Investigation of salivary free amino acid profile for early diagnosis of breast cancer with ultra performance liquid chromatography-mass spectrometry

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

Redox and metabolic reprogramming in breast cancer and cancer-associated adipose tissue

Redox and metabolic processes are tightly coupled in both physiological and pathological conditions. In cancer, their integration occurs at multiple levels and is characterized by synchronized reprogramming both in the tumor tissue and its specific but heterogeneous microenvironment. In breast cancer, the principal microenvironment is the cancer-associated adipose tissue (CAAT). Understanding how the redox-metabolic reprogramming becomes coordinated in human breast cancer is imperative both for cancer prevention and for the establishment of new therapeutic approaches. This review aims to provide an overview of the current knowledge of the redox profiles and regulation of intermediary metabolism in breast cancer while considering the tumor and CAAT of breast cancer as a unique Warburg's pseudo-organ. As cancer is now recognized as a systemic metabolic disease, we have paid particular attention to the cell-specific redox-metabolic reprogramming and the roles of estrogen receptors and circadian rhythms, as well as their crosstalk in the development, growth, progression, and prognosis of breast cancer.

Development and validation of a non-invasive method for quantifying amino acids in human saliva

As an analytical matrix, saliva has superior characteristics than blood and urine. Saliva collection is, first and foremost, non-invasive, making it convenient, painless, and secure for more susceptible people. Second, it does not need professional training for medical personnel, resulting in cost-effectiveness and suitability for extensive collection in support of research. In this study, we developed a method and used it to quantify 13 salivary-free amino acid (SFAA) profiles to support the early clinical diagnosis of diseases using LC-MS/MS. Using an Intrada Amino Acid column (100 × 3 mm, 3 μm), chromatographic separation was accomplished with a binary gradient elution, and an electrospray ionisation source running in the positive ionisation mode was chosen for data collection using the multiple reaction monitoring (MRM) modes. Amino acids were extracted from saliva using acetonitrile. In the MRM mode, LODs and LOQs for ten amino acids were in the range of 0.06-2.50 μM and 0.19-7.58 μM, respectively, and those values were in the range of 1.00-3.00 μM and 3.00-8.50 μM, respectively, for three amino acids. Matrix-matched six-point calibration curves showed a linear correlation coefficient (r 2) of ≥0.998. Recovery experiments validated the method by spiking the control sample at three different concentration levels (5, 50 and 100 μM), and the accuracy level was 85-110%. Except for Thr and Ser, intra- (n = 3) and inter-day (n = 3) precision fell between 0.02 and 7.28. Salivary amino acids can serve as possible biomarkers for various malignancies, with fluctuations in body fluids being crucial for cancer diagnosis; therefore, examining amino acid patterns in saliva can assist in early cancer detection. LC-MS offers improved selectivity and sensitivity for non-derivatised amino acid analysis, surpassing conventional methods and offering proactive quality assurance, making it suitable for complicated sample matrices. These discoveries could be significant in investigating new pathways and cancer treatments and looking for possible AA biomarkers for other malignancies and diseases.

Free Salivary Amino Acid Profile in Breast Cancer: Clinicopathological and Molecular Biological Features

The study of salivary amino acid profiles has attracted the attention of researchers, since amino acids are actively involved in most metabolic processes, including breast cancer. In this study, we analyzed the amino acid profile of saliva in a sample including all molecular biological subtypes of breast cancer to obtain a more complete picture and evaluate the potential utility of individual amino acids or their combinations for diagnostic purposes. This study included 116 patients with breast cancer, 24 patients with benign breast disease, and 25 healthy controls. From all patients, strictly before the start of treatment, saliva samples were collected, and the quantitative content of 26 amino acids was determined. Statistically significant differences between the three groups are shown in the content of Asp, Gly, Leu + Ile, Orn, Phe, Pro, Thr, and Tyr. To differentiate the three groups from each other, a decision tree was built. To construct it, we selected those amino acids for which the change in concentrations in the subgroups was multidirectional (GABA, Hyl, Arg, His, Pro, and Car). For the first time, it is shown that the amino acid profile of saliva depends on the molecular biological subtype of breast cancer. The most significant differences are shown for the luminal B HER2-positive and TNBC subgroups. In our opinion, it is critically important to consider the molecular biological subtype of breast cancer when searching for potential diagnostic markers.

Salivary Tryptophan as a Metabolic Marker of HER2-Negative Molecular Subtypes of Breast Cancer

Changes in the concentration of tryptophan (Trp) indicate a serious metabolic restructuring, which is both a cause and a consequence of many diseases. This work examines the upward change in salivary Trp concentrations among patients with breast cancer. This study involved volunteers divided into three groups: breast cancer (n = 104), non-malignant breast pathologies (n = 30) and healthy controls (n = 20). In all participants, before treatment, the quantitative content of Trp in saliva was determined by capillary electrophoresis. In 20 patients with breast cancer, Trp was re-tested four weeks after surgical removal of the tumor. An increase in the Trp content in saliva in breast cancer has been shown, which statistically significantly decreases after surgical removal of the tumor. A direct correlation was found between increased Trp levels with the degree of malignancy and aggressive molecular subtypes of breast cancer, namely triple negative and luminal B-like HER2-negative. These conclusions were based on an increase in Ki-67 and an increase in Trp in HER2-negative and progesterone-negative subtypes. Factors under which an increase in Trp concentration in saliva was observed were identified: advanced stage of breast cancer, the presence of regional metastasis, low tumor differentiation, a lack of expression of HER2, estrogen and progesterone receptors and the high proliferative activity of the tumor. Thus, the determination of salivary Trp may be a valuable tool in the study of metabolic changes associated with cancer, particularly breast cancer.

Investigation of amino acid profile alterations in maternal serum for early diagnosis of anembryonic pregnancy with high performance liquid chromatography-mass spectrometry

BACKGROUND

Anembryonic pregnancy affects 12-15 % of clinically recognized pregnancies and a previous anembryonic pregnancy is an independent risk factor for future anembryonic pregnancy. This study aimed to investigate alternations in maternal amino acid profiles and analyze the diagnostic accuracy of amino acid biomarkers for anembryonic pregnancy in the early stage.

