic PGE2 prevented the apoptosis and differentiation of pre-B cells. Further studies revealed that Alox8 deficiency dramatically and specifically induced Cox-2(Ptgs2) gene expression. Repressing Cox-2 by its shRNAs impaired the tumorigenesis driven by Alox8 loss. And, in turn, tumor cells with Alox8 or 11B3 loss were sensitive to the COX-2 inhibitor celecoxib. This correlation between COX-2 upregulation and chromosome 17p deletions was consistent in human B-cell lymphomas. Hence, our studies reveal that the arachidonate metabolism abnormality with unbalanced ALOX and COX pathways underlies human cancers with 17p deletions and suggest new susceptibility for this disease.

Altered serum lipid levels are associated with prognosis of diffuse large B cell lymphoma and influenced by utility of rituximab

Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, and the prognosis of the disease varied. This research aims to investigate the impact of serum lipid level on the outcome of DLBCL patients and their interaction with rituximab (RTX). Data of newly diagnosed DLBCL in the third affiliated hospital of Soochow University were retrospectively collected. Baseline serum lipid levels, clinical data, and survival information were simultaneously recorded. Data of healthy controls were collected with age matching. Serum lipid levels significantly differed for the patients. All were transformed into categorical variables for the analysis of survival. During a median follow-up of 58 months, 32.8% patients died. Univariate analysis revealed all serum lipid indicators were associated with overall survival (OS); all except for total cholesterol (TC) and apolipoprotein B (apoB) showed significant impact on progression-free survival (PFS). Multivariable analysis confirmed the adverse effect of triglyceride (TG) on PFS (P = 0.013) and favorable impact of high-density lipoprotein (HDL) on OS (P = 0.003). For cases treated without RTX, apolipoprotein A (apoA) had independent favorable effect on both PFS (P = 0.004) and OS (P = 0.001). Comparably, for patients who received RTX, HDL showed remarkably predictive value of PFS (P = 0.011) and OS (P = 0.019). In conclusion, the abnormal serum lipids occurred throughout the course of DLBCL, and the associations of serum lipids and the prognosis of the disease were interfered by RTX. Trial registration: 2022()CL033; June 26, 2022, retrospectively registered.

Long-chain polyunsaturated lipids associated with responsiveness to anti-PD-1 therapy are colocalized with immune infiltrates in the tumor microenvironment

The programmed cell death protein-1 (PD-1) is highly expressed on the surface of antigen-specific exhausted T cells and, upon interaction with its ligand PD-L1, can result in inhibition of the immune response. Anti-PD-1 treatment has been shown to extend survival and result in durable responses in several cancers, yet only a subset of patients benefit from this therapy. Despite the implication of metabolic alteration following cancer immunotherapy, mechanistic associations between antitumor responses and metabolic changes remain unclear. Here, we used desorption electrospray ionization mass spectrometry imaging to examine the lipid profiles of tumor tissue from three syngeneic murine models with varying treatment sensitivity at the baseline and at three time points post-anti-PD-1 therapy. These imaging experiments revealed specific alterations in the lipid profiles associated with the degree of response to treatment and allowed us to identify a significant increase of long-chain polyunsaturated lipids within responsive tumors following anti-PD-1 therapy. Immunofluorescence imaging of tumor tissues also demonstrated that the altered lipid profile associated with treatment response is localized to dense regions of tumor immune infiltrates. Overall, these results indicate that effective anti-PD-1 therapy modulates lipid metabolism in tumor immune infiltrates, and we thereby propose that further investigation of the related immune-metabolic pathways may be useful for better understanding success and failure of anti-PD-1 therapy.

Lessons from Using Genetically Engineered Mouse Models of MYC-Induced Lymphoma

Oncogenic overexpression of MYC leads to the fatal deregulation of signaling pathways, cellular metabolism, and cell growth. MYC rearrangements are found frequently among non-Hodgkin B-cell lymphomas enforcing MYC overexpression. Genetically engineered mouse models (GEMMs) were developed to understand MYC-induced B-cell lymphomagenesis. Here, we highlight the advantages of using Eµ-Myc transgenic mice. We thoroughly compiled the available literature to discuss common challenges when using such mouse models. Furthermore, we give an overview of pathways affected by MYC based on knowledge gained from the use of GEMMs. We identified top regulators of MYC-induced lymphomagenesis, including some candidates that are not pharmacologically targeted yet.

Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics

IMPORTANCE

Despite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics.

OBJECTIVE

To develop and characterize a gross morphologic classification system for HGSOC.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021.

EXPOSURES

Gross tumor morphologic characteristics.

MAIN OUTCOMES AND MEASURES

Clinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared.

