Enhanced MAF Oncogene Expression and Breast Cancer Bone Metastasis.
ABSTRACT: There are currently no biomarkers for early breast cancer patient populations at risk of bone metastasis. Identification of mediators of bone metastasis could be of clinical interest.A de novo unbiased screening approach based on selection of highly bone metastatic breast cancer cells in vivo was used to determine copy number aberrations (CNAs) associated with bone metastasis. The CNAs associated with bone metastasis were examined in independent primary breast cancer datasets with annotated clinical follow-up. The MAF gene encoded within the CNA associated with bone metastasis was subjected to gain and loss of function validation in breast cancer cells (MCF7, T47D, ZR-75, and 4T1), its downstream mechanism validated, and tested in clinical samples. A multivariable Cox cause-specific hazard model with competing events (death) was used to test the association between 16q23 or MAF and bone metastasis. All statistical tests were two-sided.16q23 gain CNA encoding the transcription factor MAF mediates breast cancer bone metastasis through the control of PTHrP. 16q23 gain (hazard ratio (HR) for bone metastasis = 14.5, 95% confidence interval (CI) = 6.4 to 32.9, P < .001) as well as MAF overexpression (HR for bone metastasis = 2.5, 95% CI = 1.7 to 3.8, P < .001) in primary breast tumors were specifically associated with risk of metastasis to bone but not to other organs.These results suggest that MAF is a mediator of breast cancer bone metastasis. 16q23 gain or MAF protein overexpression in tumors may help to select patients at risk of bone relapse.
Project description:Genomic copy number alterations (CNA) are common in breast cancer. Identifying characteristic CNAs associated with specific breast cancer subtypes is a critical step in defining potential mechanisms of disease initiation and progression. We used genome-wide array comparative genomic hybridization to identify distinctive CNAs in breast cancer subtypes from 259 young (diagnosed with breast cancer at <55 years) African American (AA) and Caucasian American (CA) women originally enrolled in a larger population-based study. We compared the average frequency of CNAs across the whole genome for each breast tumor subtype and found that estrogen receptor (ER)-negative tumors had a higher average frequency of genome-wide gain (P < 0.0001) and loss (P = 0.02) compared to ER-positive tumors. Triple-negative (TN) tumors had a higher average frequency of genome-wide gain (P < 0.0001) and loss (P = 0.003) than non-TN tumors. No significant difference in CNA frequency was observed between HER2-positive and -negative tumors. We also identified previously unreported recurrent CNAs (frequency >40%) for TN breast tumors at 10q, 11p, 11q, 16q, 20p, and 20q. In addition, we report CNAs that differ in frequency between TN breast tumors of AA and CA women. This is of particular relevance because TN breast cancer is associated with higher mortality and young AA women have higher rates of TN breast tumors compared to CA women. These data support the possibility that higher overall frequency of genomic alteration events as well as specific focal CNAs in TN breast tumors might contribute in part to the poor breast cancer prognosis for young AA women.
Project description:Copy number alterations (CNAs) are a frequent feature in human breast cancer, and one of the hallmarks of genomic instability. The FOSL1, GSTP1 and CCND1 genes are located at 11q13, a cytoband commonly affected by CNA in breast cancer, with relevant function in progression and invasion. Our main goal was to analyze CNAs of these genes and determine their association with breast cancer subtypes. Seventy-three cases of invasive breast tumors [52 Luminal, 7 HER2+ and 14 triple negative (TNBC) subtypes] were analyzed by TaqMan assays. CNAs were observed for all genes, with gains more frequently observed. Gains of the FOSL1 gene were observed in 71% of the cases. This gene was the only one with a statistically significant difference (p<0.001) among tumor subtypes, with increased copy number in TNBC compared to luminal and HER2+. No significant association of CNA and clinical and histopathological parameters from the patients was observed. Additional studies in larger breast cancer patient cohorts based on more refined molecular subtypes are necessary to confirm the observed association of FOSL1 gain with aggressive breast tumors phenotypes.
