scholarly journals Leptomeningeal Metastasis from Adrenocortical Carcinoma: A Case Report

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Anna R Schreiber ◽  
Adwitiya Kar ◽  
Andrew E Goodspeed ◽  
Nikita Pozdeyev ◽  
Hilary Somerset ◽  
...  
Keyword(s):  
Adrenocortical Carcinoma ◽  
Treatment Options ◽  
Leptomeningeal Metastasis ◽  
Signs And Symptoms ◽  
Tumor Stage ◽  
The Cancer Genome Atlas ◽  
En Bloc ◽  
Data Set ◽  
Term Survival ◽  
Cancer Genome Atlas

Abstract Adrenocortical carcinoma (ACC) is an uncommon endocrine malignancy with limited treatment options. While the overall 5-year survival rate in patients with ACC is 35%, the disease is often rapidly progressive with long-term survival in only 5% of patients. Although tumor stage, grade, and excess hormonal activity predict unfavorable prognosis, additional biomarkers are needed to identify patients with aggressive disease. A 23-year-old woman presented with rapidly progressing signs and symptoms of Cushing’s syndrome, with associated abdominal pain and fullness. Evaluation revealed a large left adrenal mass which had developed over 8 months. En bloc surgical resection was performed by an endocrine surgeon, and pathology revealed adrenocortical carcinoma with Ki67 of 60%. Despite adjuvant treatment with mitotane and etoposide–doxorubicin–carboplatin chemotherapy, the patient had rapid disease progression with metastatic spread to liver, lung, bone, brain, and leptomeningies, and she died 11 months after the initial diagnosis. Subsequent analysis of the patient’s tumor revealed mutations in TP53 and MEN1. RNA sequencing was compared against the the Cancer Genome Atlas data set and clustered with the high steroid, proliferative subtype, associated with the worst prognosis. The tumor also demonstrated a low BUB1B/PINK1 ratio and G0S2 hypermethylation, both predictive of very aggressive ACC. This case represents a subset of ACC characterized by rapid and fatal progression. Clinically available predictors as well as recently reported molecular signatures and biomarkers correlated with this tumor’s aggressiveness, suggesting that development and validation of combinations of biomarkers may be useful in guiding personalized approaches to patients with ACC.

scholarly journals CYSTM1: A Novel Biomarker for Hepatocellular Carcinoma Prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Jinguo Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Early Stage ◽  
Human Tumor ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background: The expression and molecular mechanism of cysteine rich transmembrane module containing 1 (CYSTM1) in human tumor cells remains unclear. The aim of this study was to determine whether CYSTM1 could be used as a potential prognostic biomarker for hepatocellular carcinoma (HCC).Methods: We first demonstrated the relationship between CYSTM1 expression and HCC in various public databases. Secondly, Kaplan–Meier analysis and Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CYSTM1 and the survival of HCC patients which data was downloaded in the cancer genome atlas (TCGA) database. Finally, we used the expression data of CYSTM1 in TCGA database to predict CYSTM1-related signaling pathways through bioinformatics analysis.Results: The expression level of CYSTM1 in HCC tissues was significantly correlated with T stage (p = 0.039). In addition, Kaplan–Meier analysis showed that the expression of CYSTM1 was significantly associated with poor prognosis in patients with early-stage HCC (p = 0.003). Multivariate analysis indicated that CYSTM1 is a potential predictor of poor prognosis in HCC patients (p = 0.036). The results of biosynthesis analysis demonstrated that the data set of CYSTM1 high expression was mainly enriched in neurodegeneration and oxidative phosphorylation pathways.Conclusion: CYSTM1 is an effective biomarker for the prognosis of patients with early-stage HCC and may play a key role in the occurrence and progression of HCC.

scholarly journals Recurrent Amplification of the Osmotic Stress Transcription Factor NFAT5 in Adrenocortical Carcinoma