RESULTS

Of 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10-24), hypoxia (FDR q-value, 1.52 × 10-5), and angiogenesis pathways (FDR q-value, 2.11 × 10-2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10-9) and cell cycle progression (FDR q-value, 1.10 × 10-5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes.

CONCLUSIONS AND RELEVANCE

This study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies.

Serum Metabolomics Profiling Reveals Metabolic Alterations Prior to a Diagnosis with Non-Small Cell Lung Cancer among Chinese Community Residents: A Prospective Nested Case-Control Study

The present high mortality of lung cancer in China stems mainly from the lack of feasible, non-invasive and early disease detection biomarkers. Serum metabolomics profiling to reveal metabolic alterations could expedite the disease detection process and suggest those patients who are harboring disease. Using a nested case-control design, we applied ultra-high-performance liquid chromatography/mass spectrometry (LC-MS)-based serum metabolomics to reveal the metabolomic alterations and to indicate the presence of non-small cell lung cancer (NSCLC) using serum samples collected prior to disease diagnoses. The studied serum samples were collected from 41 patients before a NSCLC diagnosis (within 3.0 y) and 38 matched the cancer-free controls from the prospective Shanghai Suburban Adult Cohort. The NSCLC patients markedly presented cellular metabolism alterations in serum samples collected prior to their disease diagnoses compared with the cancer-free controls. In total, we identified 18 significantly expressed metabolites whose relative abundance showed either an upward or a downward trend, with most of them being lipid and lipid-like molecules, organic acids, and nitrogen compounds. Choline metabolism in cancer, sphingolipid, and glycerophospholipid metabolism emerged as the significant metabolic disturbance of NSCLC. The metabolites involved in these biological processes may be the distinctive features associated with NSCLC prior to a diagnosis.

Super-enhancer-associated INSM2 regulates lipid metabolism by modulating mTOR signaling pathway in neuroblastoma

Background

Abnormal lipid metabolism is one of the most prominent metabolic changes in cancer. Studies have shown that lipid metabolism also plays an important role in neuroblastoma. We recently discovered that the insulinoma-associated 2 gene (INSM2) could regulate lipid metabolism in neuroblastoma (NB) and is improperly controlled by super enhancers, a mammalian genome region that has been shown to control the expression of NB cell identity genes. However, the specific molecular pathways by which INSM2 leads to NB disease development are unknown.

Results

We identified INSM2 as a gene regulated by super enhancers in NB. In addition, INSM2 expression levels were significantly upregulated in NB and correlated with poor prognosis in patients. We found that INSM2 drives the growth of NB cell lines both in vitro and in vivo. Knocking down INSM2 inhibited fatty acid metabolism in NB cells. Mechanistically, INSM2 regulates the expression of SREBP1 by regulating the mTOR signaling pathway, which in turn affects lipid metabolism, thereby mediating the occurrence and development of neuroblastoma.

Conclusion

INSM2 as a super-enhancer-associated gene could regulates lipid metabolism by modulating mTOR signaling pathway in neuroblastoma.

Targeting lipid metabolism in the treatment of ovarian cancer

Cancer cells undergo alterations in lipid metabolism to support their high energy needs, tumorigenesis and evade an anti-tumor immune response. Alterations in fatty acid production are controlled by multiple enzymes, chiefly Acetyl CoA Carboxylase, ATP-Citrate Lyase, Fatty Acid Synthase, and Stearoyl CoA Desaturase 1. Ovarian cancer (OC) is a common gynecological malignancy with a high rate of aggressive carcinoma progression and drug resistance. The accumulation of unsaturated fatty acids in ovarian cancer supports cell growth, increased cancer cell migration, and worse patient outcomes. Ovarian cancer cells also expand their lipid stores via increased uptake of lipids using fatty acid translocases, fatty acid-binding proteins, and low-density lipoprotein receptors. Furthermore, increased lipogenesis and lipid uptake promote chemotherapy resistance and dampen the adaptive immune response needed to eliminate tumors. In this review, we discuss the role of lipid synthesis and metabolism in driving tumorigenesis and drug resistance in ovarian cancer conferring poor prognosis and outcomes in patients. We also cover some aspects of how lipids fuel ovarian cancer stem cells, and how these metabolic alterations in intracellular lipid content could potentially serve as biomarkers of ovarian cancer.

