scholarly journals Adrenocortical Carcinoma Steroid Profiles: In Silico Pan-Cancer Analysis of TCGA Data Uncovers Immunotherapy Targets for Potential Improved Outcomes

2021 ◽  
Vol 12 ◽  
Author(s):  
João C. D. Muzzi ◽  
Jessica M. Magno ◽  
Milena A. Cardoso ◽  
Juliana de Moura ◽  
Mauro A. A. Castro ◽  
...  
Keyword(s):  
Immune Evasion ◽  
Adrenocortical Carcinoma ◽  
In Silico ◽  
Immune Cell ◽  
Treatment Options ◽  
The Cancer Genome Atlas ◽  
Immune Modulators ◽  
Cancer Subtypes ◽  
Steroid Profiles ◽  
Immune Pathways

Despite progress in understanding the biology of adrenocortical carcinoma (ACC), treatment options have not dramatically changed in the last three decades, nor have we learned how to avoid some of its long-term side effects. Our goal was to improve the understanding of immune pathways that may include druggable targets to enhance immune responses of patients with ACC, focusing on immune evasion and the activation of immune cells against ACC. Our strategy was aimed at improving insight regarding gene expression without steroid interference. Using approaches based on high and low steroid phenotypes (HSP and LSP, respectively), we characterized immune pathways using The Cancer Genome Atlas (TCGA) ACC cohort data. Although previous studies have suggested that patients with ACC receive minimal benefit from immunotherapy, high expression of immune modulators was noted in patients with LSP, suggesting the activation of these biomarkers may be an important adjuvant therapy target after clearance of excess glucocorticoids. In addition, patients with LSP ACC had higher immune cell infiltration than patients with HSP ACC and other cancer subtypes. Our findings can be summarized as follows (1): we confirmed and improved the definition of two immune response pathways to ACC (HSP and LSP) based on in silico transcriptome analysis (2), we demonstrated the steroid profile should be considered, otherwise analyses of ACC immune characteristics can generate confounding results (3), among the overexpressed immunotherapy targets, we demonstrated that LSP was rich in PDCD1LG2 (PD-L2) and both HSP and LSP overexpressed CD276 (B7-H3), which was associated with resistance to anti-PD1 therapy and may have accounted for the modest results of previous clinical trials, and (4) identification of patients with LSP or HSP ACC can be used to help determine whether immunotherapy should be used. In conclusion, we highlighted the differences between LSP and HSP, drawing attention to potential therapeutic targets (CD276, PDCD1, and PDCD1LG2). Treatments to reduce immune evasion, as well as the use of other natural and pharmacological immune activators, should include prior pharmacological inhibition of steroidogenesis. Attempts to combine these with tumor cell proliferation inhibitors, if they do not affect cells of the immune system, may produce interesting results.

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 Cancer Stemness Associated With Prognosis and the Efficacy of Immunotherapy in Adrenocortical Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoxi Shi ◽  
Yuanlin Liu ◽  
Shuai Cheng ◽  
Haidi Hu ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Adrenocortical Carcinoma ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Potential Biomarker ◽  
Lower Expression

