Multi-omics Integration Analysis Robustly Predicts High-Grade Patient Survival and Identifies CPT1B Effect on Fatty Acid Metabolism in Bladder Cancer

UPLC-Q-TOF/MS-based urine metabolomics for the diagnosis and staging of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common malignant tumour of the urinary system. Currently, the gold standard for diagnosing BC is cystoscopy, but it is an invasive examination that can lead to a certain psychological burden on the patient. In this study, we aimed to identify non-invasive potential metabolic biomarkers that could improve the diagnostic accuracy of bladder cancer.

METHODS

Urine from 30 healthy people and 50 BC patients, including 40 non-muscle-invasive bladder cancer (NMIBC) patients and 10 muscle-invasive bladder cancer (MIBC) patients, were analyzed by liquid chromatography coupled with mass spectrometry to identify potential diagnostic metabolites. Binary Logistic regression was used to construct biomarker panels. Correlation analysis and construction of compound-reaction-enzyme-gene network were also performed to explore the possible mechanisms of BC development.

RESULTS

Twenty-six metabolites were identified for differentiating BC patients from healthy controls, and eight metabolites were identified for differentiating NMIBC patients form MIBC patients. The biomarker panel consisting of urate, 4-Androstene-3α, 17β-diol and 3-Indoxyl sulfate can distinguish well between BC patients and healthy controls, with an area under the ROC curve (AUC) value of 0.983. And the biomarker panel consisting of L-Octanoylcarnitine, γ-Glutamylleucine, and heptanoylcarnitine for distinguishing NMIBC patients from MIBC patients had an AUC value of 0.941.

CONCLUSIONS

The diagnostic capability of the biomarker panels are superior to that of any single potential biomarker. This panel significantly benefits bladder cancer diagnostics and reveals insight into bladder cancer pathogenesis.

Magnetic 3D macroporous MOF oriented urinary exosome metabolomics for early diagnosis of bladder cancer

Bladder cancer (BCa) exhibits the escalating incidence and mortality due to the untimely and inaccurate early diagnosis. Urinary exosome metabolites, carrying critical tumor cell information and directly related to bladder, emerge as promising non-invasive diagnostic biomarkers of BCa. Herein, the magnetic 3D ordered macroporous zeolitic imidazolate framework-8 (magMZIF-8) is synthesized and used for efficient urinary exosome isolation. Notably, beyond retaining the single crystals and micropores of conventional ZIF-8, MZIF-8 is further enhanced with highly oriented and ordered macropores (150 nm) and the large specific surface area (973 m2·g-1), which could enable the high purity and yield separation of exosomes via leveraging the combination of size exclusion, affinity, and electrostatic interactions between magMZIF-8 and the surfaces of exosome. Furthermore, the magnetic and hydrophilic properties of magMZIF-8 will further simplify the process and enhance the efficiency of separation. After conditional optimization, a 50 mL of urine is sufficient for exosome metabolomics analysis, and the time for isolating exosomes from 42 urine samples was 2 hours only. Incorporating machine learning algorithms with LC-MS/MS analysis of the metabolic patterns obtained from isolated exosomes, early-stage BCa patients were differentiated from healthy controls, with area under the curve (AUC) value of 0.844-0.9970 in the training set and 0.875-1.00 in the test set, signifying its potential as a reliable diagnostic tool. This study offers a promising approach for the non-invasive and efficient diagnosis of BCa on a large scale via exosome metabolomics.

The Role of the CPT Family in Cancer: Searching for New Therapeutic Strategies

Along with abnormalities in glucose metabolism, disturbances in the balance of lipid catabolism and synthesis have emerged as a new area of cancer metabolism that needs to be studied in depth. Disturbances in lipid metabolic homeostasis, represented by fatty acid oxidation (FAO) imbalance, leading to activation of pro-cancer signals and abnormalities in the expression and activity of related metabolically critical rate-limiting enzymes, have become an important part of metabolic remodeling in cancer. The FAO process is a metabolic pathway that facilitates the breakdown of fatty acids into CO2 and H2O and releases large amounts of energy in the body under aerobic conditions. More and more studies have shown that FAO provides an important energy supply for the development of cancer cells. At the same time, the CPT family, including carnitine palmitoyltransferase 1 (CPT1) and carnitine palmitoyltransferase 2 (CPT2), are key rate-limiting enzymes for FAO that exert a pivotal influence on the genesis and progression of neoplastic growth. Therefore, we look at molecular structural properties of the CPT family, the roles they play in tumorigenesis and development, the target drugs, and the possible regulatory roles of CPTs in energy metabolism reprogramming to help understand the current state of CPT family research and to search for new therapeutic strategies.

Tobacco smoke exposure is a driver of altered oxidative stress response and immunity in head and neck cancer

Purpose

Exposomes are critical drivers of carcinogenesis. However, how they modulate tumor behavior remains unclear. Extensive clinical data link cigarette smoke as a key exposome that promotes aggressive tumors, higher rates of metastasis, reduced response to chemoradiotherapy, and suppressed anti-tumor immunity. We sought to determine whether smoke itself can modulate aggressive tumor behavior in head and neck squamous cell carcinoma (HNSCC) through reprogramming the cellular reductive state.

Experimental design

Using established human and murine HNSCC cell lines and syngeneic mouse models, we utilized conventional western blotting, steady state and flux metabolomics, RNA sequencing, quantitative proteomics and flow cytometry to analyze the impact of smoke exposure on HNSCC tumor biology.

Results

Cigarette smoke persistently activated Nrf2 target genes essential for maintenance of the cellular reductive state and survival under conditions of increased oxidative stress in HNSCC regardless of HPV status. In contrast to e-cigarette vapor, conventional cigarette smoke mobilizes cellular metabolism toward oxidative stress adaptation, resulting in development of cross-resistance to cisplatin. In parallel, smoke exposure modulates both expression of PDL1 and the secretory phenotype of HNSCC cells through activation of NF-κB resulting in an altered tumor immune microenvironment (TIME) in syngeneic mouse models and altered PBMC differentiation that includes downregulated expression of antigen presentation and costimulatory genes in myeloid cells.

Conclusion

Cigarette smoke exposome is a potent activator of the Nrf2 pathway and is a likely primary trigger for the tripartite phenotype of aggressive HNSCC consisting of: 1) reduced chemotherapy sensitivity, 2) enhanced metastatic potential and 3) suppressed anti-tumor immunity.

Statement of significance

The smoke exposome drives aggressive tumor behavior, treatment resistance and suppressed immunity through coordinated metabolic reprogramming. Successfully targeting this adaptation is critical to improving survival in smokers with head and neck cancer.

m6A-Mediated Induction of 7-Dehydrocholesterol Reductase Stimulates Cholesterol Synthesis and cAMP Signaling to Promote Bladder Cancer Metastasis

Dysregulation of cholesterol homeostasis occurs in multiple types of tumors and promotes cancer progression. Investigating the specific processes that induce abnormal cholesterol metabolism could identify therapeutic targets to improve cancer treatment. In this investigation, we observed upregulation of 7-dehydrocholesterol reductase (DHCR7), a vital enzyme involved in the synthesis of cholesterol, within bladder cancer tissues in comparison to normal tissues, which was correlated with increased bladder cancer metastasis. Increased expression of DHCR7 in bladder cancer was attributed to decreased mRNA degradation mediated by YTHDF2. Loss or inhibition of DHCR7 reduced bladder cancer cell invasion in vitro and metastasis in vivo. Mechanistically, DHCR7 promoted bladder cancer metastasis by activating the cAMP/protein kinase A/FAK pathway. Specifically, DHCR7 increased cAMP levels by elevating cholesterol content in lipid rafts, thereby facilitating the transduction of signaling pathways mediated by cAMP receptors. DHCR7 additionally enhanced the cAMP signaling pathway by reducing the concentration of 7-dehydrocholesterol and promoting the transcription of the G protein-coupled receptor, namely gastric inhibitory polypeptide receptor. Overall, these findings demonstrate that DHCR7 plays an important role in bladder cancer invasion and metastasis by modulating cholesterol synthesis and cAMP signaling. Furthermore, inhibition of DHCR7 shows promise as a viable therapeutic strategy for suppressing bladder cancer invasion and metastasis. Significance: Inhibiting DHCR7 induces cholesterol metabolism reprogramming and lipid raft remodeling to inactivate the cAMP/protein kinase A/FAK axis and suppress bladder cancer metastasis, indicating the therapeutic potential of targeting DHCR7.

Mitochondrial reprogramming by activating OXPHOS via glutamine metabolism in African American patients with bladder cancer

Bladder cancer (BLCA) mortality is higher in African American (AA) patients compared with European American (EA) patients, but the molecular mechanism underlying race-specific differences are unknown. To address this gap, we conducted comprehensive RNA-Seq, proteomics, and metabolomics analysis of BLCA tumors from AA and EA. Our findings reveal a distinct metabolic phenotype in AA BLCA characterized by elevated mitochondrial oxidative phosphorylation (OXPHOS), particularly through the activation of complex I. The results provide insight into the complex I activation-driven higher OXPHOS activity resulting in glutamine-mediated metabolic rewiring and increased disease progression, which was also confirmed by [U]13C-glutamine tracing. Mechanistic studies further demonstrate that knockdown of NDUFB8, one of the components of complex I in AA BLCA cells, resulted in reduced basal respiration, ATP production, GLS1 expression, and proliferation. Moreover, preclinical studies demonstrate the therapeutic potential of targeting complex I, as evidenced by decreased tumor growth in NDUFB8-depleted AA BLCA tumors. Additionally, genetic and pharmacological inhibition of GLS1 attenuated mitochondrial respiration rates and tumor growth potential in AA BLCA. Taken together, these findings provide insight into BLCA disparity for targeting GLS1-Complex I for future therapy.

