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Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

Metabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I–IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476–0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.

Incomplete understanding of the metastatic process hinders personalized therapy. Here we report the most comprehensive whole-genome study of colorectal metastases vs. matched primary tumors. 65% of somatic mutations originate from a common progenitor, with 15% being tumor- and 19% metastasis-specific, implicating a higher mutation rate in metastases. Tumor- and metastasis-specific mutations harbor elevated levels of BRCAness. We confirm multistage progression with new components ARHGEF7/ARHGEF33 . Recurrently mutated non-coding elements include ncRNAs RP11-594N15.3, AC010091, SNHG14 , 3’ UTRs of FOXP2, DACH2, TRPM3, XKR4, ANO5, CBL, CBLB , the latter four potentially dual protagonists in metastasis and efferocytosis-/ PD-L1 mediated immunosuppression. Actionable metastasis-specific lesions include FAT1, FGF1, BRCA2, KDR , and AKT2 -, AKT3 -, and PDGFRA -3’ UTRs. Metastasis specific mutations are enriched in PI3K-Akt signaling, cell adhesion, ECM and hepatic stellate activation genes, suggesting genetic programs for site-specific colonization. Our results put forward hypotheses on tumor and metastasis evolution, and evidence for metastasis-specific events relevant for personalized therapy. The evolution and genetic nature of metastatic lesions is not completely characterized. Here the authors perform a comprehensive whole-genome study of colorectal metastases in comparison to matched primary tumors and define a multistage progression model and metastasis-specific changes that, in part, are therapeutically actionable.

A comparative analysis of blood samples (depleted of albumin and IgG) obtained from lung cancer patients before chemotherapy versus after a second cycle of chemotherapy was performed using two-dimensional difference gel electrophoresis (2D-DIGE). The control group consisted of eight patients with non-cancerous lung diseases, and the experimental group consisted of four adenocarcinoma (ADC) and four squamous cell carcinoma (SCC) patients. Analyses of gels revealed significant changes in proteins and/or their proteoforms between control patients and lung cancer patients, both before and after a second cycle of chemotherapy. Most of these proteins were related to inflammation, including acute phase proteins (APPs) such as forms of haptoglobin and transferrin, complement component C3, and clusterin. The variable expression of APPs can potentially be used for profiling lung cancer. The greatest changes observed after chemotherapy were in transferrin and serotransferrin, which likely reflect disturbances in iron turnover after chemotherapy-induced anaemia. Significant changes in plasma proteins between ADC and SCC patients were also revealed, suggesting use of plasma vitronectin as a potential marker of SCC.

Obesity is a new risk factor, to which more and more research is devoted, related to the development of cancer. Many studies of recent years have drawn attention to the role of adipose tissue as an important internal endocrine organ. In the adipose tissue proteins are produced, referred to by the common name as adipokines. In the case of obesity, the neoplasm cells are constantly stimulated by pro-inflammatory cytokines and adipokines, among which leptin dominates. The studies show that leptin can affect the cancer cells through numerous phenomena, e.g. inflammation, cell proliferation, suppression of apoptosis and angiogenesis. In this literature review we examined the role of leptin in the development of the individual cancers: breast cancer, colorectal cancer, prostate cancer, ovarian cancer, endometrial cancer and brain neoplasms: glioma and meningioma. However, leptin has very complicated mechanisms of action which require better understanding in certain types of cancer.

