Complex Genomic Profiles Research Articles

Novel therapies for advanced squamous cell carcinoma of the lung.

Advanced squamous non-small-cell lung carcinoma (SqCC) has traditionally been considered the 'neglected sibling' compared with lung adenocarcinoma due to lack of effective targeted treatment options. Currently, limited progress has been made in the systemic treatment of advanced disease and combination chemotherapy remains the gold standard. However, the recent completion of the molecular characterization of SqCC revealed an interestingly complex genomic profile, comprising various genetic alterations that can potentially function as molecular targets for the development of novel targeted agents. Recent encouraging results of the use of immune checkpoint inhibitors in several neoplasms has emerged as a promising novel treatment option for advanced SqCC. Future personalized studies, enrolling SqCC patients according to specific driving mutations are underway.

ESPL1 is a candidate oncogene of luminal B breast cancers.

ESPL1/separase is a putative oncogene of luminal B breast cancers. Histoclinical correlations of its expression have never been explored in large series of breast tumors, and specifically in the luminal subtype. In a pooled series of invasive breast carcinomas profiled using DNA microarrays, we identified 3,074 luminal cases, including 1,307 luminal B tumors, in which we searched for correlations between ESPL1 mRNA expression and molecular and histoclinical features. Compared to normal breast samples, ESPL1 was overexpressed in 52% of luminal tumors, and much more frequently in luminal B (83%) than luminal A tumors (29%). In luminal breast cancers, higher ESPL1 expression was associated with poor-prognosis criteria (age≤50years, ductal type, advanced stage, large tumor size, lymph node-positive status, high grade, PR-negative status, luminal B subtype) and with poor metastasis-free survival in both uni- and multivariate analyses. This independent prognostic value was also observed in luminal B tumors only, and persisted when compared with gene expression signatures (PAM50, Recurrence Score, Mammaprint, EndoPredict) currently proposed to refine the indications of adjuvant chemotherapy in hormone receptor-positive/HER2-negative breast cancer. We also confirmed the observations made with experimental mouse models: ESPL1-overexpressing luminal tumors showed complex genomic profiles and molecular features of chromosomal instability and loss of tumor suppressor genes (P53 and Rb). Our results reinforce the idea that ESPL1 is a candidate oncogene in luminal B cancers. Its expression may help improve the prognostication. Inhibiting ESPL1 may represent a promising therapeutic approach for these poor-prognosis tumors.

Fifty years of advances in sarcoma treatment: moving the needle from conventional chemotherapy to targeted therapy.

Much of the progress in systemic therapy for sarcomas was accomplished in the first half of the last 5 decades. Various chemotherapeutic agents were tested in the 70s through the 80s and became part of the standard of care for this patient population. During the decade of the 90s, dose intensification became feasible as a result of improved supportive care and the availability of growth factors, thus maximizing the therapeutic potential of this class of agents. However, response rates and survival plateaued and it became obvious that newer and mechanistically different agents were needed to improve the therapeutic index and gain further enhancement of outcomes. Since early 2000, primarily inspired by the experience with imatinib in gastrointestinal stromal tumors (GISTs), several targeted therapies have been tested in sarcomas with modest success. The major limitations encountered include the lack of drivers and actionable targets for bone and soft tissue sarcomas with complex genomic profiles. Continued investigations and sequencing of larger numbers of these rare and heterogeneous malignancies could shed some light on a path toward improved outcomes.

Genome-wide analyses on high-grade osteosarcoma: Making sense of a genomically most unstable tumor

High-grade osteosarcoma is an extremely genomically unstable tumor. This, together with other challenges, such as the heterogeneity within and between tumor samples, and the rarity of the disease, renders it difficult to study this tumor on a genome-wide level. Now that most laboratories change from genome-wide microarray experiments to Next-Generation Sequencing it is important to discuss the lessons we have learned from microarray studies. In this review, we discuss the challenges of high-grade osteosarcoma data analysis. We give an overview of microarray studies that have been conducted so far on both osteosarcoma tissue samples and cell lines. We discuss recent findings from integration of different data types, which is particularly relevant in a tumor with such a complex genomic profile. Finally, we elaborate on the translation of results obtained with bioinformatics into functional studies, which has lead to valuable findings, especially when keeping in mind that no new therapies with a significant impact on survival have been developed in the past decades.

