scholarly journals Systems Biology Approach Identifies Prognostic Signatures of Poor Overall Survival and Guides the Prioritization of Novel BET-CHK1 Combination Therapy for Osteosarcoma

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2426
Author(s):  
Pankita H. Pandya ◽  
Lijun Cheng ◽  
M. Reza Saadatzadeh ◽  
Khadijeh Bijangi-Vishehsaraei ◽  
Shan Tang ◽  
...  

Osteosarcoma (OS) patients exhibit poor overall survival, partly due to copy number variations (CNVs) resulting in dysregulated gene expression and therapeutic resistance. To identify actionable prognostic signatures of poor overall survival, we employed a systems biology approach using public databases to integrate CNVs, gene expression, and survival outcomes in pediatric, adolescent, and young adult OS patients. Chromosome 8 was a hotspot for poor prognostic signatures. The MYC-RAD21 copy number gain (8q24) correlated with increased gene expression and poor overall survival in 90% of the patients (n = 85). MYC and RAD21 play a role in replication-stress, which is a therapeutically actionable network. We prioritized replication-stress regulators, bromodomain and extra-terminal proteins (BETs), and CHK1, in order to test the hypothesis that the inhibition of BET + CHK1 in MYC-RAD21+ pediatric OS models would be efficacious and safe. We demonstrate that MYC-RAD21+ pediatric OS cell lines were sensitive to the inhibition of BET (BETi) and CHK1 (CHK1i) at clinically achievable concentrations. While the potentiation of CHK1i-mediated effects by BETi was BET-BRD4-dependent, MYC expression was BET-BRD4-independent. In MYC-RAD21+ pediatric OS xenografts, BETi + CHK1i significantly decreased tumor growth, increased survival, and was well tolerated. Therefore, targeting replication stress is a promising strategy to pursue as a therapeutic option for this devastating disease.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14538-e14538
Author(s):  
Hainan Li ◽  
Changguo Shan ◽  
Chongzhu Fan ◽  
Shengnan Wu ◽  
Mingyao Lai ◽  
...  

e14538 Background: Molecular charactersitcs are essential for the classification and grading of gliomas. However, majority of current understanding is based on public databases that might not accurately reflect the Asian population. Here, we studied the mutation landscape of Chinese glioma patients in hope to provide new insights for glioma prognosis and treatment. Methods: Tissue samples from 112 glioma patients underwent next-generation sequencing targeting 425 cancer-relevant genes. Gene mutations and copy number variations were investigated for their prognostic effect using overall survival data. Pathway-based survival analysis was peformed using top ten predefined oncogenic pathways. Results: We identified similar prevalence of currently established molecular diagnostic markers of glioma, including TP53 (33%), EGFR(26%), TERT (24%), PTEN (21%), ATRX (14%), BRAF (13%) and IDH1/2 (6%). Among all genetic abberations with more than 5% occurrence rate, four mutations and four copy number gains were significantly associated with poor overall survival (univariate, P < 0.05). Of these, TERT mutations (hazard ratio [HR], 3.14; 95% confidence interval [CI], 1.31 to 7.49; P = 0.01) and EGFR amplification (HR, 2.67; 95% CI, 1.20 to 5.95; P = 0.02) remained significant after adjusting for clinical parameters. Similarly, PIK3CA mutations, which was also frequently mutated in glioma but not used for clinical classification, were found to correlate with poor prognosis (HR, 2.61; 95% CI, 1.19 to 5.74; P = 0.02). Additionally, we have also identified MCL1 amplification as a potential novel biomarker for glioma (HR, 2.73; 95% CI, 1.47 to 5.07; P < 0.001), which was seldom reported in the TCGA database and might possibly be ancestral specific giving its high prevelance in our cohort (found in 32% patients). Pathway analyses revealed significantly worse prognosis with abnormal PI3K (HR, 1.81; 95% CI, 1.12 to 2.95; P = 0.02) and cell cycle pathways (HR, 2.04; 95% CI, 1.2 to 3.47; P < 0.001), both of which stayed meaningful after adjusting for clinical factors. Conclusions: In this study, we discovered PIK3CA mutations and MCL1 amplification as novel prognostic markers of glioma. We also demonstrated shorter survival with abnormal PI3K and cell cycle pathways that provided an intergrative understanding of glioma.