Epithelial ovarian cancer (EOC) is one of the leading cancers in women, with high-grade serous ovarian cancer (HGSOC) being the most common and lethal subtype of this disease. A vast majority of HGSOC are diagnosed at the late stage of the disease when the treatment and total recovery chances are low. Thus, there is an urgent need for novel, more sensitive and specific methods for early and routine HGSOC clinical diagnosis. In this study, we performed miRNA expression profiling using the NanoString miRNA assay in 34 serum samples from patients with HGSOC and 36 healthy women. We identified 13 miRNAs that were differentially expressed (DE). For additional exploration of expression patterns correlated with HGSOC, we performed weighted gene co-expression network analysis (WGCNA). As a result, we showed that the module most correlated with tumour size, nodule and metastasis contained 8 DE miRNAs. The panel including miR-1246 and miR-150-5p was identified as a signature that could discriminate HGSOC patients with AUCs of 0.98 and 1 for the training and test sets, respectively. Furthermore, the above two-miRNA panel had an AUC = 0.946 in the verification cohorts of RT-qPCR data and an AUC = 0.895 using external data from the GEO public database. Thus, the model we developed has the potential to markedly improve the diagnosis of ovarian cancer.

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

(1) Background: The novel hybrid of positron emission tomography/magnetic resonance (PET/MR) examination has been introduced to clinical practice. The aim of our study was to evaluate PET/MR usefulness in preoperative staging of head and neck cancer (HNC) patients (pts); (2) Methods: Thirty eight pts underwent both computed tomography (CT) and PET/MR examination, of whom 21 pts underwent surgical treatment as first-line therapy and were further included in the present study. Postsurgical tissue material was subjected to routine histopathological (HP) examination with additional evaluation of p16, human papillomavirus (HPV), Epstein-Barr virus (EBV) and Ki67 status. Agreement of clinical and pathological T staging, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of CT and PET/MR in metastatic lymph nodes detection were defined. The verification of dependences between standardized uptake value (SUV value), tumor geometrical parameters, number of metastatic lymph nodes in PET/MR and CT, biochemical parameters, Ki67 index, p16, HPV and EBV status was made with statistical analysis of obtained results; (3) Results: PET/MR is characterized by better agreement in T staging, higher specificity, sensitivity, PPV and NPV of lymph nodes evaluation than CT imaging. Significant correlations were observed between SUVmax and maximal tumor diameter from PET/MR, between SUVmean and CT tumor volume, PET/MR tumor volume, maximal tumor diameter assessed in PET/MR. Other correlations were weak and insignificant; (4) Conclusions: Hybrid PET/MR imaging is useful in preoperative staging of HNC. Further studies are needed.

The diagnosis of brain gliomas is mainly based on imaging methods. The gold standard in this area is MRI. Recommendations for the prevention, diagnosis, and treatment of gliomas are periodically modified and updated. One of the diagnostic techniques used when a brain glioma is suspected is liquid biopsy. However, this technique requires further development to confirm its effectiveness. This paper presents a proposal of three potential biomarkers of brain gliomas—extracellular matrix metalloproteinase-1 (MMP-1), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and the 20S proteasome—which were quantified in blood plasma using SPRi biosensors. A statistical analysis of the results indicated no significant changes in the concentrations between the control group (K) and grades G1 and G2, and similarly between grades G3 and G4. However, the differences in the concentrations between the groups K/G1/G2 and G3/G4 were statistically significant. A positive average correlation was found between the concentrations of the proteins and the patient’s age. The individual tested proteins were also highly correlated with each other. Our work proposes a new diagnostic technique that may aid in the diagnosis of brain gliomas.

The presented work is based on the quantification of LN-5, FN, and COL IV in blood plasma as potential biomarkers in patients diagnosed with glioma in grades G1 to G4. The obtained concentration results were compared with the protein content in the control group, which consisted of smokers of different ages. The obtained results were statistically analysed and interpreted based on the available clinical description. Quantitative determinations of LN-5, FN, and COL IV were performed with the use of SPRi biosensors specific to the tested proteins. Comparing groups K and G4, as well as G2 and G4, statistically significant relationships between changes in the concentration of individual proteins, were observed. The analysis showed significant correlations between FN and LN-5, between FN and COL IV, and between LN-5 and COL IV. There was a moderate positive correlation between individual proteins and the age of the patient. The ROC analysis distinguished patients with advanced disease from the control group. The results of the research show that LN-5, FN, and COL IV are effective biomarkers of brain glioma that may be helpful in non-invasive diagnosis and determining the grade of the disease.