METHODS

Fasting serum from anembryonic pregnancy patients (n = 103) and healthy pregnancies (n = 97) was collected, and amino acid concentrations were determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of each of the amino acid biomarkers and the amino acid profile index for anembryonic pregnancy screening.

RESULTS

The concentrations of 15 amino acids were significantly different between anembryonic pregnancy patients and healthy controls, and most of them were significantly higher at 7 weeks' gestational age in anembryonic pregnancy subjects. The area under the curve (AUC) based on an amino acid profile index combined with alanine, citrulline, aspartic acid, threonine, serine and isoleucine was 0.90 (sensitivity 82.76 %, specificity 83.64 %) for distinguishing early anembryonic pregnancy from healthy controls.

CONCLUSION

Maternal serum amino acid concentrations were significantly elevated in anembryonic pregnancy patients. The diagnostic potential of amino aicds for anembryonic pregnancy was verified, and the diagnostic efficiency was improved in the use of the amino acid profile index. The amino acid profile is expected to be applied for the risk screening of early-stage of anembryonic pregnancy in the future.

Normative Data on Serum and Plasma Tryptophan and Kynurenine Concentrations from 8089 Individuals Across 120 Studies: A Systematic Review and Meta-Analysis

In this systematic review and meta-analysis, a normative dataset is generated from the published literature on the kynurenine pathway in control participants extracted from case-control and methodological validation studies. Study characteristics were mapped, and studies were evaluated in terms of analytical rigour and methodological validation. Meta-analyses of variance between types of instruments, sample matrices and metabolites were conducted. Regression analyses were applied to determine the relationship between metabolite, sample matrix, biological sex, participant age and study age. The grand mean concentrations of tryptophan in the serum and plasma were 60.52 ± 15.38 μM and 51.45 ± 10.47 μM, respectively. The grand mean concentrations of kynurenine in the serum and plasma were 1.96 ± 0.51 μM and 1.82 ± 0.54 μM, respectively. Regional differences in metabolite concentrations were observed across America, Asia, Australia, Europe and the Middle East. Of the total variance within the data, mode of detection (MOD) accounted for up to 2.96%, sample matrix up to 3.23%, and their interaction explained up to 1.53%; the latter of which was determined to be negligible. This review was intended to inform future empirical research and method development studies and successfully synthesised pilot data. The pilot data reported in this study will inform future precision medicine initiatives aimed at targeting the kynurenine pathway by improving the availability and quality of normative data.

Pyrroline-5-carboxylate reductase 1 reprograms proline metabolism to drive breast cancer stemness under psychological stress

Cancer stem-like cells (CSCs) contribute to cancer metastasis, drug resistance and tumor relapse, yet how amino acid metabolism promotes CSC maintenance remains exclusive. Here, we identify that proline synthetase PYCR1 is critical for breast cancer stemness and tumor growth. Mechanistically, PYCR1-synthesized proline activates cGMP-PKG signaling to enhance cancer stem-like traits. Importantly, cGMP-PKG signaling mediates psychological stress-induced cancer stem-like phenotypes and tumorigenesis. Ablation of PYCR1 markedly reverses psychological stress-induced proline synthesis, cGMP-PKG signaling activation and cancer progression. Clinically, PYCR1 and cGMP-PKG signaling components are highly expressed in breast tumor specimens, conferring poor survival in breast cancer patients. Targeting proline metabolism or cGMP-PKG signaling pathway provides a potential therapeutic strategy for breast patients undergoing psychological stress. Collectively, our findings unveil that PYCR1-enhanced proline synthesis displays a critical role in maintaining breast cancer stemness.

Diagnostic Value of Salivary Amino Acid Levels in Cancer

This review analyzed 21 scientific papers on the determination of amino acids in various types of cancer in saliva. Most of the studies are on oral cancer (8/21), breast cancer (4/21), gastric cancer (3/21), lung cancer (2/21), glioblastoma (2/21) and one study on colorectal, pancreatic, thyroid and liver cancer. The amino acids alanine, valine, phenylalanine, leucine and isoleucine play a leading role in the diagnosis of cancer via the saliva. In an independent version, amino acids are rarely used; the authors combine either amino acids with each other or with other metabolites, which makes it possible to obtain high values of sensitivity and specificity. Nevertheless, a logical and complete substantiation of the changes in saliva occurring in cancer, including changes in salivary amino acid levels, has not yet been formed, which makes it important to continue research in this direction.

Amino Acid Profiling Identifies Disease-Specific Signatures in IgE-Mediated and Non-IgE-Mediated Food Allergy in Pediatric Patients with Atopic Dermatitis

An IgE-mediated food allergy (FA) in atopic dermatitis (AD) children should be easily differentiated from other immune-mediated adverse effects related to food. Specific IgEs for particular protein components has provided additional diagnostic value. However, component-resolved diagnostics (CRD) has not solved all diagnostic problems either. We analysed the serum profile of 42 amino acids (AAs) in 76 AD children aged 2-60 months with an IgE-mediated FA (n = 36), with a non-IgE-mediated FA (n = 15) and without an FA (n = 25) using high-performance liquid chromatography coupled with mass spectrometry (LC-MS/MS) and an aTRAQ kit. We identified homocitrulline (Hcit), sarcosine (Sar) and L-tyrosine (Tyr) as features that differentiated the studied groups (one-way ANOVA with least significant difference post hoc test). The Hcit concentrations in the non-IgE-mediated FA group were significantly decreased compared with the IgE-mediated FA group (p = 0.018) and the control group (p = 0.008). In AD children with a non-IgE-mediated FA, the Tyr levels were also significantly reduced compared with the controls (p = 0.009). The mean concentration of Sar was the highest in the non-IgE-mediated FA group and the lowest in the IgE-mediated FA group (p = 0.047). Future studies should elucidate the involvement of these AAs in the molecular pathway of IgE- and non-IgE-mediated allergic responses.

