scholarly journals Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Chao Qin ◽  
Xiaoyan He ◽  
Yanding Zhao ◽  
Chun-Yip Tong ◽  
Kenneth Y. Zhu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Proportional Hazards ◽  
Patient Survival ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Models ◽  
Gain Loss ◽  
Chromosome Bands

Abstract Background Neuroblastoma (NB) is the most common extracranial solid tumor found in children. The frequent gain/loss of many chromosome bands in tumor cells and absence of mutations found at diagnosis suggests that NB is a copy number-driven cancer. Despite the previous work, a systematic analysis that investigates the relationship between such frequent gain/loss of chromosome bands and patient prognosis has yet to be implemented. Methods First, we analyzed two NB CNV datasets to select chromosomal bands with a high frequency of gain or loss. Second, we applied a computational approach to infer sample-specific CNVs for each chromosomal band selected in step 1 based on gene expression data. Third, we applied univariate Cox proportional hazards models to examine the association between the resulting inferred copy number values (iCNVs) and patient survival. Finally, we applied multivariate Cox proportional hazards models to select chromosomal bands that remained significantly associated with prognosis after adjusting for critical clinical variables, including age, stage, gender, and MYCN amplification status. Results Here, we used a computational method to infer the copy number variations (CNVs) of sample-specific chromosome bands from NB patient gene expression profiles. The resulting inferred CNVs (iCNVs) were highly correlated with the experimentally determined CNVs, demonstrating CNVs can be accurately inferred from gene expression profiles. Using this iCNV metric, we identified 58 frequent gain/loss chromosome bands that were significantly associated with patient survival. Furthermore, we found that 7 chromosome bands were still significantly associated with patient survival even when clinical factors, such as MYCN status, were considered. Particularly, we found that the chromosome band chr11p14 has high potential as a novel candidate cytogenetic biomarker for clinical use. Conclusion Our analysis resulted in a comprehensive list of prognostic chromosome bands supported by strong statistical evidence. In particular, the chr11p14 gain event provided additional prognostic value in addition to well-established clinical factors, including MYCN status, and thereby represents a novel candidate cytogenetic biomarker with high clinical potential. Additionally, this computational framework could be readily extended to other cancer types, such as leukemia.

Evidence for a field effect in early prostate cancer (PCa): Gene expression profiles in normal-appearing prostate tissue (NT) adjacent to tumor (T) as predictors of clinical outcome.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 5029-5029 ◽  
Author(s):  
Eric A. Klein ◽  
Sara Moscovita Falzarano ◽  
Nan Zhang ◽  
Dejan Knezevic ◽  
Tara Maddala ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Field Effect ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cox Proportional Hazards ◽  
Clinical Recurrence ◽  
Molecular Alterations ◽  
Cox Proportional Hazards Models

5029 Background: We previously identified genes whose expression predicts aggressive PCa (clinical recurrence (cR), prostate cancer death (PCD), adverse pathology) when assessed in histologically heterogeneous tumor foci and in biopsies (Klein ASCO 2012). These results enabled the definition of a multi-gene Genomic Prostate Score (GPS), which has been clinically validated (Cooperberg AUA 2013). There is interest regarding a possible field effect in PCa, i.e. molecular alterations throughout the gland that may influence PCa development. We conducted exploratory analyses to evaluate gene expression, including GPS, in adjacent normal-appearing tissue (NT) for prediction of cR and PCD. Methods: Cohort sampling was used to select 127 patients with and 374 without cR from 2,641 patients treated with RP for T1/T2 PCa. Expression of 732 genes was measured by qRT-PCR separately in T and NT (defined as > 3 mm from T) specimens. GPS (0-100 units) was determined using the genes and algorithm from the validation study. Analysis used Cox proportional hazards models and Storey’s false discovery rate (FDR) control. Results: 410 evaluable patients had paired T and NT. Of the 405 genes which were predictive of outcome in T (FDR < 20%), 289 (71%) showed similar but weaker effects in NT. 47 genes were associated with cR in NT (FDR < 20%), of which 34 also concordantly predicted cR in T (FDR < 20%). GPS assessed in NT significantly predicted time to cR (HR/20 units = 1.8; 95% CI: 1.3-2.4; p< 0.001) and PCD (HR/20 units = 1.9; 95% CI: 1.2-3.0; p = 0.005) but was less predictive than GPS in T (HR/20 units = 4.8 for cR; 95% CI: 3.7-6.2; p < 0.001 and HR/20 units = 6.9 for PCD; 95% CI: 4.4-10.7; p < 0.001). The strongest components of GPS in predicting cR and PCD in NT were stromal response and androgen signaling genes (p < 0.05); proliferation and cellular organization genes did not consistently provide a significant contribution in NT. Conclusions: These data indicate that gene expression profiles, including GPS, can predict outcome in NT, albeit more weakly than in tumor. These findings suggest that there is an underlying field effect associated with the development of aggressive PCa.

