Stellar Evolutionary Effects on the Abundances of PAH and SN-Condensed Dust in Galaxies

Spectral and photometric observations of nearby galaxies show a correlation between the strength of their mid-IR aromatic features, attributed to PAH molecules, and their metal abundance, leading to a deficiency of these features in low-metallicity galaxies. In this paper, we suggest that the observed correlation represents a trend of PAH abundance with galactic age, reflecting the delayed injection of carbon dust into the ISM by AGB stars in the final post-AGB phase of their evolution. AGB stars are the primary sources of PAHs and carbon dust in galaxies, and recycle their ejecta back to the interstellar medium only after a few hundred million years of evolution on the main sequence. In contrast, more massive stars that explode as Type II supernovae inject their metals and dust almost instantaneously after their formation. We first determined the PAH abundance in galaxies by constructing detailed models of UV-to-radio SED of galaxies that estimate the contribution of dust in PAH-free HII regions, and PAHs and dust from photodissociation regions, to the IR emission. All model components: the galaxies' stellar content, properties of their HII regions, and their ionizing and non-ionizing radiation fields and dust abundances, are constrained by their observed multiwavelength spectrum. After determining the PAH and dust abundances in 35 nearby galaxies using our SED model, we use a chemical evolution model to show that the delayed injection of carbon dust by AGB stars provides a natural explanation to the dependence of the PAH content in galaxies with metallicity. We also show that larger dust particles giving rise to the far-IR emission follow a distinct evolutionary trend closely related to the injection of dust by massive stars into the ISM.Comment: ApJ, 69 pages, 46 figures, Accepte

Proteomic Profiling of Hepatocellular Adenomas Paves the Way to Diagnostic and Prognostic Approaches

Background and Aims : Through an exploratory proteomic approach based on typical hepatocellular adenomas (HCAs), we previously identified a diagnostic biomarker for a distinctive subtype of HCA with high risk of bleeding, already validated on a multicenter cohort. We hypothesized that the whole protein expression deregulation profile could deliver much more informative data for tumor characterization. Therefore, we pursued our analysis with the characterization of HCA proteomic profiles, evaluating their correspondence with the established genotype/phenotype classification and assessing whether they could provide added diagnosis and prognosis values. Approach and Results : From a collection of 260 cases, we selected 52 typical cases of all different subgroups on which we built a reference HCA proteomics database. Combining laser microdissection and mass-spectrometry–based proteomic analysis, we compared the relative protein abundances between tumoral (T) and nontumoral (NT) liver tissues from each patient and we defined a specific proteomic profile of each of the HCA subgroups. Next, we built a matching algorithm comparing the proteomic profile extracted from a patient with our reference HCA database. Proteomic profiles allowed HCA classification and made diagnosis possible, even for complex cases with immunohistological or genomic analysis that did not lead to a formal conclusion. Despite a well-established pathomolecular classification, clinical practices have not substantially changed and the HCA management link to the assessment of the malignant transformation risk remains delicate for many surgeons. That is why we also identified and validated a proteomic profile that would directly evaluate malignant transformation risk regardless of HCA subtype. Conclusions : This work proposes a proteomic-based machine learning tool, operational on fixed biopsies, that can improve diagnosis and prognosis and therefore patient management for HCAs.European Funds for Regional Development (Feder), N° Presage 3207

ASS1 Overexpression:A Hallmark of Sonic Hedgehog Hepatocellular Adenomas; Recommendations for Clinical Practice

Until recently, 10% of hepatocellular adenomas (HCAs) remained unclassified (UHCA). Among the UHCAs, the sonic hedgehog HCA (shHCA) was defined by focal deletions that fuse the promoter of Inhibin beta E chain with GLI1. Prostaglandin D2 synthase was proposed as immunomarker. In parallel, our previous work using proteomic analysis showed that most UHCAs constitute a homogeneous subtype associated with overexpression of argininosuccinate synthase (ASS1). To clarify the use of ASS1 in the HCA classification and avoid misinterpretations of the immunohistochemical staining, the aims of this work were to study (1) the link between shHCA and ASS1 overexpression and (2) the clinical relevance of ASS1 overexpression for diagnosis. Molecular, proteomic, and immunohistochemical analyses were performed in UHCA cases of the Bordeaux series. The clinico-pathological features, including ASS1 immunohistochemical labeling, were analyzed on a large international series of 67 cases. ASS1 overexpression and the shHCA subgroup were superimposed in 15 cases studied by molecular analysis, establishing ASS1 overexpression as a hallmark of shHCA. Moreover, the ASS1 immunomarker was better than prostaglandin D2 synthase and only found positive in 7 of 22 shHCAs. Of the 67 UHCA cases, 58 (85.3%) overexpressed ASS1, four cases were ASS1 negative, and in five cases ASS1 was noncontributory. Proteomic analysis performed in the case of doubtful interpretation of ASS1 overexpression, especially on biopsies, can be a support to interpret such cases. ASS1 overexpression is a specific hallmark of shHCA known to be at high risk of bleeding. Therefore, ASS1 is an additional tool for HCA classification and clinical diagnosis

ESM-1 expression in stromal cells is predictive of recurrence after radiofrequency ablation in early hepatocellular carcinoma

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