SalivaDB-a comprehensive database for salivary biomarkers in humans

Saliva as a non-invasive diagnostic fluid has immense potential as a tool for early diagnosis and prognosis of patients. The information about salivary biomarkers is broadly scattered across various resources and research papers. It is important to bring together all the information on salivary biomarkers to a single platform. This will accelerate research and development in non-invasive diagnosis and prognosis of complex diseases. We collected widespread information on five types of salivary biomarkers-proteins, metabolites, microbes, micro-ribonucleic acid (miRNA) and genes found in humans. This information was collected from different resources that include PubMed, the Human Metabolome Database and SalivaTecDB. Our database SalivaDB contains a total of 15 821 entries for 201 different diseases and 48 disease categories. These entries can be classified into five categories based on the type of biomolecules; 6067, 3987, 2909, 2272 and 586 entries belong to proteins, metabolites, microbes, miRNAs and genes, respectively. The information maintained in this database includes analysis methods, associated diseases, biomarker type, regulation status, exosomal origin, fold change and sequence. The entries are linked to relevant biological databases to provide users with comprehensive information. We developed a web-based interface that provides a wide range of options like browse, keyword search and advanced search. In addition, a similarity search module has been integrated which allows users to perform a similarity search using Basic Local Alignment Search Tool and Smith-Waterman algorithm against biomarker sequences in SalivaDB. We created a web-based database-SalivaDB, which provides information about salivary biomarkers found in humans. A wide range of web-based facilities have been integrated to provide services to the scientific community. https://webs.iiitd.edu.in/raghava/salivadb/.

Saliva - a new opportunity for fluid biopsy

Saliva is a complex biological fluid with a variety of biomolecules, such as DNA, RNA, proteins, metabolites and microbiota, which can be used for the screening and diagnosis of many diseases. In addition, saliva has the characteristics of simple collection, non-invasive and convenient storage, which gives it the potential to replace blood as a new main body of fluid biopsy, and it is an excellent biological diagnostic fluid. This review integrates recent studies and summarizes the research contents of salivaomics and the research progress of saliva in early diagnosis of oral and systemic diseases. This review aims to explore the value and prospect of saliva diagnosis in clinical application.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part II: Applications to the Diagnosis and Prognostic Monitoring of Oral and Systemic Cancers

Human saliva offers many advantages over other biofluids regarding its use and value as a bioanalytical medium for the identification and prognostic monitoring of human diseases, mainly because its collection is largely non-invasive, is relatively cheap, and does not require any major clinical supervision, nor supervisory input. Indeed, participants donating this biofluid for such purposes, including the identification, validation and quantification of surrogate biomarkers, may easily self-collect such samples in their homes following the provision of full collection details to them by researchers. In this report, the authors have focused on the applications of metabolomics technologies to the diagnosis and progressive severity monitoring of human cancer conditions, firstly oral cancers (e.g., oral cavity squamous cell carcinoma), and secondly extra-oral (systemic) cancers such as lung, breast and prostate cancers. For each publication reviewed, the authors provide a detailed evaluation and critical appraisal of the experimental design, sample size, ease of sample collection (usually but not exclusively as whole mouth saliva (WMS)), their transport, length of storage and preparation for analysis. Moreover, recommended protocols for the optimisation of NMR pulse sequences for analysis, along with the application of methods and techniques for verifying and resonance assignments and validating the quantification of biomolecules responsible, are critically considered. In view of the authors’ specialisms and research interests, the majority of these investigations were conducted using NMR-based metabolomics techniques. The extension of these studies to determinations of metabolic pathways which have been pathologically disturbed in these diseases is also assessed here and reviewed. Where available, data for the monitoring of patients’ responses to chemotherapeutic treatments, and in one case, radiotherapy, are also evaluated herein. Additionally, a novel case study featured evaluates the molecular nature, levels and diagnostic potential of ¹H NMR-detectable salivary ‘acute-phase’ glycoprotein carbohydrate side chains, and/or their monomeric saccharide derivatives, as biomarkers for cancer and inflammatory conditions.

Studies about the Dietary Impact on "Free" Glycation Compounds in Human Saliva

Glycation reactions play a key role in post-translational modifications of amino acids in food proteins. Questions have arisen about a possible pathophysiological role of dietary glycation compounds. Several studies assessed the metabolic fate of dietary glycation compounds into blood and urine, but studies about saliva are rare. We investigated here the dietary impact on salivary concentrations of the individual Maillard reaction products (MRPs) N-ε-fructosyllysine, N-ε-carboxymethyllysine (CML), N-ε-carboxyethyllysine (CEL), pyrraline (Pyr), and methylglyoxal-derived hydroimidazolone 1 (MG-H1). Quantitation was performed using stable isotope dilution analysis (LC-MS/MS). We describe here, that a low MRP diet causes a significant lowering of salivary levels of Pyr from 1.9 ± 0.4 ng/mL to below the LOD and MG-H1 from 2.5 ± 1.5 ng/mL to 0.7 ± 1.8 ng/mL. An impact on the salivary protein fraction was not observed. Furthermore, salivary Pyr and MG-H1 levels are modified in a time-dependent manner after a dietary intervention containing 1.2 mg Pyr and 4.7 mg MG-H1. An increase in mean salivary concentrations to 1.4 ng/mL Pyr and 4.2 ng/mL MG-H1 was observed within 30–210 min. In conclusion, saliva may be a useful tool for monitoring glycation compound levels by using Pyr and MG-H1 as biomarkers for intake of heated food.