Differences in Prediagnostic Serum Metabolomic and Lipidomic Profiles Between Cirrhosis Patients with and without Incident Hepatocellular Carcinoma

Background

Early detection of hepatocellular carcinoma (HCC) is crucial for improving patient outcomes, but we lack robust clinical biomarkers. This study aimed to identify a metabolite and/or lipid panel for early HCC detection.

Methods

We developed a high-resolution liquid chromatography mass spectrometry (LC-MS)-based profiling platform and evaluated differences in the global metabolome and lipidome between 28 pre-diagnostic serum samples from patients with cirrhosis who subsequently developed HCC (cases) and 30 samples from patients with cirrhosis and no HCC (controls). We linked differentially expressed metabolites and lipids to their associated genes, proteins, and transcriptomic signatures in publicly available datasets. We used machine learning models to identify a minimal panel to distinguish between cases and controls.

Results

Among cases compared with controls, 124 metabolites and 246 lipids were upregulated, while 208 metabolites and 73 lipids were downregulated. The top upregulated metabolites were glycoursodeoxycholic acid, 5-methyltetrahydrofolic acid, octanoyl-coenzyme A, and glycocholic acid. Elevated lipids comprised glycerol lipids, cardiolipin, and phosphatidylethanolamine, whereas suppressed lipids included oxidized phosphatidylcholine and lysophospholipids. There was an overlap between differentially expressed metabolites and lipids and previously published transcriptomic signatures, illustrating an association with liver disease severity. A panel of 12 metabolites that distinguished between cases and controls with an area under the receiver operating curve of 0.98 for the support vector machine (interquartile range, 0.9-1).

Conclusion

Using prediagnostic serum samples, we identified a promising metabolites panel that accurately identifies patients with cirrhosis who progressed to HCC. Further validation of this panel is required.

MT1G induces lipid droplet accumulation through modulation of H3K14 trimethylation accelerating clear cell renal cell carcinoma progression

BACKGROUND

Lipid droplet formation is a prominent histological feature in clear cell renal cell carcinoma (ccRCC), but the significance and mechanisms underlying lipid droplet accumulation remain unclear.

METHODS

Expression and clinical significance of MT1G in ccRCC were analyzed by using TCGA data, GEO data and scRNASeq data. MT1G overexpression or knockdown ccRCC cell lines were constructed and in situ ccRCC model, lung metastasis assay, metabolomics and lipid droplets staining were performed to explore the role of MT1G on lipid droplet accumulation in ccRCC.

RESULTS

Initially, we observed low MT1G expression in ccRCC tissues, whereas high MT1G expression correlated with advanced disease stage and poorer prognosis. Elevated MT1G expression promoted ccRCC growth and metastasis both in vitro and in vivo. Mechanistically, MT1G significantly suppressed acylcarnitine levels and downstream tricarboxylic acid (TCA) cycle activity, resulting in increased fatty acid and lipid accumulation without affecting cholesterol metabolism. Notably, MT1G inhibited H3K14 trimethylation (H3K14me3) modification. Under these conditions, MT1G-mediated H3K14me3 was recruited to the CPT1B promoter through direct interaction with specific promoter regions, leading to reduced CPT1B transcription and translation.

CONCLUSIONS

Our study unveils a novel mechanism of lipid droplet accumulation in ccRCC, where MT1G inhibits CPT1B expression through modulation of H3K14 trimethylation, consequently enhancing lipid droplet accumulation and promoting ccRCC progression. Graphical abstract figure Schematic diagram illustrating MT1G/H3K14me3/CPT1B-mediated lipid droplet accumulation promoted ccRCC progression via FAO inhibition.

ASCT2 Regulates Fatty Acid Metabolism to Trigger Glutamine Addiction in Basal-like Breast Cancer

As a crucial amino acid, glutamine can provide the nitrogen and carbon sources needed to support cancer cell proliferation, invasion, and metastasis. Interestingly, different types of breast cancer have different dependences on glutamine. This research shows that basal-like breast cancer depends on glutamine, while the other types of breast cancer may be more dependent on glucose. Glutamine transporter ASCT2 is highly expressed in various cancers and significantly promotes the growth of breast cancer. However, the key regulatory mechanism of ASCT2 in promoting basal-like breast cancer progression remains unclear. Our research demonstrates the significant change in fatty acid levels caused by ASCT2, which may be a key factor in glutamine sensitivity. This phenomenon results from the mutual activation between ASCT2-mediated glutamine transport and lipid metabolism via the nuclear receptor PPARα. ASCT2 cooperatively promoted PPARα expression, leading to the upregulation of lipid metabolism. Moreover, we also found that C118P could inhibit lipid metabolism by targeting ASCT2. More importantly, this research identifies a potential avenue of evidence for the prevention and early intervention of basal-like breast cancer by blocking the glutamine-lipid feedback loop.

Higher genetically predicted triglyceride level increases the bladder cancer risk independent of LDL and HDL levels

The causal relationship between lipid levels and bladder cancer is still inconclusive currently. We aimed to reveal the causal relationship between triglycerides, HDL, and LDL and the risk of bladder cancer by univariable and multivariable Mendelian randomization (MR) analysis. The single nucleotide polymorphisms (SNPs) of exposure (triglycerides: 441,016 samples; HDL: 403,943 samples; LDL: 440,546 samples) were obtained from UK Biobank. The Genetic variation related to bladder cancer included 1554 cases and 359,640 controls. Univariable and multivariable MR methods were conducted with subsequent analysis, and smoking was regarded as a confounder. The inverse-variance weighted (IVW), MR-Egger, weighted-median method, Cochran's Q test, and MR-PRESSO were considered the main MR analysis and sensitivity analysis methods. Univariable MR analysis results suggested the triglycerides level (P = 0.011, OR = 1.001, 95% CI = 1.000-1.002) was causally associated with increased risk of bladder cancer. Multivariable MR results indicated that higher triglyceride levels could still increase the risk of bladder cancer after adjusting the effects of HDL, LDL, and smoking (P = 0.042, OR = 1.001, 95% CI = 1.000-1.002). Our findings supported that triglyceride level is causally associated with an increased risk of bladder cancer independent of LDL and HDL at the genetic level. Timely attention to changes in blood lipid levels might reduce the risk of bladder cancer.

Metabolomic Profiles in Jamaican Children With and Without Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a wide range of behavioral and cognitive impairments. While genetic and environmental factors are known to contribute to its etiology, metabolic perturbations associated with ASD, which can potentially connect genetic and environmental factors, remain poorly understood. Therefore, we conducted a metabolomic case-control study and performed a comprehensive analysis to identify significant alterations in metabolite profiles between children with ASD and typically developing (TD) controls in order to identify specific metabolites that may serve as biomarkers for the disorder. We conducted metabolomic profiling on plasma samples from participants in the second phase of Epidemiological Research on Autism in Jamaica, an age and sex-matched cohort of 200 children with ASD and 200 TD controls (2-8 years old). Using high-throughput liquid chromatography-mass spectrometry techniques, we performed a targeted metabolite analysis, encompassing amino acids, lipids, carbohydrates, and other key metabolic compounds. After quality control and missing data imputation, we performed univariable and multivariable analysis using normalized metabolites while adjusting for covariates, age, sex, socioeconomic status, and child's parish of birth. Our findings revealed unique metabolic patterns in children with ASD for four metabolites compared to TD controls. Notably, three metabolites were fatty acids, including myristoleic acid, eicosatetraenoic acid, and octadecenoic acid. The amino acid sarcosine exhibited a significant association with ASD. These findings highlight the role of metabolites in the etiology of ASD and suggest opportunities for the development of targeted interventions.

Urinary microbiome dysbiosis is associated with an inflammatory environment and perturbed fatty acids metabolism in the pathogenesis of bladder cancer

BACKGROUND

Bladder cancer is a common malignancy with high recurrence rate. Early diagnosis and recurrence surveillance are pivotal to patients' outcomes, which require novel minimal-invasive diagnostic tools. The urinary microbiome is associated with bladder cancer and can be used as biomarkers, but the underlying mechanism is to be fully illustrated and diagnostic performance to be improved.

METHODS

A total of 23 treatment-naïve bladder cancer patients and 9 non-cancerous subjects were enrolled into the Before group and Control group. After surgery, 10 patients from the Before group were further assigned into After group. Void mid-stream urine samples were collected and sent for 16S rDNA sequencing, targeted metabolomic profiling, and flow cytometry. Next, correlations were analyzed between microbiota, metabolites, and cytokines. Finally, receiver operating characteristic (ROC) curves of the urinary biomarkers were plotted and compared.

