Adrenal pheochromocytoma impacts three main pathways: cysteine-methionine, pyrimidine, and tyrosine metabolism. / è‚¾ä¸Šè ºå—œé“¬ç»†èƒžç˜¤å½±å“ä¸‰æ¡ä¸»è¦ä»£è°¢é€šè·¯ï¼šåŠèƒ±æ°¨é ¸-è›‹æ°¨é ¸ä»£è°¢ã€å˜§å•¶ä»£è°¢å’Œé ªæ°¨é ¸ä»£è°¢é€šè·¯.

Pheochromocytomas and paragangliomas (PPGLs) cause symptoms by altering the circulation levels of catecholamines and peptide hormones. Currently, the diagnosis of PPGLs relies on diagnostic imaging and the detection of catecholamines. In this study, we used ultra-performance liquid chromatography (UPLC)/quadrupole time-of-flight mass spectrometry (Q-TOF MS) analysis to identify and measure the perioperative differential metabolites in the plasma of adrenal pheochromocytoma patients. We identified differentially expressed genes by comparing the transcriptomic data of pheochromocytoma with the normal adrenal medulla. Through conducting two steps of metabolomics analysis, we identified 111 differential metabolites between the healthy group and the patient group, among which 53 metabolites were validated. By integrating the information of differential metabolites and differentially expressed genes, we inferred that the cysteine-methionine, pyrimidine, and tyrosine metabolism pathways were the three main metabolic pathways altered by the neoplasm. The analysis of transcription levels revealed that the tyrosine and cysteine-methionine metabolism pathways were downregulated in pheochromocytoma, whereas the pyrimidine pathway showed no significant difference. Finally, we developed an optimized diagnostic model of two metabolites, L-dihydroorotic acid and vanylglycol. Our results for these metabolites suggest that they may serve as potential clinical biomarkers and can be used to supplement and improve the diagnosis of pheochromocytoma.

Alternative polyadenylation quantitative trait methylation mapping in human cancers provides clues into the molecular mechanisms of APA.

Genetic variants are involved in the orchestration of alternative polyadenylation (APA) events, while the role of DNA methylation in regulating APA remains unclear. We generated a comprehensive atlas of APA quantitative trait methylation sites (apaQTMs) across 21 different types of cancer (1,612 to 60,219 acting in cis and 4,448 to 142,349 in trans). Potential causal apaQTMs in non-cancer samples were also identified. Mechanistically, we observed a strong enrichment of cis-apaQTMs near polyadenylation sites (PASs) and both cis- and trans-apaQTMs in proximity to transcription factor (TF) binding regions. Through the integration of ChIP-signals and RNA-seq data from cell lines, we have identified several regulators of APA events, acting either directly or indirectly, implicating novel functions of some important genes, such as TCF7L2, which is known for its involvement in type 2 diabetes and cancers. Furthermore, we have identified a vast number of QTMs that share the same putative causal CpG sites with five different cancer types, underscoring the roles of QTMs, including apaQTMs, in the process of tumorigenesis. DNA methylation is extensively involved in the regulation of APA events in human cancers. In an attempt to elucidate the potential underlying molecular mechanisms of APA by DNA methylation, our study paves the way for subsequent experimental validations into the intricate biological functions of DNA methylation in APA regulation and the pathogenesis of human cancers. To present a comprehensive catalog of apaQTM patterns, we introduce the Pancan-apaQTM database, available at https://pancan-apaqtm-zju.shinyapps.io/pancanaQTM/.

OpenNAU: An open-source platform for normalizing, analyzing, and visualizing cancer untargeted metabolomics data.

Objective: As an important part of metabolomics analysis, untargeted metabolomics has become a powerful tool in the study of tumor mechanisms and the discovery of metabolic markers with high-throughput spectrometric data which also poses great challenges to data analysis, from the extraction of raw data to the identification of differential metabolites. To date, a large number of analytical tools and processes have been developed and constructed to serve untargeted metabolomics research. The different selection of analytical tools and parameter settings lead to varied results of untargeted metabolomics data. Our goal is to establish an easily operated platform and obtain a repeatable analysis result. Methods: We used the R language basic environment to construct the preprocessing system of the original data and the LAMP (Linux+Apache+MySQL+PHP) architecture to build a cloud mass spectrum data analysis system. Results: An open-source analysis software for untargeted metabolomics data (openNAU) was constructed. It includes the extraction of raw mass data and quality control for the identification of differential metabolic ion peaks. A reference metabolomics database based on public databases was also constructed. Conclusions: A complete analysis system platform for untargeted metabolomics was established. This platform provides a complete template interface for the addition and updating of the analysis process, so we can finish complex analyses of untargeted metabolomics with simple human-computer interactions. The source code can be downloaded from https://github.com/zjuRong/openNAU.