«Salivaomics» of Different Molecular Biological Subtypes of Breast Cancer

The aim of the study was to determine the metabolic characteristics of saliva depending on the molecular biological subtype of breast cancer, as well as depending on the expression levels of HER2, estrogen receptors (ER), and progesterone receptors (PR). The study included 487 patients with morphologically verified breast cancer and 298 volunteers without breast pathologies. Saliva samples were obtained from all patients strictly before the start of treatment and the values of 42 biochemical indicators were determined. It has been established that the saliva of healthy volunteers and patients with various molecular biological subtypes of breast cancer differs in 12 biochemical indicators: concentrations of protein, urea, nitric oxide, malondialdehyde, total amino acid content, and activity of lactate dehydrogenase, alkaline phosphatase, gamma-glutamyltransferase, catalase, amylase, superoxide dismutase, and peroxidases. The saliva composition of patients with basal-like breast cancer differs from other subtypes in terms of the maximum number of indicators. Changes in biochemical indicators indicated an increase in the processes of lipid peroxidation and endogenous intoxication and a weakening of antioxidant protection, which correlates with the severity of the disease and the least favorable prognosis for this subtype of breast cancer. An analysis was made of the individual contribution of the expression level of HER2, estrogen, and progesterone receptors to changes in the biochemical composition of saliva. The HER2 (−)/HER2 (+) group, which should be considered as a single group, as well as ER-positive breast cancer, differ statistically significantly from the control group. For ER/PR-positive breast cancer, a more favorable ratio of saliva biochemical indicators was also noted compared to ER/PR-negative breast cancer.

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis

BACKGROUND

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

METHODS

We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

RESULTS

Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

CONCLUSION

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Salivary metabolomics with machine learning for colorectal cancer detection

As the worldwide prevalence of colorectal cancer (CRC) increases, it is vital to reduce its morbidity and mortality through early detection. Saliva‐based tests are an ideal noninvasive tool for CRC detection. Here, we explored and validated salivary biomarkers to distinguish patients with CRC from those with adenoma (AD) and healthy controls (HC). Saliva samples were collected from patients with CRC, AD, and HC. Untargeted salivary hydrophilic metabolite profiling was conducted using capillary electrophoresis–mass spectrometry and liquid chromatography–mass spectrometry. An alternative decision tree (ADTree)‐based machine learning (ML) method was used to assess the discrimination abilities of the quantified metabolites. A total of 2602 unstimulated saliva samples were collected from subjects with CRC (n = 235), AD (n = 50), and HC (n = 2317). Data were randomly divided into training (n = 1301) and validation datasets (n = 1301). The clustering analysis showed a clear consistency of aberrant metabolites between the two groups. The ADTree model was optimized through cross‐validation (CV) using the training dataset, and the developed model was validated using the validation dataset. The model discriminating CRC + AD from HC showed area under the receiver‐operating characteristic curves (AUC) of 0.860 (95% confidence interval [CI]: 0.828‐0.891) for CV and 0.870 (95% CI: 0.837‐0.903) for the validation dataset. The other model discriminating CRC from AD + HC showed an AUC of 0.879 (95% CI: 0.851‐0.907) and 0.870 (95% CI: 0.838‐0.902), respectively. Salivary metabolomics combined with ML demonstrated high accuracy and versatility in detecting CRC.

Salivary Metabolomics for Oral Cancer Detection: A Narrative Review

The development of low- or non-invasive screening tests for cancer is crucial for early detection. Saliva is an ideal biofluid containing informative components for monitoring oral and systemic diseases. Metabolomics has frequently been used to identify and quantify numerous metabolites in saliva samples, serving as novel biomarkers associated with various conditions, including cancers. This review summarizes the recent applications of salivary metabolomics in biomarker discovery in oral cancers. We discussed the prevalence, epidemiologic characteristics, and risk factors of oral cancers, as well as the currently available screening programs, in India and Japan. These data imply that the development of biomarkers by itself is inadequate in cancer detection. The use of current diagnostic methods and new technologies is necessary for efficient salivary metabolomics analysis. We also discuss the gap between biomarker discovery and nationwide screening for the early detection of oral cancer and its prevention.

Potential Diagnostic Significance of Salivary Copper Determination in Breast Cancer Patients: A Pilot Study

Determination of the copper content in the saliva of breast cancer patients was carried out to assess the potential diagnostic and prognostic value. The malignant group included 75 breast cancer patients; the benign group included 87 patients with fibroadenomas; and the control group included 20 volunteers without breast pathology. All participants had 1 ml of saliva collected prior to treatment. The determination of copper in saliva was carried out by the stripping voltammetric method. Overall survival was assessed using the Kaplan-Meier method with the presentation of survival curves and the calculation of the significance of differences by Log-rank. The average copper content in the saliva of breast cancer patients is 49.3% higher than in patients with fibroadenomas and 60.4% higher than in volunteers without breast pathologies. Within the group of breast cancer patients, the content of copper in saliva is heterogeneous, which limits the possibilities of using this indicator for diagnostic purposes. The copper content increases when comparing the initial stages and locally widespread (+ 22.4%) and then sharply increases by 3.5 times at the T_3-4N_0-2M₀ stage. For HER2-positive breast cancer, the copper content in saliva is 51.9% higher than for HER2-negative, a similar pattern was observed for luminal A and B breast cancer subtypes. The content of copper in saliva less than 1.14 mg/l is a prognostically unfavorable sign, while the relative risk of dying from breast cancer more than doubles. Thus, the content of copper in saliva can be used in clinical practice for planning treatment tactics.

HPLC method with post-column derivatization for the analysis of endogenous histidine in human saliva validated using the total-error concept

Histidine (His) is an essential amino acid that plays an important biological role and associated with various pathological conditions. A simple and reliable method for the determination of endogenous histidine in human saliva was optimized and validated. The analyte was separated from the saliva matrix by cation exchange chromatography and detected fluorimetrically (λ_ex/λ_em = 360/440 nm) after online, specific post-column derivatization (PCD) reaction with o-phthalaldehyde. The chemical and instrumental variables of the post-column reaction were optimized using Box-Behnken experimental design to achieve maximum sensitivity. Method validation was carried out employing the total-error concept. Histidine could be analyzed reliably in the range of 0.5-5.0 μΜ, with an LOD (S/N = 3) of 50 nM. Monte Carlo simulations and capability analysis were used to investigate the ruggedness of the PCD reaction. The sampling strategy, sample preparation and stability were also investigated. Seventeen saliva samples were successfully analyzed with histidine levels being in the range of 2.7-19.5 μΜ.