2021 ◽  
Vol 10 ◽  
Author(s):  
Hainan Li ◽  
Changguo Shan ◽  
Shengnan Wu ◽  
Baijie Cheng ◽  
Chongzu Fan ◽  
...  

BackgroundMolecular characteristics are essential for the classification and grading of gliomas. However, diagnostic classification of midline glioma is still debatable and substantial molecular and clinical heterogeneity within each subgroup suggested that they should be further stratified. Here, we studied the mutation landscape of Chinese midline glioma patients in hope to provide new insights for glioma prognosis and treatment.MethodsTissue samples from 112 midline glioma patients underwent next-generation sequencing targeting 425 cancer-relevant genes. Gene mutations and copy number variations were investigated for their somatic interactions and prognostic effect using overall survival data. Pathway-based survival analysis was performed for ten canonical oncogenic pathways.ResultsWe identified several currently established diagnostic and prognostic biomarkers of glioma, including TP53 (33%), EGFR (26%), TERT (24%), PTEN (21%), PIK3CA (14%), ATRX (14%), BRAF (13%), and IDH1/2 (6%). Among all genetic aberrations with more than 5% occurrence rate, six mutations and three copy number gains were greatly associated with poor overall survival (univariate, P &lt; 0.1). Of these, TERT mutations (hazard ratio [HR], 3.00; 95% confidence interval [CI], 1.37–6.61; P = 0.01) and PIK3CA mutations (HR, 2.04; 95% CI, 1.08–3.84; P = 0.02) remained significant in multivariate analyses. Additionally, we have also identified a novel MCL1 amplification (found in 31% patients) as a potential independent biomarker for glioma (multivariate HR, 2.78; 95% CI, 1.53–5.08; P &lt; 0.001), which was seldom reported in public databases. Pathway analyses revealed significantly worse prognosis with abnormal PI3K (HR, 1.81; 95% CI, 1.12–2.95; P = 0.01) and cell cycle pathways (HR, 1.97; 95% CI, 1.15–3.37; P = 0.01), both of which stayed meaningful after multivariate adjustment.ConclusionsIn this study, we discovered shorter survival in midline glioma patients with PIK3CA and TERT mutations and with abnormal PI3K and cell cycle pathways. We also revealed a novel prognostic marker, MCL1 amplification that collectively provided new insights and opportunities in understanding and treating midline gliomas.


2017 ◽  
Vol 55 (2) ◽  
pp. 1299-1322 ◽  
Author(s):  
Giovanna Morello ◽  
Maria Guarnaccia ◽  
Antonio Gianmaria Spampinato ◽  
Valentina La Cognata ◽  
Velia D’Agata ◽  
...  

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 434-434
Author(s):  
Eva Chao ◽  
Kyaw Lwin Aung ◽  
Qi Xu ◽  
William H. Matsui ◽  
Jeanne Kowalski

434 Background: There is no known molecular taxonomy of pancreatic cancer that can guide therapeutic strategies. Understanding the fundamental molecular mechanism underlying pancreatic cancer biology remains an unmet need. We explore the extent to which combinations of DNA-based molecular changes in copy number (CN) and methylation separate early stage PAAD tumors and associated with survival outcomes. Methods: We performed genome-wide combined cluster analyses on DNA-based CN and methylation changes using TCGA data. We examined cluster associations with clinical outcomes by comparing in months (mos), Kaplan--Meier estimated overall survival (OS) and disease-free interval (DFI) using a log-rank test. We performed additional comparisons among CN-Methylation derived clusters with respect to PAAD phenotypes. Results: Using 78 early stage pancreatic cancer tumors from TCGA with CN, methylation and clinical outcomes data, we identified two patient clusters with distinct gene copy number signatures that when combined with three methylation signatures, resulted in three additional clusters. Thus, the same gene CN signature, when combined with different methylation signatures, further differentiated tumors into sub-clusters with varying levels of associations with clinical outcome. Among them, analogous to current gene-expression based subtypes, we also identified an immune-rich subtype that was associated with improved overall survival (n=21, median OS=16mos; DFI=16mos), and an extracellular matrix (ECM)-rich with worse survival (n=19, median OS=12mos; DFI=8mos). Unlike previous expression subtypes, we identified another metabolic-enriched subtype with the same worse median OS and DFI, differentiated by methylation with the ECM-rich subtype. The improved OS cluster had a signature of CN neutral and increased methylation, while the poor cluster had a signature of CN gains and increased methylation among a set of genes distinct from the improved cluster. No significant differences in age, site, microsatellite instability and KRAS status among clusters were noted. Notably, in a multivariable model that included gene expression-based subtypes, only our DNA-level subtypes remained significantly associated with overall survival. Conclusions: While RNA-level changes often display large variations, DNA-level changes are more robust. Copy number changes appear to separate tumors into poor and improved prognosis clusters, while methylation appears to inform on the further separation of poor prognosis into various levels. A DNA-based molecular taxonomy for early stage pancreatic cancer could prove invaluable when used in combination with methylation-based circulating tumor DNA assays for clinical trial monitoring of tumor responses.


