MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-β pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.

Insight into the complexity of male infertility: a multi-omics review

Male infertility is a reproductive disorder, accounting for 40-50% of infertility. Currently, in about 70% of infertile men, the cause remains unknown. With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging. The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, non-coding RNA, proteins, and metabolites worth further exploring. Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping. A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics. A GO enrichment analysis was performed using the Enrichr tool. We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies. Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent. With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.

Deciphering dynamic interactions between spermatozoa and the ovarian microenvironment through integrated multi-omics approaches in viviparous Sebastes schlegelii

The ovarian microenvironment plays a crucial role in ensuring the reproductive success of viviparous teleosts. However, the molecular mechanism underlying the interaction between spermatozoa and the ovarian microenvironment has remained elusive. This study aimed to contribute to a better understanding of this process in black rockfish (Sebastes schlegelii) using integrated multi-omics approaches. The results demonstrated significant upregulation of ovarian complement-related proteins and pattern recognition receptors, along with remodeling of glycans on the surface of spermatozoa at the early spermatozoa-storage stage (1 month after mating). As spermatozoa were stored over time, ovarian complement proteins were progressively repressed by tryptophan and hippurate, indicating a remarkable adaptation of spermatozoa to the ovarian microenvironment. Before fertilization, a notable upregulation of cellular junction proteins was observed. The study revealed that spermatozoa bind to ZPB2a protein through GSTM3 and that ZPB2a promotes spermatozoa survival and movement in a GSTM3-dependent manner. These findings shed light on a key mechanism that influences the dynamics of spermatozoa in the female reproductive tract, providing valuable insights into the molecular networks regulating spermatozoa adaptation and survival in species with internal fertilization.

Dynamic changes in the non-volatile and flavour compounds in withered tea leaves of three different colour cultivars based on multi-omics

In this study, metabolomics and proteomics were performed to investigate the fluctuations of non-volatile compounds and proteins in tea leaves from three tea cultivars with varying colours during withering. A total of 2798 compounds were detected, exhibiting considerable variations in amino acids, phenylpropanoids, and flavonoids. The ZH1 cultivar displayed increased levels of amino acids but decreased levels of polyphenols, which might be associated with the up-regulation of enzymes responsible for protein degradation and subsequent amino acid production, as well as the down-regulation of enzymes involved in phenylpropanoid and flavonoid biosynthesis. The FUD and ZH1 cultivars had elevated levels of flavanols and flavanol-O-glycosides, which were regulated by the upregulation of FLS. The ZJ and ZH1 cultivars displayed elevated levels of theaflavin and peroxidase. This work presents a novel investigation into the alterations of metabolites and proteins between tea cultivars during withering, and helps with the tea cultivar selection and manufacturing development.

Multi-omics and chemical profiling approaches to understand the material foundation and pharmacological mechanism of sophorae tonkinensis radix et rhizome-induced liver injury in mice

ETHNOPHARMACOLOGICAL RELEVANCE

Sophorae tonkinensis Radix et Rhizoma (STR) is an extensively applied traditional Chinese medicine (TCM) in southwest China. However, its clinical application is relatively limited due to its hepatotoxicity effects.

AIM OF THE STUDY

To understand the material foundation and liver injury mechanism of STR.

MATERIALS AND METHODS

Chemical compositions in STR and its prototypes in mice were profiled by ultra-performance liquid chromatography coupled quadrupole-time of flight mass spectrometry (UPLC-Q/TOF MS). STR-induced liver injury (SILI) was comprehensively evaluated by STR-treated mice mode. The histopathologic and biochemical analyses were performed to evaluate liver injury levels. Subsequently, network pharmacology and multi-omics were used to analyze the potential mechanism of SILI in vivo. And the target genes were further verified by Western blot.

RESULTS

A total of 152 compounds were identified or tentatively characterized in STR, including 29 alkaloids, 21 organic acids, 75 flavonoids, 1 quinone, and 26 other types. Among them, 19 components were presented in STR-medicated serum. The histopathologic and biochemical analysis revealed that hepatic injury occurred after 4 weeks of intragastric administration of STR. Network pharmacology analysis revealed that IL6, TNF, STAT3, etc. were the main core targets, and the bile secretion might play a key role in SILI. The metabolic pathways such as taurine and hypotaurine metabolism, purine metabolism, and vitamin B6 metabolism were identified in the STR exposed groups. Among them, taurine, hypotaurine, hypoxanthine, pyridoxal, and 4-pyridoxate were selected based on their high impact value and potential biological function in the process of liver injury post STR treatment.

CONCLUSIONS

The mechanism and material foundation of SILI were revealed and profiled by a multi-omics strategy combined with network pharmacology and chemical profiling. Meanwhile, new insights were taken into understand the pathological mechanism of SILI.

Multi-omics analysis reveals epigenetically regulated processes and patient classification in lung adenocarcinoma

Aberrant DNA methylation is a hallmark of many cancer types. Despite our knowledge of epigenetic and transcriptomic alterations in lung adenocarcinoma (LUAD), we lack robust multi-modal molecular classifications for patient stratification. This is partly because the impact of epigenetic alterations on lung cancer development and progression is still not fully understood. To that end, we identified disease-associated processes under epigenetic regulation in LUAD. We performed a genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis by integrating DNA methylation and gene expression data from 453 patients in the TCGA cohort. Using a community detection algorithm, we identified distinct communities of CpG-gene associations with diverse biological processes. Interestingly, we identified a community linked to hormone response and lipid metabolism; the identified CpGs in this community were enriched in enhancer regions and binding regions of transcription factors such as FOXA1/2, GRHL2, HNF1B, AR, and ESR1. Furthermore, the CpGs were connected to their associated genes through chromatin interaction loops. These findings suggest that the expression of genes involved in hormone response and lipid metabolism in LUAD is epigenetically regulated through DNA methylation and enhancer-promoter interactions. By applying consensus clustering on the integrated expression-methylation pattern of the emQTL-genes and CpGs linked to hormone response and lipid metabolism, we further identified subclasses of patients with distinct prognoses. This novel patient stratification was validated in an independent patient cohort of 135 patients and showed increased prognostic significance compared to previously defined molecular subtypes.

Multi-omics reveal the effects and regulatory mechanism of dietary neutral detergent fiber supplementation on carcass characteristics, amino acid profiles, and meat quality of finishing pigs

This study aimed to reveal the effects and regulatory mechanism of dietary NDF on the performance of pigs by multi-omics analysis. Results showed that 16 % dietary NDF significantly improved meat quality, increased flavor amino acid content, and reduced backfat thickness and the feed-to-gain ratio. 16S rDNA sequencing showed that 16 % NDF significantly increased the abundance of Akkermansia, Lachnoclostridium, and Ruminococcus. Transcript analysis showed that genes related to muscle development and lipid metabolism were significantly modified. Metabonomic analysis showed that 16 % NDF significantly increased amino and fatty acid related metabolites. Correlation analysis suggested that 16 % NDF treatment may alter the gut microbiota and metabolites, regulate the expression of genes related to lipid and amino metabolism, and ultimately affect the flavor and performance of pigs. This study provides a novel understanding about the effect and regulatory mechanism of NDF supplements on the finishing pigs and a relevant reference for the improvement of diet formulation.

Combined multi-omics approach to analyze the flavor characteristics and formation mechanism of gabaron green tea

Gabaron green tea (GAGT) has unique flavor and health benefits through the special anaerobic treatment. However, how this composite processing affects the aroma formation of GAGT and the regulatory mechanism was rarely reported. This study used nontargeted metabolomics and molecular sensory science to overlay screen differential metabolites and key aroma contributors. The potential regulatory mechanism of anaerobic treatment on the aroma formation of GAGT was investigated by transcriptomics and correlation analyses. Five volatiles: benzeneacetaldehyde, nonanal, geraniol, linalool, and linalool oxide III, were screened as target metabolites. Through the transcriptional-level differential genes screening and analysis, some CsERF transcription factors in the ethylene signaling pathway were proposed might participate the response to the anaerobic treatment. They might regulate the expression of related genes in the metabolic pathway of the target metabolites thus affecting the GAGT flavor. The findings of this study provide novel information on the flavor and its formation of GAGT.

Multiomics integrated with sensory evaluations to identify characteristic aromas and key genes in a novel brown navel orange (Citrus sinensis)

'Zong Cheng' navel orange (ZC) is a brown mutant of Lane Late navel orange (LL) and emits a more pleasant odor than that of LL. However, the key volatile compound of this aroma and underlying mechanism remains unclear. In this study, sensory evaluations and volatile profiling were performed throughout fruit development to identify significant differences in sensory perception and metabolites between LL and ZC. It revealed that the sesquiterpene content varied significantly between ZC and LL. Based on aroma extract dilution and gas chromatography-olfactometry analyses, the volatile compound leading to the background aroma of LL and ZC is d-limonene, the orange note in LL was mainly attributed to octanal, whilst valencene, β-myrcene, and (E)-β-ocimene presented balsamic, sweet, and herb notes in ZC. Furthermore, Cs5g12900 and six potential transcription factors were identified as responsible for valencene accumulation in ZC, which is important for enhancing the aroma of ZC.