Project description:Genomic copy number aberrations (CNAs) in gastric cancer have already been extensively characterized by array comparative genomic hybridization (array CGH) analysis. However, involvement of genomic CNAs in the process of submucosal invasion and lymph node metastasis in early gastric cancer is still poorly understood. In this study, to address this issue, we collected a total of 59 tumor samples from 27 patients with submucosal-invasive gastric cancers (SMGC), analyzed their genomic profiles by array CGH, and compared them between paired samples of mucosal (MU) and submucosal (SM) invasion (23 pairs), and SM invasion and lymph node (LN) metastasis (9 pairs). Initially, we hypothesized that acquisition of specific CNA(s) is important for these processes. However, we observed no significant difference in the number of genomic CNAs between paired MU and SM, and between paired SM and LN. Furthermore, we were unable to find any CNAs specifically associated with SM invasion or LN metastasis. Among the 23 cases analyzed, 15 had some similar pattern of genomic profiling between SM and MU. Interestingly, 13 of the 15 cases also showed some differences in genomic profiles. These results suggest that the majority of SMGCs are composed of heterogeneous subpopulations derived from the same clonal origin. Comparison of genomic CNAs between SMGCs with and without LN metastasis revealed that gain of 11q13, 11q14, 11q22, 14q32 and amplification of 17q21 were more frequent in metastatic SMGCs, suggesting that these CNAs are related to LN metastasis of early gastric cancer. In conclusion, our data suggest that generation of genetically distinct subclones, rather than acquisition of specific CNA at MU, is integral to the process of submucosal invasion, and that subclones that acquire gain of 11q13, 11q14, 11q22, 14q32 or amplification of 17q21 are likely to become metastatic.
Project description:Copy number alteration (CNA) is a major contributor to genome instability, a hallmark of cancer. Here, we studied genomic alterations in single primary tumor cells and circulating tumor cells (CTCs) from the same patient. Single-nucleotide variants (SNVs) in single cells from both samples occurred sporadically, whereas CNAs among primary tumor cells emerged accumulatively rather than abruptly, converging toward the CNA in CTCs. Focal CNAs affecting the MYC gene and the PTEN gene were observed only in a minor portion of primary tumor cells but were present in all CTCs, suggesting a strong selection toward metastasis. Single-cell structural variant (SV) analyses revealed a two-step mechanism, a complex rearrangement followed by gene amplification, for the simultaneous formation of anomalous CNAs in multiple chromosome regions. Integrative CNA analyses of 97 CTCs from 23 patients confirmed the convergence of CNAs and revealed single, concurrent, and mutually exclusive CNAs that could be the driving events in cancer metastasis.
Project description:Breast tumor heterogeneity has been well documented through the use of multiplatform -omic studies in human tumors. However, there is no integrative database to capture the heterogeneity within mouse models of breast cancer. This project identifies genomic copy number alterations (CNAs) in 600 tumors across 27 major mouse models of breast cancer through the application of a predictive algorithm to publicly available gene expression data. It was found that despite the presence of strong oncogenic drivers in most mouse models, CNAs are extremely common but heterogeneous both between models and within models. Many mouse CNA events are largely conserved in human tumors and in the mouse we show that they are associated with secondary tumor characteristics such as tumor histology, metastasis, as well as enhanced oncogenic signaling. These data serve as an important resource in guiding investigators when choosing a mouse model to understand the gene copy number changes relevant to human breast cancer.
Project description:Accurate detection of copy number alterations (CNAs) using next-generation sequencing technology is essential for the development and application of more precise medical treatments for human cancer. Here, we evaluated seven CNA estimation tools (ExomeCNV, CoNIFER, VarScan2, CODEX, ngCGH, saasCNV, and falcon) using whole-exome sequencing data from 419 breast cancer tumor-normal sample pairs from The Cancer Genome Atlas. Estimations generated using each tool were converted into gene-based copy numbers; concordance for gains and losses and the sensitivity and specificity of each tool were compared to validated copy numbers from a single nucleotide polymorphism reference array. The concordance and sensitivity of the tumor-normal pair methods for estimating CNAs (saasCNV, ExomeCNV, and VarScan2) were better than those of the tumor batch methods (CoNIFER and CODEX). SaasCNV had the highest gain and loss concordances (65.0%), sensitivity (69.4%), and specificity (89.1%) for estimating copy number gains or losses. These findings indicate that improved CNA detection algorithms are needed to more accurately interpret whole-exome sequencing results in human cancer.
