Stem cell research has become a hot topic in biology, as the understanding of stem cell biology can provide new insights for both regenerative medicine and clinical treatment of diseases. Accurately ...deciphering the fate of stem cells is the basis for understanding the mechanism and function of stem cells during tissue repair and regeneration. Cre-loxP-mediated recombination has been widely applied in fate mapping of stem cells for many years. However, nonspecific labeling by conventional cell lineage tracing strategies has led to discrepancies or even controversies in multiple fields. Recently, dual recombinase-mediated lineage tracing strategies have been developed to improve both the resolution and precision of stem cell fate mapping. These new genetic strategies also expand the application of lineage tracing in studying cell origin and fate. Here, we review cell lineage tracing methods, especially dual genetic approaches, and then provide examples to describe how they are used to study stem cell fate plasticity and function in vivo.
20-80% of Nonalcoholic Fatty Liver Disease (NAFLD) have been observed to have dyslipidemia. Nevertheless, the probable mechanism of dyslipidemia's effect on NAFLD remains unclear. Mendelian ...randomization (MR) was utilized to investigate the relationship between lipids, inflammatory factors, and NAFLD; and also, to determine the proportion mediated by interleukin-17(IL-17) and interleukin-1β(IL-1β) for the effect between lipids and NAFLD.
Summary statistics of traits were obtained from the latest and largest genome-wide association study (GWAS). The UK Biobank provided a summary of lipid statistics, which comprised up to 500,000 participants of European descent. And NAFLD GWAS summary statistics were obtained from the FinnGen Biobank which included a total sample size of 218,792 participants of European ancestry. In order to gain an overall picture of how lipids affect NAFLD, MR with two samples was carried out. Multivariable MR determined lipids direct effects on NAFLD after adjusting for inflammatory factors, namely IL-1β, interleukin-6(IL-6), interleukin-16(IL-16), IL-17, and interleukin-18(IL-18); those lipids comprise HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), triglycerides (TGs), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB). For the purpose of determining the MR impact, an inverse variance weighted (IVW) meta-analysis of each Wald Ratio was carried out, while other methods were also performed for sensitivity analysis.
We discovered a positive association between genetically predicted TGs levels and a 45.5% elevated risk of NAFLD, while genetically predicted IL-1β (IVW: OR 1.315 (1.060-1.630),
= 0.012) and IL-17 (IVW: OR 1.468 (1.035-2.082),
= 0.032 were positively associated with 31.5% and 46.8% increased risk of NAFLD, respectively. Moreover, TG was positively associated with 10.5% increased risk of IL-1β and 17.3% increased risk of IL-17. The proportion mediated by IL-17 and IL-1β respectively and both was 2.6%, 3.1%, 14.1%.
Genetically predicted TGs, IL-1β, and IL-17 were positively associated with increased risk of NAFLD, with evidence that IL-1β and IL-17 mediated TGs effect upon NAFLD risk. It indicated that early diet management, weight management, lipid-lowering and anti-inflammatory treatment should be carried out for patients with hyperlipidemia to prevent the NAFLD.
The use of the dual recombinase-mediated intersectional genetic approach involving Cre-loxP and Dre-rox has significantly enhanced the precision of in vivo lineage tracing, as well as gene ...manipulation. However, this approach is limited by the small number of Dre recombinase driver constructs available. Here, we developed more than 70 new intersectional drivers to better target diverse cell lineages. To highlight their applicability, we used these new tools to study the in vivo adipogenic fate of perivascular progenitors, which revealed that PDGFRa+ but not PDGFRa–PDGFRb+ perivascular cells are the endogenous progenitors of adult adipocytes. In addition to lineage tracing, we used members of this new suite of drivers to more specifically knock out genes in complex tissues, such as white adipocytes and lymphatic vessels, that heretofore cannot be selectively targeted by conventional Cre drivers alone. In summary, these new transgenic tools expand the intersectional genetic approach while enhancing its precision.
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•More than 70 new Dre driver lines are provided as a resource for intersectional genetics•PDGFRa+PDGFRb+ or PDGFRa+ perivascular cells contribute to de novo adipocytes•“Exclusion” dual recombinase enables gene deletion in white but not brown adipocytes•Sequential dual recombinase enables gene deletion in lymphatic endothelial cells
The combinatory use of Dre and Cre recombinase-mediated intersectional genetics significantly enhances the precision of in vivo lineage tracing and gene targeting. Han et al. developed more than 70 new intersectional drivers to target diverse cell lineages. Highlighting their application, Han et al. used these new tools to study perivascular progenitors of adipocytes and performed gene knockout in white adipocytes (WAs) and lymphatic endothelial cells (LECs).
