The TP53 tumor suppressor gene is frequently mutated in human cancers. An analysis of five data platforms in 10,225 patient samples from 32 cancers reported by The Cancer Genome Atlas (TCGA) enables ...comprehensive assessment of p53 pathway involvement in these cancers. More than 91% of TP53-mutant cancers exhibit second allele loss by mutation, chromosomal deletion, or copy-neutral loss of heterozygosity. TP53 mutations are associated with enhanced chromosomal instability, including increased amplification of oncogenes and deep deletion of tumor suppressor genes. Tumors with TP53 mutations differ from their non-mutated counterparts in RNA, miRNA, and protein expression patterns, with mutant TP53 tumors displaying enhanced expression of cell cycle progression genes and proteins. A mutant TP53 RNA expression signature shows significant correlation with reduced survival in 11 cancer types. Thus, TP53 mutation has profound effects on tumor cell genomic structure, expression, and clinical outlook.
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•TP53 mutation effects analyzed by five data platforms in 32 cancers/10,225 patients•More than 91% of cancers with TP53 mutations show loss of both functional TP53 alleles•TP53 mutation affects genomic stability, global RNA, miRNA, and protein expression•Mutant p53 RNA expression signature helps prognostic predictions in 11 cancer types
Donehower et al. performed a comprehensive analysis of the effects of TP53 gene mutation in 32 cancer types and 10,225 patients from The Cancer Genome Atlas (TCGA). Data synthesized from five different analysis platforms show how mutant TP53 increases genomic instability and induces major pathway signaling changes in cancer cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Non-small-cell lung cancer (NSCLC) demonstrates remarkable molecular diversity. With the completion of The Cancer Genome Atlas (TCGA), there is opportunity for systematic analyses of the entire TCGA ...NSCLC cohort, including comparisons and contrasts between different disease subsets. On the basis of multidimensional and comprehensive molecular characterization (including DNA methylation and copy, and RNA and protein expression), 1023 NSCLC cases-519 from TCGA adenocarcinoma (AD) project and 504 from TCGA squamous cell carcinoma (SQCC) project-were classified using a 'cluster-of-clusters' analytic approach. Patterns from TCGA NSCLC subsets were examined in independent external databases, including the PROSPECT (Profiling of Resistance patterns and Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax) NSCLC data set. Nine genomic subtypes of NSCLC were identified, three within SQCC and six within AD. SQCC subtypes were associated with transcriptional targets of SOX2 or p63. One predominately AD subtype (with a large proportion of SQCC) shared molecular features with neuroendocrine tumors. Two AD subtypes manifested a CpG island methylator phenotype. Three AD subtypes showed high p38 and mTOR pathway activation. AD subtypes associated with low differentiation showed relatively worse prognosis. SQCC subtypes and two of the AD subtypes expressed cancer testis antigen genes, whereas three AD subtypes expressed several immune checkpoint genes including PDL1 and PDL2, corresponding with patterns of greater immune cell infiltration. Subtype associations for several immune-related markers-including PD1, PDL1, CD3 and CD8-were confirmed in the PROSPECT cohort using immunohistochemistry. NSCLC molecular subtypes have therapeutic implications and lend support to a personalized approach to NSCLC management based on molecular characterization.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients' lives. The Cancer Genome Atlas project has analysed ...messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and ...annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)—mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations—comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the ‘legacy’ GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as ‘harmonized’ by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.
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•A systematic analysis on how the reference genome affects various TCGA data types•The GRCh37 (hg19) and GRCh38 (hg38) TCGA data versions are highly concordant•Generate the gene lists showing significant differences between the two versions•Provide detailed information about TCGA software, pipelines, and annotations
Gao et al. performed a systematic analysis of the effects of synchronizing the large-scale, widely used, multi-omic dataset of The Cancer Genome Atlas to the current human reference genome. For each of the five molecular data platforms assessed, they demonstrated a very high concordance between the ‘legacy’ GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as ‘harmonized’ by the Genomic Data Commons.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Cancer cell lines (CCLs) serve as models to study the functional consequences of the genomic lesions in patients and as screening platforms for prediction of drug response. While genomic and ...transcriptomic data have proven to be useful predictors, the ability of these omics platforms to predict protein level and function is limited. Furthermore, since proteins are the targets of the majority of the targeted therapies, protein levels and importantly protein function would be expected to provide more powerful predictions than DNA or RNA data. While large scale genomic and transcriptomic data linked to drug sensitivity are available for over a thousand CCLs, proteomic data is available for only a small subset of lines. Here we performed proteomic profiling of 736 cell lines using reverse-phase protein arrays (RPPAs) with approximately 300 antibodies providing an unbiased sparse representation of the majority of signaling pathways.
