Tumour biomarkers: homeostasis as a novel prognostic indicator

Volatile organic compounds in exhaled breath: a promising approach for accurate differentiation of lung adenocarcinoma and squamous cell carcinoma

Lung cancer subtyping, particularly differentiating adenocarcinoma (ADC) from squamous cell carcinoma (SCC), is paramount for clinicians to develop effective treatment strategies. In this study, we aimed: (i) to discover volatile organic compound (VOC) biomarkers for precise diagnosis of ADC and SCC, (ii) to investigated the impact of risk factors on ADC and SCC prediction, and (iii) to explore the metabolic pathways of VOC biomarkers. Exhaled breath samples from patients with ADC (n= 149) and SCC (n= 94) were analyzed by gas chromatography-mass spectrometry. Both multivariate and univariate statistical analysis method were employed to identify VOC biomarkers. Support vector machine (SVM) prediction models were developed and validated based on these VOC biomarkers. The impact of risk factors on ADC and SCC prediction was investigated. A panel of 13 VOCs was found to differ significantly between ADC and SCC. Utilizing the SVM algorithm, the VOC biomarkers achieved a specificity of 90.48%, a sensitivity of 83.50%, and an area under the curve (AUC) value of 0.958 on the training set. On the validation set, these VOC biomarkers attained a predictive power of 85.71% for sensitivity and 73.08% for specificity, along with an AUC value of 0.875. Clinical risk factors exhibit certain predictive power on ADC and SCC prediction. Integrating these risk factors into the prediction model based on VOC biomarkers can enhance its predictive accuracy. This work indicates that exhaled breath holds the potential to precisely detect ADCs and SCCs. Considering clinical risk factors is essential when differentiating between these two subtypes.

MicroRNAs’ Crucial Role in Salivary Gland Cancers’ Onset and Prognosis

Simple Summary

Salivary gland cancers are incredibly heterogeneous, both in the physical onset and in the aggressiveness. Setting up a novel diagnostic and prognostic detection method based on the noninvasive microRNAs’ profiling might represent a goal for the clinical management of those particular malignancies, saving precious time for the patients.

Abstract

Salivary gland cancer (SGC) is an uncommon and heterogeneous disease that accounts for around 8.5% of all head and neck cancers. MicroRNAs (miRNAs) consist of a class of highly conserved, short, single-stranded segments (18–25 nucleotides) of noncoding RNA that represent key gene-transcription regulators in physiological and pathological human conditions. However, their role in SGC development and progression is not completely clear. This review aims to compile and summarize the recent findings on the topic, focusing on the prognostic and diagnostic value of the major modulated and validated microRNAs in SGC. Their differential expression could possibly aid the clinician in delivering an early diagnosis, therapeutic strategy and precision medicine.

Non-Small Cell Lung Cancer Detection and Subtyping by UPLC-HRMS-Based Tissue Metabolomics

Non-small cell lung cancer (NSCLC) is the prevalent histological subtype of lung cancer. In this study, we performed ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS)-based metabolic profiling of 227 tissue samples from 79 lung cancer patients with adenocarcinoma (AC) or squamous cell carcinoma (SCC). Orthogonal partial least squares-discriminant analysis (oPLS-DA) analyses showed that AC, SCC, and NSCLC tumors were discriminated from adjacent noncancerous tissue (ANT) and distant noncancerous tissue (DNT) samples with good accuracies (91.3, 100, and 88.3%), sensitivities (85.7, 100, and 83.9%), and specificities (94.3, 100, and 90.7%), using 12, 4, and 7 discriminant metabolites, respectively. The discriminant panel for AC detection included valine, sphingosine, glutamic acid γ-methyl ester, and lysophosphatidylcholine (LPC) (16:0), levels of which in tumor tissues were significantly altered. Valine, sphingosine, LPC (18:1), and leucine derivatives were used for SCC detection. The discrimination between AC and SCC had 96.8% accuracy, 98.2% sensitivity, and 85.7% specificity using a five-metabolite panel, of which valine and creatine had significant differences. The classification models were further verified with external validation sets, showing a promising prospect for NSCLC tissue detection and subtyping.