During injury, monocytes are recruited from the circulation to inflamed tissues and differentiate locally into mature macrophages, with prior reports showing that cavity macrophages of the peritoneum ...and pericardium invade deeply into the respective organs to promote repair. Here we report a dual recombinase-mediated genetic system designed to trace cavity macrophages in vivo by intersectional detection of two characteristic markers. Lineage tracing with this method shows accumulation of cavity macrophages during lung and liver injury on the surface of visceral organs without penetration into the parenchyma. Additional data suggest that these peritoneal or pleural cavity macrophages do not contribute to tissue repair and regeneration. Our in vivo genetic targeting approach thus provides a reliable method to identify and characterize cavity macrophages during their development and in tissue repair and regeneration, and distinguishes these cells from other lineages.
Colonic adenocarcinoma, representing the predominant histological subtype of neoplasms in the colon, is commonly denoted as colon cancer. This study endeavors to develop and validate a nomogram model ...designed for predicting overall survival (OS) in patients with colon cancer, specifically those presenting with perineural invasion (PNI).
The Surveillance, Epidemiology, and End Results (SEER) database supplied pertinent data spanning from 2010 to 2015, which facilitated the randomization of patients into distinct training and validation cohorts at a 7:3 ratio. Both univariate and multivariate analyses were employed to construct a prognostic nomogram based on the training cohort. Subsequently, the nomogram's accuracy and efficacy were rigorously evaluated through the application of a concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves.
In the training cohorts, multivariable analysis identified age, grade, T-stage, N-stage, M-stage, chemotherapy, tumor size, carcinoembryonic antigen (CEA), marital status, and insurance as independent risk factors for OS, all with
-values less than 0.05. Subsequently, a new nomogram was constructed. The C-index of this nomogram was 0.765 (95% CI: 0.755-0.775), outperforming the American Joint Committee on Cancer (AJCC) TNM staging system's C-index of 0.686 (95% CI: 0.674-0.698). Calibration plots for 3- and 5-year OS demonstrated good consistency, while DCA for 3- and 5-year OS revealed excellent clinical utility in the training cohorts. Comparable outcomes were observed in the validation cohorts. Furthermore, we developed a risk stratification system, which facilitated better differentiation among three risk groups (low, intermediate, and high) in terms of OS for all patients.
In this study, we have devised a robust nomogram and risk stratification system to accurately predict OS in colon cancer patients exhibiting PNI. This innovative tool offers valuable guidance for informed clinical decision-making, thereby enhancing patient care and management in oncology practice.
Rupture risk stratification is critical for incidentally detected intracranial aneurysms. Here we developed and validated an institutional nomogram to solve this issue. We reviewed the imaging and ...clinical databases for aneurysms from January 2015 to September 2018. Aneurysms were reconstructed and morphological features were extracted by the Pyradiomics in python. Multiple logistic regression was performed to develop the nomogram. The consistency of the nomogram predicted rupture risks and PHASES scores was assessed. The performance of the nomogram was evaluated by the discrimination, calibration, and decision curve analysis (DCA). 719 aneurysms were enrolled in this study. For each aneurysm, twelve morphological and nine clinical features were obtained. After logistic regression, seven features were enrolled in the nomogram, which were SurfaceVolumeRatio, Flatness, Age, Hyperlipemia, Smoker, Multiple aneurysms, and Location of the aneurysm. The nomogram had a positive and close correlation with PHASES score in predicting aneurysm rupture risks. AUCs of the nomogram in discriminating aneurysm rupture status was 0.837 in a separate testing set. The calibration curves fitted well and DCA demonstrated positive net benefits of the nomogram in guiding clinical decisions. In conclusion, Pyradiomics derived morphological features based institutional nomogram was useful for aneurysm rupture risk stratification.
The past decade has witnessed unprecedented scientific breakthroughs, including immunotherapy, which has great potential in clinical applications for liver cancer.
Public data were obtained from The ...Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases and analyzed with R software.
The LASSO and SVM-RFE machine learning algorithms identified 16 differentially expressed genes (DEGs) related to immunotherapy, namely, GNG8, MYH1, CHRNA3, DPEP1, PRSS35, CKMT1B, CNKSR1, C14orf180, POU3F1, SAG, POU2AF1, IGFBPL1, CDCA7, ZNF492, ZDHHC22, and SFRP2. Moreover, a logistic model (CombinedScore) was established based on these DEGs, showing an excellent prediction performance for liver cancer immunotherapy. Patients with a low CombinedScore might respond better to immunotherapy. Gene Set Enrichment Analysis showed that many metabolism pathways were activated in patients with a high CombinedScore, including butanoate metabolism, bile acid metabolism, fatty acid metabolism, glycine serine and threonine metabolism, and propanoate metabolism. Our comprehensive analysis showed that the CombinedScore was negatively correlated with the levels of most tumor-infiltrating immune cells and the activities of key steps of cancer immunity cycles. Continually, the CombinedScore was negatively associated with the expression of most immune checkpoints and immunotherapy response-related pathways. Moreover, patients with a high and a low CombinedScore exhibited diverse genomic features. Furthermore, we found that CDCA7 was significantly correlated with patient survival. Further analysis showed that CDCA7 was positively associated with M0 macrophages and negatively associated with M2 macrophages, suggesting that CDCA7 could influence the progression of liver cancer cells by affecting macrophage polarization. Next, single-cell analysis showed that CDCA7 was mainly expressed in prolif T cells. Immunohistochemical results confirmed that the staining intensity of CDCA7 was prominently increased in the nucleus in primary liver cancer tissues compared to adjacent non-tumor tissues.