RESULTS

Comparing to the Control group, levels of IL-6 (p < 0.01), IL-8 (p < 0.05), and IL-10 (p < 0.05) were remarkably elevated in the Before group. The α diversity of urine microbiome was also significantly higher, with the feature microbiota positively correlated to the level of IL-6 (r = 0.58, p < 0.01). Significant differences in metabolic composition were also observed between the Before and Control groups, with fatty acids and fatty acylcarnitines enriched in the Before group. After tumor resection, cytokine levels and the overall microbiome structure in the After group remained similar to that of the Before group, but fatty acylcarnitines were significantly reduced (p < 0.05). Pathway enrichment analysis revealed beta-oxidation of fatty acids was significantly involved (p < 0.001). ROC curves showed that the biomarker panel of Actinomycetaceae + arachidonic acid + IL-6 had superior diagnostic performance, with sensitivity of 0.94 and specificity of 1.00.

CONCLUSIONS

Microbiome dysbiosis, proinflammatory environment and altered fatty acids metabolism are involved in the pathogenesis of bladder cancer, which may throw light on novel noninvasive diagnostic tool development.

CPT1B maintains redox homeostasis and inhibits ferroptosis to induce gemcitabine resistance via the KEAP1/NRF2 axis in pancreatic cancer

BACKGROUND

Although we have made progress in treatment and have increased the 5-year survival by ≤30% in pancreatic cancer, chemotherapy resistance remains a major obstacle. However, whether reprogrammed lipid metabolism contributes to chemoresistance still needs to be further studied.

METHODS

Gene expression was determined using Western blotting and quantitative reverse transcription polymerase chain reaction. Cell cloning formation assay, Cell Counting Kit-8, EdU assay, wound healing assay, transwell assay, and flow cytometry were used to detect apoptosis, cell proliferation capacity, migration capacity, and cytotoxicity of gemcitabine. Confocal fluorescence microscopy, transmission electron microscopy, etc., were used to detect the changes in intracellular reactive oxygen species, glutathione, lipid peroxidation level, and cell morphology. An animal study was performed to evaluate the effect of CPT1B knockdown on tumor growth and gemcitabine efficacy.

RESULTS

In our study, we observed that the CPT1B expression level was higher in pancreatic ductal adenocarcinoma tissues than in normal tissues and correlated with a low rate of survival. Moreover, silencing of CPT1B significantly suppressed the proliferative ability and metastasis of pancreatic cancer cells. Furthermore, we discovered that CPT1B interacts with Kelch-like ECH-associated protein 1, and CPT1B knockdown led to decreased NRF2 expression and ferroptosis induction. In addition, CPT1B expression increased after gemcitabine treatment, and it was highly expressed in gemcitabine-resistant pancreatic ductal adenocarcinoma cells. Finally, we discovered that ferroptosis induced by CPT1B knockdown enhanced the gemcitabine toxicity in pancreatic ductal adenocarcinoma.

CONCLUSION

CPT1B may act as a promising target in treating patients with gemcitabine-resistant pancreatic ductal adenocarcinoma .

CD24 negativity reprograms mitochondrial metabolism to PPARα and NF-κB-driven fatty acid β-oxidation in triple-negative breast cancer

CD24 is a well-characterized breast cancer (BC) stem cell (BCSC) marker. Primary breast tumor cells having CD24-negativity together with CD44-positivity is known to maintain high metastatic potential. However, the functional role of CD24 gene in triple-negative BC (TNBC), an aggressive subtype of BC, is not well understood. While the significance of CD24 in regulating immune pathways is well recognized in previous studies, the significance of CD24 low expression in onco-signaling and metabolic rewiring is largely unknown. Using CD24 knock-down and over-expression TNBC models, our in vitro and in vivo analysis suggest that CD24 is a tumor suppressor in metastatic TNBC. Comprehensive in silico gene expression analysis of breast tumors followed by lipidomic and metabolomic analyses of CD24-modulated cells revealed that CD24 negativity induces mitochondrial oxidative phosphorylation and reprograms TNBC metabolism toward the fatty acid beta-oxidation (FAO) pathway. CD24 silencing activates PPARα-mediated regulation of FAO in TNBC cells. Further analysis using reverse-phase protein array and its validation using CD24-modulated TNBC cells and xenograft models nominated CD24-NF-κB-CPT1A signaling pathway as the central regulatory mechanism of CD24-mediated FAO activity. Overall, our study proposes a novel role of CD24 in metabolic reprogramming that can open new avenues for the treatment strategies for patients with metastatic TNBC.

Unmasking the Metabolite Signature of Bladder Cancer: A Systematic Review

Bladder cancer (BCa) research relying on Omics approaches has increased over the last few decades, improving the understanding of BCa pathology and contributing to a better molecular classification of BCa subtypes. To gain further insight into the molecular profile underlying the development of BCa, a systematic literature search was performed in PubMed until November 2023, following the PRISMA guidelines. This search enabled the identification of 25 experimental studies using mass spectrometry or nuclear magnetic resonance-based approaches to characterize the metabolite signature associated with BCa. A total of 1562 metabolites were identified to be altered by BCa in different types of samples. Urine samples displayed a higher likelihood of containing metabolites that are also present in bladder tumor tissue and cell line cultures. The data from these comparisons suggest that increased concentrations of L-isoleucine, L-carnitine, oleamide, palmitamide, arachidonic acid and glycoursodeoxycholic acid and decreased content of deoxycytidine, 5-aminolevulinic acid and pantothenic acid should be considered components of a BCa metabolome signature. Overall, molecular profiling of biological samples by metabolomics is a promising approach to identifying potential biomarkers for early diagnosis of different BCa subtypes. However, future studies are needed to understand its biological significance in the context of BCa and to validate its clinical application.

Metabolomic profiles in Jamaican children with and without autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a wide range of behavioral and cognitive impairments. While genetic and environmental factors are known to contribute to its etiology, the underlying metabolic perturbations associated with ASD which can potentially connect genetic and environmental factors, remain poorly understood. Therefore, we conducted a metabolomic case-control study and performed a comprehensive analysis to identify significant alterations in metabolite profiles between children with ASD and typically developing (TD) controls.

Objective

To elucidate potential metabolomic signatures associated with ASD in children and identify specific metabolites that may serve as biomarkers for the disorder.

Methods

We conducted metabolomic profiling on plasma samples from participants in the second phase of Epidemiological Research on Autism in Jamaica (ERAJ-2), which was a 1:1 age (±6 months)-and sex-matched cohort of 200 children with ASD and 200 TD controls (2-8 years old). Using high-throughput liquid chromatography-mass spectrometry techniques, we performed a targeted metabolite analysis, encompassing amino acids, lipids, carbohydrates, and other key metabolic compounds. After quality control and imputation of missing values, we performed univariable and multivariable analysis using normalized metabolites while adjusting for covariates, age, sex, socioeconomic status, and child's parish of birth.

Results

Our findings revealed unique metabolic patterns in children with ASD for four metabolites compared to TD controls. Notably, three of these metabolites were fatty acids, including myristoleic acid, eicosatetraenoic acid, and octadecenoic acid. Additionally, the amino acid sarcosine exhibited a significant association with ASD.

Conclusions

These findings highlight the role of metabolites in the etiology of ASD and suggest opportunities for the development of targeted interventions.

Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers

The principal aim of this investigation is to identify pivotal biomarkers linked to the prognosis of osteosarcoma (OS) through the application of artificial intelligence (AI), with an ultimate goal to enhance prognostic prediction. Expression profiles from 88 OS cases and 396 normal samples were procured from accessible public databases. Prognostic models were established using univariate COX regression analysis and an array of AI methodologies including the XGB method, RF method, GLM method, SVM method, and LASSO regression analysis. Multivariate COX regression analysis was also employed. Immune cell variations in OS were examined using the CIBERSORT software, and a differential analysis was conducted. Routine blood data from 20,679 normal samples and 437 OS cases were analyzed to validate lymphocyte disparity. Histological assessments of the study's postulates were performed through immunohistochemistry and hematoxylin and eosin (HE) staining. AI facilitated the identification of differentially expressed genes, which were utilized to construct a prognostic model. This model discerned that the survival rate in the high-risk category was significantly inferior compared to the low-risk cohort (p < 0.05). SERPINE2 was found to be positively associated with memory B cells, while CPT1B correlated positively with CD8 T cells. Immunohistochemical assessments indicated that SERPINE2 was more prominently expressed in OS tissues relative to adjacent non-tumorous tissues. Conversely, CPT1B expression was elevated in the adjacent non-tumorous tissues compared to OS tissues. Lymphocyte counts from routine blood evaluations exhibited marked differences between normal and OS groups (p < 0.001). The study highlights SERPINE2 and CPT1B as crucial biomarkers for OS prognosis and suggests that dysregulation of lymphocytes plays a significant role in OS pathogenesis. Both SERPINE2 and CPT1B have potential utility as prognostic biomarkers for OS.