Metabolic Features of Saliva in Breast Cancer Patients

The aim of the work was to study the metabolic characteristics of saliva in breast cancer and the subsequent assessment of the potential information content of its individual biochemical indicators. The study included 487 patients of the Omsk Clinical Oncology Center with morphologically verified breast cancer and 298 volunteers without breast pathologies. Saliva samples were obtained from all patients before the start of treatment, and the values of 34 biochemical indicators were determined. It has been shown that concentration of total protein, urea, uric acid (UA), the total content of α-amino acids and lipid peroxidation products, and the activity of metabolic and antioxidant enzymes (in particular catalase—CAT) of saliva changed significantly in breast cancer. Biochemical indicators characterizing early breast cancer have been identified, which can be used for timely diagnosis in addition to existing methods. The coefficients UA/Urea and UA·CAT/Urea are proposed, for which the maximum deviation from the norm was observed in the early stages of the disease. It was shown that for ductal breast cancer, changes in the activity of metabolic enzymes of saliva were more pronounced, while, for lobular breast cancer, the indicators of enzymatic and non-enzymatic components of antioxidant protection changed. The results confirmed the potential importance of saliva in the diagnosis of breast cancer.

Free amino acid composition of saliva in patients with healthy periodontium and periodontitis

OBJECTIVES

To identify and compare the free amino acids in the saliva of periodontitis patients and healthy individuals and to assess their levels in different periodontal disease types.

MATERIALS AND METHODS

There were three groups: healthy individuals (control (C); n = 20), Stage III Grade B generalized periodontitis (GP-B; n = 20), and Stage III Grade C generalized periodontitis (GP-C; n = 20). Clinical periodontal parameters were measured. Amino acid analysis of the saliva was accomplished by liquid chromatography-mass spectrometry (LC MS/MS), taking the mean concentration.

RESULTS

Citrulline and carnosine concentrations were significantly higher in patients with periodontitis than in the control group (p < 0.017). Methionine, glutamic acid, and arginine showed significantly higher concentrations in GP-C, whereas proline and tryptophan showed higher concentrations in the GP-B group (p < 0.017). There was a significant correlation between methionine, citrulline, arginine, and carnosine and clinical periodontal parameters.

CONCLUSIONS

Our results demonstrate that periodontal status and disease type can result in variations in salivary amino acid (AA) content in correlation with clinical inflammatory signs. The significant correlation of methionine, citrulline, carnosine, and arginine with clinical parameters, regardless of systemic status, suggests that the levels of different salivary free AAs play roles in periodontitis.

CLINICAL RELEVANCE

Salivary free AAs may be suggested as a potential diagnostic compound in patients with periodontitis.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT04642716.

Advanced Approaches to Breast Cancer Classification and Diagnosis

The International Agency for Research on Cancer (IARC) has recently reported a 66% increase in the global number of cancer deaths since 1960. In the US alone, about one in eight women is expected to develop invasive breast cancer(s) (breast cancer) at some point in their lifetime. Traditionally, a BC diagnosis includes mammography, ultrasound, and some high-end molecular bioimaging. Unfortunately, these techniques detect BC at a later stage. So early and advanced molecular diagnostic tools are still in demand. In the past decade, various histological and immuno-molecular studies have demonstrated that BC is highly heterogeneous in nature. Its growth pattern, cytological features, and expression of key biomarkers in BC cells including hormonal receptor markers can be utilized to develop advanced diagnostic and therapeutic tools. A cancer cell's progression to malignancy exhibits various vital biomarkers, many of which are still underrepresented in BC diagnosis and treatment. Advances in genetics have also enabled the development of multigene assays to detect genetic heterogeneity in BC. However, thus far, the FDA has approved only four such biomarkers-cancer antigens (CA); CA 15-3, CA 27-29, Human epidermal growth factor receptor 2 (HER2), and circulating tumor cells (CTC) in assessing BC in body fluids. An adequately structured portable-biosensor with its non-invasive and inexpensive point-of-care analysis can quickly detect such biomarkers without significantly compromising its specificity and selectivity. Such advanced techniques are likely to discriminate between BC and a healthy patient by accurately measuring the cell shape, structure, depth, intracellular and extracellular environment, and lipid membrane compositions. Presently, BC treatments include surgery and systemic chemo- and targeted radiation therapy. A biopsied sample is then subjected to various multigene assays to predict the heterogeneity and recurrence score, thus guiding a specific treatment by providing complete information on the BC subtype involved. Thus far, we have seven prognostic multigene signature tests for BC providing a risk profile that can avoid unnecessary treatments in low-risk patients. Many comparative studies on multigene analysis projected the importance of integrating clinicopathological information with genomic-imprint analysis. Current cohort studies such as MINDACT, TAILORx, Trans-aTTOM, and many more, are likely to provide positive impact on long-term patient outcome. This review offers consolidated information on currently available BC diagnosis and treatment options. It further describes advanced biomarkers for the development of state-of-the-art early screening and diagnostic technologies.

Using an Untargeted Metabolomics Approach to Identify Salivary Metabolites in Women with Breast Cancer

Metabolic alterations are a hallmark of the malignant transformation in cancer cells, which is characterized by multiple changes in metabolic pathways that are linked to macromolecule synthesis. This study aimed to explore whether salivary metabolites could help discriminate between breast cancer patients and healthy controls. Saliva samples from 23 breast cancer patients and 35 healthy controls were subjected to untargeted metabolomics using liquid chromatography-quadrupole time-of-flight mass spectrometry and a bioinformatics tool (XCMS Online), which revealed 534 compounds, characterized by their retention time in reverse-phase liquid chromatography and by the m/z ratio detected, that were shared by the two groups. Using the METLIN database, 31 compounds that were upregulated in the breast cancer group (p < 0.05) were identified, including seven oligopeptides and six glycerophospholipids (PG14:2, PA32:1, PS28:0, PS40:6, PI31:1, and PI38:7). In addition, pre-treatment and post-treatment saliva samples were analyzed for 10 patients who experienced at least a partial response to their treatment. In these patients, three peptides and PG14:2 were upregulated before but not after treatment. The area under the curve, sensitivity, and specificity for PG14:2 was 0.7329, 65.22%, and 77.14%, respectively. These results provide new information regarding the salivary metabolite profiles of breast cancer patients, which may be useful biomarkers.

