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Abstract The aim of this study was to explore the intricate relationship between serum metabolomics and lifestyle factors, shedding light on their impact on health in the context of breast cancer risk. Detailed metabolic profiles of 2283 female participants in the Trøndelag Health Study (HUNT study) were obtained through nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). We show that lifestyle-related variables can explain up to 30% of the variance in individual metabolites. Age and obesity were the primary factors affecting the serum metabolic profile, both associated with increased levels of triglyceride-rich very low-density lipoproteins (VLDL) and intermediate-density lipoproteins (IDL), amino acids and glycolysis-related metabolites, and decreased levels of high-density lipoproteins (HDL). Moreover, factors like hormonal changes associated with menstruation and contraceptive use or education level influence the metabolite levels. Participants were clustered into three distinct clusters based on lifestyle-related factors, revealing metabolic similarities between obese and older individuals, despite diverse lifestyle factors, suggesting accelerated metabolic aging with obesity. Our results show that metabolic associations to cancer risk may partly be explained by modifiable lifestyle factors.

IntroductionThe progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers.MethodsWe analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions.ResultsDespite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95).DiscussionIn conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.

BackgroundThe serum metabolome is a potential source of molecular biomarkers associated with the risk of breast cancer. Here we aimed to analyze metabolites present in pre-diagnostic serum samples collected from healthy women participating in the Norwegian Trøndelag Health Study (HUNT2 study) for whom long-term information about developing breast cancer was available.MethodsWomen participating in the HUNT2 study who developed breast cancer within a 15-year follow-up period (BC cases) and age-matched women who stayed breast cancer-free were selected (n=453 case-control pairs). Using a high-resolution mass spectrometry approach 284 compounds were quantitatively analyzed, including 30 amino acids and biogenic amines, hexoses, and 253 lipids (acylcarnitines, glycerides, phosphatidylcholines, sphingolipids, and cholesteryl esters).ResultsAge was a major confounding factor responsible for a large heterogeneity in the dataset, hence age-defined subgroups were analyzed separately. The largest number of metabolites whose serum levels differentiated BC cases and controls (82 compounds) were observed in the subgroup of younger women (64 years old). Moreover, several metabolites could be detected whose serum levels were different between BC cases diagnosed earlier (10 years) after sample collecting, yet these compounds were also correlated with the age of participants. Current results were coherent with the results of the NMR-based metabolomics study performed in the cohort of HUNT2 participants, where increased serum levels of VLDL subfractions were associated with reduced risk of breast cancer in premenopausal women.ConclusionsChanges in metabolite levels detected in pre-diagnostic serum samples, which reflected an impaired lipid and amino acid metabolism, were associated with long-term risk of breast cancer in an age-dependent manner.

Response to radiotherapy (RT) includes tissue toxicity, which may involve inflammatory reactions. We aimed to compare changes in metabolic patterns induced at the systemic level by radiation and inflammation itself. Patients treated with RT due to head and neck cancer and patients with inflammation-related diseases located in the corresponding anatomical regions were selected. PubMed and Web of Science databases were searched from 1 January 2000 to 10 August 2023. Twenty-five relevant studies where serum/plasma metabolic profiles were analyzed using different metabolomics approaches were identified. The studies showed different metabolic patterns of acute and chronic inflammatory diseases, yet changes in metabolites linked to the urea cycle and metabolism of arginine and proline were common features of both conditions. Although the reviewed reports showed only a few specific metabolites common for early RT response and inflammatory diseases, partly due to differences in metabolomics approaches, several common metabolic pathways linked to metabolites affected by radiation and inflammation were revealed. They included pathways involved in energy metabolism (e.g., metabolism of ketone bodies, mitochondrial electron transport chain, Warburg effect, citric acid cycle, urea cycle) and metabolism of certain amino acids (Arg, Pro, Gly, Ser, Met, Ala, Glu) and lipids (glycerolipids, branched-chain fatty acids). However, metabolites common for RT and inflammation-related diseases could show opposite patterns of changes. This could be exemplified by the lysophosphatidylcholine to phosphatidylcholine ratio (LPC/PC) that increased during chronic inflammation and decreased during the early phase of response to RT. One should be aware of dynamic metabolic changes during different phases of response to radiation, which involve increased levels of LPC in later phases. Hence, metabolomics studies that would address molecular features of both types of biological responses using comparable analytical and clinical approaches are needed to unravel the complexities of these phenomena, ultimately contributing to a deeper understanding of their impact on biological systems.

