Analysis of aggregated cell-cell statistical distances within pathways unveils therapeutic-resistance mechanisms in circulating tumor cells.

MOTIVATION: As 'omics' biotechnologies accelerate the capability to contrast a myriad of molecular measurements from a single cell, they also exacerbate current analytical limitations for detecting meaningful single-cell dysregulations. Moreover, mRNA expression alone lacks functional interpretation, limiting opportunities for translation of single-cell transcriptomic insights to precision medicine. Lastly, most single-cell RNA-sequencing analytic approaches are not designed to investigate small populations of cells such as circulating tumor cells shed from solid tumors and isolated from patient blood samples. RESULTS: In response to these characteristics and limitations in current single-cell RNA-sequencing methodology, we introduce an analytic framework that models transcriptome dynamics through the analysis of aggregated cell-cell statistical distances within biomolecular pathways. Cell-cell statistical distances are calculated from pathway mRNA fold changes between two cells. Within an elaborate case study of circulating tumor cells derived from prostate cancer patients, we develop analytic methods of aggregated distances to identify five differentially expressed pathways associated to therapeutic resistance. Our aggregation analyses perform comparably with Gene Set Enrichment Analysis and better than differentially expressed genes followed by gene set enrichment. However, these methods were not designed to inform on differential pathway expression for a single cell. As such, our framework culminates with the novel aggregation method, cell-centric statistics (CCS). CCS quantifies the effect size and significance of differentially expressed pathways for a single cell of interest. Improved rose plots of differentially expressed pathways in each cell highlight the utility of CCS for therapeutic decision-making. AVAILABILITY AND IMPLEMENTATION: http://www.lussierlab.org/publications/CCS/ CONTACT: yves@email.arizona.edu or piegorsch@math.arizona.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis of global and absorption, distribution, metabolism, and elimination gene expression in the progressive stages of human nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is characterized by a series of pathological changes that range from simple fatty liver to nonalcoholic steatohepatitis (NASH). The objective of this study is to describe changes in global gene expression associated with the progression of human NAFLD. This study is focused on the expression levels of genes responsible for the absorption, distribution, metabolism, and elimination (ADME) of drugs. Differential gene expression between three clinically defined pathological groups-normal, steatosis, and NASH-was analyzed. Genome-wide mRNA levels in samples of human liver tissue were assayed with Affymetrix GeneChip Human 1.0ST arrays. A total of 11,633 genes exhibited altered expression out of 33,252 genes at a 5% false discovery rate. Most gene expression changes occurred in the progression from steatosis to NASH. Principal component analysis revealed that hepatic disease status was the major determinant of differential ADME gene expression rather than age or sex of sample donors. Among the 515 drug transporters and 258 drug-metabolizing enzymes (DMEs) examined, uptake transporters but not efflux transporters or DMEs were significantly over-represented in the number of genes down-regulated. These results suggest that uptake transporter genes are coordinately targeted for down-regulation at the global level during the pathological development of NASH and that these patients may have decreased drug uptake capacity. This coordinated regulation of uptake transporter genes is indicative of a hepatoprotective mechanism acting to prevent accumulation of toxic intermediates in disease-compromised hepatocytes.

Prognostic and pathogenetic value of combining clinical and biochemical indices in patients with acute lung injury.

BACKGROUND: No single clinical or biologic marker reliably predicts clinical outcomes in acute lung injury (ALI)/ARDS. We hypothesized that a combination of biologic and clinical markers would be superior to either biomarkers or clinical factors alone in predicting ALI/ARDS mortality and would provide insight into the pathogenesis of clinical ALI/ARDS. METHODS: Eight biologic markers that reflect endothelial and epithelial injury, inflammation, and coagulation (von Willebrand factor antigen, surfactant protein D [SP-D]), tumor necrosis factor receptor-1, interleukin [IL]-6, IL-8, intercellular adhesion molecule-1, protein C, plasminogen activator inhibitor-1) were measured in baseline plasma from 549 patients in the ARDSNet trial of low vs high positive end-expiratory pressure. Mortality was modeled with multivariable logistic regression. Predictors were selected using backward elimination. Comparisons between candidate models were based on the receiver operating characteristics (ROC) and tests of integrated discrimination improvement. RESULTS: Clinical predictors (Acute Physiology And Chronic Health Evaluation III [APACHE III], organ failures, age, underlying cause, alveolar-arterial oxygen gradient, plateau pressure) predicted mortality with an area under the ROC curve (AUC) of 0.82; a combination of eight biomarkers and the clinical predictors had an AUC of 0.85. The best performing biomarkers were the neutrophil chemotactic factor, IL-8, and SP-D, a product of alveolar type 2 cells, supporting the concept that acute inflammation and alveolar epithelial injury are important pathogenetic pathways in human ALI/ARDS. CONCLUSIONS: A combination of biomarkers and clinical predictors is superior to clinical predictors or biomarkers alone for predicting mortality in ALI/ARDS and may be useful for stratifying patients in clinical trials. From a pathogenesis perspective, the degree of acute inflammation and alveolar epithelial injury are highly associated with the outcome of human ALI/ARDS.

In vivo nonmelanoma skin cancer diagnosis using Raman microspectroscopy.