TP53 mutation is enriched in colorectal cancer liver metastasis in the context of polyclonal seeding.

Cancer metastasis accounts for the majority of cancer motility burden. For colorectal cancer (CRC), the liver is the most common site of distant metastasis. It is still little known that cancer genomic mutations, which are a cell-intrinsic and heritable property, are enriched in CRC liver metastasis. Here, we try to answer the question in the context of polyclonal seeding. In this study, we sequenced 18 pairs of colorectal cancer primary tumors and their matched liver metastasis samples. Together with public available sequencing data, we compared the mutations in 113 primary and metastasis pairs. The TP53 mutation variant allele frequency (VAF) was significantly increased in metastasis compared to the paired primary tumor, although most of the frequently observed mutations in liver metastasis foci were concordant with their matched CRC primary tumors. The results support late metastasis and polyclonal seeding. Consequently, we quantitatively compared the intratumor heterogeneity (ITH) between primary and metastasis tumors, and with the help of in silico metastasis simulation, we inferred that more than 10 cells take part in the CRC liver metastasis.

Desmoplastic Small Round Cell Tumor in a Pregnant Woman: A Case Report and Literature Review.

Background: Desmoplastic small round cell tumor (DSRCT) is an aggressive malignant tumor commonly found in young men; most occurs in the abdominal cavity. Here we conducted an in-depth analysis of a pregnant patient in our hospital and explored all the case information in the literature on small round cell carcinoma of women. Case presentation: A 27-year-old pregnant woman underwent tumor resection in our hospital at 29 weeks gestational age for a large progressive shoulder lump. The postoperative pathology showed that the mass was a DSRCT. Genetic testing found no fusion gene. At 36 weeks gestation, a painful mass was found in the breast and proved to be a metastatic focus of the desmoplastic small round cell tumor. Twenty days after a successful cesarean section at 40 weeks gestation, she received the VAC-IE chemotherapy regimen, successfully completed the first course, but when awaiting the next chemotherapy, unfortunately, the patient died during follow-up due to tumor recurrence and metastasis. Conclusion: The treatment of DSRCT in pregnant women requires a multidisciplinary consultation, and the treatment and examination during pregnancy are subject to many constraints, which may have a negative impact on the patient's prognosis. Also, a review of the literature found that there is still no standard treatment protocol for DSRCT, and its prognosis in female patients is independent of age and tissue origin.

Mutant CDKN2A regulates P16/p14 expression by alternative splicing in renal cell carcinoma metastasis.

OBJECTIVE: Metastatic renal cell carcinoma (mRCC) is the important factor for patient mortality, meanwhile gene mutation constantly changes cancer prognosis in tumor process. Exploring the driver mutation in mRCC process become more and more important. MATERIALS AND METHODS: We obtained the 15 paired primary and metastatic mRCC samples and analyzed specific mutation genes in the metastatic foci (SMGs) by next generation sequencing. Moreover, we explored the Correlated networks, Pathway and Gene Ontology (GO) enrichment results, prediction analysis of AS sites and prognosis of survival. RESULTS: We identify EPCAM, TMEM127, EZH2, EXT1, CDKN2A, PRF1, AIP, CDK4, PRKARIA as SMGs and find that CDKN2A mutation sites affect the prognosis of mRCC by altering splicing elements. Based on the differential analysis for SMGs in KIRC, we found that EPCAM, PRF1 and EZH2 were differential expression in both primary tumors with metastasis compared to primary tumors without metastasis or metastatic tissues. By the AS prediction analysis, we suggest that CDKN2A mutation sites play an important role for RCC metastasis by affecting the p16/p14 expression. CONCLUSIONS: The SMGs could provide new molecular cues associated with tumor metastasis and have potential clinical implications for cancer prognosis and treatment. Definitive conclusions await further validation and follow up.

