Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

Advances in novel biosensors in biomedical applications

Biosensors, devices capable of detecting biomolecules or bioactive substances, have recently become one of the important tools in the fields of bioanalysis and medical diagnostics. A biosensor is an analytical system composed of biosensitive elements and signal-processing elements used to detect various biological and chemical substances. Biomimetic elements are key to biosensor technology and are the components in a sensor that are responsible for identifying the target analyte. The construction methods and working principles of biosensors based on synthetic biomimetic elements, such as DNAzyme, molecular imprinted polymers and aptamers, and their updated applications in biomedical analysis are summarised. Finally, the technical bottlenecks and future development prospects for biomedical analysis are summarised and discussed.

Harnessing the synergistic potential of NK1R antagonists and selective COX-2 inhibitors for simultaneous targeting of TNBC cells and cancer stem cells

Triple-negative breast cancer (TNBC) lacks the expression of oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), rendering it unresponsive to endocrine therapy and HER2 targeted treatments. Though certain chemotherapeutics targeting the cell cycle have shown efficacy to a certain extent, the presence of chemotherapy-resistant cancer stem cells (CSCs) presents a significant challenge in tackling TNBC. Multiple lines of evidence suggest the upregulation of neuropeptide Substance P (SP), its NK-1 receptor (NK1R) and the Cyclooxygenase-2 (COX-2) enzyme in TNBC patients. Upregulation of the SP/NK1R system and COX-2 influences major signalling pathways involved in cell proliferation, growth, survival, angiogenesis, inflammation, metastasis and stem cell activity. The simultaneous activation and crosstalk between the pathways activated by SP/NK1R and COX-2 consequently increase the levels of key regulators of self-renewal pathways in CSCs, promoting stemness. The combination therapy with NK1R antagonists and COX-2 inhibitors can simultaneously target TNBC cells and CSCs, thereby enhancing treatment efficacy and reducing the risk of recurrence and relapse. This review discusses the rationale for combining NK1R antagonists and COX-2 inhibitors for the better management of TNBC and a novel strategy to deliver drug cargo precisely to the tumour site to address the challenges associated with off-target binding.

FABP4-mediated lipid metabolism promotes TNBC progression and breast cancer stem cell activity

Metabolic remodeling is a pivotal feature of cancer, with cancer stem cells frequently showcasing distinctive metabolic behaviors. Nonetheless, understanding the metabolic intricacies of triple-negative breast cancer (TNBC) and breast cancer stem cells (BCSCs) has remained elusive. In this study, we meticulously characterized the metabolic profiles of TNBC and BCSCs and delved into their potential implications for TNBC treatment. Our findings illuminated the robust lipid metabolism activity within TNBC tumors, especially in BCSCs. Furthermore, we discovered that Fabp4, through its mediation of fatty acid uptake, plays a crucial role in regulating TNBC lipid metabolism. Knocking down Fabp4 or inhibiting its activity significantly suppressed TNBC tumor progression in both the MMTV-Wnt1 spontaneous TNBC model and the TNBC patient-derived xenograft model. Mechanistically, Fabp4's influence on TNBC tumor progression was linked to its regulation of mitochondrial stability, the CPT1-mediated fatty acid oxidation process, and ROS production. Notably, in a high-fat diet model, Fabp4 deficiency proved to be a substantial inhibitor of obesity-accelerated TNBC progression. Collectively, these findings shed light on the unique metabolic patterns of TNBC and BCSCs, underscore the biological significance of Fabp4-mediated fatty acid metabolism in governing TNBC progression, and offer a solid theoretical foundation for considering metabolic interventions in breast cancer treatment. SIGNIFICANCE: Triple-negative breast cancer progression and breast cancer stem cell activity can be restricted by targeting a critical regulator of lipid responses, FABP4.

Cancer cell stiffening via CoQ10 and UBIAD1 regulates ECM signaling and ferroptosis in breast cancer

CoQ10 (Coenzyme Q10) is an essential fat-soluble metabolite that plays a key role in cellular metabolism. A less-known function of CoQ10 is whether it may act as a plasma membrane-stabilizing agent and whether this property can affect cancer development and progression. Here, we show that CoQ10 and its biosynthetic enzyme UBIAD1 play a critical role in plasmamembrane mechanical properties that are of interest for breast cancer (BC) progression and treatment. CoQ10 and UBIAD1 increase membrane fluidity leading to increased cell stiffness in BC. Furthermore, CoQ10 and UBIAD1 states impair ECM (extracellular matrix)-mediated oncogenic signaling and reduce ferroptosis resistance in BC settings. Analyses on human patients and mouse models reveal that UBIAD1 loss is associated with BC development and progression and UBIAD1 expression in BC limits CTCs (circulating tumor cells) survival and lung metastasis formation. Overall, this study reveals that CoQ10 and UBIAD1 can be further investigated to develop therapeutic interventions to treat BC patients with poor prognosis.

Targeting SNRNP200-induced splicing dysregulation offers an immunotherapy opportunity for glycolytic triple-negative breast cancer

Metabolic dysregulation is prominent in triple-negative breast cancer (TNBC), yet therapeutic strategies targeting cancer metabolism are limited. Here, utilizing multiomics data from our TNBC cohort (n = 465), we demonstrated widespread splicing deregulation and increased spliceosome abundance in the glycolytic TNBC subtype. We identified SNRNP200 as a crucial mediator of glucose-driven metabolic reprogramming. Mechanistically, glucose induces acetylation at SNRNP200 K1610, preventing its proteasomal degradation. Augmented SNRNP200 then facilitates splicing key metabolic enzyme-encoding genes (GAPDH, ALDOA, and GSS), leading to increased lactic acid and glutathione production. Targeting SNRNP200 with antisense oligonucleotide therapy impedes tumor metabolism and enhances the efficacy of anti-PD-1 therapy by activating intratumoral CD8+ T cells while suppressing regulatory T cells. Clinically, higher SNRNP200 levels indicate an inferior response to immunotherapy in glycolytic TNBCs. Overall, our study revealed the intricate interplay between RNA splicing and metabolic dysregulation, suggesting an innovative combination strategy for immunotherapy in glycolytic TNBCs.

Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis

Deep vein thrombosis (DVT) is a leading cause of morbidity and mortality after trauma. Here, we integrate plasma metabolomics and proteomics to evaluate the metabolic alterations and their function in up to 680 individuals with and without DVT after trauma (pt-DVT). We identify 28 metabolites and 2 clinical parameter clusters associated with pt-DVT. Then, we develop a panel of 9 metabolites (hexadecanedioic acid, pyruvic acid, L-Carnitine, serotonin, PE(P-18:1(11Z)/18:2(9Z,12Z)), 3-Hydroxycapric acid, 5,6-DHET, 3-Methoxybenzenepropanoic acid and pentanenitrile) that can predict pt-DVT with high performance, which can be verified in an independent cohort. Furthermore, the integration analysis of metabolomics and proteomics data indicates that the upregulation of glycolysis/gluconeogenesis-TCA cycle may promote thrombosis by regulating ROS levels in red blood cells, suggesting that interfering with this process might be potential therapeutic strategies for pt-DVT. Together, our study comprehensively delineates the metabolic and hematological dysregulations for pt-DVT, and provides potential biomarkers for early detection.

Bioactive sphingolipids as emerging targets for signal transduction in cancer development

Sphingolipids, crucial components of cellular membranes, play a vital role in maintaining cellular structure and signaling integrity. Disruptions in sphingolipid metabolism are increasingly implicated in cancer development. Key bioactive sphingolipids, such as ceramides, sphingosine-1-phosphate (S1P), ceramide-1-phosphate (C1P), and glycosphingolipids, profoundly impact tumor biology. They influence the behavior of tumor cells, stromal cells, and immune cells, affecting tumor aggressiveness, angiogenesis, immune modulation, and extracellular matrix remodeling. Furthermore, abnormal expression of sphingolipids and their metabolizing enzymes modulates the secretion of tumor-derived extracellular vesicles (TDEs), which are key players in creating an immunosuppressive tumor microenvironment, remodeling the extracellular matrix, and facilitating oncogenic signaling within in situ tumors and distant pre-metastatic niches (PMNs). Understanding the role of sphingolipids in the biogenesis of tumor-derived extracellular vesicles (TDEs) and their bioactive contents can pave the way for new biomarkers in cancer diagnosis and prognosis, ultimately enhancing comprehensive tumor treatment strategies.

New Metabolomic Insights Into Cancer

ABSTRACT

Cancer has been marked by metabolic irregularities that fuel various aggressive activities such as rapid cell proliferation, evasion of the immune system, and spread to distant organs. Therefore, exploiting cancer metabolism for diagnosis, monitoring, or treatment has been extensively studied in the past couple of decades with various molecular and cellular techniques. More recently, investigating cancer diagnostics and treatments through advanced metabolomics has emerged, and these comprehensive approaches provide a holistic understanding of cancer metabolism, which supported the discovery of metabolic targets relevant across multiple cancer types and the development of more effective treatments. This study offers highlights of new knowledge on cancer metabolism enabled by recent metabolomics studies and their potential applications in aiding cancer research and predicting cancer treatment outcomes. Specifically, we discussed the use of advanced metabolomics in cancer metabolism, tumor microenvironment, and cancer immunotherapy studies to provide valuable insights that can shape future research efforts in the dynamic field of cancer metabolism research.

Evolving therapeutics and ensuing cardiotoxicities in triple-negative breast cancer

Defined as scarce expression of hormone receptors and human epidermal growth factor receptor 2, triple-negative breast cancer (TNBC) is labeled as the most heterogeneous subtype of breast cancer with poorest prognosis. Despite rapid advancements in precise subtyping and tailored therapeutics, the ensuing cancer therapy-related cardiovascular toxicity (CTR-CVT) could exert detrimental impacts to TNBC survivors. Nowadays, this interdisciplinary issue is incrementally concerned by cardiologists, oncologists and other pertinent experts, propelling cardio-oncology as a booming field focusing on the whole-course management of cancer patients with potential cardiovascular threats. Here in this review, we initially profile the evolving molecular subtyping and therapeutic landscape of TNBC. Further, we introduce various monitoring approaches of CTR-CVT. In the main body, we elaborate on typical cardiotoxicities ensuing anti-TNBC treatments in detail, ranging from chemotherapy (especially anthracyclines), surgery, anesthetics, radiotherapy to immunotherapy, with future perspectives on promising directions in the era of artificial intelligence and traditional Chinese medicine.

Docetaxel-Encapsulated Catalytic Pt/Au Nanotubes for Synergistic Chemo-Photothermal Therapy of Triple-Negative Breast Cancer

The combination of photothermal therapy with chemotherapy has emerged as a promising therapeutic modality for addressing triple-negative breast cancer (TNBC). This manuscript describes a novel hybrid nanoplatform comprising ultrathin catalytic platinum/gold (Pt/Au) nanotubes encapsulated with docetaxel and phase-change materials (PCMs) for the photoacoustic imaging-guided synergistic chemo-photothermal therapy of TNBC. Upon irradiation of near-infrared laser, the photothermal heating of nanotubes converts solid-state PCM into liquid, triggering the controlled release of the encapsulated docetaxel. The thin Pt layer within nanotubes enhances the nanotube's thermal stability, thus prolonging the photothermal ablation of tumors. Furthermore, platinum effectively mitigates tumor hypoxia by catalyzing the decomposition of hydrogen peroxides to generate oxygen in the tumor microenvironment, thus improving the efficiency of chemotherapy. It is demonstrated that the drug-loaded nanotubes achieve significant tumor inhibition rates of 75.4% in vivo on 4T1 tumor-bearing mice, significantly surpassing control groups. These nanotubes also notably extend survival, attributable to the synergistic effects of prolonged photothermal therapy facilitated by platinum and oxygenation-enhanced chemotherapy. This combination leverages the unique properties of the Pt/Au NTs-DTX/PCM nanoplatform, optimizing therapeutic outcomes. It is envisioned that this nanoplatform may find important applications in managing superficial malignant solid tumors in general.

Application and prospect of organoid technology in breast cancer

Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology.

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.

Causal role of blood metabolites in HER-positive and HER-negative breast cancer: a Mendelian randomization (MR) study

BACKGROUND

Previous studies provide evidence that in vivo metabolites are associated with breast cancer (BC). However, the causal relationship between blood metabolites and BC remains unclear.

METHOD

Comprehensive two-sample Mendelian randomization analysis was conducted to determine the causal association between 1400 publicly available genetic data on metabolic factors and human epidermal growth factor receptor positive (HER+) BC or HER- BC in this study.