Genomic Complexity and Recurrent Aberration in Multiple Myeloma: Analysis of a Compendium of aCGH and Gene Expression Profiles.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1682-1682
Author(s):  
Wee-Joo Chng ◽  
Ian Lee ◽  
Victor Jimenez-zepeda ◽  
Esteban Braggio ◽  
Jonathan Keats ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Clinical Status ◽  
Gene Expression Profiles ◽  
Cox Proportional Hazards ◽  
Comparative Genomic ◽  
Initial Attempt ◽  
Genomic Complexity

Abstract Multiple Myeloma (MM) is the second most prevalent haematological disorder in the US with great recent progress propelled by various technological and therapeutic advances. Nevertheless, the complexity of MM genomes remains inadequately characterized. We have combined high-resolution (44K Agilent) array comparative genomic hybridization (aCGH) and gene expression data with clinical outcomes in an initial attempt at indexing genomic complexity in MM and its clinical implication in 100 MM patients. We enumerated the Number of Aberrations per Tumor (NAPT) as defined by the ADM-1 algorithm available within CGH Analytics. There appear to be no difference in degree of genetic complexity between hyperdiploid and non-hyperdiploid myeloma. Generally, t(11;14) have low NAPT whereas D2 tumors have high NAPT. Amongst the high-risk genetic subtypes, tumors with maf translocations have relatively low NAPT whereas t(4;14) have high NAPT. Whilst a Multivariate Cox Proportional Hazards regression of survival outcome showed little statistical support for popular indicators such as ploidy and TC classification, results for NAPT were considerably more encouraging (p~ 0.07, median survival of 40 months in low complexity vs 18 months in high). Log-rank tests further supported prognosis based on NAPT independent of clinical status and ploidy. To characterize complexity, we clustered aCGH profiles by clinical status, ploidy and TC classification. Clear patterns of aggregation and recurrent aberration were observed suggesting that they were possibly instrument to aberrant gene expression. Indeed, expression of a large proportion of genes approximately 2Mb of the recurrent breakpoints varied significantly between patients carrying aberrations vis-a-viz others that did not. Comparison against known gene sets showed an enrichment for cell-cycle and apoptosis genes. We are presently characterizing several such breakpoint-associated genes for their functional significance.

scholarly journals The Prognostic Significance of PDE7B in Cytogenetically Normal Acute Myeloid Leukemia

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ling Cao ◽  
Weilong Zhang ◽  
Xiaoni Liu ◽  
Ping Yang ◽  
Jing Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Gene Expression Profiles ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Acute Myeloid

AbstractAcute myeloid leukemia (AML) is a malignant hematological disease in which nearly half have normal cytogenetics. We have tried to find some significant molecular markers for this part of the cytogenetic normal AML, which hopes to provide a benefit for the diagnosis, molecular typing and prognosis prediction of AML patients. In the present study, we calculated and compared the gene expression profiles of cytogenetically normal acute myeloid leukemia (CN-AML) patients in database of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and dataset Vizome (a total of 632 CN-AML samples), and we have demonstrated a correlation between PDE7B gene and CN-AML. Then we proceeded to a survival analysis and prognostic risk analysis between the expression levels of PDE7B gene and CN-AML patients. The result showed that the event-free survival (EFS) and overall survival (OS) were significantly shorter in CN-AML patients with high PDE7B levels in each dataset. And we detected a significantly higher expression level of PDE7B in the leukemia stem cell (LSC) positive group. The Cox proportional hazards regression model showed that PDE7B is an independent risk predictor for CN-AML. All results indicate that PDE7B is an unfavorable prognostic factor for CN-AML.

scholarly journals Gene expression profiles of CMS2-epithelial/canonical colorectal cancers are largely driven by DNA copy number gains

Oncogene ◽  
2019 ◽  
Vol 38 (33) ◽  
pp. 6109-6122 ◽  
Author(s):  
Kaja C. G. Berg ◽  
Anita Sveen ◽  
Maren Høland ◽  
Sharmini Alagaratnam ◽  
Marianne Berg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Colorectal Cancers ◽  
Dna Copy Number

Cytogenetic Analysis of Multiple Myeloma Identifies Cytogenetic Alterations Implicated in Disease Complexity and Progression

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3360-3360
Author(s):  
Erik Wendlandt ◽  
Guido J. Tricot ◽  
Benjamin Darbro ◽  
Fenghuang Zhan
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cathepsin B ◽  
Copy Number ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Copy Number Variations ◽  
Expression Arrays ◽  
Gene Expression Arrays

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.

scholarly journals A Prognostic Nomogram Combining Gene Expression Profiles and TNM Stage Predicts Survival in Gastric Cancer

2021 ◽  
Author(s):  
Jian Huang ◽  
Dongcun Wang ◽  
Xiaoliang Wang ◽  
Xiaoxing Ye ◽  
Jiping Da
Keyword(s):  
Gene Expression ◽  
Risk Score ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Tnm Staging ◽  
Cox Proportional Hazards ◽  
Tnm Stage ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
High Morbidity