Novel Insights on Lipid Metabolism Alterations in Drug Resistance in Cancer

Chemotherapy is one of the primary treatments for most human cancers. Despite great progress in cancer therapeutics, chemotherapy continues to be important for improving the survival of cancer patients, especially for those who has unresectable metastatic tumors or fail to respond to immunotherapy. However, intrinsic or acquired chemoresistance results in tumor recurrence, which remains a major obstacle in anti-cancer treatment. The high prevalence of chemoresistant cancer makes it urgent to deepen our understanding on chemoresistance mechanisms and to develop novel therapeutic strategies. Multiple mechanisms, including drug efflux, enhanced DNA damage reparability, increased detoxifying enzymes levels, presence of cancer stem cells (CSCs), epithelial mesenchymal transition (EMT), autophagy, ferroptosis and resistance to apoptosis, underlie the development of chemoresistance. Recently, accumulating evidence suggests that lipid metabolism alteration is closely related to drug resistance in tumor. Targeting lipid metabolism in combination with traditional chemotherapeutic drugs is a promising strategy to overcome drug resistance. Therefore, this review compiles the current knowledge about aberrant lipid metabolism in chemoresistant cancer, mainly focusing on aberrant fatty acid metabolism, and presents novel therapeutic strategies targeting altered lipid metabolism to overcome chemoresistance in cancer.

Sphingolipids and Lymphomas: A Double-Edged Sword

Lymphomas are a highly heterogeneous group of hematological neoplasms. Given their ethiopathogenic complexity, their classification and management can become difficult tasks; therefore, new approaches are continuously being sought. Metabolic reprogramming at the lipid level is a hot topic in cancer research, and sphingolipidomics has gained particular focus in this area due to the bioactive nature of molecules such as sphingoid bases, sphingosine-1-phosphate, ceramides, sphingomyelin, cerebrosides, globosides, and gangliosides. Sphingolipid metabolism has become especially exciting because they are involved in virtually every cellular process through an extremely intricate metabolic web; in fact, no two sphingolipids share the same fate. Unsurprisingly, a disruption at this level is a recurrent mechanism in lymphomagenesis, dissemination, and chemoresistance, which means potential biomarkers and therapeutical targets might be hiding within these pathways. Many comprehensive reviews describing their role in cancer exist, but because most research has been conducted in solid malignancies, evidence in lymphomagenesis is somewhat limited. In this review, we summarize key aspects of sphingolipid biochemistry and discuss their known impact in cancer biology, with a particular focus on lymphomas and possible therapeutical strategies against them.

Azapodophyllotoxin Causes Lymphoma and Kidney Cancer Regression by Disrupting Tubulin and Monoglycerols

A natural compound screen identified several anticancer compounds, among which azapodophyllotoxin (AZP) was found to be the most potent. AZP caused decreased viability of both mouse and human lymphoma and renal cell cancer (RCC) tumor-derived cell lines. Novel AZP derivatives were synthesized and screened identifying compound NSC750212 to inhibit the growth of both lymphoma and RCC both in vitro and in vivo. A nanoimmunoassay was used to assess the NSC750212 mode of action in vivo. On the basis of the structure of AZP and its mode of action, AZP disrupts tubulin polymerization. Through desorption electrospray ionization mass spectrometry imaging, NSC750212 was found to inhibit lipid metabolism. NSC750212 suppresses monoglycerol metabolism depleting lipids and thereby inhibits tumor growth. The dual mode of tubulin polymerization disruption and monoglycerol metabolism inhibition makes NSC750212 a potent small molecule against lymphoma and RCC.

The MYC oncogene - the grand orchestrator of cancer growth and immune evasion

The MYC proto-oncogenes encode a family of transcription factors that are among the most commonly activated oncoproteins in human neoplasias. Indeed, MYC aberrations or upregulation of MYC-related pathways by alternate mechanisms occur in the vast majority of cancers. MYC proteins are master regulators of cellular programmes. Thus, cancers with MYC activation elicit many of the hallmarks of cancer required for autonomous neoplastic growth. In preclinical models, MYC inactivation can result in sustained tumour regression, a phenomenon that has been attributed to oncogene addiction. Many therapeutic agents that directly target MYC are under development; however, to date, their clinical efficacy remains to be demonstrated. In the past few years, studies have demonstrated that MYC signalling can enable tumour cells to dysregulate their microenvironment and evade the host immune response. Herein, we discuss how MYC pathways not only dictate cancer cell pathophysiology but also suppress the host immune response against that cancer. We also propose that therapies targeting the MYC pathway will be key to reversing cancerous growth and restoring antitumour immune responses in patients with MYC-driven cancers.

