METTL14 downregulation drives S100A4+ monocyte-derived macrophages via MyD88/NF-κB pathway to promote MAFLD progression.

Without intervention, a considerable proportion of patients with metabolism-associated fatty liver disease (MAFLD) will progress from simple steatosis to metabolism-associated steatohepatitis (MASH), liver fibrosis, and even hepatocellular carcinoma. However, the molecular mechanisms that control progressive MAFLD have yet to be fully determined. Here, we unraveled that the expression of the N6-methyladenosine (m6A) methyltransferase METTL14 is remarkably downregulated in the livers of both patients and several murine models of MAFLD, whereas hepatocyte-specific depletion of this methyltransferase aggravated lipid accumulation, liver injury, and fibrosis. Conversely, hepatic Mettl14 overexpression alleviated the above pathophysiological changes in mice fed on a high-fat diet (HFD). Notably, in vivo and in vitro mechanistic studies indicated that METTL14 downregulation decreased the level of GLS2 by affecting the translation efficiency mediated by YTHDF1 in an m6A-depedent manner, which might help to form an oxidative stress microenvironment and accordingly recruit Cx3cr1+Ccr2+ monocyte-derived macrophages (Mo-macs). In detail, Cx3cr1+Ccr2+ Mo-macs can be categorized into M1-like macrophages and S100A4-positive macrophages and then further activate hepatic stellate cells (HSCs) to promote liver fibrosis. Further experiments revealed that CX3CR1 can activate the transcription of S100A4 via CX3CR1/MyD88/NF-κB signaling pathway in Cx3cr1+Ccr2+ Mo-macs. Restoration of METTL14 or GLS2, or interfering with this signal transduction pathway such as inhibiting MyD88 could ameliorate liver injuries and fibrosis. Taken together, these findings indicate potential therapies for the treatment of MAFLD progression.

Frozen tissue coring and layered histological analysis improves cell type-specific proteogenomic characterization of pancreatic adenocarcinoma.

BACKGROUND: Omics characterization of pancreatic adenocarcinoma tissue is complicated by the highly heterogeneous and mixed populations of cells. We evaluate the feasibility and potential benefit of using a coring method to enrich specific regions from bulk tissue and then perform proteogenomic analyses. METHODS: We used the Biopsy Trifecta Extraction (BioTExt) technique to isolate cores of epithelial-enriched and stroma-enriched tissue from pancreatic tumor and adjacent tissue blocks. Histology was assessed at multiple depths throughout each core. DNA sequencing, RNA sequencing, and proteomics were performed on the cored and bulk tissue samples. Supervised and unsupervised analyses were performed based on integrated molecular and histology data. RESULTS: Tissue cores had mixed cell composition at varying depths throughout. Average cell type percentages assessed by histology throughout the core were better associated with KRAS variant allele frequencies than standard histology assessment of the cut surface. Clustering based on serial histology data separated the cores into three groups with enrichment of neoplastic epithelium, stroma, and acinar cells, respectively. Using this classification, tumor overexpressed proteins identified in bulk tissue analysis were assigned into epithelial- or stroma-specific categories, which revealed novel epithelial-specific tumor overexpressed proteins. CONCLUSIONS: Our study demonstrates the feasibility of multi-omics data generation from tissue cores, the necessity of interval H&E stains in serial histology sections, and the utility of coring to improve analysis over bulk tissue data.

Gender dimorphism in hepatocarcinogenesis-DNA methylation modification regulated X-chromosome inactivation escape molecule XIST.

