Patterns of Practice Survey: Radiotherapy for Soft Tissue Sarcoma of the Extremities.

Background Neoadjuvant or adjuvant radiotherapy (RT) for extremity soft tissue sarcoma (STS) confers significant local control benefit. To determine patterns of practice, a survey of RT planning practices was undertaken. Method Members of the Connective Tissue Oncology Society and Canadian Association of Radiation Oncology participated in this survey pertaining to general practice patterns of RT for extremity STS, patterns of contouring and planning, and use of quality control measures such as guidelines, tumor boards, and quality assurance rounds. Results A total of 58 radiation oncologists treating extremity STS from 12 countries responded. 89.7% work in academically affiliated centres, and 55.2% saw at least 20 cases of extremity STS per year. Most (96.7%) had access to multidisciplinary sarcoma boards (85.5% of those discussed every referred sarcoma case). 78.6% held quality assurance rounds. Most (92.9%) used planning guidelines. Pre-operative RT was used nearly twice as much as post-operative RT. CT simulation with MR fusion was used by 94.6%. Patterns of clinical target volume (CTV) contouring for both superficial and deep STS were variable. 69.8% contoured a normal soft tissue strip for extremity sarcoma, 13.5% without routine constraints and the remainder with various constraints. Most (91.1%) used 50 Gy in 25 fractions pre-operatively and 39.6% reported using post-operative RT boost for positive margins. Post-operative dose was more variable from 59.4 Gy to 70 Gy. Conclusion Major aspects of RT planning for extremity STS were similar among the responders, and most were academically affiliated. Over twice as many employed pre-operative as opposed to post-operative RT. There was considerable heterogeneity in use of: margins for contouring, normal soft tissue strip as an avoidance structure, and boost for positive margins. This survey shows variable patterns of practice and identifies areas that may require further research.

Collective migration of cancer-associated fibroblasts is enhanced by overexpression of tight junction-associated proteins claudin-11 and occludin.

It has been suggested that cancer-associated fibroblasts (CAFs) positioned at the desmoplastic areas of various types of cancer are capable of executing a migratory program, characterized by accelerated motility and collective configuration. Since CAFs are reprogrammed derivatives of normal progenitors, including quiescent fibroblasts, we hypothesized that such migratory program could be context-dependent, thus being regulated by specific paracrine signals from the adjacent cancer population. Using the traditional scratch assay setup, we showed that only specific colon cancer cell lines (i.e. HT29) were able to induce collective CAF migration. By performing quantitative proteomics (SILAC), we identified a 2.7-fold increase of claudin-11, a member of the tight junction apparatus, in CAFs that exerted such collectivity in their migratory pattern. Further proteomic investigations of cancer cell line secretomes revealed a specific signature, involving TGF-ß, as potential mediator of this effect. Normal colonic fibroblasts stimulated with TGF-ß exerted myofibroblastic differentiation, occludin (OCLN) and claudin-11 (CLDN11) overexpression and cohort formation. Subsequently, inhibition of TGF-ß attenuated all the previous effects. Immunohistochemistry of the universal tight junction marker occludin in a cohort of 30 colorectal adenocarcinoma patients defined a CAF subpopulation expressing tight junctions. Overall, these data suggest that cancer cells may induce CLDN11 overexpression and subsequent collective migration of peritumoral CAFs via TGF-ß secretion.

Quantitative proteomic analysis of amniocytes reveals potentially dysregulated molecular networks in Down syndrome.

