Reactive oxygen species (ROS) are by-products of normal cell activity. They are produced in many cellular compartments and play a major role in signaling pathways. Overproduction of ROS is associated ...with the development of various human diseases (including cancer, cardiovascular, neurodegenerative, and metabolic disorders), inflammation, and aging. Tumors continuously generate ROS at increased levels that have a dual role in their development. Oxidative stress can promote tumor initiation, progression, and resistance to therapy through DNA damage, leading to the accumulation of mutations and genome instability, as well as reprogramming cell metabolism and signaling. On the contrary, elevated ROS levels can induce tumor cell death. This review covers the current data on the mechanisms of ROS generation and existing antioxidant systems balancing the redox state in mammalian cells that can also be related to tumors.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
—Tomato aspermy virus (TAV, genus
Cucumovirus
from the family Bromoviridae) is one of the most common and harmful chrysanthemum viruses, causing severe flower distortion, size reduction, and color ...breaking. Metatranscriptome sequencing of chrysanthemum plants of the Ribonette and Golden Standard cultivars from the collection of the Nikita Botanical Garden (Yalta, Republic of Crimea) generated TAV‑related RNA reads. The complete genomes of two Russian isolates of the virus were assembled from the reads. This is the first report of full-length TAV genomes from Russia. Typically of cucumoviruses, the segmented TAV genome is represented by three single-stranded positive-sense linear RNA molecules of 3412 (RNA1), 3097 (RNA2) and 2219 (RNA3) nucleotides. Five open reading frames (ORF) have been identified that encode replicase (ORF1), RNA-dependent RNA polymerase (ORF2a), silencing suppressor protein (OFR2b), movement protein (OFR3a) and the coat protein (ORF3b). The identity of TAV genomes from the two chrysanthemum cultivars was 99.8% for all three viral RNAs; with other TAV isolates from GenBank it was 97.5–99.7% (RNA1), 93.8–99.8% (RNA2), and 89.3–99.3% (RNA3). Phylogenetic analysis showed that RNA1 and RNA3 of the Russian isolates were assigned to heterogeneous groups of TAV isolates found on various plant species in different regions of the world. At the same time, RNA2 clearly clustered with tomato isolates SKO20ST2 from Slovenia and PV-0220 from Bulgaria and, to a lesser extent, with the Iranian isolate Ker.Mah.P from petunia and the Chinese isolate Henan from chrysanthemum. The incongruence of phylogenetic trees reconstructed from different genome segments suggests pseudo-recombination (reassortment) in the Russian TAV isolates.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors of the head and neck. “Germline” and somatic mutations in a number of genes were shown to be associated with the development of CPGLs; ...however, molecular mechanisms of the tumor pathogenesis have not been fully understood. In the work, we have used whole exome sequencing data of 52 CPGLs obtained earlier. Using MutSigCV, the search for genes with high mutation rate was performed. Thirty four genes (
MADCAM1
,
SARM1
,
ZFPM1
,
CTDSP2
,
DSPP
,
POTED
,
ANP32B
,
FRG2B
,
BAGE3
,
CCDC89
,
ACOT2
,
KRTAP10-1
,
ATXN1
,
GXYLT1
,
MUC2
,
AQP7
,
TMPRSS13
,
KRTAP4-3
,
PRR21
,
PSPH
,
PLBD1
,
ZNF595
,
IGSF3
,
PRR16
,
FAM157A
,
KCNJ12
,
HYDIN
,
IGFBP2
,
KIAA1671
,
DISC1
,
MUC6
,
XKR3
,
HRNR
, and
MUC4
) potentially associated with the CPGL initiation and progression were revealed. The involvement of these genes in the pathogenesis of CPGLs was first shown, and possible mechanisms of their participation in that were discussed.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Regulation of gene expression via microRNA is the key mechanism of response to biotic and abiotic stresses in plants. There are a lot of experimental data on the biological function of microRNAs in ...response to different stresses in various plant species. This review contains up-to-date information on molecular mechanisms of microRNA action in plants in response to abiotic stresses, including drought, salinity, mineral nutrient deficiency or imbalance.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