BackgroundCancer stem cells (CSCs) have been proven to influence drug resistance, recurrence, and metastasis in tumors. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in adrenocortical carcinoma.MethodsRNA-seq data and clinical characteristics were downloaded from The Cancer Genome Atlas (TCGA). The stemness indexes, mDNAsi and mRNAsi, were calculated to classify all samples into low-score and high-score groups. Two algorithms, based on the R language, ESTIMATE and single-sample Gene Set Enrichment Analysis (ssGSEA) were used to assess the immune cell infiltration states of adrenocortical carcinoma patients. Weighted Gene Co-expression Network Analysis (WGCNA) was used to find genes that were related to the stemness of cancer. By bioinformatics methods, the correlations between biomarkers capable of predicting immune checkpoint inhibitors (ICIs) responses and stemness of cancer were explored.ResultsHigh-mRNAsi predicted shorter overall survival (OS) and a higher metastatic trend in adrenocortical carcinoma (ACC) patients. Compared with the low-mRNAsi group, the high-mRNAsi group had a lower ImmuneScore and StromalScroe. Twenty-two stemness-related prognostic genes were obtained by WGCNA, which focused on the function of the cell cycle and cell mitosis. Immune cell infiltration, especially CD8+T cell, increased in the low-mRNAsi group compared with the high-mRNAsi group. Lower expression of PD-L1, CTLA-4, and TIGHT was evaluated in the high-mRNAsi group.ConclusionsACC patients with high-mRNAsi have poor prognosis and less immune cell infiltration. Combined with the finding of lower expression of CTLA-4, TIGHT, and PD-L1 in the high-mRNAsi group, we came to the conclusion that stemness index is a potential biomarker to predict the effectiveness of ICIs.

scholarly journals The landscape of interactions between cancer polygenic risk scores and somatic alterations in cancer cells

2020 ◽  
Author(s):  
Eduard Porta-Pardo ◽  
Rosalyn Sayaman ◽  
Elad Ziv ◽  
Alfonso Valencia
Keyword(s):  
Predictive Power ◽  
Molecular Subtypes ◽  
Treatment Options ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Cancer Type ◽  
Clinical Implementation ◽  
Polygenic Risk ◽  
Cancer Subtypes ◽  
Somatic Alterations

Over the last 15 years we have identified hundreds of inherited variants that increase the risk of developing cancer. Polygenic risk scores (PRS) summarize the genetic risk of each individual by accounting for the unique combination of risk alleles in their genome. So far, most studies of PRS in cancer have focused on their predictive value: i.e. to what extent the PRS can predict which individuals will develop a particular cancer type. In parallel, for most cancers, we have identified several subtypes based on their somatic molecular properties. However, little is known about the relationship between the somatic molecular subtypes of cancer and PRS and it is possible that PRS preferentially predict specific cancer subtypes. Since cancer subtypes can have very different outcomes, treatment options and molecular vulnerabilities, answering this question is very important to understand the consequences that widespread PRS use would have in which tumors are detected early. Here we used data from The Cancer Genome Atlas (TCGA) to study the correlation between PRS for different forms of cancer and the landscape of somatic alterations in the tumors developed by each patient. We first validated the predictive power of 8 different PRS in TCGA and describe how PRS for some cancer types are associated with specific molecular subtypes or somatic cancer driver events. Our results highlight important questions that could improve the predictive power of PRS and that need to be answered before their widespread clinical implementation.

scholarly journals Establishment of Novel DNA Methylation-Based Prostate Cancer Subtypes and a Risk-Predicting Eight-Gene Signature

2021 ◽  
Vol 9 ◽  
Author(s):  
Enchong Zhang ◽  
Fujisawa Shiori ◽  
Oscar YongNan Mu ◽  
Jieqian He ◽  
Yuntian Ge ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Immune Cell ◽  
Methylation Status ◽  
Disease Status ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Cancer Subtypes ◽  
Cpg Sites ◽  
Selection Operator

Prostate cancer (PCa) is the most common malignant tumor affecting males worldwide. The substantial heterogeneity in PCa presents a major challenge with respect to molecular analyses, patient stratification, and treatment. Least absolute shrinkage and selection operator was used to select eight risk-CpG sites. Using an unsupervised clustering analysis, called consensus clustering, we found that patients with PCa could be divided into two subtypes (Methylation_H and Methylation_L) based on the DNA methylation status at these CpG sites. Differences in the epigenome, genome, transcriptome, disease status, immune cell composition, and function between the identified subtypes were explored using The Cancer Genome Atlas database. This analysis clearly revealed the risk characteristics of the Methylation_H subtype. Using a weighted correlation network analysis to select risk-related genes and least absolute shrinkage and selection operator, we constructed a prediction signature for prognosis based on the subtype classification. We further validated its effectiveness using four public datasets. The two novel PCa subtypes and risk predictive signature developed in this study may be effective indicators of prognosis.

