Overview of positron emission tomography in functional imaging of the lungs for diffuse lung diseases

Positron emission tomography (PET) is a quantitative molecular imaging modality increasingly used to study pulmonary disease processes and drug effects on those processes. The wide range of drugs and other entities that can be radiolabeled to study molecularly targeted processes is a major strength of PET, thus providing a noninvasive approach for obtaining molecular phenotyping information. The use of PET to monitor disease progression and treatment outcomes in DLD has been limited in clinical practice, with most of such applications occurring in the context of research investigations under clinical trials. Given the high costs and failure rates for lung drug development efforts, molecular imaging lung biomarkers are needed not only to aid these efforts but also to improve clinical characterization of these diseases beyond canonical anatomic classifications based on computed tomography. The purpose of this review article is to provide an overview of PET applications in characterizing lung disease, focusing on novel tracers that are in clinical development for DLD molecular phenotyping, and briefly address considerations for accurately quantifying lung PET signals.

Pathological Features and Molecular Phenotype of MMTV Like-Positive Feline Mammary Carcinomas

In the last few years MMTV-like nucleotide sequences were detected in some feline and canine mammary tumours. Due to the confirmed role of cats in the epidemiology of the MMTV-like virus, the aim of this study was to investigate the main pathological features of positive feline mammary carcinomas (FMCs). Twenty-four FMCs were collected at the University of Bologna, submitted to laser microdissection and analysed by nested fluorescence-PCR using primer sets specific for MMTV env sequence. For immunohistochemistry, an antibody against MMTV protein 14 (p14) was used. MMTV-like sequences were detected in three out of 24 FMCs (12.5%), one tubular carcinoma, one tubulopapillary carcinoma and one ductal carcinoma. All PCR-positive tumours were also positive for p14. Multiple nucleotide alignment has shown similarity to MMTV ranging from 98% to 100%. All the 102 examined FMCs were submitted to immunohistochemistry for molecular phenotyping. Of the nine MMTV-like positive FMCs, six were basal-like and three luminal-like. Our results demonstrate MMTV-like sequences and protein in FMCs of different geographic areas. Molecular phenotyping could contribute to understand the possible role of MMTV-like virus in FMC tumor biology.

PTGDR2 Expression in Peripheral Blood as a Potential Biomarker in Adult Patients with Asthma

Background: Precision medicine is a promising strategy to identify biomarkers, stratify asthmatic patients according to different endotypes, and match them with the appropriate therapy. This proof-of-concept study aimed to investigate whether gene expression in peripheral blood could provide a valuable noninvasive approach for the molecular phenotyping of asthma. Methods: We performed whole-transcriptome RNA sequencing on peripheral blood of 30 non-atopic non-asthmatic controls and 30 asthmatic patients. A quantitative PCR (qPCR) validation study of PTGDR2 that encodes for CRTH2 receptor, expressed in cells involved in T2 inflammation, was developed in a cohort of 361 independent subjects: 94 non-asthmatic non-atopic controls, 187 asthmatic patients [including 82 with chronic rhinosinusitis with nasal polyposis (CRSwNP) and 24 with aspirin-exacerbated respiratory disease (AERD)], 52 with allergic rhinitis, and 28 with CRSwNP without asthma. Results: PTGDR2 was one of the most differentially overexpressed genes in asthmatic patients’ peripheral blood (p-value 2.64 × 106). These results were confirmed by qPCR in the validation study, where PTGDR2 transcripts were significantly upregulated in asthmatic patients (p < 0.001). This upregulation was mainly detected in some subgroups such as allergic asthma, asthma with CRSwNP, AERD, eosinophilic asthma, and severe persistent asthma. PTGDR2 expression was detected in different blood cell types, and its correlation with eosinophil counts showed differences in some groups of asthmatic patients. Conclusions: We found that PTGDR2 expression levels could identify asthma patients, introduce a minimally invasive biomarker for adult asthma molecular phenotyping, and add additional information to blood eosinophils. Although further studies are required, analyzing PTGDR2 expression levels in peripheral blood of asthmatics might assist in selecting patients for treatment with specific antagonists.