BACKGROUND: Sex disparities constitute a significant issue in hepatocellular carcinoma (HCC). However, the mechanism of gender dimorphism in HCC is still not completely understood. METHODS: 5-Hydroxymethylcytosine (5hmC)-Seal technology was utilised to detect the global 5hmC levels from four female and four male HCC samples. Methylation of XIST was detected by Sequenom MassARRAY methylation profiling between HCC tissues (T) and adjacent normal liver tissues (L). The role of Tet methylcytosine dioxygenase 2 (TET2) was investigated using diethylnitrosamine (DEN)-administered Tet2-/- female mice, which regulated XIST in hepatocarcinogenesis. All statistical analyses were carried out by GraphPad Prism 9.0 and SPSS version 19.0 software. RESULTS: The results demonstrated that the numbers of 5hmC reads in the first exon of XIST from female HCC tissues (T) were remarkably lower than that in female adjacent normal liver tissues (L). Correspondingly, DNA methylation level of XIST first exon region was significantly increased in female T than in L. By contrast, no significant change was observed in male HCC patients. Compared to L, the expression of XIST in T was also significantly downregulated. Female patients with higher XIST in HCC had a higher overall survival (OS) and more extended recurrence-free survival (RFS). Moreover, TET2 can interact with YY1 binding to the promoter region of XIST and maintain the hypomethylation state of XIST. In addition, DEN-administered Tet2-/- mice developed more tumours than controls in female mice. CONCLUSIONS: Our study provided that YY1 and TET2 could interact to form protein complexes binding to the promoter region of XIST, regulating the methylation level of XIST and then affecting the expression of XIST. This research will provide a new clue for studying sex disparities in hepatocarcinogenesis. HIGHLIGHTS: XIST was significantly downregulated in HCC tissues and had gender disparity. Methylation levels in the XIST first exon were higher in female HCC tissues, but no significant change in male HCC patients. The TET2-YY1 complex regulate XIST expression in female hepatocytes. Other ways regulate XIST expression in male hepatocytes.

Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma.

Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs. SIGNIFICANCE: The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors.

Lin28a maintains a subset of adult muscle stem cells in an embryonic-like state.

During homeostasis and after injury, adult muscle stem cells (MuSCs) activate to mediate muscle regeneration. However, much remains unclear regarding the heterogeneous capacity of MuSCs for self-renewal and regeneration. Here, we show that Lin28a is expressed in embryonic limb bud muscle progenitors, and that a rare reserve subset of Lin28a+Pax7- skeletal MuSCs can respond to injury at adult stage by replenishing the Pax7+ MuSC pool to drive muscle regeneration. Compared with adult Pax7+ MuSCs, Lin28a+ MuSCs displayed enhanced myogenic potency in vitro and in vivo upon transplantation. The epigenome of adult Lin28a+ MuSCs showed resemblance to embryonic muscle progenitors. In addition, RNA-sequencing revealed that Lin28a+ MuSCs co-expressed higher levels of certain embryonic limb bud transcription factors, telomerase components and the p53 inhibitor Mdm4, and lower levels of myogenic differentiation markers compared to adult Pax7+ MuSCs, resulting in enhanced self-renewal and stress-response signatures. Functionally, conditional ablation and induction of Lin28a+ MuSCs in adult mice revealed that these cells are necessary and sufficient for efficient muscle regeneration. Together, our findings connect the embryonic factor Lin28a to adult stem cell self-renewal and juvenile regeneration.

XAI-enabled neural network analysis of metabolite spatial distributions.

We used deep neural networks to process the mass spectrometry imaging (MSI) data of mouse muscle (young vs aged) and human cancer (tumor vs normal adjacent) tissues, with the aim of using explainable artificial intelligence (XAI) methods to rapidly identify biomarkers that can distinguish different classes of tissues, from several thousands of metabolite features. We also modified classic neural network architectures to construct a deep convolutional neural network that is more suitable for processing high-dimensional MSI data directly, instead of using dimension reduction techniques, and compared it to seven other machine learning analysis methods' performance in classification accuracy. After ascertaining the superiority of Channel-ResNet10, we used a novel channel selection-based XAI method to identify the key metabolite features that were responsible for its learning accuracy. These key metabolite biomarkers were then processed using MetaboAnalyst for pathway enrichment mapping. We found that Channel-ResNet10 was superior to seven other machine learning methods for MSI analysis, reaching > 98% accuracy in muscle aging and colorectal cancer datasets. We also used a novel channel selection-based XAI method to find that in young and aged muscle tissues, the differentially distributed metabolite biomarkers were especially enriched in the propanoate metabolism pathway, suggesting it as a novel target pathway for anti-aging therapy.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer.

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection.

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

FTO promotes liver inflammation by suppressing m6A mRNA methylation of IL-17RA.

