Metabolomics and the Multi-Omics View of Cancer

Current status and perspectives in environmental oncology

Cancer stands as a leading global cause of death, with its etiology characterized by complexity and multifaceted factors. Growing research indicates a strong correlation between environmental factors and cancer incidence, underscoring the critical importance of intervening in environmental risk factors to mitigate cancer occurrence. Despite this, specialized research institutions focusing on the intersection of environment and cancer remain scarce, with global investment in cancer prevention significantly trailing behind efforts in diagnosis and treatment. Against the backdrop of rapid global climate change, industrialization, urbanization, aging populations, and the globalization of lifestyles, we proposed the concept of Environmental Oncology (EO) to address these challenges. We discussed the rationale and necessity of developing EO and presented a comprehensive research framework focusing on cancer prevention and treatment. Future EO research will aim to identify cancer causes and implement early prevention strategies using advanced scientific technologies and methods. By emphasizing multidisciplinary collaboration and integrating molecular biology at the micro level, EO will explore the relationship between external and internal environments and cancer. EO will identify potential therapeutic targets by studying the pathways through which environmental exposures lead to carcinogenesis. EO will develop early warning systems and disseminate research findings by collecting big data, employing robust statistical models, and establishing research centers.

Identification of Specific Hemoglobin Adduct Patterns in Users of Different Tobacco/nicotine Products by Nontargeted GC-MS/MS Analysis

Tobacco smoke contains several electrophilic constituents which are capable of forming adducts with nucleophilic sites in DNA and proteins like hemoglobin (Hb) and albumin. New nicotine and tobacco products are discussed as less harmful forms of tobacco use compared to smoking combustible cigarettes (CC) due to reduced exposure to harmful constituents. Hence, the adduct profile in users of various tobacco/nicotine products is expected to differ characteristically. In this article, we present a novel nontargeted screening strategy using GC-MS/MS for Hb adducts based on the analysis of the respective derivatized N-terminal valine adducts after modified Edman degradation. We analyzed blood samples from a clinical study with habitual users of CCs, electronic cigarettes, heated tobacco products (HTPs), oral tobacco, nicotine replacement therapy products and nonusers of any tobacco/nicotine products. Our nontargeted approach revealed significant differences in the Hb adduct profiles of the investigated tobacco/nicotine product user groups. Adduct identification was performed by means of an internal database, retention time estimations based on the theoretical boiling points, as well as in-house synthesized reference compounds. Several chemicals that form adducts with Hb could be identified: methylating and ethylating agents, ethylene oxide, acrylonitrile, acrylamide, glycidamide and 4-hydroxybenzaldehyde. Levels were elevated in smokers compared to all other groups for Hb adducts from methylating agents, ethylene oxide, acrylonitrile, acrylamide and glycidamide. Our approach revealed higher concentrations of Hb adducts formed by ethylation, acrylamide and glycidamide in users of HTPs compared to nonusers. However, concentrations for the latter two were still lower than in smokers. Due to their long half-lives, Hb adducts related to acrylonitrile, acrylamide (glycidamide), and ethylene oxide exposure may be useful for the biochemical verification of subjects̀ compliance in longitudinal and cross-sectional studies with respect to smoking and HTP use/abstinence.

Identification of a Novel Biomarker Panel for Breast Cancer Screening

Breast cancer remains a major public health concern, and early detection is crucial for improving survival rates. Metabolomics offers the potential to develop non-invasive screening and diagnostic tools based on metabolic biomarkers. However, the inherent complexity of metabolomic datasets and the high dimensionality of biomarkers complicates the identification of diagnostically relevant features, with multiple studies demonstrating limited consensus on the specific metabolites involved. Unlike previous studies that rely on singular feature selection techniques such as Partial Least Square (PLS) or LASSO regression, this research combines supervised and unsupervised machine learning methods with random sampling strategies, offering a more robust and interpretable approach to feature selection. This study aimed to identify a parsimonious and robust set of biomarkers for breast cancer diagnosis using metabolomics data. Plasma samples from 185 breast cancer patients and 53 controls (from the Cooperative Human Tissue Network, USA) were analyzed. This study also overcomes the common issue of dataset imbalance by using propensity score matching (PSM), which ensures reliable comparisons between cancer and control groups. We employed Univariate Naïve Bayes, L2-regularized Support Vector Classifier (SVC), Principal Component Analysis (PCA), and feature engineering techniques to refine and select the most informative features. Our best-performing feature set comprised 11 biomarkers, including 9 metabolites (SM(OH) C22:2, SM C18:0, C0, C3OH, C14:2OH, C16:2OH, LysoPC a C18:1, PC aa C36:0 and Asparagine), a metabolite ratio (Kynurenine-to-Tryptophan), and 1 demographic variable (Age), achieving an area under the ROC curve (AUC) of 98%. These results demonstrate the potential for a robust, cost-effective, and non-invasive breast cancer screening and diagnostic tool, offering significant clinical value for early detection and personalized patient management.

Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction

Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.

Role of microRNA-505 during tumor progression and metastasis

Late diagnosis of cancer in advanced stages due to the lack of screening methods is considered as the main cause of poor prognosis and high mortality rate among these patients. Therefore, it is necessary to investigate the molecular tumor biology in order to introduce biomarkers that can be used in cancer screening programs and early diagnosis. MicroRNAs (miRNAs) have key roles in regulation of the cellular pathophysiological processes. Due to the high stability of miRNAs in body fluids, they are widely used as the non-invasive tumor markers. According to the numerous reports about miR-505 deregulation in a wide range of cancers, we investigated the role of miR-505 during tumor progression. It was shown that miR-505 mainly has the tumor suppressor functions through the regulation of signaling pathways, chromatin remodeling, and cellular metabolism. This review has an effective role in introducing miR-505 as a suitable marker for the early cancer diagnosis.

Microbiome and its implications in oncogenesis: a Mendelian randomization perspective

The human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.

Imagining the future of optical microscopy: everything, everywhere, all at once

The optical microscope has revolutionized biology since at least the 17th Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once - from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.

A Systematic Review on Metabolomics Analysis in Hearing Impairment: Is It a Possible Tool in Understanding Auditory Pathologies?

With more than 466 million people affected, hearing loss represents the most common sensory pathology worldwide. Despite its widespread occurrence, much remains to be explored, particularly concerning the intricate pathogenic mechanisms underlying its diverse phenotypes. In this context, metabolomics emerges as a promising approach. Indeed, lying downstream from molecular biology's central dogma, the metabolome reflects both genetic traits and environmental influences. Furthermore, its dynamic nature facilitates well-defined changes during disease states, making metabolomic analysis a unique lens into the mechanisms underpinning various hearing impairment forms. Hence, these investigations may pave the way for improved diagnostic strategies, personalized interventions and targeted treatments, ultimately enhancing the clinical management of affected individuals. In this comprehensive review, we discuss findings from 20 original articles, including human and animal studies. Existing literature highlights specific metabolic changes associated with hearing loss and ototoxicity of certain compounds. Nevertheless, numerous critical issues have emerged from the study of the current state of the art, with the lack of standardization of methods, significant heterogeneity in the studies and often small sample sizes being the main limiting factors for the reliability of these findings. Therefore, these results should serve as a stepping stone for future research aimed at addressing the aforementioned challenges.

Effectiveness of Treatments That Alter Metabolomics in Cancer Patients-A Systematic Review

INTRODUCTION

Cancer is the leading cause of death worldwide, with the most frequent being breast cancer in women, prostate cancer in men and colon cancer in both sexes. The use of metabolomics to find new biomarkers can provide knowledge about possible interventions based on the presence of oncometabolites in different cancer types.

OBJECTIVES

The primary purpose of this review is to analyze the characteristic metabolome of three of the most frequent cancer types. We further want to identify the existence and success rate of metabolomics-based intervention in patients suffering from those cancer types. Our conclusions are based on the analysis of the methodological quality of the studies.

METHODS

We searched for studies that investigated the metabolomic characteristics in patients suffering from breast cancer, prostate cancer or colon cancer in clinical trials. The data were analyzed, as well as the effects of specific interventions based on identified metabolomics and one or more oncometabolites. The used databases were PubMed, Virtual Health Library, Web of Science, EBSCO and Cochrane Library. Only nine studies met the selection criteria. Study bias was analyzed using the Cochrane risk of bias tool. This systematic review protocol was registered at the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023401474).

RESULTS

Only nine studies about clinical trials were included in this review and show a moderate quality of evidence. Metabolomics-based interventions related with disease outcome were conflictive with no or small changes in the metabolic characteristics of the different cancer types.

CONCLUSIONS

This systematic review shows some interesting results related with metabolomics-based interventions and their effects on changes in certain cancer oncometabolites. The small number of studies we identified which fulfilled our inclusion criteria in this systematic review does not allow us to draw definitive conclusions. Nevertheless, some results can be considered as promising although further research is needed. That research must focus not only on the presence of possible oncometabolites but also on possible metabolomics-based interventions and their influence on the outcome in patients suffering from breast cancer, prostate cancer or colon cancer.