BACKGROUND: Down syndrome (DS), caused by an extra copy of chromosome 21, affects 1 in 750 live births and is characterized by cognitive impairment and a constellation of congenital defects. Currently, little is known about the molecular pathogenesis and no direct genotype-phenotype relationship has yet been confirmed. Since DS amniocytes are expected to have a distinct biological behaviour compared to normal amniocytes, we hypothesize that relative quantification of proteins produced from trisomy and euploid (chromosomally normal) amniocytes will reveal dysregulated molecular pathways. RESULTS: Chromosomally normal- and Trisomy 21-amniocytes were quantitatively analyzed by using Stable Isotope Labeling of Amino acids in Cell culture and tandem mass spectrometry. A total of 4919 unique proteins were identified from the supernatant and cell lysate proteome. More specifically, 4548 unique proteins were identified from the lysate, and 91% of these proteins were quantified based on MS/MS spectra ratios of peptides containing isotope-labeled amino acids. A total of 904 proteins showed significant differential expression and were involved in 25 molecular pathways, each containing a minimum of 16 proteins. Sixty of these proteins consistently showed aberrant expression from trisomy 21 affected amniocytes, indicating their potential role in DS pathogenesis. Nine proteins were analyzed with a multiplex selected reaction monitoring assay in an independent set of Trisomy 21-amniocyte samples and two of them (SOD1 and NES) showed a consistent differential expression. CONCLUSIONS: The most extensive proteome of amniocytes and amniotic fluid has been generated and differentially expressed proteins from amniocytes with Trisomy 21 revealed molecular pathways that seem to be most significantly affected by the presence of an extra copy of chromosome 21.

Development of a multiplex selected reaction monitoring assay for quantification of biochemical markers of down syndrome in amniotic fluid samples.

Down syndrome (DS) is one of the most common chromosomal abnormalities affecting about 1 of every 700 fetuses. Current screening strategies have detection rates of 90-95% at a 5% false positive rate. The aim of this study was to discover new biomarkers of DS in amniotic fluid by using a multiplex selected reaction monitoring assay. Nine proteins were analyzed: CEL, CPA1, MUC13, CLCA1, MUC5AC, PLUNC, and HAPLN1, and CGB as positive control and serotransferrin as negative control. One proteotypic peptide for each protein was selected, and internal heavy isotope-labeled peptide standards were spiked into the samples. Fifty-four samples from pregnant women carrying normal (n = 37) or DS-affected (n = 17) fetuses were analyzed. The median protein concentrations for DS and normal samples, respectively, were as follows: 20 and 49 ng/mL (p < 0.01) for CEL; 3.7 and 14 ng/mL (p < 0.001) for CPA1; 80 and 263 ng/mL (p < 0.001) for MUC13; 46 and 135 ng/mL (p < 0.001) for CLCA1; 0.65 and 0.93 µg/mL (p < 0.05) for MUC5AC; 61 and 73 ng/mL (p > 0.05) for PLUNC; 144 and 86 ng/mL (p < 0.01) for HAPLN1; 0.89 and 0.54 µg/mL (p = 0.05) for CGB; 91 and 87 µg/mL (p > 0.05) for serotransferrin. Statistically significant differences were found in six out of the seven candidate proteins analyzed, reflecting a different regulation in DS.

Verification of a biomarker discovery approach for detection of Down syndrome in amniotic fluid via multiplex selected reaction monitoring (SRM) assay.

Prenatal screening test for Down syndrome (DS) can be improved by discovery of novel biomarkers. A multiplex selected reaction monitoring (SRM) assay was developed to test previously identified thirteen candidate proteins in amniotic fluid (AF). One unique peptide was selected for each protein based on discovery data, while three MS/MS transitions were selected based on intelligent SRM results. For one of the candidates, matrix metalloproteinase-2 (MMP2), ELISA was also performed to validate SRM results in AF and to test serum samples. Comparison of AF samples from DS versus controls via SRM assay revealed five proteins that were differentially expressed. Bile salt-activated lipase, mucin-13, carboxypeptidase A1, and dipeptidyl peptidase 4 showed a decrease in DS-affected AF, and MMP2 showed an increase, in comparison to controls (P<0.05). Discovery-based spectral counting ratios and SRM ratios showed a strong correlation, and MMP2 ELISA further confirmed the validity of the SRM data. Potential implications of differentially expressed proteins during fetal development are proposed. Our data also shows that SRM can provide a high-throughput and accurate platform for biomarker verification.

Application of proteomics to prenatal screening and diagnosis for aneuploidies.

