Increased fluoroscopy time for central venous catheter placement by radiology residents versus staff radiologists.

PURPOSE: To evaluate differences in interventional radiology procedural fluoroscopy time (FT) for radiology residents versus staff radiologists, using central venous catheter (CVC) placement as an index service. METHODS: To minimize interservice and complexity variables, stand-alone temporary internal jugular CVC procedures were targeted for analysis. Reports and images from 1,067 temporary CVC services from 2 hospitals over 2 years were reviewed as part of a quality improvement initiative. Insertion site, catheter type (eg, smaller triple lumen versus larger hemodialysis), resident identifier, staff identifier, and documented FT were compiled and analyzed. RESULTS: Applying clinical (eg, concomitant venous angioplasty) and anatomic (eg, femoral access) exclusions, 537 cases with complete CVC procedure records were available for analysis. Radiology residents and staff radiologists were primary operators in 128 and 409 procedures, respectively. Distribution of resident procedures (82% right, 66% large lumen) was similar to that of staff (79% right, 63% large lumen). Mean FT of resident services was twice as long as that of staff services (1.24 minutes versus 0.63 minutes, P < .0001). Resident FT was independent of supervising staff radiologist. Increasing years of training for residents did not significantly reduce FT. CONCLUSIONS: When CVCs are placed by radiology residents, FT is double that for identical procedures performed by staff radiologists. Similar discrepancies likely exist for other interventional radiologic procedures. Residency training programs should initiate measures to monitor and manage fluoroscopy during interventional procedures to minimize radiation dose to patients, trainees, and other staff.

Central venous access: evolving roles of radiology and other specialties nationally over two decades.

PURPOSE: The aim of this study was to evaluate national trends in central venous access (CVA) procedures over 2 decades with regard to changing specialty group roles and places of service. METHODS: Aggregated claims data for temporary central venous catheter and long-term CVA device (CVAD) procedures were extracted from Medicare Physician/Supplier Procedure Summary Master Files from 1992 through 2011. Central venous catheter and CVAD procedure volumes by specialty group and place of service were studied. RESULTS: Between 1992 and 2011, temporary and long-term CVA placement procedures increased from 638,703 to 808,071 (+27%) and from 76,444 to 316,042 (+313%), respectively. For temporary central venous catheters, radiology (from 0.4% in 1992 to 32.6% in 2011) now exceeds anesthesiology (from 37% to 22%) and surgery (from 30.4% to 11.7%) as the dominant provider group. Surgery continues to dominate in placement and explantation of long-term CVADs (from 80.7% to 50.4% and from 81.6% to 47.7%, respectively), but radiology's share has grown enormously (from 0.7% to 37.6% and from 0.2% to 28.6%). Although volumes remain small (<10% of all procedures), midlevel practitioners have experienced >100-fold growth for most services. The inpatient hospital remains the dominant site for temporary CVA procedures (90.0% in 1992 and 81.2% in 2011), but the placement of long-term CVADs has shifted from the inpatient (from 68.9% to 45.2%) to hospital outpatient (from 26.9% to 44.3%) setting. In all hospital settings combined, radiologists place approximately half of all tunneled catheters and three-quarters all peripherally inserted central catheters. CONCLUSIONS: Over the past 2 decades, CVA procedures on Medicare beneficiaries have increased considerably. Radiology is now the dominant overall provider.

Identification of blood protein biomarkers that aid in the clinical assessment of patients with malignant glioma.

Analyzing molecular biomarkers using blood is an important approach for clinical assessment of malignant glioma. We investigated a molecular proteomic biomarker-based approach for glioblastoma using patients' blood samples. The expression levels of a list of candidate proteins were quantified in plasma and serum samples from two different cohorts of patients with malignant glioma and normal controls. The biological function was studied for one of the identified markers. Additionally, the prognostic significance of protein marker expression was measured by survival analysis. As a result, protein biomarkers associated with malignant glioma were identified from the blood specimens and five of the protein biomarkers were common to both cohorts. Immunohistochemical analysis demonstrated that many of the protein biomarkers identified in peripheral blood specimens were expressed in malignant gliomas. Staining levels for one of the biomarkers, MIP-1α, was found to correlate with WHO grade among invasive gliomas, and we demonstrate that MIP-1α promotes human glioblastoma cell proliferation and migration. Additionally, four prognostic protein biomarkers were identified. In conclusion, we demonstrate that both peripheral blood plasma and serum specimens are highly valuable and complementary to each other in the quest for protein biomarkers of malignant glioma. Sets of novel protein biomarkers were identified that may aid in the diagnosis and prognosis of patients with malignant glioma.