A multi-omics study reveals the therapeutic effect of Linderae Radix water extract on irritable bowel syndrome (IBS-D)

ETHNOPHARMACOLOGICAL RELEVANCE

Linderae Radix (Lindera aggregata (Sims) Kosterm) is a traditional Chinese medicine known for its capability to regulate qi and relieve pain, particularly in the context of gastrointestinal disorders.

AIM OF THE STUDY

While our previous research has demonstrated the efficacy of the Linderae Radix water extract (LRWE) in the treatment of diarrhea-predominant irritable bowel syndrome (IBS-D), the precise mechanisms remain elusive. This study aims to provide a comprehensive understanding of the therapeutic effects of LRWE on IBS-D through multi-omics techniques.

MATERIALS AND METHODS

16 S rRNA gene sequencing combined with LC-MS metabolomics was employed to investigate the effect of LRWE on the gut microbiota and metabolites of IBS-D rats. Spearman correlation analysis was performed on the gut microbiota and metabolites.

RESULTS

LRWE administration significantly ameliorated IBS-D rats' symptoms, including diarrhea, visceral hypersensitivity, and low-grade intestinal inflammation. Gut microbiota analysis revealed that LRWE influenced the diversity of the gut microbiota in IBS-D rats by significantly reducing the relative abundance of Patescibacteria and Candidatus Saccharimonas, while increasing the relative abundance of Jeotgalicoccus. Serum metabolomic analysis identified 16 differential metabolites, associated with LRWE's positive effects on IBS-D symptoms, focusing on glyoxylate and dicarboxylic acid metabolism, and cysteine and methionine metabolism. Spearman analysis demonstrated a strong correlation between cecal microbiota composition and serum metabolite levels.

CONCLUSIONS

This study elucidates that LRWE plays a crucial role in the comprehensive therapeutic approach to IBS-D by restoring the relative abundance of gut microbiota and addressing the disturbed metabolism of endogenous biomarkers. The identified bacteria and metabolites present potential therapeutic targets for IBS-D.

Multi-omics Analysis of Volatile Flavor Components in Pacific Chub and Spanish Mackerel during Freezing using GC-MS-O

This study employed gas chromatography-mass spectrometry with olfactory (GC-MS-O) and multi-omics methods to investigate the changes in volatile flavor compounds during the freezing process of Pacific chub mackerel (Scomber japonicus) from Japan and China, and Spanish mackerel (Scomberomorus niphonius). A total of 18 volatile flavor compounds were identified, and significant differences in volatile flavor components were observed among samples frozen for 1 week, 1 year, and 2 years. The results of the Partial least squares regression (PLSR) indicated that the fishy odor was correlated with independent variables such as fatty acids (FA 22:4, FA 28:6, FA 24:4), differentially expressed genes (Gene.2425 (NDUFA5), Gene.38 (GPX1), and Gene.2844 (DAD1)). Classification and regression tree (CART) analysis revealed that the peak area values of fatty acids (FA 22:5, FA 20:4) and fatty acid esters of hydroxy fatty acids (FAHFA 18:0/22:3) were the main differentiating factors for fishy odor perception.

A new high-throughput screening methodology for the discovery of cancer-testis antigen using multi-omics data

BACKGROUND

Cancer/testis antigens (CTAs), also known as tumor-specific antigens (TSAs) are specifically expressed in cancer cells and exhibit high immunogenicity, making them promising targets for immunotherapy and cancer vaccines.

METHODS

A new integrated high-throughput screening methodology for CTAs was proposed in this study through combining DNA methylation and RNA sequencing data. Briefly, the genes with increased transcript level and decreased DNA methylation were identified by multi-omics analysis. RNA sequencing studies in cell lines exposed to DNA methyltransferase (DNMT) inhibitors were performed to validate the inherent causal relationship between DNA hypomethylation and gene expression upregulation.

RESULTS

We proposed a new integrated high-throughput screening methodology for identification of CTAs using multi-omics analysis. In addition, we tested the feasibility of this method using gastric cancer (GC) as an example. In GC, we identified over 2000 primary candidate CTAs and ultimately identified 20 CTAs with significant tissue-specificity, including a testis-specific serine protease TESSP1/PRSS41. Integrated analysis confirmed that PRSS41 expression was reactivated in gastrointestinal cancers by promoter DNA hypomethylation at the CpG site (cg08104780). Additionally, DNA hypomethylation of PRSS41 predicted a poor prognosis in GC.

CONCLUSION

We propose a new high-throughput screening method for the identification of CTAs in cancer and validate its effectiveness. Our work emphasizes that serine protease PRSS41 is a novel TSA that is reactivated in GC due to promoter DNA hypomethylation.

Integration of multi-omics data for survival prediction of lung adenocarcinoma

BACKGROUND AND OBJECTIVE

The morbidity of lung adenocarcinoma (LUAD) has been increasing year by year and the prognosis is poor. This has prompted researchers to study the survival of LUAD patients to ensure that patients can be cured in time or survive after appropriate treatment. There is still no fully valid model that can be applied to clinical practice.

METHODS

We introduced struc2vec-based multi-omics data integration (SBMOI), which could integrate gene expression, somatic mutations and clinical data to construct mutation gene vectors representing LUAD patient features. Based on the patient features, the random survival forest (RSF) model was used to predict the long- and short-term survival of LUAD patients. To further demonstrate the superiority of SBMOI, we simultaneously replaced scale-free gene co-expression network (FCN) with a protein-protein interaction (PPI) network and a significant co-expression network (SCN) to compare accuracy in predicting LUAD patient survival under the same conditions.

RESULTS

Our results suggested that compared with SCN and PPI network, the FCN based SBMOI combined with RSF model had better performance in long- and short-term survival prediction tasks for LUAD patients. The AUC of 1-year, 5-year, and 10-year survival in the validation dataset were 0.791, 0.825, and 0.917, respectively.

CONCLUSIONS

This study provided a powerful network-based method to multi-omics data integration. SBMOI combined with RSF successfully predicted long- and short-term survival of LUAD patients, especially with high accuracy on long-term survival. Besides, SBMOI algorithm has the potential to combine with other machine learning models to complete clustering or stratificational tasks, and being applied to other diseases.

Biosynthetic potential of uncultured anammox community bacteria revealed through multi-omics analysis

Microbial secondary metabolites (SMs) and their derivatives have been widely used in medicine, agriculture, and energy. Growing needs for renewable energy and the challenges posed by antibiotic resistance, cancer, and pesticides emphasize the crucial hunt for new SMs. Anaerobic ammonium-oxidation (anammox) systems harbor many uncultured or underexplored bacteria, representing potential resources for discovering novel SMs. Leveraging HiFi long-read metagenomic sequencing, 1,040 biosynthetic gene clusters (BGCs) were unearthed from the anammox microbiome with 58% being complete and showcasing rich diversity. Most of them showed distant relations to known BGCs, implying novelty. Members of the underexplored lineages (Chloroflexota and Planctomycetota) and Proteobacteria contained lots of BGCs, showcasing substantial biosynthetic potential. Metaproteomic results indicated that Planctomycetota members harbored the most active BGCs, particularly those involved in producing potential biofuel-ladderane. Overall, these findings underscore that anammox microbiomes could serve as valuable resources for mining novel BGCs and discovering new SMs for practical application.

Multiomics profiling of the therapeutic effect of Dan-deng-tong-nao capsule on cerebral ischemia-reperfusion injury

BACKGROUND

Stroke is a complex physiological process associated with intestinal flora dysbiosis and metabolic disorders. Dan-deng-tong-nao capsule (DDTN) is a traditional Chinese medicine used clinically to treat cerebral ischemia-reperfusion injury (CIRI) for many years. However, little is known about the effects of DDTN in the treatment of CIRI from the perspective of gut microbiota and metabolites.

PURPOSE

This study aimed to investigate the regulatory roles of DDTN in endogenous metabolism and gut microbiota in CIRI rats, thus providing a basis for clinical rational drug use and discovering natural products with potential physiological activities in DDTN for the treatment of CIRI.

METHODS

The chemical composition of DDTN in vitro and in vivo was investigated using ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLCHRMS), followed by target prediction using reverse molecular docking. Secondly, a biological evaluation of DDTN ameliorating neural damage in CIRI was performed at the whole animal level. Then, an integrated omics approach based on UHPLCHRMS and 16S rRNA sequencing was proposed to reveal the anti-CIRI effect and possible mechanism of DDTN. Finally, exploring the intrinsic link between changes in metabolite profiles, changes in the intestinal flora, and targets of components to reveal DDTN for the treatment of CIRI.