RESULT

Epiandrosterone sulfate levels (OR = 1.07, 95% CI = 1.02 ~ 1.10, p = 0.0013), 5alpha-androstan-3beta,17beta-diol monosulfate (2) levels (OR = 1.07, 95% CI = 1.03 ~ 1.12, p = 0.0012), glycohyocholate levels (OR = 0.85, 95% CI = 0.77 ~ 0.93, p = 0.0007) and etiocholanolone glucuronide levels (OR = 1.12, 95% CI = 1.05 ~ 1.20, p = 0.0013) were causally correlated with HER+ BC. 5 metabolites were causally correlated with HER- BC: Vanillic acid glycine levels (OR = 1.14, 95% CI = 1.06 ~ 1.22, p = 0.0003), Thyroxine levels (OR = 1.26, 95% CI = 1.11 ~ 1.44, p = 0.0004), 1-palmitoyl-2-linoleoyl-GPI (16:0/18:2) levels (OR = 0.86, 95% CI = 0.79 ~ 0.94, p = 0.0010), N-acetylphenylalanine levels (OR = 1.12, 95% CI = 1.05 ~ 1.19, p = 0.0007) and Glucose-to-mannose ratio (OR = 1.15, 95% CI = 1.06 ~ 1.24, p = 0.0008). Two common causally related metabolites were identified: Gamma-glutamyl glutamate and X-12849 levels.

CONCLUSIONS

Our study has respectively demonstrated the connection between blood metabolites and HER+ or HER- BC by genetic means, thereby offering opportunities for therapeutic targets.

From Lipid Signatures to Cellular Responses: Unraveling the Complexity of Melanoma and Furthering Its Diagnosis and Treatment

Recent advancements in mass spectrometry have significantly enhanced our understanding of complex lipid profiles, opening new avenues for oncological diagnostics. This review highlights the importance of lipidomics in the comprehension of certain metabolic pathways and its potential for the detection and characterization of various cancers, in particular melanoma. Through detailed case studies, we demonstrate how lipidomic analysis has led to significant breakthroughs in the identification and understanding of cancer types and its potential for detecting unique biomarkers that are instrumental in its diagnosis. Additionally, this review addresses the technical challenges and future perspectives of these methodologies, including their potential expansion and refinement for clinical applications. The discussion underscores the critical role of lipidomic profiling in advancing cancer diagnostics, proposing a new paradigm in how we approach this devastating disease, with particular emphasis on its application in comparative oncology.

A Multiomics, Molecular Atlas of Breast Cancer Survivors

Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched healthy control cohort (N = 100) provides deep molecular phenotyping of breast cancer survivors. In this study, the BCS cohort had significantly higher polygenic risk scores for breast cancer than the control group. Carnitine and hexanoyl carnitine were significantly different. Several bile acid and fatty acid metabolites were significantly dissimilar, most notably the Omega-3 Index (O3I) (significantly lower in BCS). Proteomic and metagenomic analyses identified group and pathway differences, which warrant further investigation. The database built from this study contributes a wealth of data on breast cancer survivorship where there has been a paucity, affording the ability to identify patterns and novel insights that can drive new hypotheses and inform future research. Expansion of this database in the treatment-naïve, newly diagnosed, controlling for treatment confounders, and through the disease progression, can be leveraged to profile and contextualize breast cancer and breast cancer survivorship, potentially leading to the development of new strategies to combat this disease and improve the quality of life for its victims.

Metabolomics in Radiotherapy-Induced Early Adverse Skin Reactions of Breast Cancer Patients

Background

Early adverse skin reactions (EASRs) are common side effects of radiotherapy (RT) that impact the quality of life of breast cancer patients. This study used global metabolomics profiles of breast cancer populations to identify metabolic pathways and biomarkers significantly associated with RT-induced EASRs to identify potential targets for precision interventions.

Methods

We used a frequency-matched study design to identify pre-RT urine samples from 60 female breast cancer patients (30 with high and 30 with low EASRs) for metabolomic analysis by Metabolon Inc. using UPLC-MS/MS and GC-MS. Using MetaboAnalyst, we performed metabolomic data analysis and visualization on 84 candidate metabolites from 478 total compounds. We used the Oncology Nursing Society (ONS) Skin Toxicity Criteria (0-6) for EASRs assessment.

Results

Seven metabolic pathways were significantly associated with RT-induced EASRs, including alanine, aspartate, and glutamate metabolism (p = 0.0028), caffeine metabolism (p = 0.0360), pentose and glucuronate interconversions (p = 0.0028), glycine, serine, and threonine metabolism (p = 0.0360), beta-alanine metabolism (p = 0.0210), pantothenate and CoA biosynthesis (p = 0.0028), and glutathione metabolism (p = 0.0490). The alanine, aspartate, and glutamate metabolic pathway had the lowest false discovery rate (FDR)-adjusted p-value and the highest impact value of 0.60. Thirteen metabolite biomarkers were significantly associated with RT-induced EASRs.

Conclusion

Our data show that the alanine, aspartate, and glutamate metabolism pathways had the highest impact value on RT-induced EASRs. Future larger studies are warranted to validate our findings and facilitate targeted interventions for preventing or mitigating RT-induced EASRs, offering a promising direction for further research and clinical applications.

Biomarkers in the Immuno-oncology Interface of Triple Negative Breast Cancer: A Scoping Review with Perioperative Considerations

PURPOSE OF REVIEW

Identification of biomarkers for immunotherapy treatment in triple negative breast cancer remains crucial for improving outcomes and optimising regimes, particularly in the perioperative setting. There is a need to conduct a scoping review to provide an overview of current research, explore the wider context, and highlight future research considerations in this field.

RECENT FINDINGS

The most commonly assessed biomarkers are PD-L1, TILs and CD8 + cells with correlation to outcomes mainly focused on survival. There is a growing interest in evaluating genetic markers. Conclusions are currently limited by knowledge gaps around contextual factors. Important areas of focus for future research include a greater understanding of complex cellular, genetic and metabolic interactions in the perioperative tumour microenvironment, including patient-specific immune profiles. An important challenge remains elucidating the clinical significance of the immunological effects of interventions at each stage of the perioperative period, including the use of anaesthetic agents.

Plasma Metabolome Signatures to Predict Responsiveness to Neoadjuvant Chemotherapy in Breast Cancer

BACKGROUND

Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data.

METHODS

Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively.

RESULTS

The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance.

CONCLUSION

We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification.

