Analysis of gene expression data of the NCl 60 cancer cell lines using Bayesian hierarchical effects model

2001 ◽  
Author(s):  
Jae K. Lee ◽  
Uwe Scherf ◽  
Lawrence H. Smith ◽  
Lorraine Tanabe ◽  
John N. Weinstein
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gene Expression Data ◽  
Cancer Cell Lines ◽  
Expression Data ◽  
Bayesian Hierarchical

scholarly journals Multi-Omics Analysis of Cancer Cell Lines with High/Low Ferroptosis Scores and Development of a Ferroptosis-Related Model for Multiple Cancer Types

2021 ◽  
Vol 9 ◽  
Author(s):  
Guangyao Shan ◽  
Huan Zhang ◽  
Guoshu Bi ◽  
Yunyi Bian ◽  
Jiaqi Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gene Expression Data ◽  
Cancer Cell Lines ◽  
Expression Data ◽  
Rna Seq ◽  
Multiple Cancer ◽  
Related Model ◽  
Cancer Types

Background: Ferroptosis is a newly identified regulated cell death characterized by iron-dependent lipid peroxidation and subsequent membrane oxidative damage, which has been implicated in multiple types of cancers. The multi-omics differences between cancer cell lines with high/low ferroptosis scores remain to be elucidated.Methods and Materials: We used RNA-seq gene expression, gene mutation, miRNA expression, metabolites, copy number variation, and drug sensitivity data of cancer cell lines from DEPMAP to detect multi-omics differences associated with ferroptosis. Based on the gene expression data of cancer cell lines, we performed LASSO-Logistic regression analysis to build a ferroptosis-related model. Lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), esophageal cancer (ESCA), bladder cancer (BLCA), cervical cancer (CESC), and head and neck cancer (HNSC) patients from the TCGA database were used as validation cohorts to test the efficacy of this model.Results: After stratifying the cancer cell lines into high score (HS) and low score (LS) groups according to the median of ferroptosis scores generated by gene set variation analysis, we found that IC50 of 66 agents such as oxaliplatin (p < 0.001) were significantly different, among which 65 were higher in the HS group. 851 genes such as KEAP1 and NRAS were differentially muted between the two groups. Differentially expressed genes, miRNAs and metabolites were also detected—multiple items such as IL17F (logFC = 6.58, p < 0.001) differed between the two groups. Unlike the TCGA data generated by bulk RNA-seq, the gene expression data in DEPMAP are from pure cancer cells, so it could better reflect the traits of tumors in cancer patients. Thus, we built a 15-signature model (AUC = 0.878) based on the gene expression data of cancer cell lines. The validation cohorts demonstrated a higher mutational rate of NFE2L2 and higher expression levels of 12 ferroptosis-related genes in HS groups.Conclusion: This article systemically analyzed multi-omics differences between cancer cell lines with high/low ferroptosis scores and a ferroptosis-related model was developed for multiple cancer types. Our findings could improve our understanding of the role of ferroptosis in cancer and provide new insight into treatment for malignant tumors.

scholarly journals SVExpress: identifying gene features altered recurrently in expression with nearby structural variant breakpoints

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiqun Zhang ◽  
Fengju Chen ◽  
Chad J. Creighton
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Integrative Analysis ◽  
Human Tumors ◽  
Gene Fusions ◽  
Expression Data ◽  
Altered Expression ◽  
Altered Gene

Abstract Background Combined whole-genome sequencing (WGS) and RNA sequencing of cancers offer the opportunity to identify genes with altered expression due to genomic rearrangements. Somatic structural variants (SVs), as identified by WGS, can involve altered gene cis-regulation, gene fusions, copy number alterations, or gene disruption. The absence of computational tools to streamline integrative analysis steps may represent a barrier in identifying genes recurrently altered by genomic rearrangement. Results Here, we introduce SVExpress, a set of tools for carrying out integrative analysis of SV and gene expression data. SVExpress enables systematic cataloging of genes that consistently show increased or decreased expression in conjunction with the presence of nearby SV breakpoints. SVExpress can evaluate breakpoints in proximity to genes for potential enhancer translocation events or disruption of topologically associated domains, two mechanisms by which SVs may deregulate genes. The output from any commonly used SV calling algorithm may be easily adapted for use with SVExpress. SVExpress can readily analyze genomic datasets involving hundreds of cancer sample profiles. Here, we used SVExpress to analyze SV and expression data across 327 cancer cell lines with combined SV and expression data in the Cancer Cell Line Encyclopedia (CCLE). In the CCLE dataset, hundreds of genes showed altered gene expression in relation to nearby SV breakpoints. Altered genes involved TAD disruption, enhancer hijacking, and gene fusions. When comparing the top set of SV-altered genes from cancer cell lines with the top SV-altered genes previously reported for human tumors from The Cancer Genome Atlas and the Pan-Cancer Analysis of Whole Genomes datasets, a significant number of genes overlapped in the same direction for both cell lines and tumors, while some genes were significant for cell lines but not for human tumors and vice versa. Conclusion Our SVExpress tools allow computational biologists with a working knowledge of R to integrate gene expression with SV breakpoint data to identify recurrently altered genes. SVExpress is freely available for academic or commercial use at https://github.com/chadcreighton/SVExpress. SVExpress is implemented as a set of Excel macros and R code. All source code (R and Visual Basic for Applications) is available.