2020 ◽  
Vol 4 (7) ◽  
Author(s):  
Taylor C Brown ◽  
Norman G Nicolson ◽  
Jianliang Man ◽  
Courtney E Gibson ◽  
Adam Stenman ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Osmotic Stress ◽  
Protein Expression ◽  
Adrenocortical Carcinoma ◽  
The Cancer Genome Atlas ◽  
Discovery Cohort ◽  
Adrenocortical Adenomas ◽  
Cancer Genome Atlas ◽  
Mrna Expression Levels ◽  
Genome Atlas

Abstract Tumorigenesis requires mitigation of osmotic stress and the transcription factor nuclear factor of activated T cells 5 (NFAT5) coordinates this response by inducing transcellular transport of ions and osmolytes. NFAT5 modulates in vitro behavior in several cancer types, but a potential role of NFAT5 in adrenocortical carcinoma (ACC) has not been studied. A discovery cohort of 28 ACCs was selected for analysis. Coverage depth analysis of whole-exome sequencing reads assessed NFAT5 copy number alterations in 19 ACCs. Quantitative real-time PCR measured NFAT5 mRNA expression levels in 11 ACCs and 23 adrenocortical adenomas. Immunohistochemistry investigated protein expression in representative adrenal samples. The Cancer Genome Atlas database was analyzed to corroborate NFAT5 findings from the discovery cohort and to test whether NFAT5 expression correlated with ion/osmolyte channel and regulatory protein expression patterns in ACC. NFAT5 was amplified in 10 ACCs (52.6%) and clustered in the top 6% of all amplified genes. mRNA expression levels were 5-fold higher compared with adrenocortical adenomas (P < 0.0001) and NFAT5 overexpression had a sensitivity and specificity of 81.8% and 82.7%, respectively, for malignancy. Increased protein expression and nuclear localization occurred in representative ACCs. The Cancer Genome Atlas analysis demonstrated concomitant NFAT5 amplification and overexpression (P < 0.0001) that correlated with increased expression of sodium/myo-inositol transporter SLC5A3 (r2 = 0.237, P < 0.0001) and 14 other regulatory proteins (P < 0.05) previously shown to interact with NFAT5. Amplification and overexpression of NFAT5 and associated osmotic stress response related genes may play an important role adrenocortical tumorigenesis.

scholarly journals Pathogenetic Analysis of Sinonasal Teratocarcinosarcomas Reveal Actionable β-catenin Overexpression and a β-catenin Mutation

2017 ◽  
Vol 78 (04) ◽  
pp. 346-352 ◽  
Author(s):  
Megan Yanik ◽  
Megan Scott ◽  
Carol Bradford ◽  
Jonathan McHugh ◽  
Scott McLean ◽  
...  
Keyword(s):  
Treatment Options ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Molecular Alterations ◽  
Online Databases ◽  
Activating Mutation ◽  
Cancer Mutations ◽  
Cancer Genome Atlas ◽  
Sinonasal Teratocarcinosarcoma ◽  
Index Tumor

Objective Sinonasal teratocarcinosarcomas are rare, aggressive tumors of the skull base. Treatment options are limited and outcomes are poor. Little is known in regard to the genetic factors regulating these tumors. Characterization of actionable molecular alterations in these tumors could provide potentially successful therapeutic options. Methods We performed targeted exome sequencing on an index sinonasal teratocarcinosarcoma specimen to identify potential driver mutations. We performed immunohistochemical stains for β-catenin on paraffin-embedded tissue on the index tumor and a subsequent teratocarcinosarcoma. Online databases of cancer mutations (Catalogue of Somatic Mutations in Cancer and The Cancer Genome Atlas) were accessed. Results We identified an activating p.S45F mutation in β-catenin in our index sinonasal teratocarcinosarcoma. This mutation results in constitutive signaling in the Wnt/β-catenin pathway. We confirmed β-catenin overexpression and nuclear localization via immunohistochemistry in the index tumor and a second patient. The p.S45F activating mutation was found in a variety of solid tumors, and accounts for 3.3 to 10.4% of all known β-catenin mutations. Conclusion We identified a potential driver mutation in β-catenin in a sinonasal teratocarcinosarcoma, resulting in β-catenin overexpression. These findings suggest a role for the Wnt/β-catenin pathway in sinonasal teratocarcinosarcoma tumorigenesis and a role for anti-β-catenin targeted therapy.