Integrative Metabolomic and Lipidomic Profiling of Lung Squamous Cell Carcinoma for Characterization of Metabolites and Intact Lipid Species Related to the Metastatic Potential

SQCC is a major type of NSCLC, which is a major cause of cancer-related deaths, and there were no reports regarding the prediction of metastatic potential of lung SQCC by metabolomic and lipidomic profiling. In this study, metabolomic and lipidomic profiling of lung SQCC were performed to predict its metastatic potential and to suggest potential therapeutic targets for the inhibition of lung SQCC metastasis. Human bronchial epithelial cells and four lung SQCC cell lines with different metastatic potentials were analyzed using gas chromatography-mass spectrometry and direct infusion-mass spectrometry. Based on the obtained metabolic and lipidomic profiles, we constructed models to predict the metastatic potential of lung SQCC; glycerol, putrescine, β-alanine, hypoxanthine, inosine, myo-inositol, phosphatidylinositol (PI) 18:1/18:1, and PI 18:1/20:4 were suggested as characteristic metabolites and intact lipid species associated with lung SQCC metastatic potential. In this study, we established predictive models for the metastatic potential of lung SQCC; furthermore, we identified metabolites and intact lipid species relevant to lung SQCC metastatic potential that may serve as potential therapeutic targets for the inhibition of lung SQCC metastasis.

Direct Liquid Extraction and Ionization Techniques for Understanding Multimolecular Environments in Biological Systems (Secondary Publication)

A combination of direct liquid extraction using a small volume of solvent and electrospray ionization allows the rapid measurement of complex chemical components in biological samples and visualization of their distribution in tissue sections. This review describes the development of such techniques and their application to biological research since the first reports in the early 2000s. An overview of electrospray ionization, ion suppression in samples, and the acceleration of specific chemical reactions in charged droplets is also presented. Potential future applications for visualizing multimolecular environments in biological systems are discussed.

Investigation of the lipidomic changes in differentiated glioblastoma cells after drug treatment using MALDI-MS

Lipids differences between tumor and normal tissue have been proved to be of diagnostic and therapeutic significance. The research of lipidomics in tumor is more and more important. Mass spectrometry like matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) can be more convenient and informative for lipids researching in biological and clinical researches. Most of malignant tumors like glioblastoma are characterized by incomplete differentiation, so differentiation therapy has made important progress in tumor treatment. Lipid profiles changes after therapy are worthy investigating. In our study, glioblastoma cell line U87-MG cells were treated by inducers of sodium phenylbutyrate (SPB) and all-trans retinoic acid (ATRA). The changes in lipids on cell membrane were profiled by MALDI-MS. The differentiation degree was assessed by cell proliferation, cell cycle, morphology and protein expression before MALDI-MS analysis. Comparing the inducer treated and untreated U87-MG cells, reduced proliferation rate, blocked cell cycle, benign nucleus morphology and changed expression of protein CD133 and glial fibrillary acidic protein (GFAP), were found after drug treatment. Moreover, the lipids of cell membrane presented distinguished differences in the drug treated cells. Most of the glycerophosphocholines (PC) with an increasing abundance are unsaturated PCs (PC (38:1), 816 m/z; PC (36:1), 788 m/z; PC (31:1), 725 m/z), and those decreasing are saturated PCs (PC (32:0), 734 m/z). These results provide the lipidomic differentiation which may be a significant guidance for evaluating the therapeutic effect of tumor therapy.

Breaking Through the Barrier: Regulatory Considerations Relevant to Ambient Mass Spectrometry at the Bedside

Rapid characterization of tissue disorder using ambient mass spectrometry (MS) techniques, requiring little to no preanalytical preparations of sampled tissues, has been shown using a variety of ion sources and with many disease classes. A brief overview of ambient MS in clinical applications, the state of the art in regulatory affairs, and recommendations to facilitate adoption for use at the bedside are presented. Unique challenges in the validation of untargeted MS methods and additional safety and compliance requirements for deployment within a clinical setting are further discussed. Development of a harmonized validation strategy for ambient MS methods is emphasized.

Metabotype analysis of Mthfd1l-null mouse embryos using desorption electrospray ionization mass spectrometry imaging

Mammalian folate-dependent one-carbon (1C) metabolism provides the building blocks essential during development via amino acid interconversion, methyl-donor production, regeneration of redox factors, and de novo purine and thymidylate synthesis. Folate supplementation prevents many neural tube defects (NTDs) that occur during the embryonic process of neurulation. The mechanism by which folate functions during neurulation is not well understood, and not all NTDs are preventable by folate supplementation. Mthfd1l is a mitochondrial 1C metabolism enzyme that produces formate, a 1C donor that fuels biosynthesis and the methyl cycle in the cytoplasm. Homozygous deletion of the Mthfd1l gene in mice (Mthfd1l^z/z) causes embryonic lethality, developmental delay, and folate-resistant NTDs. These mice also have defects in cranial mesenchyme formation. In this work, mass spectrometry imaging was used to obtain ion maps of the cranial mesenchyme that identified the spatial distribution and relative abundance of metabolites in wild-type and Mthfd1l^z/z embryos. The relative abundances of purine and thymidylate derivatives, as well as amino acids, were diminished in the cranial mesenchyme of Mthfd1l^z/z embryos. Loss of Mthfd1l activity in this region also led to abnormal levels of methionine and dysregulated energy metabolism. These alterations in metabolism suggest possible approaches to preventing NTDs in humans.

