Muscle distribution in relation to all-cause and cause-specific mortality in young and middle-aged adults.

BACKGROUND: The relationship between muscle and prognosis, especially that between muscle distribution across different body parts, and the related prognosis is not well established. OBJECTIVE: To investigate the relationship between muscle distribution and all-cause and cause-specific mortality and their potential modifiers. DESIGN: Longitudinal cohort study. C-index, IDI, and NRI were used to determine the best indicator of prognosis. COX regression analysis was performed to explore the relationship between variables and outcomes. Interaction and subgroup analyses were applied to identify the potential modifiers. PARTICIPANTS: A total of 5052 participants (weighted: 124,841,420) extracted from the NHANES 2003-2006 of median age 45 years and constituting 50.3% men were assessed. For validation, we included 3040 patients from the INSCOC cohort in China. MAIN MEASURES: Muscle mass and distribution. KEY RESULTS: COX regression analysis revealed that upper limbs (HR = 0.41, 95% CI 0.33-0.51), lower limbs (HR = 0.54, 95% CI 0.47-0.64), trunk (HR = 0.71, 95% CI, 0.59-0.85), gynoid (HR = 0.47, 95% CI 0.38-0.58), and total lean mass (HR = 0.55, 95% CI 0.45-0.66) were all associated with the better survival of participants (P trend < 0.001). The changes in the lean mass ratio of the upper and lower limbs and the lean mass ratio of the android and gynoid attenuated the protective effect of lean mass. Age and sex acted as potential modifiers, and the relationship between lean mass and the prognosis was more significant in men and middle-aged participants when compared to that in other age groups. Sensitive analyses depicted that despite lean mass having a long-term impact on prognosis (15 years), it has a more substantial effect on near-term survival (5 years). CONCLUSION: Muscle mass and its distribution affect the prognosis with a more significant impact on the near-term than that on the long-term prognosis. Age and sex acted as vital modifiers.

TSTA3 overexpression promotes malignant characteristics in LUSC by regulating LAMP2-mediated autophagy and tumor microenvironment.

BACKGROUND: TSTA3 gene encoding GDP-L-fucose synthase has recently been proved to be closely related to the prognosis of patients with various tumors. However, its role in lung cancer is still unclear. The purpose of this study is to explore the expression level, prognostic effect, potential function and mechanism of TSTA3 in lung cancer. METHODS: Based on TCGA database, Kaplan-Meier and COX regression was used to analyze the relationship between TSTA3 expression and prognosis of lung cancer patients. Immunohistochemistry was used to determine the TSTA3 protein expression in lung cancer and normal tissues. The function of TSTA3 in lung squamous cell carcinoma (LUSC) cell was determined by CCK8, colony formation, transwell assay in vitro and subcutaneous xenografts in vivo. Transcriptome analysis, Lyso-Tracker Red staining and rescue experiment were used to explore the possible underlying mechanism. RESULTS: The expression of TSTA3 was significantly increased in lung cancer, especially in LUSC, and was significantly correlated with the malignant characteristics of LUSC. COX regression analysis showed that the high expression of TSTA3 was an independent prognostic factor in LUSC patients. This was also confirmed by immunohistochemical staining. Compared with the control group, the proliferation, colony formation, invasion and migration ability of LUSC cells with TSTA3 overexpression was enhanced. Similarly, the ability of cell proliferation, colony formation, invasion and migration were weakened after transient knockdown of TSTA3. In vivo experiment showed that compared with control group, TSTA3 overexpression significantly promoted the growth of tumor and shortened survival time. In addition, transcriptome sequencing analysis showed that the differentially expressed genes between TSTA3 overexpression and control group was mainly concentrated in the lysosome pathway. Further study found that TSTA3 might affect the proliferation, invasion and migration of LUSC by regulating the expression of lysosome-associated membrane protein 2 (LAMP2) in LUSC. CONCLUSION: The expression level of TSTA3 in LUSC is significantly higher than that in normal tissues. High expression of TSTA3 is associated with poor prognosis of LUSC patients. TSTA3 may affect the proliferation, invasion and migration of LUSC by regulating LAMP2.

An N-glycoproteomic site-mapping analysis reveals glycoprotein alterations in esophageal squamous cell carcinoma.