Light-emitting diodes (LEDs) were used for the spring greenhouse cultivation of eggplant (Solanum melongena L.) 'Milar F1' and tomato (S. lycopersicon L.) 'Benito F1' transplants. Seedlings were grown under natural light conditions with the supplemental LED light. A 16-h photoperiod provided plants with a DLI of 12.6 (eggplant) and 9.6 (tomato) mol m2/day. Four supplemental light spectra were tested: L1 (90% red + 10% blue); L2 (80% red + 20% blue); L3 (43% red + 42% blue+15% green) and L4 (56% red + 26% blue + 15% green + 3% UV-A). The PPFD in each LED light treatment was 150 ± 20 µmol/m2.s. Compared to the control plants (without LED lighting), the eggplant transplants had about a 25% larger leaf area and a higher level of total phenol content as well as a higher antiradical scavenging activity under the L1 spectrum. The favourable spectrum for the tomato transplants consisted of red to blue in a ratio of 1 : 1 mixed with a green light (L3) - the leaves were characterised by a higher content of dry matter, soluble sugars, photosynthetic pigments and total phenols; also the radical scavenging activity increased in comparison to the control group. It was shown that the supplemental irradiation of transplants was economically acceptable.

Heat shock factor 1 (HSF1), a key regulator of transcriptional responses to proteotoxic stress, was linked to estrogen (E2) signaling through estrogen receptor α (ERα). We found that an HSF1 deficiency may decrease ERα level, attenuate the mitogenic action of E2, counteract E2-stimulated cell scattering, and reduce adhesion to collagens and cell motility in ER-positive breast cancer cells. The stimulatory effect of E2 on the transcriptome is largely weaker in HSF1-deficient cells, in part due to the higher basal expression of E2-dependent genes, which correlates with the enhanced binding of unliganded ERα to chromatin in such cells. HSF1 and ERα can cooperate directly in E2-stimulated regulation of transcription, and HSF1 potentiates the action of ERα through a mechanism involving chromatin reorganization. Furthermore, HSF1 deficiency may increase the sensitivity to hormonal therapy (4-hydroxytamoxifen) or CDK4/6 inhibitors (palbociclib). Analyses of data from The Cancer Genome Atlas database indicate that HSF1 increases the transcriptome disparity in ER-positive breast cancer and can enhance the genomic action of ERα. Moreover, only in ER-positive cancers an elevated HSF1 level is associated with metastatic disease.

Heat Shock Factor 1 (HSF1), a transcription factor frequently overexpressed in cancer, is activated by proteotoxic agents and participates in the regulation of cellular stress response. To investigate how HSF1 level affects the response to proteotoxic stress, we integrated data from functional genomics analyses performed in MCF7 breast adenocarcinoma cells. Although the general transcriptional response to heat shock was impaired due to HSF1 deficiency (mainly chaperone expression was inhibited), a set of genes was identified, including ATF3 and certain FOS and JUN family members, whose stress-induced activation was stronger and persisted longer than in cells with normal HSF1 levels. These genes were direct HSF1 targets, suggesting a dual (activatory/suppressory) role for HSF1. Moreover, we found that heat shock-induced inflammatory response could be stronger in HSF1-deficient cells. Analyses of The Cancer Genome Atlas data indicated that higher ATF3, FOS, and FOSB expression levels correlated with low HSF1 levels in estrogen receptor-positive breast cancer, reflecting higher heat shock-induced expression of these genes in HSF1-deficient MCF7 cells observed in vitro. However, differences between the analyzed cancer types were noted in the regulation of HSF1-dependent genes, indicating the presence of cell-type-specific mechanisms. Nevertheless, our data indicate the existence of the heat shock-induced network of transcription factors (associated with the activation of TNFα signaling) which includes HSF1. Independent of its chaperone-mediated cytoprotective function, HSF1 may be involved in the regulation of this network but prevents its overactivation in some cells during stress.

Exosomes that are released by T cells are key messengers involved in immune regulation. However, the molecular profiling of these vesicles, which is necessary for understanding their functions, requires their isolation from a very heterogeneous mixture of extracellular vesicles that are present in the human plasma. It has been shown that exosomes that are produced by T cells could be isolated from plasma by immune capture using antibodies that target the CD3 antigen, which is a key component of the TCR complex that is present in all T lymphocytes. Here, we demonstrate that CD3(+) exosomes that are isolated from plasma can be used for high-throughput molecular profiling using proteomics and metabolomics tools. This profiling allowed for the identification of proteins and metabolites that differentiated the CD3(+) from the CD3(−) exosome fractions that were present in the plasma of healthy donors. Importantly, the proteins and metabolites that accumulated in the CD3(+) vesicles reflected the known molecular features of T lymphocytes. Hence, CD3(+) exosomes that are isolated from human plasma by immune capture could serve as a “T cell biopsy”.