Androgen Insensitivity Syndrome with Bilateral Gonadal Sertoli Cell Lesions, Sertoli-Leydig Cell Tumor, and Paratesticular Leiomyoma: A Case Report and First Systematic Literature Review.

Androgen insensitivity syndrome (AIS) is a rare Mendelian disorder caused by mutations of the androgen receptor (AR) gene on the long arm of the X chromosome. As a result of the mutation, the receptor becomes resistant to androgens, and hence, karyotypically male patients (46,XY) carry a female phenotype. Their cryptorchid gonads are prone to the development of several types of tumors (germ cell, sex cord stromal, and others). Here, we report a 15-year-old female-looking patient with primary amenorrhea who underwent laparoscopic gonadectomy. Histologically, the patient's gonads showed Sertoli cell hamartomas (SCHs) and adenomas (SCAs) with areas of Sertoli-Leydig cell tumors (SLCTs) and a left-sided paratesticular leiomyoma. Rudimentary Fallopian tubes were also present. The patient's karyotype was 46,XY without any evidence of aberrations. Molecular genetic analysis of the left gonad revealed two likely germline mutations-a pathogenic frameshift deletion in the AR gene (c.77delT) and a likely pathogenic missense variant in the RAC1 gene (p.A94V). Strikingly, no somatic mutations, fusions, or copy number variations were found. We also performed the first systematic literature review (PRISMA guidelines; screened databases: PubMed, Scopus, Web of Science; ended on 7 December 2023) of the reported cases of patients with AIS showing benign or malignant Sertoli cell lesions/tumors in their gonads (n = 225; age: 4-84, mean 32 years), including Sertoli cell hyperplasia (1%), Sertoli cell nodules (6%), SCHs (31%), SCAs (36%), Sertoli cell tumors (SCTs) (16%), and SLCTs (4%). The few cases (n = 14, 6%; six SCAs, four SCTs, two SLCTs, and two SCHs) with available follow-up (2-49, mean 17 months) showed no evidence of disease (13/14, 93%) or died of other causes (1/14, 7%) despite the histological diagnosis. Smooth muscle lesions/proliferations were identified in 19 (8%) cases (including clearly reported rudimentary uterine remnants, 3 cases; leiomyomas, 4 cases). Rudimentary Fallopian tube(s) were described in nine (4%) cases. Conclusion: AIS may be associated with sex cord/stromal tumors and, rarely, mesenchymal tumors such as leiomyomas. True malignant sex cord tumors can arise in these patients. Larger series with longer follow-ups are needed to estimate the exact prognostic relevance of tumor histology in AIS.

Accounting for B-cell Behavior and Sampling Bias Predicts Anti-PD-L1 Response in Bladder Cancer.

Cancer immunotherapy is predominantly based on T cell-centric approaches. At the same time, the adaptive immune response in the tumor environment also includes clonally produced immunoglobulins and clonal effector/memory B cells that participate in antigen-specific decisions through their interactions with T cells. Here, we investigated the role of infiltrating B cells in bladder cancer via patient dataset analysis of intratumoral immunoglobulin repertoires. We showed that the IgG1/IgA ratio is a prognostic indicator for several subtypes of bladder cancer and for the whole IMVigor210 anti-PD-L1 immunotherapy study cohort. A high IgG1/IgA ratio associated with the prominence of a cytotoxic gene signature, T-cell receptor signaling, and IL21-mediated signaling. Immunoglobulin repertoire analysis indicated that effector B-cell function, rather than clonally produced antibodies, was involved in antitumor responses. From the T-cell side, we normalized a cytotoxic signature against the extent of immune cell infiltration to neutralize the artificial sampling-based variability in immune gene expression. Resulting metrics reflected proportion of cytotoxic cells among tumor-infiltrating immune cells and improved prediction of anti-PD-L1 responses. At the same time, the IgG1/IgA ratio remained an independent prognostic factor. Integration of the B-cell, natural killer cell, and T-cell signatures allowed for the most accurate prediction of anti-PD-L1 therapy responses. On the basis of these findings, we developed a predictor called PRedIctive MolecUlar Signature (PRIMUS), which outperformed PD-L1 expression scores and known gene signatures. Overall, PRIMUS allows for reliable identification of responders among patients with muscle-invasive urothelial carcinoma, including the subcohort with the low-infiltrated "desert" tumor phenotype.

