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1.
Nat Commun ; 15(1): 3443, 2024 Apr 24.
Article in English | MEDLINE | ID: mdl-38658557

ABSTRACT

The hypothalamus contains a remarkable diversity of neurons that orchestrate behavioural and metabolic outputs in a highly plastic manner. Neuronal diversity is key to enabling hypothalamic functions and, according to the neuroscience dogma, it is predetermined during embryonic life. Here, by combining lineage tracing of hypothalamic pro-opiomelanocortin (Pomc) neurons with single-cell profiling approaches in adult male mice, we uncovered subpopulations of 'Ghost' neurons endowed with atypical molecular and functional identity. Compared to 'classical' Pomc neurons, Ghost neurons exhibit negligible Pomc expression and are 'invisible' to available neuroanatomical approaches and promoter-based reporter mice for studying Pomc biology. Ghost neuron numbers augment in diet-induced obese mice, independent of neurogenesis or cell death, but weight loss can reverse this shift. Our work challenges the notion of fixed, developmentally programmed neuronal identities in the mature hypothalamus and highlight the ability of specialised neurons to reversibly adapt their functional identity to adult-onset obesogenic stimuli.


Subject(s)
Hypothalamus , Neurons , Obesity , Pro-Opiomelanocortin , Single-Cell Analysis , Animals , Pro-Opiomelanocortin/metabolism , Pro-Opiomelanocortin/genetics , Neurons/metabolism , Obesity/metabolism , Obesity/pathology , Male , Mice , Hypothalamus/metabolism , Hypothalamus/cytology , Disease Models, Animal , Diet, High-Fat , Mice, Inbred C57BL , Mice, Transgenic , Neurogenesis , Mice, Obese
2.
Hepatology ; 74(3): 1595-1610, 2021 09.
Article in English | MEDLINE | ID: mdl-33754354

ABSTRACT

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.


Subject(s)
Adenoma, Liver Cell/metabolism , Liver Neoplasms/metabolism , Adenoma, Liver Cell/classification , Adenoma, Liver Cell/complications , Adenoma, Liver Cell/genetics , Adolescent , Adult , Carcinogenesis , Databases, Factual , Female , Hemorrhage/etiology , Humans , Liver Neoplasms/classification , Liver Neoplasms/complications , Liver Neoplasms/genetics , Machine Learning , Male , Middle Aged , Proteomics , Risk Assessment , Young Adult
3.
Sci Rep ; 7(1): 10949, 2017 09 08.
Article in English | MEDLINE | ID: mdl-28887457

ABSTRACT

Strong breakthrough pain is one of the most disabling symptoms of cancer since it affects up to 90% of cancer patients and is often refractory to treatments. Alteration in gene expression is a known mechanism of cancer pain in which microRNAs (miRNAs), a class of non-coding regulatory RNAs, play a crucial role. Here, in a mouse model of cancer pain, we show that miR-124 is down-regulated in the spinal cord, the first relay of the pain signal to the brain. Using in vitro and in vivo approaches, we demonstrate that miR-124 is an endogenous and specific inhibitor of synaptopodin (Synpo), a key protein for synaptic transmission. In addition, we demonstrate that Synpo is a key component of the nociceptive pathways. Interestingly, miR-124 was down-regulated in the spinal cord in cancer pain conditions, leading to an up-regulation of Synpo. Furthermore, intrathecal injections of miR-124 mimics in cancerous mice normalized Synpo expression and completely alleviated cancer pain in the early phase of the cancer. Finally, miR-124 was also down-regulated in the cerebrospinal fluid of cancer patients who developed pain, suggesting that miR-124 could be an efficient analgesic drug to treat cancer pain patients.


Subject(s)
Bone Neoplasms/physiopathology , Cancer Pain/metabolism , MicroRNAs/genetics , Nociception , Spinal Cord/metabolism , Animals , Bone Neoplasms/complications , Cancer Pain/etiology , Humans , Male , Mice , MicroRNAs/metabolism , Microfilament Proteins/genetics , Microfilament Proteins/metabolism
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