Metabolic Abnormalities in Patients with Chronic Disorders of Consciousness

The vegetative state (VS) and minimally conscious state (MCS) are two major types of chronic disorders of consciousness (DoC). The assessment of these two consciousness states generally relies on the Coma Recovery Scale-Revised (CRS-R) score, but a high misdiagnosis rate limits the generalized use of this score. To identify metabolites in human plasma that can accurately distinguish VS from MCS patients, comprehensive plasma metabolic profiles were obtained with targeted metabolomics analysis and untargeted and targeted lipidomics analysis. Univariate and multivariate analyses were used to assess the significance of differences. Compared with healthy controls (HCs), the DoC groups, Emerged from Minimally Conscious State (EMCS) group and Alzheimer’s disease (AD) group had significantly different metabolic profiles. Purine metabolism pathway differed the most between the DoC (MCS and VS) and HC groups. In this pathway, adenosine, ADP, and AMP, which are the derived products of ATP degradation, were decreased in the MCS and VS groups compared to healthy controls. More importantly, we identified certain lipids for which the levels were enriched in the VS or MCS groups. Specifically, phosphatidylcholine, (38:5)-H (PC(38:5)-H), and arachidonic acid (AA) differed substantially between the VS and MCS groups and may be used to distinguish these two groups of patients. Together, our findings suggest that metabolic profiling is significantly altered in patients with chronic DoC.

Inhibition of fatty acid synthesis induces differentiation and reduces tumor burden in childhood neuroblastoma

Many metabolic pathways, including lipid metabolism, are rewired in tumors to support energy and biomass production and to allow adaptation to stressful environments. Neuroblastoma is the second deadliest solid tumor in children. Genetic aberrations, as the amplification of the MYCN-oncogene, correlate strongly with disease progression. Yet, there are only a few molecular targets successfully exploited in the clinic. Here we show that inhibition of fatty acid synthesis led to increased neural differentiation and reduced tumor burden in neuroblastoma xenograft experiments independently of MYCN-status. This was accompanied by reduced levels of the MYCN or c-MYC oncoproteins and activation of ERK signaling. Importantly, the expression levels of genes involved in de novo fatty acid synthesis showed prognostic value for neuroblastoma patients. Our findings demonstrate that inhibition of de novo fatty acid synthesis is a promising pharmacological intervention strategy for the treatment of neuroblastoma independently of MYCN-status.

Mass spectrometry-based phospholipid imaging: methods and findings

Introduction: Imaging is a technique used for direct visualization of the internal structure or distribution of biomolecules of a living system in a two-dimensional or three-dimensional fashion. Phospholipids are important structural components of biological membranes and have been reported to be associated with various human diseases. Therefore, the visualization of phospholipids is crucial to understand the underlying mechanism of cellular and molecular processes in normal and diseased conditions. Areas covered: Mass spectrometry imaging (MSI) has enabled the label-free imaging of individual phospholipids in biological tissues and cells. The commonly used MSI techniques include matrix-assisted laser desorption ionization-MSI (MALDI-MSI), desorption electrospray ionization-MSI (DESI-MSI), and secondary ion mass spectrometry (SIMS) imaging. This special report described those methods, summarized the findings, and discussed the future development for the imaging of phospholipids. Expert opinion: Phospholipids imaging in complex biological samples has been significantly benefited from the development of MSI methods. In MALDI-MSI, novel matrix that produces homogenous crystals exclusively with polar lipids is important for phospholipids imaging with greater efficiency and higher spatial resolution. DESI-MSI has the potential of live imaging of the biological surface while SIMS is expected to image at the subcellular level in the near future.