Differentially Expressed Genes Associated With Prognosis in Locally Advanced Lymph Node-Negative Prostate Cancer.

Older age is one of the main risk factors for cancer development. The incidence of prostate cancer, as a multifactorial disease, also depends upon demographic factors, race, and genetic predisposition. Prostate cancer most frequently occurs in men over 60 years of age, indicating a clear association between older age and disease onset. Carcinogenesis is followed by the deregulation of many genes, and some of these changes could serve as biomarkers for diagnosis, prognosis, prediction of drug therapy efficacy, as well as possible therapeutic targets. We have performed a bioinformatic analysis of a The Cancer Genome Atlas (TCGA) data and RNA-Seq profiling of a Russian patient cohort to reveal prognostic markers of locally advanced lymph node-negative prostate cancer (lymph node-negative LAPC). We also aimed to identify markers of the most common molecular subtype of prostate cancer carrying a fusion transcript TMPRSS2-ERG. We have found several genes that were differently expressed between the favorable and unfavorable prognosis groups and involved in the enriched KEGG pathways based on the TCGA (B4GALNT4, PTK6, and CHAT) and Russian patient cohort data (AKR1C1 and AKR1C3). Additionally, we revealed such genes for the TMPRSS2-ERG prostate cancer molecular subtype (B4GALNT4, ASRGL1, MYBPC1, RGS11, SLC6A14, GALNT13, and ST6GALNAC1). Obtained results contribute to a better understanding of the molecular mechanisms behind prostate cancer progression and could be used for further development of the LAPC prognosis marker panel.

Multi-dimensional immunoproteomics coupled with in vitro recapitulation of oncogenic NRASQ61R identifies diagnostically relevant autoantibody biomarkers in thyroid neoplasia.

Tumor-associated antigen (TAA)-specific autoantibodies have been widely implicated in cancer diagnosis. However, cancer cell lines that are typically exploited as candidate TAA sources in immunoproteomic studies may fail to accurately represent the autoantigen-ome of lower-grade neoplasms. Here, we established an integrated strategy for the identification of disease-relevant TAAs in thyroid neoplasia, which combined NRASQ61R oncogene expression in non-tumorous thyroid Nthy-ori 3-1 cells with a multi-dimensional proteomic technique DISER that consisted of profiling NRASQ61R-induced proteins using 2-dimensional difference gel electrophoresis (2D-DIGE) coupled with serological proteome analysis (SERPA) of the TAA repertoire of patients with thyroid encapsulated follicular-patterned/RAS-like phenotype (EFP/RLP) tumors. We identified several candidate cell-based (nicotinamide phosphoribosyltransferase NAMPT, glutamate dehydrogenase GLUD1, and glutathione S-transferase omega-1 GSTO1) and autoantibody (fumarate hydratase FH, calponin-3 CNN3, and pyruvate kinase PKM autoantibodies) biomarkers, including NRASQ61R-induced TAA phosphoglycerate kinase 1 PGK1. Meta-profiling of the reactivity of the identified autoantibodies across an independent SERPA series implicated the PKM autoantibody as a histological phenotype-independent biomarker of thyroid malignancy (11/38 (29%) patients with overtly malignant and uncertain malignant potential (UMP) tumors vs 0/22 (p = 0.0046) and 0/20 (p = 0.011) patients with non-invasive EFP/RLP tumors and healthy controls, respectively). PGK1 and CNN3 autoantibodies were identified as EFP/RLP-specific biomarkers, potentially suitable for further discriminating tumors with different malignant potential (PGK1: 7/22 (32%) patients with non-invasive EFP/RLP tumors vs 0/38 (p = 0.00044) and 0/20 (p = 0.0092) patients with other tumors and healthy controls, respectively; СNN3: 9/29 (31%) patients with malignant and borderline EFP/RLP tumors vs 0/31 (p = 0.00068) and 0/20 (p = 0.0067) patients with other tumors and healthy controls, respectively). The combined use of PKM, CNN3, and PGK1 autoantibodies allowed the reclassification of malignant/UMP tumor risk in 19/41 (46%) of EFP/RLP tumor patients. Taken together, we established an experimental pipeline DISER for the concurrent identification of cell-based and TAA biomarkers. The combination of DISER with in vitro oncogene expression allows further targeted identification of oncogene-induced TAAs. Using this integrated approach, we identified candidate autoantibody biomarkers that might be of value for differential diagnostic purposes in thyroid neoplasia.