One important question in aging research is how differences in genomics and transcriptomics determine the maximum lifespan in various species. Despite recent progress, much is still unclear on the ...topic, partly due to the lack of samples in nonmodel organisms and due to challenges in direct comparisons of transcriptomes from different species. The novel ranking‐based method that we employ here is used to analyze gene expression in the gray whale and compare its de novo assembled transcriptome with that of other long‐ and short‐lived mammals. Gray whales are among the top 1% longest‐lived mammals. Despite the extreme environment, or maybe due to a remarkable adaptation to its habitat (intermittent hypoxia, Arctic water, and high pressure), gray whales reach at least the age of 77 years. In this work, we show that long‐lived mammals share common gene expression patterns between themselves, including high expression of DNA maintenance and repair, ubiquitination, apoptosis, and immune responses. Additionally, the level of expression for gray whale orthologs of pro‐ and anti‐longevity genes found in model organisms is in support of their alleged role and direction in lifespan determination. Remarkably, among highly expressed pro‐longevity genes many are stress‐related, reflecting an adaptation to extreme environmental conditions. The conducted analysis suggests that the gray whale potentially possesses high resistance to cancer and stress, at least in part ensuring its longevity. This new transcriptome assembly also provides important resources to support the efforts of maintaining the endangered population of gray whales.
Long‐lived mammals (whales, humans, naked mole‐rat) share common transcription patterns, including high expression of genes for DNA repair, autophagy, ubiquitination, apoptosis, and immune responses. Additionally, the expression of gray whale orthologs of pro‐ and anti‐longevity genes found in model organisms coincides well with their effects on lifespan. Our results suggest that gray whales might possess high resistance to cancer and stress, ensuring at least in part their longevity.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Cell metabolic reprogramming is one of the cancer hallmarks. Glycolysis activation, along with suppression of oxidative phosphorylation and, to a lower extent, the TCA cycle, occurs in the majority ...of malignant tumors. A bioinformatics search for the glucose metabolism genes that are differentially expressed in colorectal cancer (CC) was performed using the data of The Cancer Genome Atlas (TCGA) Project.
OGDHL
for an oxoglutarate dehydrogenase complex subunit, which is involved in the TCA cycle and is indirectly responsible for the induction of apoptosis, was identified as one of the most promising candidates. A quantitative PCR analysis showed, on average, an eightfold downregulation of
OGDHL
in 50% (15/30) of CC samples. Based on the TCGA data, promoter hypermethylation was assumed to be a major mechanism of
OGDHL
inactivation. Bisulfite sequencing identified the
OGDHL
promoter region (+327…+767 relative to the transcription start site) that is often methylated in CC samples with downregulated
ODGHL
expression (80%, 8/10) and is possibly crucial for gene inactivation. Thus, frequent and significant
OGDHL
downregulation due to hypermethylation of a specific promoter region was demonstrated for CC. The
OGDHL
promoter methylation pattern was assumed to provide a marker for differential diagnosis of CIMP
+
(CpG island methylator phenotype) tumors, which display dense hypermethylation of the promoter region in many genes.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Glycolysis activation is one of the main features of energy metabolism in cancer cells that is associated with the increase in glycolytic enzyme synthesis, primarily, hexokinases (HKs), in many types ...of tumors. Conversely, in colorectal cancer (CRC) the decrease in the expression of
HK2
gene, which encodes one of the key rate-limiting enzyme of glycolysis, was revealed, thus, the study of the mechanisms of its inhibition in CRC is of particular interest. To search for potential microRNAs, inhibiting the expression of
HK2
in CRC, we have performed the analysis of data from “The Cancer Genome Atlas” (TCGA) and five microRNA–mRNA target interaction databases (TargetScan, DIANA microT, mirSVR (miRanda), PicTar, and miRTarBase) using original CrossHub software. Seven microRNAs containing binding site on mRNA
HK2
, which expression is negatively correlated with
HK2
expression, were selected for further analysis. The expression levels of these microRNAs and mRNA
HK2
were estimated by quantitative PCR on a set of CRC samples. It has been shown, that the expression of three microRNAs (miR-9-5p, -98-5p, and -199-5p) was increased and correlated negatively with mRNA level of
HK2
