Targeted molecular analysis in adrenocortical carcinomas: a strategy towards improved personalized prognostication

Context: Adrenocortical carcinoma (ACC) has a heterogeneous prognosis, and current medical therapies have limited efficacy in its advanced stages. Genome-wide multiomics studies identified molecular patterns associated with clinical outcome. Objective: Here, we aimed at identifying a molecular signature useful for both personalized prognostic stratification and druggable targets, using methods applicable in clinical routine. Design: In total, 117 tumor samples from 107 patients with ACC were analyzed. Targeted next-generation sequencing of 160 genes and pyrosequencing of 4 genes were applied to formalin-fixed, paraffin-embedded (FFPE) specimens to detect point mutations, copy number alterations, and promoter region methylation. Molecular results were combined with clinical/histopathological parameters (tumor stage, age, symptoms, resection status, and Ki-67) to predict progression-free survival (PFS). Results: In addition to known driver mutations, we detected recurrent alterations in genes not previously associated with ACC (e.g., NOTCH1, CIC, KDM6A, BRCA1, BRCA2). Best prediction of PFS was obtained integrating molecular results (more than one somatic mutation, alterations in Wnt/beta-catenin and p53 pathways, high methylation pattern) and clinical/histopathological parameters into a combined score (P <0.0001, chi(2) = 68.6). Accuracy of prediction for early disease progress was 83.3% (area under the receiver operating characteristic curve: 0.872, 95% confidence interval 0.80 to 0.94). Furthermore, 17 potentially targetable alterations were found in 64 patients (e.g., inCDK4, NOTCH1, NF1, MDM2, and EGFR and in DNA repair system). Conclusions: This study demonstrates that molecular profiling of FFPE tumor samples improves prognostication of ACC beyond clinical/histopathological parameters and identifies new potential drug targets. These findings pave the way to precision medicine in this rare disease

Spontaneous aminolytic cyclization and self-assembly of dipeptide methyl esters in water

Dipeptides are known to spontaneously cyclize to diketopiperazines, and in some cases these cyclic dipeptides have been shown to self-assemble to form supramolecular nanostructures. Herein, we demonstrate the in situ cyclization of dipeptide methyl esters in aqueous buffer by intramolecular aminolysis, leading to the formation of diverse supramolecular nanostructures. The chemical nature of the amino acid side chains dictates the supramolecular arrangement and resulting nanoscale architectures. For c[LF], supramolecular gels are formed, and the concentration of starting materials influences the mechanical properties of hydrogels. Moreover, by adding metalloporphyrin to the starting dipeptide ester solution, these become incorporated through cooperative assembly, resulting in the formation of nanofibers able to catalyse the oxidation of organic phenol in water. The approach taken here, which combines the chemically activated assembly with the versatility of short peptides might pave the way for achieving the spontaneous formation of supramolecular order and function using simple building blocks

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

Prognostic factors in stage III-IV adrenocortical carcinomas (ACC): an European Network for the Study of Adrenal Tumor (ENSAT) study.

BACKGROUND: The clinical course of advanced adrenocortical carcinoma (ACC) is heterogeneous. Our study aimed primarily to refine and make headway in the prognostic stratification of advanced ACC. PATIENTS AND METHODS: Patients with advanced ENSAT ACC (stage III or stage IV) at diagnosis registered between 2000 and 2009 in the ENSAT database were enrolled. The primary end point was overall survival (OS). Parameters of potential prognostic relevance were selected. Univariate and multivariate analyses were carried out: model 1 'before surgery'; model 2 'post-surgery'. RESULTS: Four hundred and forty-four patients with advanced ENSAT ACC (stage III: 210; stage IV: 234) were analyzed. After a median follow-up of 55.2 months, the median OS was 24 months. A modified ENSAT (mENSAT) classification was validated: stage III (invasion of surrounding tissues/organs or the vena renalis/cava) and stage IVa, IVb, IVc (2, 3 or >3 metastatic organs, including N, respectively). Two- or 5-year OS was 73%, 46%, 26% and 15% or 50%, 15%, 14% and 2% for stages III, IVa, IVb and IVc, respectively. In the multivariate analysis, mENSAT stages (stages IVa, IVb, or IVc, respectively) were significantly correlated with OS (P 6 and/or Ki67 ≥20%, P = 0.06) in model 2. CONCLUSION: The mENSAT classification and GRAS parameters (Grade, R status, Age and Symptoms) were found to best stratify the prognosis of patients with advanced ACC

Cohesive versus Flexible Evolution of Functional Modules in Eukaryotes

Although functionally related proteins can be reliably predicted from phylogenetic profiles, many functional modules do not seem to evolve cohesively according to case studies and systematic analyses in prokaryotes. In this study we quantify the extent of evolutionary cohesiveness of functional modules in eukaryotes and probe the biological and methodological factors influencing our estimates. We have collected various datasets of protein complexes and pathways in Saccheromyces cerevisiae. We define orthologous groups on 34 eukaryotic genomes and measure the extent of cohesive evolution of sets of orthologous groups of which members constitute a known complex or pathway. Within this framework it appears that most functional modules evolve flexibly rather than cohesively. Even after correcting for uncertain module definitions and potentially problematic orthologous groups, only 46% of pathways and complexes evolve more cohesively than random modules. This flexibility seems partly coupled to the nature of the functional module because biochemical pathways are generally more cohesively evolving than complexes