scholarly journals In Silico Analysis Reveals a Shared Immune Signature in CASP8-Mutated Carcinomas with Varying Correlations to Prognosis

2018 ◽  
Author(s):  
Yashoda Ghanekar ◽  
Subhashini Sadasivam
Keyword(s):  
Overall Survival ◽  
Cell Death ◽  
In Silico ◽  
Immune Cell ◽  
Negative Regulator ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Tumor Cell Death ◽  
Immune Signature ◽  
Molecular Features

AbstractBackgroundSequencing studies across multiple cancers continue to reveal the spectrum of mutations and genes involved in the pathobiology of these cancers. Exome sequencing of oral cancers, a subset of Head and Neck Squamous cell Carcinomas (HNSCs) common among tobacco-chewing populations, revealed that ~34% of the affected patients harbor mutations in the CASP8 gene. Uterine Corpus Endometrial Carcinoma (UCEC) is another cancer type where about 10% cases harbor CASP8 mutations. Caspase-8, the protease encoded by CASP8 gene, plays a dual role in programmed cell death, which in turn has an important role in tumor cell death and drug resistance. CASP8 is a protease required for the extrinsic pathway of apoptosis and is also a negative regulator of necroptosis. Using bioinformatics approaches to mine data in The Cancer Genome Atlas, we compared the molecular features and survival of these carcinomas with and without CASP8 mutations.ResultsOur in silico analyses showed that HNSCs with CASP8 mutations displayed a prominent signature of genes involved in immune response and inflammation, and were rich in immune cell infiltrates. However, in contrast to Human Papilloma Virus-positive HNSCs, a subtype that exhibits high immune cell infiltration and better overall survival, HNSC patients with mutant-CASP8 tumors did not display any survival advantage. A similar bioinformatic analyses in UCECs revealed that while UCECs with CASP8 mutations also displayed an immune signature, they had better overall survival, in contrast to the HNSC scenario. On further examination, we found that there was significant up-regulation of neutrophils as well as the cytokine, IL33 in mutant-CASP8 HNSCs, both of which were not observed in mutant-CASP8 UCECs.ConclusionsThese results suggested that carcinomas with mutant CASP8 have broadly similar immune signatures albeit with different effects on survival. We hypothesize that subtle tissue-dependent differences could influence survival by modifying the micro-environment of mutant-CASP8 carcinomas. High neutrophil numbers, which is a well-known negative prognosticator in HNSCs, and/or high IL33 levels may be some of the factors affecting survival of mutant-CASP8 cases.

scholarly journals Cancer subtype identification using somatic mutation data

2017 ◽  
Author(s):  
Marieke L. Kuijjer ◽  
Joseph N. Paulson ◽  
Peter Salzman ◽  
Wei Ding ◽  
John Quackenbush
Keyword(s):  
Somatic Mutation ◽  
Treatment Options ◽  
Biological Pathways ◽  
The Cancer Genome Atlas ◽  
Phenotypic Data ◽  
Primary Tumors ◽  
Cancer Subtypes ◽  
Cancer Types ◽  
Mutation Data ◽  
Pan Cancer

BACKGROUNDWith the onset of next generation sequencing technologies, we have made great progress in identifying recurrent mutational drivers of cancer. As cancer tissues are now frequently screened for specific sets of mutations, a large amount of samples has become available for analysis. Classification of patients with similar mutation profiles may help identifying subgroups of patients who might benefit from specific types of treatment. However, classification based on somatic mutations is challenging due to the sparseness and heterogeneity of the data.METHODSHere, we describe a new method to de-sparsify somatic mutation data using biological pathways. We applied this method to 23 cancer types from The Cancer Genome Atlas, including samples from 5, 805 primary tumors.RESULTSWe show that, for most cancer types, de-sparsified mutation data associates with phenotypic data. We identify poor prognostic subtypes in three cancer types, which are associated with mutations in signal transduction pathways for which targeted treatment options are available. We identify subtype-drug associations for 14 additional subtypes. Finally, we perform a pan-cancer subtyping analysis and identify nine pan-cancer subtypes, which associate with mutations in four overarching sets of biological pathways.CONCLUSIONSThis study is an important step towards understanding mutational patterns in cancer.