High-Throughput Metabolomics Applications in Pathogenesis and Diagnosis of Valvular Heart Disease

High-throughput metabolomics techniques are a useful tool to understand many disease conditions including cardiovascular disease such as valvular heart disease(s) (VHD). VHD involves damage to heart valves, mostly presenting as stenosis, regurgitation or prolapse and can be classified into degenerative, rheumatic, congenital, or prosthetic valve disease. Gaps remain in our understanding of the pathogenesis of the common VHD. It is now fitting to place into perspective the contribution of metabolomics in the mechanism of development, diagnosis, and prognosis of VHD. A structured search for metabolomics studies centred on human VHD was undertaken. Biomarkers associated with the pathogenesis of bicuspid aortic valve disease, mitral valve disease, rheumatic heart disease, and degenerative aortic valve stenosis are reviewed and discussed. In addition, metabolic biomarkers reported to prognosticate patient outcomes of post-valve repair or replacement are highlighted. Finally, we also review the pitfalls and limitations to consider when designing metabolomics studies, especially from a clinician's viewpoint. In the future, reliable and simple metabolic biomarker(s) may supplement the existing diagnostic tools in the early diagnosis of VHD.

Glutamine Starvation Affects Cell Cycle, Oxidative Homeostasis and Metabolism in Colorectal Cancer Cells

Cancer cells adjust their metabolism to meet energy demands. In particular, glutamine addiction represents a distinctive feature of several types of tumors, including colorectal cancer. In this study, four colorectal cancer cell lines (Caco-2, HCT116, HT29 and SW480) were cultured with or without glutamine. The growth and proliferation rate, colony-forming capacity, apoptosis, cell cycle, redox homeostasis and metabolomic analysis were evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide test (MTT), flow cytometry, high-performance liquid chromatography and gas chromatography/mass spectrometry techniques. The results show that glutamine represents an important metabolite for cell growth and that its deprivation reduces the proliferation of colorectal cancer cells. Glutamine depletion induces cell death and cell cycle arrest in the GO/G1 phase by modulating energy metabolism, the amino acid content and antioxidant defenses. Moreover, the combined glutamine starvation with the glycolysis inhibitor 2-deoxy-D-glucose exerted a stronger cytotoxic effect. This study offers a strong rationale for targeting glutamine metabolism alone or in combination with glucose metabolism to achieve a therapeutic benefit in the treatment of colon cancer.

An omics approach to delineating the molecular mechanisms that underlie the biological effects of physical plasma

The use of physical plasma to treat cancer is an emerging field, and interest in its applications in oncology is increasing rapidly. Physical plasma can be used directly by aiming the plasma jet onto cells or tissue, or indirectly, where a plasma-treated solution is applied. A key scientific question is the mechanism by which physical plasma achieves selective killing of cancer over normal cells. Many studies have focused on specific pathways and mechanisms, such as apoptosis and oxidative stress, and the role of redox biology. However, over the past two decades, there has been a rise in omics, the systematic analysis of entire collections of molecules in a biological entity, enabling the discovery of the so-called "unknown unknowns." For example, transcriptomics, epigenomics, proteomics, and metabolomics have helped to uncover molecular mechanisms behind the action of physical plasma, revealing critical pathways beyond those traditionally associated with cancer treatments. This review showcases a selection of omics and then summarizes the insights gained from these studies toward understanding the biological pathways and molecular mechanisms implicated in physical plasma treatment. Omics studies have revealed how reactive species generated by plasma treatment preferentially affect several critical cellular pathways in cancer cells, resulting in epigenetic, transcriptional, and post-translational changes that promote cell death. Finally, this review considers the outlook for omics in uncovering both synergies and antagonisms with other common cancer therapies, as well as in overcoming challenges in the clinical translation of physical plasma.