Background: Previous studies have demonstrated that inflammation-related interleukin-17 (IL-17) signaling plays a pivotal role in the pathogenesis of non-alcoholic steatohepatitis (NASH)- and alcoholic liver disease (ALD)-induced hepatocellular carcinoma (HCC). However, rare efforts have been intended at implementing the analysis of N6-methyladenosine (m6A) mRNA methylation to elucidate the underpinning function of the IL-17 receptor A (IL-17RA) during the inflammation-carcinogenesis transformation of HCC. Methods: We performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) using normal, HCC tumor and paired tumor adjacent tissues from patients to investigate the dynamic changes of m6A mRNA methylation in the process of HCC. Additionally, murine non-alcoholic fatty liver disease (NAFLD) model and murine chronic liver injury model were utilized to investigate the role of IL-17RA regulated by m6A mRNA modulator fat mass and obesity-associated (FTO) in chronic hepatic inflammation. Results: MeRIP-seq revealed the reduction of m6A mRNA methylation of IL-17RA in tumor adjacent tissues with chronic inflammation, suggesting the potential role of IL-17RA in the inflammation-carcinogenesis transformation of HCC. Besides, we demonstrated that FTO, rather than methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14), and alkB homolog 5 (ALKBH5) functions as a main modulator for the decrease of m6A mRNA methylation of IL-17RA via knockdown and overexpression of FTO in vitro and in vivo. Conclusions: Overall, we elaborated the underlying mechanisms of the increase of IL-17RA resulting in chronic inflammation via the demethylation of FTO in tumor adjacent tissues and demonstrated that targeting the specific m6A modulator FTO may provide an effective treatment for hepatitis patients to prevent the development of HCC.

Optimized data-independent acquisition approach for proteomic analysis at single-cell level.

BACKGROUND: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

Spatial maps of hepatocellular carcinoma transcriptomes reveal spatial expression patterns in tumor immune microenvironment.

Rationale: Hepatocellular carcinoma (HCC) is a highly heterogeneous and malignant disease with the complex immune microenvironment, which ultimately influence clinic outcomes of patients. However, the spatial expression patterns of diverse immune cells among tumor microenvironment remain to be further deciphered. Methods: Spatial transcriptomics sequencing (ST) was implemented on two portions of HCC specimens. Differentially expressed genes, cell cycle phases, epithelial-mesenchymal features, pseudo-time and immune infiltration analysis were applied to demonstrate the intratumor heterogeneity and define the specific immune-related regions, and the results were further validated by a second analysis on another ST study. In vitro and in vivo experiments were conducted to confirm the functional mechanisms of key molecules such as CCL15, CCL19 and CCL21. Clinical tissue samples were used to assess their potential prognostic and therapeutic values. Results: Totally, 7553 spots were categorized into 15 subsets by hierarchical clustering, and malignant subsets with intratumor heterogeneity phenotypes were identified. Spatial heterogeneity from distinct sectors highlights specific chemokines: CCL15 is remarkable in the core region of the carcinoma sector and facilitates the immunosuppressive microenvironment by recruiting and polarizing M2-like macrophages in vitro and in vivo; High expression of CCL15 and CD163 respectively predicts poor prognosis of HCC patients, and the combined application of them has better predictive value. CCL19 and CCL21, sharing similar spatial expression patterns, are highly-correlated and prominent in the immune infiltration enrichment and recruit CD3+ T cells and CD20+ B cells to inhibit the growth of HCC, indicating a good prognosis of HCC patients. Conclusions: Taken together, our studies preliminarily reveal intratumor heterogeneity of HCC based on ST techniques and unravel the previously unexplored spatial expression patterns in the immune microenvironment. We also highlight the clinical significance and spatial discrepancy of key molecules, providing novel insight for further developing therapeutic strategies in HCC.

Improving the detection of aggressive prostate cancer using immunohistochemical staining of protein marker panels.