RESULTS

A total of 112 chemical components of DDTN were identified in vitro and 10 absorbed constituents in vivo. The efficacy of DDTN in the treatment of CIRI was confirmed by alleviating cerebral infarction and neurological deficits. After the DDTN intervention, 21 and 26 metabolites were significantly altered in plasma and fecal, respectively. Based on the fecal microbiome, a total of 36 genera were enriched among the different groups. Finally, the results of the network integration analysis showed that the 10 potential active ingredients of DDTN could mediate the differential expression of 24 metabolites and 6 gut microbes by targeting 25 target proteins.

CONCLUSION

This study was the first to outline the landscapes of metabolites as well as gut microbiota regulated by DDTN in CIRI rats using multi-omics data, and comprehensively revealed the systematic relationships among ingredients, targets, metabolites, and gut microbiota, thus providing new perspectives on the mechanism of DDTN in the treatment of CIRI.

Multi-omics data integration and drug screening of AML cancer using Generative Adversarial Network

In the era of precision medicine, accurate disease phenotype prediction for heterogeneous diseases, such as cancer, is emerging due to advanced technologies that link genotypes and phenotypes. However, it is difficult to integrate different types of biological data because they are so varied. In this study, we focused on predicting the traits of a blood cancer called Acute Myeloid Leukemia (AML) by combining different kinds of biological data. We used a recently developed method called Omics Generative Adversarial Network (GAN) to better classify cancer outcomes. The primary advantages of a GAN include its ability to create synthetic data that is nearly indistinguishable from real data, its high flexibility, and its wide range of applications, including multi-omics data analysis. In addition, the GAN was effective at combining two types of biological data. We created synthetic datasets for gene activity and DNA methylation. Our method was more accurate in predicting disease traits than using the original data alone. The experimental results provided evidence that the creation of synthetic data through interacting multi-omics data analysis using GANs improves the overall prediction quality. Furthermore, we identified the top-ranked significant genes through statistical methods and pinpointed potential candidate drug agents through in-silico studies. The proposed drugs, also supported by other independent studies, might play a crucial role in the treatment of AML cancer. The code is available on GitHub; https://github.com/SabrinAfroz/omicsGAN_codes?fbclid=IwAR1-/stuffmlE0hyWgSu2wlXo6dYlKUei3faLdlvpxTOOUPVlmYCloXf4Uk9ejK4I.

Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer

PURPOSE

The progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) in humans is highly variable. To better understand the relationship between them, we performed a multi-omic characterization of co-occurring DCIS and IBC lesions in a cohort of individuals.

METHODS

Formalin-fixed paraffin-embedded tissue samples from 50 patients with co-occurring DCIS and IBC lesions were subjected to DNA-seq and whole transcriptome RNA-seq. Paired DCIS and IBC multi-omics profiles were then interrogated for DNA mutations, gene expression profiles and pathway analysis.

RESULTS

Most small variants and copy number variations were shared between co-occurring DCIS and IBC lesions, with IBC exhibiting on average a higher degree of additional mutations. However, 36% of co-occurring lesions shared no common mutations and 49% shared no common copy number variations. The most frequent genomic variants in both DCIS and IBC were PIK3CA, TP53, KMT2C, MAP3K1, GATA3 and SF3B1, with KMT2C being more frequent in DCIS and TP53 and MAP3K1 more frequent in IBC, though the numbers are too small for definitive conclusions. The most frequent copy number variations were seen in MCL1, CKSB1 and ERBB2. ERBB2 changes were not seen in IBC unless present in the corresponding DCIS. Transcriptional profiles were highly distinct between DCIS and IBC, with DCIS exhibiting upregulation of immune-related signatures, while IBC showed significant overexpression in genes and pathways associated with cell division and proliferation. Interestingly, DCIS and IBC exhibited significant differential expression of different components of extracellular matrix (ECM) formation and regulation, with DCIS showing overexpression of ECM-membrane interaction components while IBC showed upregulation of genes associated with fibronectin and invadopodia.

CONCLUSION

While most co-occurring DCIS and IBC were mutationally similar and suggestive of a common clonal progenitor, transcriptionally the lesions are highly distinct, with IBC expressing key pathways that facilitate invasion and proliferation. These results are suggestive of additional levels of regulation, epigenetic or other, that facilitate the acquisition of invasive properties during tumor evolution.

Qijiao Shengbai Capsule alleviated leukopenia by interfering leukotriene pathway: Integrated network study of multi-omics

BACKGROUND

Leukopenia could be induced by chemotherapy, which leads to bone marrow suppression and even affects the therapeutic progression of cancer. Qijiao Shengbai Capsule (QSC) has been used for the treatment of leukopenia in clinic, but its bioactive components and mechanisms have not yet been elucidated clearly.

PURPOSE

This study aimed to elucidate the molecular mechanisms of QSC in treating leukopenia.

STUDY DESIGN

Serum pharmacochemistry, multi-omics, network pharmacology, and validation experiment were combined to study the effect of QSC in murine leukopenia model.

METHODS

First, UPLC-QTOF-MS was used to clarify the absorbed components of QSC. Then, cyclophosphamide (CTX) was used to induce mice model with leukopenia, and the therapeutic efficacy of QSC was assessed by an integrative approach of multi-omics and network pharmacology strategy. Finally, molecular mechanisms and potential therapeutic targets were identified by validated experiments.

RESULTS

121 compounds absorbed in vivo were identified. QSC significantly increase the count of white blood cells (WBCs) in peripheral blood of leukopenia mice with 15 days treatment. Multi-omics and network pharmacology revealed that leukotriene pathway and MAPK signaling pathway played crucial roles during the treatment of leukopenia with QSC. Six targets (ALOX5, LTB4R, CYSLTR1, FOS, JUN, IL-1β) and 13 prototype compounds were supposed to be the key targets and potential active components, respectively. The validation experiment further confirmed that QSC could effectively inhibit the inflammatory response induced by leukopenia. The inhibitors of ALOX5 activity can significantly increase the number of WBCs in leukopenia mice. Molecular docking of ALOX5 suggested that calycosin, daidzein, and medicarpin were the potentially active compounds of QSC.

CONCLUSION

Leukotriene pathway was found for the first time to be a key role in the development of leukopenia, and ALOX5 was conformed as the potential target. QSC may inhibit the inflammatory response and interfere the leukotriene pathway, it is able to improve hematopoiesis and achieve therapeutic effects in the mice with leukopenia.

Multi-omics reveals that 5-O-methylvisammioside prevention acute liver injury in mice by regulating the TNF/MAPK/NF-κB/arachidonic acid pathway

BACKGROUND

The pathogenesis of acute liver injury (ALI) has been a pressing issue in the medical scientific community. We previously found that 5-O-methylvisammioside (MeV) from Saposhnikovia divaricata (Turcz.) Schischk has excellent anti-inflammatory properties. However, the mechanism by which MeV protects against ALI still needs to be deeply investigated.

PURPOSE

In the present study, we established an acetaminophen (APAP) -induced ALI mouse model and pre-protected the mice with MeV.

METHODS & RESULTS

Our findings indicate that MeV (5 and 10 mg/kg) lowered the blood levels of alanine aminotransferase and aspartate aminotransferase and reduced the infiltration of inflammatory cells in the liver. MeV initially showed an inhibitory effect on ALI. We then analyzed the molecular mechanisms underlying the effects of MeV by transcriptomic and metabolomic analyzes. Through transcriptomic analysis, we identified 4675 differentially expressed genes between the APAP+MeV group and the APAP-induced ALI group, which were mainly enriched in the MAPK pathway, the TNF pathway, and the NF-κB pathway. Through metabolomic analysis, we found that 249 metabolites in the liver were differentially regulated between the APAP+MeV group and the APAP- induced ALI group, which were mainly enriched in the arachidonic acid pathway. The mRNA expression levels of key genes (encoding TNF-α, p38, AP-1, RelB, IL-1β, and Ptges), as determined by RT-PCR analysis, were consistent with the RNA-seq data. The ELISA results indicate that MeV markedly decreased the serum levels of TNF-α and IL-1β in mice. Finally, the key proteins in the NF-κB and MAPK pathways were examined using immunoblotting. The results showed that MeV decreased IκB-α phosphorylation and inhibited the nuclear translocation of NF-κB. In addition, MeV reduced the hepatic inflammatory burst mainly by inhibiting the phosphorylation of p38 and JNK in the MAPK pathway.

CONCLUSION

The present study demonstrated (i) that MeV could ameliorate APAP-induced ALI by inhibiting arachidonic acid metabolism and the TNF, MAPK, and NF-κB pathways, and (ii) that MeV is a promising drug candidate for the prevention of ALI.