2020 ◽  
Vol 48 (1) ◽  
pp. 156-165
Author(s):  
Habtamu Abera Goshu ◽  
Wu Xiaoyun ◽  
Min Chu ◽  
Bao Pengjia ◽  
Ding Xue Zhi ◽  
...  

PLoS ONE ◽  
2011 ◽  
Vol 6 (9) ◽  
pp. e24829 ◽  
Author(s):  
Tzu-Pin Lu ◽  
Liang-Chuan Lai ◽  
Mong-Hsun Tsai ◽  
Pei-Chun Chen ◽  
Chung-Ping Hsu ◽  
...  

2018 ◽  
Vol 71 (9) ◽  
pp. 787-794 ◽  
Author(s):  
Stephanie Robertson ◽  
Gustav Stålhammar ◽  
Eva Darai-Ramqvist ◽  
Mattias Rantalainen ◽  
Nicholas P Tobin ◽  
...  

AimsThe accuracy of biomarker assessment in breast pathology is vital for therapy decisions. The therapy predictive and prognostic biomarkers oestrogen receptor (ER), progesterone receptor, HER2 and Ki67 may act as surrogates to gene expression profiling of breast cancer. The aims of this study were to investigate the concordance of consecutive biomarker assessment by immunocytochemistry on preoperative fine-needle aspiration cytology versus immunohistochemistry (IHC) on the corresponding resected breast tumours. Further, to investigate the concordance with molecular subtype and correlation to stage and outcome.MethodsTwo retrospective cohorts comprising 385 breast tumours with clinicopathological data including gene expression-based subtype and up to 10-year overall survival data were evaluated.ResultsIn both cohorts, we identified a substantial variation in Ki67 index between cytology and histology and a switch between low and high proliferation within the same tumour in 121/360 cases. ER evaluations were discordant in only 1.5% of the tumours. From cohort 2, gene expression data with PAM50 subtype were used to correlate surrogate subtypes. IHC-based surrogate classification could identify the correct molecular subtype in 60% and 64% of patients by cytology (n=63) and surgical resections (n=73), respectively. Furthermore, high Ki67 in surgical resections but not in cytology was associated with poor overall survival and higher probability for axillary lymph node metastasis.ConclusionsThis study shows considerable differences in the prognostic value of Ki67 but not ER in breast cancer depending on the diagnostic method. Furthermore, our findings show that both methods are insufficient in predicting true molecular subtypes.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3360-3360
Author(s):  
Erik Wendlandt ◽  
Guido J. Tricot ◽  
Benjamin Darbro ◽  
Fenghuang Zhan