Prevalence of the most frequent BRCA1 mutations in Polish population

The purpose of our study was to establish the frequency and distribution of the four most common BRCA1 mutations in Polish general population and in a series of breast cancer patients. Analysis of the population frequency of 5382insC (c.5266dupC), 300T >G (p.181T >G), 185delAG (c.68_69delAG) and 3819del5 (c.3700_3704del5) mutations of the BRCA1 gene were performed on a group of respectively 16,849, 13,462, 12,485 and 3923 anonymous samples collected at birth in seven Polish provinces. The patient group consisted of 1845 consecutive female breast cancer cases. The most frequent BRCA1 mutation in the general population was 5382insC found in 29 out of 16,849 samples (0.17%). 300T >G and 3819del5 mutations were found in respectively 11 of 13,462 (0.08%) and four of 3923 (0.1%) samples. The population prevalence for combined Polish founder 5382insC and 300T >G mutations was 0.25% (1/400). The frequencies of 5382insC and 300T >G carriers among consecutive breast cancer cases were, respectively, 1.9% (35/1845) and 1.2% (18/1486). Comparing these data with the population frequency, we calculated the relative risk of breast cancer for 5382insC mutation at OR = 17 and for 300T >G mutation at OR = 26. Our results, based on large population studies, show high frequencies of founder 5382insC and 300T >G BRCA1 mutations in Polish general population. Carriage of one of these mutations is connected with a very high relative risk of breast cancer

Enrichment of homologs in insignificant BLAST hits by co-complex network alignment

<p>Abstract</p> <p>Background</p> <p>Homology is a crucial concept in comparative genomics. The algorithm probably most widely used for homology detection in comparative genomics, is BLAST. Usually a stringent score cutoff is applied to distinguish putative homologs from possible false positive hits. As a consequence, some BLAST hits are discarded that are in fact homologous.</p> <p>Results</p> <p>Analogous to the use of the genomics context in genome alignments, we test whether conserved functional context can be used to select candidate homologs from insignificant BLAST hits. We make a co-complex network alignment between complex subunits in yeast and human and find that proteins with an insignificant BLAST hit that are part of homologous complexes, are likely to be homologous themselves. Further analysis of the distant homologs we recovered using the co-complex network alignment, shows that a large majority of these distant homologs are in fact ancient paralogs.</p> <p>Conclusions</p> <p>Our results show that, even though evolution takes place at the sequence and genome level, co-complex networks can be used as circumstantial evidence to improve confidence in the homology of distantly related sequences.</p

Metastatic Pheochromocytoma and Paraganglioma: Somatostatin Receptor 2 Expression, Genetics, and Therapeutic Responses

CONTEXT: Pheochromocytomas and paragangliomas (PPGLs) with pathogenic mutations in the succinate dehydrogenase subunit B (SDHB) are associated with a high metastatic risk. Somatostatin receptor 2 (SSTR2)-dependent imaging is the most sensitive imaging modality for SDHB-related PPGLs, suggesting that SSTR2 expression is a significant cell surface therapeutic biomarker of such tumors. OBJECTIVE: Exploration of the relationship between SSTR2 immunoreactivity and SDHB immunoreactivity, mutational status, and clinical behavior of PPGLs. Evaluation of SSTR-based therapies in metastatic PPGLs. METHODS: Retrospective analysis of a multicenter cohort of PPGLs at 6 specialized Endocrine Tumor Centers in Germany, The Netherlands, and Switzerland. Patients with PPGLs participating in the ENSAT registry were included. Clinical data were extracted from medical records, and immunohistochemistry (IHC) for SDHB and SSTR2 was performed in patients with available tumor tissue. Immunoreactivity of SSTR2 was investigated using Volante scores. The main outcome measure was the association of SSTR2 IHC positivity with genetic and clinical-pathological features of PPGLs. RESULTS: Of 202 patients with PPGLs, 50% were SSTR2 positive. SSTR2 positivity was significantly associated with SDHB- and SDHx-related PPGLs, with the strongest SSTR2 staining intensity in SDHB-related PPGLs (P = .01). Moreover, SSTR2 expression was significantly associated with metastatic disease independent of SDHB/SDHx mutation status (P < .001). In metastatic PPGLs, the disease control rate with first-line SSTR-based radionuclide therapy was 67% (n = 22, n = 11 SDHx), and with first-line "cold" somatostatin analogs 100% (n = 6, n = 3 SDHx). CONCLUSION: SSTR2 expression was independently associated with SDHB/SDHx mutations and metastatic disease. We confirm a high disease control rate of somatostatin receptor-based therapies in metastatic PPGLs