Colorectal cancer is one of the most common cancers in the world. It is well known that the chronic inflammation can promote the progression of colorectal cancer (CRC). Recently, a number of studies revealed a potential association between colorectal inflammation, cancer progression, and infection caused by enterotoxigenic Bacteroides fragilis (ETBF). Bacterial enterotoxin activates spermine oxidase (SMO), which produces spermidine and H₂O₂ as byproducts of polyamine catabolism, which, in turn, enhances inflammation and tissue injury. Using qPCR analysis, we estimated the expression of SMOX gene and ETBF colonization in CRC patients. We found no statistically significant associations between them. Then we selected genes involved in polyamine metabolism, metabolic reprogramming, and inflammation regulation and estimated their expression in CRC. We observed overexpression of SMOX, ODC1, SRM, SMS, MTAP, c-Myc, C/EBPβ (CREBP), and other genes. We found that two mediators of metabolic reprogramming, inflammation, and cell proliferation c‐Myc and C/EBPβ may serve as regulators of polyamine metabolism genes (SMOX, AZIN1, MTAP, SRM, ODC1, AMD1, and AGMAT) as they are overexpressed in tumors, have binding site according to ENCODE ChIP‐Seq data, and demonstrate strong coexpression with their targets. Thus, increased polyamine metabolism in CRC could be driven by c‐Myc and C/EBPβ rather than ETBF infection.

Colorectal cancer (CRC) is a common cancer worldwide. The main cause of death in CRC includes tumor progression and metastasis. At molecular level, these processes may be triggered by epithelial-mesenchymal transition (EMT) and necessitates specific alterations in cell metabolism. Although several EMT-related metabolic changes have been described in CRC, the mechanism is still poorly understood. Using CrossHub software, we analyzed RNA-Seq expression profile data of CRC derived from The Cancer Genome Atlas (TCGA) project. Correlation analysis between the change in the expression of genes involved in glycolysis and EMT was performed. We obtained the set of genes with significant correlation coefficients, which included 21 EMT-related genes and a single glycolytic gene, HK3. The mRNA level of these genes was measured in 78 paired colorectal cancer samples by quantitative polymerase chain reaction (qPCR). Upregulation of HK3 and deregulation of 11 genes (COL1A1, TWIST1, NFATC1, GLIPR2, SFPR1, FLNA, GREM1, SFRP2, ZEB2, SPP1, and RARRES1) involved in EMT were found. The results of correlation study showed that the expression of HK3 demonstrated a strong correlation with 7 of the 21 examined genes (ZEB2, GREM1, TGFB3, TGFB1, SNAI2, TWIST1, and COL1A1) in CRC. Upregulation of HK3 is associated with EMT in CRC and may be a crucial metabolic adaptation for rapid proliferation, survival, and metastases of CRC cells.

Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.

Carotid body tumor (CBT) is a form of head and neck paragangliomas (HNPGLs) arising at the bifurcation of carotid arteries. Paragangliomas are commonly associated with germline and somatic mutations involving at least one of more than thirty causative genes. However, the specific functionality of a number of these genes involved in the formation of paragangliomas has not yet been fully investigated. Exome library preparation was carried out using Nextera® Rapid Capture Exome Kit (Illumina, USA). Sequencing was performed on NextSeq 500 System (Illumina). Exome analysis of 52 CBTs revealed potential driver mutations (PDMs) in 21 genes: ARNT, BAP1, BRAF, BRCA1, BRCA2, CDKN2A, CSDE1, FGFR3, IDH1, KIF1B, KMT2D, MEN1, RET, SDHA, SDHB, SDHC, SDHD, SETD2, TP53BP1, TP53BP2, and TP53I13. In many samples, more than one PDM was identified. There are also 41% of samples in which we did not identify any PDM; in these cases, the formation of CBT was probably caused by the cumulative effect of several not highly pathogenic mutations. Estimation of average mutation load demonstrated 6–8 mutations per megabase (Mb). Genes with the highest mutation rate were identified. Exome analysis of 52 CBTs for the first time revealed the average mutation load for these tumors and also identified potential driver mutations as well as their frequencies and co-occurrence with the other PDMs.

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. 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). 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. 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.

This review evaluates the advances in the early detection and diagnosis of endometrial cancer (EC), emphasizing the growing importance of minimally invasive techniques and novel biomarkers. Current diagnostic protocols for EC rely heavily on invasive procedures such as transvaginal ultrasound (TVU), hysteroscopy, and endometrial biopsy, which, although effective, can be overly burdensome for patients and inefficient for asymptomatic or low-risk populations. As there is no consensus on EC screening in high-risk or general populations, recent studies have explored alternative methods using biofluids and genomic biomarkers to improve sensitivity and specificity and facilitate access for patients. This review summarizes findings on DNA methylation markers, circulating tumor-derived nucleic acids, and the potential of liquid biopsy approaches for the early detection of EC. These innovations may not only streamline screening but also reduce the need for invasive procedures. This review highlights the potential of these biomarkers to be integrated seamlessly into the existing cervical cancer screening programs, which could transform screening methods for endometrial cancer and support the development of personalized, less invasive diagnostic procedures.