An integrative multi-omics approach aimed to gain insight on the effect of composition, style, yeast, and wheat species on wheat craft beer flavour

This study was aimed to unravel the effect of raw materials (barley and wheat), wheat concentration (0, 25, 40, and 100 %), wheat species (common and durum), beer style (Blanche and Weiss), and yeast (US-05 and WB-06) on the chemical composition, volatiles, and sensory profile of wheat craft beers by using a multivariate statistical approach. Beer samples were analysed for their composition, volatiles and sensory profile and data were processed using unsupervised multivariate analyses, PLS regression and a multi-omics approach using multi-block PLS-DA. Multi-block variable sparsification was used as an embedded dimension reduction step. The adopted multi-omics approach permitted to correctly classify beers with different styles and wheat concentration, and to accurate classify (95 % accuracy) beers according to yeast type. Wheat species was of lower importance since it permitted a classification with 49 % accuracy which increased to 74 % in Blanche beers, thus suggesting that malting flattened differences determined by wheat species.

Insight into the chemical compositions of Anhua dark teas derived from identical tea materials: A multi-omics, electronic sensory, and microbial sequencing analysis

Anhua dark teas (DTs), including Tianjian tea, Qianliang tea, Hei brick tea, and Fu brick tea, are unique fermented teas from China's Anhua County; yet their chemical composition differences remain unclear. Herein, metabolomics, volatolomics, and electronic sensory assessments were employed to analyze and compare chemical compositions and sensory characteristics of five types of Anhua DTs. All of these teas were derived from identical tea materials. Chemical compositions differed significantly among Anhua DTs, with Tianjian tea remarkable. Long-lasting fermentation and complex processing methods led to transformation of multiple compounds, particularly catechins. Eighteen volatile compounds with OVA > 1 were key aroma contributors in Anhua DTs. Internal transcribed spacer and 16S ribosomal DNA sequencing showed that Eurotium, Pseudomonas, and Bacillus are dominant microorganisms in Anhua DTs. Furthermore, this study unveiled notable differences in chemical compositions between Anhua DTs and five other traditional types of tea. This research enhances our understanding of Anhua DTs processing.

[Multi-omics prediction of lymph node metastasis status in breast cancer]

Lymph node metastasis status stands as a pivotal prognostic indicator in forecasting the outlook for breast cancer patients. Consequently, precise evaluation of this status holds paramount importance in the staging, treatment, and prognosis of breast cancer. The utilization of radiomics, genomics, proteomics, transcriptomics, and histopathology methodologies has notably enhanced the precision of lymph node metastasis status prediction in breast cancer. This review provides an overview of recent advancements in omics-based lymph node metastasis prediction for breast cancer, elucidating the significance of various omics prediction models and integrated multi-omics models in this predictive endeavor. The overarching goal is to augment the accuracy of preoperative lymph node metastasis status prediction in breast cancer, thereby aiding clinicians in the selection of efficacious personalized treatment strategies, while concurrently averting undertreatment of patients with a heightened risk of metastasis.

Molecular insights into the catabolism of dibutyl phthalate in Pseudomonas aeruginosa PS1 based on biochemical and multi-omics approaches

A comprehensive understanding of the molecular mechanisms underlying microbial catabolism of dibutyl phthalate (DBP) is still lacking. Here, we newly isolated a bacterial strain identified as Pseudomonas aeruginosa PS1 with high efficiency of DBP degradation. The degradation ratios of DBP at 100-1000 mg/L by this strain reached 80-99 % within 72 h without a lag phase. A rare DBP-degradation pathway containing two monobutyl phthalate-catabolism steps was proposed based on intermediates identified by HPLC-TOF-MS/MS. In combination with genomic and transcriptomic analyses, we identified 66 key genes involved in DBP biodegradation and revealed the genetic basis for a new complete catabolic pathway from DBP to Succinyl-CoA or Acetyl-CoA in the genus Pseudomonas for the first time. Notably, we found that a series of homologous genes in Pht and Pca clusters were simultaneously activated under DBP exposure and some key intermediate degradation related gene clusters including Pht, Pca, Xyl, Ben, and Cat exhibited a favorable coexisting pattern, which contributed the high-efficient DBP degradation ability and strong adaptability to this strain. Overall, these results broaden the knowledge of the catabolic diversity of DBP in microorganisms and enhance our understanding of the molecular mechanism underlying DBP biodegradation.

A multi-omics investigation of the lung injury induced by PM2.5 at environmental levels via the lung-gut axis

Long-term exposure to fine particulate matter (PM2.5) posed injury for gastrointestinal and respiratory systems, ascribing with the lung-gut axis. However, the cross-talk mechanisms remain unclear. Here, we attempted to establish the response networks of lung-gut axis in mice exposed to PM2.5 at environmental levels. Male Balb/c mice were exposed to PM2.5 (dose of 0.1, 0.5, and 1.0 mg/kg) collected from Chengdu, China for 10 weeks, through intratracheally instillation, and examined the effect of PM2.5 on lung functions of mice. The changes of lung and gut microbiota and metabolic profiles of mice in different groups were determined. Furthermore, the results of multi-omics were conjointly analyzed to elucidate the primary microbes and the associated metabolites in lung and gut responsible for PM2.5 exposure. Accordingly, the cross-talk network and key pathways between lung-gut axis were established. The results indicated that exposed to PM2.5 0.1 mg/kg induced obvious inflammations in mice lung, while emphysema was observed at 1.0 mg/kg. The levels of metabolites guanosine, hypoxanthine, and hepoxilin B3 increased in the lung might contribute to lung inflammations in exposure groups. For microbiotas in lung, PM2.5 exposure significantly declined the proportions of Halomonas and Lactobacillus. Meanwhile, the metabolites in gut including L-tryptophan, serotonin, and spermidine were up-regulated in exposure groups, which were linked to the decreasing of Oscillospira and Helicobacter in gut. Via lung-gut axis, the activations of pathways including Tryptophan metabolism, ABC transporters, Serotonergic synapse, and Linoleic acid metabolism contributed to the cross-talk between lung and gut tissues of mice mediated by PM2.5. In summary, the microbes including Lactobacillus, Oscillospira, and Parabacteroides, and metabolites including hepoxilin B3, guanosine, hypoxanthine, L-tryptophan, and spermidine were the main drivers. In this lung-gut axis study, we elucidated some pro- and pre-biotics in lung and gut microenvironments contributed to the adverse effects on lung functions induced by PM2.5 exposure.

Integrated multi-omics analysis reveals liver metabolic reprogramming by fish iridovirus and antiviral function of alpha-linolenic acid

Iridovirus poses a substantial threat to global aquaculture due to its high mortality rate; however, the molecular mechanisms underpinning its pathogenesis are not well elucidated. Here, a multi-omics approach was applied to groupers infected with Singapore grouper iridovirus (SGIV), focusing on the roles of key metabolites. Results showed that SGIV induced obvious histopathological damage and changes in metabolic enzymes within the liver. Furthermore, SGIV significantly reduced the contents of lipid droplets, triglycerides, cholesterol, and lipoproteins. Metabolomic analysis indicated that the altered metabolites were enriched in 19 pathways, with a notable down-regulation of lipid metabolites such as glycerophosphates and alpha-linolenic acid (ALA), consistent with disturbed lipid homeostasis in the liver. Integration of transcriptomic and metabolomic data revealed that the top enriched pathways were related to cell growth and death and nucleotide, carbohydrate, amino acid, and lipid metabolism, supporting the conclusion that SGIV infection induced liver metabolic reprogramming. Further integrative transcriptomic and proteomic analysis indicated that SGIV infection activated crucial molecular events in a phagosome-immune depression-metabolism dysregulation-necrosis signaling cascade. Of note, integrative multi-omics analysis demonstrated the consumption of ALA and linoleic acid (LA) metabolites, and the accumulation of L-glutamic acid (GA), accompanied by alterations in immune, inflammation, and cell death-related genes. Further experimental data showed that ALA, but not GA, suppressed SGIV replication by activating antioxidant and anti-inflammatory responses in the host. Collectively, these findings provide a comprehensive resource for understanding host response dynamics during fish iridovirus infection and highlight the antiviral potential of ALA in the prevention and treatment of iridoviral diseases.