Novel potential causative genes in carotid paragangliomas.

BACKGROUND: Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors that arise from the paraganglion at the bifurcation of the carotid artery and are responsible for approximately 65% of all head and neck paragangliomas. CPGLs can occur sporadically or along with different hereditary tumor syndromes. Approximately 30 genes are known to be associated with CPGLs. However, the genetic basis behind the development of these tumors is not fully elucidated, and the molecular mechanisms underlying CPGL pathogenesis remain unclear. METHODS: Whole exome and transcriptome high-throughput sequencing of CPGLs was performed on an Illumina platform. Exome libraries were prepared using a Nextera Rapid Capture Exome Kit (Illumina) and were sequenced under 75 bp paired-end model. For cDNA library preparation, a TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (Illumina) was used; transcriptome sequencing was carried out with 100 bp paired-end read length. Obtained data were analyzed using xseq which estimates the influence of mutations on gene expression profiles allowing to identify potential causative genes. RESULTS: We identified a total of 16 candidate genes (MYH15, CSP1, MYH3, PTGES3L, CSGALNACT2, NMD3, IFI44, GMCL1, LSP1, PPFIBP2, RBL2, MAGED1, CNIH3, STRA6, SLC6A13, and ATM) whose variants potentially influence their expression (cis-effect). The strongest cis-effect of loss-of-function variants was found in MYH15, CSP1, and MYH3, and several likely pathogenic variants in these genes associated with CPGLs were predicted. CONCLUSIONS: Using the xseq probabilistic model, three novel potential causative genes, namely MYH15, CSP1, and MYH3, were identified in carotid paragangliomas.

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

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.

Mutational load in carotid body tumor.

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.

HK3 overexpression associated with epithelial-mesenchymal transition in colorectal cancer.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Exome analysis of carotid body tumor.

BACKGROUND: 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. METHODS: Exome library preparation was carried out using Nextera® Rapid Capture Exome Kit (Illumina, USA). Sequencing was performed on NextSeq 500 System (Illumina). RESULTS: 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. CONCLUSIONS: 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.

A high-throughput assay for quantitative measurement of PCR errors.

The accuracy with which DNA polymerase can replicate a template DNA sequence is an extremely important property that can vary by an order of magnitude from one enzyme to another. The rate of nucleotide misincorporation is shaped by multiple factors, including PCR conditions and proofreading capabilities, and proper assessment of polymerase error rate is essential for a wide range of sensitive PCR-based assays. In this paper, we describe a method for studying polymerase errors with exceptional resolution, which combines unique molecular identifier tagging and high-throughput sequencing. Our protocol is less laborious than commonly-used methods, and is also scalable, robust and accurate. In a series of nine PCR assays, we have measured a range of polymerase accuracies that is in line with previous observations. However, we were also able to comprehensively describe individual errors introduced by each polymerase after either 20 PCR cycles or a linear amplification, revealing specific substitution preferences and the diversity of PCR error frequency profiles. We also demonstrate that the detected high-frequency PCR errors are highly recurrent and that the position in the template sequence and polymerase-specific substitution preferences are among the major factors influencing the observed PCR error rate.

Application of nonsense-mediated primer exclusion (NOPE) for preparation of unique molecular barcoded libraries.