Evaluation of the influence of diet supplementation with conjugated linoleic acid isomers on elemental composition in the cardio-oncological nutritional programming rat' model

BACKGROUND

The 'developmental origin of health and disease' (DOHaD) hypothesis assumes that due to the action of some stimuli during fetal life the long-term physiological changes occurs and may affects the risk of various diseases. The main aim of this study was to assess impact of supplementation of maternal' and early postnatal diet with conjugated linoleic acids (CLA) isomers on selected elements content in hearts of their female offspring with chemically induced breast cancer.

METHODS

Elemental composition was determined by quadrupole mass spectrometer with inductively coupled plasma ionization (ICP-MS).

RESULTS

The effect of maternal' diet on the elements content was more pronounced than the progeny diet modifications. Significant correlations among determined elements, especially macroelements, and lipidomic parameters, in the experimental factors dependent manner were observed. It can be concluded that supplementation of maternal and progeny diets with CLA isomers may significantly influence the contents of both macro- and microelements in cardiac tissue of newborns.

CONCLUSION

Our results also indicate, that dynamic and intricate balance among various elements in body may be affected by the lipid dietary supplements also in the pathological state. Utility of cardio-oncological approach in developmental programming study was confirmed.

Electrolyte Disorders Induced by Antineoplastic Drugs

The use of antineoplastic drugs has a central role in treatment of patients affected by cancer but is often associated with numerous electrolyte derangements which, in many cases, could represent life-threatening conditions. In fact, while several anti-cancer agents can interfere with kidney function leading to acute kidney injury, proteinuria, and hypertension, in many cases alterations of electrolyte tubular handling and water balance occur. This review summarizes the mechanisms underlying the disturbances of sodium, potassium, magnesium, calcium, and phosphate metabolism during anti-cancer treatment. Platinum compounds are associated with sodium, potassium, and magnesium derangements while alkylating agents and Vinca alkaloids with hyponatremia due to syndrome of inappropriate antidiuretic hormone secretion (SIADH). Novel anti-neoplastic agents, such as targeted therapies (monoclonal antibodies, tyrosine kinase inhibitors, immunomodulators, mammalian target of rapamycin), can induce SIADH-related hyponatremia and, less frequently, urinary sodium loss. The blockade of epidermal growth factor receptor (EGFR) by anti-EGFR antibodies can result in clinically significant magnesium and potassium losses. Finally, the tumor lysis syndrome is associated with hyperphosphatemia, hypocalcemia and hyperkalemia, all of which represent serious complications of chemotherapy. Thus, clinicians should be aware of these side effects of antineoplastic drugs, in order to set out preventive measures and start appropriate treatments.

Exploratory study on classification of lung cancer subtypes through a combined K-nearest neighbor classifier in breathomics

Accurate classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) in lung cancer is critical to physicians’ clinical decision-making. Exhaled breath analysis provides a tremendous potential approach in non-invasive diagnosis of lung cancer but was rarely reported for lung cancer subtypes classification. In this paper, we firstly proposed a combined method, integrating K-nearest neighbor classifier (KNN), borderline2-synthetic minority over-sampling technique (borderlin2-SMOTE), and feature reduction methods, to investigate the ability of exhaled breath to distinguish AC from SCC patients. The classification performance of the proposed method was compared with the results of four classification algorithms under different combinations of borderline2-SMOTE and feature reduction methods. The result indicated that the KNN classifier combining borderline2-SMOTE and feature reduction methods was the most promising method to discriminate AC from SCC patients and obtained the highest mean area under the receiver operating characteristic curve (0.63) and mean geometric mean (58.50) when compared to others classifiers. The result revealed that the combined algorithm could improve the classification performance of lung cancer subtypes in breathomics and suggested that combining non-invasive exhaled breath analysis with multivariate analysis is a promising screening method for informing treatment options and facilitating individualized treatment of lung cancer subtypes patients.