Metabolism and immunity in breast cancer

Breast cancer is one of the most common malignancies that seriously threaten women's health. In the process of the malignant transformation of breast cancer, metabolic reprogramming and immune evasion represent the two main fascinating characteristics of cancer and facilitate cancer cell proliferation. Breast cancer cells generate energy through increased glucose metabolism. Lipid metabolism contributes to biological signal pathways and forms cell membranes except energy generation. Amino acids act as basic protein units and metabolic regulators in supporting cell growth. For tumor-associated immunity, poor immunogenicity and heightened immunosuppression cause breast cancer cells to evade the host's immune system. For the past few years, the complex mechanisms of metabolic reprogramming and immune evasion are deeply investigated, and the genes involved in these processes are used as clinical therapeutic targets for breast cancer. Here, we review the recent findings related to abnormal metabolism and immune characteristics, regulatory mechanisms, their links, and relevant therapeutic strategies.

Splicing Factor Transcript Abundance in Saliva as a Diagnostic Tool for Breast Cancer

Breast cancer is the second leading cause of death in women above 60 years in the US. Screening mammography is recommended for women above 50 years; however, 22% of breast cancer cases are diagnosed in women below this age. We set out to develop a test based on the detection of cell-free RNA from saliva. To this end, we sequenced RNA from a pool of ten women. The 1254 transcripts identified were enriched for genes with an annotation of alternative pre-mRNA splicing. Pre-mRNA splicing is a tightly regulated process and its misregulation in cancer cells promotes the formation of cancer-driving isoforms. For these reasons, we chose to focus on splicing factors as biomarkers for the early detection of breast cancer. We found that the level of the splicing factors is unique to each woman and consistent in the same woman at different time points. Next, we extracted RNA from 36 healthy subjects and 31 breast cancer patients. Recording the mRNA level of seven splicing factors in these samples demonstrated that the combination of all these factors is different in the two groups (p value = 0.005). Our results demonstrate a differential abundance of splicing factor mRNA in the saliva of breast cancer patients.

Alterations in Serum-Free Amino Acid Profiles in Childhood Asthma

Asthma often begins in childhood, although making an early diagnosis is difficult. Clinical manifestations, the exclusion of other causes of bronchial obstruction, and responsiveness to anti-inflammatory therapy are the main tool of diagnosis. However, novel, precise, and functional biochemical markers are needed in the differentiation of asthma phenotypes, endotypes, and creating personalized therapy. The aim of the study was to search for metabolomic-based asthma biomarkers among free amino acids (AAs). A wide panel of serum-free AAs in asthmatic children, covering both proteinogenic and non-proteinogenic AAs, were analyzed. The examination included two groups of individuals between 3 and 18 years old: asthmatic children and the control group consisted of children with neither asthma nor allergies. High-performance liquid chromatography combined with tandem mass spectrometry (LC-MS/MS technique) was used for AA measurements. The data were analyzed by applying uni- and multivariate statistical tests. The obtained results indicate the decreased serum concentration of taurine, L-valine, DL-β-aminoisobutyric acid, and increased levels of ƴ-amino-n-butyric acid and L-arginine in asthmatic children when compared to controls. The altered concentration of these AAs can testify to their role in the pathogenesis of childhood asthma. The authors' results should contribute to the future introduction of new diagnostic markers into clinical practice.

Salivary biomarkers for cancer diagnosis: a meta-analysis

Background: Saliva represents a promising non-invasive source of novel biomarkers for diagnosis and prognosis cancer. This meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumours to better define the value of saliva as an alternative liquid biopsy.Materials and methods: We performed a systematic review and meta-analysis. PubMed, Embase, LILACS and the Cochrane Library were searched to identify articles that examined the potential of salivary biomarkers for the diagnosis of malignant non-oral tumours. To assess the overall accuracy, we calculated the diagnostic odds ratio (DOR), area under hierarchical summary receiver operating characteristic (AUC) curve, sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) using a random- or fixed-effects model. Heterogeneity and publication bias were assessed. Statistical tests were two-sided.Results: One hundred fifty-five study units from 29 articles with 11,153 subjects were included. The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.76 (95% confidence intervals (CI), 0.74-0.77), 0.76 (95% CI, 0.75-0.77), 3.22 (95% CI, 2.92-3.55), 0.31 (95% CI, 0.28-0.34), 13.42 (95% CI, 12.28-15.96) and 0.85 (95% CI, 0.84-0.87), respectively.Conclusion: Salivary biomarkers may be potentially used for non-invasive diagnosis of malignant non-oral tumours.Key messagesThis meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumours to better define the role of saliva as an alternative liquid biopsy.Salivary biomarkers showed 85% accuracy for cancer distant to the oral cavity.Saliva represents a promising non-invasive source of novel biomarkers in cancer.

Salivary metabolites to detect patients with cancer: a systematic review

Novel adjunctive screening aids are needed to reduce the morbidity and mortality related to cancer, and every effort should be made for early diagnosis. This systematic review aimed to evaluate salivary metabolites and their diagnostic value in patients with cancer.The systematic review was performed in two phases and included studies that focused on the diagnostic value of salivary metabolites in humans with solid malignant neoplasms. Five electronic databases were searched, and the risk of bias in individual studies was evaluated using the revised Quality Assessment of Diagnostic Accuracy Studies criteria (QUADAS-2). All procedures were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.Of the 1151 studies retrieved, 25 were included; 13 studies used targeted and 12 untargeted metabolomics approaches. Most studies included patients with breast and oral cancer. Except for one, all studies had case-control designs, and none fulfilled all quality assessments. Overall, 140 salivary metabolites were described. The most frequently reported metabolites were alanine, valine, and leucine. Among the 11 studies that reported diagnostic test accuracy (DTA) values, proline, threonine, and histidine in combination and monoacylglycerol alone demonstrated the highest DTA for breast cancer. Combined choline, betaine, pipecolinic acid, and L-carnitine showed better discriminatory performance for early oral cancer.This systematic review highlights the current evidence on salivary metabolites that may be used as a future strategy to diagnose cancer. Further studies including larger sample sizes with confirmation of the results by untargeted analysis are warranted.