Divergent Metabolomic Signatures of TGFβ2 and TNFα in the Induction of Retinal Epithelial-Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a dedifferentiation program in which polarized, differentiated epithelial cells lose their cell-cell adhesions and transform into matrix-producing mesenchymal cells. EMT of retinal pigment epithelial (RPE) cells plays a crucial role in many retinal diseases, including age-related macular degeneration, proliferative vitreoretinopathy, and diabetic retinopathy. This dynamic process requires complex metabolic reprogramming to accommodate the demands of this dramatic cellular transformation. Both transforming growth factor-beta 2 (TGFβ2) and tumor necrosis factor-alpha (TNFα) have the capacity to induce EMT in RPE cells; however, little is known about their impact on the RPE metabolome. Untargeted metabolomics using high-resolution mass spectrometry was performed to reveal the metabolomic signatures of cellular and secreted metabolites of primary human fetal RPE cells treated with either TGFβ2 or TNFα for 5 days. A total of 638 metabolites were detected in both samples; 188 were annotated as primary metabolites. Metabolomics profiling showed distinct metabolomic signatures associated with TGFβ2 and TNFα treatment. Enrichment pathway network analysis revealed alterations in the pentose phosphate pathway, galactose metabolism, nucleotide and pyrimidine metabolism, purine metabolism, and arginine and proline metabolism in TNFα-treated cells compared to untreated control cells, whereas TGFβ2 treatment induced perturbations in fatty acid biosynthesis metabolism, the linoleic acid pathway, and the Notch signaling pathway. These results provide a broad metabolic understanding of the bioenergetic rewiring processes governing TGFβ2- and TNFα-dependent induction of EMT. Elucidating the contributions of TGFβ2 and TNFα and their mechanistic differences in promoting EMT of RPE will enable the identification of novel biomarkers for diagnosis, management, and tailored drug development for retinal fibrotic diseases.

Personalized breast cancer onset prediction from lifestyle and health history information

We propose a method to predict when a woman will develop breast cancer (BCa) from her lifestyle and health history features. To address this objective, we use data from the Alberta's Tomorrow Project of 18,288 women to train Individual Survival Distribution (ISD) models to predict an individual's Breast-Cancer-Onset (BCaO) probability curve. We show that our three-step approach-(1) filling missing data with multiple imputations by chained equations, followed by (2) feature selection with the multivariate Cox method, and finally, (3) using MTLR to learn an ISD model-produced the model with the smallest L1-Hinge loss among all calibrated models with comparable C-index. We also identified 7 actionable lifestyle features that a woman can modify and illustrate how this model can predict the quantitative effects of those changes-suggesting how much each will potentially extend her BCa-free time. We anticipate this approach could be used to identify appropriate interventions for individuals with a higher likelihood of developing BCa in their lifetime.

Pathways to Identify Electrophiles In Vivo Using Hemoglobin Adducts: Hydroxypropanoic Acid Valine Adduct and Its Possible Precursors

Analytical methods and tools for the characterization of the human exposome by untargeted mass spectrometry approaches are advancing rapidly. Adductomics methods have been developed for untargeted screening of short-lived electrophiles, in the form of adducts to proteins or DNA, in vivo. The identification of an adduct and its precursor electrophile in the blood is more complex than that of stable chemicals. The present work aims to illustrate procedures for the identification of an adduct to N-terminal valine in hemoglobin detected with adductomics, and pathways for the tracing of its precursor and possible exposure sources. Identification of the adduct proceeded via preparation and characterization of standards of adduct analytes. Possible precursor(s) and exposure sources were investigated by measurements in blood of adduct formation by precursors in vitro and adduct levels in vivo. The adduct was identified as hydroxypropanoic acid valine (HPA-Val) by verification with a synthesized reference. The HPA-Val was measured together with other adducts (from acrylamide, glycidamide, glycidol, and acrylic acid) in human blood (n = 51, schoolchildren). The HPA-Val levels ranged between 6 and 76 pmol/g hemoglobin. The analysis of reference samples from humans and rodents showed that the HPA-Val adduct was observed in all studied samples. No correlation of the HPA-Val level with the other studied adducts was observed in humans, nor was an increase in tobacco smokers observed. A small increase was observed in rodents exposed to glycidol. The formation of the HPA-Val adduct upon incubation of blood with glycidic acid (an epoxide) was shown. The relatively high adduct levels observed in vivo in relation to the measured reactivity of the epoxide, and the fact that the epoxide is not described as naturally occurring, suggest that glycidic acid is not the only precursor of the HPA-Val adduct identified in vivo. Another endogenous electrophile is suspected to contribute to the in vivo HPA-Val adduct level.