A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework

Neuroblastoma (NB) is one of the leading causes of cancer-associated death in children. MYCN amplification is a prominent genetic marker for NB, and its targeting to halt NB progression is difficult to achieve. Therefore, an in-depth understanding of the molecular interactome of NB is needed to improve treatment outcomes. Analysis of NB multi-omics unravels valuable insight into the interplay between MYCN transcriptional and miRNA post-transcriptional modulation. Moreover, it aids in the identification of various miRNAs that participate in NB development and progression. This study proposes an integrated computational framework with three levels of high-throughput NB data (mRNA-seq, miRNA-seq, and methylation array). Similarity Network Fusion (SNF) and ranked SNF methods were utilized to identify essential genes and miRNAs. The specified genes included both miRNA-target genes and transcription factors (TFs). The interactions between TFs and miRNAs and between miRNAs and their target genes were retrieved where a regulatory network was developed. Finally, an interaction network-based analysis was performed to identify candidate biomarkers. The candidate biomarkers were further analyzed for their potential use in prognosis and diagnosis. The candidate biomarkers included three TFs and seven miRNAs. Four biomarkers have been previously studied and tested in NB, while the remaining identified biomarkers have known roles in other types of cancer. Although the specific molecular role is yet to be addressed, most identified biomarkers possess evidence of involvement in NB tumorigenesis. Analyzing cellular interactome to identify potential biomarkers is a promising approach that can contribute to optimizing efficient therapeutic regimens to target NB vulnerabilities.

Deciphering smooth muscle cell heterogeneity in atherosclerotic plaques and constructing model: a multi-omics approach with focus on KLF15/IGFBP4 axis

BACKGROUND

Ruptured atherosclerotic plaques often precipitate severe ischemic events, such as stroke and myocardial infarction. Unraveling the intricate molecular mechanisms governing vascular smooth muscle cell (VSMC) behavior in plaque stabilization remains a formidable challenge.

METHODS

In this study, we leveraged single-cell and transcriptomic datasets from atherosclerotic plaques retrieved from the gene expression omnibus (GEO) database. Employing a combination of single-cell population differential analysis, weighted gene co-expression network analysis (WGCNA), and transcriptome differential analysis techniques, we identified specific genes steering the transformation of VSMCs in atherosclerotic plaques. Diagnostic models were developed and validated through gene intersection, utilizing the least absolute shrinkage and selection operator (LASSO) and random forest (RF) methods. Nomograms for plaque assessment were constructed. Tissue localization and expression validation were performed on specimens from animal models, utilizing immunofluorescence co-localization, western blot, and reverse-transcription quantitative-polymerase chain reaction (RT-qPCR). Various online databases were harnessed to predict transcription factors (TFs) and their interacting compounds, with determination of the cell-specific localization of TF expression using single-cell data.

RESULTS

Following rigorous quality control procedures, we obtained a total of 40,953 cells, with 6,261 representing VSMCs. The VSMC population was subsequently clustered into 5 distinct subpopulations. Analyzing inter-subpopulation cellular communication, we focused on the SMC2 and SMC5 subpopulations. Single-cell subpopulation and WGCNA analyses revealed significant module enrichments, notably in collagen-containing extracellular matrix and cell-substrate junctions. Insulin-like growth factor binding protein 4 (IGFBP4), apolipoprotein E (APOE), and cathepsin C (CTSC) were identified as potential diagnostic markers for early and advanced plaques. Notably, gene expression pattern analysis suggested that IGFBP4 might serve as a protective gene, a hypothesis validated through tissue localization and expression analysis. Finally, we predicted TFs capable of binding to IGFBP4, with Krüppel-like family 15 (KLF15) emerging as a prominent candidate showing relative specificity within smooth muscle cells. Predictions about compounds associated with affecting KLF15 expression were also made.

CONCLUSION

Our study established a plaque diagnostic and assessment model and analyzed the molecular interaction mechanisms of smooth muscle cells within plaques. Further analysis revealed that the transcription factor KLF15 may regulate the biological behaviors of smooth muscle cells through the KLF15/IGFBP4 axis, thereby influencing the stability of advanced plaques via modulation of the PI3K-AKT signaling pathway. This could potentially serve as a target for plaque stability assessment and therapy, thus driving advancements in the management and treatment of atherosclerotic plaques.

Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis

Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.

Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma

We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10-7.67, Cox P = 2.63e-05) and PFS (HR = 3.72, 95% CI 2.06-6.73, Cox P = 1.38e-05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24-6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16-3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2-3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08-3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH.

Nanoplastic toxicity induces metabolic shifts in Populus × euramericana cv. '74/76' revealed by multi-omics analysis

There is increasing global concern regarding the pervasive issue of plastic pollution. We investigated the response of Populus × euramericana cv. '74/76' to nanoplastic toxicity via phenotypic, microanatomical, physiological, transcriptomic, and metabolomic approaches. Polystyrene nanoplastics (PS-NPs) were distributed throughout the test plants after the application of PS-NPs. Nanoplastics principally accumulated in the roots; minimal fractions were translocated to the leaves. In leaves, however, PS-NPs easily penetrated membranes and became concentrated in chloroplasts, causing thylakoid disintegration and chlorophyll degradation. Finally, oxidant damage from the influx of PS-NPs led to diminished photosynthesis, stunted growth, and etiolation and/or wilting. By integrating dual-omics data, we found that plants could counteract mild PS-NP-induced oxidative stress through the antioxidant enzyme system without initiating secondary metabolic defense mechanisms. In contrast, severe PS-NP treatments promoted a shift in metabolic pattern from primary metabolism to secondary metabolic defense mechanisms, an effect that was particularly pronounced during the upregulation of flavonoid biosynthesis. Our findings provide a useful framework from which to further clarify the roles of key biochemical pathways in plant responses to nanoplastic toxicity. Our work also supports the development of effective strategies to mitigate the environmental risks of nanoplastics by biologically immobilizing them in contaminated lands.

Implications of GCLC in prognosis and immunity of lung adenocarcinoma and multi-omics regulation mechanisms

BACKGROUND

Ferroptosis is an iron-dependent type of regulated cell death, and has been implicated in lung adenocarcinoma (LUAD). Evidence has proved the key role of glutamate-cysteine ligase catalytic subunit (GCLC) in ferroptosis, but its role in LUAD remains unclear. Herein, we explored the implications of GCLC and relevant genes in LUAD prognosis and immunity as well as underlying molecular mechanisms.

METHODS

This work gathered mRNA, miRNA, DNA methylation, somatic mutation and copy-number variation data from TCGA-LUAD. WGCNA was utilized for selecting GCLC-relevant genes, and a GCLC-relevant prognostic signature was built by uni- and multivariate-cox regression analyses. Immune compositions were estimated via CIBERSORT, and two immunotherapy cohorts of solid tumors were analyzed. Multi-omics regulatory mechanisms were finally assessed.

RESULTS

Our results showed that GCLC was overexpressed in LUAD, and potentially resulted in undesirable survival. A prognostic model was generated, which owned accurate and independent performance in prognostication. GCLC, and relevant genes were notably connected with immune compositions and immune checkpoints. High GCLC expression was linked with better responses to anti-PD-L1 and anti-CTLA-4 treatment. Their possible DNA methylation sites were inferred, e.g., hypomethylation in cg19740353 might contribute to GCLC up-regulation. Frequent genetic mutations also affected their expression. Upstream transcription factors (E2F1/3/4, etc.), post-transcriptional regulation of miRNAs (hsa-mir-30c-1, etc.), lncRNAs (C8orf34-AS1, etc.), and IGF2BP1-mediated m6A modification were identified. It was also found NOP58-mediated SUMOylation post-translational modification.

CONCLUSIONS

Together, we show that GCLC and relevant genes exert crucial roles in LUAD prognosis and immunity, and their expression can be controlled by complex multi-omics mechanisms.

Multiomics unravels potential molecular switches in the C3 to CAM transition of Mesembryanthemum crystallinum

Mesembryanthemum crystallinum (common ice plant), a facultative CAM plant, shifts from C3 to CAM photosynthesis under salt stress, enhancing water use efficiency. Here we used transcriptomics, proteomics, and targeted metabolomics to profile molecular changes during the diel cycle of C3 to CAM transition. The results confirmed expected changes associated with CAM photosynthesis, starch biosynthesis and degradation, and glycolysis/gluconeogenesis. Importantly, they yielded new discoveries: 1) Transcripts displayed greater circadian regulation than proteins. 2) Oxidative phosphorylation and inositol methylation may play important roles in initiating the transition. 3) V-type H+-ATPases showed consistent transcriptional regulation, aiding in vacuolar malate uptake. 4) A protein phosphatase 2C, a major component in the ABA signaling pathway, may trigger the C3 to CAM transition. Our work highlights the potential molecular switches in the C3 to CAM transition, including the potential role of ABA signaling. SIGNIFICANCE: The common ice plant is a model facultative CAM plant, and under stress conditions it can shift from C3 to CAM photosynthesis within a three-day period. However, knowledge about the molecular changes during the transition and the molecular switches enabling the transition is lacking. Multi-omic analyses not only revealed the molecular changes during the transition, but also highlighted the importance of ABA signaling, inositol methylation, V-type H+-ATPase in initiating the shift. The findings may explain physiological changes and nocturnal stomatal opening, and inform future synthetic biology effort in improving crop water use efficiency and stress resilience.