scholarly journals CPXM1: a novel biomarker for gastric cancer prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Mengxiang Zhu ◽  
Wenwu Yan ◽  
Changsheng Yao ◽  
Qingyi Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Poor Prognosis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Signal Pathways ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background The molecular role of carboxypeptidase X, M14 family member (CPXM1) in oncogenesis or tumor progression remains unclear. The aim of this study was to determine whether CPXM1 can be used as a potential prognostic biomarker for gastric cancer (GC). Methods We first demonstrated the relationship between CPXM1 expression and GC in various public databases. Secondly, the expression of CPXM1 in GC tissues was further verified by immunohistochemical staining using tissue microarray containing 96 cases of GC patients. Kaplan–Meier analysis and a Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CPXM1 and the survival of GC patients. Finally, we used the expression data of CPXM1 in The Cancer Genome Atlas database to predict CPXM1-related signaling pathways through bioinformatics analysis. Results The expression level of CPXM1 in GC tissues was significantly correlated with tumor size (p = 0.041) and lymph node metastasis (p = 0.014). In addition, Kaplan–Meier analysis showed that the expression of CPXM1 in GC tissues was significantly associated with poor prognosis (p = 0.011). Multivariate analysis indicated that CPXM1 is a potential predictor of poor prognosis in GC patients (p = 0.026). The results of biosynthesis analysis demonstrated that the data set of CPXM1 high expression was mainly enriched in cancer-related signal pathways. Conclusion CPXM1 is an effective biomarker for the prognosis of GC patients and may play a key role in the occurrence and progression of GC.

scholarly journals TRGAted: A web tool for survival analysis using protein data in the Cancer Genome Atlas.

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1235 ◽  
Author(s):  
Nicholas Borcherding ◽  
Nicholas L. Bormann ◽  
Andrew P. Voigt ◽  
Weizhou Zhang
Keyword(s):  
Tumor Stage ◽  
Cancer Genome ◽  
Protein Quantification ◽  
The Cancer Genome Atlas ◽  
Dot Blot ◽  
Link Type ◽  
Free Interval ◽  
Level Data ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Reverse-phase protein arrays (RPPAs) are a highthroughput approach to protein quantification utilizing antibody-based micro-to-nano scale dot blot. Within the Cancer Genome Atlas (TCGA), RPPAs were used to quantify over 200 proteins in 8,167 tumor and metastatic samples. Protein-level data has particular advantages in assessing putative prognostic or therapeutic targets in tumors. However, many of the available pipelines do not allow for the partitioning of clinical and RPPA information to make meaningful conclusions. We developed a cloud-based application, TRGAted to enable researchers to better examine patient survival based on single or multiple proteins across 31 cancer types in the TCGA. TRGAted contains up-to-date overall survival, disease-specific survival, disease-free interval and progression-free interval information. Furthermore, survival information for primary tumor samples can be stratified based on gender, age, tumor stage, histological type, and subtype, allowing for highly adaptive and intuitive user experience. The code and processed data are open sourced and available on github and contains a tutorial built into the application for assisting users.

Reannotation and Analysis of Clinical and Chemotherapy Outcomes in the Ovarian Data Set From The Cancer Genome Atlas

