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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.

The study aimed to investigate late radiation-induced changes in the histology, ultrastructure, and activity of lysosomal enzymes in mouse liver exposed to ionizing radiation. The experiment was conducted on C57BL/6J male mice whose distal part of the liver was exposed occasionally to single doses of radiation (6 MV photons) during targeted heart irradiation; estimated doses delivered to analyzed tissue were 0.025 Gy, 0.25 Gy, 1 Gy, and 2 Gy. Tissues were collected 40 weeks after irradiation. We have observed that late effects of radiation have an adaptive nature and their intensity was dose-dependent. Morphological changes in hepatocytes included an increased number of primary lysosomes and autophagic vacuoles, which were visible in tissues irradiated with 0.25 Gy and higher doses. On the other hand, a significant increase in the activity of lysosomal hydrolases was observed only in tissues exposed to 2 Gy. The etiology of these changes may be multifactorial and result, among others, from unintentional irradiation of the distal part of the liver and/or functional interaction of the liver with an irradiated heart. In conclusion, we confirmed the presence of late dose-dependent ultrastructural and biochemical changes in mouse hepatocytes after liver irradiation in vivo.

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of lung cancer diagnosis in CT-based screening. Thus, we aimed to verify whether the combination of these two techniques, which provides local/morphological and systemic/molecular features of disease at the same time, increases the performance of lung cancer classification models. The collected cohort consists of 1086 patients with radiomic and 246 patients with serum metabolomic evaluations. Different machine learning techniques, i.e., random forest and logistic regression were applied for each omics. Next, model predictions were combined with various integration methods to create a final model. The best single omics models were characterized by an AUC of 83% in radiomics and 60% in serum metabolomics. The model integration only slightly increased the performance of the combined model (AUC equal to 85%), which was not statistically significant. We concluded that radiomics itself has a good ability to discriminate lung cancer from benign lesions. However, additional research is needed to test whether its combination with other molecular assessments would further improve the diagnosis of screening-detected lung nodules.

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.

Abstract Transforming growth factor β (TGFβ) is a major component of tumor‐derived small extracellular vesicles (TEX) in cancer patients. Mechanisms utilized by TGFβ+ TEX to promote tumor growth and pro‐tumor activities in the tumor microenvironment (TME) are largely unknown. TEX produced by head and neck squamous cell carcinoma (HNSCC) cell lines carried TGFβ and angiogenesis‐promoting proteins. TGFβ+ TEX stimulated macrophage chemotaxis without a notable M1/M2 phenotype shift and reprogrammed primary human macrophages to a pro‐angiogenic phenotype characterized by the upregulation of pro‐angiogenic factors and functions. In a murine basement membrane extract plug model, TGFβ+ TEX promoted macrophage infiltration and vascularization (p < 0.001), which was blocked by using the TGFβ ligand trap mRER (p < 0.001). TGFβ+ TEX injected into mice undergoing the 4‐nitroquinoline‐1‐oxide (4‐NQO)‐driven oral carcinogenesis promoted tumor angiogenesis (p < 0.05), infiltration of M2‐like macrophages in the TME (p < 0.05) and ultimately tumor progression (p < 0.05). Inhibition of TGFβ signaling in TEX with mRER ameliorated these pro‐tumor activities. Silencing of TGFβ emerges as a critical step in suppressing pro‐angiogenic functions of TEX in HNSCC.

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.