DX-21

Tetracycline (TC), widely found in various environments, poses significant risks to ecosystems and human health. While efficient biodegradation removes TC, the mechanisms underlying this process have not been elucidated. This study investigated the molecular mechanisms underlying TC biosorption and transfer within the extracellular polymeric substances (EPS) of strain DX-21 and its biodegradation process using fourier transform infrared spectroscopy, molecular docking, and multiomics. Under TC stress, DX-21 increased TC biosorption by secreting more extracellular polysaccharides and proteins, particularly the latter, mitigating toxicity. Moreover, specialized transporter proteins with increased binding capacity facilitated TC movement from the EPS to the cell membrane and within the cell. Transcriptomic and untargeted metabolomic analyses revealed that the presence of TC led to the differential expression of 306 genes and significant alterations in 37 metabolites. Notably, genes related to key enzymes, such as electron transport, peroxidase, and oxidoreductase, exhibited significant differential expression. DX-21 combated and degraded TC by regulating metabolism, altering cell membrane permeability, enhancing oxidative defense, and enhancing energy availability. Furthermore, integrative omics analyses indicated that DX-21 degrades TC via various enzymes, reallocating resources from other biosynthetic pathways. These results advance the understanding of the metabolic responses and regulatory mechanisms of DX-21 in response to TC.

Developing and validating multi-omics prediction models for late patient-reported dysphagia in head and neck radiotherapy

Background and purpose. To investigate models developed using radiomic and dosiomic (multi-omics) features from planning and treatment imaging for late patient-reported dysphagia in head and neck radiotherapy.Materials and methods. Training (n = 64) and testing (n = 23) cohorts of head and neck cancer patients treated with curative intent chemo-radiotherapy with a follow-up time greater than 12 months were retrospectively examined. Patients completed the MD Anderson Dysphagia Inventory and a composite score ≤60 was interpreted as patient-reported dysphagia. A chart review collected baseline dysphagia and clinical factors. Multi-omic features were extracted from planning and last synthetic CT images using the pharyngeal constrictor muscle contours as a region of interest. Late patient-reported dysphagia models were developed using a random forest backbone, with feature selection and up-sampling methods to account for the imbalanced data. Models were developed and validated for multi-omic feature combinations for both timepoints.Results. A clinical and radiomic feature model developed using the planning CT achieved good performance (validation: sensitivity = 80 ± 27% / balanced accuracy = 71 ± 23%, testing: sensitivity = 80 ± 10% / balanced accuracy = 73 ± 11%). The synthetic CT models did not show improvement over the plan CT multi-omics models, with poor reliability of the radiomic features on these images. Dosiomic features extracted from the synthetic CT showed promise in predicting late patient-reported dysphagia.Conclusion. Multi-omics models can predict late patient-reported dysphagia in head and neck radiotherapy patients. Synthetic CT dosiomic features show promise in developing successful models to account for changes in delivered dose distribution. Multi-center or prospective studies are required prior to clinical implementation of these models.

Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease

Parkinson's disease (PD) is a complex neurodegenerative disorder without a cure. The onset of PD symptoms corresponds to 50% loss of midbrain dopaminergic (mDA) neurons, limiting early-stage understanding of PD. To shed light on early PD development, we study time series scRNA-seq datasets of mDA neurons obtained from patient-derived induced pluripotent stem cell differentiation. We develop a new data integration method based on Non-negative Matrix Tri-Factorization that integrates these datasets with molecular interaction networks, producing condition-specific "gene embeddings". By mining these embeddings, we predict 193 PD-related genes that are largely supported (49.7%) in the literature and are specific to the investigated PINK1 mutation. Enrichment analysis in Kyoto Encyclopedia of Genes and Genomes pathways highlights 10 PD-related molecular mechanisms perturbed during early PD development. Finally, investigating the top 20 prioritized genes reveals 12 previously unrecognized genes associated with PD that represent interesting drug targets.

A study protocol to characterise pathophysiological and molecular markers of rheumatic heart disease and degenerative aortic stenosis using multiparametric cardiovascular imaging and multiomics techniques

INTRODUCTION

Rheumatic heart disease (RHD), degenerative aortic stenosis (AS), and congenital valve diseases are prevalent in sub-Saharan Africa. Many knowledge gaps remain in understanding disease mechanisms, stratifying phenotypes, and prognostication. Therefore, we aimed to characterise patients through clinical profiling, imaging, histology, and molecular biomarkers to improve our understanding of the pathophysiology, diagnosis, and prognosis of RHD and AS.

METHODS

In this cross-sectional, case-controlled study, we plan to recruit RHD and AS patients and compare them to matched controls. Living participants will undergo clinical assessment, echocardiography, CMR and blood sampling for circulatory biomarker analyses. Tissue samples will be obtained from patients undergoing valve replacement, while healthy tissues will be obtained from cadavers. Immunohistology, proteomics, metabolomics, and transcriptome analyses will be used to analyse circulatory- and tissue-specific biomarkers. Univariate and multivariate statistical analyses will be used for hypothesis testing and identification of important biomarkers. In summary, this study aims to delineate the pathophysiology of RHD and degenerative AS using multiparametric CMR imaging. In addition to discover novel biomarkers and explore the pathomechanisms associated with RHD and AS through high-throughput profiling of the tissue and blood proteome and metabolome and provide a proof of concept of the suitability of using cadaveric tissues as controls for cardiovascular disease studies.

EmptyDropsMultiome discriminates real cells from background in single-cell multiomics assays

Multiomic droplet-based technologies allow different molecular modalities, such as chromatin accessibility and gene expression (scATAC-seq and scRNA-seq), to be probed in the same nucleus. We develop EmptyDropsMultiome, an approach that distinguishes true nuclei-containing droplets from background. Using simulations, we show that EmptyDropsMultiome has higher statistical power and accuracy than existing approaches, including CellRanger-arc and EmptyDrops. On real datasets, we observe that CellRanger-arc misses more than half of the nuclei identified by EmptyDropsMultiome and, moreover, is biased against certain cell types, some of which have a retrieval rate lower than 20%.

Multi-omics integration highlights the role of ubiquitination in endometriosis fibrosis

BACKGROUND

Endometriosis, characterized by the presence of active endometrial-like tissues outside the uterus, causes symptoms like dysmenorrhea and infertility due to the fibrosis of endometrial cells, which involves excessive deposition of extracellular matrix (ECM) proteins. Ubiquitination, an important post-transcriptional modification, regulates various biological processes in human diseases. However, its role in the fibrosis process in endometriosis remains unclear.

METHODS

We employed multi-omics approaches on two cohorts of endometriosis patients with 39 samples. GO terms and KEGG pathways enrichment analyses were used to investigate the functional changes involved in endometriosis. Pearson's correlation coefficient analysis was conducted to explore the relationship between global proteome and ubiquitylome in endometriosis. The protein expression levels of ubiquitin-, fibrosis-related proteins, and E3 ubiquitin-protein ligase TRIM33 were validated via Western blot. Transfecting human endometrial stroma cells (hESCs) with TRIM33 small interfering RNA (siRNA) in vitro to explore how TRIM33 affects fibrosis-related proteins.

RESULTS

Integration of proteomics and transcriptomics showed genes with concurrent change of both mRNA and protein level which involved in ECM production in ectopic endometria. Ubiquitylomics distinguished 1647 and 1698 ubiquitinated lysine sites in the ectopic (EC) group compared to the normal (NC) and eutopic (EU) groups, respectively. Further multi-omics integration highlighted the essential role of ubiquitination in key fibrosis regulators in endometriosis. Correlation analysis between proteome and ubiquitylome showed correlation coefficients of 0.32 and 0.36 for ubiquitinated fibrosis proteins in EC/NC and EC/EU groups, respectively, indicating positive regulation of fibrosis-related protein expression by ubiquitination in ectopic lesions. We identified ubiquitination in 41 pivotal proteins within the fibrosis-related pathway of endometriosis. Finally, the elevated expression of TGFBR1/α-SMA/FAP/FN1/Collagen1 proteins in EC tissues were validated across independent samples. More importantly, we demonstrated that both the mRNA and protein levels of TRIM33 were reduced in endometriotic tissues. Knockdown of TRIM33 promoted TGFBR1/p-SMAD2/α-SMA/FN1 protein expressions in hESCs but did not significantly affect Collagen1/FAP levels, suggesting its inhibitory effect on fibrosis in vitro.

CONCLUSIONS

This study, employing multi-omics approaches, provides novel insights into endometriosis ubiquitination profiles and reveals aberrant expression of the E3 ubiquitin ligase TRIM33 in endometriotic tissues, emphasizing their critical involvement in fibrosis pathogenesis and potential therapeutic targets.