Combining laser capture microdissection and proteomics: methodologies and clinical applications.

Laser capture microdissection (LCM) has become an important tool for biomedical research. Various molecular biology techniques have been combined with LCM to reveal molecular profiles at an unprecedented tissue resolution. Proteomics is among those techniques that have proved fruitful in combination with LCM. This review provides an overview of the various proteomic techniques that have been developed for analyzing cells obtained using LCM. Methods for analyzing microdissected cells for various proteomic techniques are described and compared. In addition, various applications based on LCM and proteomics are discussed.

Quantitative analysis of the secretome of TGF-beta signaling-deficient mammary fibroblasts.

Transforming growth factor beta (TGF-beta) is a master regulator of autocrine and paracrine signaling pathways between a tumor and its microenvironment. Decreased expression of TGF-beta type II receptor (TbetaRII) in stromal cells is associated with increased tumor metastasis and shorter patient survival. In this study, SILAC quantitative proteomics was used to identify differentially externalized proteins in the conditioned media from the mammary fibroblasts with or without intact TbetaRII. Over 1000 proteins were identified and their relative differential levels were quantified. Immunoassays were used to further validate identification and quantification of the proteomic results. Differential expression was detected for various extracellular proteins, including proteases and their inhibitors, growth factors, cytokines, and extracellular matrix proteins. CXCL10, a cytokine found to be up-regulated in the TbetaRII knockout mammary fibroblasts, is shown to directly stimulate breast tumor cell proliferation and migration. Overall, this study revealed hundreds of specific extracellular protein changes modulated by deletion of TbetaRII in mammary fibroblasts, which may play important roles in the tumor microenvironment. These results warrant further investigation into the effects of inhibiting the TGF-beta signaling pathway in fibroblasts because systemic inhibition of TGF-beta signaling pathways is being considered as a potential cancer therapy.

Microdialysis combined with proteomics for protein identification in breast tumor microenvironment in vivo.

UNLABELLED: Tumor microenvironment constitutes a reservoir for proteins released from tumor cells and the host, which can contribute significantly to tumor growth and invasion. This study aims to apply a method of combining in vivo microdialysis and proteomics to identify proteins in mammary tumor interstitial fluids, a major component of tumor microenvironment. In vivo microdialysis was performed in polyomavirus middle T antigen (PyVmT) transgenic mouse mammary tumors and age-matched control wild-type mammary glands. Over four hundred proteins were identified from the microdialysis perfusates, using the Multidimensional Protein Identification Technology. Osteopontin (OPN) is one of the proteins overexpressed in breast tumor perfusates, as confirmed with immunoassays. OPN was also found to be present in tumor-associated stroma in both PyVmT and human breast tumors, using immunohistochemistry. Specifically, fibroblasts were further shown to express OPN at both mRNA and protein levels. In vitro assays showed that OPN can stimulate PyVmT breast carcinoma cell proliferation and migration. Finally, the expression of OPN was significantly higher in the peripheral blood of mice bearing breast tumors, compared to wild-type mice. Overall, microdialysis combined with proteomics is a unique technique for identifying proteins in a tumor microenvironment in vivo. Mammary fibroblasts can secrete OPN, and its overexpression in mammary tumor microenvironment may contribute significantly to mammary tumor progression. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12307-010-0046-3) contains supplementary material, which is available to authorized users.

Identification of early intestinal neoplasia protein biomarkers using laser capture microdissection and MALDI MS.