Metabolic Effects of Recurrent Genetic Aberrations in Multiple Myeloma

Oncogene activation and malignant transformation exerts energetic, biosynthetic and redox demands on cancer cells due to increased proliferation, cell growth and tumor microenvironment adaptation. As such, altered metabolism is a hallmark of cancer, which is characterized by the reprogramming of multiple metabolic pathways. Multiple myeloma (MM) is a genetically heterogeneous disease that arises from terminally differentiated B cells. MM is characterized by reciprocal chromosomal translocations that often involve the immunoglobulin loci and a restricted set of partner loci, and complex chromosomal rearrangements that are associated with disease progression. Recurrent chromosomal aberrations in MM result in the aberrant expression of MYC, cyclin D1, FGFR3/MMSET and MAF/MAFB. In recent years, the intricate mechanisms that drive cancer cell metabolism and the many metabolic functions of the aforementioned MM-associated oncogenes have been investigated. Here, we discuss the metabolic consequences of recurrent chromosomal translocations in MM and provide a framework for the identification of metabolic changes that characterize MM cells.

Advances in understanding and in multi-disciplinary methodology used to assess lipid regulation of signalling cascades from the cancer cell plasma membrane

The lipid bilayer is a functional component of cells, forming a stable platform for the initiation of key biological processes, including cell signalling. There are distinct changes in the lipid composition of cell membranes during oncogenic transformation resulting in aberrant activation and inactivation of signalling transduction pathways. Studying the role of the cell membrane in cell signalling is challenging, since techniques are often limited to by timescale, resolution, sensitivity, and averaging. To overcome these limitations, combining 'computational', 'wet-lab' and 'semi-dry' approaches offers the best opportunity to resolving complex biological processes involved in membrane organisation. In this review, we highlight analytical tools that have been applied for the study of cell signalling initiation from the cancer cell membranes through computational microscopy, biological assays, and membrane biophysics. The cancer therapeutic potential of extracellular membrane-modulating agents, such as cholesterol-reducing agents is also discussed, as is the need for future collaborative inter-disciplinary research for studying the role of the cell membrane and its components in cancer therapy.

Optimal Clinical Management and the Molecular Biology of Angiosarcomas

Angiosarcomas comprise less than 3% of all soft tissue sarcomas but have a poor prognosis. Most angiosarcomas occur without obvious risk factors but secondary angiosarcoma could arise after radiotherapy or chronic lymphedema. Surgery remains the standard treatment for localized angiosarcoma but neoadjuvant systemic treatment may improve the curability. For advanced angiosarcoma, anthracyclines and taxanes are the main chemotherapy options. Anti-angiogenic agents have a substantial role but the failure of a randomized phase 3 trial of pazopanib with or without an anti-endoglin antibody brings a challenge to future trials in angiosarcomas. Immune checkpoint inhibitors as single agents or in combination with oncolytic virus may play an important role but the optimal duration remains to be investigated. We also report the current understanding of the molecular pathways involved in angiosarcoma pathogenesis including MYC amplification, activation of angiogenic pathways and different molecular alterations that are associated with angiosarcomas of different aetiology. The success of the patient-partnered Angiosarcoma Project (ASCProject) has provided not only detailed insights into the molecular features of angiosarcomas of different origins but also offers a template for future fruitful collaborations between patients, physicians, and researchers. Lastly, we provide our perspective of future developments in optimizing the clinical management of angiosarcomas.

Inositol-Requiring Enzyme 1α Promotes Zika Virus Infection through Regulation of Stearoyl Coenzyme A Desaturase 1-Mediated Lipid Metabolism

Zika virus (ZIKV) is an emerging mosquito-borne flavivirus which has become a global epidemic threat due to its rapid spread and association with serious consequences of infection, including neonatal microcephaly. Inositol-requiring enzyme 1α (IRE1α) is an endoplasmic reticulum (ER)-related transmembrane protein that mediates unfolded protein response (UPR) pathway and has been indicated to play an important role in flavivirus replication. However, the mechanism of how IRE1α affects ZIKV replication remains unknown. In this study, we explored the role of IRE1α in ZIKV infection in vitro and in vivo by using CRISPR/Cas9-based gene knockout and RNA interference-based gene knockdown techniques. Both knockout and knockdown of IRE1α dramatically reduced ZIKV replication levels, including viral RNA levels, protein expression, and titers in different human cell lines. Trans-complementation with IRE1α restored viral replication levels decreased by IRE1α depletion. Furthermore, the proviral effect of IRE1α was dependent on its kinase and RNase activities. Importantly, we found that IRE1α promoted the replication of ZIKV through upregulating the accumulation of monounsaturated fatty acid (MUFA) rate-limiting enzyme stearoyl coenzyme A (stearoyl-CoA) desaturase 1 (SCD1), which further affected the production of oleic acid (OA) and lipid droplet. Finally, our data demonstrated that in the brain tissues of ZIKV-infected mice, the replication levels of ZIKV and virus-related lesions were significantly suppressed by both the kinase and RNase inhibitors of IRE1α. Taken together, our results identified IRE1α as a ZIKV dependency factor which promotes viral replication through affecting SCD1-mediated lipid metabolism, potentially providing a novel molecular target for the development of anti-ZIKV agents.IMPORTANCE Zika virus (ZIKV) has been linked to serious neurologic disorders and causes widespread concern in the field of global public health. Inositol requiring enzyme 1α (IRE1α) is an ER-related transmembrane protein that mediates unfolded protein response (UPR) pathway. Here, we revealed that IRE1α is a proviral factor for ZIKV replication both in culture cells and mice model, which relies on its kinase and RNase activities. Importantly, we further provided evidence that upon ZIKV infection, IRE1α is activated and splices XBP1 mRNA which enhances the expression of monounsaturated fatty acids rate-limiting enzyme stearoyl coenzyme A (stearoyl-CoA) desaturase 1 (SCD1) and subsequent lipid droplet production. Our data uncover a novel mechanism of IRE1α proviral effect by modulating lipid metabolism, providing the first evidence of a close relationship between IRE1α-mediated UPR, lipid metabolism, and ZIKV replication and indicating IRE1α inhibitors as potentially effective anti-ZIKV agents.