Abstract Background Ability to adapt to temperature changes trough the Heat Shock Response (HSR) pathways is one of the most fundamental and clinically relevant cellular response systems. Heat Shock (HS) affects the signalling and gene expression responses of the Nuclear Factor κB (NF-κB) transcription factor, a critical regulator of proliferation and inflammation, however, our quantitative understanding of how cells sense and adapt to temperature changes is limited. Methods We used live-cell time-lapse microscopy and mathematical modelling to understand the signalling of the NF-κB system in the human MCF7 breast adenocarcinoma cells in response to pro-inflammatory Interleukin 1β (IL1β) and Tumour Necrosis Factor α (TNFα) cytokines, following exposure to a 37–43 °C range of physiological and clinical temperatures. Results We show that exposure to 43 °C 1 h HS inhibits the immediate NF-κB signalling response to TNFα and IL1β stimulation although uptake of cytokines is not impaired. Within 4 h after HS treatment IL1β-induced NF-κB responses return to normal levels, but the recovery of the TNFα-induced responses is still affected. Using siRNA knock-down of Heat Shock Factor 1 (HSF1) we show that this stimulus-specificity is conferred via the Inhibitory κB kinase (IKK) signalosome where HSF1-dependent feedback regulates TNFα, but not IL1β-mediated IKK recovery post HS. Furthermore, we demonstrate that through the temperature-dependent denaturation and recovery of IKK, TNFα and IL1β-mediated signalling exhibit different temperature sensitivity and adaptation to repeated HS when exposed to a 37–43 °C temperature range. Specifically, IL1β-mediated NF-κB responses are more robust to temperature changes in comparison to those induced by TNFα treatment. Conclusions We demonstrate that the kinetics of the NF-κB system following temperature stress is cytokine specific and exhibit differential adaptation to temperature changes. We propose that this differential temperature sensitivity is mediated via the IKK signalosome, which acts as a bona fide temperature sensor trough the HSR cross-talk. This novel quantitative understanding of NF-κB and HSR interactions is fundamentally important for the potential optimization of therapeutic hyperthermia protocols. Video Abstract

Abstract Background Early detection of treatment failure may improve clinical outcome and overall survival in patients with head and neck cancer after first-line treatment. Circulating cell-free HPV16 DNA (cfHPV16 DNA) was evaluated as a possible complementary marker to radiological assessment of early response in patients with HPV-related oropharyngeal cancer (OPC) after radiotherapy alone or combined with chemotherapy. Methods The study included 66 patients with HPV-related OPC receiving radical radiotherapy alone or in combination with chemotherapy. cfHPV16 DNA was assessed in the blood of all patients before treatment using TaqMan-based qPCR. Subsequent analysis of cfHPV16 DNA was performed 12 weeks after treatment completion, along with radiological assessment of early treatment results. Results Complete (CRR) and incomplete radiological response (IRR) was found in 43 (65%) and 23 (35%) patients respectively. cfHPV16 DNA was present in 5 (28%) patients with IRR, while only in 1 (4%) with CRR. Three of five patients with IRR that were positive for cfHPV16 DNA exhibited histopathologically confirmed local or regional treatment failure, and other two developed distant metastases. None of the patients with negative cfHPV16 DNA presented disease failure. Conclusion The post-treatment assessment of cfHPV16 DNA in patients with HPV-related OPC may be used as a complementary biomarker to conventional imaging-based examinations for early identification of treatment failure.

Different aspects of intra-tumor heterogeneity (ITH), which are associated with the development of cancer and its response to treatment, have postulated prognostic value. Here we searched for potential association between phenotypic ITH analyzed by mass spectrometry imaging (MSI) and prognosis of head and neck cancer. The study involved tissue specimens resected from 77 patients with locally advanced oral squamous cell carcinoma, including 37 patients where matched samples of primary tumor and synchronous lymph node metastases were analyzed. A 3-year follow-up was available for all patients which enabled their separation into two groups: with no evidence of disease (NED, n = 41) and with progressive disease (PD, n = 36). After on-tissue trypsin digestion, peptide maps of all cancer regions were segmented using an unsupervised approach to reveal their intrinsic heterogeneity. We found that intra-tumor similarity of spectra was higher in the PD group and diversity of clusters identified during image segmentation was higher in the NED group, which indicated a higher level of ITH in patients with more favorable outcomes. Signature of molecular components that correlated with long-term outcomes could be associated with proteins involved in the immune functions. Furthermore, a positive correlation between ITH and histopathological lymphocytic host response was observed. Hence, we proposed that a higher level of ITH revealed by MSI in cancers with a better prognosis could reflect the presence of heterotypic components of tumor microenvironment such as infiltrating immune cells enhancing the response to the treatment.

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”.

Lung cancer is the leading cause of cancer-related death worldwide, and a major problem affecting its mortality is the late diagnosis of the majority of cases, where treatment options are limited and overall prognosis is very bad. Currently, a low-dose computed tomography (LD-CT) screening in the high-risk group is the only available diagnostic strategy that could reduce mortality due to this malignancy. However, the LD-CT screening test suffers from a high false positive rate. Hence, complementation of LD-CT examination with blood-based biomarkers is a rational approach to increase efficacy and reduce the cost of early lung cancer screening programs. Several molecular signatures that discriminate between patients with early lung cancer and healthy individuals have been proposed in recent years, which are based on components of serum/plasma metabolome. However, none of these signatures has been validated by independent studies based on material collected during real lung cancer screening. Therefore, the validation of the real diagnostic value of these otherwise promising candidates remains a critical step in this challenging field of cancer diagnostics.