Metabolomic Rewiring Promotes Endocrine Therapy Resistance in Breast Cancer

Approximately one-third of endocrine-treated women with estrogen receptor alpha-positive (ER+) breast cancers are at risk of recurrence due to intrinsic or acquired resistance. Thus, it is vital to understand the mechanisms underlying endocrine therapy resistance in ER+ breast cancer to improve patient treatment. Mitochondrial fatty acid β-oxidation (FAO) has been shown to be a major metabolic pathway in triple-negative breast cancer (TNBC) that can activate Src signaling. Here, we found metabolic reprogramming that increases FAO in ER+ breast cancer as a mechanism of resistance to endocrine therapy. A metabolically relevant, integrated gene signature was derived from transcriptomic, metabolomic, and lipidomic analyses in TNBC cells following inhibition of the FAO rate-limiting enzyme carnitine palmitoyl transferase 1 (CPT1), and this TNBC-derived signature was significantly associated with endocrine resistance in patients with ER+ breast cancer. Molecular, genetic, and metabolomic experiments identified activation of AMPK-FAO-oxidative phosphorylation (OXPHOS) signaling in endocrine-resistant ER+ breast cancer. CPT1 knockdown or treatment with FAO inhibitors in vitro and in vivo significantly enhanced the response of ER+ breast cancer cells to endocrine therapy. Consistent with the previous findings in TNBC, endocrine therapy-induced FAO activated the Src pathway in ER+ breast cancer. Src inhibitors suppressed the growth of endocrine-resistant tumors, and the efficacy could be further enhanced by metabolic priming with CPT1 inhibition. Collectively, this study developed and applied a TNBC-derived signature to reveal that metabolic reprogramming to FAO activates the Src pathway to drive endocrine resistance in ER+ breast cancer.

SIGNIFICANCE

Increased fatty acid oxidation induced by endocrine therapy activates Src signaling to promote endocrine resistance in breast cancer, which can be overcome using clinically approved therapies targeting FAO and Src.

Metabolomic Signatures of Treatment Response in Bladder Cancer

Bladder cancer (BC) stands as one of the most prevalent urological malignancies, with over 500 thousand newly diagnosed cases annually. Treatment decisions in BC depend on factors like the risk of recurrence, the type of tumor, and the stage of the disease. While standard therapeutic approaches encompass transurethral resection of the bladder tumor, radical cystectomy, and chemo- or immunotherapy, these methods exhibit limited efficacy in mitigating the aggressive and recurrent nature of bladder tumors. To overcome this challenge, it is crucial to develop innovative methods for monitoring and predicting treatment responses among patients with BC. Metabolomics is gaining recognition as a promising approach for discovering biomarkers. It has the potential to reveal metabolic disruptions that precisely reflect how BC patients respond to particular treatments, providing a revolutionary method to improve accuracy in monitoring and predicting outcomes. In this article, we present a comprehensive review of studies employing metabolomics approaches to investigate the metabolic responses associated with different treatment modalities for BC. The review encompasses an exploration of various models, samples, and analytical techniques applied in this context. Special emphasis is placed on the reported changes in metabolite levels derived from these studies, highlighting their potential as biomarkers for personalized medicine in BC.

Identification and immune landscape analysis of fatty acid metabolism genes related subtypes of gastric cancer

Fatty acid metabolism (FAM) is associated with prognosis and immune microenvironment remodeling in many tumors. It is currently unknown how FAM affects the immunological microenvironment and prognosis of Gastric cancer (GC). Therefore, the current work aims to categorize GC samples based on the expression status of genes involved in FAM and to identify populations that might benefit from immunotherapy. In total, 50 FAM genes associated with overall survival (OS) were determined through univariate Cox proportional hazard regression analysis by mining the public TCGA and GEO databases. The GSE84437 and TCGA-STAD cohort samples were divided into two clusters using the "NMF" R package. According to the survival curve, patients in Cluster-1 showed considerably longer OS than those in Cluster-2. Patients in Cluster-1 exhibited earlier T stages, more intestinal GCs, and were older. MSI molecular subtypes were mainly distributed in Cluster-1, while GS molecular subtypes were distributed primarily in Cluster-2. There were 227 upregulated and 22 down-regulated genes (logFC > 1 or logFC < - 1, FDR < 0.05) in Cluster-2 compared with Cluster-1. One hub module (edges = 64, nodes = 12) was identified with a module score of 11.636 through Cytoscape plug-in MCODE. KEGG and GO analysis showed that the hub genes were associated with the cell cycle and cell division. Different immune cell infiltrates profile, and immune pathway enrichment existed between the subtypes. In conclusion, the current findings showed that practically all immunological checkpoint and immunoregulatory genes were elevated in patients with Cluster-2 GC, indicating that FAM subtypes may be crucial in GC immunotherapy.

The Physiological and Pathological Role of Acyl-CoA Oxidation

Fatty acid metabolism, including β-oxidation (βOX), plays an important role in human physiology and pathology. βOX is an essential process in the energy metabolism of most human cells. Moreover, βOX is also the source of acetyl-CoA, the substrate for (a) ketone bodies synthesis, (b) cholesterol synthesis, (c) phase II detoxication, (d) protein acetylation, and (d) the synthesis of many other compounds, including N-acetylglutamate-an important regulator of urea synthesis. This review describes the current knowledge on the importance of the mitochondrial and peroxisomal βOX in various organs, including the liver, heart, kidney, lung, gastrointestinal tract, peripheral white blood cells, and other cells. In addition, the diseases associated with a disturbance of fatty acid oxidation (FAO) in the liver, heart, kidney, lung, alimentary tract, and other organs or cells are presented. Special attention was paid to abnormalities of FAO in cancer cells and the diseases caused by mutations in gene-encoding enzymes involved in FAO. Finally, issues related to α- and ω- fatty acid oxidation are discussed.

Mume Fructus (Prunus mume Sieb. et Zucc.) extract accelerates colonic mucosal healing of mice with colitis induced by dextran sulfate sodium through potentiation of cPLA2-mediated lysophosphatidylcholine synthesis

BACKGROUND

Mume Fructus (MF) is the fruit of Prunus mume Sieb. et Zucc, a plant of Rosaceae family. Previous studies demonstrated that MF was capable of ameliorating ulcerative colitis (UC) in mice, its action mechanism needs to be clarified.

PURPOSE

This study deciphered whether and how MF extract accelerates colonic mucosal healing, the therapeutic endpoint of UC.

METHODS

Biochemical, histopathological and qRT-PCR analyses were utilized to define the therapeutic efficacy of MF on dextran sulfate sodium (DSS)-induced colitis in mice. UHPLC-QTOF-MS/MS-based metabolomics technique was adopted to explore the changes of endogenous metabolites associated with UC and responses to MF intervention. qRT-PCR analysis was performed to confirm the molecular pathway in vivo. The effects of MF and lysophosphatidylcholine (LPC) on cell viability, wound healing, proliferation, and migration were examined through a series of in vitro experiments. Moreover, the effects of different subtypes of phospholipase A2 (PLA2) inhibitors on MF-treated colonic epithelial cells were detected by wound healing test and transwell assay.

RESULTS

Orally administered MF could alleviate colitis in mice mainly by accelerating the healing of colonic mucosa. Guided by an unbiased metabolomics screen, we identified LPC synthesis as a major modifying pathway in colitis mice after MF treatment. Notably, MF facilitated the synthesis of LPC by enhancing the expression of PLA2 in colitis mice. Mechanistically, MF and LPC accelerated wound closure by promoting cell migration. Moreover, the promotion of MF on wound healing and migration of colonic epithelial cells was blunted by a cytosolic phospholipase A2 (cPLA2) inhibitor.

CONCLUSION

MF can facilitate colonic mucosal healing of mice with colitis through cPLA2-mediated intestinal LPC synthesis, which may become a novel therapeutic agent of UC.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

Identification of fatty acid metabolism-based molecular subtypes and prognostic signature to predict immune landscape and guide clinical drug treatment in renal clear cell carcinoma

Three subtypes of samples were generated based on genes involved in fatty acid metabolism in The Cancer Genome Atlas (TCGA)-RCC patients using a non-negative matrix factorization (NMF) algorithm. 32 co-expressed modules were identified using WCGNA. We constructed a four-gene signature in our training set using least absolute shrinkage selection operator regression analysis and verified it in our testing and overall sets. A relevant study analysis in clinical trials was conducted, which showed the model had good stability and potential application value for predicting outcomes. We analyzed the immune microenvironment using MCPcounter, CIBERSORT, quanTIseq, TIMER and ESTIMATE algorithms, and the result indicated risk was positively related to T cells, B-lineage, and fibroblasts and negatively correlated with monocytic lineage, myeloid dendritic cells, neutrophils, and endothelial cells, and CPT1B was positively related to T cells, CD8 + T cells, Cytotoxic lymphocytes and NK cells, and negatively correlated with myeloid dendritic cells, fibroblasts, endothelial cells. Tumor mutation burden was positively related to risk score and the expression of CPT1B using the R packages corrplot, circlize. Through the R package pRRophetic, drug sensitivity tests showed that the low-risk score group would benefit more from sunitinib and less from pazopanib, sorafenib, temsirolimus, gemcitabine and doxorubicin than the high-risk score group. We performed the relevant basic assay validation for CPT1B, and the proliferation ability of RCC cells was inhibited after the knockdown of protein expression of CPT1B. In conclusion, we established a four-gene model that can predict outcomes of RCC with potential applications in diagnosis and treatment.