Molecular Cluster Mining of Adrenocortical Carcinoma via Multi-Omics Data Analysis Aids Precise Clinical Therapy

Adrenocortical carcinoma (ACC) is a malignancy of the endocrine system. We collected clinical and pathological features, genomic mutations, DNA methylation profiles, and mRNA, lncRNA, microRNA, and somatic mutations in ACC patients from the TCGA, GSE19750, GSE33371, and GSE49278 cohorts. Based on the MOVICS algorithm, the patients were divided into ACC1-3 subtypes by comprehensive multi-omics data analysis. We found that immune-related pathways were more activated, and drug metabolism pathways were enriched in ACC1 subtype patients. Furthermore, ACC1 patients were sensitive to PD-1 immunotherapy and had the lowest sensitivity to chemotherapeutic drugs. Patients with the ACC2 subtype had the worst survival prognosis and the highest tumor-mutation rate. Meanwhile, cell-cycle-related pathways, amino-acid-synthesis pathways, and immunosuppressive cells were enriched in ACC2 patients. Steroid and cholesterol biosynthetic pathways were enriched in patients with the ACC3 subtype. DNA-repair-related pathways were enriched in subtypes ACC2 and ACC3. The sensitivity of the ACC2 subtype to cisplatin, doxorubicin, gemcitabine, and etoposide was better than that of the other two subtypes. For 5-fluorouracil, there was no significant difference in sensitivity to paclitaxel between the three groups. A comprehensive analysis of multi-omics data will provide new clues for the prognosis and treatment of patients with ACC.

Hematogenous metastasis and tumor dormancy as concepts or dogma? The continuum of vessel co-option and angiotropic extravascular migratory metastasis as an alternative

It has been accepted for many years that tumor cells spread via the circulation to distant sites. The latency period between treatment and tumor recurrence has been attributed to dormant cells in distant organs that emerge and grow as metastatic tumors. These processes are accepted with an incomplete demonstration of their existence. Challenging such a well-established accepted paradigm is not easy as history as shown. An alternative or co-existing mechanism involving tumor cell migration along the outside of the vessels and co-option of the blood vessel has been studied for over 25 years and is presented. Several lines of data support this new mechanism of tumor spread and metastatic growth and is termed angiotropic extravascular migratory metastasis or EVMM. This slow migration along the outside of the vessel wall may explain the latency period between treatment and metastatic tumor growth. The reader is asked to be open to this possible new concept in how tumors spread and grow and the reason for this latency period. A full understanding of how tumors spread and grow is fundamental for the targeting of new therapeutics.

Cancer Genetics and Clinical Research

Understanding how complex diseases as well as cancers arise is one of the great challenges of modern medicine [...].

Urinary metabolic modulation in human participants residing in Siachen: a 1H NMR metabolomics approach

The main physiological challenge in high altitude environment is hypoxia which affects the aerobic metabolism reducing the energy supply. These changes may further progress toward extreme environment-related diseases. These are further reflected in changes in small molecular weight metabolites and metabolic pathways. In the present study, metabolic changes due to chronic environmental hypoxia were assessed using 1H NMR metabolomics by analysing the urinary metabolic profile of 70 people at sea level and 40 people at Siachen camp (3700 m) for 1 year. Multivariate statistical analysis was carried out, and PLSDA detected 15 metabolites based on VIP score > 1. ROC analysis detected cis-aconitate, Nicotinamide Mononucleotide, Tyrosine, Choline and Creatinine metabolites with a high range of sensitivity and specificity. Pathway analysis revealed 16 pathways impact > 0.05, and phenylalanine tyrosine and tryptophan biosynthesis was the most prominent altered pathway indicating metabolic remodelling to meet the energy requirements. TCA cycle, Glycine serine and Threonine metabolism, Glutathione metabolism and Cysteine alterations were other metabolic pathways affected during long-term high-altitude hypoxia exposure. Present findings will help unlock a new dimension for the potential application of NMR metabolomics to address extreme environment-related health problems, early detection and developing strategies to combat high altitude hypoxia.

Research Progress of RNA Methylation Modification in Colorectal Cancer

Accumulating evidence indicates that RNA methylation, as the most common modification of mRNA, is of great significance in tumor progression and metastasis. Colorectal cancer is a common malignant tumor of the digestive system that seriously affects the health of middle-aged and elderly people. Although there have been many studies on the biological mechanism of the occurrence and development of colorectal cancer, there are still major deficiencies in the diagnosis and prognosis of colorectal cancer. With the deep study of RNA methylation, it was found that RNA modification is highly related to colorectal cancer tumorigenesis, development and prognosis. Here, we will highlight various RNA chemical modifications including N6-methyladenosine, 5-methylcytosine, N1-methyladenosine, 7-methylguanine, pseudouridine and their modification enzymes followed by summarizing their functions in colorectal cancer.