An integrated multi-omics approach reveals polymethoxylated flavonoid biosynthesis in Citrus reticulata cv. Chachiensis

Citrus reticulata cv. Chachiensis (CRC) is an important medicinal plant, its dried mature peels named "Guangchenpi", has been used as a traditional Chinese medicine to treat cough, indigestion, and lung diseases for several hundred years. However, the biosynthesis of the crucial natural products polymethoxylated flavonoids (PMFs) in CRC remains unclear. Here, we report a chromosome-scale genome assembly of CRC with the size of 314.96 Mb and a contig N50 of 16.22 Mb. Using multi-omics resources, we discover a putative caffeic acid O-methyltransferase (CcOMT1) that can transfer a methyl group to the 3-hydroxyl of natsudaidain to form 3,5,6,7,8,3',4'-heptamethoxyflavone (HPMF). Based on transient overexpression and virus-induced gene silencing experiments, we propose that CcOMT1 is a candidate enzyme in HPMF biosynthesis. In addition, a potential gene regulatory network associated with PMF biosynthesis is identified. This study provides insights into PMF biosynthesis and may assist future research on mining genes for the biosynthesis of plant-based medicines.

Integrative multiomics enhancer activity profiling identifies therapeutic vulnerabilities in cholangiocarcinoma of different etiologies

OBJECTIVES

Cholangiocarcinoma (CCA) is a heterogeneous malignancy with high mortality and dismal prognosis, and an urgent clinical need for new therapies. Knowledge of the CCA epigenome is largely limited to aberrant DNA methylation. Dysregulation of enhancer activities has been identified to affect carcinogenesis and leveraged for new therapies but is uninvestigated in CCA. Our aim is to identify potential therapeutic targets in different subtypes of CCA through enhancer profiling.

DESIGN

Integrative multiomics enhancer activity profiling of diverse CCA was performed. A panel of diverse CCA cell lines, patient-derived and cell line-derived xenografts were used to study identified enriched pathways and vulnerabilities. NanoString, multiplex immunohistochemistry staining and single-cell spatial transcriptomics were used to explore the immunogenicity of diverse CCA.

RESULTS

We identified three distinct groups, associated with different etiologies and unique pathways. Drug inhibitors of identified pathways reduced tumour growth in in vitro and in vivo models. The first group (ESTRO), with mostly fluke-positive CCAs, displayed activation in estrogen signalling and were sensitive to MTOR inhibitors. Another group (OXPHO), with mostly BAP1 and IDH-mutant CCAs, displayed activated oxidative phosphorylation pathways, and were sensitive to oxidative phosphorylation inhibitors. Immune-related pathways were activated in the final group (IMMUN), made up of an immunogenic CCA subtype and CCA with aristolochic acid (AA) mutational signatures. Intratumour differences in AA mutation load were correlated to intratumour variation of different immune cell populations.

CONCLUSION

Our study elucidates the mechanisms underlying enhancer dysregulation and deepens understanding of different tumourigenesis processes in distinct CCA subtypes, with potential significant therapeutics and clinical benefits.

Integrated multi-omic approach reveals the effect of a Graminaceae-derived biostimulant and its lighter fraction on salt-stressed lettuce plants

Plant biostimulants are widely applied in agriculture for their ability to improve plant fitness. In the present work, the impact of Graminaceae-derived protein hydrolysate (P) and its lighter molecular fraction F3 (< 1 kDa) on lettuce plants, subjected to either no salt or high salt conditions, was investigated through the combination of metabolomics and transcriptomics. The results showed that both treatments significantly modulated the transcriptome and metabolome of plants under salinity stress, highlighting an induction of the hormonal response. Nevertheless, P and F3 also displayed several peculiarities. F3 specifically modulated the response to ethylene and MAPK signaling pathway, whereas P treatment induced a down-accumulation of secondary metabolites, albeit genes controlling the biosynthesis of osmoprotectants and antioxidants were up-regulated. Moreover, according with the auxin response modulation, P promoted cell wall biogenesis and plasticity in salt-stressed plants. Notably, our data also outlined an epigenetic control of gene expression induced by P treatment. Contrarily, experimental data are just partially in agreement when not stressed plants, treated with P or F3, were considered. Indeed, the reduced accumulation of secondary metabolites and the analyses of hormone pathways modulation would suggest a preferential allocation of resources towards growth, that is not coherent with the down-regulation of the photosynthetic machinery, the CO2 assimilation rate and leaves biomass. In conclusion, our data demonstrate that, although they might activate different mechanisms, both the P and F3 can result in similar benefits, as far as the accumulation of protective osmolytes and the enhanced tolerance to oxidative stress are concerned. Notably, the F3 fraction exhibits slightly greater growth promotion effects under high salt conditions. Most importantly, this research further corroborates that biostimulants' mode of action is dependent on plants' physiological status and their composition, underscoring the importance of investigating the bioactivity of the different molecular components to design tailored applications for the agricultural practice.

Multiomics-based molecular subtyping based on the commensal microbiome predicts molecular characteristics and the therapeutic response in breast cancer

The gut microbiota has been demonstrated to be correlated with the clinical phenotypes of diseases, including cancers. However, there are few studies on clinical subtyping based on the gut microbiota, especially in breast cancer (BC) patients. Here, using machine learning methods, we analysed the gut microbiota of BC, colorectal cancer (CRC), and gastric cancer (GC) patients to identify their shared metabolic pathways and the importance of these pathways in cancer development. Based on the gut microbiota-related metabolic pathways, human gene expression profile and patient prognosis, we established a novel BC subtyping system and identified a subtype called "challenging BC". Tumours with this subtype have more genetic mutations and a more complex immune environment than those of other subtypes. A score index was proposed for in-depth analysis and showed a significant negative correlation with patient prognosis. Notably, activation of the TPK1-FOXP3-mediated Hedgehog signalling pathway and TPK1-ITGAE-mediated mTOR signalling pathway was linked to poor prognosis in "challenging BC" patients with high scores, as validated in a patient-derived xenograft (PDX) model. Furthermore, our subtyping system and score index are effective predictors of the response to current neoadjuvant therapy regimens, with the score index significantly negatively correlated with both treatment efficacy and the number of immune cells. Therefore, our findings provide valuable insights into predicting molecular characteristics and treatment responses in "challenging BC" patients.

Research on the mechanism of regulating spleen-deficient obesity in rats by bawei guben huashi jiangzhi decoction based on multi-omics analysis

ETHNOPHARMACOLOGY RELEVANCE

Bawei Guben Huashi Jiangzhi Decoction (BGHJ), a traditional Chinese compound formula, comprises eight Chinese medicinal herbs: Codonopsis Radix, Atractylodis Macrocephalae Rhizoma, Cassiae Semen, Lysimachiae Herba, Edgeworthiae Gardner Flos, Oryzae Semen cum Monasco, Nelumbinis Folium, and Alismatis Rhizoma. It has the therapeutic effects of improving digestive and absorptive functions of the gastrointestinal tract, reducing cholesterol levels, and helping to lose weight. Therefore, BGHJ is mainly used to treat spleen-deficient obesity (SDO) clinically.

AIM OF THE STUDY

This study aims to examine the efficacy and mechanism of BGHJ in a model of SDO in rats, as well as the potentially involved constituents entering the blood and differential metabolites.

METHODS

The SDO rat model was replicated utilizing a high-fat and high-sugar diet in conjunction with exhaustive swimming. Subsequently, the rats were subjected to a six-week intervention comprising varying dosages of BGHJ and a positive control, orlistat. To evaluate the efficacy of BGHJ on SDO model rats, we first measured the rats' body weight, body surface temperature, spleen index, as well as biochemical indicators in the serum and colon, and then assessed the pathological state of the colon and liver. Afterward, we analyzed the 16S rDNA gut microbiota, non-targeted serum metabolomics, and serum pharmacology to study the main active components of BGHJ and its action mechanism against SDO model rats. In addition, we constructed a network diagram for overall visualization and analysis, and experimentally verified the predicted results. Finally, we used quantitative polymerase chain reaction (qPCR) to detect the gene expression of proopiomelanocortin (POMC) and neuropeptide Y (NPY) indicators in rat hypothalamic neurons. We quantitatively targeted the detection of neurotransmitters dopamine (DA), acetylcholine (Ach), 5-hydroxytryptamine (5-HT), and noradrenaline (NA) in rat hypothalamus.

RESULTS

The results demonstrated that all dosage regimens of BGHJ exhibited the capacity to moderately modulate parameters including body weight, surface temperature, spleen index, total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), glucagon-like peptide-1 (GLP-1), cholecystokinin (CCK), 5-HT, interleukin 6 (IL-6) and interleukin 17 (IL-17), while concurrently reducing hepatic lipid droplet deposition and restoring intestinal integrity. Subsequent experimental results showed that we successfully identified 27 blood components of BGHJ and identified 52 differential metabolites in SDO model rats. At the same time, the experiment proved that BGHJ could effectively inhibit the metabolic pathway of arachidonic acid. In addition, BGHJ can also restore the intestinal microbiota composition of SDO model rats. Finally, we also found that BGHJ could regulate the expression of hypothalamic neurons and neurotransmitters.