Obtaining protein profiles from a homogeneous cell population in tissues can significantly improve our capability in protein biomarker discovery. In this study, unique protein profiles from the top and bottom sections of mouse crypts and Apc(Min+/-) adenomas were obtained using laser capture microdissection (LCM) combined with MALDI MS. Statistically significant protein peaks with differential expression were selected, and a set of novel protein biomarkers were identified. Immunohistochemistry was performed to confirm the differentially expressed protein biomarkers found by LCM combined with MALDI MS. To validate the relevance of the findings in human colorectal cancer (CRC), S100A8 was further confirmed in human CRC using immunohistochemistry. In addition, S100A8 was found to have an increased expression at different human CRC stages (Duke's A-D) compared with controls at both protein (n = 168 cases) and RNA (n = 215 cases) levels. Overall LCM combined with MALDI MS is a promising method to identify intestinal protein biomarkers from minute amounts of tissue. The novel protein biomarkers identified from the top and bottom crypts will increase our knowledge of the specific protein changes taking place during cell migration from the crypt bottom to top. In addition, the identified cancer protein biomarkers will aid in the exploration of colorectal tumorigenesis mechanisms as well as in the advancement of molecularly based diagnosis of colorectal cancer.

A novel comprehensive wave-form MS data processing method.

MOTIVATION: Mass spectrometry (MS) can generate high-throughput protein profiles for biomedical research to discover biologically related protein patterns/biomarkers. The noisy functional MS data collected by current technologies, however, require consistent, sensitive and robust data-processing techniques for successful biomedical application. Therefore, it is important to detect features precisely for each spectrum, quantify them well and assign a unique label to features from the same protein/peptide across spectra. RESULTS: In this article, we propose a new comprehensive MS data preprocessing package, Wave-spec, which includes several novel algorithms. It can overcome several conventional difficulties. Wave-spec can be applied to multiple types of MS data generated with different MS technologies. Results from this new package were evaluated and compared to several existing approaches based on a MALDI-TOF MS dataset. AVAILABILITY: An example of MATLAB scripts used to implement the methods described in this article, along with Supplementary Figures, can be found at http://www.vicc.org/biostatistics/supp.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Differentiating proteomic biomarkers in breast cancer by laser capture microdissection and MALDI MS.

We assessed proteomic patterns in breast cancer using MALDI MS and laser capture microdissected cells. Protein and peptide expression in invasive mammary carcinoma versus normal mammary epithelium and estrogen-receptor positive versus estrogen-receptor negative tumors were compared. Biomarker candidates were identified by statistical analysis and classifiers were developed and validated in blinded test sets. Several of the m/ z features used in the classifiers were identified by LC-MS/MS and two were confirmed by immunohistochemistry.

MALDI-MS derived prognostic protein markers for resected non-small cell lung cancer.

Protein signals obtained directly from frozen lung tissue sections using MALDI-MS were used to predict nodal involvement and survival in resected non-small cell lung cancer (NSCLC). We have identified a list of these protein signals and further evaluated their prognostic values for NSCLC using immunohistochemistry (IHC). Kaplan-Meier analysis was used to assess the mortality risk associated with the prognostic protein IHC-staining intensities. The combined IHC scores of calmodulin, thymosin ß4, and thymosin ß10 were found to be correlated with NSCLC patient survival (p = 0.004). Furthermore, low cofilin-1 IHC-staining intensity was found to be correlated with a better outcome for patients with negative lymph node status (p = 0.006) while high cofilin-1 IHC-staining intensity was found to be correlated with a better outcome for patients with positive node status (p = 0.034). In conclusion, the prognostic protein signals selected using MALDI-MS can be identified and tested by IHC in formalin-fixed tissue samples. MALDI-MS-derived protein signals can be potentially translated to a conventional clinical setting to aid in the prognosis of patients with NSCLC at the molecular level.

Variability of in situ proteomic profiling and implications for study design in colorectal tumors.

