Martin C. Abba

TP53 codon 72 polymorphism and cervical cancer: a pooled analysis of individual data from 49 studies.

BACKGROUND Cervical cancer is caused primarily by human papillomaviruses (HPV). The polymorphism rs1042522 at codon 72 of the TP53 tumour-suppressor gene has been investigated as a genetic cofactor. More than 80 studies were done between 1998 and 2006, after it was initially reported that women who are homozygous for the arginine allele had a risk for cervical cancer seven times higher than women who were heterozygous for the allele. However, results have been inconsistent. Here we analyse pooled data from 49 studies to determine whether there is an association between TP53 codon 72 polymorphism and cervical cancer. METHODS Individual data on 7946 cases and 7888 controls from 49 different studies worldwide were reanalysed. Odds ratios (OR) were estimated using logistic regression, stratifying by study and ethnic origin. Subgroup analyses were done for infection with HPV, ethnic origin, Hardy-Weinberg equilibrium, study quality, and the material used to determine TP53 genotype. FINDINGS The pooled estimates (OR) for invasive cervical cancer were 1.22 (95% CI 1.08-1.39) for arginine homozygotes compared with heterozygotes, and 1.13 (0.94-1.35) for arginine homozygotes versus proline homozygotes. Subgroup analyses showed significant excess risks only in studies where controls were not in Hardy-Weinberg equilibrium (1.71 [1.21-2.42] for arginine homozygotes compared with heterozygotes), in non-epidemiological studies (1.35 [1.15-1.58] for arginine homozygotes compared with heterozygotes), and in studies where TP53 genotype was determined from tumour tissue (1.39 [1.13-1.73] for arginine homozygotes compared with heterozygotes). Null results were noted in studies with sound epidemiological design and conduct (1.06 [0.87-1.29] for arginine homozygotes compared with heterozygotes), and studies in which TP53 genotype was determined from white blood cells (1.06 [0.87-1.29] for arginine homozygotes compared with heterozygotes). INTERPRETATION Subgroup analyses indicated that excess risks were most likely not due to clinical or biological factors, but to errors in study methods. No association was found between cervical cancer and TP53 codon 72 polymorphism when the analysis was restricted to methodologically sound studies. FUNDING German Research Foundation (DFG).

Gene expression signature of estrogen receptor α status in breast cancer

BackgroundEstrogens are known to regulate the proliferation of breast cancer cells and to modify their phenotypic properties. Identification of estrogen-regulated genes in human breast tumors is an essential step toward understanding the molecular mechanisms of estrogen action in cancer. To this end we generated and compared the Serial Analysis of Gene Expression (SAGE) profiles of 26 human breast carcinomas based on their estrogen receptor α (ER) status. Thus, producing a breast cancer SAGE database of almost 2.5 million tags, representing over 50,000 transcripts.ResultsWe identified 520 transcripts differentially expressed between ERα-positive (+) and ERα-negative (-) primary breast tumors (Fold change ≥ 2; p < 0.05). Furthermore, we identified 220 high-affinity Estrogen Responsive Elements (EREs) distributed on the promoter regions of 163 out of the 473 up-modulated genes in ERα (+) breast tumors. In brief, we observed predominantly up-regulation of cell growth related genes, DNA binding and transcription factor activity related genes based on Gene Ontology (GO) biological functional annotation. GO terms over-representation analysis showed a statistically significant enrichment of various transcript families including: metal ion binding related transcripts (p = 0.011), calcium ion binding related transcripts (p = 0.033) and steroid hormone receptor activity related transcripts (p = 0.031). SAGE data associated with ERα status was compared with reported information from breast cancer DNA microarrays studies. A significant proportion of ERα associated gene expression changes was validated by this cross-platform comparison. However, our SAGE study also identified novel sets of genes as highly expressed in ERα (+) invasive breast tumors not previously reported. These observations were further validated in an independent set of human breast tumors by means of real time RT-PCR.ConclusionThe integration of the breast cancer comparative transcriptome analysis based on ERα status coupled to the genome-wide identification of high-affinity EREs and GO over-representation analysis, provide useful information for validation and discovery of signaling networks related to estrogen response in this malignancy.

Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression

IntroductionGenomic and transcriptomic alterations affecting key cellular processes such us cell proliferation, differentiation and genomic stability are considered crucial for the development and progression of cancer. Most invasive breast carcinomas are known to derive from precursor in situ lesions. It is proposed that major global expression abnormalities occur in the transition from normal to premalignant stages and further progression to invasive stages. Serial analysis of gene expression (SAGE) was employed to generate a comprehensive global gene expression profile of the major changes occurring during breast cancer malignant evolution.MethodsIn the present study we combined various normal and tumor SAGE libraries available in the public domain with sets of breast cancer SAGE libraries recently generated and sequenced in our laboratory. A recently developed modified t test was used to detect the genes differentially expressed.ResultsWe accumulated a total of approximately 1.7 million breast tissue-specific SAGE tags and monitored the behavior of more than 25,157 genes during early breast carcinogenesis. We detected 52 transcripts commonly deregulated across the board when comparing normal tissue with ductal carcinoma in situ, and 149 transcripts when comparing ductal carcinoma in situ with invasive ductal carcinoma (P < 0.01).ConclusionA major novelty of our study was the use of a statistical method that correctly accounts for the intra-SAGE and inter-SAGE library sources of variation. The most useful result of applying this modified t statistics beta binomial test is the identification of genes and gene families commonly deregulated across samples within each specific stage in the transition from normal to preinvasive and invasive stages of breast cancer development. Most of the gene expression abnormalities detected at the in situ stage were related to specific genes in charge of regulating the proper homeostasis between cell death and cell proliferation. The comparison of in situ lesions with fully invasive lesions, a much more heterogeneous group, clearly identified as the most importantly deregulated group of transcripts those encoding for various families of proteins in charge of extracellular matrix remodeling, invasion and cell motility functions.

Frequent loss of WWOX expression in breast cancer: correlation with estrogen receptor status.

WWOX is a cancer gene, spanning the common chromosomal fragile site 16D. Genomic and expression aberrations affecting this gene and locus are common in various neoplasias including breast cancer. The aim of the present study was to evaluate the relationship between WWOX expression at the protein level with respect to clinico-pathological characteristics. We performed immunohistochemical analyses on breast specific tissue microarrays representing, human normal breast epithelium (n=16), ductal carcinoma in situ (n=15) and invasive breast cancer cases (n=203). Staining intensity measurements were objectively determined utilizing an image analysis system. Western blot analyses were also performed on an independent set of 23 invasive breast carcinomas. All normal breast epithelial samples express WWOX protein abundantly while 34% (69/203 cases) of invasive breast carcinomas were ‘completely negative’ for WWOX expression and an additional 26% (52/203) of cases expressed WWOX very weakly. For DCIS samples five out of 15 (33%) were negative or weak for WWOX staining. Interestingly, we found a statistically significant correlation between WWOX expression and estrogen receptor (ER) status, 27% of ER+ breast carcinomas were completely negative for WWOX expression versus 46% for ER−cases (p = 0.0054). Furthermore, when negative plus weakly WWOX stained cases were considered the difference became more significant with 51% of ER+ cases and 73% for the ER − group, with a p = 0.003. These data indicate that loss of WWOX expression is a common event in breast cancer. It is unclear at this point whether loss of WWOX expression is a consequence of tumor progression or represents a subclass of breast carcinomas. The strong association of WWOX expression with ER status reinforces the suggested role of this protein as an enzyme involved in sex steroid metabolism.

From mice to humans: Identification of commonly deregulated genes in mammary cancer via comparative SAGE studies

Genetically engineered mouse mammary cancer models have been used over the years as systems to study human breast cancer. However, much controversy exists on the utility of such models as valid equivalents to the human cancer condition. To perform an interspecies gene expression comparative study in breast cancer we used a mouse model that most closely resembles human breast carcinogenesis. This system relies on the transplant of p53 null mouse mammary epithelial cells into the cleared mammary fat pads of syngeneic hosts. Serial analysis of gene expression (SAGE) was used to obtain gene expression profiles of normal and tumor samples from this mouse mammary cancer model (>300,000 mouse mammary-specific tags). The resulting mouse data were compared with 25 of our human breast cancer SAGE libraries (>2.5 million human breast-specific tags). We observed significant similarities in the deregulation of specific genes and gene families when comparing mouse with human breast cancer SAGE data. A total of 72 transcripts were identified as commonly deregulated in both species. We observed a systematic and significant down-regulation in all of the tumors from both species of various cytokines, including CXCL1 (GRO1), LIF, interleukin 6, and CCL2. All of the mouse and most human mammary tumors also displayed decreased expression of genes known to inhibit cell proliferation, including NFKBIA (IKBα), GADD45B, and CDKN1A (p21); transcription-related genes such as CEBP, JUN, JUNB, and ELF1; and apoptosis-related transcripts such as IER3 and GADD34/PPP1R15A. Examples of overexpressed transcripts in tumors from both species include proliferation-related genes such as CCND1, CKS1B, and STMN1 (oncoprotein 18); and genes related to other functions such as SEPW1, SDFR1, DNCI2, and SP110. Importantly, abnormal expression of several of these genes has not been associated previously with breast cancer. The consistency of these observations was validated in independent mouse and human mammary cancer sets. This is the first interspecies comparison of mammary cancer gene expression profiles. The comparative analysis of mouse and human SAGE mammary cancer data validates this p53 null mouse tumor model as a useful system closely resembling human breast cancer development and progression. More importantly, these studies are allowing us to identify relevant biomarkers of potential use in human studies while leading to a better understanding of specific mechanisms of human breast carcinogenesis.