MED12 Alterations in Both Human Benign and Malignant Uterine Soft Tissue Tumors

The relationship between benign uterine leiomyomas and their malignant counterparts, i.e. leiomyosarcomas and smooth muscle tumors of uncertain malignant potential (STUMP), is still poorly understood. The idea that a leiomyosarcoma could derive from a leiomyoma is still controversial. Recently MED12 mutations have been reported in uterine leiomyomas. In this study we asked whether such mutations could also be involved in leiomyosarcomas and STUMP oncogenesis. For this purpose we examined 33 uterine mesenchymal tumors by sequencing the hot-spot mutation region of MED12. We determined that MED12 is altered in 66.6% of typical leiomyomas as previously reported but also in 11% of STUMP and 20% of leiomyosarcomas. The mutated allele is predominantly expressed in leiomyomas and STUMP. Interestingly all classical leiomyomas exhibit MED12 protein expression while 40% of atypical leiomyomas, 50% of STUMP and 80% of leiomyosarcomas (among them the two mutated ones) do not express MED12. All these tumors without protein expression exhibit complex genomic profiles. No mutations and no expression loss were identified in an additional series of 38 non-uterine leiomyosarcomas. MED12 mutations are not exclusive to leiomyomas but seem to be specific to uterine malignancies. A previous study has suggested that MED12 mutations in leiomyomas could lead to Wnt/β-catenin pathway activation however our immunohistochemistry results show that there is no association between MED12 status and β-catenin nuclear/cytoplasmic localization. Collectively, our results show that subgroups of benign and malignant tumors share a common genetics. We propose here that MED12 alterations could be implicated in the development of smooth muscle tumor and that its expression could be inhibited in malignant tumors.

Abstract 5128: Identification of osteosarcoma driver genes by integrative analysis of copy number and gene expression data

Abstract High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents. The extensive genomic alterations obscure the identification of genes driving tumorigenesis in osteosarcoma progenitor cells. In order to identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of osteosarcoma as compared with its putative progenitor cells, i.e. mesenchymal stem cells (n=12) or osteoblasts (n=3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which we had both DNA and mRNA profiles. Integrative analyses were performed in Nexus Copy Number Software and statistical language R. Paired analyses were performed on all probes which were significantly differentially expressed in corresponding LIMMA analyses. For both non-paired and paired analyses, copy number aberration frequency was set to >35%. Non-paired integrative analyses resulted in 45 genes that were present in both analyses using different control sets, i.e. MSCs and osteoblasts. 101 genes overlapped between the two paired integrative analyses. Paired analyses detected >90% of all genes found with the corresponding non-paired analyses. Remarkably, approximately twice as many genes as found in the corresponding non-paired analyses were detected. Affected genes were compared with differential expression in osteosarcoma cell lines. An overrepresentation of altered cell division related genes was found, such as MCM4 and LATS2, suggesting that deregulation of the cell cycle is an initial driver of osteosarcomagenesis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5128. doi:1538-7445.AM2012-5128

Identification of osteosarcoma driver genes by integrative analysis of copy number and gene expression data

High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents with a second peak at middle age. The extensive genomic alterations obscure the identification of genes driving tumorigenesis during osteosarcoma development. To identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of high-grade osteosarcoma as compared with its putative progenitor cells, i.e., mesenchymal stem cells (n = 12) or osteoblasts (n = 3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which both DNA and mRNA profiles were available. Integrative analyses were performed in Nexus Copy Number software and statistical language R. Paired analyses were performed on all probes detecting significantly differentially expressed genes in corresponding LIMMA analyses. For both nonpaired and paired analyses, copy number aberration frequency was set to >35%. Nonpaired and paired integrative analyses resulted in 45 and 101 genes, respectively, which were present in both analyses using different control sets. Paired analyses detected >90% of all genes found with the corresponding nonpaired analyses. Remarkably, approximately twice as many genes as found in the corresponding nonpaired analyses were detected. Affected genes were intersected with differentially expressed genes in osteosarcoma cell lines, resulting in 31 new osteosarcoma driver genes. Cell division related genes, such as MCM4 and LATS2, were overrepresented and genomic instability was predictive for metastasis-free survival, suggesting that deregulation of the cell cycle is a driver of osteosarcomagenesis.

From PTEN loss of expression to RICTOR role in smooth muscle differentiation: complex involvement of the mTOR pathway in leiomyosarcomas and pleomorphic sarcomas

Over the past decade, comprehensive genomic studies demonstrated that leiomyosarcomas and most of the tumors previously labeled as ‘malignant fibrous histiocytomas' share complex karyotypes and genomic profiles, and can be referred to as ‘sarcomas with complex genomics'. We recently reported a series of 160 sarcomas with complex genomics such as leiomyosarcomas, myxofibrosarcomas, pleomorphic liposarcomas/rhabdomyosarcomas and undifferentiated pleomorphic sarcomas. These tumors present with a frequent loss of chromosome 10 region encompassing the tumor suppressor gene PTEN. In the present study, we assessed PTEN genomic level and protein expression in this large series of sarcomas with complex genomics, as well as activation of downstream pathways. PTEN partial genomic loss was observed in only 46% of tumors, especially in well-differentiated leiomyosarcomas, whereas up to 68% of these tumors demonstrate a loss of protein expression on western blot analysis. Specific discrepancies in PTEN immunohistochemical results suggested bias in this latter technique. PTEN mutations were rare, with only 4 point mutations in the 65 samples studied. Subsequent activation of AKT and mTOR pathways was only observed in 2 out of 3 of PTEN-deleted tumors. On the other hand, RICTOR, a major component of the mTOR complex 2, was significantly overexpressed in well-differentiated leiomyosarcomas. These results, confirmed on tissue micro-array immunohistochemical analysis of 459 sarcomas, could suggest a link between RICTOR overexpression and leiomyosarcomas oncogenesis. As therapeutics directed against the mTOR pathway are assessed in sarcomas, RICTOR overexpression in sarcomas and its links to therapeutic response need to be assessed.