Computational Identification of Tumor Suppressor Genes Based on Gene Expression Profiles in Normal and Cancerous Gastrointestinal Tissues.

Cancer prevails in various gastrointestinal (GI) organs, such as esophagus, stomach, and colon. However, the small intestine has an extremely low cancer risk. It is interesting to investigate the molecular cues that could explain the significant difference in cancer incidence rates among different GI tissues. Using several large-scale normal and cancer tissue genomics datasets, we compared the gene expression profiling between small intestine and other GI tissues and between GI cancers and normal tissues. We identified 17 tumor suppressor genes (TSGs) which showed significantly higher expression levels in small intestine than in other GI tissues and significantly lower expression levels in GI cancers than in normal tissues. These TSGs were mainly involved in metabolism, immune, and cell growth signaling-associated pathways. Many TSGs had a positive expression correlation with survival prognosis in various cancers, confirming their tumor suppressive function. We demonstrated that the downregulation of many TSGs was associated with their hypermethylation in cancer. Moreover, we showed that the expression of many TSGs inversely correlated with tumor purity and positively correlated with antitumor immune response in various cancers, suggesting that these TSGs may exert their tumor suppressive function by promoting antitumor immunity. Furthermore, we identified a transcriptional regulatory network of the TSGs and their master transcriptional regulators (MTRs). Many of MTRs have been recognized as tumor suppressors, such as HNF4A, ZBTB7A, p53, and RUNX3. The TSGs could provide new molecular cues associated with tumorigenesis and tumor development and have potential clinical implications for cancer diagnosis, prognosis, and treatment.

Correction to: The Cancer Omics Atlas: an integrative resource for cancer omics annotations.

Following publication of the original article [1], the authors reported an error in Fig. 1A.

The Cancer Omics Atlas: an integrative resource for cancer omics annotations.

BACKGROUND: The Cancer Genome Atlas (TCGA) is an important data resource for cancer biologists and oncologists. However, a lack of bioinformatics expertise often hinders experimental cancer biologists and oncologists from exploring the TCGA resource. Although a number of tools have been developed for facilitating cancer researchers to utilize the TCGA data, these existing tools cannot fully satisfy the large community of experimental cancer biologists and oncologists without bioinformatics expertise. METHODS: We developed a new web-based tool The Cancer Omics Atlas (TCOA, http://tcoa.cpu.edu.cn ) for fast and straightforward querying of TCGA "omics" data. RESULTS: TCOA provides the querying of gene expression, somatic mutations, microRNA (miRNA) expression, protein expression data based on a single molecule or cancer type. TCOA also provides the querying of expression correlation between gene pairs, miRNA pairs, gene and miRNA, and gene and protein. Moreover, TCOA provides the querying of the associations between gene, miRNA, or protein expression and survival prognosis in cancers. In addition, TCOA displays transcriptional profiles across various human cancer types based on the pan-cancer analysis. Finally, TCOA provides the querying of molecular profiles for 2877 immune-related genes in human cancers. These immune-related genes include those that are established or promising targets for cancer immunotherapy such as CTLA4, PD1, PD-L1, PD-L2, IDO1, LAG3, and TIGIT. CONCLUSIONS: TCOA is a useful tool that supplies a number of unique and new functions complementary to the existing tools to facilitate exploration of the TCGA resource.

A Pharmacokinetic-Pharmacodynamic Model of Tamoxifen and Endoxifen to Predict Their Distribution and Effects on Inhibition of Tumor Growth.