Knowledge of intrinsic tumor heterogeneity is vital for understanding of tumor progression mechanisms as well as for providing efficient treatments. In situ proteomic profiling of tumors is a powerful technology with potential to enhance our understanding of tumor biology, but sources of variability due to patient and tumor heterogeneity are poorly understood and are the topic of this investigation. Clarification of variability within case and between cases is also important for designing future studies. Direct protein profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a sensitive and powerful technology for obtaining hundreds of protein expression peaks from a thin tissue section. By combining robotic microspotting and laser capture microdissection with MALDI MS, we acquired multiple spectra per case to evaluate inter- and intra-case variability in human colorectal tumor and murine cecal carcinoma. We detected 256 peaks from 164 samples of 111 patients, which consisted of 55 normal colorectal mucosal samples, 24 adenomas, 71 primary carcinomas, and 14 hepatic metastases. In addition, we detected 291 peptide/protein peaks from 34 orthotopically transplanted murine cecal carcinomas and 14 hepatic metastases. In human colorectal samples, we observed that proteomic profiling in adenomas was more homogeneous across patients than in normal mucosa specimens (p=0.0008), but primary carcinoma exhibited greater heterogeneity than normal mucosa and adenomas (both p<0.0001). Murine cecal carcinomas were homogeneous within and between carcinomas, while their hepatic metastases tended toward greater intra-tumor differences (p<0.0001). Inter- and intra-case variability was approximately equal for many protein peaks. Acquiring up to 5 subsamples per case could reduce the total number of cases required, but further reduction from additional subsampling was modest unless intra-case variability comprises a greater proportion of total variation (e.g. >70%). In summary, this study characterizes intra- and inter-case variability of high-throughput protein expression in colorectal tumors, and provides guidance for the sample numbers required for in situ proteomic studies.

Genomic and proteomic analysis of mammary tumors arising in transgenic mice.

Transforming growth factor-beta (TGF-beta) is the prototype of a large family of signaling molecules. TGF-beta signaling profoundly influences tumor development as demonstrated in several engineered mouse models. The present study was designed to identify differences by cDNA microarray and MALDI-TOF MS analyses in mammary carcinomas with and without TGF-beta signaling. The results demonstrate a significant potential for combination of profiling technologies to further understand the molecular mechanisms of breast cancer.

Proteomic patterns and prediction of glomerulosclerosis and its mechanisms.

Protein expression profiles linked to sclerosis in the 5/6 nephrectomy (Nx) rat model of focal segmental glomerulosclerosis were investigated. Sections of control glomeruli from normal baseline Nx tissue and nonsclerotic and sclerotic glomeruli from 12 wk after 5/6 Nx were isolated by laser capture microdissection. Protein profiles were acquired directly by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Classification accuracy was 99.2% for distinguishing normal versus sclerotic glomeruli and 96.7 and 97.8% for nonsclerotic versus normal and sclerotic glomeruli, respectively. The proteomic pattern of the nonsclerotic glomeruli was more similar to sclerotic than normal glomeruli (P < 0.0001). Thymosin beta4, a protein with relevant interactions with plasminogen activator inhibitor-1, angiogenesis, and wound healing, was identified as a key differentially expressed protein. Thymosin beta4 immunostaining was increased in sclerotic glomeruli, predominantly in endothelial cells. Downregulation of thymosin beta4 by RNAi in cultured glomerular endothelial cells decreased angiotensin II-induced plasminogen activator inhibitor-1 expression. In conclusion, proteomic patterns can accurately distinguish normal versus nonsclerotic versus sclerotic glomeruli. The closely related proteomic patterns of nonsclerotic and sclerotic glomeruli suggest early activation of prosclerotic mechanisms even in seemingly intact glomeruli. Thymosin beta4 is a marker of such early events and may even contribute to sclerosis.

Integrating histology and imaging mass spectrometry.

MALDI (matrix-assisted laser desorption/ionization) imaging mass spectrometry (IMS) is a new technology that generates molecular profiles and two-dimensional ion density maps of peptide and protein signals directly from the surface of thin tissue sections. This allows specific information to be obtained on the relative abundance and spatial distribution of proteins. One important aspect of this is the opportunity to correlate these specific ion images with histological features observed by optical microscopy. To facilitate this, we have developed protocols that allow MALDI mass spectrometry imaging and optical microscopy to be performed on the same section. Key components of these protocols involve the use of conductive glass slides as sample support for the tissue sections and MS-friendly tissue staining protocols. We show the effectiveness of these with protein standards and with several types of tissue sections. Although stain-specific intensity variations occur, the overall protein pattern and spectrum quality remain consistent between stained and control tissue samples. Furthermore, imaging mass spectrometry experiments performed on stained sections showed good image quality with minimal delocalization of proteins resulting from the staining protocols.

Molecular fingerprinting in human lung cancer.