Metabolite correlation permutation after mice acute exposure to PM2.5: Holistic exploration of toxicometabolomics by network analysis

Many environmental toxicants can cause systemic effects, such as fine particulate matter (PM2.5), which can penetrate the respiratory barrier and induce effects in multiple tissues. Although metabolomics has been used to identify biomarkers for PM2.5, its multi-tissue toxicology has not yet been explored holistically. Our objective is to explore PM2.5 induced metabolic alterations and unveil the intra-tissue responses along with inter-tissue communicational effects. In this study, following a single intratracheal instillation of multiple doses (0, 25, and 150 μg as the control, low, and high dose), non-targeted metabolomics was employed to evaluate the metabolic impact of PM2.5 across multiple tissues. PM2.5 induced tissue-specific and dose-dependent disturbances of metabolites and their pathways. The remarkable increase of both intra- and inter-tissue correlations was observed, with emphasis on the metabolism connectivity among lung, spleen, and heart; the tissues' functional specificity has marked their toxic modes. Beyond the inter-status comparison of the metabolite fold-changes, the current correlation network built on intra-status can offer additional insights into how the multiple tissues and their metabolites coordinately change in response to external stimuli such as PM2.5 exposure.

Deciphering metabolic crosstalk in context: lessons from inflammatory diseases

Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.

Comprehensive profiling of lipid metabolic reprogramming expands precision medicine for HCC

BACKGROUND AND AIMS

Liver HCC is the second leading cause of cancer-related deaths worldwide. The heterogeneity of this malignancy is driven by a wide range of genetic alterations, leading to a lack of effective therapeutic options. In this study, we conducted a systematic multi-omics characterization of HCC to uncover its metabolic reprogramming signature.

APPROACH AND RESULTS

Through a comprehensive analysis incorporating transcriptomic, metabolomic, and lipidomic investigations, we identified significant changes in metabolic pathways related to glucose flux, lipid oxidation and degradation, and de novo lipogenesis in HCC. The lipidomic analysis revealed abnormal alterations in glycerol-lipids, phosphatidylcholine, and sphingolipid derivatives. Machine-learning techniques identified a panel of genes associated with lipid metabolism as common biomarkers for HCC across different etiologies. Our findings suggest that targeting phosphatidylcholine with saturated fatty acids and long-chain sphingolipid biosynthesis pathways, particularly by inhibiting lysophosphatidylcholine acyltransferase 1 ( LPCAT1 ) and ceramide synthase 5 ( CERS5 ) as potential therapeutic strategies for HCC in vivo and in vitro. Notably, our data revealed an oncogenic role of CERS5 in promoting tumor progression through lipophagy.

CONCLUSIONS

In conclusion, our study elucidates the metabolic reprogramming nature of lipid metabolism in HCC, identifies prognostic markers and therapeutic targets, and highlights potential metabolism-related targets for therapeutic intervention in HCC.

Metabolome-wide association identifies altered metabolites and metabolic pathways in the serum of patients with cholangiocarcinoma

Background & Aims

Metabolomic and lipidomic analyses provide an opportunity for novel biological insights. Cholangiocarcinoma (CCA) remains a highly lethal cancer with limited response to systemic, targeted, and immunotherapeutic approaches. Using a global metabolomics and lipidomics platform, this study aimed to discover and characterize metabolomic variations and associated pathway derangements in patients with CCA.

Methods

Leveraging a biospecimen collection, including samples from patients with digestive diseases and normal controls, global serum metabolomic and lipidomic profiling was performed on 213 patients with CCA and 98 healthy controls. The CCA cohort of patients included representation of intrahepatic, perihilar, and distal CCA tumours. Metabolome-wide association studies utilizing multivariable linear regression were used to perform case-control comparisons, followed by pathway enrichment analysis, CCA subtype analysis, and disease stage analysis. The impact of biliary obstruction was evaluated by repeating analyses in subsets of patients only with normal bilirubin levels.

Results

Of the 420 metabolites that discriminated patients with CCA from controls, decreased abundance of cysteine-glutathione disulfide was most closely associated with CCA. Additional conjugated bile acid species were found in increased abundance even in the absence of clinically relevant biliary obstruction denoted by elevated serum bilirubin levels. Pathway enrichment analysis also revealed alterations in caffeine metabolism and mitochondrial redox-associated pathways in the serum of patients with CCA.

Conclusions

The presented metabolomic and lipidomic profiling demonstrated multiple alterations in the serum of patients with CCA. These exploratory data highlight novel metabolic pathways in CCA and support future work in therapeutic targeting of these pathways and the development of a precision biomarker panel for diagnosis.

Impact and implications

Cholangiocarcinoma (CCA) is a highly lethal hepatobiliary cancer with limited treatment response, highlighting the need for a better understanding of the disease biology. Using a global metabolomics and lipidomics platform, we characterized distinct changes in the serum of 213 patients with CCA compared with healthy controls. The results of this study elucidate novel metabolic pathways in CCA. These findings benefit stakeholders in both the clinical and research realms by providing a foundation for improved disease diagnostics and identifying novel targets for therapeutic design.

Metabolic landscape of head and neck squamous cell carcinoma informs a novel kynurenine/Siglec-15 axis in immune escape

BACKGROUND

Metabolic reprograming and immune escape are two hallmarks of cancer. However, how metabolic disorders drive immune escape in head and neck squamous cell carcinoma (HNSCC) remains unclear. Therefore, the aim of the present study was to investigate the metabolic landscape of HNSCC and its mechanism of driving immune escape.

METHODS

Analysis of paired tumor tissues and adjacent normal tissues from 69 HNSCC patients was performed using liquid/gas chromatography-mass spectrometry and RNA-sequencing. The tumor-promoting function of kynurenine (Kyn) was explored in vitro and in vivo. The downstream target of Kyn was investigated in CD8+ T cells. The regulation of CD8+ T cells was investigated after Siglec-15 overexpression in vivo. An engineering nanoparticle was established to deliver Siglec-15 small interfering RNA (siS15), and its association with immunotherapy response were investigated. The association between Siglec-15 and CD8+ programmed cell death 1 (PD-1)+ T cells was analyzed in a HNSCC patient cohort.