Decreased DC-SIGNR expression in hepatocellular carcinoma predicts poor patient prognosis

Dendritic cell-specific intercellular adhesion molecule-grabbing non-integrin-related protein (DC-SIGNR) is a transmembrane receptor primarily involved in pathogen recognition by the innate immune system, with particular importance for viral recognition. DC-SIGNR may also be associated with tumorigenesis. The aim of the present study was to investigate the association between DC-SIGNR expression, development of hepatocellular carcinoma (HCC), and clinicopathological features. Immunohistochemistry was used to assess DC-SIGNR protein expression in HCC and paired non-cancerous tissue samples. DC-SIGNR expression was lower in HCC tissues compared with adjacent non-tumor tissue samples. The expression of DC-SIGNR was associated with small tumor size, low Edmondson grade and high patient long term survival rates. Bioinformatics analyses were performed on several datasets to assess the potential function of DC-SIGNR and related genes; the data revealed that DC-SIGNR mRNA expression was lower in HCC tissues compared with non-cancerous controls, and analyses of ten-year survival rates indicated patients with low DC-SIGNR expression exhibited shorter average survival times. In conclusion, decreased DC-SIGNR expression in HCC tissues may be a relevant predictive biomarker of clinical prognosis, in addition to being a viable therapeutic target for HCC treatment.

Determination of urokinase-type plasminogen activator serum levels in healthy and oncologic cats

The urokinase plasminogen activator system (uPAS) has been poorly investigated in veterinary oncology. The aim of this study was to determine uPA serum concentrations in healthy and oncologic cats to understand the potential value of uPA as a cancer biomarker. Serum samples were collected from 19 healthy cats and 18 cats with spontaneous malignant neoplasms and uPA was measured through a specific enzyme-linked immunosorbent assay kit. The differences between uPA values and their relation with intrinsic factors and clinicopathological parameters were analyzed using an analysis of variance (ANOVA) and independent t-test. The average serum concentration of uPA in cancerous cats (0.54 ± 0.22 ng/mL) differed from that of healthy cats (1.10 ± 1.16 ng/mL) but was not significantly influenced by cats' clinicopathological parameters or by the presence of metastases. This study describes, for the first time, the serum concentrations of uPA in cats and proposes directions for future studies to uncover the relevance of uPAS in feline carcinogenesis.

Microtubule-associated tumor suppressors as prognostic biomarkers in breast cancer

PURPOSE

Breast cancer is the most common malignancy in women worldwide. Although important therapeutic progress was achieved over the past decade, this disease remains a public health problem. In light of precision medicine, the identification of new prognostic biomarkers in breast cancer is urgently needed to stratify populations of patients with poor clinical outcome who may benefit from new personalized therapies. The microtubule cytoskeleton plays a pivotal role in essential cellular functions and is an interesting target for cancer therapy. Microtubule assembly and dynamics are regulated by a wide range of microtubule-associated proteins (MAPs), some of which have oncogenic or tumor suppressor effects in breast cancer.

RESULTS

This review covers current knowledge on microtubule-associated tumor suppressors (MATS) in breast cancer and their potential value as prognostic biomarkers. We present recent studies showing that combinatorial expression of ATIP3 and EB1, two microtubule-associated biomarkers with tumor suppressor and oncogenic effects, respectively, improves breast cancer prognosis compared to each biomarker alone.

CONCLUSIONS

These findings are discussed regarding the increasing complexity of protein networks composed of MAPs that coordinate microtubule dynamics and functions. Further studies are warranted to evaluate the prognostic value of combined expression of different MATS and their interacting partners in breast cancer.

Is it true that gut microbiota is considered as panacea in cancer therapy?

Recent studies demonstrated that a combination of the gut microbiome has the vital effect on the efficacy of anticancer immune therapies. Regulatory effects of microbiota have been shown in different types of cancer therapies such as chemotherapy and immunotherapy. Immune-checkpoint-blocked therapies are the recent efficient cancer immunotherapy strategies. The target of immune-checkpoint blocking is cytotoxic T lymphocyte protein-4 (CTLA-4) or blockade of programmed death-1 (PD-1) protein and its ligand programmed death ligand 1 (PD-L1) that they have been considered as cancer immunotherapy in recent years. In the latest studies, it have been demonstrated that several gut bacteria such as Akkermansia muciniphila, Bifidobacterium spp., Faecalibacterium spp., and Bacteroides fragilis have the regulatory effects on PD-1, PD-L1, and CTLA-4 blocked anticancer therapy outcome.

Correlation Between Raf/MEK/ERK Signaling Pathway and Clinicopathological Features and Prognosis for Patients With Breast Cancer Having Axillary Lymph Node Metastasis

Objective:

This study aims to investigate the correlations between rapidly accelerated fibrosarcoma/mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase signaling pathway and clinicopathological features and prognosis for patients with breast cancer having axillary lymph node metastasis.