The functional proteomic analysis revealed 10 protein-based clusters across all cell lines. Similar to human tumors, the breast cell lines fell into three major clusters representing basal-like, luminal/Her2-amplified and claudin-low breast cancer subtypes. The basal-like and claudin-low clusters contained all of the representative breast cancer cell lines as well as a much larger number of other CCLs. For example, the 6 claudin-low breast cancers analyzed reside in an EMT cluster, in which only 8/126 are breast cell lines. However, the complete cluster including multiple non-breast cancer cell lines recapitulated mRNA and protein features of claudin-low breast tumors, including a high EMT signature and low level of hormone receptor pathway activity. We thus explored whether we could gain power for linking the limited number of basal and claudin-low breast cancer cell lines to therapeutic sensitivity by assessing patterns of drug sensitivity in each cluster for both the breast and non-breast cancer cell lines in the cluster. We explored drug sensitivity of 481 therapeutic compounds from the Cancer Therapeutic Response Portal (CTRP v2) and demonstrated that the non- breast cancer and breast cancer cell lines in each cluster provided similar patterns of drug sensitivity. For example, Claudin-low/EMT cell lines of both breast cancer and non-breast cancer origin showed decreased sensitivity to PI3K/mTOR inhibitors compared to luminal breast cancers (p<0.05 for 4 mTOR inhibitors) and drugs targeting EGFR family compared to basal cell lines (p<0.05 for 7 EGFR/ERBB2 inhibitors). Thus it is possible to gain information by characterizing cell lines with similar patterns of protein expression and provide important information related to drug sensitivity of uncommon breast cancer lineages. The functional proteomic analysis provides a wealth of information that complements the genomic and transciptomic studies of cancer cell lines, and demonstrates the opportunity to leverage cell line 'pan-cancer' proteomic patterns to improve characterization of specific breast cancer subtypes. To facilitate broad access to these data, we developed a user-friendly data portal, the MD Anderson Cell Lines Project (MCLP), that provides both data analysis and download (http://ibl.mdanderson.org/mclp/).
Citation Format: Zhao W, Li J, Lu Y, Akbani R, Liang H, Mills GB. A pan-cancer perspective of functional proteomics provides novel information content for uncommon breast cancer subtypes abstract. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-07-01.
Elliptic curve cryptosystem and its applications Raju, G.V.S.; Akbani, R.
SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483),
2003, Volume:
2
Conference Proceeding
The goal of this research is to develop a basis for utilizing efficient encryption schemes in wireless communications and in devices with low computing power and resources. Elliptic curve ...cryptography (ECC) fits well for an efficient and secure encryption scheme. It is more efficient than the ubiquitous RSA based schemes because ECC utilizes smaller key sizes for equivalent security. A comparative study of ECC with RSA is made in terms of key size, computational power, size of data files and encrypted files. Also, another aim is to design an API to implement ECC encryption/decryption algorithm.
An organization consists of many resources and entities who want to access those resources. Not all entities are granted full access rights to every resource, so there must be a Trust Management ...System (TMS) in place to enforce access rights. In this paper, we present a new Hybrid Trust Management System (HTMS) that combines Role Based Trust Management (RBTM) with Reputation Systems (RS). At any point in time, the privilege level of an entity is determined not only by its role in the system, but also by its reputation score, which in turn is based on its behavior. If a privileged node becomes compromised and conducts several malicious or risky transactions, its privilege level is quickly reduced to limit its access to resources and minimize the damage it can inflict further. The system uses a global, network-wide perspective in order to thwart global attacks. Such fine-grained variations of access control and dynamically assigning privilege levels would be very difficult to accomplish manually. We evaluated HTMS by comparing an implementation of it against an ideal response. We show that HTMS performs very close to the ideal if we can accurately estimate the proportion of malicious nodes in the network. We suggest using sampling to estimate this proportion. However, even if this estimate is not accurate, the results are still much better than using RBTM by itself.
Authentication in Wireless Networks Raju, G.V.S.; Akbani, R.
2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07),
2007-Jan.
Conference Proceeding
With the explosive growth in the adoption of wireless networks in the recent years, the limitations of wireless security have become a topic of wide spread concern. It is easy for hackers to enter or ...leave a wireless network. They can directly attack the network and inject spurious packets, tamper with packets, drop packets, or impersonate another node. This violates the network's goals of availability, integrity and authentication. This paper presents an authentication scheme for mobile ad hoc networks (MANETs) that is designed to combat such attacks from adversaries. In this scheme, every packet is authenticated at every node. The performance of the proposed scheme is compared with other published schemes and it is found to be just as efficient while improving on security
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