Immune correlates of CD73 expression in patients with urothelial carcinoma (UC).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4548-4548
Author(s):  
Edwin Lin ◽  
Roberto Nussenzveig ◽  
Andrew W Hahn ◽  
Mark Yandell ◽  
Lauren Christine Harshman ◽  
...  
Keyword(s):  
Nk Cells ◽  
Immune Evasion ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Statistical Significance ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Cancer Dataset ◽  
Immune Correlates ◽  
Tumor Phenotype

4548 Background: Checkpoint inhibitors have improved outcomes in UC. However, response rates are low and additional mechanisms of immune evasion need to be ascertained. CD73 (encoded by NT5E) converts extracellular AMP to adenosine, which exerts an immunosuppressive effect in the tumor microenvironment by inhibiting infiltrating T and NK cells. Utilizing The Cancer Genome Atlas (TCGA) bladder cancer dataset, we evaluated correlations between NT5E expression and the immune milieu in UC. Methods: RNA-seq data from 411 primary UC tumor samples were obtained from the TCGA. Patients were split into low, intermediate, and high NT5E expression groups (≤ -1, -1 to 1 and ≥1 standard deviation from the overall mean). A tumor inflammation signature (TIS) reflecting an inflamed tumor phenotype was calculated based on the averaged expression of 18 previously validated genes (Ayers et al, 2017). NT5E expression was compared between tumors with high and low TIS scores and among the TCGA molecular subtypes. Abundance of infiltrating immune cell subsets was estimated based on expression of previously identified 782 immune metagenes and compared between NT5E expression groups (Charoentong et al, 2017). The Mann-Whitney U test assessed statistical significance, and the Bonferroni correction was used to control for false discovery rate. Results: NT5E expression was significantly higher in tumors with a high TIS score compared to those with low TIS score (P<0.0001) and correlated with expression of other immune checkpoints such as PD-L1, IDO and LAG-3 (each P<0.01). Patients with basal/squamous subtype had the highest NT5E expression compared to luminal or neuronal subtypes. High NT5E expression was associated with increased infiltrating NK cells, neutrophils, Tregs and decreased Type 2 T helper cells. Conclusions: High expression of NT5E in UC patients with an inflamed tumor phenotype was associated with an increase in infiltrating Tregs, and the basal/squamous subtype. Our findings highlight a potential role of CD73-adenosine pathway as a mechanism of immune evasion and a novel therapeutic target in UC. Further studies to assess the clinical impact of NT5E expression on outcomes in UC patients treated with immunotherapy are needed. AT and NA: equal contribution.

scholarly journals Uncovering the Subtype-Specific Molecular Characteristics of Breast Cancer by Multiomics Analysis of Prognosis-Associated Genes, Driver Genes, Signaling Pathways, and Immune Activity

2021 ◽  
Vol 9 ◽  
Author(s):  
Xinhui Li ◽  
Jian Zhou ◽  
Mingming Xiao ◽  
Lingyu Zhao ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Signaling Pathways ◽  
Immune Cell ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Subtypes ◽  
Molecular Characteristics ◽  
Driver Genes ◽  
Cancer Subtypes ◽  
Molecular Events