A genomic strategy to combinatorial therapeutics in solid tumors

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 2031-2031
Author(s):  
A. Potti ◽  
H. K. Dressman ◽  
A. Bild ◽  
R. Riedel ◽  
M. Kelley ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Drug Response ◽  
Cancer Cell Lines ◽  
Pi3 Kinase ◽  
Expression Data ◽  
Chemotherapy Sensitivity ◽  
Response Data ◽  
Pathway Deregulation

2031 Background: For most advanced solid tumors, the response rate to cytotoxic drugs is generally low, highlighting the importance of identifying those patients most likely to respond, either to single agents or combinations of cytotoxic or targeted therapies. Methods: We have made use of in vitro drug response data generated on the NCI-60 panel of cancer cell lines, coupled with Affymetrix U133 2.0 plus gene expression data, to develop genomic predictors of chemotherapy sensitivity. These models were then validated in independent cancer cell lines as well as response data from patient treatment studies. Results: Predictive models making use of gene expression data were developed for docetaxel, adriamycin, 5-flourouracil, cyclophosphamide, paclitaxel, and topotecan. These models were shown to accurately predict sensitivity to the drugs in an independent set (n = 30) of cancer cell lines. Importantly, three of the predictors (docetaxel, topotecan, paclitaxel) also accurately (> 80%) predicted response in patient studies. When evaluated in a large collection of human cancers (n = 381), these gene expression signatures of drug response identified patterns of predicted sensitivity suggesting potential opportunities for novel combinations. We also combined the predictions of chemotherapy sensitivity with predictions of pathway deregulation (Bild A, Nature 2005), to develop further opportunities for combination therapy. For instance, this analysis revealed a significant relationship between PI3 kinase pathway deregulation and docetaxel resistance (p = 0.001), and a correlation between docetaxel sensitivity and the activation of the Rb/E2F pathway (p = 0.009). Furthermore, cell lines showing an increased probability of PI3 kinase and Rb/E2F activation were also more likely to respond to a PI3 kinase (LY-294002) inhibitor (p = 0.01) or R-Roscovitine (p = 0.03), a cell cycle inhibitor, respectively. Conclusions: The development and validation of chemotherapeutic response predictors, together with oncogenic pathway signatures that can guide the use of targeted agents, provides an opportunity to develop effective combinatorial therapeutic strategies geared to the individual patient. No significant financial relationships to disclose.

scholarly journals Protein citrullination as a source of cancer neoantigens

2021 ◽  
Vol 9 (6) ◽  
pp. e002549
Author(s):  
Hiroyuki Katayama ◽  
Makoto Kobayashi ◽  
Ehsan Irajizad ◽  
Alejandro Sevillarno ◽  
Nikul Patel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Immune Response ◽  
Protein Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Family Members ◽  
Immunohistochemical Analysis ◽  
Cancer Cell Lines ◽  
Mhc Ii

BackgroundCitrulline post-translational modification of proteins is mediated by protein arginine deiminase (PADI) family members and has been associated with autoimmune diseases. The role of PADI-citrullinome in immune response in cancer has not been evaluated. We hypothesized that PADI-mediated citrullinome is a source of neoantigens in cancer that induces immune response.MethodsProtein expression of PADI family members was evaluated in 196 cancer cell lines by means of indepth proteomic profiling. Gene expression was assessed using messenger RNA data sets from The Cancer Genome Atlas. Immunohistochemical analysis of PADI2 and peptidyl-citrulline was performed using breast cancer tissue sections. Citrullinated 12–34-mer peptides in the putative Major Histocompatibility Complex-II (MHC-II) binding range were profiled in breast cancer cell lines to investigate the relationship between protein citrullination and antigen presentation. We further evaluated immunoglobulin-bound citrullinome by mass spectrometry using 156 patients with breast cancer and 113 cancer-free controls.ResultsProteomic and gene expression analyses revealed PADI2 to be highly expressed in several cancer types including breast cancer. Immunohistochemical analysis of 422 breast tumor tissues revealed increased expression of PADI2 in ER− tumors (p<0.0001); PADI2 protein expression was positively correlated (p<0.0001) with peptidyl-citrulline staining. PADI2 expression exhibited strong positive correlations with a B cell immune signature and with MHC-II-bound citrullinated peptides. Increased circulating citrullinated antigen–antibody complexes occurred among newly diagnosed breast cancer cases relative to controls (p=0.0012).ConclusionsAn immune response associated with citrullinome is a rich source of neoantigens in breast cancer with a potential for diagnostic and therapeutic applications.