Project description:DNA copy number alterations (CNAs) are frequent in cancer, and recently developed CNA signatures revealed their value in molecular tumor stratification for patient prognosis and platinum resistance prediction in ovarian cancer. Head and neck squamous cell carcinoma (HNSCC) is also characterized by high CNAs. In this study, we determined CNA in 173 human papilloma virus-negative HNSCC from a Dutch multicenter cohort by low-coverage whole genome sequencing and tested the prognostic value of seven cancer-derived CNA signatures for these cisplatin- and radiotherapy-treated patients. We find that a high CNA signature 1 (s1) score is associated with low values for all other signatures and better patient outcomes in the Dutch cohorts and The Cancer Genome Atlas HNSCC data set. High s5 and s7 scores are associated with increased distant metastasis rates and high s6 scores with poor overall survival. High cumulative cisplatin doses result in improved outcomes in chemoradiotherapy-treated HNSCC patients. Here we find that tumors high in s1 or low in s6 are most responsive to a change in cisplatin dose. High s5 values, however, significantly increase the risk for metastasis in patients with low cumulative cisplatin doses. Together this suggests that the processes causing these CNA signatures affect cisplatin response in HNSCC. In conclusion, CNA signatures derived from a different cancer type were prognostic and associated with cisplatin response in HNSCC, suggesting they represent underlying molecular processes that define patient outcome.
Project description:DNA copy number aberrations (CNAs) and gene expression (GE) changes provide valuable information for studying chromosomal instability and its consequences in cancer. While it is clear that the structural aberrations and the transcript levels are intertwined, their relationship is more complex and subtle than initially suspected. Most studies so far have focused on how a CNA affects the expression levels of those genes contained within that CNA.To better understand the impact of CNAs on expression, we investigated the correlation of each CNA to all other genes in the genome. The correlations are computed over multiple patients that have both expression and copy number measurements in brain, bladder and breast cancer data sets. We find that a CNA has a direct impact on the gene amplified or deleted, but it also has a broad, indirect impact elsewhere. To identify a set of CNAs that is coordinately associated with the expression changes of a set of genes, we used a biclustering algorithm on the correlation matrix. For each of the three cancer types examined, the aberrations in several loci are associated with cancer-type specific biological pathways that have been described in the literature: CNAs of chromosome (chr) 7p13 were significantly correlated with epidermal growth factor receptor signaling pathway in glioblastoma multiforme, chr 13q with NF-kappaB cascades in bladder cancer, and chr 11p with Reck pathway in breast cancer. In all three data sets, gene sets related to cell cycle/division such as M phase, DNA replication and cell division were also associated with CNAs. Our results suggest that CNAs are both directly and indirectly correlated with changes in expression and that it is beneficial to examine the indirect effects of CNAs.The code is available upon request.
Project description:Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.
Project description:Oral squamous cell carcinoma (OSCC) is a common cancer in Taiwan and worldwide. To provide some clues for clinical management of OSCC, 72 advanced-stage OSCCs were analyzed using two microarray platforms (26 cases with Affymetrix 500 K and 46 cases with Affymetrix SNP 6.0). Genomic identification of significant targets in cancer analyses were used to identify significant copy number alterations (CNAs) using a q-value cutoff of 0.25. Among the several significant regions, 12 CNAs were common between these two platforms. Two gain regions contained the well-known oncogenes EGFR (7p11.2) and CCND1 (11q13.3) and several known cancer suppressor genes, such as FHIT (3p14.2-p12.1), FAT1 (4q35.1), CDKN2A (9p21.3), and ATM (11q22.3-q24.3), reside within the 10 deletion regions. Copy number gains of EGFR and CCND1 were further confirmed by fluorescence in situ hybridization and TaqMan CN assay, respectively, in 257 OSCC cases. Our results indicate that EGFR and CCND1 CNAs are significantly associated with clinical stage, tumor differentiation, and lymph node metastasis. Furthermore, EGFR and CCND1 CNAs have an additive effect on OSCC tumor progression. Thus, current genome-wide CNA analysis provides clues for future characterization of important oncogenes and tumor suppressor genes associated with the behaviors of the disease.