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Addressing Cellular Heterogeneity in Cancer through Precision Proteomics

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

Regulation of cancer cell metabolism: oncogenic MYC in the driver's seat

Cancer cells must rewire cellular metabolism to satisfy the demands of unbridled growth and proliferation. As such, most human cancers differ from normal counterpart tissues by a plethora of energetic and metabolic reprogramming. Transcription factors of the MYC family are deregulated in up to 70% of all human cancers through a variety of mechanisms. Oncogenic levels of MYC regulates almost every aspect of cellular metabolism, a recently revisited hallmark of cancer development. Meanwhile, unrestrained growth in response to oncogenic MYC expression creates dependency on MYC-driven metabolic pathways, which in principle provides novel targets for development of effective cancer therapeutics. In the current review, we summarize the significant progress made toward understanding how MYC deregulation fuels metabolic rewiring in malignant transformation.

Multiplatform Investigation of Plasma and Tissue Lipid Signatures of Breast Cancer Using Mass Spectrometry Tools

Plasma and tissue from breast cancer patients are valuable for diagnostic/prognostic purposes and are accessible by multiple mass spectrometry (MS) tools. Liquid chromatography-mass spectrometry (LC-MS) and ambient mass spectrometry imaging (MSI) were shown to be robust and reproducible technologies for breast cancer diagnosis. Here, we investigated whether there is a correspondence between lipid cancer features observed by desorption electrospray ionization (DESI)-MSI in tissue and those detected by LC-MS in plasma samples. The study included 28 tissues and 20 plasma samples from 24 women with ductal breast carcinomas of both special and no special type (NST) along with 22 plasma samples from healthy women. The comparison of plasma and tissue lipid signatures revealed that each one of the studied matrices (i.e., blood or tumor) has its own specific molecular signature and the full interposition of their discriminant ions is not possible. This comparison also revealed that the molecular indicators of tissue injury, characteristic of the breast cancer tissue profile obtained by DESI-MSI, do not persist as cancer discriminators in peripheral blood even though some of them could be found in plasma samples.

The choice of tissue fixative is a key determinant for mass spectrometry imaging based tumor metabolic reprogramming characterization

The application of mass spectrometry imaging (MSI) for the study of spatiotemporal alterations of the metabolites in tumors has brought a number of significant biological results. At present, metabolite profiling based on MSI is typically performed on frozen tissue sections; however, the majority of clinical specimens need to be fixed in tissue fixative to avoid autolysis and to preserve antigenicity. In this study, we present the global impacts of different fixatives on the MS imaging of gastric cancer tissue metabolites. The MSI performances of 17 kinds of metabolites, such as amino acids, polyamines, cholines, organic acids, polypeptides, nucleotides, nucleosides, nitrogen bases, cholesterols, fatty acids, and phospholipids, in untreated, 10% formalin-, 4% paraformaldehyde-, acetone-, and 95% ethanol-fixed gastric cancer tissues were thoroughly explored for the first time. Furthermore, we also investigated the spatial expressions of 6 metabolic enzymes, namely, GLS, FASN, CHKA, PLD2, cPLA2, and EGFR, closely related to tumor-associated metabolites. Immunohistochemical staining carried out on the same tissue sections' which have undergone MSI analysis' suggests that enzymatic characterization is feasible after metabolite imaging. Combining the spatial signatures of metabolites and pathway-related metabolic enzymes in heterogeneous tumor tissues offers an insight to understand the complex tumor metabolism. Graphical abstract.

