Network-Based Pipeline for Analyzing MS Data: An Application toward Liver Cancer

10.1021/pr1010845Journal of Proteome Research1052261-2272JPRO

CUT Domain Proteins in DNA Repair and Cancer

Recent studies revealed that CUT domains function as accessory factors that accelerate DNA repair by stimulating the enzymatic activities of the base excision repair enzymes OGG1, APE1, and DNA pol β. Strikingly, the role of CUT domain proteins in DNA repair is exploited by cancer cells to facilitate their survival. Cancer cells in which the RAS pathway is activated produce an excess of reactive oxygen species (ROS) which, if not counterbalanced by increased production of antioxidants, causes sustained oxidative DNA damage and, ultimately, cell senescence. These cancer cells can adapt by increasing their capacity to repair oxidative DNA damage in part through elevated expression of CUT domain proteins such as CUX1, CUX2, or SATB1. In particular, CUX1 overexpression was shown to cooperate with RAS in the formation of mammary and lung tumors in mice. Conversely, knockdown of CUX1, CUX2, or SATB1 was found to be synthetic lethal in cancer cells exhibiting high ROS levels as a consequence of activating mutations in KRAS, HRAS, BRAF, or EGFR. Importantly, as a byproduct of their adaptation, cancer cells that overexpress CUT domain proteins exhibit increased resistance to genotoxic treatments such as ionizing radiation, temozolomide, and cisplatin

Proteomics Signature Profiling (PSP): A Novel Contextualization Approach for Cancer Proteomics

Traditional proteomics analysis is plagued by the use of arbitrary thresholds resulting in large loss of information. We propose here a novel method in proteomics that utilizes all detected proteins. We demonstrate its efficacy in a proteomics screen of 5 and 7 liver cancer patients in the moderate and late stage, respectively. Utilizing biological complexes as a cluster vector, and augmenting it with submodules obtained from partitioning an integrated and cleaned protein–protein interaction network, we calculate a Proteomics Signature Profile (PSP) for each patient based on the hit rates of their reported proteins, in the absence of fold change thresholds, against the cluster vector. Using this, we demonstrated that moderate- and late-stage patients segregate with high confidence. We also discovered a moderate-stage patient who displayed a proteomics profile similar to other poor-stage patients. We identified significant clusters using a modified version of the SNet approach. Comparing our results against the Proteomics Expansion Pipeline (PEP) on which the same patient data was analyzed, we found good correlation. Building on this finding, we report significantly more clusters (176 clusters here compared to 70 in PEP), demonstrating the sensitivity of this approach. Gene Ontology (GO) terms analysis also reveals that the significant clusters are functionally congruent with the liver cancer phenotype. PSP is a powerful and sensitive method for analyzing proteomics profiles even when sample sizes are small. It does not rely on the ratio scores but, rather, whether a protein is detected or not. Although consistency of individual proteins between patients is low, we found the reported proteins tend to hit clusters in a meaningful and informative manner. By extracting this information in the form of a Proteomics Signature Profile, we confirm that this information is conserved and can be used for (1) clustering of patient samples, (2) identification of significant clusters based on real biological complexes, and (3) overcoming consistency and coverage issues prevalent in proteomics data sets

Proteomics Signature Profiling (PSP): A Novel Contextualization Approach for Cancer Proteomics

Traditional proteomics analysis is plagued by the use of arbitrary thresholds resulting in large loss of information. We propose here a novel method in proteomics that utilizes all detected proteins. We demonstrate its efficacy in a proteomics screen of 5 and 7 liver cancer patients in the moderate and late stage, respectively. Utilizing biological complexes as a cluster vector, and augmenting it with submodules obtained from partitioning an integrated and cleaned protein–protein interaction network, we calculate a Proteomics Signature Profile (PSP) for each patient based on the hit rates of their reported proteins, in the absence of fold change thresholds, against the cluster vector. Using this, we demonstrated that moderate- and late-stage patients segregate with high confidence. We also discovered a moderate-stage patient who displayed a proteomics profile similar to other poor-stage patients. We identified significant clusters using a modified version of the SNet approach. Comparing our results against the Proteomics Expansion Pipeline (PEP) on which the same patient data was analyzed, we found good correlation. Building on this finding, we report significantly more clusters (176 clusters here compared to 70 in PEP), demonstrating the sensitivity of this approach. Gene Ontology (GO) terms analysis also reveals that the significant clusters are functionally congruent with the liver cancer phenotype. PSP is a powerful and sensitive method for analyzing proteomics profiles even when sample sizes are small. It does not rely on the ratio scores but, rather, whether a protein is detected or not. Although consistency of individual proteins between patients is low, we found the reported proteins tend to hit clusters in a meaningful and informative manner. By extracting this information in the form of a Proteomics Signature Profile, we confirm that this information is conserved and can be used for (1) clustering of patient samples, (2) identification of significant clusters based on real biological complexes, and (3) overcoming consistency and coverage issues prevalent in proteomics data sets

