Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer.

PURPOSE: We sought to exploit the heterogeneity afforded by patient-derived tumor xenografts (PDX) to first, optimize and identify robust radiomic features to predict response to therapy in subtype-matched triple negative breast cancer (TNBC) PDX, and second, to implement PDX-optimized image features in a TNBC co-clinical study to predict response to therapy using machine learning (ML) algorithms. METHODS: TNBC patients and subtype-matched PDX were recruited into a co-clinical FDG-PET imaging trial to predict response to therapy. One hundred thirty-one imaging features were extracted from PDX and human-segmented tumors. Robust image features were identified based on reproducibility, cross-correlation, and volume independence. A rank importance of predictors using ReliefF was used to identify predictive radiomic features in the preclinical PDX trial in conjunction with ML algorithms: classification and regression tree (CART), Naïve Bayes (NB), and support vector machines (SVM). The top four PDX-optimized image features, defined as radiomic signatures (RadSig), from each task were then used to predict or assess response to therapy. Performance of RadSig in predicting/assessing response was compared to SUVmean, SUVmax, and lean body mass-normalized SULpeak measures. RESULTS: Sixty-four out of 131 preclinical imaging features were identified as robust. NB-RadSig performed highest in predicting and assessing response to therapy in the preclinical PDX trial. In the clinical study, the performance of SVM-RadSig and NB-RadSig to predict and assess response was practically identical and superior to SUVmean, SUVmax, and SULpeak measures. CONCLUSIONS: We optimized robust FDG-PET radiomic signatures (RadSig) to predict and assess response to therapy in the context of a co-clinical imaging trial.

Optimal co-clinical radiomics: Sensitivity of radiomic features to tumour volume, image noise and resolution in co-clinical T1-weighted and T2-weighted magnetic resonance imaging.

BACKGROUND: Radiomics analyses has been proposed to interrogate the biology of tumour as well as to predict/assess response to therapy in vivo. The objective of this work was to assess the sensitivity of radiomics features to noise, resolution, and tumour volume in the context of a co-clinical trial. METHODS: Triple negative breast cancer (TNBC) patients were recruited into an ongoing co-clinical imaging trial. Sub-typed matched TNBC patient-derived tumour xenografts (PDX) were generated to investigate optimal co-clinical MR radiomic features. The MR imaging protocol included T1-weighed and T2-weighted imaging. To test the sensitivity of radiomics to resolution, PDX were imaged at three different resolutions. Multiple sets of images with varying signal-to-noise ratio (SNR) were generated, and an image independent patch-based method was implemented to measure the noise levels. Forty-eight radiomic features were extracted from manually segmented 2D and 3D segmented tumours and normal tissues of T1- and T2- weighted co-clinical MR images. FINDINGS: Sixteen radiomics features were identified as volume dependent and corrected for volume-dependency following normalization. Features from grey-level run-length matrix (GLRLM), grey-level size zone matrix (GLSZM) were identified as most sensitive to noise. Radiomic features Kurtosis and Run-length variance (RLV) from GLSZM were most sensitive to changes in resolution in both T1w and T2w MRI. In general, 3D radiomic features were more robust compared to 2D (single slice) measures, although the former exhibited higher variability between subjects. INTERPRETATION: Tumour volume, noise characteristics, and image resolution significantly impact radiomic analysis in co-clinical studies.

Sexual dimorphism in myocardial acylcarnitine and triglyceride metabolism.

BACKGROUND: Cardiovascular disease is the leading cause of death among diabetic patients. Importantly, recent data highlight the apparent sexual dimorphism in the pathogenesis of cardiovascular disease in diabetics with respect to both frequency- and age-related risk factors. The disposition to cardiovascular disease among diabetic patients has been attributed, at least in part, to excess lipid supply to the heart culminating in lipotoxicity of the heart and downstream derangements. A confounding factor in obese animal models of diabetes is that increased peripheral lipid availability to the heart can induce cardio-metabolic remodeling independent of the underlying pathophysiology of diabetes, thus masking the diabetic phenotype. To that end, we hypothesized that the use of non-obese diabetic (NOD) animal models will reveal metabolic signatures of diabetes in a sex-specific manner. METHODS: To test this hypothesis, male and female NOD Goto-Kakizaki (GK) rats were used to assess the expression profile of 84 genes involved in lipid metabolism. In parallel, targeted lipidomics analysis was performed to characterize sex differences in homeostasis of non-esterified fatty acids (NEFA), acylcarnitines (AC), and triglycerides (TG). RESULTS: Our analysis revealed significant sex differences in the expression of a broad range of genes involved in transport, activation, and utilization of lipids. Furthermore, NOD male rats exhibited enhanced oxidative metabolism and accumulation of TG, whereas female NOD rats exhibited reduced TG content coupled with accumulation of AC species. Multi-dimensional statistical analysis identified saturated AC16:0, AC18:0, and AC20:0 as dominant metabolites in mediating sex differences in AC metabolism. Confocal microscopy of rat cardiomyocytes exposed to AC14:0, AC16:0, and AC18:0 confirmed induction of ROS with AC18:0 being more potent followed by AC14:0. CONCLUSION: Overall, we demonstrate sex differences in myocardial AC and TG metabolism with implications for therapy and diagnosis of diabetic cardiovascular disease.