Prostate cancer (PCa) is a heterogeneous group of tumors, including non-aggressive (NAG) and aggressive (AG) cancer, with variable clinical outcomes. Clinically, in order to assess the aggressiveness of a PCa, a core needle biopsy of a tumor is usually obtained to evaluate the Gleason pattern and score of the tumor. However, it may be difficult to assign on a small biopsy sample using histology. Therefore, additional tool is needed to aid in the assessment. We studied the diagnostic utility of 12 protein markers to identify AG tumors using immunohistochemistry (IHC) and tumor tissue microarray (TMA), including 215 cores of PCa and 111 cores of tumor-matched normal adjacent tissue (NAT). Protein markers were evaluated for their potential utility as single or combined panels for identification of AG. Of 12 proteins, PSMA, phospho-EGFR, AR and P16 were over-expressed in AG. Galectin-3, DPP4 and MAN1B1 revealed stronger staining patterns in NAG. The sensitivity and specificity of individual marker varied widely. Based on AUC values of individual marker, we constructed two- and three-marker panels. In two-marker panels, especially in the panel of DPP4 and PSMA, the AUC value reached 0.83 (ranging from 0.76 to 0.83). In three-marker panels, containing both DPP4 and PSMA with either Galectin-3 or phospho-EGFR, the AUC value reached 0.86 (ranging from 0.83 to 0.86). The specificities at 95% sensitivity of three-marker panels were also significantly improved. In addition to Gleason score, our IHC panels provide a practical tool to assess the aggressiveness of PCa.

Aqueous proteins help predict the response of patients with neovascular age-related macular degeneration to anti-VEGF therapy.

BackgroundTo reduce the treatment burden for patients with neovascular age-related macular degeneration (nvAMD), emerging therapies targeting vascular endothelial growth factor (VEGF) are being designed to extend the interval between treatments, thereby minimizing the number of intraocular injections. However, which patients will benefit from longer-acting agents is not clear.MethodsEyes with nvAMD (n = 122) underwent 3 consecutive monthly injections with currently available anti-VEGF therapies, followed by a treat-and-extend protocol. Patients who remained quiescent 12 weeks from their prior treatment entered a treatment pause and were switched to pro re nata (PRN) treatment (based on vision, clinical exam, and/or imaging studies). Proteomic analysis was performed on aqueous fluid to identify proteins that correlate with patients' response to treatment.ResultsAt the end of 1 year, 38 of 122 eyes (31%) entered a treatment pause (≥30 weeks). Conversely, 21 of 122 eyes (17%) failed extension and required monthly treatment at the end of year 1. Proteomic analysis of aqueous fluid identified proteins that correlated with patients' response to treatment, including proteins previously implicated in AMD pathogenesis. Interestingly, apolipoprotein-B100 (ApoB100), a principal component of drusen implicated in the progression of nonneovascular AMD, was increased in treated patients who required less frequent injections. ApoB100 expression was higher in AMD eyes compared with controls but was lower in eyes that develop choroidal neovascularization (CNV), consistent with a protective role. Accordingly, mice overexpressing ApoB100 were partially protected from laser-induced CNV.FundingThis work was supported by the National Eye Institute, National Institutes of Health grants R01EY029750, R01EY025705, and R01 EY27961; the Research to Prevent Blindness, Inc.; the Alcon Research Institute; and Johns Hopkins University through the Robert Bond Welch and Branna and Irving Sisenwein professorships in ophthalmology.ConclusionAqueous biomarkers could help identify patients with nvAMD who may not require or benefit from long-term treatment with anti-VEGF therapy.

Influence of stereochemistry on the activity of rapadocin, an isoform-specific inhibitor of the nucleoside transporter ENT1.

Rapadocin is a novel rapamycin-inspired polyketide-tetrapeptide hybrid macrocycle that possesses highly potent and isoform-specific inhibitory activity against the human equilibrative nucleoside transporter 1 (hENT1). Rapadocin contains an epimerizable chiral center in phenylglycine and an olefin group, and can thus exist as a mixture of four stereoisomers. Herein, we report the first total synthesis of the four stereoisomers of rapadocin using two different synthetic strategies and the assignment of their structures. The inhibitory activity of each of the four synthetic isomers on both hENT1 and hENT2 was determined. It was found that the stereochemistry of phenylglycine played a more dominant role than the configuration of the olefin in the activity of rapadocin. These findings will guide the future design and development of rapadocin analogs as new modulators of adenosine signaling.