RESULTS

A total of 178 metabolites showed significant dysregulation in HNSCC, including carbohydrates, lipids and lipid-like molecules, and amino acids. Among these, amino acid metabolism was the most significantly altered, especially Kyn, which promoted tumor proliferation and metastasis. In addition, most immune checkpoint molecules were upregulated in Kyn-high patients based on RNA-sequencing. Furthermore, tumor-derived Kyn was transferred into CD8+ T cells and induced T cell functional exhaustion, and blocking Kyn transporters restored its killing activity. Accroding to the results, mechanistically, Kyn transcriptionally regulated the expression of Siglec-15 via aryl hydrocarbon receptor (AhR), and overexpression of Siglec-15 promoted immune escape by suppressing T cell infiltration and activation. Targeting AhR in vivo reduced Kyn-mediated Siglec-15 expression and promoted intratumoral CD8+ T cell infiltration and killing capacity. Finally, a NH2-modified mesoporous silica nanoparticle was designed to deliver siS15, which restored CD8+ T cell function status and enhanced anti-PD-1 efficacy in tumor-bearing immunocompetent mice. Clinically, Siglec-15 was positively correlated with AhR expression and CD8+PD-1+ T cell infiltration in HNSCC tissues.

CONCLUSIONS

The findings describe the metabolic landscape of HNSCC comprehensively and reveal that the Kyn/Siglec-15 axis may be a novel potential immunometabolism mechanism, providing a promising therapeutic strategy for cancers.

FBXO22 is a potential therapeutic target for recurrent chondrosarcoma

Chondrosarcoma (CHS) is a malignant bone tumor with insensitivity to both radiotherapy and chemotherapy, and a high recurrence rate. However, the latent mechanism of recurrent CHS (Re-CHS) remains elusive. Here, we discovered that FBXO22 was highly expressed in clinical samples of Re-CHS. FBXO22 played a significant role in various cancers. However, the role of FBXO22 in Re-CHS remained unclear. Our research demonstrated that suppressing FBXO22 abated the proliferation and migration of CHS cells and facilitated their apoptosis. In addition, suppressing FBXO22 raised the expression of PD-L1 in Re-CHS. All these findings provide new evidence for using FBXO22 and PD-L1 as combined targets to prevent and treat Re-CHS, which may prove to be a novel strategy for immunotherapy of CHS, especially Re-CHS.

A review of big data technology and its application in cancer care

The development of modern medical devices and information technology has led to a rapid growth in the amount of data available for health protection information, with the concept of medical big data emerging globally, along with significant advances in cancer care relying on data-driven approaches. However, outstanding issues such as fragmented data governance, low-quality data specification, and data lock-in still make sharing challenging. Big data technology provides solutions for managing massive heterogeneous data while combining artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) to better mine the intrinsic connections between data. This paper surveys and organizes recent articles on big data technology and its applications in cancer, dividing them into three different types to outline their primary content and summarize their critical role in assisting cancer care. It then examines the latest research directions in big data technology in cancer and evaluates the current state of development of each type of application. Finally, current challenges and opportunities are discussed, and recommendations are made for the further integration of big data technology into the medical industry in the future.

Epigenetic modulations in triple-negative breast cancer: Therapeutic implications for tumor microenvironment

Triple-negative breast cancer (TNBC) is an aggressive subtype lacking estrogen receptors, progesterone receptors and lacks HER2 overexpression. This absence of critical molecular targets poses significant challenges for conventional therapies. Immunotherapy, remarkably immune checkpoint blockade, offers promise for TNBC treatment, but its efficacy remains limited. Epigenetic dysregulation, including altered DNA methylation, histone modifications, and imbalances in regulators such as BET proteins, plays a crucial role in TNBC development and resistance to treatment. Hypermethylation of tumor suppressor gene promoters and the imbalance of histone methyltransferases such as EZH2 and histone deacetylases (HDACs) profoundly influence tumor cell proliferation, survival, and metastasis. In addition, epigenetic alterations critically shape the tumor microenvironment (TME), including immune cell composition, cytokine signaling, and immune checkpoint expression, ultimately contributing to immune evasion. Targeting these epigenetic mechanisms with specific inhibitors such as EZH2 and HDAC inhibitors in combination with immunotherapy represents a compelling strategy to remodel the TME, potentially overcoming immune evasion and enhancing therapeutic outcomes in TNBC. This review aims to comprehensively elucidate the current understanding of epigenetic modulation in TNBC, its influence on the TME, and the potential of combining epigenetic therapies with immunotherapy to overcome the challenges posed by this aggressive breast cancer subtype.

Building consensus on the application of organoid-based drug sensitivity testing in cancer precision medicine and drug development

Patient-derived organoids (PDOs) have emerged as a promising platform for clinical and translational studies. A strong correlation exists between clinical outcomes and the use of PDOs to predict the efficacy of chemotherapy and/or radiotherapy. To standardize interpretation and enhance scientific communication in the field of cancer precision medicine, we revisit the concept of PDO-based drug sensitivity testing (DST). We present an expert consensus-driven approach for medication selection aimed at predicting patient responses. To further standardize PDO-based DST, we propose guidelines for clarification and characterization. Additionally, we identify several major challenges in clinical prediction when utilizing PDOs.

The colonization of Penicillium oxalicum SL2 on rice root surface increased Pb interception capacity of iron plaque and decreased Pb uptake by roots

The exploration of microbial resources to reduce Pb accumulation in rice attracted great attention. In this study, we found Penicillium oxalicum SL2, a Pb-tolerant strain with good capability of dissolving phosphorus and stabilizing Pb in soil, was able to colonize on the root surface of rice seedlings without additional carbon sources, and promoted the secretion of metabolites related to amino acid metabolism, organic acid metabolism, signal transduction and other pathways in rhizosphere exudates, in which the secretion of oxalate increased by 47.7 %. However, P. oxalicum SL2 increased Fe(II) proportion and Fe availability on the root surface, resulting in iron plaque content decrease. Moreover, by converting root surface Pb from Pb-Fe state to PbC2O4 and Pb-P compounds, P. oxalicum SL2 increased Pb intercept capacity of iron plaque by 118.0 %. Furthermore, P. oxalicum SL2 regulated element distribution on the root surface, and reduced the relative content of Pb on the maturation zone of root tip, which was conducive to reducing Pb uptake by apoplastic pathway and the risk of Pb accumulation in root system. Our findings further revealed the interaction between P. oxalicum SL2 and rice root, providing a theoretical basis for the development and application of microbial agents in Pb-contaminated farmland.

Metabolomics at the tumor microenvironment interface: Decoding cellular conversations

Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.