Resveratrol attenuates staphylococcal enterotoxin B-activated immune cell metabolism via upregulation of miR-100 and suppression of mTOR signaling pathway

Acute Respiratory Distress Syndrome (ARDS) is triggered by a variety of insults, such as bacterial and viral infections, including SARS-CoV-2, leading to high mortality. In the murine model of ARDS induced by Staphylococcal enterotoxin-B (SEB), our previous studies showed that while SEB triggered 100% mortality, treatment with Resveratrol (RES) completely prevented such mortality by attenuating inflammation in the lungs. In the current study, we investigated the metabolic profile of SEB-activated immune cells in the lungs following treatment with RES. RES-treated mice had higher expression of miR-100 in the lung mononuclear cells (MNCs), which targeted mTOR, leading to its decreased expression. Also, Single-cell RNA-seq (scRNA seq) unveiled the decreased expression of mTOR in a variety of immune cells in the lungs. There was also an increase in glycolytic and mitochondrial respiration in the cells from SEB + VEH group in comparison with SEB + RES group. Together these data suggested that RES alters the metabolic reprogramming of SEB-activated immune cells, through suppression of mTOR activation and its down- and upstream effects on energy metabolism. Also, miR-100 could serve as novel potential therapeutic molecule in the amelioration of ARDS.

Characterizing treatment resistance in muscle invasive bladder cancer using the chicken egg chorioallantoic membrane patient-derived xenograft model

Background

Non-metastatic muscle invasive urothelial bladder cancer (MIBC) has a poor prognosis and standard of care (SOC) includes neoadjuvant cisplatin-based chemotherapy (NAC) combined with cystectomy. Patients receiving NAC have at best <10% improvement in five-year overall survival compared to cystectomy alone. This major clinical problem underscores gaps in our understanding of resistance mechanisms and a need for reliable pre-clinical models. The chicken embryo chorioallantoic membrane (CAM) represents a rapid, scalable, and cost-effective alternative to immunocompromised mice for establishing patient-derived xenografts (PDX) in vivo. CAM-PDX leverages an easily accessible engraftment scaffold and vascular-rich, immunosuppressed environment for the engraftment of PDX tumors and subsequent functional studies.

Methods

We optimized engraftment conditions for primary MIBC tumors using the CAM-PDX model and tested concordance between cisplatin-based chemotherapy response of patients to matching PDX tumors using tumor growth coupled with immunohistochemistry markers of proliferation and apoptosis. We also tested select kinase inhibitor response on chemotherapy-resistant bladder cancers on the CAM-PDX using tumor growth measurements and immuno-detection of proliferation marker, Ki-67.

Results

Our results show primary, NAC-resistant, MIBC tumors grown on the CAM share histological characteristics along with cisplatin-based chemotherapy resistance observed in the clinic for matched parent human tumor specimens. Patient tumor specimens acquired after chemotherapy treatment (post-NAC) and exhibiting NAC resistance were engrafted successfully on the CAM and displayed decreased tumor growth size and proliferation in response to treatment with a dual EGFR and HER2 inhibitor, but had no significant response to either CDK4/6 or FGFR inhibition.

Conclusions

Our data suggests concordance between cisplatin-based chemotherapy resistance phenotypes in primary patient tumors and CAM-PDX models. Further, proteogenomic informed kinase inhibitor use on MIBC CAM-PDX models suggests a benefit from integration of rapid in vivo testing of novel therapeutics to inform more complex, pre-clinical mouse PDX experiments for more effective clinical trial design aimed at achieving optimal precision medicine for patients with limited treatment options.

The effect of CPT1B gene on lipid metabolism and its polymorphism analysis in Chinese Simmental cattle

Carnitine palmitoyltransferase 1B (CPT1B) is a candidate gene that regulates livestock animal lipid metabolism and encodes the rate-limiting enzyme in fatty acid β-oxidation. To explore the effect of this gene on lipid metabolism in cattle, this study examined CPT1B gene polymorphism in Chinese Simmental cattle and the effect of CPT1B on lipid metabolism. The results showed that the triglyceride content increased significantly with increasing CPT1B gene expression in bovine fetal fibroblasts (BFFs) (p < 0.05), while CPT1B knockout led to decreased CPT1B expression and a downward trend in triglyceride levels. Correlation analysis showed a significant association between the g.119896238 G > C locus and Chinese Simmental cattle backfat thickness (p < 0.05). Backfat thickness was significantly greater in individuals with the GC genotype (0.93 ± 0.67 cm) than in those with the CC genotype (0.84 ± 0.60 cm). The g.119889302 T > C locus was significantly correlated with arachidonic acid content in Chinese Simmental cattle (p < 0.05). The arachidonic acid content in the longissimus muscle was significantly higher in CC genotype beef cattle (0.054 g/100 g) than in those with the other two genotypes (0.046 g/100 g, 0.049 g/100 g). These molecular markers can be effectively used for marker-assisted selection in cattle breeding.

Prediction of the immunological and prognostic value of five signatures related to fatty acid metabolism in patients with cervical cancer

A growing attention has been attached to the role of fatty acid metabolism (FAM) in the development of cancer, and cervical cancer (CC) is still the primary cause of cancer-associated death in women worldwide. Therefore, it is imperative to explore the possible prognostic significance of FAM in CC. In this study, CC samples and corresponding normal samples were acquired from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). Single sample gene set enrichment analysis (ssGSEA) was conducted for calculating FAM-related scores (FAMRs) to screen FAM-related genes (FAMRGs). Two subtypes related to FAM were identified by consistent clustering. Among them, subtype C2 had a poor prognosis, and C1 had a high level of immune cell infiltration, while C2 had a high possibility of immune escape and was insensitive to chemotherapy drugs. Based on the differentially expressed genes (DEGs) in the two subtypes, a 5-gene signature (PLCB4, FBLN5, TSPAN8, CST6, and SERPINB7) was generated by the least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). The model demonstrated a high prognostic accuracy (area under the curve (AUC)>0.7) in multiple cohorts and was one independent prognostic factor for CC patients. Accordingly, FAMRGs can be adopted as a biomarker for the prediction of CC patients' prognosis and help guide the immunotherapy of CC.

Identification of a necroptosis-related prognostic gene signature associated with tumor immune microenvironment in cervical carcinoma and experimental verification

Cervical carcinoma (CC) has been associated with high morbidity, poor prognosis, and high intratumor heterogeneity. Necroptosis is the significant cellular signal pathway in tumors which may overcome tumor cells’ apoptosis resistance. To investigate the relationship between CC and necroptosis, we established a prognostic model based on necroptosis-related genes for predicting the overall survival (OS) of CC patients. The gene expression data and clinical information of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients were obtained from The Cancer Genome Atlas (TCGA). We identified 43 differentially expressed necroptosis-related genes (NRGs) in CESC by examining differential gene expression between CESC tumors and normal tissues, and 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Gene ontology (GO) and KEGG enrichment analysis illustrated that the genes identified were mainly related to cell necrosis, extrinsic apoptosis, Influenza A, I − kappaB kinase/NF − kappaB, NOD − like receptor, and other signaling pathways. Subsequently, least absolute shrinkage and selection operator (LASSO) regression and univariate and multivariate Cox regression analyses were used to screen for NRGs that were correlated with patient prognosis. A prognostic signature that includes CAMK2A, CYBB, IL1A, IL1B, SLC25A5, and TICAM2 was established. Based on the prognostic model, patients were stratified into either the high-risk or low-risk subgroups with distinct survival. Receiver operating characteristic (ROC) curve analysis was used to identify the predictive accuracy of the model. In relation to different clinical variables, stratification analyses were performed to demonstrate the associations between the expression levels of the six identified NRGs and the clinical variables in CESC. Immunohistochemical (IHC) validation experiments explored abnormal expressions of these six NRGs in CESC. We also explored the relationship between risk score of this necroptosis signature and expression levels of some driver genes in TCGA CESC database and Gene Expression Omnibus (GEO) datasets. Significant relationships between the six prognostic NRGs and immune-cell infiltration, chemokines, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoints in CESC were discovered. In conclusion, we successfully constructed and validated a novel NRG signature for predicting the prognosis of CC patients and might also play a crucial role in the progression and immune microenvironment in CC.

Calcium/calmodulin-dependent protein kinase kinase 2 regulates hepatic fuel metabolism

OBJECTIVE

The liver is the primary internal metabolic organ that coordinates whole body energy homeostasis in response to feeding and fasting. Genetic ablation or pharmacological inhibition of calcium/calmodulin-dependent protein kinase kinase 2 (CaMKK2) has been shown to significantly improve hepatic health and peripheral insulin sensitivity upon overnutrition with high fat diet. However, the precise molecular underpinnings that explain this metabolic protection have remained largely undefined.