Biologie moléculaire des sarcomes

Sarcomas represent a heterogeneous group of tumors with a complex and poorly reproducible classification. However, in the last ten years, several specific genetic alterations have been described allowing a molecular classification with: 1) sarcomas with a specific translocation which can be used as a diagnostic marker. These translocations can be demonstrated by RT-PCR or by FISH with commercially available break apart probes; 2) sarcomas with simple genomic profile showing amplification of a few genes. Well differentiated liposarcomas, dedifferentiated liposarcomas and intimal sarcomas show a simple genomic profile characterised by MDM2 and CDK4 amplifications associated with amplification of other genes in dedifferentiated liposarcomas; 3) sarcomas with activating mutations: about 90% of GIST show activating mutation of a receptor tyrosine kinase gene, either KIT or PDGFRA. The most frequent mutation involves exon 11 of KIT followed by exon 9 of KIT and exon 18 of PDGFRA. Demonstration of these mutations is useful for the diagnosis of CD117 negative GIST, for predicting response to imatinib and to explain secondary resistance to imatinib; 4) sarcomas with inactivating mutations: malignant rhabdoid tumors show biallelic inactivation of INI1 gene with a lost of INI1 expression which can be demonstrated by immunohistochemistry; 5) other sarcomas usually show a complex genomic profile characterised by numerous gains and losses of genes with a frequent loss of RB1 and alterations of P53. Leiomyosarcomas, pleomorphic rhabdomyosarcomas, pleomorphic liposarcomas, myxofibrosarcomas, poorly differentiated sarcomas (so-called MFH and fibrosarcomas) belong to this category and show no specific molecular abnormality.

Soft tissue sarcomas with complex genomic profiles

Soft tissue sarcomas (STS) with complex genomic profiles (50% of all STS) are predominantly composed of spindle cell/pleomorphic sarcomas, including leiomyosarcoma, myxofibrosarcoma, pleomorphic liposarcoma, pleomorphic rhabdomyosarcoma, malignant peripheral nerve sheath tumor, angiosarcoma, extraskeletal osteosarcoma, and spindle cell/pleomorphic unclassified sarcoma (previously called spindle cell/pleomorphic malignant fibrous histiocytoma). These neoplasms show, characteristically, gains and losses of numerous chromosomes or chromosome regions, as well as amplifications. Many of them share recurrent aberrations (e.g., gain of 5p13-p15) that seem to play a significant role in tumor progression and/or metastatic dissemination. In this paper, we review the cytogenetic, molecular genetic, and clinicopathologic characteristics of the most common STS displaying complex genomic profiles. Features of diagnostic or prognostic relevance will be discussed when needed.

Estimation of Relevant Variables on High-Dimensional Biological Patterns Using Iterated Weighted Kernel Functions

BackgroundThe analysis of complex proteomic and genomic profiles involves the identification of significant markers within a set of hundreds or even thousands of variables that represent a high-dimensional problem space. The occurrence of noise, redundancy or combinatorial interactions in the profile makes the selection of relevant variables harder.Methodology/Principal FindingsHere we propose a method to select variables based on estimated relevance to hidden patterns. Our method combines a weighted-kernel discriminant with an iterative stochastic probability estimation algorithm to discover the relevance distribution over the set of variables. We verified the ability of our method to select predefined relevant variables in synthetic proteome-like data and then assessed its performance on biological high-dimensional problems. Experiments were run on serum proteomic datasets of infectious diseases. The resulting variable subsets achieved classification accuracies of 99% on Human African Trypanosomiasis, 91% on Tuberculosis, and 91% on Malaria serum proteomic profiles with fewer than 20% of variables selected. Our method scaled-up to dimensionalities of much higher orders of magnitude as shown with gene expression microarray datasets in which we obtained classification accuracies close to 90% with fewer than 1% of the total number of variables.ConclusionsOur method consistently found relevant variables attaining high classification accuracies across synthetic and biological datasets. Notably, it yielded very compact subsets compared to the original number of variables, which should simplify downstream biological experimentation.

Evaluation of methods for molecular typing and identification of members of the genus Brevibacterium and other related species

The genus Brevibacterium includes pleomorphic Gram-positive bacteria with a high mol% G+C content. Species in the genus are difficult to identify by classical methods. The discriminatory power of DNA-based methods is assessed. Strains representing the four well established Brevibacterium species, and other related bacteria, were compared by amplified ribosomal DNA restriction analysis (ARDRA), repetitive-sequence-based PCR (rep-PCR) and ribotyping. Fingerprinting by rep-PCR and ribotyping provided complex genomic profiles with the highest discriminatory potential for molecular typing at the strain level, whereas ARDRA showed differentiation from the genus to the species levels. A high degree of heterogeneity within the genus Brevibacterium is apparent, thus indicating that the taxonomy of the genus should be further studied.