Abstract Background: Multiple myeloma is the second most common blood borne neoplasia, accounting for nearly 10% of all diagnosed hematologic malignancies and has a disproportionately high incidence in elderly populations. Here we explored copy number variations using the high fidelity CytoScan HD arrays to develop a detailed map of copy number variations and identify novel mediators of disease progression. The results from CytoScan HD microarrays provide a detailed view of the entire genome with a resolution up to 25kb. Furthermore, 750,000 single-nucleotide polymorphisms are included and the array provides information about loss of heterozygosity and uniparental disomy. Materials and methods: CytoScan HD arrays were performed on 97 myeloma patient samples to identify cytogenetic regions important to the development and progression of the disease. Gene expression profiles from 351 patients were analyzed to identify genes with a change in gene expression of 1.5 fold or more. Data from CytoScan and gene expression arrays was combined to perform chromosomal positional enrichment analysis to identify cytogenetic driver lesions, or lesions that provide a small, but significant growth and survival advantage to the cell. Furthermore, Kaplan-Meier, log-rank test and Hazard ratio analyses were performed to identify gene within the driver lesions that have a significant impact on survival when dysregulated. Results: The results from the CytoScan HD analysis closely mirrored what has been shown by FISH and SNP arrays, with gains to the odd numbered chromosomes, specifically 3, 5, 7, 9, 11, 15 and 17 as well as losses to chromosomes 1p and 13. Interestingly, we identified gains to a small region within chromosome 8p, contrary to published reports demonstrating a large scale loss of this region. We identified numerous genes within this region that are important for survival and their overexpression resulted in a decreased progression free survival. For example, Cathepsin B (CTSB) is encoded for in chromosome 8p22-p21 with an increased gene expression of at least 1.5 fold over normal controls, among others. Furthermore, Cathepsin B, a cysteine protease, has been linked to cancer of the ileum, suggesting that a similar role may be present within myeloma. We then integrated the 97 copy number profiles results with 351 myeloma gene expression profiles to identify cytogenetic driver lesions in myeloma important for disease development, progression and poor clinical outcome. Chromosomal positional enrichment analysis was employed to identify global myeloma cytogenetic driver aneuploidies as well as develop unique cytogenetic copy number profiles. Our results identified portions of chromosomes 1q, 3, 8p, 9, 13q and 16q, among others, as important driver lesions with changes to these regions providing growth advantages to the cell. Furthermore, our analysis identified five unique cytogenetic classifications based on common cytogenetic lesions. We continue to explore these driver regions to identify lesions important for the oncogenic properties of the larger regions. Conclusion: The data presented here represents a novel and highly sensitive approach for the identification of novel copy number variations and driver lesions. Furthermore, correlations between copy number variations and gene expression arrays identified novel targets important for disease progression and patient survival. CytoScan HD arrays in conjunction with gene expression analysis provided a high resolution image of important cytogenetic lesions in myeloma and identified potentially important therapeutic targets for drug development. Further work is needed to validate our findings and determine the therapeutic efficacy of the identified targets. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2841-2841 ◽  
Author(s):  
Yosaku Watatani ◽  
Yasunobu Nagata ◽  
Vera Grossmann ◽  
Yusuke Okuno ◽  
Tetsuichi Yoshizato ◽  
...  