Abstract BackgroundGastric carcinoma (GC) is a highly aggressive malignancy and is associated with high morbidity and mortality rates around the world, the current tumor-node-metastasis (TNM) staging system is inadequate to predict overall survival (OS) in GC patients. therefore, potential forecasting methods for prognosis are important to investigate.MethodsDifferentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas (TCGA). We then construct a risk score signature model by univariate Cox proportional hazards regression (CPHR) analysis, the Kaplan-Meier method（KM）and multivariate CPHR analysis. Using TNM stage, we developed a signature-based nomogram. Finally, we utilize an independent Gene Expression Omnibus dataset (GSE62254) validate the prognostic value of risk score signature model and nomogram.ResultsWe identified five OS-related mRNAs among 1113 mRNAs that were differentially expressed between GC and normal samples in the TCGA dataset. We then constructed a five-mRNA signature model, which efficiently distinguished high-risk from low-risk patient in both cohort, and even viable in the TNM stage-III, gender(male, female) and age(＜65-year-old, ≥65-year-old) subgroups (P<0.05). Utilizing TNM stage, we developed a signature-based nomogram, which performed better than use the TNM stage or five-mRNA signature alone for prognostic prediction in the TCGA and GSE62254 dataset.ConclusionsThese results suggest that both risk signature and nomogram were effective prognostic indicators for patients with GCs, and could potentially be used for individualized management of such patients.

scholarly journals Cervical Cancer Development: Implications of HPV16 E6E7-NFX1-123 Regulated Genes

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6182
Author(s):  
Kevin M. Quist ◽  
Isaiah Solorzano ◽  
Sebastian O. Wendel ◽  
Sreenivasulu Chintala ◽  
Cen Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Disease Progression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Models ◽  
Cervical Precancer ◽  
Regulatory Effects ◽  
Cervical Cancer Development

High-risk human papillomavirus (HR HPV) causes nearly all cervical cancers, half of which are due to HPV type 16 (HPV16). HPV16 oncoprotein E6 (16E6) binds to NFX1-123, and dysregulates gene expression, but their clinical implications are unknown. Additionally, HPV16 E7’s role has not been studied in concert with NFX1-123 and 16E6. HR HPVs express both oncogenes, and transformation requires their expression, so we sought to investigate the effect of E7 on gene expression. This study’s goal was to define gene expression profiles across cervical precancer and cancer stages, identify genes correlating with disease progression, assess patient survival, and validate findings in cell models. We analyzed NCBI GEO datasets containing transcriptomic data linked with cervical cancer stage and utilized LASSO analysis to identify cancer-driving genes. Keratinocytes expressing 16E6 and 16E7 (16E6E7) and exogenous NFX1-123 were tested for LASSO-identified gene expression. Ten out of nineteen genes correlated with disease progression, including CEBPD, NOTCH1, and KRT16, and affected survival. 16E6E7 in keratinocytes increased CEBPD, KRT16, and SLPI, and decreased NOTCH1. Exogenous NFX1-123 in 16E6E7 keratinocytes resulted in significantly increased CEBPD and NOTCH1, and reduced SLPI. This work demonstrates the clinical relevance of CEBPD, NOTCH1, KRT16, and SLPI, and shows the regulatory effects of 16E6E7 and NFX1-123.

scholarly journals Comprehensive Profiling of Primary and Metastatic ccRCC Reveals a High Homology of the Metastases to a Subregion of the Primary Tumour

Cancers ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 812 ◽  
Author(s):  
Paranita Ferronika ◽  
Joost Hof ◽  
Gursah Kats-Ugurlu ◽  
Rolf H. Sijmons ◽  
Martijn M. Terpstra ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Lung Metastases ◽  
Expression Profiles ◽  
Clonal Evolution ◽  
Primary Tumour ◽  
Vena Cava ◽  
Gene Expression Profiles ◽  
Cell Renal Cell Carcinoma ◽  
Number Pattern

While intratumour genetic heterogeneity of primary clear cell renal cell carcinoma (ccRCC) is well characterized, the genomic profiles of metastatic ccRCCs are seldom studied. We profiled the genomes and transcriptomes of a primary tumour and matched metastases to better understand the evolutionary processes that lead to metastasis. In one ccRCC patient, four regions of the primary tumour, one region of the thrombus in the inferior vena cava, and four lung metastases (including one taken after pegylated (PEG)-interferon therapy) were analysed separately. Each sample was analysed for copy number alterations and somatic mutations by whole exome sequencing. We also evaluated gene expression profiles for this patient and 15 primary tumour and 15 metastasis samples from four additional patients. Copy number profiles of the index patient showed two distinct subgroups: one consisted of three primary tumours with relatively minor copy number changes, the other of a primary tumour, the thrombus, and the lung metastases, all with a similar copy number pattern and tetraploid-like characteristics. Somatic mutation profiles indicated parallel clonal evolution with similar numbers of private mutations in each primary tumour and metastatic sample. Expression profiling of the five patients revealed significantly changed expression levels of 57 genes between primary tumours and metastases, with enrichment in the extracellular matrix cluster. The copy number profiles suggest a punctuated evolution from a subregion of the primary tumour. This process, which differentiated the metastases from the primary tumours, most likely occurred rapidly, possibly even before metastasis formation. The evolutionary patterns we deduced from the genomic alterations were also reflected in the gene expression profiles.

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