Salivary biomarkers for diagnosis of systemic diseases and malignant tumors. A systematic review

Background

Saliva evaluation could be a possible alternative to blood and/or tissue analyses, for researching specific molecules associated to the presence of systemic diseases and malignancies. The present systematic review has been designed in order to answer to the question “are there significant associations between specific salivary biomarkers and diagnosis of systemic diseases or malignancies?”.

Material and Methods

The Preferred Reporting Item for Systematic Reviews and Meta-analysis (PRISMA) statement was used to guide the review. The combinations of “saliva” and “systemic diseases” or “diagnosis” or “biomarkers” or “cancers” or “carcinoma” or “tumors”, were used to search Medline, Scopus and Web of Science databases. Endpoint of research has been set at May 2019. Studies were classified into 3 groups according to the type of disease investigated for diagnosis: 1) malignant tumors; 2) neurologic diseases and 3) inflammatory/metabolic/cardiovascular diseases. Assessment of quality has been assigned according to a series of questions proposed by the National Institute of Health. Level of evidence was assessed using the categories proposed in the Oxford Center for Evidence-Based medicine (CEMB) levels for diagnosis (2011).

Results

Seventy-nine studies met the inclusion and exclusion criteria. Fifty-one (64%) investigated malignant tumors, 14 (17.5%) neurologic and 14 (18.5%) inflammatory/cardiovascular/metabolic diseases. Among studies investigating malignant tumors, 12 (23.5%) were scored as “good” and 11 of these reported statistically significant associations between salivary molecules and pathology. Two and 5 studies were found to have a good quality, among those evaluating the association between salivary biomarkers and neurologic and inflammatory/metabolic/cardiovascular diseases, respectively.

Conclusions

The present systematic review confirms the existence of some “good” quality evidence to support the role of peculiar salivary biomarkers for diagnosis of systemic diseases (e.g. lung cancer and EGFR).

Key words:Salivary diagnostics, biomarkers, systemic diseases, malignant tumors, early diagnosis.

Non-separative method based on a single quadrupole mass spectrometer for the semi-quantitative determination of amino acids in saliva samples. A preliminary study

Amino acids have been of great interest in clinical studies since variation in their concentration may provide information about different disorders. For the first time, a non-separative method based on single quadrupole mass spectrometry (qMS) for the simultaneous semiquantitative determination of sixteen amino acids in saliva samples has been developed. The method includes derivatisation of amino acids with ethyl chloroformate-pyridine-ethanol to obtain volatile products, liquid-liquid extraction (LLE) and further analysis using a programmed temperature vaporizer (PTV) coupled to qMS. This method could be applied to the analysis of a great number of saliva samples, limiting the use of separative methods only when abnormal concentrations of amino acids were found, reducing analysis time and cost. The results obtained in the determination of amino acids using the non-separative method were compared to those obtained when a separative method based on gas chromatography (GC) was used, providing values of average relative predictive error (E %) ranging between 2 and 48%. Repeatability and reproducibility were tested, obtaining relative standard deviation (RSD) values equal to or lower than 11% and 16%, respectively. Detection limits were in the range of 0.076-8.747 mg L^-1 for the non-separative method.

Quantitation of free glycation compounds in saliva

In the course of the Maillard reaction, which occurs during heating of food but also under physiological condition, a broad spectrum of reaction products is formed. Among them, the advanced glycation endproducts (AGEs) Nε-carboxymethyllysine (CML), pyrraline (Pyr), methylglyoxal-derived hydroimidazolone 1 (MG-H1) and Nε-carboxyethyllysine (CEL) are the quantitatively dominating compounds during later reaction stages. Those dietary glycation compounds are under discussion as to be associated with chronic inflammation and the pathophysiological consequences of diseases such as diabetes. In the present study, the concentration of individual glycation compounds in saliva was monitored for the first time and related to their dietary uptake. Fasting saliva of 33 metabolically healthy subjects was analyzed with HPLC-MS/MS. The observed levels of individual glycation compounds ranged from 0.5 to 55.2 ng/ml and differed both intra- and interindividually. Patterns did not correlate with subject-related features such as vegetarianism or sports activities, indicating that dietary intake may play an important role. Therefore, six volunteers were asked to eat a raw food diet free of glycation compounds for two days. Within two days, salivary Pyr was lowered from median 1.7 ng/ml to a minimum level below the limit of detection, and MG-H1 decreased from 3.6 to 1.7 ng/ml in in a time-dependent manner after two days. Salivary CML and CEL concentrations were not affected. Therefore, measuring Pyr and MG-H1 in saliva is a suitable diagnostic tool to monitor the dietary intake and metabolic transit of glycation compounds present in heated foods.

Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination

PURPOSE

The aim of this study is to explore new salivary biomarkers to discriminate breast cancer patients from healthy controls.

METHODS

Saliva samples were collected after 9 h fasting and were immediately stored at - 80 °C. Capillary electrophoresis and liquid chromatography with mass spectrometry were used to quantify hundreds of hydrophilic metabolites. Conventional statistical analyses and artificial intelligence-based methods were used to assess the discrimination abilities of the quantified metabolites. A multiple logistic regression (MLR) model and an alternative decision tree (ADTree)-based machine learning method were used. The generalization abilities of these mathematical models were validated in various computational tests, such as cross-validation and resampling methods.

RESULTS

One hundred sixty-six unstimulated saliva samples were collected from 101 patients with invasive carcinoma of the breast (IC), 23 patients with ductal carcinoma in situ (DCIS), and 42 healthy controls (C). Of the 260 quantified metabolites, polyamines were significantly elevated in the saliva of patients with breast cancer. Spermine showed the highest area under the receiver operating characteristic curves [0.766; 95% confidence interval (CI) 0.671-0.840, P < 0.0001] to discriminate IC from C. In addition to spermine, polyamines and their acetylated forms were elevated in IC only. Two hundred each of two-fold, five-fold, and ten-fold cross-validation using different random values were conducted and the MLR model had slightly better accuracy. The ADTree with an ensemble approach showed higher accuracy (0.912; 95% CI 0.838-0.961, P < 0.0001). These prediction models also included spermine as a predictive factor.