BACKGROUND: Tamoxifen is widely used in the therapy for breast cancer and has three major metabolites, N-desmethyltamoxifen, 4-hydroxytamoxifen, and endoxifen. Endoxifen has played a major role in the inhibition of tumor growth of breast cancer and the tumor growth is related to endoxifen concentration. OBJECTIVES: The aim of this study was to develop a pharmacokinetic-pharmacodynamic model to predict the distribution of tamoxifen and endoxifen quantitatively, and to discover the anti-tumor effect patterns of tamoxifen and endoxifen. METHODS: The pharmacokinetic-pharmacodynamic model was established by integrating a four compartments pharmacokinetics model and a pharmacodynamic model, the first one include central compartment and peripheral compartment both of which contain tamoxifen and endoxifen. The parameters of the model were calculated by the values of plasma concentrations and the tumor growth data before and after the administration of tamoxifen. RESULTS: The transport rate k42 (6.0003) of endoxifen from the peripheral compartment to the central compartment and the metabolism rate k34 (0.0031) from tamoxifen to endoxifen in the peripheral compartment were proven to be significant, which showed that tamoxifen and endoxifen are mainly distributed in the central compartment. The model provided reasonable predictions of tumor growth, which was inhibited after the administration and varies with the concentration of endoxifen. CONCLUSION: We established a PK-PD model of tamoxifen and endoxifen to predict the tumor growth. The parameters of the pharmacodynamic model, which characterized the tumor growth, revealed the patterns of tamoxifen's anti-tumor functions. The PK-PD model successfully provided illustration for the pharmacokinetics of tamoxifen and endoxifen, and predicted the inhibition effect of endoxifen on the tumor growth.

Transcriptional landscape of human cancers.

The homogeneity and heterogeneity in somatic mutations, copy number alterations and methylation across different cancer types have been extensively explored. However, the related exploration based on transcriptome data is lacking. In this study we explored gene expression profiles across 33 human cancer types using The Cancer Genome Atlas (TCGA) data. We identified consistently upregulated genes (such as E2F1, EZH2, FOXM1, MYBL2, PLK1, TTK, AURKA/B and BUB1) and consistently downregulated genes (such as SCARA5, MYOM1, NKAPL, PEG3, USP2, SLC5A7 and HMGCLL1) across various cancers. The dysregulation of these genes is likely to be associated with poor clinical outcomes in cancer. The dysregulated pathways commonly in cancers include cell cycle, DNA replication, repair, and recombination, Notch signaling, p53 signaling, Wnt signaling, TGFß signaling, immune response etc. We also identified genes consistently upregulated or downregulated in highly-advanced cancers compared to lowly-advanced cancers. The highly (low) expressed genes in highly-advanced cancers are likely to have higher (lower) expression levels in cancers than in normal tissue, indicating that common gene expression perturbations drive cancer initiation and cancer progression. In addition, we identified a substantial number of genes exclusively dysregulated in a single cancer type or inconsistently dysregulated in different cancer types, demonstrating the intertumor heterogeneity. More importantly, we found a number of genes commonly dysregulated in various cancers such as PLP1, MYOM1, NKAPL and USP2 which were investigated in few cancer related studies, and thus represent our novel findings. Our study provides comprehensive portraits of transcriptional landscape of human cancers.

TP53 mutations, expression and interaction networks in human cancers.

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers.

PLK1, A Potential Target for Cancer Therapy.

Polo-like kinase 1 (PLK1) plays an important role in the initiation, maintenance, and completion of mitosis. Dysfunction of PLK1 may promote cancerous transformation and drive its progression. PLK1 overexpression has been found in a variety of human cancers and was associated with poor prognoses in cancers. Many studies have showed that inhibition of PLK1 could lead to death of cancer cells by interfering with multiple stages of mitosis. Thus, PLK1 is expected to be a potential target for cancer therapy. In this article, we examined PLK1's structural characteristics, its regulatory roles in cell mitosis, PLK1 expression, and its association with survival prognoses of cancer patients in a wide variety of cancer types, PLK1 interaction networks, and PLK1 inhibitors under investigation. Finally, we discussed the key issues in the development of PLK1-targeted cancer therapy.

Pediatric esophageal leiomyosarcoma: a case report.

Esophageal leiomyosarcoma accounts for only 0.5% of all esophageal tumors. This rare tumor has been reported in middle-aged or elderly patients. In contrast, pediatric esophageal leiomyosarcomas have never been reported. The case described herein is the first report of an esophageal leiomyosarcoma in a pediatric patient with its own characteristics. The patient had symptoms of mild cough without dysphagia. The lesion grew rapidly and reached dimensions of 7.0 cm × 5.0 cm × 6.0 cm in a 3-month period. On computed tomography scan of the chest, the mass exhibited mild enhancement after injection of a contrast agent. More evident enhancement was found on the 3-minute delayed enhanced computed tomography scan. A Phemister operation (transthoracic esophagectomy and esophagogastrostomy) was performed on the patient. The patient did not receive adjuvant postoperative radiotherapy or chemotherapy. He has been followed for 3 years and is free of disease.