Metabolomic profiling of dried blood spots reveals gender-specific discriminant models for the diagnosis of small cell lung cancer

The accurate diagnosis of small cell lung cancer (SCLC) at initial presentation is essential to ensure appropriate treatment. No validated blood biomarkers that could distinguish SCLC from non-small cell lung cancer (NSCLC) has yet been developed. Dried blood spot (DBS) microsampling has gained increasing interest in biomarkers discovery. In this study, we first performed metabolomic profiling of DBS samples from 37 SCLC, 40 NSCLC, and 37 controls. Two gender-specific multianalyte discriminant models were established for males and females, respectively to distinguish SCLC from NSCLC and controls. The receiver operator characteristic (ROC) curve analysis showed the diagnostic accuracy of 95% (95% CI: 83%-100%) in males SCLC using five metabolites in DBS and 94% (95% CI: 74%-100%) for females using another set of five metabolites. The robustness of the models was confirmed by the random permutation tests (P < 0.01 for both). The performance of the discriminant models was further evaluated using a validation cohort with 78 subjects. The developed discriminant models yielded an accuracy of 91% and 81% for males and females, respectively, in the validation cohort. Our results highlighted the potential clinical utility of the metabolomic profiling of DBS as a convenient and effective approach for the diagnosis of SCLC.

In Situ DESI-MSI Lipidomic Profiles of Breast Cancer Molecular Subtypes and Precursor Lesions

Clinically meaningful molecular subtypes for classification of breast cancers have been established, however, initiation and progression of these subtypes remain poorly understood. The recent development of desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) facilitates the convergence of analytical chemistry and traditional pathology, allowing chemical profiling with minimal tissue pretreatment in frozen samples. Here, we characterized the chemical composition of molecular subtypes of breast cancer with DESI-MSI. Regions of interest were identified, including invasive breast cancer (IBC), ductal carcinoma in situ (DCIS), and adjacent benign tissue (ABT), and metabolomic profiles at 200 μm elaborated using Biomap software and the Lasso method. Top ions identified in IBC regions included polyunsaturated fatty acids, deprotonated glycerophospholipids, and sphingolipids. Highly saturated lipids, as well as antioxidant molecules [taurine (m/z 124.0068), uric acid (m/z 167.0210), ascorbic acid (m/z 175.0241), and glutathione (m/z 306.0765)], were able to distinguish IBC from ABT. Moreover, luminal B and triple-negative subtypes showed more complex lipid profiles compared with luminal A and HER2 subtypes. DCIS and IBC were distinguished on the basis of cell signaling and apoptosis-related ions [fatty acids (341.2100 and 382.3736 m/z) and glycerophospholipids (PE (P-16:0/22:6, m/z 746.5099, and PS (38:3), m/z 812.5440)]. In summary, DESI-MSI identified distinct lipid composition between DCIS and IBC and across molecular subtypes of breast cancer, with potential implications for breast cancer pathogenesis. SIGNIFICANCE: These findings present the first in situ metabolomic findings of the four molecular subtypes of breast cancer, DCIS, and normal tissue, and add to the understanding of their pathogenesis.

Ambient Lipidomic Analysis of Single Mammalian Oocytes and Preimplantation Embryos Using Desorption Electrospray Ionization (DESI) Mass Spectrometry

Desorption electrospray ionization (DESI) is a spray-based ambient ionization method for mass spectrometry (MS) that generates ions in native atmospheric conditions (e.g., pressure and temperature). Ambient ionization allows in situ analysis of unmodified samples by eliminating analyte extraction and separation steps before MS. Lipid analysis of individual mammalian oocytes and preimplantation embryos is challenging because of their complex chemical composition and minute dimensions (100-300 μm in diameter). Nonetheless, DESI-MS can provide comprehensive lipidomic profiles of individual oocytes or embryos using a fast and simple workflow. DESI-MS lipid profiles include many classes of lipids such as phosphatidylcholines (PC), triacylglycerols (TAG), free fatty acids (FFA), phosphatidylethanolamines (PE), phosphatidylinositols (PI), phosphatidylserines (PS), diacylglycerols (DAG), ubiquinone, cholesterol and cholesterol derivatives (e.g., cholesterol sulfate and cholesterol esters). Depending on the mass spectrometer used, there is the additional possibility of obtaining structural information of lipids via MSⁿ, and molecular formulae via high resolution MS. Here, we describe the procedures for sample handling, the DESI-MS experimental arrangement, and the data collection and data analysis using low and high-resolution mass spectrometers (such as a linear ion trap and Orbitrap mass analyzer, respectively), as well as strategies for structural characterization of lipids. Lastly, we detail our workflow for relating the chemical information obtained by DESI-MS into the biological context of oocyte and embryo metabolism.