BACKGROUND: Recently we proposed efficient method to exclude undesirable primers at any stage of amplification reaction, here termed NOPE (NOnsense-mediated Primer Exclusion). According to this method, added oligonucleotide overlapping with the 3'-end of unwanted amplification primer (NOPE oligo) simultaneously provides a template for its elongation. This elongation disrupts specificity of unwanted primer, preventing its further participation in PCR. The suggested approach allows to rationally manage the course of PCR reactions in order to facilitate analysis of complex DNA mixtures as well as to perform multistage PCR bypassing intermediate purification steps. RESULTS: Here we apply NOPE method to DNA library preparation for the high-throughput sequencing (HTS) with the PCR-based introduction of unique molecular identifiers (UMI). We show that NOPE oligo efficiently neutralizes UMI-containing oligonucleotides after introduction of UMI into sample DNA molecules, thus allowing to proceed with further amplification steps without purification and associated loss of starting material. At the same time, NOPE oligo does not affect the efficiency of target PCR amplification. CONCLUSION: We describe a simple, robust and cheap modification of UMI-labeled HTS libraries preparation procedure, that allows to bypass purification step and thus to preserve starting material which may be limited, e.g. circulating tumor DNA, circulating fetal DNA, or small amounts of isolated cells of interest. Furthermore, demonstrated simplicity and robustness of NOPE method should make it popular in various PCR protocols.

MAGERI: Computational pipeline for molecular-barcoded targeted resequencing.

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.

Molecular markers of paragangliomas/pheochromocytomas.

Paragangliomas/pheochromocytomas comprise rare tumors that arise from the extra-adrenal paraganglia, with an incidence of about 2 to 8 per million people each year. Approximately 40% of cases are due to genetic mutations in at least one out of more than 30 causative genes. About 25-30% of pheochromocytomas/paragangliomas develop under the conditions of a hereditary tumor syndrome a third of which are caused by mutations in the VHL gene. Together, the gene mutations in this disorder have implicated multiple processes including signaling pathways, translation initiation, hypoxia regulation, protein synthesis, differentiation, survival, proliferation, and cell growth. The present review contemplates the mutations associated with the development of pheochromocytomas/paragangliomas and their potential to serve as specific markers of these tumors and their progression. These data will improve our understanding of the pathogenesis of these tumors and likely reveal certain features that may be useful for early diagnostics, malignancy prognostics, and the determination of new targets for disease therapeutics.

The Dysregulation of Polyamine Metabolism in Colorectal Cancer Is Associated with Overexpression of c-Myc and C/EBPß rather than Enterotoxigenic Bacteroides fragilis Infection.

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/EBPß (CREBP), and other genes. We found that two mediators of metabolic reprogramming, inflammation, and cell proliferation c-Myc and C/EBPß 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/EBPß rather than ETBF infection.

Important molecular genetic markers of colorectal cancer.

Colorectal cancer (CRC) ranks third in the incidences of cancer morbidity and mortality worldwide. CRC is rather heterogeneous with regard to molecular genetic characteristics and pathogenic pathways. A wide spectrum of biomarkers is used for molecular subtype determination, prognosis, and estimation of sensitivity to different drugs in practice. These biomarkers can include germline and somatic mutations, chromosomal aberrations, genomic abnormalities, gene expression alterations at mRNA or protein level and changes in DNA methylation status. In the present review we discuss the most important and well-studied CRC biomarkers, and their potential clinical significance and current approaches to molecular classification of colorectal tumors.

CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms.

The contribution of different mechanisms to the regulation of gene expression varies for different tissues and tumors. Complementation of predicted mRNA-miRNA and gene-transcription factor (TF) relationships with the results of expression correlation analyses derived for specific tumor types outlines the interactions with functional impact in the current biomaterial. We developed CrossHub software, which enables two-way identification of most possible TF-gene interactions: on the basis of ENCODE ChIP-Seq binding evidence or Jaspar prediction and co-expression according to the data of The Cancer Genome Atlas (TCGA) project, the largest cancer omics resource. Similarly, CrossHub identifies mRNA-miRNA pairs with predicted or validated binding sites (TargetScan, mirSVR, PicTar, DIANA microT, miRTarBase) and strong negative expression correlations. We observed partial consistency between ChIP-Seq or miRNA target predictions and gene-TF/miRNA co-expression, demonstrating a link between these indicators. Additionally, CrossHub expression-methylation correlation analysis can be used to identify hypermethylated CpG sites or regions with the greatest potential impact on gene expression. Thus, CrossHub is capable of outlining molecular portraits of a specific gene and determining the three most common sources of expression regulation: promoter/enhancer methylation, miRNA interference and TF-mediated activation or repression. CrossHub generates formatted Excel workbooks with the detailed results. CrossHub is freely available athttps://sourceforge.net/projects/crosshub/.