2018 ◽  
pp. 1-16 ◽  
Author(s):  
Victor M. Villalobos ◽  
Yan C. Wang ◽  
Branimir I. Sikic
Keyword(s):  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
First Line ◽  
Data Set ◽  
Proteomic Data ◽  
First Line Therapy ◽  
Line Therapy ◽  
Risk Patients ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Purpose The ovarian cancer data set from The Cancer Genome Atlas integrates genomic and proteomic data with clinical annotations based on chart abstractions. We aimed to develop an algorithm to create a matching, more accessible clinical data set cataloging time to treatment failure (TTF) of sequential lines of treatment in patients with serous ovarian cancers. Materials and Methods The master data set of 587 patients with serous ovarian cancer was condensed into a more homogeneous and clinically relevant population comprised of high-risk patients with both grade 3 cancers and stage III or IV disease, resulting in a subgroup of 450 patients. We quantified the TTF of different lines of therapy as well as different therapeutic combinations by extrapolating from the time of starting one therapy to the time of starting a subsequent therapy. Results The overall survival (OS) of patients was highly related to platinum sensitivity status, with median OS times of 56.6, 27.0, and 11.6 months in patients who had platinum-sensitive, -resistant, or -refractory disease, respectively. In high-risk patients, the median TTFs were 14.8, 10.2, 5.7, and 4.1 months with the first, second, third, and fourth lines of chemotherapy, respectively. Patients with stable disease after first-line therapy had similar OS outcomes as patients with partial remissions (34.4 v 33.7 months, respectively). Conclusion This new data set enhances the clinical annotation by providing exploitable chemotherapy benefit data that can now be paired with genomic and proteomic data within The Cancer Genome Atlas data. The major determinant of OS in this study was platinum sensitivity status. TTF decreased with each successive line of therapy. However, patients who achieved only stable disease with first-line therapy had OS similar to those with partial remission.

Expression profiles and prognostic roles of m6A writers, erasers and readers in gastric cancer

2021 ◽  
Vol 17 (20) ◽  
pp. 2605-2620
Author(s):  
Jing-Jing Jing ◽  
Xu Zhao ◽  
Hao Li ◽  
Li-ping Sun ◽  
Yuan Yuan
Keyword(s):  
Gastric Cancer ◽  
Expression Profiles ◽  
Tumor Stage ◽  
The Cancer Genome Atlas ◽  
Pathological Stage ◽  
Rna Methylation ◽  
Web Resources ◽  
Cancer Genome Atlas ◽  
M6a Rna Methylation ◽  
Using Data

Aim: To explore the expression profiles of N6-methyladenosine (m6A) enzymes (writers, erasers and readers) and their associations with gastric cancer (GC) prognosis. Methods: Gene expression was analyzed using the UALCAN and Oncomine web resources. The prognostic roles of these genes in GC were analyzed using data from The Cancer Genome Atlas. Results: Thirteen m6A enzymes were found to be upregulated in GC tissues. The expression of m6A writers METTL3, RBM15 and WTAP was associated with pathological stage. The m6A eraser FTO was related to tumor stage and ALKBH5 expression was related to GC prognosis. The m6A reader YTHDF3 expression was associated with tumor stage. YTHDC2 was associated with survival of GC patients. Conclusion: Abnormal changes of key genes involved in m6A RNA methylation may have an important impact on GC development and prognosis.

scholarly journals Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale

2018 ◽  
Vol 17 ◽  
pp. 117693511877478 ◽  
Author(s):  
Jovan Cejovic ◽  
Jelena Radenkovic ◽  
Vladimir Mladenovic ◽  
Adam Stanojevic ◽  
Milica Miletic ◽  
...  
Keyword(s):  
Semantic Web ◽  
Cancer Genomics ◽  
Large Data ◽  
The Cancer Genome Atlas ◽  
Data Sets ◽  
Sequencing Data ◽  
Semantic Web Technologies ◽  
Data Set ◽  
Seamless Integration ◽  
Cancer Genome Atlas

Increased efforts in cancer genomics research and bioinformatics are producing tremendous amounts of data. These data are diverse in origin, format, and content. As the amount of available sequencing data increase, technologies that make them discoverable and usable are critically needed. In response, we have developed a Semantic Web–based Data Browser, a tool allowing users to visually build and execute ontology-driven queries. This approach simplifies access to available data and improves the process of using them in analyses on the Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org ). The Data Browser makes large data sets easily explorable and simplifies the retrieval of specific data of interest. Although initially implemented on top of The Cancer Genome Atlas (TCGA) data set, the Data Browser’s architecture allows for seamless integration of other data sets. By deploying it on the CGC, we have enabled remote researchers to access data and perform collaborative investigations.

scholarly journals Regulation of PD1 signaling is associated with prognosis in glioblastoma multiforme