BACKGROUND: Aberrant glycosylation has been recognized as a hallmark of cancer and N-glycosylation is one of the main types of glycosylation in eukaryotes. Although N-glycoproteomics has made contributions to the discovery of biomarkers in a variety of cancers, less is known about the abnormal glycosylation signatures in esophageal squamous cell carcinoma (ESCC). METHODS: In this study, we reported the proteomics and N-glycoproteomic site-mapping analysis of eight pairs of ESCC tissues and adjacent normal tissues. With zic-HILIC enrichment, TMT-based isobaric labeling, LC-MS/MS analysis, differentially expressed N-glycosylation was quantitatively characterized. Lectin affinity enrichment combined with western blot was used to validate the potential biomarkers in ESCC. RESULTS: A series of differentially expressed glycoproteins (e.g., LAMP2, PLOD2) and enriched signaling pathways (e.g., metabolism-related pathway, ECM-receptor interaction, focal adhesion) were identified. Besides that, seven significantly enriched motifs were found from the identified N-glycosylation sites. Three clusters were identified after conducting the dynamic profiling analysis of glycoprotein change during lymph node metastasis progression. Further validation found that the elevated fucosylation level of ITGB1, CD276 contributed to the occurrence and development of ESCC, which might be the potential biomarkers in ESCC. CONCLUSION: In summary, we characterized the N-glycosylation and N-glycoprotein alterations associated with ESCC. The typical changes in glycoprotein expression and glycosylation occupancy identified in our study will not only be used as ESCC biomarkers but also improve the understanding of ESCC biology.

New-Onset Age of Nonalcoholic Fatty Liver Disease and Cancer Risk.

Importance: The onset age of nonalcoholic fatty liver disease (NAFLD) is decreasing, and whether earlier ages of NAFLD onset are associated with increased cancer risk is currently unclear. Objective: To explore the association between NAFLD new-onset age and cancer risk. Design, Setting, and Participants: This cohort study was conducted among 179 328 participants included in the Kailuan Cohort Study between 2006 and 2021. In total, 46 100 incident NAFLD cases were identified. For each case, a participant matched by age (older or younger by 1 year) and sex was randomly selected to create a new matched study cohort. Data were analyzed from December 2022 through April 2023. Exposure: Onset of NAFLD. Main Outcomes and Measures: The association between the onset age of NAFLD and the risk of different cancer types was evaluated using weighted Cox regression models. Population-attributable fractions (PAFs) were used to quantify the association of NAFLD with cancer risk at different ages. Results: Among 63 696 participants (mean [SD] age, 51.37 [12.43] years; ‭10 932 females [17.2%] and ‭52 764 males [82.8%]), 31 848 individuals had NAFLD and 31 848 individuals were in the control group. During a median (IQR) follow-up of 10.16 (7.89-11.67) years, 2415 patients were diagnosed with cancer. Compared with the matched group, patients aged less than 45 years at NAFLD onset exhibited a higher risk of cancer (average hazard ratio [AHR], 1.52; 95% CI, 1.09-2.12), and as the onset age of NAFLD increased, the cancer risk decreased (ages 45-54 years: AHR, 1.50; 95% CI, 1.15-1.97; ages 55-64 years: AHR, 1.13; 95% CI, 0.97-1.33; ages >65 years: AHR, 0.75; 95% CI, 0.45-1.27; P for interaction < .001). Among patients aged less than 45 years at NAFLD onset, cancers were mainly digestive system and lung cancers, with AHR values of 2.00 (95% CI, 1.08-3.47) and 2.14 (95% CI, 1.05-4.36), respectively. PAFs also showed that in patients aged less than 45 years at NAFLD onset, 17.83% (95% CI, 4.92%-29.86%) of cancer risk was attributable to NAFLD.‬‬‬‬. Conclusions and Relevance: This study found that NAFLD was associated with increased cancer risk and there was an interaction with onset age, such that the younger the onset age of NAFLD, the greater the cancer risk.

Novel Diagnostic and Prognostic Tools for Lung Cancer Cachexia: Based on Nutritional and Inflammatory Status.

Background: Cachexia is one of the most common complications affecting lung cancer patients that seriously affects their quality-of-life and survival time. This study aimed to analyze the predictors and prognostic factors of lung cancer cachexia as well as to develop a convenient and accurate clinical prediction tool for oncologists. Methods: In this multicenter cohort study, 4022 patients with lung cancer were retrospectively analyzed. The patients were randomly categorized into training and verification sets (7:3 ratio). Univariate and multivariate logistic regression analyses were performed to determine the risk factors of cachexia in patients with lung cancer. Cox regression analysis was applied to determine independent prognostic factors in the patients with lung cancer cachexia. Meanwhile, two nomograms were established and evaluated by time-dependent receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA). Results: Stage, serum albumin, ALI, anemia, and surgery were independent risk factors for cachexia in patients with lung cancer. Patients with lung cancer cachexia have a shorter survival time. Sex, stage, serum albumin, ALI, KPS score, and surgery served as independent prognostic factors for patients with lung cancer cachexia. The area under the curves (AUCs) of diagnostic nomogram in the training and validation sets were 0.702 and 0.688, respectively, the AUCs of prognostic nomogram in the training set for 1-, 3-, and 5-year were 0.70, 0.72, and 0.75, respectively, while in the validation set the AUCs were 0.71, 0.75, and 0.79, respectively. The calibration curves and DCA of the two nomograms were consistent and the clinical benefit rate was high. Conclusion: Cachexia brings an additional economic burden and worsens the prognosis of lung cancer patients. The two nomograms can accurately screen and predict the probability of occurrence of cachexia in lung cancer and the prognosis of patients with lung cancer cachexia, and guide clinical work.