Multi-omics staging of locally advanced rectal cancer predicts treatment response: a pilot study

Treatment response assessment of rectal cancer patients is a critical component of personalized cancer care and it allows to identify suitable candidates for organ-preserving strategies. This pilot study employed a novel multi-omics approach combining MRI-based radiomic features and untargeted metabolomics to infer treatment response at staging. The metabolic signature highlighted how tumor cell viability is predictively down-regulated, while the response to oxidative stress was up-regulated in responder patients, showing significantly reduced oxoproline values at baseline compared to non-responder patients (p-value < 10-4). Tumors with a high degree of texture homogeneity, as assessed by radiomics, were more likely to achieve a major pathological response (p-value < 10-3). A machine learning classifier was implemented to summarize the multi-omics information and discriminate responders and non-responders. Combining all available radiomic and metabolomic features, the classifier delivered an AUC of 0.864 (± 0.083, p-value < 10-3) with a best-point sensitivity of 90.9% and a specificity of 81.8%. Our results suggest that a multi-omics approach, integrating radiomics and metabolomic data, can enhance the predictive value of standard MRI and could help to avoid unnecessary surgical treatments and their associated long-term complications.

Integrating Machine Learning in Metabolomics: A Path to Enhanced Diagnostics and Data Interpretation

Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation. It also highlights multiomics integration, demonstrating machine learning's potential in elucidating biological phenomena and advancing disease diagnostics. This work contributes significantly to metabolomics by merging it with machine learning, offering innovative solutions to analytical challenges and setting new standards for omics data analysis.

NOX4 promotes tumor progression through the MAPK-MEK1/2-ERK1/2 axis in colorectal cancer

BACKGROUND

Metabolic reprogramming plays a key role in cancer progression and clinical outcomes; however, the patterns and primary regulators of metabolic reprogramming in colorectal cancer (CRC) are not well understood.

AIM

To explore the role of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) in promoting progression of CRC.

METHODS

We evaluated the expression and function of dysregulated and survival-related metabolic genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Consensus clustering was used to cluster CRC based on dysregulated metabolic genes. A prediction model was constructed based on survival-related metabolic genes. Sphere formation, migration, invasion, proliferation, apoptosis and clone formation was used to evaluate the biological function of NOX4 in CRC. mRNA sequencing was utilized to explore the alterations of gene expression NOX4 over-expression tumor cells. In vivo subcutaneous and lung metastasis mouse tumor model was used to explore the effect of NOX4 on tumor growth.

RESULTS

We comprehensively analyzed 3341 metabolic genes in CRC and identified three clusters based on dysregulated metabolic genes. Among these genes, NOX4 was highly expressed in tumor tissues and correlated with worse survival. In vitro, NOX4 overexpression induced clone formation, migration, invasion, and stemness in CRC cells. Furthermore, RNA-sequencing analysis revealed that NOX4 overexpression activated the mitogen-activated protein kinase-MEK1/2-ERK1/2 signaling pathway. Trametinib, a MEK1/2 inhibitor, abolished the NOX4-mediated tumor progression. In vivo, NOX4 overexpression promoted subcutaneous tumor growth and lung metastasis, whereas trametinib treatment can reversed the metastasis.

CONCLUSION

Our study comprehensively analyzed metabolic gene expression and highlighted the importance of NOX4 in promoting CRC metastasis, suggesting that trametinib could be a potential therapeutic drugs of CRC clinical therapy targeting NOX4.

Calcification-associated molecular traits and therapeutic strategies in hormone receptor-positive HER2-negative breast cancer

OBJECTIVE

Mammographic calcifications are a common feature of breast cancer, but their molecular characteristics and treatment implications in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer remain unclear.

METHODS

We retrospectively collected mammography records of an HR+/HER2- breast cancer cohort (n = 316) with matched clinicopathological, genomic, transcriptomic, and metabolomic data. On the basis of mammographic images, we grouped tumors by calcification status into calcification-negative tumors, tumors with probably benign calcifications, tumors with calcification of low-moderate suspicion for maligancy and tumors with calcification of high suspicion for maligancy. We then explored the molecular characteristics associated with each calcification status across multiple dimensions.

RESULTS

Among the different statuses, tumors with probably benign calcifications exhibited elevated hormone receptor immunohistochemical staining scores, estrogen receptor (ER) pathway activation, lipid metabolism, and sensitivity to endocrine therapy. Tumors with calcifications of high suspicion for malignancy had relatively larger tumor sizes, elevated lymph node metastasis incidence, Ki-67 staining scores, genomic instability, cell cycle pathway activation, and may benefit from cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors.

CONCLUSIONS

Our research established links between tumor calcifications and molecular features, thus proposing potential precision treatment strategies for HR+/HER2- breast cancer.

Genetic interactions reveal distinct biological and therapeutic implications in breast cancer

Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.

Metabolic Heterogeneity and Potential Immunotherapeutic Responses Revealed by Single-Cell Transcriptomics of Breast Cancer

BACKGROUND

Breast cancer (BC) exhibits remarkable heterogeneity. However, the transcriptomic heterogeneity of BC at the single-cell level has not been fully elucidated.

METHODS

We acquired BC samples from 14 patients. Single-cell RNA sequencing (scRNA-seq), bioinformatic analyses, along with immunohistochemistry (IHC) and immunofluorescence (IF) assays were carried out.

RESULTS

According to the scRNA-seq results, 10 different cell types were identified. We found that Cancer-Associated Fibroblasts (CAFs) exhibited distinct biological functions and may promote resistance to therapy. Metabolic analysis of tumor cells revealed heterogeneity in glycolysis, gluconeogenesis, and fatty acid synthetase reprogramming, which led to chemotherapy resistance. Furthermore, patients with multiple metastases and progression were predicted to benefit from immunotherapy based on a heterogeneity analysis of T cells and tumor cells.

CONCLUSIONS

Our findings provide a comprehensive understanding of the heterogeneity of BC, provide comprehensive insight into the correlation between cancer metabolism and chemotherapy resistance, and enable the prediction of immunotherapy responses based on T-cell heterogeneity.

Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957-0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610-0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901-0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities

Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches.