2021 ◽  
Author(s):  
Camila Lopes-Ramos ◽  
Tatiana Belova ◽  
Tess Brunner ◽  
John Quackenbush ◽  
Marieke L. Kuijjer
Keyword(s):  
Gene Regulatory Networks ◽  
Transcriptional Repression ◽  
Regulatory Networks ◽  
Treatment Options ◽  
Neoadjuvant Treatment ◽  
The Cancer Genome Atlas ◽  
Therapeutic Interventions ◽  
Short Term ◽  
Term Survival ◽  
Gene Regulatory

Glioblastoma is an aggressive cancer of the brain and spine. While analysis of glioblastoma ‘omics data has somewhat improved our understanding of the disease, it has not led to direct improvement in patient survival. Cancer survival is often characterized by differences in expression of particular genes, but the mechanisms that drive these differences are generally unknown. We therefore set out to model the regulatory mechanisms that associate with glioblastoma survival. We inferred individual patient gene regulatory networks using data from two different expression platforms from The Cancer Genome Atlas (n=522 and 431). We performed a comparative network analysis between patients with long- and short-term survival, correcting for patient age, sex, and neoadjuvant treatment status. We identified seven pathways associated with survival, all of which were involved in immune system signaling. Differential regulation of PD1 signaling was validated in an independent dataset from the German Glioma Network (n=70). We found that transcriptional repression of genes in this pathway—for which treatment options are available—was lost in short-term survivors and that this was independent of mutation burden and only weakly associated with T-cell infiltrate. These results provide a new way to stratify glioblastoma patients that uses network features as biomarkers to predict survival, and identify new potential therapeutic interventions, thus underscoring the value of analyzing gene regulatory networks in individual cancer patients.

scholarly journals Body Mass Index and Metastatic Renal Cell Carcinoma: Clinical and Biological Correlations

2016 ◽  
Vol 34 (30) ◽  
pp. 3655-3663 ◽  
Author(s):  
Laurence Albiges ◽  
A. Ari Hakimi ◽  
Wanling Xie ◽  
Rana R. McKay ◽  
Ronit Simantov ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Validation Cohort ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Atlas Data ◽  
Cancer Genome Atlas ◽  
Low Bmi ◽  
High Bmi

Purpose Obesity is an established risk factor for clear cell renal cell carcinoma (RCC); however, some reports suggest that RCC developing in obese patients may be more indolent. We investigated the clinical and biologic effect of body mass index (BMI) on treatment outcomes in patients with metastatic RCC. Methods The impact of BMI (high BMI: ≥ 25 kg/m2 v low BMI: < 25 kg/m2) on overall survival (OS) and treatment outcome with targeted therapy was investigated in 1,975 patients from the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) and in an external validation cohort of 4,657 patients. Gene expression profiling focusing on fatty acid metabolism pathway, in The Cancer Genome Atlas data set, and immunohistochemistry staining for fatty acid synthase (FASN) were also investigated. Cox regression was undertaken to estimate the association of BMI with OS, adjusted for the IMDC prognostic factors. Results In the IMDC cohort, median OS was 25.6 months (95% CI, 23.2 to 28.6) in patients with high BMI versus 17.1 months (95% CI, 15.5 to 18.5) in patients with low BMI (adjusted hazard ratio, 0.84; 95% CI, 0.73 to 0.95). In the validation cohort, high BMI was associated with improved OS (adjusted hazard ratio, 0.83; 95% CI, 0.74 to 0.93; medians: 23.4 months [95% CI, 21.9 to 25.3 months] v 14.5 months [95% CI, 13.8 to 15.9 months], respectively). In The Cancer Genome Atlas data set (n = 61), FASN gene expression inversely correlated with BMI (P = .034), and OS was longer in the low FASN expression group (medians: 36.8 v 15.0 months; P = .002). FASN immunohistochemistry positivity was more frequently detected in IMDC poor (48%) and intermediate (34%) risk groups than in the favorable risk group (17%; P-trend = .015). Conclusion High BMI is a prognostic factor for improved survival and progression-free survival in patients with metastatic RCC treated with targeted therapy. Underlying biology suggests a role for the FASN pathway.

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