METHODS

To characterize the role of CaMKK2 in hepatic metabolism, we developed and challenged liver-specific CaMKK2 knockout (CaMKK2LKO) mice with high fat diet and performed glucose and insulin tolerance tests to evaluate peripheral insulin sensitivity. We used a combination of RNA-Sequencing, glucose and fatty acid istotopic tracer studies, a newly developed Seahorse assay for measuring the oxidative capacity of purified peroxisomes, and a degenerate peptide libarary to identify putative CaMKK2 substrates that mechanistically explain the protective effects of hepatic CaMKK2 ablation.

RESULTS

Consistent with previous findings, we show that hepatic CaMKK2 ablation significantly improves indices of peripheral insulin sensitivity. Mechanistically, we found that CaMKK2 phosphorylates and regulates GAPDH to promote glucose metabolism and PEX3 to blunt peroxisomal fatty acid catabolism in the liver.

CONCLUSION

CaMKK2 is a central metabolic fuel sensor in the liver that significantly contributes to whole body systems metabolism.

Probiotic Fermented Feed Alleviates Liver Fat Deposition in Shaoxing Ducks via Modulating Gut Microbiota

The aim of this study was to investigate the effects of different probiotic fermented feed (PFF) on ameliorating liver fat accumulation by modulating the gut microbiota. A total of 216, 120-day-old Shaoxing ducks were divided into three groups, including the control group (basal diet), or the basal diet supplemented with 25 or 35% PFF. The results of the animal experiment showed that supplementation with PFF markedly alleviated the formation of liver and abdominal lipid droplet and decreased the levels of serum triglyceride (TG) in Shaoxing ducks. 16s rDNA showed that PFF could modulate the composition of gut microbiota, in particular, modulating the ratio of Firmicutes to Bacteroidetes. Moreover, PFF restructures the gut microbiome by reducing the abundance of Ruminococcaceae, Lachnospiraceae, and Prevotellaceae in ducks. Additionally, liver transcriptome analysis indicated that the PFF supplementation significantly downregulated the mRNA expression of peroxisome proliferator-activated receptor gamma (PPARG), acyl-CoA desaturase (SCD), DBI, fatty acid synthase (FASN), ELOVL fatty acid elongase 2 (ELOVL2), ELOVL6, and hydroxysteroid 17-beta dehydrogenase (HSD17B12) and upregulated the mRNA expression of CPT1B, which was widely associated with lipid metabolism processes, such as fatty acid elongation, PPAR signaling pathway, and ether lipid metabolism. Correlation analysis indicates that the expression changes of liver metabolism-related genes by PFF are highly correlated with the Ruminococcaceae, Lachnospiraceae, and Prevotellaceae levels. These findings demonstrated that PFF supplementation modulates gut microbial composition to activate liver lipid metabolism-related genes, which results in less lipid deposition in ducks. These findings provide novel insights into the molecular mechanisms of dietary PFF underlying liver fat accumulation by regulating gut microbiota.

A Fatty Acid Metabolism Signature Associated With Clinical Therapy in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma is one of the most common tumors in the urinary system, among which clear cell renal cell carcinoma is the most common subtype with poor prognosis. As one of the tumors closely related to lipid metabolism, the role of fatty acid metabolism in ccRCC was investigated to predict the prognosis and guide treatment strategies. RNA-seq and clinical information of patients with ccRCC and expression microarray of human renal cell carcinoma cell lines were obtained from TCGA and GEO databases. Fatty acid metabolism–related risk signature was established by the univariate Cox regression and LASSO analysis to predict patient prognosis and response to different treatment modalities. Using the fatty acid metabolism risk signature, the risk score for each sample in the TCGA cohort was calculated and divided into high-risk and low-risk groups, with the cutoff point being the median. Patients with higher risk scores had a poorer prognosis than those with lower risk scores. The response of each sample to immunotherapy was predicted from the “TIDE” algorithm, while the sensitivity of each sample to sunitinib was obtained using the “pRRophetic” R package. Patients with lower risk scores had higher expression of PD-L1 and better efficacy for sunitinib than those in the high-risk group and were less likely to develop drug resistance, while patients with high-risk scores had a strong response to the anti-CTLA4 antibody therapy. A nomogram was constructed by independent prognostic factors to predict the 1-, 3-, and 5-year survival. According to the calibration curves, the nomogram had an excellent ability to predict survival for patients with ccRCC. Therefore, the fatty acid metabolism risk signature we established can not only predict the survival of patients with ccRCC but also predict patient response to targeted therapy and immunotherapy to provide optimal treatment strategies for patients.

Lipidomic Profiling Identifies a Novel Lipid Signature Associated with Ethnicity-Specific Disparity of Bladder Cancer

Bladder Cancer (BLCA) is the ninth most frequently diagnosed cancer globally and the sixth most common cancer in the US. African Americans (AA) exhibit half the BLCA incidence compared to European Americans (EA), but they have a 70% higher risk of cancer-related death; unfortunately, this disparity in BLCA mortality remains poorly understood. In this study, we have used an ethnicity-balanced cohort for unbiased lipidomics profiling to study the changes in the lipid fingerprint for AA and EA BLCA tissues collected from similar geographical regions to determine a signature of ethnic-specific alterations. We identified 86 lipids significantly altered between self-reported AA and EA BLCA patients from Augusta University (AU) cohort. The majority of altered lipids belong to phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), ly sophosphatidylcholines (lysoPCs), phosphatidylserines (PSs), and diglycerides (DGs). Interestingly, levels of four lysoPCs (lyso PCs 20:3, lyso PCs 22:1, lyso PCs 22:2, and lyso PCs 26:1) were elevated while, in contrast, the majority of the PCs were reduced in AA BLCA. Significant alterations in long-chain monounsaturated (MonoUN) and polyunsaturated (PolyUN) lipids were also observed between AA and EA BLCA tumor tissues. These first-in-field results implicate ethnic-specific lipid alterations in BLCA.

Comparisons of Forecasting for Survival Outcome for Head and Neck Squamous Cell Carcinoma by using Machine Learning Models based on Multi-omics

Background: Machine learning methods showed excellent predictive ability in a wide range of fields. For the survival of head and neck squamous cell carcinoma (HNSC), its multi-omics influence is crucial. This study attempts to establish a variety of machine learning multi-omics models to predict the survival of HNSC and find the most suitable machine learning prediction method. Methods: The HNSC clinical data and multi-omics data were downloaded from the TCGA database. The important variables were screened by the LASSO algorithm. We used a total of 12 supervised machine learning models to predict the outcome of HNSC survival and compared the results. In vitro qPCR was performed to verify core genes predicted by the random forest algorithm. Results: For omics of HNSC, the results of the twelve models showed that the performance of multi-omics was better than each single-omic alone. Results were presented, which showed that the Bayesian network(BN) model (area under the curve [AUC] 0.8250, F1 score=0.7917) and random forest(RF) model (area under the curve [AUC] 0.8002,F1 score=0.7839) played good prediction performance in HNSC multi-omics data. The results of in vitro qPCR were consistent with the RF algorithm. Conclusion: Machine learning methods could better forecast the survival outcome of HNSC. Meanwhile, this study found that the BN model and the RF model were the most superior. Moreover, the forecast result of multi-omics was better than single-omic alone in HNSC.

Biochemical recurrence related metabolic novel signature associates with immunity and ADT treatment responses in prostate cancer

BACKGROUND

Prostate cancer (PCa) is a unique cancer from a metabolic perspective. Androgen receptor assumes a vital part in normal and malignant prostate cells regarding almost all aspects of cell metabolism, such as glucose, fat, amino acids, nucleotides, and so on.

METHODS

We used The Cancer Genome Atlas database as training set, Memorial Sloan-Kettering Cancer Center cohort as validation set, and Gene Expression Omnibus database (GSE70769) as test set to identify the optimal prognostic signature. We evaluated the signature in terms of biochemical progression-free survival (bPFS), ROC curve, clinicopathological features, independent prognostic indicators, tumor microenvironment, and infiltrating immune cells. Nomogram was built dependent on the results of cox regression analyses. GSEA algorithm was used to evaluate differences in metabolism. The signature's prediction of androgen deprivation therapy (ADT) response was validated based on two groups of basic cytological experiments treat with ADT (GSE143408 and GSE120343) and the transcriptional information of pre-ADT/post-ADT of six local PCa patients.

RESULTS

We finally input four screened genes into the stepwise regression model to construct metabolism-related signature. The signature shows good prediction performance in training set, verification set, and test set. A nomogram based on the PSA, Gleason score, T staging, and the signature risk score could predict 1-, 3-, and 5-year bPFS with the high area under curve values. Based on gene-set enrichment analysis, the characteristics of four genes signature could influence some important metabolic biological processes of PCa and were serendipitously found to be significantly related to androgen response. Subsequently, two cytological experimental data sets and our local patient sequencing data set verified that the signature may be helpful to evaluate the therapeutic response of PCa to ADT.

CONCLUSIONS

Our systematic study definite a metabolism-related gene signature to foresee prognosis of PCa patients which might add to individual prevention and treatment.

Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) comprises the majority (~85%) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Multi-modal omics profiling has been carried out in NSCLC, but no studies have yet reported a unique metabolite-related gene signature and altered metabolic pathways associated with LUAD and LUSC.