Biological aging is associated with various morphological and functional changes, yet the mechanisms of these phenomena remain unclear in many tissues and organs. Hyperlipidemia is among the factors putatively involved in the aging of the liver and heart. Here, we analyzed morphological, ultrastructural, and biochemical features in adult (7-month-old) and elderly (17-month-old) mice, and then compared age-related features between wild type (C57Bl/6 strain) and ApoE-deficient (transgenic ApoE−/−) animals. Increased numbers of damaged mitochondria, lysosomes, and lipid depositions were observed in the hepatocytes of elderly animals. Importantly, these aging-related changes were significantly stronger in hepatocytes from ApoE-deficient animals. An increased number of damaged mitochondria was observed in the cardiomyocytes of elderly animals. However, the difference between wild type and ApoE-deficient mice was expressed in the larger size of mitochondria detected in the transgenic animals. Moreover, a few aging-related differences were noted between wild type and ApoE-deficient mice at the level of plasma biochemical markers. Levels of cholesterol and HDL increased in the plasma of elderly ApoE−/− mice and were markedly higher than in the plasma of elderly wild type animals. On the other hand, the activity of alanine transaminase (ALT) decreased in the plasma of elderly ApoE−/− mice and was markedly lower than in the plasma of elderly wild type animals.

Extracellular vesicles (EVs) are well-known mediators of the cellular response to different stress factors, yet the exact mechanism of their action remains unclear. Hence, the characterization of their cargo, consisting of proteins, nucleic acids, and different classes of metabolites, helps to elucidate an understanding of their function in stress-related communication. The unexpected diversity and complexity of these vesicles requires the incorporation of multiple technologically advanced approaches in EV-oriented studies. This mini review focuses on the invaluable role of proteomics, especially mass spectrometry-based tools, in the investigation of the role of small EVs in their response to stress. Though relatively few experimental works address this issue to date, the available data indicate that stress conditions would affect the composition of protein cargo of vesicles released by stressed cells, as evidenced by the functional importance of such changes in the context of the response of recipient cells.

Untargeted proteomics analysis of extracellular vesicles (EVs) isolated from human serum or plasma remains a technical challenge due to the contamination of these vesicles with lipoproteins and other abundant serum components. Here we aimed to test a simple method of EV isolation from a small amount of human serum (

Many studies emphasize the influence of the status of spermatozoal nucleus on fertilization, mainly with regard to DNA fragmentation. This study was undertaken to analyze the influence of DNA adducts content in spermatozoa on fertilization during assisted reproduction. Ovarian hyperstimulation, oocyte retrieval and laboratory work-up in 61 IVF (in vitro fertilization) and 118 ICSI (intracytoplasmic sperm injection) first cycles were performed according to the same protocol. Semen analysis was made according to WHO Manual (1999). DNA adducts assay in spermatozoa was performed by 32Ppostlabeling method. In total 331 fertilizable oocytes were obtained during IVF and 659 during ICSI. Both groups differed significantly by sperm count, motility and morphology but not by the concentration of DNA adducts in spermatozoa (0.0306 +/- 0.0217 in IVF versus 0.0373 +/- 0.0321 in ICSI). The fertilization rate during IVF was significantly influenced by sperm count (p=0.0002) and motility (p=0.0037) but not by DNA adducts concentration (p=0.30528), whereas during ICSI was positively influenced by sperm motility (p=0.04669) and negatively by DNA adducts concentration (p=0.00796). DNA adducts concentration in spermatozoa significantly negatively influences fertilization rate during ICSI, but not during IVF.

