RESUMO
BACKGROUND: Cachexia-associated body composition alterations and tumor metabolic activity are both associated with survival of cancer patients. Recently, subcutaneous adipose tissue properties have emerged as particularly prognostic body composition features. We hypothesized that tumors with higher metabolic activity instigate cachexia related peripheral metabolic alterations, and investigated whether tumor metabolic activity is associated with body composition and survival in patients with non-small-cell lung cancer (NSCLC), focusing on subcutaneous adipose tissue. METHODS: A retrospective analysis was performed on a cohort of 173 patients with NSCLC. 18F-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) scans obtained before treatment were used to analyze tumor metabolic activity (standardized uptake value (SUV) and SUV normalized by lean body mass (SUL)) as well as body composition variables (subcutaneous and visceral adipose tissue radiodensity (SAT/VAT radiodensity) and area; skeletal muscle radiodensity (SM radiodensity) and area). Subjects were divided into groups with high or low SAT radiodensity based on Youden Index of Receiver Operator Characteristics (ROC). Associations between tumor metabolic activity, body composition variables, and survival were analyzed by Mann-Whitney tests, Cox regression, and Kaplan-Meier analysis. RESULTS: The overall prevalence of high SAT radiodensity was 50.9% (88/173). Patients with high SAT radiodensity had shorter survival compared with patients with low SAT radiodensity (mean: 45.3 vs. 50.5 months, p = 0.026). High SAT radiodensity was independently associated with shorter overall survival (multivariate Cox regression HR = 1.061, 95% CI: 1.022-1.101, p = 0.002). SAT radiodensity also correlated with tumor metabolic activity (SULpeak rs = 0.421, p = 0.029; SUVpeak rs = 0.370, p = 0.048). In contrast, the cross-sectional areas of SM, SAT, and VAT were not associated with tumor metabolic activity or survival. CONCLUSION: Higher SAT radiodensity is associated with higher tumor metabolic activity and shorter survival in patients with NSCLC. This may suggest that tumors with higher metabolic activity induce subcutaneous adipose tissue alterations such as decreased lipid density, increased fibrosis, or browning.
Assuntos
Composição Corporal , Caquexia , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Gordura Subcutânea , Humanos , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/metabolismo , Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Masculino , Feminino , Estudos Retrospectivos , Gordura Subcutânea/diagnóstico por imagem , Gordura Subcutânea/metabolismo , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Idoso , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Pessoa de Meia-Idade , Caquexia/metabolismo , Caquexia/mortalidade , Caquexia/diagnóstico por imagem , Fluordesoxiglucose F18 , PrognósticoRESUMO
BACKGROUND: Cancer cachexia is a multifactorial metabolic syndrome characterized by systemic inflammation and ongoing skeletal muscle loss resulting in weakness, poor quality of life, and decreased survival. Whereas lipid accumulation in skeletal muscle is associated with cancer cachexia as well as the prognosis of cancer patients, surprisingly little is known about the nature of the lipids that accumulate in the muscle during cachexia, and whether this is related to inflammation. We aimed to identify the types and distributions of intramyocellular lipids in patients with and without cancer cachexia. METHODS: Rectus abdominis muscle biopsies were collected during surgery of patients with pancreatic ductal adenocarcinoma (n = 10 without cachexia, n = 20 cachectic without inflammation (CRP < 10 mg/L), n = 10 cachectic with inflammation (CRP ≥ 10 mg/L). L3-CT scans were analysed to assess body composition based on validated thresholds in Hounsfield units (HU). Muscle sections were stained with Oil-Red O and H&E to assess general lipid accumulation and atrophy. Untargeted lipidomic analyses were performed on laser-microdissected myotubes using LC-MS/MS. The spatial distribution of intramyocellular lipids with differential abundance between groups was visualized by mass-spectrometry imaging. Genes coding for inflammation markers and enzymes involved in de novo ceramide synthesis were studied by qPCR. RESULTS: Muscle radiation attenuation was lower in cachectic patients with inflammation (median 24.3 [18.6-30.8] HU) as compared with those without inflammation (34.2 [29.3-38.7] HU, P = 0.033) or no cachexia (37.4 [33.9-42.9] HU, P = 0.012). Accordingly, intramyocellular lipid content was lower in non-cachectic patients (1.9 [1.6-2.1]%) as compared with those with cachexia with inflammation (5.5 [4.5-7.3]%, P = 0.002) or without inflammation (4.8 [2.6-6.0]%, P = 0.017). Intramyocellular lipid accumulation was associated with both local IL-6 mRNA levels (rs = 0.57, P = 0.015) and systemic CRP levels (rs = 0.49, P = 0.024). Compared with non-cachectic subjects, cachectic patients had a higher relative abundance of intramyocellular glycerophospholipids and a lower relative abundance of glycerolipids. Furthermore, increases in several intramyocellular lipids such as SM(d36:1), PC(34:1), and TG(48:1) were found in cachectic patients with inflammation and correlated with specific cachexia features. Altered intramyocellular lipid species such as PC(34:1), LPC(18:2), and TG(48:1) showed an uneven distribution in muscle sections of cachectic and non-cachectic patients, with areas featuring abundance of these lipids next to areas almost devoid of them. CONCLUSIONS: Intramyocellular lipid accumulation in patients with cachexia is associated with both local and systemic inflammation, and characterized by changes in defined lipid species such as glycerolipids and glycerophospholipids.
Assuntos
Caquexia , Inflamação , Metabolismo dos Lipídeos , Neoplasias Pancreáticas , Humanos , Caquexia/etiologia , Caquexia/metabolismo , Inflamação/metabolismo , Masculino , Neoplasias Pancreáticas/complicações , Neoplasias Pancreáticas/metabolismo , Feminino , Idoso , Pessoa de Meia-Idade , Músculo Esquelético/metabolismo , Músculo Esquelético/patologia , Lipídeos/análise , Composição CorporalRESUMO
Strong sex differences in the frequencies and manifestations of Long COVID (LC) have been reported with females significantly more likely than males to present with LC after acute SARS-CoV-2 infection 1-7 . However, whether immunological traits underlying LC differ between sexes, and whether such differences explain the differential manifestations of LC symptomology is currently unknown. Here, we performed sex-based multi-dimensional immune-endocrine profiling of 165 individuals 8 with and without LC in an exploratory, cross-sectional study to identify key immunological traits underlying biological sex differences in LC. We found that female and male participants with LC experienced different sets of symptoms, and distinct patterns of organ system involvement, with female participants suffering from a higher symptom burden. Machine learning approaches identified differential sets of immune features that characterized LC in females and males. Males with LC had decreased frequencies of monocyte and DC populations, elevated NK cells, and plasma cytokines including IL-8 and TGF-ß-family members. Females with LC had increased frequencies of exhausted T cells, cytokine-secreting T cells, higher antibody reactivity to latent herpes viruses including EBV, HSV-2, and CMV, and lower testosterone levels than their control female counterparts. Testosterone levels were significantly associated with lower symptom burden in LC participants over sex designation. These findings suggest distinct immunological processes of LC in females and males and illuminate the crucial role of immune-endocrine dysregulation in sex-specific pathology.
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Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) data for novel discoveries. We developed scNAT, a deep learning method that integrates paired scRNA-seq and scTCR-seq data to represent data in a unified latent space for downstream analysis. We demonstrate that scNAT is capable of removing batch effects, and identifying cell clusters and a T cell migration trajectory from blood to cerebrospinal fluid in multiple sclerosis.