RAS Transformation Requires CUX1-Dependent Repair of Oxidative DNA Damage

The Cut homeobox 1 (CUX1) gene is a target of loss-of-heterozygosity in many cancers, yet elevated CUX1 expression is frequently observed and is associated with shorter disease-free survival. The dual role of CUX1 in cancer is illustrated by the fact that most cell lines with CUX1 LOH display amplification of the remaining allele, suggesting that decreased CUX1 expression facilitates tumor development while increased CUX1 expression is needed in tumorigenic cells. Indeed, CUX1 was found in a genome-wide RNAi screen to identify synthetic lethal interactions with oncogenic RAS. Here we show that CUX1 functions in base excision repair as an ancillary factor for the 8-oxoG-DNA glycosylase, OGG1. Single cell gel electrophoresis (comet assay) reveals that Cux1⁺/⁻ MEFs are haploinsufficient for the repair of oxidative DNA damage, whereas elevated CUX1 levels accelerate DNA repair. In vitro base excision repair assays with purified components demonstrate that CUX1 directly stimulates OGG1's enzymatic activity. Elevated reactive oxygen species (ROS) levels in cells with sustained RAS pathway activation can cause cellular senescence. We show that elevated expression of either CUX1 or OGG1 prevents RAS-induced senescence in primary cells, and that CUX1 knockdown is synthetic lethal with oncogenic RAS in human cancer cells. Elevated CUX1 expression in a transgenic mouse model enables the emergence of mammary tumors with spontaneous activating Kras mutations. We confirmed cooperation between Kras(G12V) and CUX1 in a lung tumor model. Cancer cells can overcome the antiproliferative effects of excessive DNA damage by inactivating a DNA damage response pathway such as ATM or p53 signaling. Our findings reveal an alternate mechanism to allow sustained proliferation in RAS-transformed cells through increased DNA base excision repair capability. The heightened dependency of RAS-transformed cells on base excision repair may provide a therapeutic window that could be exploited with drugs that specifically target this pathway

Somatic Mutations and Loss-Of-Heterozygosity Impair The DNA Repair Functions Of CUX1 in Myelodysplastic Syndromes (MDS)

Abstract Chromosome 7 lesions are common and are associated almost uniformly with a deleterious outcome in MDS and related myeloid neoplasms. We analyzed a large cohort of these patients (pts) (n=1595) and identified those with loss of heterozygosity (LOH) of chromosome 7, including del(7q), monosomy7 (-7) and UPD(7q) in 171 cases. Using single nucleotide polymorphism (SNP)-array karyotyping, 3 commonly deleted regions (CDR) have been isolated, including 7q22, 7q34, and 7q35-36. CDR 7q22 was involved in 119 cases and spanned among others PLOD3, RBL5 and CUX1 genes, which could play a role in del(7q) pathogenesis. To further investigate the molecular pathogenesis of -7/del(7q), we performed whole exome new generation sequencing (NGS) in 428 pts with MDS and related conditions; this cohort included 72 -7/del(7q) or UPD7. When we studied the mutational status of genes in 7q22, we noted 5 cases of CUX1mutations, including 2 with heterozygous and 3 with homozygous mutations (associated with UPD7q). These mutations were validated by Sanger sequencing and targeted deep sequencing of DNA from both tumor and normal cells. All CUX1 mutations revealed critical structural and functional determinants such as nonsense mutations resulting in premature stop codons (n=3), nonsense mutation located in the DNA-binding Cut homeodomain (p.R1296K, n=1) and splice site mutation (n=1). CUX1 mutation occurred in MDS (n=2) and MDS/MPN (n=3), and concomitant TET2 mutations were seen in 4 cases. No hemizygous CUX1mutations were found in cases with del(7q). CUX1 is haploinsufficient in cases with -7/del(7q). In total 166 cases (10.9%) had -7/del(7q) involving CUX1, in addition to pts in whom CUX1 was affected by likely hypomorphic/inactivating mutations. Pts with decreased expression of CUX1 had poor survival compared to pts without CUX1 (p<.01, HR=1.99), suggesting that deficient function (deletion or mutation) of CUX1affects disease progression. In addition to somatic mutations, LOH of CUX1 has been reported in several cancers. A role of CUX1 as a haploinsufficient tumor suppressor cannot be explained by the known functions of CUX1 in stimulating cell proliferation, motility and resistance to apoptosis. We recently identified a novel molecular function of CUX1 in DNA repair that may explain how haplo-deficient expression of CUX1 contributes to leukemic transformation. We used single cell gel electrophoresis (comet assay) to show that Cux1-/- mouse embryo fibroblasts (MEFs) are deficient, while Cux1+/- MEFs are haploinsufficient, in the repair of oxidative DNA damage. Using an inverse-PCR assay, following etoposide exposure, the frequency of chromosomal translocations involving the mixed lineage leukemia (Mll) gene is significantly and progressively increased in Cux1+/- and Cux1-/- MEFs compared to Cux1+/+ MEFs. We then performed comet assays using primary leukemic cells that harbor a frameshift mutation predicted to inactivate CUX1 by producing a C-terminally truncated protein devoid of a nuclear localization signal. Repair of oxidative DNA damage was delayed in leukemic cells compared to bone marrow cells from a healthy donor. Using an in vitrobase excision repair assay, we show that repair of 8-oxoguanine is reduced in a cell line displaying LOH of CUX1. Similarly, repair of 8-oxoguanine is reduced following siRNA-mediated CUX1 knockdown, but is rescued by the addition of a purified CUX1 protein. Together these results demonstrate that CUX1 plays a direct role in DNA repair and that inactivation of one CUX1 allele reduces the DNA repair capability of cells. In conclusion, novel somatic mutations of CUX1 as a candidate gene are associated with poor prognosis in MDS pts with -7/del(7q) and UPD7. Somatic events constitute loss of function of CUX1, resulting in insufficiency of DNA repair mechanisms, which is associated with leukemogenesis and could be considered as a new therapeutic target. CUX1 mutations may affect base excision repair, and dysfunction of CUX1 could theoretically predispose to chromosomal translocations and complex karyotype, seen in conjunction with del(7q) cases. Disclosures: Makishima: AA & MDS international foundation: Research Funding; Scott Hamilton CARES grant: Research Funding. Maciejewski:NIH: Research Funding; Aplastic anemia&MDS International Foundation: Research Funding