Many studies emphasize the influence of the status of spermatozoal nucleus on fertilization, mainly with regard to DNA fragmentation. This study was undertaken to analyze the influence of DNA adducts content in spermatozoa on fertilization during assisted reproduction. Ovarian hyperstimulation, oocyte retrieval and laboratory work-up in 61 IVF (in vitro fertilization) and 118 ICSI (intracytoplasmic sperm injection) first cycles were performed according to the same protocol. Semen analysis was made according to WHO Manual (1999). DNA adducts assay in spermatozoa was performed by 32Ppostlabeling method. In total 331 fertilizable oocytes were obtained during IVF and 659 during ICSI. Both groups differed significantly by sperm count, motility and morphology but not by the concentration of DNA adducts in spermatozoa (0.0306 +/- 0.0217 in IVF versus 0.0373 +/- 0.0321 in ICSI). The fertilization rate during IVF was significantly influenced by sperm count (p=0.0002) and motility (p=0.0037) but not by DNA adducts concentration (p=0.30528), whereas during ICSI was positively influenced by sperm motility (p=0.04669) and negatively by DNA adducts concentration (p=0.00796). DNA adducts concentration in spermatozoa significantly negatively influences fertilization rate during ICSI, but not during IVF.

BackgroundNeoadjuvant radiotherapy (neo-RT) is widely used in locally advanced rectal cancer (LARC) as a component of radical treatment. Despite the advantages of neo-RT, which typically improves outcomes in LARC patients, the lack of reliable biomarkers that predict response and monitor the efficacy of therapy, can result in the application of unnecessary aggressive therapy affecting patients’ quality of life. Hence, the search for molecular biomarkers for assessing the radio responsiveness of this cancer represents a relevant issue.MethodsHere, we combined proteomic and metabolomic approaches to identify molecular signatures, which could discriminate LARC tumors with good and poor responses to neo-RT.ResultsThe integration of data on differentially accumulated proteins and metabolites made it possible to identify disrupted metabolic pathways and signaling processes connected with response to irradiation, including ketone bodies synthesis and degradation, purine metabolism, energy metabolism, degradation of fatty acid, amino acid metabolism, and focal adhesion. Moreover, we proposed multi-component panels of proteins and metabolites which could serve as a solid base to develop biomarkers for monitoring and predicting the efficacy of preoperative RT in rectal cancer patients.ConclusionWe proved that an integrated multi-omic approach presents a valid look at the analysis of the global response to cancer treatment from the perspective of metabolomic reprogramming.

Abstract Molecular profiling of small extracellular vesicles (sEV) isolated from plasma of cancer patients emerges as promising strategy for biomarkers discovery. We investigated the proteomic profiles of sEV immunoselected using anti‐CSPG4 antibodies from 15 melanoma patients’ plasma. The proteomes of sEV separated into melanoma cell‐derived (MTEX) and non‐malignant cell‐derived (NMTEX) were compared using high‐resolution mass spectrometry. Paired analysis identified the MTEX‐associated profile of 16 proteins that discriminated MTEX from NMETEX. We also identified the MTEX profile that discriminated between seven patients with no evidence of melanoma (NED) after therapy and eight with progressive disease (PD). Among 75 MTEX proteins overexpressed in PD patients, PDCD6IP (ALIX) had the highest discriminating value, while CNTN1 (contactin‐1) was upregulated only in MTEX of NED patients. This is the first report documenting that proteomes of tumour‐derived sEV in patients’ plasma discriminate cancer from non‐cancer and identify proteins with potential to serve as prognostic biomarkers in melanoma.

Abstract Background The cellular response to ionizing radiation involves activation of p53-dependent pathways and activation of the atypical NF-κB pathway. The crosstalk between these two transcriptional networks include (co)regulation of common gene targets. Here we looked for novel genes potentially (co)regulated by p53 and NF-κB using integrative genomics screening in human osteosarcoma U2-OS cells irradiated with a high dose (4 and 10 Gy). Radiation-induced expression in cells with silenced TP53 or RELA (coding the p65 NF-κB subunit) genes was analyzed by RNA-Seq while radiation-enhanced binding of p53 and RelA in putative regulatory regions was analyzed by ChIP-Seq, then selected candidates were validated by qPCR. Results We identified a subset of radiation-modulated genes whose expression was affected by silencing of both TP53 and RELA, and a subset of radiation-upregulated genes where radiation stimulated binding of both p53 and RelA. For three genes, namely IL4I1, SERPINE1, and CDKN1A, an antagonistic effect of the TP53 and RELA silencing was consistent with radiation-enhanced binding of both p53 and RelA. This suggested the possibility of a direct antagonistic (co)regulation by both factors: activation by NF-κB and inhibition by p53 of IL4I1, and activation by p53 and inhibition by NF-κB of CDKN1A and SERPINE1. On the other hand, radiation-enhanced binding of both p53 and RelA was observed in a putative regulatory region of the RRAD gene whose expression was downregulated both by TP53 and RELA silencing, which suggested a possibility of direct (co)activation by both factors. Conclusions Four new candidates for genes directly co-regulated by NF-κB and p53 were revealed.