METHODS

We integrated transcriptomics and metabolomics to analyze 30 human lung tumors and adjacent noncancerous tissues. Differential co-expression was used to identify modules of metabolites that were altered between normal and tumor.

RESULTS

We identified unique metabolite-related gene signatures specific for LUAD and LUSC and key pathways aberrantly regulated at both transcriptional and metabolic levels. Differential co-expression analysis revealed that loss of coherence between metabolites in tumors is a major characteristic in both LUAD and LUSC. We identified one metabolic onco-module gained in LUAD, characterized by nine metabolites and 57 metabolic genes. Multi-omics integrative analysis revealed a 28 metabolic gene signature associated with poor survival in LUAD, with six metabolite-related genes as individual prognostic markers.

CONCLUSIONS

We demonstrated the clinical utility of this integrated metabolic gene signature in LUAD by using it to guide repurposing of AZD-6482, a PI3Kβ inhibitor which significantly inhibited three genes from the 28-gene signature. Overall, we have integrated metabolomics and transcriptomics analyses to show that LUAD and LUSC have distinct profiles, inferred gene signatures with prognostic value for patient survival, and identified therapeutic targets and repurposed drugs for potential use in NSCLC treatment.

Fatty Acid Synthase Is the Key Regulator of Fatty Acid Metabolism and Is Related to Immunotherapy in Bladder Cancer

Fatty acid metabolism (FAM) genes are potentially useful for predicting prognosis and immunotherapy response in bladder cancer (BC). To examine this, we constructed a prognostic model and identified key FAM genes in BC. Using transcriptional expression profiles and clinical data of BC patients from public datasets and Changhai (CH) hospital, we built and validated a risk-score model based on 13 prognostic FAM genes. Differential gene expression identified fatty acid synthase (FASN) as central to fatty acid metabolism in BC. FASN was differentially expressed between normal and tumor tissue, and was related to survival. In the CH dataset, FASN independently predicted muscle-invasive BC. FASN differential expression was significantly related to immune-cell infiltration and patients with low FASN expression responded better to immune checkpoint inhibitor (ICI) treatment. SREBF1 was predicted as the most significant transcription factor for FASN. Competing endogenous RNA network analysis suggested that lncRNA AC107027.3 may upregulate FASN by competitively binding miR-27A-3p, thereby regulating the immunotherapy response in BC. Dasatinib and temsirolimus are potential FASN-targeting drugs. Our model efficiently predicted prognosis in BC. FASN is central to fatty acid metabolism, and a potential indicator and regulator of ICI treatment.

Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer

Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

Differential Expression Profiles and Bioinformatics Analysis of tRNA-Derived Small RNAs in Muscle-Invasive Bladder Cancer in a Chinese Population

Muscle-invasive bladder cancer (MIBC) leads to a large societal burden. Recently, tRNA-derived small RNAs (tsRNAs), a novel type of noncoding RNA (ncRNAs), have been identified. However, the expression patterns and functions of tsRNAs in MIBC have not yet been identified. Here, RNA sequencing, bioinformatics, and quantitative reverse transcription- polymerase chain reaction (qRT-PCR) were used to screen the expression profiles and predict the potential roles of tsRNAs in MIBC. Of 406 tsRNAs differentially expressed in MIBC tissues, 91 tsRNAs were significantly differentially expressed. Then, four candidate tsRNAs, tiRNA-1:34-Val-CAC-2, tiRNA-1:33-Gly-GCC-1, tRF-1:32-Gly-GCC-1, and tRF-+1:T20-Ser-TGA-1, were selected. Next, a bioinformatics analysis showed the potential target genes and tsRNA–mRNA network. The most significant and meaningful terms of gene ontology were the positive regulation of the phosphate metabolic process, lamellipodium, and protein-cysteine S-acyltransferase activity in the biological process, cellular component, and molecular function, respectively. In addition, the top four pathways were predicted by the Kyoto Encyclopedia of Genes and Genomes database (KEGG). Finally, qRT-PCR demonstrated a similar expression pattern compared to sequencing data for the candidate tsRNAs. In short, we find differential expression profiles and predict that tiRNA-1:33-Gly-GCC-1, tRF-1:32-Gly-GCC-1, and tRF-+1:T20-Ser-TGA-1 are very likely to engage in the pathophysiological process of MIBC via regulating the target genes in the key pathways.

Defining the mammalian coactivation of hepatic 12-h clock and lipid metabolism

The 12-h clock coordinates lipid homeostasis, energy metabolism, and stress rhythms via the transcriptional regulator XBP1. However, the biochemical and physiological bases for integrated control of the 12-h clock and diverse metabolic pathways remain unclear. Here, we show that steroid receptor coactivator SRC-3 coactivates XBP1 transcription and regulates hepatic 12-h cistrome and gene rhythmicity. Mice lacking SRC-3 show abnormal 12-h rhythms in hepatic transcription, metabolic functions, systemic energetics, and rate-limiting lipid metabolic processes, including triglyceride, phospholipid, and cardiolipin pathways. Notably, 12-h clock coactivation is not only preserved, with its cistromic activation priming ahead of the zeitgeber cue of light, but concomitant with rhythmic remodeling in the absence of food. These findings reveal that SRC-3 integrates the mammalian 12-h clock, energy metabolism, and membrane and lipid homeostasis and demonstrates a role for the 12-h clock machinery as an active transcriptional mechanism in anticipating physiological and metabolic energy needs and stresses.

The Chicken Embryo Chorioallantoic Membrane (CAM): A Versatile Tool for the Study of Patient-Derived Xenografts

Patient-derived xenografts represent the gold standard in pre-clinical research models. The chicken embryo chorioallantoic membrane (CAM) is used in functional studies for studying biological processes such as blood vessel development and embryogenesis, biocompatible material testing, and more recently three-dimensional patient-derived xenograft (PDX) tumor modeling. We describe here a detailed method used to readily engraft established mouse PDX and primary patient tumor specimens on the CAM with as little as 25 mg of tissue per embryonated egg.

Myocardial Rev-erb-Mediated Diurnal Metabolic Rhythm and Obesity Paradox

BACKGROUND

The nuclear receptor Rev-erbα/β, a key component of the circadian clock, emerges as a drug target for heart diseases, but the function of cardiac Rev-erb has not been studied in vivo. Circadian disruption is implicated in heart diseases, but it is unknown whether cardiac molecular clock dysfunction is associated with the progression of any naturally occurring human heart diseases. Obesity paradox refers to the seemingly protective role of obesity for heart failure, but the mechanism is unclear.

METHODS

We generated mouse lines with cardiac-specific Rev-erbα/β knockout (KO), characterized cardiac phenotype, conducted multi-omics (RNA-sequencing, chromatin immunoprecipitation sequencing, proteomics, and metabolomics) analyses, and performed dietary and pharmacological rescue experiments to assess the time-of-the-day effects. We compared the temporal pattern of cardiac clock gene expression with the cardiac dilation severity in failing human hearts.

RESULTS

KO mice display progressive dilated cardiomyopathy and lethal heart failure. Inducible ablation of Rev-erbα/β in adult hearts causes similar phenotypes. Impaired fatty acid oxidation in the KO myocardium, in particular, in the light cycle, precedes contractile dysfunctions with a reciprocal overreliance on carbohydrate utilization, in particular, in the dark cycle. Increasing dietary lipid or sugar supply in the dark cycle does not affect cardiac dysfunctions in KO mice. However, obesity coupled with systemic insulin resistance paradoxically ameliorates cardiac dysfunctions in KO mice, associated with rescued expression of lipid oxidation genes only in the light cycle in phase with increased fatty acid availability from adipose lipolysis. Inhibition of glycolysis in the light cycle and lipid oxidation in the dark cycle, but not vice versa, ameliorate cardiac dysfunctions in KO mice. Altered temporal patterns of cardiac Rev-erb gene expression correlate with the cardiac dilation severity in human hearts with dilated cardiomyopathy.

CONCLUSIONS

The study delineates temporal coordination between clock-mediated anticipation and nutrient-induced response in myocardial metabolism at multi-omics levels. The obesity paradox is attributable to increased cardiac lipid supply from adipose lipolysis in the fasting cycle due to systemic insulin resistance and adiposity. Cardiac molecular chronotypes may be involved in human dilated cardiomyopathy. Myocardial bioenergetics downstream of Rev-erb may be a chronotherapy target in treating heart failure and dilated cardiomyopathy.

Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.

Identification of a Novel PPAR Signature for Predicting Prognosis, Immune Microenvironment, and Chemotherapy Response in Bladder Cancer

Background

Mounting evidence has confirmed that peroxisome proliferator-activated receptors (PPARs) played a crucial role in the development and progression of bladder cancer (BLCA). The purpose of this study is to comprehensively investigate the function and prognostic value of PPAR-targeted genes in BLCA.

Methods

The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed for screening prognostic PPAR-targeted genes and constructing the prognostic PPAR signature and then validated by GSE13507 cohort and GSE32894 cohort. A nomogram was constructed to predict the outcomes of BLCA patients in combination with PPAR signature and clinical factors. Gene set enrichment analysis (GSEA) and immune cell infiltration were implemented to explore the molecular characteristics of the signature. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict the chemotherapy responses of the prognostic signature. The candidate small molecule drugs targeting PPAR-targeted genes were screened by the CMAP database.