High Intensity Focused Ultrasound-Driven Nanomotor for Effective Ferroptosis-Immunotherapy of TNBC

The heterogeneity of triple-negative breast cancers (TNBC) remains challenging for various treatments. Ferroptosis, a recently identified form of cell death resulting from the unrestrained peroxidation of phospholipids, represents a potential vulnerability in TNBC. In this study, a high intensity focused ultrasound (HIFU)-driven nanomotor is developed for effective therapy of TNBC through induction of ferroptosis. Through bioinformatics analysis of typical ferroptosis-associated genes in the FUSCCTNBC dataset, gambogic acid is identified as a promising ferroptosis drug and loaded it into the nanomotor. It is found that the rapid motion of nanomotors propelled by HIFU significantly enhanced tumor accumulation and penetration. More importantly, HIFU not only actuated nanomotors to trigger effective ferroptosis of TNBC cells, but also drove nanomotors to activate ferroptosis-mediated antitumor immunity in primary and metastatic TNBC models, resulting in effective tumor regression and prevention of metastases. Overall, HIFU-driven nanomotors show great potential for ferroptosis-immunotherapy of TNBC.

The molecular subtyping and precision medicine in triple-negative breast cancer---based on Fudan TNBC classification

Triple-negative breast cancer (TNBC) is widely recognized as the most aggressive form of breast cancer, occurring more frequently in younger patients and characterized by high heterogeneity, early distant metastases and poor prognosis. Multiple treatment options have failed to achieve the expected therapeutic effects due to the lack of clear molecular targets. Based on genomics, transcriptomics and metabolomics, the multi-omics analysis further clarifies TNBC subtyping, which provides a greater understanding of tumour heterogeneity and targeted therapy sensitivity. For instance, the luminal androgen receptor subtype (LAR) exhibits responsiveness to anti-AR therapy, and the basal-like immune-suppressed subtype (BLIS) tends to benefit from poly (ADP-ribose) polymerase inhibitors (PARPis) and anti-angiogenic therapy. The efficacy of multi-dimensional combination therapy holds immense importance in guiding personalized and precision medicine for TNBC. This review offers a systematic overview of recent FuDan TNBC molecular subtyping and its role in the instruction of clinical precision therapy.

Role of ferroptosis and ferroptosis-related long non'coding RNA in breast cancer

Ferroptosis, a therapeutic strategy for tumours, is a regulated cell death characterised by the increased accumulation of iron-dependent lipid peroxides (LPO). Tumour-associated long non-coding RNAs (lncRNAs), when combined with traditional anti-cancer medicines or radiotherapy, can improve efficacy and decrease mortality in cancer. Investigating the role of ferroptosis-related lncRNAs may help strategise new therapeutic options for breast cancer (BC). Herein, we briefly discuss the genes and pathways of ferroptosis involved in iron and reactive oxygen species (ROS) metabolism, including the XC-/GSH/GPX4 system, ACSL4/LPCAT3/15-LOX and FSP1/CoQ10/NAD(P)H pathways, and investigate the correlation between ferroptosis and LncRNA in BC to determine possible biomarkers related to ferroptosis.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

The therapeutic effect of wine-processed Corni Fructus on chronic renal failure in rats through the interference with the LPS/IL-1-mediated inhibition of RXR function

ETHNOPHARMACOLOGICAL RELEVANCE

Corni Fructus, derived from the fruit of Cornus officinalis Sieb. et Zucc, is a widely utilized traditional Chinese medicine (TCM) with established efficacy in the treatment of diverse chronic kidney diseases. Crude Corni Fructus (CCF) and wine-processed Corni Fructus (WCF) are the main processed forms of Corni Fructus. Generally, TCM is often used after processing (paozhi). Despite the extensive use of processed TCM, the underlying mechanisms of processing for most TCMs have been unclear so far.

AIM OF THE STUDY

In this study, an integrated strategy combined renal metabolomics with proteomics was established and investigated the potential processing mechanisms of CCF or WCF on chronic renal failure (CRF) models.

MATERIALS AND METHODS

Firstly, the differences in biochemical parameters and pathological histology were compared to evaluate the effects of CCF and WCF on CRF model rats. Then, the tissue differential metabolites and proteins between CCF and WCF on CRF model rats were screened based on metabolomics and proteomics technology. Concurrently, a combined approach of metabolomics and proteomics was employed to investigate the underlying mechanisms associated with these marker metabolic products and proteins.

RESULTS

Compared to the MG group, there were 27 distinct metabolites and 143 different proteins observed in the CCF-treatment group, while the WCF-treatment group exhibited 24 distinct metabolites and 379 different proteins. Further, the integration interactions analysis of the protein and lipid metabolite revealed that both WCF and CCF improved tryptophan degradation and LPS/IL-1-mediated inhibition of RXR function. WCF inhibited RXR function more than CCF via the modulation of LPS/IL-1 in the CRF model. Experimental results were validated by qRT-PCR and western blotting. Notably, the gene expression amount and protein levels of FMO3 and CYP2E1 among 8 genes influenced by WCF were higher compared to CCF.

CONCLUSION

The results of this study provide a theoretical basis for further study of Corni Fructus with different processing techniques in CRF. The findings also offer guidance for investigating the mechanism of action of herbal medicines in diseases employing diverse processing techniques.

Targeting EMSY-mediated methionine metabolism is a potential therapeutic strategy for triple-negative breast cancer

Cancer stem cells (CSCs) are the most intractable subpopulation of triple-negative breast cancer (TNBC) cells, which have been associated with a high risk of relapse and poor prognosis. However, eradication of CSCs continues to be difficult. Here, we integrate the multiomics data of a TNBC cohort (n = 360) to identify vital markers of CSCs. We discover that EMSY, inducing a BRCAness phenotype, is preferentially expressed in breast CSCs, promotes ALDH+ cells enrichment, and is positively correlated with poor relapse-free survival. Mechanistically, EMSY competitively binds to the Jmjc domain, which is critical for KDM5B enzyme activity, to reshape methionine metabolism, and to promote CSC self-renewal and tumorigenesis in an H3K4 methylation-dependent manner. Moreover, EMSY accumulation in TNBC cells sensitizes them to PARP inhibitors against bulk cells and methionine deprivation against CSCs. These findings indicate that clinically relevant eradication of CSCs could be achieved with a strategy that targets CSC-specific vulnerabilities in amino acid metabolism.

From genome to clinic: The power of translational bioinformatics in improving human health

Translational bioinformatics (TBI) has transformed healthcare by providing personalized medicine and tailored treatment options by integrating genomic data and clinical information. In recent years, TBI has bridged the gap between genome and clinical data because of significant advances in informatics like quantum computing and utilizing state-of-the-art technologies. This chapter discusses the power of translational bioinformatics in improving human health, from uncovering disease-causing genes and variations to establishing new therapeutic techniques. We discuss key application areas of bioinformatics in clinical genomics, such as data sources and methods used in translational bioinformatics, the impact of translational bioinformatics on human health, and how machine learning and artificial intelligence are being used to mine vast amounts of data for drug development and precision medicine. We also look at the problems, constraints, and ethical concerns connected with exploiting genomic data and the future of translational bioinformatics and its potential impact on medicine and human health. Ultimately, this chapter emphasizes the great potential of translational bioinformatics to alter healthcare and enhance patient outcomes.