Human papillomavirus (HPV) is an etiologic factor in head and neck squamous cell carcinoma (HNSCC). HPV(+) cancers respond favorably to therapy potentially due to more robust anti-tumor immune responses. We hypothesized that tumor-derived exosomes (TEX) produced by HPV(+) or HPV(-) HNSCCs differentially modulate anti-tumor immune responses. Proteomes of exosomes from HPV(+) and HPV(-) HNSCC cell lines were compared in search for proteins putatively involved in the communication with immune system. TEX were isolated from supernatants of HPV(+) (SCC-2, SCC-47, and SCC-90) or HPV(-) (PCI-13 and PCI-30) cells by size exclusion chromatography. A comparison of proteome profiles was performed by high-resolution mass spectrometry. The presence and biological activity of selected immunoregulatory proteins were validated by flow cytometry and co-incubation assays. Exosomes produced by SCC-90 and PCI-30 cells contained 711 proteins, including 80 proteins specific for HPV(+) exosomes and 77 specific for HPV(-) exosomes, associated with similar GO terms such as regulation of cell growth, metabolism, communication, and cellular signaling. Search for proteins localized in the membrane and involved in immune regulation identified a few proteins detected specifically in HPV(+) or HPV(-) exosomes. Only HPV(+) exosomes were enriched in immune effector cell-related CD47 and CD276 antigens; only HPV(-) exosomes contained tumor-protective/growth-promoting antigens, MUC-1 and HLA-DA. Flow cytometry and Western blots confirmed the reciprocal presence/paucity of these proteins in a whole panel of tumor cells and corresponding exosomes. The differential content of protein cargos in HPV(+) and HPV(-) exosomes might contribute to the disparity in immune responses that characterize HPV(+) and HPV(-) HNSCC.

The molecular etiology of keratoconus (KC), a pathological condition of the human cornea, remains unclear. The aim of this work was to perform profiling of metabolites and identification of features discriminating this pathology from the normal cornea. The combination of gas chromatography and mass spectrometry (GC/MS) techniques has been applied for profiling and identification of metabolites in corneal buttons from 6 healthy controls and 7 KC patients. An untargeted GC/MS-based approach allowed the detection of 377 compounds, including 46 identified unique metabolites, whose levels enabled the separation of compared groups of samples in unsupervised hierarchical cluster analysis. There were 13 identified metabolites whose levels differentiated between groups of samples. Downregulation of several carboxylic acids, fatty acids, and steroids was observed in KC when compared to the normal cornea. Metabolic pathways associated with compounds that discriminated both groups were involved in energy production, lipid metabolism, and amino acid metabolism. An observed signature may reflect cellular processes involved in the development of KC pathology, including oxidative stress and inflammation.

Anticancer treatment induces systemic molecular changes that could be detected at the level of biofluids. Understanding how human metabolism is influenced by these treatments is crucial to predict the individual response and adjust personalized therapies. Here, we aimed to compare profiles of metabolites in serum of head and neck cancer patients treated with concurrent chemo-radiotherapy, radiotherapy alone, or induction chemotherapy. Serum samples were analyzed by a targeted quantitative approach using combined direct flow injection and liquid chromatography coupled to tandem mass spectrometry, which allowed simultaneous quantification of 149 metabolites. There were 45 metabolites whose levels were significantly changed between pretreatment and within- or post-treatment serum samples, including 38 phospholipids. Concurrent chemo-radiotherapy induced faster and stronger effects than radiotherapy alone. On the other hand, chemotherapy alone did not result in significant changes. The decreased level of total phospholipids was the most apparent effect observed during the first step of the treatment. This corresponded to the loss of patients’ body mass, yet no correlation between both parameters was observed for individual patients. We concluded that different molecular changes were measured at the level of serum metabolome in response to different treatment modalities.