The behavior and outcome of lung cancers are highly variable, and not only is the molecular basis of this variability unknown, but neither standard histopathology nor currently available molecular markers can predict these characteristics. Accordingly, the identification of novel biomarkers to differentiate tumor from normal cells and predict tumor behavior such as pathologic stage, response to chemotherapy, and site of relapse, is of great importance in clinical practice. None of the hundreds of single markers evaluated to date have demonstrated significant clinical utility, but by surveying thousands of genes at once with use of microarrays or proteomic technologies, it is now possible to read the molecular signature of an individual patient's tumor. When the signature is mathematically analyzed, new classes of cancer can be observed and insight can be gained into prediction, prognosis, and mechanism. Although some success has been achieved with genomic approaches, proteomics-based approaches allow examination of expressed proteins of a tissue or cell type, complement the genome initiatives, and are increasingly being used to address biomedical questions. This review aims to summarize the state of the art of gene and protein expression profiling for non-small-cell lung cancer

Profiling and imaging proteins in the mouse epididymis by imaging mass spectrometry.

Different aspects of matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) have been used as discovery tools to obtain global and time-correlated information on the local proteomic composition of the sexually mature mouse epididymis from both qualitative and semiquantitative points of view. Tissue sections and laser captured microdissected cells and secretory products were analyzed by MALDI-MS and from the recovered protein profiles, over 400 different proteins were monitored. Over 50 of these, some of which have been identified, displayed regionalized behavior from caput to cauda within the epididymis. Combining the information obtained from high-resolution imaging mass spectrometry and laser captured microdissection experiments, numerous proteins were localized within the epididymis at the cellular level. Furthermore, from the signal intensities observed in the different protein profiles organized in space, semiquantitative information for each protein was obtained.

Proteomic patterns of tumour subsets in non-small-cell lung cancer.

BACKGROUND: Proteomics-based approaches complement the genome initiatives and may be the next step in attempts to understand the biology of cancer. We used matrix-assisted laser desorption/ionisation mass spectrometry directly from 1-mm regions of single frozen tissue sections for profiling of protein expression from surgically resected tissues to classify lung tumours. METHODS: Proteomic spectra were obtained and aligned from 79 lung tumours and 14 normal lung tissues. We built a class-prediction model with the proteomic patterns in a training cohort of 42 lung tumours and eight normal lung samples, and assessed their statistical significance. We then applied this model to a blinded test cohort, including 37 lung tumours and six normal lung samples, to estimate the misclassification rate. FINDINGS: We obtained more than 1600 protein peaks from histologically selected 1 mm diameter regions of single frozen sections from each tissue. Class-prediction models based on differentially expressed peaks enabled us to perfectly classify lung cancer histologies, distinguish primary tumours from metastases to the lung from other sites, and classify nodal involvement with 85% accuracy in the training cohort. This model nearly perfectly classified samples in the independent blinded test cohort. We also obtained a proteomic pattern comprised of 15 distinct mass spectrometry peaks that distinguished between patients with resected non-small-cell lung cancer who had poor prognosis (median survival 6 months, n=25) and those who had good prognosis (median survival 33 months, n=41, p<0.0001). INTERPRETATION: Proteomic patterns obtained directly from small amounts of fresh frozen lung-tumour tissue could be used to accurately classify and predict histological groups as well as nodal involvement and survival in resected non-small-cell lung cancer.

Direct analysis of laser capture microdissected cells by MALDI mass spectrometry.

Laser capture microdissection (LCM) has become an important tool in biological research, permitting isolation of specific cell populations from frozen tissue samples containing a mixture of cell types. Cells obtained by LCM can be directly analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). We report here methodology for the preparation and analysis of LCM captured cells with MALDI MS, giving high sensitivity and mass resolution. Comparison of the spectra obtained from cell populations of interest can identify unique disease or function-related protein markers. Using this approach, mass spectra obtained from human breast tissue containing invasive mammary carcinoma and normal breast epithelium using LCM were compared. Over 40 peaks were identified that significantly differed in intensity between invasive mammary carcinoma and normal breast epithelium. In addition, mass spectra are presented that show protein patterns from mouse liver and mouse colon crypts. The reported tissue preparation procedure and subsequent analysis by MALDI MS provide a new methodology for protein discovery involving LCM captured cells.