Dysregulated N6-methyladenosine (m6A) processing in hepatocellular carcinoma.

N6-methyladenosine (m6A) is the most thoroughly studied type of internal RNA modification, as this epigenetic modification is the most abundant in eukaryotic RNAs to date. This modification occurs in various types of RNAs and plays significant roles in dominant RNA-related processes, such as translation, splicing, export and degradation. These processes are catalyzed by three types of prominent enzymes: writers, erasers and readers. Increasing evidence has shown that m6A modification is vital for the regulation of gene expression, carcinogenesis, tumor progression and other abnormal changes, and recent studies have shown that m6A is important in the development of hepatocellular carcinoma (HCC). Herein, we summarize the nature and regulatory mechanisms of m6A modification, including its role in the pathogenesis of HCC and related chronic liver diseases. We also highlight the clinical significance and future strategies involving RNA m6A modifications in HCC.

Evaluation of the Sensitivity and Reproducibility of Targeted Proteomic Analysis Using Data-Independent Acquisition for Serum and Cerebrospinal Fluid Proteins.

There is a need for targeted analysis of biological fluids for diagnosis, prognosis, or monitoring the progression of diseases. Cerebrospinal fluid (CSF) and serum have been widely used for the development of protein analysis for neurodegenerative diseases and other diseases, respectively. Recently, data-independent acquisition (DIA) mass spectrometry (MS) has been developed to increase the throughput over data-dependent acquisition (DDA) on screening of a large number of samples and discovery of candidate targets. When it comes to target validation, the analytical performance of targeted analysis is critical. However, the inter- and intralaboratory analytical performances of the DIA-MS for targeted proteomic analysis of CSF and serum samples have not yet been investigated. In this study, we showed that the DIA-MS approach allowed us to identify and quantify 1732 CSF and 424 serum proteins, with 90% of proteins identified and quantified in at least 50% of DIA-MS runs. To evaluate the sensitivity, linearity, and dynamic range of the DIA approach, we included the stable isotope-labeled (SI) peptides into CSF and serum samples with serial dilutions. The lower limit of quantification (LLOQ) of peptides was 0.1-0.5 fmol, and the dynamic range was over 3.53 orders of magnitude, with excellent linearity (r2 < 0.978) in CSF and serum samples. Finally, the reproducibility of the DIA-MS approach was evaluated using entire proteins identified in CSF and serum samples. The intralaboratory three replicate results showed reliable reproducibility with 12.5 and 17.3% of the median coefficient of variation (CV) in both CSF and serum matrices, whereas the median CVs of interlaboratory three replicates were 23.8 and 32.0% in CSF and serum samples, respectively. The comparison of the quantitative result between replicates showed close similarity at intra- and interlaboratories with a median Pearson correlation value of >0.98 in CSF and serum, respectively. In conclusion, we demonstrate the capability of the DIA approach as a targeted proteomic analysis for candidate proteins from CSF and serum samples.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Discovery of a Potent GLUT Inhibitor from a Library of Rapafucins by Using 3D Microarrays.

Glucose transporters play an essential role in cancer cell proliferation and survival and have been pursued as promising cancer drug targets. Using microarrays of a library of new macrocycles known as rapafucins, which were inspired by the natural product rapamycin, we screened for new inhibitors of GLUT1. We identified multiple hits from the rapafucin 3D microarray and confirmed one hit as a bona fide GLUT1 ligand, which we named rapaglutin A (RgA). We demonstrate that RgA is a potent inhibitor of GLUT1 as well as GLUT3 and GLUT4, with an IC50 value of low nanomolar for GLUT1. RgA was found to inhibit glucose uptake, leading to a decrease in cellular ATP synthesis, activation of AMP-dependent kinase, inhibition of mTOR signaling, and induction of cell-cycle arrest and apoptosis in cancer cells. Moreover, RgA was capable of inhibiting tumor xenografts in vivo without obvious side effects. RgA could thus be a new chemical tool to study GLUT function and a promising lead for developing anticancer drugs.