Methods:

A total of 118 breast cancer tissues with axillary lymph node metastasis (axillary lymph node metastasis group), 150 breast cancer tissues with non-axillary lymph node metastasis (non-axillary lymph node metastasis group), and 216 normal breast tissues (normal group) were enrolled in this study. The messenger RNA and protein expressions of rapidly accelerated fibrosarcoma, MEK, extracellular signal-regulated kinase, and their phosphorylated (p-) proteins were examined by reverse transcriptase quantitative polymerase chain reaction and immunohistochemistry, respectively. All patients received a 1-year follow-up, and the clinical follow-up data were collected. The multiple factors on the prognosis of patients with breast cancer having axillary lymph node metastasis were tested by Cox regression analysis.

Results:

The messenger RNA expressions of rapidly accelerated fibrosarcoma, MEK, and extracellular signal-regulated kinase and positive rates of rapidly accelerated fibrosarcoma, MEK, phosphorylated MEK, extracellular signal-regulated kinase, and p-extracellular signal-regulated kinase in the axillary lymph node metastasis group were higher than in the non-axillary lymph node metastasis and normal groups (all P < .05). The protein expressions of rapidly accelerated fibrosarcoma, MEK, phosphorylated MEK, extracellular signal-regulated kinase, and p-extracellular signal-regulated kinase were associated with tumor size, clinical stage, and axillary lymph node metastasis number (all P < .05). Rapidly accelerated fibrosarcoma, MEK, and extracellular signal-regulated kinase expressions were significantly correlated with the prognosis of patients with breast cancer (all P < .05). Patients with BC having positive rapidly accelerated fibrosarcoma, MEK, phosphorylated MEK, extracellular signal-regulated kinase, and phosphorylated ERK expressions had a higher survival rate than patients with BC having the negative ones (all P < .05). Rapidly accelerated fibrosarcoma and extracellular signal-regulated kinase protein expressions, clinical stage, pathological grade, and axillary lymph node metastasis number were independent prognostic factors in patients with breast cancer having axillary lymph node metastasis (all P < .05).

Conclusion:

Our study proved that rapidly accelerated fibrosarcoma/MEK/extracellular signal-regulated kinase signaling pathway is significantly correlated with the clinicopathological features and prognosis for patients with BC having axillary lymph node metastasis. Rapidly accelerated fibrosarcoma and extracellular signal-regulated kinase protein expressions are independent prognostic factors for patients with breast cancer having axillary lymph node metastasis.

Metabolomic profiling of human lung tumor tissues - nucleotide metabolism as a candidate for therapeutic interventions and biomarkers

Although metabolomics has attracted considerable attention in the field of lung cancer (LC) detection and management, only a very limited number of works have applied it to tissues. As such, the aim of this study was the thorough analysis of metabolic profiles of relevant LC tissues, including the most important histological subtypes (adenocarcinoma and squamous cell lung carcinoma). Mass spectrometry‐based metabolomics, along with genetic expression and histological analyses, were performed as part of this study, the widest to date, to identify metabolic alterations in tumors of the most relevant histological subtypes in lung. A total of 136 lung tissue samples were analyzed and 851 metabolites were identified through metabolomic analysis. Our data show the existence of a clear metabolic alteration not only between tumor vs. nonmalignant tissue in each patient, but also inherently intrinsic changes in both AC and SCC. Significant changes were observed in the most relevant biochemical pathways, and nucleotide metabolism showed an important number of metabolites with high predictive capability values. The present study provides a detailed analysis of the metabolomic changes taking place in relevant biochemical pathways of the most important histological subtypes of LC, which can be used as biomarkers and also to identify novel targets.

