SDHx mutations are associated with the PI3K-Akt signaling pathway in vagal paragangliomas

Background: Vagal paraganglioma (VPGL) is a very rare neuroendocrine tumor arising from the paraganglion associated with the vagus nerve. VPGL is mainly characterized by an asymptomatic course and slow growth. However, up to 19% of tumors can metastasize. Due to the rarity of this tumor, information about VPGL is limited to single cases and small sample sets; the data on molecular genetic features is extremely scarce. Methods: For the first time we have analyzed the enrichment of biological pathways associated with mutations in the SDHx genes in VPGLs. Bioinformatics analysis was performed based on the results of high-throughput transcriptome sequencing on an Illumina platform for 33 tumor tissues obtained from patients with vagal paragangliomas. Results: Eight pathways of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database with gene overrepresentation (top-40 mode) have been identified. Significant changes were shown for the cancer-associated PI3K-Akt signaling pathway and interconnected pathways of focal adhesion and interaction of receptors with the extracellular matrix enriched by overexpressed genes. Conclusion: Our result indicates the association of SDHx mutations with changes in the PI3K-Akt signaling pathway in vagal paraganglioma. The potential mechanism of deregulation in this pathway could be linked with a state of pseudohypoxia induced by the dysfunction of succinate dehydrogenase due to mutations in the SDHx genes

<i>ALDH3A2</i>, <i>ODF2</i>, <i>QSOX2</i>, and MicroRNA-503-5p Expression to Forecast Recurrence in <i>TMPRSS2-ERG</i>-Positive Prostate Cancer

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

Impact TMPRSS2–ERG Molecular Subtype on Prostate Cancer Recurrence

Currently, seven molecular subtypes of prostate cancer (PCa) are known, the most common of which being the subtype characterized by the presence of the TMPRSS2–ERG fusion transcript. While there is a considerable amount of work devoted to the influence of this transcript on the prognosis of the disease, data on its role in the progression and prognosis of PCa remain controversial. The present study is devoted to the analysis of the association between the TMPRSS2–ERG transcript and the biochemical recurrence of PCa. The study included two cohorts: the RNA–Seq sample of Russian patients with PCa (n = 72) and the TCGA–PRAD data (n = 203). The results of the analysis of the association between the TMPRSS2–ERG transcript and biochemical recurrence were contradictory. The differential expression analysis (biochemical recurrence cases versus biochemical recurrence-free) and the gene set enrichment analysis revealed a list of genes involved in major cellular pathways. The GNL3, QSOX2, SSPO, and SYS1 genes were selected as predictors of the potential prognostic model (AUC = 1.000 for a cohort of Russian patients with PCa and AUC = 0.779 for a TCGA–PRAD cohort)

Lymphatic Dissemination in Prostate Cancer: Features of the Transcriptomic Profile and Prognostic Models

Radical prostatectomy is the gold standard treatment for prostate cancer (PCa); however, it does not always completely cure PCa, and patients often experience a recurrence of the disease. In addition, the clinical and pathological parameters used to assess the prognosis and choose further tactics for treating a patient are insufficiently informative and need to be supplemented with new markers. In this study, we performed RNA-Seq of PCa tissue samples, aimed at identifying potential prognostic markers at the level of gene expression and miRNAs associated with one of the key signs of cancer aggressiveness—lymphatic dissemination. The relative expression of candidate markers was validated by quantitative PCR, including an independent sample of patients based on archival material. Statistically significant results, derived from an independent set of samples, were confirmed for miR-148a-3p and miR-615-3p, as well as for the CST2, OCLN, and PCAT4 genes. Considering the obtained validation data, we also analyzed the predictive value of models based on various combinations of identified markers using algorithms based on machine learning. The highest predictive potential was shown for the “CST2 + OCLN + pT” model (AUC = 0.863) based on the CatBoost Classifier algorithm

Mutational load in carotid body tumor

Abstract Background Carotid body tumor (CBT) is a rare neoplasm arising from paraganglion located near the bifurcation of the carotid artery. There is great intra-tumor heterogeneity, and CBT development could be associated with both germline and somatic allelic variants. Studies on the molecular genetics of CBT are limited, and the molecular mechanisms of its pathogenesis are not fully understood. This work is focused on the estimation of mutational load (ML) in CBT. Methods Using the NextSeq 500 platform, we performed exome sequencing of tumors with matched lymph node tissues and peripheral blood obtained from six patients with CBT. To obtain reliable results in tumors with low ML, we developed and successfully applied a complex approach for the analysis of sequencing data. ML was evaluated as the number of somatic variants per megabase (Mb) of the target regions covered by the Illumina TruSeq Exome Library Prep Kit. Results The ML in CBT varied in the range of 0.09–0.28/Mb. Additionally, we identified several pathogenic/likely pathogenic somatic and germline allelic variants across six patients studied (including TP53 variants). Conclusions Using the developed approach, we estimated the ML in CBT, which is much lower than in common malignant tumors. Identified variants in known paraganglioma/pheochromocytoma-causative genes and novel genes could be associated with the pathogenesis of CBT. The obtained results expand our knowledge of the mutation process in CBT as well as the biology of tumor development

The CIMP-high phenotype is associated with energy metabolism alterations in colon adenocarcinoma

Abstract Background CpG island methylator phenotype (CIMP) is found in 15–20% of malignant colorectal tumors and is characterized by strong CpG hypermethylation over the genome. The molecular mechanisms of this phenomenon are not still fully understood. The development of CIMP is followed by global gene expression alterations and metabolic changes. In particular, CIMP-low colon adenocarcinoma (COAD), predominantly corresponded to consensus molecular subtype 3 (CMS3, “Metabolic”) subgroup according to COAD molecular classification, is associated with elevated expression of genes participating in metabolic pathways. Methods We performed bioinformatics analysis of RNA-Seq data from The Cancer Genome Atlas (TCGA) project for CIMP-high and non-CIMP COAD samples with DESeq2, clusterProfiler, and topGO R packages. Obtained results were validated on a set of fourteen COAD samples with matched morphologically normal tissues using quantitative PCR (qPCR). Results Upregulation of multiple genes involved in glycolysis and related processes (ENO2, PFKP, HK3, PKM, ENO1, HK2, PGAM1, GAPDH, ALDOA, GPI, TPI1, and HK1) was revealed in CIMP-high tumors compared to non-CIMP ones. Most remarkably, the expression of the PKLR gene, encoding for pyruvate kinase participating in gluconeogenesis, was decreased approximately 20-fold. Up to 8-fold decrease in the expression of OGDHL gene involved in tricarboxylic acid (TCA) cycle was observed in CIMP-high tumors. Using qPCR, we confirmed the increase (4-fold) in the ENO2 expression and decrease (2-fold) in the OGDHL mRNA level on a set of COAD samples. Conclusions We demonstrated the association between CIMP-high status and the energy metabolism changes at the transcriptomic level in colorectal adenocarcinoma against the background of immune pathway activation. Differential methylation of at least nine CpG sites in OGDHL promoter region as well as decreased OGDHL mRNA level can potentially serve as an additional biomarker of the CIMP-high status in COAD