gene. Thus, downregulation of
HK2
gene may be caused by its negative regulation through microRNAs miR-9-5p, -98-5p, and -199-5p.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Understanding the molecular mechanisms of plant response to unfavorable conditions is necessary for the effective selection of tolerant genotypes. Earlier, using high-throughput transcriptome ...sequencing of flax plants after exposure to aluminum ions (Al
3+
) and high soil acidity, we detected stress-induced alteration in the expression of several genes, including
CAX3
, which encodes Ca
2+
/H
+
-exchanger involved in calcium ion transport. Here we describe
CAX3
mRNA levels in flax cultivars either tolerant (Hermes and TMP1919) or sensitive (Lira and Orshanskiy) to Al
3+
. Stress-induced increased expression of
CAX3
was detected only in aluminum-tolerant flax cultivars. The product of
CAX3
gene may participate in flax response to high soil acidity and high Al
3+
concentration through Ca
2+
-mediated intracellular regulation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Following radical surgery, patients may suffer a relapse. It is important to identify such patients so that therapy tactics can be modified appropriately. Existing stratification schemes do not ...display the probability of recurrence with enough precision since locally advanced prostate cancer (PCa) is classified as high-risk but is not ranked in greater detail. Between 40 and 50% of PCa cases belong to the TMPRSS2-ERG subtype that is a sufficiently homogeneous group for high-precision prognostic marker search to be possible. This study includes two independent cohorts and is based on high throughput sequencing and qPCR data. As a result, we have been able to suggest a perspective-trained model involving a deep neural network based on both qPCR data for mRNA and miRNA and clinicopathological criteria that can be used for recurrence risk forecasts in patients with TMPRSS2-ERG-positive, locally advanced PCa (the model uses ALDH3A2 + ODF2 + QSOX2 + hsa-miR-503-5p + ISUP + pT, with an AUC = 0.944). In addition to the prognostic model’s use of identified differentially expressed genes and miRNAs, miRNA–target pairs were found that correlate with the prognosis and can be presented as an interactome network.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Quantitative PCR (qPCR) remains the most widely used technique for gene expression evaluation. Obtaining reliable data using this method requires reference genes (RGs) with stable mRNA level under ...experimental conditions. This issue is especially crucial in cancer studies because each tumor has a unique molecular portrait. The Cancer Genome Atlas (TCGA) project provides RNA-Seq data for thousands of samples corresponding to dozens of cancers and presents the basis for assessment of the suitability of genes as reference ones for qPCR data normalization. Using TCGA RNA-Seq data and previously developed CrossHub tool, we evaluated mRNA level of 32 traditionally used RGs in 12 cancer types, including those of lung, breast, prostate, kidney, and colon. We developed an 11-component scoring system for the assessment of gene expression stability. Among the 32 genes,
was one of the most stably expressed in the majority of examined cancers, whereas
, which is widely used as a RG, showed significant mRNA level alterations in more than a half of cases. For each of 12 cancer types, we suggested a pair of genes that are the most suitable for use as reference ones. These genes are characterized by high expression stability and absence of correlation between their mRNA levels. Next, the scoring system was expanded with several features of a gene: mutation rate, number of transcript isoforms and pseudogenes, participation in cancer-related processes on the basis of Gene Ontology, and mentions in PubMed-indexed articles. All the genes covered by RNA-Seq data in TCGA were analyzed using the expanded scoring system that allowed us to reveal novel promising RGs for each examined cancer type and identify several "universal" pan-cancer RG candidates, including
, and
. The choice of RGs is the basis for precise gene expression evaluation by qPCR. Here, we suggested optimal pairs of traditionally used RGs for 12 cancer types and identified novel promising RGs that demonstrate high expression stability and other features of reliable and convenient RGs (high expression level, low mutation rate, non-involvement in cancer-related processes, single transcript isoform, and absence of pseudogenes).
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