Exosomes, the smallest subset of extracellular vesicles (EVs), have recently attracted much attention in the scientific community. Their involvement in intercellular communication and molecular reprogramming of different cell types created a demand for a stringent characterization of the proteome which exosomes carry and deliver to recipient cells. Mass spectrometry (MS) has been extensively used for exosome protein profiling. Unfortunately, no standards have been established for exosome isolation and their preparation for MS, leading to accumulation of artefactual data. These include the presence of high-abundance exosome-contaminating serum proteins in culture media which mask low-abundance exosome-specific components, isolation methods that fail to yield "pure" vesicles or variability in protein solubilization protocols. There is an unmet need for the development of standards for exosome generation, harvesting, and isolation from cellular supernatants and for optimization of protein extraction methods before proteomics analysis by MS. In this communication, we illustrate the existing problems in this field and provide a set of recommendations that are expected to harmonize exosome processing for MS and provide the faithful picture of the proteomes carried by exosomes. The recommended workflow for effective and specific identification of proteins in exosomes released by the low number of cells involves culturing cells in medium with a reduced concentration of exosome-depleted serum, purification of exosomes by size-exclusion chromatography, a combination of different protein extraction method and removal of serum-derived proteins from the final dataset using an appropriate sample of cell-unexposed medium as a control. Application of this method allowed detection of >250 vesicle-specific proteins in exosomes from 10 mL of culture medium.

Partial body irradiation during cancer radiotherapy (RT) induces a response of irradiated tissues that could be observed at the level of serum proteome. Here we aimed to characterize the response to RT in group of patients treated because of prostate cancer. Five consecutive blood samples were collected before, during, and after the end of RT in a group of 126 patients who received definitive treatment with a maximum dose of 76 Gy. Serum peptidome, which was profiled in the 2000–16,000 Da range using MALDI-MS. Serum proteins were identified and quantified using the shotgun LC-MS/MS approach. The majority of changes in serum peptidome were detected between pre-treatment samples and samples collected after 3–4 weeks of RT (~25% of registered peptides changed their abundances significantly), yet the intensity of observed changes was not correlated significantly with the degree of acute radiation toxicity or the volume of irradiated tissues. Furthermore, there were a few serum proteins identified, the abundances of which were different in pre-RT and post-RT samples, including immunity and inflammation-related factors. Observed effects were apparently weaker than in comparable groups of head and neck cancer patients in spite of similar radiation doses and volumes of irradiated tissues in both groups. We concluded that changes observed at the level of serum proteome were low for this cohort of prostate cancer patients, although the specific components involved are associated with immunity and inflammation, and reflect the characteristic acute response of the human body to radiation.

Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses. In this paper we present an efficient algorithm for Gaussian mixture modeling of proteomic mass spectra of different types (e.g., MALDI-ToF profiling, MALDI-IMS). The main idea is automated partitioning of protein mass spectral signal into fragments. The obtained fragments are separately decomposed into Gaussian mixture models. The parameters of the mixture models of fragments are then aggregated to form the mixture model of the whole spectrum. We compare the elaborated algorithm to existing algorithms for peak detection and we demonstrate improvements of peak detection efficiency obtained by using Gaussian mixture modeling. We also show applications of the elaborated algorithm to real proteomic datasets of low and high resolution.

Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

Formalin-fixed paraffin-embedded (FFPE) tissue specimens constitute a highly valuable source of clinical material for retrospective molecular studies. However, metabolomic assessment of such archival material remains still in its infancy. Hence, there is an urgent need for efficient methods enabling extraction and profiling of metabolites present in FFPE tissue specimens. Here we demonstrate the methodology for isolation of primary metabolites from archival tissues; either fresh-frozen, formalin-fixed or formalin-fixed and paraffin-embedded specimens of mouse kidney were analysed and compared in this work. We used gas chromatography followed by mass spectrometry (GC/MS approach) to identify about 80 metabolites (including amino acids, saccharides, carboxylic acids, fatty acids) present in such archive material. Importantly, about 75% of identified compounds were detected in all three types of specimens. Moreover, we observed that fixation with formalin itself (and their duration) did not affect markedly the presence of particular metabolites in tissue-extracted material, yet fixation for 24h could be recommended as a practical standard. Paraffin embedding influenced efficiency of extraction, which resulted in reduced quantities of several compounds. Nevertheless, we proved applicability of FFPE specimens for non-targeted GS/MS-based profiling of tissue metabolome, which is of great importance for feasibility of metabolomics studies using retrospective clinical material.