CONCLUSIONS

These data indicated that combinations of salivary metabolomics with the ADTree-based machine learning methods show potential for non-invasive screening of breast cancer.

Salivary Glycopatterns as Potential Biomarkers for Screening of Early-Stage Breast Cancer

OBJECTIVE

We systematically investigated and assessed the alterations of salivary glycopatterns and possibility as biomarkers for diagnosis of early-stage breast cancer.

DESIGN

Alterations of salivary glycopatterns were probed using lectin microarrays and blotting analysis from 337 patients with breast benign cyst or tumor (BB) or breast cancer (I/II stage) and 110 healthy humans. Their diagnostic models were constructed by a logistic stepwise regression in the retrospective cohort. Then, the performance of the diagnostic models were assessed by ROC analysis in the validation cohort. Finally, a double-blind cohort was tested to confirm the application potential of the diagnostic models.

RESULTS

The diagnostic models were constructed based on 9 candidate lectins (e.g., PHA-E+L, BS-I, and NPA) that exhibited significant alterations of salivary glycopatterns, which achieved better diagnostic powers with an AUC value >0.750 (p<0.001) for the diagnosis of BB (AUC: 0.752, sensitivity: 0.600, and specificity: 0.835) and I stage breast cancer (AUC: 0.755, sensitivity: 0.733, and specificity: 0.742) in the validation cohort. The diagnostic model of I stage breast cancer exhibited a high accuracy of 0.902 in double-blind cohort.

CONCLUSIONS

This study could contribute to the screening for patients with early-stage breast cancer based on precise alterations of salivary glycopatterns.

Increased nutrient availability in dense breast tissue of postmenopausal women in vivo

Metabolic reprogramming is a hallmark of cancer. Nutrient availability in the tissue microenvironment determines cellular events and may play a role in breast carcinogenesis. High mammographic density is an independent risk factor for breast cancer. Whether nutrient availability differs in normal breast tissues with various densities is unknown. Therefore we investigated whether breast tissues with various densities exhibited differences in nutrient availability. Healthy postmenopausal women from the regular mammographic screening program who had either predominantly fatty breast tissue (nondense), n = 18, or extremely dense breast tissue (dense), n = 20, were included. Microdialysis was performed for the in vivo sampling of amino acids (AAs), analyzed by ultra-high performance liquid chromatography with tandem mass spectroscopy, glucose, lactate and vascular endothelial growth factor (VEGF) in breast tissues and, as a control, in abdominal subcutaneous (s.c.) fat. We found that dense breast tissue exhibited significantly increased levels of 20 proteinogenic AAs and that 18 of these AAs correlated significantly with VEGF. No differences were found in the s.c. fat, except for one AA, suggesting tissue-specific alterations in the breast. Glucose and lactate were unaltered. Our findings provide novel insights into the biology of dense breast tissue that may be explored for breast cancer prevention strategies.

Cancer Salivary Biomarkers for Tumours Distant to the Oral Cavity

The analysis of saliva as a diagnostic approach for systemic diseases was proposed just two decades ago, but recently great interest in the field has emerged because of its revolutionary potential as a liquid biopsy and its usefulness as a non-invasive sampling method. Multiple molecules isolated in saliva have been proposed as cancer biomarkers for diagnosis, prognosis, drug monitoring and pharmacogenetic studies. In this review, we focus on the current status of the salivary diagnostic biomarkers for different cancers distant to the oral cavity, noting their potential use in the clinic and their applicability in personalising cancer therapies.

Nonessential amino acid metabolism in breast cancer

Interest in studying cancer metabolism has risen in recent years, as it has become evident that the relationship between cancer and metabolic pathways could reveal novel biomarkers and therapeutic targets. Metabolic starvation therapy is particularly promising due to its low toxicity. Nonessential amino acids are promising metabolites for such therapy because they become essential in many tumor cells, including breast cancer cells. This review will focus on four nonessential amino acid metabolism pathways: glutamine-glutamate, serine-glycine, cysteine, and arginine-proline metabolism. Recent studies of these amino acids have revealed metabolic enzymes that have the potential to be effective as cancer therapy targets or biomarkers for response to metabolic starvation therapy. The review will also discuss features of nonessential amino acid metabolism that merit further investigation to determine their relevancy to breast cancer treatment.

Effect of oncogene activating mutations and kinase inhibitors on amino acid metabolism of human isogenic breast cancer cells

We investigated the changes in amino acid (AA) metabolism induced in MCF10A, a human mammary epithelial cell line, by the sequential knock-in of K-Ras and PI3K mutant oncogenes. Differentially regulated genes associated to AA pathways were identified on comparing gene expression patterns in the isogenic cell lines. Additionally, we monitored the changes in the levels of AAs and transcripts in the cell lines treated with kinase inhibitors (REGO: a multi-kinase inhibitor, PI3K-i: a PI3K inhibitor, and MEK-i: a MEK inhibitor). In total, 19 AAs and 58 AA-associated transcripts were found to be differentially regulated by oncogene knock-in and by drug treatment. In particular, the multi-kinase and MEK inhibitor affected pathways in K-Ras mutant cells, whereas the PI3K inhibitor showed a major impact in the K-Ras/PI3K double mutant cells. These findings may indicate the dependency of AA metabolism on the oncogene mutation pattern in human cancer. Thus, future therapy might include combinations of kinase inhibitors and drug targeting enzymes of AA pathways.

Nanobiosensors in diagnostics

Medical diagnosis has been greatly improved thanks to the development of new techniques capable of performing very sensitive detection and quantifying certain parameters. These parameters can be correlated with the presence of specific molecules and their quantity. Unfortunately, these techniques are demanding, expensive, and often complicated. On the other side, progress in other fields of science and technology has contributed to the rapid growth of nanotechnology. Although being an emerging discipline, nanotechnology has raised huge interest and expectations. Most of the enthusiasm comes from new possibilities and properties of nanomaterials. Biosensors (simple, robust, sensitive, cost-effective) combined with nanomaterials, also called nanobiosensors, are serving as bridge between advanced detection/diagnostics and daily/routine tests. Here we review some of the latest applications of nanobiosensors in diagnostics field.