Breast cancer is a heterogeneous malignant disease with different prognoses and has been divided into four molecular subtypes. It is believed that molecular events occurring in breast stem/progenitor cells contribute to the carcinogenesis and development of different breast cancer subtypes. However, these subtype-specific molecular characteristics are largely unknown. In this study, we employed 1217 breast cancer samples from The Cancer Genome Atlas (TCGA) database for a multiomics analysis of the molecular characteristics of different breast cancer subtypes based on PAM50 algorithms. We detected the expression changes of subtype-specific genes and revealed that the expression of particular subtype-specific genes significantly affected prognosis. We also investigated the mutations and copy number variations (CNVs) of breast cancer driver genes and the representative genes of ten signaling pathways in different subtypes and revealed several subtype-specifically altered genes. Moreover, we detected the infiltration of various immune cells in different subtypes of breast cancer and showed that the infiltration levels of major immune cell types are different among these subtypes. Additionally, we investigated the factors affecting the immune infiltration level and the immune cytolytic activity in different breast cancer subtypes, namely, the mutation burden, genome instability and cancer-associated fibroblast (CAF) infiltration. This study may shed light on the molecular events contributing to carcinogenesis and development and provide potential markers and targets for the clinical diagnosis and treatment of different breast cancer subtypes.

scholarly journals Comprehensive Analysis of Subtype-Specific Molecular Characteristics of Colon Cancer: Specific Genes, Driver Genes, Signaling Pathways, and Immunotherapy Responses

2021 ◽  
Vol 9 ◽  
Author(s):  
Fangjie Hu ◽  
Jianyi Wang ◽  
Minghui Zhang ◽  
Shuoshuo Wang ◽  
Lingyu Zhao ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Signaling Pathways ◽  
Classification System ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Driver Genes ◽  
Cancer Subtypes

Colon cancer is a complex, heterogeneous disease. The Colorectal Cancer Subtyping Consortium reported a novel classification system for colon cancer in 2015 to better understand its heterogeneity. This molecular classification system divided colon cancer into four distinct consensus molecular subtypes (CMS 1, 2, 3, and 4). However, the characteristics of different colon cancer molecular subtypes have not been fully elucidated. This study comprehensively analyzed the molecular characteristics of varying colon cancer subtypes using multiple databases and algorithms, including The Cancer Genome Atlas (TCGA) database, DriverDBv3 database, CIBERSORT, and MCP-counter algorithms. We analyzed the alterations in the subtype-specific genes of different colon cancer subtypes, such as the RNA levels and DNA alterations, and showed that specific subtype-specific genes significantly affected prognosis. We also explored the changes in colon cancer driver genes and representative genes of 10 signaling pathways in different subtypes. We identified genes that were altered in specific subtypes. We further detected the infiltration of 22 immune cell types in four colon cancer subtypes and the infiltration level of primary immune cells among these subtypes. Additionally, we explored changes in immune checkpoint genes (ICGs) and immunotherapy responses among different colon cancer subtypes. This study may provide clues for the molecular mechanism of tumorigenesis and progression in colon cancer. It also offers potential biomarkers and targets for the clinical diagnosis and treatment of different colon cancer subtypes.

Pursuit of the Abscopal Effect

2020 ◽  
Vol 04 (04) ◽  
pp. 369-372
Author(s):  
Paul B. Romesser ◽  
Christopher H. Crane
Keyword(s):  
Tumor Immunology ◽  
Antitumor Immunity ◽  
Clinical Success ◽  
Immune Recognition ◽  
Immune Modulators ◽  
Cancer Subtypes ◽  
The Past ◽  
Tumor Irradiation ◽  
Wide Range ◽  
Tumor Recognition

AbstractEvasion of immune recognition is a hallmark of cancer that facilitates tumorigenesis, maintenance, and progression. Systemic immune activation can incite tumor recognition and stimulate potent antitumor responses. While the concept of antitumor immunity is not new, there is renewed interest in tumor immunology given the clinical success of immune modulators in a wide range of cancer subtypes over the past decade. One particularly interesting, yet exceedingly rare phenomenon, is the abscopal response, characterized by a potent systemic antitumor response following localized tumor irradiation presumably attributed to reactivation of antitumor immunity.

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