Abstract Myelodysplastic syndromes (MDS) and related disorders are a heterogeneous group of chronic myeloid neoplasms with a high propensity to acute myeloid leukemia. A cardinal feature of MDS, as revealed by the recent genetic studies, is a high frequency of mutations and copy number variations (CNVs) affecting epigenetic regulators, such as TET2, IDH1/2, DNMT3A, ASXL1, EZH2, and other genes, underscoring a major role of deregulated epigenetic regulation in MDS pathogenesis. Meanwhile, these mutations/deletions have different impacts on the phenotype and the clinical outcome of MDS, suggesting that it should be important to understand the underlying mechanism for abnormal epigenetic regulation for better classification and management of MDS. SETD2 and ASH1L are structurally related proteins that belong to the histone methyltransferase family of proteins commonly engaged in methylation of histone H3K36. Both genes have been reported to undergo frequent somatic mutations and copy number alterations, and also show abnormal gene expression in a variety of non-hematological cancers. Moreover, germline mutation of SETD2 has been implicated in overgrowth syndromes susceptible to various cancers. However, the role of alterations in these genes has not been examined in hematological malignancies including myelodysplasia. In this study, we interrogated somatic mutations and copy number variations, among a total of 1116 cases with MDS and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), who had been analyzed by target deep sequencing (n=944), and single nucleotide polymorphism-array karyotyping (SNP-A) (n=222). Gene expression was analyzed in MDS cases and healthy controls, using publically available gene expression datasets. SETD2 mutations were found in 6 cases, including 2 with nonsense and 4 with missense mutations, and an additional 10 cases had gene deletions spanning 1.8-176 Mb regions commonly affecting the SETD2 locus in chromosome 3p21.31, where SETD2 represented the most frequently deleted gene within the commonly deleted region. SETD2 deletion significantly correlated with reduced SETD2 expression. Moreover, MDS cases showed a significantly higher SETD2 expression than healthy controls. In total, 16 cases had either mutations or deletions of the SETD2 gene, of which 70% (7 out of 10 cases with detailed diagnostic information) were RAEB-1/2 cases. SETD2 -mutated/deleted cases had frequent mutations in TP53 (n=4), SRSF2 (n=3), and ASXL1 (n=3) and showed a significantly poor prognosis compared to those without mutations/deletions (HR=3.82, 95%CI; 1.42-10.32, P=0.004). ASH1L, on the other hand, was mutated and amplified in 7 and 13 cases, respectively, of which a single case carried both mutation and amplification with the mutated allele being selectively amplified. All the mutations were missense variants, of which 3 were clustered between S1201 and S1209. MDS cases showed significantly higher expression of ASH1L compared to healthy controls, suggesting the role of ASH1L overexpression in MDS development. Frequent mutations in TET2 (n=8) and SF3B1 (n=6) were noted among the 19 cases with ASH1L lesions. RAEB-1/2 cases were less frequent (n=11) compared to SETD2-mutated/deleted cases. ASH1L mutations did not significantly affect overall survival compared to ASH1L-intact cases. Gene Set Expression Analysis (Broad Institute) on suppressed SETD2 and accelerated ASH1L demonstrated 2 distinct expression signatures most likely due to the differentially methylated H3K36. We described recurrent mutations and CNVs affecting two histone methyltransferase genes, which are thought to represent novel driver genes in MDS involved in epigenetic regulations. Given that SETD2 overexpression and reduced ASH1L expression are found in as many as 89% of MDS cases, deregulation of both genes might play a more role than expected from the incidence of mutations and CNVs alone. Although commonly involved in histone H3K36 methylation, both methyltransferases have distinct impacts on the pathogenesis and clinical outcome of MDS in terms of the mode of genetic alterations and their functional consequences: SETD2 was frequently affected by truncating mutations and gene deletions, whereas ASH1L underwent gene amplification without no truncating mutations, suggesting different gene targets for both methyltransferases, which should be further clarified through functional studies. Disclosures Alpermann: MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Shih:Novartis: Research Funding.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 9510-9510
Author(s):  
Edoardo Missiaglia ◽  
Dan Williamson ◽  
Julia C. Chisholm ◽  
Pratyaksha Wirapati ◽  
Gaëlle Pierron ◽  
...  

9510 Background: Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma and comprises two major histological subtypes: alveolar and embryonal. The majority of alveolar tumors harbor PAX/FOXO1 fusion genes. Current patient risk stratification, unlike other pediatric embryonal tumors, does not utilize any molecular data. Therefore, we aimed to improve the risk stratification of RMS patients through the use of molecular biological data. Methods: Two independent data sets of gene expression profiling for 124 and 101 RMS were used to derive prognostic gene signatures by meta-analysis. Genomic array CGH data for 109 RMS was also evaluated to develop a prognostic marker based on copy number variations (CNVs). The performance and usefulness of these derived metagenes and CNVs as well as a previously published metagene signature were evaluated using rigorous leave-one-out cross-validation analyses. Results: The new prognostic gene expression signature, MG15, and one previously published (MG34) (Davicioni. JCO. 2010) performed well with reproducible and significant effects (HR 3.2 [1.7-5.9] p < 0.001 and HR 2.5 [1.5-4.3] p < 0.001, respectively). However, they did not significantly add new prognostic information over the fusion gene status (PAX3/FOXO1, PAX7/FOXO1 and Negative). Similarly, a prognostic CNV marker, although showing HR 2.9 [1.5-5.6] p < 0.01, was also not improving models with fusion gene status. Within fusion negative RMS, the analysis identified prognostic markers based on either gene expression or CNVs and showed significant association with patients outcome (HR 6.3 [1.5-26.3] p ≤ 0.016 and HR 11.2 [2.5-50.7] p < 0.010, respectively). Moreover, these were able to identify distinct risk groups within the COG (Children's Oncology Group) risk categories, which is currently used to guide treatment. Conclusions: Molecular signatures derived using all RMS effectively stratify patients by their risk, but most of their prognostic information is contained in the PAX/FOXO1 fusion gene status which is simpler to assay. New markers developed within the fusion negative population seem improving current RMS risk classifier and should be tested in follow-up studies.


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