Superbinder based phosphoproteomic landscape revealed PRKCD_pY313 mediates the activation of Src and p38 MAPK to promote TNBC progression

Phosphorylation proteomics is the basis for the study of abnormally activated kinase signaling pathways in breast cancer, which facilitates the discovery of new oncogenic agents and drives the discovery of potential targets for early diagnosis and therapy of breast cancer. In this study, we have explored the aberrantly active kinases in breast cancer development and to elucidate the role of PRKCD_pY313 in triple negative breast cancer (TNBC) progression. We collected 47 pairs of breast cancer and paired far-cancer normal tissues and analyzed phosphorylated tyrosine (pY) peptides by Superbinder resin and further enriched the phosphorylated serine/threonine (pS/pT) peptides using TiO2 columns. We mapped the kinases activity of different subtypes of breast cancer and identified PRKCD_pY313 was upregulated in TNBC cell lines. Gain-of-function assay revealed that PRKCD_pY313 facilitated the proliferation, enhanced invasion, accelerated metastasis, increased the mitochondrial membrane potential and reduced ROS level of TNBC cell lines, while Y313F mutation and low PRKCD_pY313 reversed these effects. Furthermore, PRKCD_pY313 significantly upregulated Src_pY419 and p38_pT180/pY182, while low PRKCD_pY313 and PRKCD_Y313F had opposite effects. Dasatinib significantly inhibited the growth of PRKCD_pY313 overexpression cells, and this effect could be enhanced by Adezmapimod. In nude mice xenograft model, PRKCD_pY313 significantly promoted tumor progression, accompanied by increased levels of Ki-67, Bcl-xl and Vimentin, and decreased levels of Bad, cleaved caspase 3 and ZO1, which was opposite to the trend of Y313F group. Collectively, the heterogeneity of phosphorylation exists in different molecular subtypes of breast cancer. PRKCD_pY313 activates Src and accelerates TNBC progression, which could be inhibited by Dasatinib.

Metabolomics unveils the exacerbating role of arachidonic acid metabolism in atherosclerosis

Atherosclerosis is a complex vascular disorder characterized by the deposition of lipids, inflammatory cascades, and plaque formation in arterial walls. A thorough understanding of its causes and progression is necessary to develop effective diagnostic and therapeutic strategies. Recent breakthroughs in metabolomics have provided valuable insights into the molecular mechanisms and genetic factors involved in atherosclerosis, leading to innovative approaches for preventing and treating the disease. In our study, we analyzed clinical serum samples from both atherosclerosis patients and animal models using laser desorption ionization mass spectrometry. By employing methods such as orthogonal partial least-squares discrimination analysis (OPLS-DA), heatmaps, and volcano plots, we can accurately classify atherosclerosis (AUC = 0.892) and identify key molecules associated with the disease. Specifically, we observed elevated levels of arachidonic acid and its metabolite, leukotriene B4, in atherosclerosis. By inhibiting arachidonic acid and monitoring its downstream metabolites, we discovered the crucial role of this metabolic pathway in regulating atherosclerosis. Metabolomic research provides detailed insights into the metabolic networks involved in atherosclerosis development and reveals the close connection between abnormal metabolism and the disease. These studies offer new possibilities for precise diagnosis, treatment, and monitoring of disease progression, as well as evaluating the effectiveness of therapeutic interventions.

Profiling canine mammary tumors: A potential model for studying human breast cancer

Despite all clinical progress recorded in the last decades, human breast cancer (HBC) remains a major challenge worldwide both in terms of its incidence and its management. Canine mammary tumors (CMTs) share similarities with HBC and represent an alternative model for HBC. The utility of the canine model in studying HBC relies on their common features, include spontaneous development, subtype classification, mutational profile, alterations in gene expression profile, and incidence/prevalence. This review describes the similarities between CMTs and HBC regarding genomic landscape, microRNA expression alteration, methylation, and metabolomic changes occurring during mammary gland carcinogenesis. The primary purpose of this review is to highlight the advantages of using the canine model as a translational animal model for HBC research and to investigate the challenges and limitations of this approach.

Image-guided metabolomics and transcriptomics reveal tumour heterogeneity in luminal A and B human breast cancer beyond glucose tracer uptake

BACKGROUND

Breast cancer is a metabolically heterogeneous disease, and although the concept of heterogeneous cancer metabolism is known, its precise role in human breast cancer is yet to be fully elucidated.

METHODS

We investigated in an explorative approach a cohort of 42 primary mamma carcinoma patients with positron emission tomography/magnetic resonance imaging (PET/MR) prior to surgery, followed by histopathology and molecular diagnosis. From a subset of patients, which showed high metabolic heterogeneity based on tracer uptake and pathology classification, tumour centre and periphery specimen tissue samples were further investigated by a targeted breast cancer gene expression panel and quantitative metabolomics by nuclear magnetic resonance (NMR) spectroscopy. All data were analysed in a combinatory approach.

RESULTS

[18 F]FDG (2-deoxy-2-[fluorine-18]fluoro-d-glucose) tracer uptake confirmed dominance of glucose metabolism in the breast tumour centre, with lower levels in the periphery. Additionally, we observed differences in lipid and proliferation related genes between luminal A and B subtypes in the centre and periphery. Tumour periphery showed elevated acetate levels and enrichment in lipid metabolic pathways genes especially in luminal B. Furthermore, serine was increased in the periphery and higher expression of thymidylate synthase (TYMS) indicated one-carbon metabolism increased in tumour periphery. The overall metabolic activity based on [18 F]FDG uptake of luminal B subtype was higher than that of luminal A and the difference between the periphery and centre increased with tumour grade.

CONCLUSION

Our analysis indicates variations in metabolism among different breast cancer subtypes and sampling locations which details the heterogeneity of the breast tumours. Correlation analysis of [18 F]FDG tracer uptake, transcriptome and tumour metabolites like acetate and serine facilitate the search for new candidates for metabolic tracers and permit distinguishing luminal A and B. This knowledge may help to differentiate subtypes preclinically or to provide patients guide for neoadjuvant therapy and optimised surgical protocols based on individual tumour metabolism.