Current screening for fetal aneuploidies relies on biochemical and ultrasound measurements, and the sensitivity and specificity needs to be improved to reduce the number of pregnant women subjected to invasive diagnostic procedures, such as amniocentesis. Proteomic technologies enable new strategies for discovering biomarkers from complex biological fluids in a high-throughput and sensitive manner. Since mass spectrometry-based techniques allow for both qualitative and quantitative analysis of a given proteome, they have been widely used to resolve and compare the proteome of maternal plasma, serum, urine, cervical-vaginal fluid, and amniotic fluid. Comparisons of proteomes of normal fluids with those from aneuploidy pregnancies have revealed a host of candidate markers that still need to be verified. In parallel with proteomics, there is interest in other emerging techniques, such as RNA-SNP analysis or quantitation of fetal DNA by shotgun sequencing. Although these genomic techniques hold much promise, discovery of additional markers via quantitative proteomic comparisons could drastically improve current conventional screening at reasonable cost. Proteomics-based biomarker discovery is applicable to detection of not just aneuploidies, but also other pregnancy-related diseases.

Amniotic fluid proteome analysis from Down syndrome pregnancies for biomarker discovery.

Down syndrome (DS) is an anomaly caused by an extra chromosome 21, and it affects 1 in 750 live births. Phenotypes include cognitive impairment, congenital defects, and increased risk for several diseases such as Alzheimer's disease and leukemia. Current DS-screening tests subject many women to invasive procedures for accurate diagnosis due to insufficient specificity. Since amniotic fluid (AF) surrounds the developing fetus, understanding the changes in AF composition in the presence of DS may provide insights into genotype-phenotype associations, and aid in discovery of novel biomarkers for better screening. On the basis of our previous study, in which we reported an extensive proteome of AF, we performed two-dimensional liquid chromatography followed by MS/MS to analyze triplicates of pooled AF of chromosomally normal and DS-affected pregnancies (10 samples per pool). A total of 542 proteins were identified from the two sets of triplicate analyses by the LTQ-Orbitrap mass spectrometer and data were compared semiquantitatively by spectral counting. Candidate biomarkers were selected based on the spectral count differences between the two conditions after normalization. Comparison between the two groups revealed 60 candidates that showed greater than 2-fold increase or decrease in concentration in the presence of DS. Among these candidates, amyloid precursor protein and tenascin-C were verified by ELISA, and both showed a 2-fold increase, on average, in DS-AF samples compared to controls. All proteins that showed significant differences between the two conditions were bioinformatically analyzed to preliminarily understand their biological implications in DS.

Proteomics analysis of human amniotic fluid.

Amniotic fluid is a dynamic and complex mixture that reflects the physiological status of the developing fetus. In this study, the human amniotic fluid (AF) proteome of a 16-18-week normal pregnancy was profiled and analyzed to investigate the composition and functions of this fluid. Due to the complexity of AF, we utilized three different fractionation strategies to provide greater coverage. Two types of two-dimensional LC/MS/MS as well as an LC-SDS-PAGE-LC-MS/MS platform were used. A total of 16 AF samples between gestational ages of 16 and 18 weeks from women carrying chromosomally normal fetuses were analyzed by one of the three fractionation methods followed by a common reverse phase LC-MS/MS step. Mascot and The Global Proteome Machine engines were used to search the International Protein Index human database for peptide sequence identification. The list of proteins was generated by combining the results of both engines through the PeptideProphet of Scaffold software. All identified proteins were combined to generate the AF proteome comprising 1,026 unique gene matches or 842 non-redundant proteins. This list includes most of the currently used biomarkers for pregnancy-associated pathologic conditions such as preterm delivery, intra-amniotic infection, and chromosomal anomalies of the fetus. The subcellular localization, tissue expression, functions, and networks of the AF proteome were analyzed by various bioinformatic tools. These data will contribute to the better understanding of amniotic fluid function and to the discovery of novel biomarkers for prenatal diagnosis of fetal abnormalities.