Results

We constructed and validated the prognostic signature comprising of 4 PPAR-targeted genes (CPT1B, CALR, AHNAK, and FADS2), which was an independent prognostic biomarker in BLCA patients. A nomogram based on the signature and clinical factors was established in the TCGA set, and the calibration plots displayed the excellent predictive capacity. GSEA analysis indicated that PPAR signature was implicated in multiple oncogenic signaling pathways and correlated with tumor immune cell infiltration. Patients in the high-risk groups showed greater sensitivity to chemotherapy than those in the low-risk groups. Moreover, 11 candidate small molecule drugs were identified for the treatment of BLCA.

Conclusion

We constructed and validated a novel PPAR signature, which showed the excellent performance in predicting prognosis and chemotherapy sensitivity of BLCA patients.

Multi-Omics Analysis of Fatty Acid Metabolism in Thyroid Carcinoma

Objective

Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancer and affects a large number of individuals. The pathogenesis of PTC has not been completely elucidated thus far. Metabolic reprogramming is a common feature in tumours. Our previous research revealed the reprogramming of lipid metabolism in PTC. Further studies on lipid metabolism reprogramming may help elucidate the pathogenesis of PTC.

Methods

Clinical samples of PTC and para-tumour tissue were analysed using lipidomic, proteomic, and metabolomic approaches. A multi-omics integrative strategy was adopted to identify the important pathways in PTC. The findings were further confirmed using western blotting, tissue microarray, bioinformatics, and cell migration assays.

Results

Multi-omics data and the results of integrated analysis revealed that the three steps of fatty acid metabolism (hydrolysis, transportation, and oxidation) were significantly enhanced in PTC. Especially, the expression levels of LPL, FATP2, and CPT1A, three key enzymes in the respective steps, were elevated in PTC. Moreover, LPL, FATP2 and CPT1A expression was associated with the TNM stage, lymph node metastasis of PTC. Moreover, high levels of FATP2 and CPT1A contributed to poor prognosis of PTC. In addition, ectopic overexpression of LPL, FATP2 and CPT1A can each promote the migration of thyroid cancer cells.

Conclusions

Our data suggested that enhanced fatty acid metabolism supplied additional energy and substrates for PTC progression. This may help elucidating the underlying mechanism of PTC pathogenesis and identifying the potential therapeutic targets for PTC.

miR-27a Regulates Sheep Adipocyte Differentiation by Targeting CPT1B Gene

Simple Summary

The content of intramuscular fat (IMF) is the main determinant of the nutritional and economic value of sheep meat. Therefore, lipid synthesis in sheep longissimus lumborum (LL) has become an important research focus. MicroRNA-27a (miR-27a) has been shown to play a crucial role in the proliferation and differentiation of adipocyte progenitor cells. In this study, we revealed that miR-27a significantly inhibited the formation of lipid droplets by targeting CPT1B to inhibit genes involved in lipid synthesis including PPAR γ, SCD, LPL, and FABP4. Here, we constructed a miR-27a-CPT1B regulatory network map, which revealed the interaction between miR-27a and CPT1B in lipid synthesis in ovine preadipocytes.

Abstract

MiRNAs are vital regulators and play a major role in cell differentiation, biological development, and disease occurrence. In recent years, many studies have found that miRNAs are involved in the proliferation and differentiation of adipocytes. The objective of this study was to evaluate the effect of miR-27a and its target gene CPT1B on ovine preadipocytes differentiation in Small-tailed Han sheep (Ovis aries). Down-regulation of miR-27a significantly promoted the production of lipid droplets, while overexpression of miR-27a led to a reduction in lipid droplet production. In addition, inhibition of miR-27a led to a significant increase in the expression of genes involved in lipid synthesis, including PPAR γ, SCD, LPL, and FABP4. Target Scan software predicted that CPT1B is a new potential target gene of miR-27a. Further experiments revealed that CPT1B gene expression and protein levels were negatively correlated with miR-27a expression. Overexpression of miR-27a led to a significant decrease in CPT1B mRNA levels and inhibited the accumulation of lipid droplets and vice versa. Moreover, overexpression of CPT1B promoted the synthesis of lipid droplets in ovine preadipocytes. Furthermore, luciferase reporter assays confirmed CPT1B to be a miR-27a direct target gene. This study confirmed that miR-27a increases the expression of genes related to lipid synthesis in ovine preadipocytes by targeting CPT1B, thereby promoting the synthesis of lipid droplets. The results of this study can be used to be exploited in devising novel approaches for improving the IMF content of sheep.

Lipid Alterations in African American Men with Prostate Cancer

African-American (AA) men are more than twice as likely to die of prostate cancer (PCa) than European American (EA) men. Previous in silico analysis revealed enrichment of altered lipid metabolic pathways in pan-cancer AA tumors. Here, we performed global unbiased lipidomics profiling on 48 matched localized PCa and benign adjacent tissues (30 AA, 24 ancestry-verified, and 18 EA, 8 ancestry verified) and quantified 429 lipids belonging to 14 lipid classes. Significant alterations in long chain polyunsaturated lipids were observed between PCa and benign adjacent tissues, low and high Gleason tumors, as well as associated with early biochemical recurrence, both in the entire cohort, and within AA patients. Alterations in cholesteryl esters, and phosphatidyl inositol classes of lipids delineated AA and EA PCa, while the levels of lipids belonging to triglycerides, phosphatidyl glycerol, phosphatidyl choline, phosphatidic acid, and cholesteryl esters distinguished AA and EA PCa patients with biochemical recurrence. These first-in-field results implicate lipid alterations as biological factors for prostate cancer disparities.

ACSL4 Expression Is Associated With CD8+ T Cell Infiltration and Immune Response in Bladder Cancer

Objective

This study aimed to explore the role of ACSL4 in CD8+ T cell tumor infiltration and outcomes of bladder cancer (BLCA) patients after immunotherapy.

Methods

The correlation between ACSL4 expression and tumor infiltration of immune cells was analyzed using the Tumor Immune Estimation Resource database. The prognostic significance of ACSL4 in BLCA was analyzed using Kaplan–Meier curves. Immunohistochemistry was used to detect CD8+ T cell infiltration in tumors with high and low ACSL4 expression obtained from patients at the Fudan University Shanghai Cancer Center. The relationships between immune checkpoint genes and immune response were analyzed using The Cancer Genome Atlas and IMvigor 210 cohorts. The molecular functions, cellular components, and biological processes involving ACSL4 were explored using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment pathway analyses.

Results

The expression level of ACSL4 was significantly correlated with the infiltration of CD8+ T cells in BLCA tumors (r = 0.192, P = 2.22e-04). Elevated ACSL4 was associated with suppressed tumor progression and better outcomes for BLCA patients. The higher expression level of ACSL4 predicted better immunotherapeutic responses and was associated with higher expression levels of core immune checkpoint genes, including CD274, CTLA4, PDCD1, and LAG3, compared with the low ACSL4 expression group.

Conclusion

This study demonstrated for the first time that elevated ACSL4 correlated significantly with CD8+ T cell infiltration and contributed to better immunotherapeutic responses in BLCA patients. Furthermore, ACSL4 serves as a novel biomarker for predicting patient outcomes after immunotherapeutic treatments, which may improve the development of individualized immunotherapy for BLCA.

Development of computational models using omics data for the identification of effective cancer metabolic biomarkers

Identification of novel biomarkers has been an active area of study for the effective diagnosis, prognosis and treatment of cancers. Among various types of cancer biomarkers, metabolic biomarkers, including enzymes, metabolites and metabolic genes, deserve attention as they can serve as a reliable source for diagnosis, prognosis and treatment of cancers. In particular, efforts to identify novel biomarkers have been greatly facilitated by a rapid increase in the volume of multiple omics data generated for a range of cancer cells. These omics data in turn serve as ingredients for developing computational models that can help derive deeper insights into the biology of cancer cells, and identify metabolic biomarkers. In this review, we provide an overview of omics data generated for cancer cells, and discuss recent studies on computational models that were developed using omics data in order to identify effective cancer metabolic biomarkers.

Metabolomic credentialing of murine carcinogen-induced urothelial cancer

Bladder cancer (BCa) is the most common malignancy of the urinary system with increasing incidence, mortality, and limited treatment options. Therefore, it is imperative to validate preclinical models that faithfully represent BCa cellular, molecular, and metabolic heterogeneity to develop new therapeutics. We performed metabolomic profiling of premalignant and non-muscle invasive bladder cancer (NMIBC) that ensued in the chemical carcinogenesis N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) mouse model. We identified the enriched metabolic signatures that associate with premalignant and NMIBC. We found that enrichment of lipid metabolism is the forerunner of carcinogen-induced premalignant and NMIBC lesions. Cross-species analysis revealed the prognostic value of the enzymes associated with carcinogen-induced enriched metabolic in human disease. To date, this is the first study describing the global metabolomic profiles associated with early premalignant and NMIBC and provide evidence that these metabolomic signatures can be used for prognostication of human disease.