Network-Based Pipeline for Analyzing MS Data: An Application toward Liver Cancer

Current limitations in proteome analysis by high-throughput mass spectrometry (MS) approaches have sometimes led to incomplete (or inconclusive) data sets being published or unpublished. In this work, we used an iTRAQ reference data on hepatocellular carcinoma (HCC) to design a two-stage functional analysis pipeline to widen and improve the proteome coverage and, subsequently, to unveil the molecular changes that occur during HCC progression in human tumorous tissue. The first involved functional cluster analysis by incorporating an expansion step on a cleaned integrated network. The second used an in-house developed pathway database where recovery of shared neighbors was followed by pathway enrichment analysis. In the original MS data set, over 500 proteins were detected from the tumors of 12 male patients, but in this paper we reported an additional 1000 proteins after application of our bioinformatics pipeline. Through an integrative effort of network cleaning, community finding methods, and network analysis, we also uncovered several biologically interesting clusters implicated in HCC. We established that HCC transition from a moderate to poor stage involved densely connected clusters that comprised of PCNA, XRCC5, XRCC6, PARP1, PRKDC, and WRN. From our pathway enrichment analyses, it appeared that the HCC moderate stage, unlike the poor stage, is enriched in proteins involved in immune responses, thus suggesting the acquisition of immuno-evasion. Our strategy illustrates how an original oncoproteome could be expanded to one of a larger dynamic range where current technology limitations prevent/limit comprehensive proteome characterization

Network-Based Pipeline for Analyzing MS Data: An Application toward Liver Cancer

Current limitations in proteome analysis by high-throughput mass spectrometry (MS) approaches have sometimes led to incomplete (or inconclusive) data sets being published or unpublished. In this work, we used an iTRAQ reference data on hepatocellular carcinoma (HCC) to design a two-stage functional analysis pipeline to widen and improve the proteome coverage and, subsequently, to unveil the molecular changes that occur during HCC progression in human tumorous tissue. The first involved functional cluster analysis by incorporating an expansion step on a cleaned integrated network. The second used an in-house developed pathway database where recovery of shared neighbors was followed by pathway enrichment analysis. In the original MS data set, over 500 proteins were detected from the tumors of 12 male patients, but in this paper we reported an additional 1000 proteins after application of our bioinformatics pipeline. Through an integrative effort of network cleaning, community finding methods, and network analysis, we also uncovered several biologically interesting clusters implicated in HCC. We established that HCC transition from a moderate to poor stage involved densely connected clusters that comprised of PCNA, XRCC5, XRCC6, PARP1, PRKDC, and WRN. From our pathway enrichment analyses, it appeared that the HCC moderate stage, unlike the poor stage, is enriched in proteins involved in immune responses, thus suggesting the acquisition of immuno-evasion. Our strategy illustrates how an original oncoproteome could be expanded to one of a larger dynamic range where current technology limitations prevent/limit comprehensive proteome characterization