scholarly journals Predicting tumor response to drugs based on gene-expression biomarkers of sensitivity learned from cancer cell lines

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yuanyuan Li ◽  
David M. Umbach ◽  
Juno M. Krahn ◽  
Igor Shats ◽  
Xiaoling Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Predictive Models ◽  
Drug Sensitivity ◽  
Human Cancer ◽  
Cancer Cell Lines ◽  
The Cancer Genome Atlas ◽  
Differential Sensitivity ◽  
Tumor Type

Abstract Background Human cancer cell line profiling and drug sensitivity studies provide valuable information about the therapeutic potential of drugs and their possible mechanisms of action. The goal of those studies is to translate the findings from in vitro studies of cancer cell lines into in vivo therapeutic relevance and, eventually, patients’ care. Tremendous progress has been made. Results In this work, we built predictive models for 453 drugs using data on gene expression and drug sensitivity (IC50) from cancer cell lines. We identified many known drug-gene interactions and uncovered several potentially novel drug-gene associations. Importantly, we further applied these predictive models to ~ 17,000 bulk RNA-seq samples from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database to predict drug sensitivity for both normal and tumor tissues. We created a web site for users to visualize and download our predicted data (https://manticore.niehs.nih.gov/cancerRxTissue). Using trametinib as an example, we showed that our approach can faithfully recapitulate the known tumor specificity of the drug. Conclusions We demonstrated that our approach can predict drugs that 1) are tumor-type specific; 2) elicit higher sensitivity from tumor compared to corresponding normal tissue; 3) elicit differential sensitivity across breast cancer subtypes. If validated, our prediction could have relevance for preclinical drug testing and in phase I clinical design.

Gastrin regulates growth of human pancreatic cancer in a tonic and autocrine fashion

1996 ◽  
Vol 270 (5) ◽  
pp. R1078-R1084 ◽  
Author(s):  
J. P. Smith ◽  
A. Shih ◽  
Y. Wu ◽  
P. J. McLaughlin ◽  
I. S. Zagon
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Pancreatic Cancer Cell ◽  
Cancer Cell Lines ◽  
Human Pancreatic Cancer ◽  
Growth Media ◽  
Human Pancreatic Cancer Cell ◽  
Cell Extracts

The gastrointestinal peptides gastrin and cholecystokinin (CCK) stimulate growth of human pancreatic cancer through a CCK-B/gastrin- like receptor. In the present study we evaluated whether growth of human pancreatic cancer is endogenously regulated by gastrin. Immunohistomical examination of BxPC-3 cells and tumor xenografts revealed specifc gastrin immunoreactivity. Gastrin was detected by radioimmunoassay in pancreatic cancer cell extracts and in pancreatic cancer cell extracts and in the growth media. With use of reverse-transcriptase polymerase chain reaction gastrin gene expression was detected in both cultured BxPC-3 cancer cells and transplanted tumors, as well as seven addition human pancreatic cancer cell lines. Growth of BxPC-3 human pancreatic cancer cell in serum-free medium was inhibited by the addition of the CCK-B/gastrin receptor antagonist L-365,260, and gastrin treatment reversed the inhibitory effect of the antagonist. A selective gastrin antibody (Ab repressed growth of BxPC-3 cells. Gastrin immunoreactivity was detected in fresh human pancreatic cancer specimens but not in normal human pancreatic tissue. These data provide the first evidence that growth of a human pancreatic cancer is tonically stimulated by the autocrine production of gastrin. Evidence for the ubiquity of this system was provided by the detection of gastrin gene expression in multiple human pancreatic cancer cell lines and detection of gastrin in cell lines and fresh pancreatic tumors.

Regulation of DNA repair gene expression in human cancer cell lines

2006 ◽  
Vol 97 (5) ◽  
pp. 1121-1136 ◽  
Author(s):  
Claire J. McGurk ◽  
Michele Cummings ◽  
Beate Köberle ◽  
John A. Hartley ◽  
R. Timothy Oliver ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Repair ◽  
Cell Lines ◽  
Cancer Cell ◽  
Human Cancer ◽  
Cancer Cell Lines ◽  
Human Cancer Cell ◽  
Repair Gene ◽  
Human Cancer Cell Lines ◽  
Dna Repair Gene
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