Protein kinase C and cancer: what we know and what we do not

Since their discovery in the late 1970s, protein kinase C (PKC) isozymes represent one of the most extensively studied signaling kinases. PKCs signal through multiple pathways and control the expression of genes relevant for cell cycle progression, tumorigenesis and metastatic dissemination. Despite the vast amount of information concerning the mechanisms that control PKC activation and function in cellular models, the relevance of individual PKC isozymes in the progression of human cancer is still a matter of controversy. Although the expression of PKC isozymes is altered in multiple cancer types, the causal relationship between such changes and the initiation and progression of the disease remains poorly defined. Animal models developed in the last years helped to better understand the involvement of individual PKCs in various cancer types and in the context of specific oncogenic alterations. Unraveling the enormous complexity in the mechanisms by which PKC isozymes have an impact on tumorigenesis and metastasis is key for reassessing their potential as pharmacological targets for cancer treatment.

Breast Cancer Molecular Signatures as Determined by SAGE: Correlation with Lymph Node Status

Global gene expression measured by DNA microarray platforms have been extensively used to classify breast carcinomas correlating with clinical characteristics, including outcome. We generated a breast cancer Serial Analysis of Gene Expression (SAGE) high-resolution database of ∼2.7 million tags to perform unsupervised statistical analyses to obtain the molecular classification of breast-invasive ductal carcinomas in correlation with clinicopathologic features. Unsupervised statistical analysis by means of a random forest approach identified two main clusters of breast carcinomas, which differed in their lymph node status (P = 0.01); this suggested that lymph node status leads to globally distinct expression profiles. A total of 245 (55 up-modulated and 190 down-modulated) transcripts were differentially expressed between lymph node (+) and lymph node (−) primary breast tumors (fold change, ≥2; P < 0.05). Various lymph node (+) up-modulated transcripts were validated in independent sets of human breast tumors by means of real-time reverse transcription-PCR (RT-PCR). We validated significant overexpression of transcripts for HOXC10 (P = 0.001), TPD52L1 (P = 0.007), ZFP36L1 (P = 0.011), PLINP1 (P = 0.013), DCTN3 (P = 0.025), DEK (P = 0.031), and CSNK1D (P = 0.04) in lymph node (+) breast carcinomas. Moreover, the DCTN3 (P = 0.022) and RHBDD2 (P = 0.002) transcripts were confirmed to be overexpressed in tumors that recurred within 6 years of follow-up by real-time RT-PCR. In addition, meta-analysis was used to compare SAGE data associated with lymph node (+) status with publicly available breast cancer DNA microarray data sets. We have generated evidence indicating that the pattern of gene expression in primary breast cancers at the time of surgical removal could discriminate those tumors with lymph node metastatic involvement using SAGE to identify specific transcripts that behave as predictors of recurrence as well. (Mol Cancer Res 2007;5(9):881–90)

Analysis of adenocarcinoma of the colon and rectum: detection of human papillomavirus (HPV) DNA by polymerase chain reaction

Objective  The aim of the present work was to evaluate the presence of human papillomavirus genotypes in malignant and normal mucosa of the colon and rectum in order to determine if a relationship exists between HPV infection and colon neoplasms.

Identification of Novel Amplification Gene Targets in Mouse and Human Breast Cancer at a Syntenic Cluster Mapping to Mouse ch8A1 and Human ch13q34

Serial analysis of gene expression from aggressive mammary tumors derived from transplantable p53 null mouse mammary outgrowth lines revealed significant up-regulation of Tfdp1 (transcription factor Dp1), Lamp1 (lysosomal membrane glycoprotein 1) and Gas6 (growth arrest specific 6) transcripts. All of these genes belong to the same linkage cluster, mapping to mouse chromosome band 8A1. BAC-array comparative genomic hybridization and fluorescence in situ hybridization analyses revealed genomic amplification at mouse region ch8A1.1. The minimal region of amplification contained genes Cul4a, Lamp1, Tfdp1, and Gas6, highly overexpressed in the p53 null mammary outgrowth lines at preneoplastic stages, and in all its derived tumors. The same amplification was also observed in spontaneous p53 null mammary tumors. Interestingly, this region is homologous to human chromosome 13q34, and some of the same genes were previously observed amplified in human carcinomas. Thus, we further investigated the occurrence and frequency of gene amplification affecting genes mapping to ch13q34 in human breast cancer. TFDP1 showed the highest frequency of amplification affecting 31% of 74 breast carcinomas analyzed. Statistically significant positive correlation was observed for the amplification of CUL4A, LAMP1, TFDP1, and GAS6 genes (P < 0.001). Meta-analysis of publicly available gene expression data sets showed a strong association between the high expression of TFDP1 and decreased overall survival (P = 0.00004), relapse-free survival (P = 0.0119), and metastasis-free interval (P = 0.0064). In conclusion, our findings suggest that CUL4A, LAMP1, TFDP1, and GAS6 are targets for overexpression and amplification in breast cancers. Therefore, overexpression of these genes and, in particular, TFDP1 might be of relevance in the development and/or progression in a significant subset of human breast carcinomas.

Breast Cancer Biomarker Discovery in the Functional Genomic Age: A Systematic Review of 42 Gene Expression Signatures

In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules significantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identified meta-signature improves breast cancer patient stratification independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.