Low selenium (Se) status correlates with increased risk of colorectal cancer (CRC). Since Se exerts its biological roles through the selenoproteins, genetic variations in selenoprotein genes may influence susceptibility to CRC. This study analysed 12 single-nucleotide polymorphisms (SNPs) in selenoprotein genes [glutathione peroxidase 1 (GPX1), GPX4, 15 kDa selenoprotein (SEP15), selenoprotein S (SELS), selenoprotein P (SEPP1) and thioredoxin reductase 2 (TXNRD2)] and in genes that code for a key protein in Se incorporation [SECIS-binding protein 2 (SBP2)] and in antioxidant defence [superoxide dismutase 2 (SOD2)] in relation to sporadic CRC incidence. CRC patients (832) and controls (705) from the Czech Republic were genotyped using allele specific PCR. Logistic regression analysis showed that three SNPs were significantly associated with an altered risk of CRC: rs7579 (SEPP1), rs713041 (GPX4) and rs34713741 (SELS). The association of these SNPs with disease risk remained after data stratification for diagnosis and adjustments for lifestyle factors and sex. Significant two-loci interactions were observed between rs4880 (SOD2), rs713041 (GPX4) and rs960531 (TXNRD2) and between SEPP1 and either SEP15 or GPX4. The results indicate that SNPs in SEPP1, GPX4 and SELS influence risk of CRC. We hypothesize that the two-loci interactions reflect functional interactions between the gene products. We propose that these variants play a role in cancer development and represent potential biomarkers of CRC risk.

ABCA12, ABCA13, ABCC1, ABCC8 and ABCD2 present potential modifiers of progression and response to the chemotherapy of breast carcinoma.

Esophageal and gastric cancers represent tumors with poor prognosis. Unfortunately, radiotherapy, chemotherapy, and targeted therapy have made only limited progress in recent years in improving the generally disappointing outcome. Immunotherapy with checkpoint inhibitors is a novel treatment approach that quickly entered clinical practice in malignant melanoma and renal cell cancer, but the role in esophageal and gastric cancer is still poorly defined. The principal prognostic/predictive biomarkers for immunotherapy efficacy currently considered are PD-L1 expression along with defects in mismatch repair genes resulting in microsatellite instability (MSI-H) phenotype. The new molecular classification of gastric cancer also takes these factors into consideration. Available reports regarding PD-1, PD-L1, PD-L2 expression and MSI status in gastric and esophageal cancer are reviewed to summarize the clinical prognostic and predictive role together with potential clinical implications. The most important recently published clinical trials evaluating checkpoint inhibitor efficacy in these tumors are also summarized.

The comprehensive approach for the lipidomic characterization of human breast cancer and surrounding normal tissues is based on hydrophilic interaction liquid chromatography (HILIC)-electrospray ionization mass spectrometry (ESI-MS) quantitation of polar lipid classes of total lipid extracts followed by multivariate data analysis using unsupervised principal component analysis (PCA) and supervised orthogonal partial least square (OPLS). This analytical methodology is applied for the detailed lipidomic characterization of ten patients with the goal to find the statistically relevant differences between tumor and normal tissues. This strategy is selected for better visualization of differences, because the breast cancer tissue is compared with the surrounding healthy tissue of the same patient, therefore changes in the lipidome are caused predominantly by the tumor growth. A large increase of total concentrations for several lipid classes is observed, including phosphatidylinositols, phosphatidylethanolamines, phosphatidylcholines, and lysophosphatidylcholines. Concentrations of individual lipid species inside the abovementioned classes are also changed, and in some cases, these differences are statistically significant. PCA and OPLS analyses enable a clear differentiation of tumor and normal tissues based on changes of their lipidome. A notable decrease of relative abundances of ether and vinylether (plasmalogen) lipid species is detected for phosphatidylethanolamines, but no difference is apparent for phosphatidylcholines.