CONCLUSIONS

The research revealed the main active ingredients of BGHJ and its mechanism against SDO model rats through gut microbiota, non-target serum metabolomics, and serum drug chemistry.

Multi-omics reveals the testosterone promotion effect mechanism of Cordyceps Sobolifera on Leydig cells

ETHNOPHARMACOLOGICAL RELEVANCE

Cordyceps sobolifera (CS) has been traditionally utilized as an ethnic remedy for various health conditions, including chronic kidney diseases, anti-fatigue interventions, and management of chronic inflammation. Notably, CS is recognized for its substantial content of bioactive compounds, among which nucleosides prominently feature as constituents with diverse therapeutic advantages.

AIM OF THE STUDY

This study aims to investigate the effects of CS on testosterone secretion in Leydig cells and explore the underlying mechanism.

MATERIALS AND METHODS

Leydig cells were isolated from rat testes to establish a primary rat Leydig cells model. Cell proliferation and testosterone secretion were assessed via the methyl-piperidino-pyrazole (MTT) assay and enzyme-linked immunosorbent assay (ELISA), respectively. Samples earmarked for RNA sequencing (RNA-Seq) analysis facilitated the identification of significantly differentially expressed genes (DEGs), and we conducted Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation and enrichment analyses. The veracity of our findings was validated through quantitative real time polymerase chain reaction (qRT-PCR) and western blotting.

RESULTS

The results showed that CS and guanosine could promote Leydig cell proliferation and bolster testosterone secretion. Our integrative analysis of metabolomics and transcriptomics has unveiled the potential mechanisms governing testosterone synthesis. Specifically, metabolomics has illuminated striking correlations within cholesterol metabolism, and bile secretion. Concurrently, transcriptomics has underscored the pivotal roles played by the cyclic adenosine monophosphate (cAMP) signaling pathway and steroid hormone biosynthesis. Furthermore, our investigation has demonstrated CS's aptitude in elevating the expression of proteins and genes. Notably, our findings have elucidated that these effects can be mitigated by protein kinase A (PKA) and adenylate cyclase (AC) specific inhibitors.

CONCLUSION

This study delineates the cAMP-PKA pathways as plausible mechanisms underpinning the testosterone-enhancing properties of CS, with guanosine emerging as a fundamental bioactive constituent.

A time-resolved multi-omics atlas of transcriptional regulation in response to high-altitude hypoxia across whole-body tissues

High-altitude hypoxia acclimatization requires whole-body physiological regulation in highland immigrants, but the underlying genetic mechanism has not been clarified. Here we use sheep as an animal model for low-to-high altitude translocation. We generate multi-omics data including whole-genome sequences, time-resolved bulk RNA-Seq, ATAC-Seq and single-cell RNA-Seq from multiple tissues as well as phenotypic data from 20 bio-indicators. We characterize transcriptional changes of all genes in each tissue, and examine multi-tissue temporal dynamics and transcriptional interactions among genes. Particularly, we identify critical functional genes regulating the short response to hypoxia in each tissue (e.g., PARG in the cerebellum and HMOX1 in the colon). We further identify TAD-constrained cis-regulatory elements, which suppress the transcriptional activity of most genes under hypoxia. Phenotypic and transcriptional evidence indicate that antenatal hypoxia could improve hypoxia tolerance in offspring. Furthermore, we provide time-series expression data of candidate genes associated with human mountain sickness (e.g., BMPR2) and high-altitude adaptation (e.g., HIF1A). Our study provides valuable resources and insights for future hypoxia-related studies in mammals.

Multiomics-assisted characterization of rice-Yellow Stem Borer interaction provides genomic and mechanistic insights into stem borer resistance in rice

KEY MESSAGE

By deploying a multi-omics approach, we unraveled the mechanisms that might help rice to combat Yellow Stem Borer infestation, thus providing insights and scope for developing YSB resistant rice varieties. Yellow Stem Borer (YSB), Scirpophaga incertulas (Walker) (Lepidoptera: Crambidae), is a major pest of rice, that can lead to 20-60% loss in rice production. Effective management of YSB infestation is challenged by the non-availability of adequate sources of resistance and poor understanding of resistance mechanisms, thus necessitating studies for generating resources to breed YSB resistant rice and to understand rice-YSB interaction. In this study, by using bulk-segregant analysis in combination with next-generation sequencing, Quantitative Trait Loci (QTL) intervals in five rice chromosomes were mapped that could be associated with YSB resistance at the vegetative phase in a resistant rice line named SM92. Further, multiple SNP markers that showed significant association with YSB resistance in rice chromosomes 1, 5, 10, and 12 were developed. RNA-sequencing of the susceptible and resistant lines revealed several genes present in the candidate QTL intervals to be differentially regulated upon YSB infestation. Comparative transcriptome analysis revealed a putative candidate gene that was predicted to encode an alpha-amylase inhibitor. Analysis of the transcriptome and metabolite profiles further revealed a possible link between phenylpropanoid metabolism and YSB resistance. Taken together, our study provides deeper insights into rice-YSB interaction and enhances the understanding of YSB resistance mechanism. Importantly, a promising breeding line and markers for YSB resistance have been developed that can potentially aid in marker-assisted breeding of YSB resistance among elite rice cultivars.

Multi-omics analysis revealed that the protein kinase MoKin1 affected the cellular response to endoplasmic reticulum stress in the rice blast fungus, Magnaporthe oryzae

BACKGROUND

Previous studies have shown that protein kinase MoKin1 played an important role in the growth, conidiation, germination and pathogenicity in rice blast fungus, Magnaporthe oryzae. ΔMokin1 mutant showed significant phenotypic defects and significantly reduced pathogenicity. However, the internal mechanism of how MoKin1 affected the development of physiology and biochemistry remained unclear in M. oryzae.

RESULT

This study adopted a multi-omics approach to comprehensively analyze MoKin1 function, and the results showed that MoKin1 affected the cellular response to endoplasmic reticulum stress (ER stress). Proteomic analysis revealed that the downregulated proteins in ΔMokin1 mutant were enriched mainly in the response to ER stress triggered by the unfolded protein. Loss of MoKin1 prevented the ER stress signal from reaching the nucleus. Therefore, the phosphorylation of various proteins regulating the transcription of ER stress-related genes and mRNA translation was significantly downregulated. The insensitivity to ER stress led to metabolic disorders, resulting in a significant shortage of carbohydrates and a low energy supply, which also resulted in severe phenotypic defects in ΔMokin1 mutant. Analysis of MoKin1-interacting proteins indicated that MoKin1 really took participate in the response to ER stress.

CONCLUSION

Our results showed the important role of protein kinase MoKin1 in regulating cellular response to ER stress, providing a new research direction to reveal the mechanism of MoKin1 affecting pathogenic formation, and to provide theoretical support for the new biological target sites searching and bio-pesticides developing.

Multiomics analysis identifies oxidative phosphorylation as a cancer vulnerability arising from myristoylation inhibition

BACKGROUND

In humans, two ubiquitously expressed N-myristoyltransferases, NMT1 and NMT2, catalyze myristate transfer to proteins to facilitate membrane targeting and signaling. We investigated the expression of NMTs in numerous cancers and found that NMT2 levels are dysregulated by epigenetic suppression, particularly so in hematologic malignancies. This suggests that pharmacological inhibition of the remaining NMT1 could allow for the selective killing of these cells, sparing normal cells with both NMTs.

METHODS AND RESULTS

Transcriptomic analysis of 1200 NMT inhibitor (NMTI)-treated cancer cell lines revealed that NMTI sensitivity relates not only to NMT2 loss or NMT1 dependency, but also correlates with a myristoylation inhibition sensitivity signature comprising 54 genes (MISS-54) enriched in hematologic cancers as well as testis, brain, lung, ovary, and colon cancers. Because non-myristoylated proteins are degraded by a glycine-specific N-degron, differential proteomics revealed the major impact of abrogating NMT1 genetically using CRISPR/Cas9 in cancer cells was surprisingly to reduce mitochondrial respiratory complex I proteins rather than cell signaling proteins, some of which were also reduced, albeit to a lesser extent. Cancer cell treatments with the first-in-class NMTI PCLX-001 (zelenirstat), which is undergoing human phase 1/2a trials in advanced lymphoma and solid tumors, recapitulated these effects. The most downregulated myristoylated mitochondrial protein was NDUFAF4, a complex I assembly factor. Knockout of NDUFAF4 or in vitro cell treatment with zelenirstat resulted in loss of complex I, oxidative phosphorylation and respiration, which impacted metabolomes.

CONCLUSIONS

Targeting of both, oxidative phosphorylation and cell signaling partly explains the lethal effects of zelenirstat in select cancer types. While the prognostic value of the sensitivity score MISS-54 remains to be validated in patients, our findings continue to warrant the clinical development of zelenirstat as cancer treatment.