A PET-compatible tissue bioreactor for research, discovery, and validation of imaging biomarkers and radiopharmaceuticals: system design and proof-of-concept studies.

UNLABELLED: Research and discovery of novel radiopharmaceuticals and targets thereof generally involves initial studies in cell cultures, followed by animal studies, both of which present several inherent limitations. The objective of this work was to develop a tissue bioreactor (TBR) enabling modulation of the microenvironment and to integrate the TBR with a small-animal PET scanner to facilitate imaging biomarker research and discovery and validation of radiopharmaceuticals. METHODS: The TBR chamber is a custom-blown, water-jacketed, glass vessel enclosed in a circulating perfusion bath powered by a peristaltic pump, which is integrated within the field of view of the PET scanner. The chamber is in series with a gas exchanger and a vessel for degassing the system during filling. Dissolved oxygen/temperature probes and septa for injection or sampling are located at the inlet and outlet of the cell chamber. A pH probe is located at the chamber outlet. Effluent is collected in the fraction collector as mixed-cup samples. In addition, both medium and tissue chamber can be sampled to investigate tissue and secretory products through multiscale analysis. As a proof of concept, we studied the effects of lipids on glucose uptake using HepG2 cells. To that end, we varied the nutrient substrate environment over a period of approximately 27 d, before and after the addition of lipids, and studied the effects of pioglitazone, a peroxisome proliferator-activated receptor γ agonist, on lipid and glucose uptake. In parallel, the TBR was imaged by PET in conjunction with (11)C-palmitate in the presence and absence of lipids to characterize (11)C-palmitate uptake. RESULTS: The O2 consumption, glucose consumption, lactate production, and free fatty acid consumption and production rates were consistent in demonstrating the effects of lipids on glucose uptake. Pioglitazone exhibited improved glucose uptake within 3 d of treatment. Semiquantitative analysis suggested that lipids induced greater (11)C-palmitate uptake. CONCLUSION: The integrated TBR offers a platform to monitor and modulate the tissue microenvironment, thus facilitating tissue-specific imaging and therapeutic biomarkers of disease, identification of molecular diagnostic markers, and validation of radiopharmaceuticals in both rodent and human cell lines.

Artificial tissue bioreactor (ATB) for biological and imaging applications.

Three-dimensional (3D) culture systems are increasingly applied to study tissue biology. In this work, we report on the development of an artificial tissue bioreactor (ATB) designed to simulate the 3D structure and microenvironment of tissues in vivo, with multiple avenues of sampling, including the tissue chamber, for downstream analysis. Additionally, the ATB is integrated with the microPET Focus F220 for in-vivo imaging applications. As a proof-of-concept, we characterized the effects of lipids on glucose utilization using HepG2 cells. ATB studies were performed pre- and post- therapeutic intervention with the PPAR-γ agonist pioglitazone. In parallel, Glucose Tolerance Test (GTT) is performed on media samples to assess glucose uptake by cells as a measures of insulin signaling sensitivity. Fatty acid uptake in the ATB cell chamber is measured using [(11)C]Palmitate with microPET imaging. Overall, the ATB will facilitate the use of existing and novel radiopharmaceuticals in discovery of validating and translating insights derived from ATB studies to pre-clinical animal studies, to clinical evaluation.

The number of genes changing expression after chronic exposure to code division multiple access or frequency DMA radiofrequency radiation does not exceed the false-positive rate.

Experiments with cultured C3H 10T 1/2 cells were performed to determine if exposure to cell phone radiofrequency (RF) radiations induce changes in gene expression. Following a 24 h exposure of 5 W/kg specific adsorption rate, RNA was extracted from the exposed and sham control cells for microarray analysis on Affymetrix U74Av2 Genechips. Cells exposed to 0.68 Gy of X-rays with a 4-h recovery were used as positive controls. The number of gene expression changes induced by RF radiation was not greater than the number of false positives expected based on a sham versus sham comparison. In contrast, the X-irradiated samples showed higher numbers of probe sets changing expression level than in the sham versus sham comparison.

Expression of the proto-oncogene Fos after exposure to radiofrequency radiation relevant to wireless communications.

In this study the expression levels of the proto-oncogene Fos were measured after exposure to radiofrequency (RF) radiation at two relatively high specific absorption rates (SARs) of 5 and 10 W/kg for three types of modulated signals: 847.74 MHz code division multiple access (CDMA), 835.62 MHz frequency division multiple access (FDMA), and 836.55 MHz time division multiple access (TDMA). This work was undertaken to confirm a previous report by Goswami et al. (Radiat. Res. 151, 300-309, 1999) that CDMA and FDMA radiation caused small but statistically significant increases in Fos levels as cells entered plateau phase during exposure. No effects on Myc or Jun levels were observed in that study. Therefore, in the present study, analyses were restricted to Fos expression during the transition from exponential growth to plateau phase. Fos expression was measured using the real-time polymerase chain reaction (RT-PCR) technique. Serum-stimulated C3H 10T(1/2) cells were used as a positive control for Fos expression. Possible influences of final cell number or pH variability on Fos expression were evaluated. Expression of Fos mRNA in C3H 10T(1/2) cells was not significantly different from that found after sham exposure at either SAR level for any signal modulation. Therefore, the results of Goswami et al. could not be confirmed.