Associations of transcript levels of oxidative stress-modifying genes SOD2, SOD3, NQO1 and NQO2 and their functional single nucleotide polymorphisms (SNPs) rs4880, rs1799895, rs2536512, rs699473, rs1800566 and rs1143684 with prognosis of breast cancer patients were studied. SNPs were assessed by allelic discrimination in a cohort of 321 breast cancer patients from the Czech Republic. Transcript levels were determined by real-time polymerase chain reaction (PCR) with absolute quantification in tumor and adjacent non-neoplastic control tissues. Both genotypes and transcript levels were then compared with available clinical data on patients. Patients carrying low activity allele Leu in NQO2 rs1143684 had a greater incidence of stage 0 or I disease (i.e., better prognosis) than patients with the Phe/Phe genotype. This association was more evident in patients without expression of progesterone receptors (p 5 0.031). Patients carrying the Thr allele in SOD3 rs2536512 SNP had a significantly greater incidence of tumors expressing estrogen receptors than patients carrying the Ala/Ala genotype (p 5 0.007). SOD3 transcript level was significantly higher in grade 1 or 2 tumors than in grade 3 tumors (p 5 0.006). Patients carrying T allele in SOD3 rs699473 SNP had significantly poorer progression-free survival (PFS) than patients carrying the CC genotype (p 5 0.038). The same applied to the subgroup of patients treated by hormonal regimens (p 5 0.021). Patients carrying the high activity Ala/Ala genotype in SOD2 (rs4880) had significantly poorer PFS than Val allele carriers in the group treated by cyclophosphamide but not hormonal regimens (p 5 0.004). Our results suggest that NQO2, SOD2 and SOD3 may significantly modify prognosis of breast cancer patients and that their significance should be further characterized.Breast cancer is the most common cancer in women. In 2008, about 1,383,523 new cases of invasive breast cancer were diagnosed worldwide. 1 The necessity of treating such a large number of patients calls for efficient tools that can be used for subgrouping patients according to estimated prognosis. A different spectrum of treatment modalities with diverse mechanisms of action and adverse effects could then be offered to various prognostic groups. Besides well-established classical prognostic factors such as tumor size, nodal status, grading and expression of hormonal receptors, numerous biological molecules are under investigation as potential prognostic biomarkers in breast carcinomas.Excess of oxidative stress, mediated by reactive oxygen species, may cause cellular deregulation leading to cell apoptosis, 2 proliferation or tumor promotion. 3 Alkylation and topoisomerase poisoning present the major mechanisms of action of cyclophosphamide and anthracyclines, respectively. Oxidative stress represents an additional cytotoxic mechanism. 4,5 One of the initial molecules of oxidative stress, superoxide anion radical, is formed by the univalent reduction of triplet-state molecular oxygen. This process is mediated by e...

Matrix-assisted laser desorption/ionization coupled with Orbitrap mass spectrometry (MALDI-Orbitrap-MS) is used for the clinical study of patients with renal cell carcinoma (RCC), as the most common type of kidney cancer. Significant changes in sulfoglycosphingolipid abundances between tumor and autologous normal kidney tissues are observed. First, sulfoglycosphingolipid species in studied RCC samples are identified using high mass accuracy full scan and tandem mass spectra. Subsequently, optimization, method validation, and statistical evaluation of MALDI-MS data for 158 tissues of 80 patients are discussed. More than 120 sulfoglycosphingolipids containing one to five hexosyl units are identified in human RCC samples based on the systematic study of their fragmentation behavior. Many of them are recorded here for the first time. Multivariate data analysis (MDA) methods, i.e., unsupervised principal component analysis (PCA) and supervised orthogonal partial least square discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples to reveal the most up- and downregulated lipids in tumor tissues. Obtained results are closely correlated with MALDI mass spectrometry imaging (MSI) and histologic staining. Important steps of the present MALDI-Orbitrap-MS approach are also discussed, such as the selection of best matrix, correct normalization, validation for semiquantitative study, and problems with possible isobaric interferences on closed masses in full scan mass spectra. Graphical Abstract ᅟ.

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