BACKGROUND AND OBJECTIVES: Nonmelanoma skin cancers, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are the most common skin cancers, presenting nearly as many cases as all other cancers combined. The current gold-standard for clinical diagnosis of these lesions is histopathologic examination, an invasive, time-consuming procedure. There is thus considerable interest in developing a real-time, automated, noninvasive tool for nonmelanoma skin cancer diagnosis. In this study, we explored the capability of Raman microspectroscopy to provide differential diagnosis of BCC, SCC, inflamed scar tissue, and normal tissue in vivo. STUDY DESIGN: Based on the results of previous in vitro studies, we developed a portable confocal Raman system with a handheld probe for clinical study. Using this portable system, we measured Raman spectra of 21 suspected nonmelanoma skin cancers in 19 patients with matched normal skin spectra. These spectra were input into nonlinear diagnostic algorithms to predict pathological designation. RESULTS: All of the BCC (9/9), SCC (4/4), and inflamed scar tissues (8/8) were correctly predicted by the diagnostic algorithm, and 19 out of 21 normal tissues were correctly classified. This translates into a 100% (21/21) sensitivity and 91% (19/21) specificity for abnormality, with a 95% (40/42) overall classification accuracy. CONCLUSIONS: These findings reveal Raman microspectroscopy to be a viable tool for real-time diagnosis and guidance of nonmelanoma skin cancer resection.

Proteomics of transformed lymphocytes from a family with familial pulmonary arterial hypertension.

RATIONALE: Not all family members with BMPR2 mutations develop pulmonary arterial hypertension (PAH), implying that additional modifier genes or proteins are necessary for full expression of the disease. OBJECTIVES: To determine whether protein expression is altered in patients with familial PAH (FPAH) compared with obligate carriers and nondiseased control subjects. METHODS: Protein extracts from transformed blood lymphocytes from four patients with FPAH, three obligate carriers, and three married-in control subjects from one family with a known BMPR2 mutation (exon 3 T354G) were labeled with either Cy3 or Cy5. Cy3/5 pairs were separated by standard two-dimensional differential gel electrophoresis using a Cy2-labeled internal standard of all patient samples. Log volume ratios were analyzed using a linear mixed-effects model. Proteins were identified by matrix-assisted laser desorption ionization, time-of-flight mass spectrometry (MALDI-TOF MS) and tandem TOF/TOF MS/MS. MEASUREMENTS AND MAIN RESULTS: Hierarchical clustering, heat-map, and principal components analysis revealed marked changes in protein expression in patients with FPAH when compared with obligate carriers. Significant changes were apparent in expression of 16 proteins (P < 0.05) when affected patients were compared with obligates: nine showed a significant increase and seven showed a significant reduction. CONCLUSIONS: A series of novel proteins with altered expression were found that could distinguish affected patients from obligate carriers and married-in controls in a single family with a BMPR2 mutation. These differences provide new information highlighting proteins that may be involved in the mechanism(s) that differentiates those individuals with a BMPR2 mutation who develop FPAH from those who do not.

Repeatability of a reference region model for analysis of murine DCE-MRI data at 7T.

PURPOSE: To test the repeatability of a reference region (RR) model for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) in a mouse model of cancer at high field. MATERIALS AND METHODS: Seven mice were injected with 10(6) 4T1 mammary carcinoma cells and imaged eight to 10 days later on a Varian 7.0T scanner. Two DCE-MRI studies were performed for each mouse (separated by 2.5 hours). The RR model was used to analyze the data, and returned estimates on the perfusion-permeability index (Ktrans) for the RR and the tissue of interest (TOI), as well as the extravascular extracellular volume fraction (ve) for the TOI. RESULTS: When the first injection was compared with the second injection, all parameters tested were highly correlated (r2=0.90, 0.62, 0.82 for the RR Ktrans, TOI Ktrans, and TOI ve, respectively, with P<0.001 for all). To observe a statistically significant change (at the 5% level) in a treatment study with seven animals in each group, log10 changes of 0.084 and 0.077 in the tumor Ktrans and ve, respectively, are required. CONCLUSION: If a reliable arterial input function (AIF) is unavailable, the RR model is a reasonable alternative to measuring MRI contrast-agent (CA) kinetics in mouse models of cancer at high field.

Urine PGE-M: A metabolite of prostaglandin E2 as a potential biomarker of advanced colorectal neoplasia.

BACKGROUND & AIMS: The enzyme cyclooxygenase-2 is expressed in a majority of colorectal carcinomas (CRCs) and is important in prostaglandin production. We have developed an accurate method to measure the urinary metabolite of prostaglandin E(2) (PGE-M) using recently developed mass spectrometric techniques. The purpose of this pre-validation study was to determine if urinary PGE-M levels can be used as a biomarker to discriminate between healthy patients and those with colorectal disease. METHODS: Urine PGE-M was assessed in a total of 228 patients with CRC, colonic adenomatous polyps, Crohn's disease, and in subjects with no endoscopically detectable disease. Thirteen rectal carcinoma patients were treated with celecoxib and urinary PGE-M was measured before and after treatment. RESULTS: Urine PGE-M levels were increased among healthy men compared with healthy women (median, 8.59 [interquartile range (IQR), 5.67-22.3] vs 4.25 [IQR, 2.35-6.03], P = .0027). Urine PGE-M levels among patients with Crohn's disease (median, 19.85 [IQR, 6.89-90.2]), CRC (median, 14.65 [IQR, 5.94-92.1]), or large adenomas greater than 1 cm in size (median, 18.85 [IQR, 11.9-25.6]) were significantly increased when compared with patients who had either small polyps less than 1 cm in size (median, 9.69 [IQR, 6.41-22.2]), or no polyps (median, 7.05 [IQR, 2.35-24.7]) (P = .0001). PGE-M levels decreased significantly after celecoxib treatment in patients with rectal cancer (median, 21.7 [IQR, 16.2-29.9] vs 9.14 [IQR, 7.14-13.2], P = .009). CONCLUSIONS: The increase in urinary PGE-M in patients with colorectal cancers and large adenomas suggests that urinary PGE-M is a potentially useful biomarker for the detection of advanced colorectal neoplasia.