RETRACTED: Downregulation of lncRNA GAS5 confers tamoxifen resistance by activating miR-222 in breast cancer

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief. Upon investigation, it was discovered that 5 figures contain fabrication. Figures 1C, 3D, 5C, 5D, and 6G contain manipulated and/or duplicated data. The authors requested a corrigendum be published, however, due to the large number of corrections applied (figures 3, 6, 7, 8 and S3), it cannot be concluded that these changes would not alter the conclusions of the paper. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

Molecular paleopathology and paleo-oncology-State of the art, potentials, limitations and perspectives

This paper reviews the current knowledge on molecular paleopathology with respect to oncological information. This covers both the information on the protein level (proteome) as well as the gene level (genome) and includes data on carcinogenic factors - such as molecular evidence for oncogenic viral infections. Currently, relatively little data is available for neoplastic disease in paleopathology. Likewise, few studies describe the biochemical or immunohistochemical analysis of tumors - a tool to potentially classify the tumor type and the underlying primary tumor in metastases. On the gene level, two studies described distinct molecular mutations in either a tumor-driving oncogene or a tumor suppressor gene, both being excellent examples for paleo-oncological studies. The paucity of historic tumor material - particularly when only osseous remains are available - represents the most hindering factor for molecular paleo-oncology. This can only be overcome in future by both the thorough investigation of mummified archaeological biomaterial and the improvement of analytical assays in order to trace even minute amounts of tumor material in osseous lesions.

Microbiota effects on cancer: from risks to therapies

Gut microbiota, a group of 1014 bacteria, eukaryotes and virus living in gastrointestinal tract, is crucial for many physiological processes in particular plays an important role in inflammatory and immune reactions. Several internal and external factors can influence this population, and shifts in their composition, have been demonstrated to contribute and affect different diseases. During dysbiosis several bacteria related to inflammation, one of the most necessary factors in carcinogenesis; it has been shown that some bacterial strains through deregulation of different signals/pathways may affect tumor development through the production of many factors. Gut microbiota might be considered as a holistic hub point for cancer development: direct and indirect involvements have been studying in several neoplasms such as colon rectal cancer, hepatocellular carcinoma and breast cancer. This review discuss over the evidence of crosstalk between gut microbiota and cancer, its ability to modulate chemotherapy, radiotherapy and immunotherapy, and the possibility that the intestinal microbial is a new target for therapeutic approaches to improve the prognosis and quality of life of cancer patients.

Human salivary microRNAs in Cancer

Circulating microRNAs (miRNAs) have emerged as excellent candidates for cancer biomarkers. Several recent studies have highlighted the potential use of saliva for the identification of miRNAs as novel biomarkers, which represents a great opportunity to improve diagnosis and monitor general health and disease. This review summarises the mechanisms of miRNAs deregulation in cancer, the value of targeting them with a therapeutic intention and the evidence of the potential clinical use of miRNAs expressed in saliva for the detection of different cancer types. We also provide a comprehensive review of the different methods for normalising the levels of specific miRNAs present in saliva, as this is a critical step in their analysis, and the challenge to validate salivary miRNAs as a reality to manage cancer patients.

Development of LC-QTOF-MS method for human lung tissue fingerprinting. A preliminary application to nonsmall cell lung cancer

The major histologic subtypes of non-small cell lung cancer (NSCLC) include adenocarcinoma (ADC), squamous cell lung carcinoma (SCC), and large-cell carcinoma (LCC). Clinical trials of targeted agents and newer chemotherapy agents yielded differences in outcomes according to histologic subgroups providing a rationale for histology-based treatment in NSCLC. Currently, NSCLC subtyping is performed based on histopathological examinations and immunohistochemistry. However available methods leave about 10% of NSCLC cases as not otherwise specified. The purpose of this study was development of an LC-QTOF-MS method for human lung tissue metabolic fingerprinting that could discriminate NSCLC histological subtypes and propose biomarkers candidates that could support proper NSCLC diagnosis. Metabolites were extracted with acetonitrile or methanol/ethanol and different chromatographic conditions were tested. In the final method 10 mg of lung tissue was homogenized with 50% methanol and metabolites were extracted with acetonitrile. Metabolites were separated on C8-RP and HILIC columns. About 3500 and 2000 of metabolic features (in both ion modes) were detected with good repeatability (CV < 20%) by RP and HILIC methods, respectively. Lung tumor and control tissue samples obtained from NSCLC patients were analyzed with developed methodology. Acylcarnitines, fatty acids, phospholipids, and amino acids were found more abundant in tumor as compared to control tissue. Acylcarnitines, lysophospholipids, creatinine, creatine, and alanine were identified as potential targets enabling classification of NSCLC subtypes.