Applying Molecular Phenotyping Tools to Explore Sugarcane Carbon Potential

Sugarcane (Saccharum spp.), a C4 grass, has a peculiar feature: it accumulates, gradient-wise, large amounts of carbon (C) as sucrose in its culms through a complex pathway. Apart from being a sustainable crop concerning C efficiency and bioenergetic yield per hectare, sugarcane is used as feedstock for producing ethanol, sugar, high-value compounds, and products (e.g., polymers and succinate), and bioelectricity, earning the title of the world’s leading biomass crop. Commercial cultivars, hybrids bearing high levels of polyploidy, and aneuploidy, are selected from a large number of crosses among suitable parental genotypes followed by the cloning of superior individuals among the progeny. Traditionally, these classical breeding strategies have been favoring the selection of cultivars with high sucrose content and resistance to environmental stresses. A current paradigm change in sugarcane breeding programs aims to alter the balance of C partitioning as a means to provide more plasticity in the sustainable use of this biomass for metabolic engineering and green chemistry. The recently available sugarcane genetic assemblies powered by data science provide exciting perspectives to increase biomass, as the current sugarcane yield is roughly 20% of its predicted potential. Nowadays, several molecular phenotyping tools can be applied to meet the predicted sugarcane C potential, mainly targeting two competing pathways: sucrose production/storage and biomass accumulation. Here we discuss how molecular phenotyping can be a powerful tool to assist breeding programs and which strategies could be adopted depending on the desired final products. We also tackle the advances in genetic markers and mapping as well as how functional genomics and genetic transformation might be able to improve yield and saccharification rates. Finally, we review how “omics” advances are promising to speed up plant breeding and reach the unexplored potential of sugarcane in terms of sucrose and biomass production.

Breath biopsy of breast cancer using sensor array signals and machine learning analysis

Breast cancer causes metabolic alteration, and volatile metabolites in the breath of patients may be used to diagnose breast cancer. The objective of this study was to develop a new breath test for breast cancer by analyzing volatile metabolites in the exhaled breath. We collected alveolar air from breast cancer patients and non-cancer controls and analyzed the volatile metabolites with an electronic nose composed of 32 carbon nanotubes sensors. We used machine learning techniques to build prediction models for breast cancer and its molecular phenotyping. Between July 2016 and June 2018, we enrolled a total of 899 subjects. Using the random forest model, the prediction accuracy of breast cancer in the test set was 91% (95% CI: 0.85–0.95), sensitivity was 86%, specificity was 97%, positive predictive value was 97%, negative predictive value was 97%, the area under the receiver operating curve was 0.99 (95% CI: 0.99–1.00), and the kappa value was 0.83. The leave-one-out cross-validated discrimination accuracy and reliability of molecular phenotyping of breast cancer were 88.5 ± 12.1% and 0.77 ± 0.23, respectively. Breath tests with electronic noses can be applied intraoperatively to discriminate breast cancer and molecular subtype and support the medical staff to choose the best therapeutic decision.

Promising potential of high-throughput molecular phenotyping of freshwater fishes for environmental assessment

The recent democratisation of high-throughput molecular phenotyping allows the rapid expansion of promising untargeted multi-dimensional approaches (e.g. epigenomics, transcriptomics, proteomics, metabolomics, as well as microbiome metabarcoding), that now represent innovative perspectives for environmental assessments. Indeed, when developed for ecologically relevant species, these emerging omics analyses may present valuable alternatives for the development of novel generations of ecological indicators, that in turn could provide early warnings of eco(toxico)logical impairments. This pilot study investigates the bio-indicative potential of different multi-metric tools based on different high-throughput molecular phenotyping approaches (i.e. metabarcoding of the intestine microbiome, and liver metabolomics by nuclear magnetic resonance (NMR) and liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) on two sentinel fish species (Perca fluviatilis and Lepomis gibbosus) from a set of eight water bodies of the peri-urban area of Paris (France). We show that the LC-MS metabolome dataset allows remarkably clear separation of individuals according to the species but also according to their respective sampling lakes. Interestingly, the similar variations of Perca and Lepomis metabolomes occur locally indicating that local environmental constraints drive the observed metabolome variations beyond their obvious genetic differences. Thus, the development of such reliable molecular phenotyping for environmental monitoring constitutes a promising and innovative bio-indicative tool for environmental assessment.