Our results provide novel insights into the DEGs and factors affecting liver cancer immunotherapy. Meanwhile, CDCA7 was identified as a potential therapeutic target in this patient population.
Biliary system cancers are most commonly gallbladder cancers (GBC). Elderly patients (≥ 65) were reported to suffer from an unfavorable prognosis. In this study, we analyzed the RNA-seq and clinical ...data of elderly GBC patients to derive the genetic characteristics and the survival-related nomograms.
RNA-seq data from 14 GBC cases were collected from the Gene Expression Omnibus (GEO) database, grouped by age, and subjected to gene differential and enrichment analysis. In addition, a Weighted Gene Co-expression Network Analysis (WGCNA) was performed to determine the gene sets associated with age grouping further to characterize the gene profile of elderly GBC patients. The database of Surveillance, Epidemiology, and End Results (SEER) was searched for clinicopathological information regarding elderly GBC patients. Nomograms were constructed to predict the overall survival (OS) and cancer-specific survival (CSS) of elderly GBC patients. The predictive accuracy and capability of nomograms were evaluated through the concordance index (C-index), calibration curves, time-dependent operating characteristic curves (ROC), as well as area under the curve (AUC). Decision curve analysis (DCA) was performed to check out the clinical application value of nomograms.
Among the 14 patients with GBC, four were elderly, while the remaining ten were young. Analysis of gene differential and enrichment indicated that elderly GBC patients exhibited higher expression levels of cell cycle-related genes and lower expression levels of energy metabolism-related genes. Furthermore, the WGCNA analysis indicated that elderly GBC patients demonstrated a decrease in the expression of genes related to mitochondrial respiratory enzymes and an increase in the expression of cell cycle-related genes. 2131 elderly GBC patients were randomly allocated into the training cohort (70%) and validation cohort (30%). Our nomograms showed robust discriminative ability with a C-index of 0.717/0.747 for OS/CSS in the training cohort and 0.708/0.740 in the validation cohort. Additionally, calibration curves, AUCs, and DCA results suggested moderate predictive accuracy and superior clinical application value of our nomograms.
Discrepancies in cell cycle signaling and metabolic disorders, especially energy metabolism, were obviously observed between elderly and young GBC patients. In addition to being predictively accurate, the nomograms of elderly GBC patients also contributed to managing and strategizing clinical care.
To investigate the relationship between function of thyroid, lipids, and cholelithiasis and to identify whether lipids mediate the causal relationship between function of thyroid and cholelithiasis.
...A Mendelian randomization (MR) study of two samples was performed to determine the association of thyroid function with cholelithiasis. A two-step MR was also performed to identify whether lipid metabolism traits mediate the effects of thyroid function on cholelithiasis. A method of inverse variance weighted (IVW), weighted median method, maximum likelihood, MR-Egger, MR-robust adjusted profile score (MR-RAPS) method, and MR pleiotropy residual sum and outlier test (MR-PRESSO) methods were utilized to obtain MR estimates.
The IVW method revealed that FT4 levels were correlated with an elevated risk of cholelithiasis (OR: 1.149, 95% CI: 1.082-1.283,
= 0.014). Apolipoprotein B (OR: 1.255, 95% CI: 1.027-1.535,
= 0.027) and low-density lipoprotein cholesterol (LDL-C) (OR: 1.354, 95% CI: 1.060-1.731,
= 0.016) were also correlated with an elevated risk of cholelithiasis. The IVW method demonstrated that FT4 levels were correlated with the elevated risk of apolipoprotein B (OR: 1.087, 95% CI: 1.019-1.159,
= 0.015) and LDL-C (OR: 1.084, 95% CI: 1.018-1.153,
= 0.012). Thyroid function and the risk of cholelithiasis are mediated by LDL-C and apolipoprotein B. LDL-C and apolipoprotein B had 17.4% and 13.5% of the mediatory effects, respectively.
We demonstrated that FT4, LDL-C, and apolipoprotein B had significant causal effects on cholelithiasis, with evidence that LDL-C and apolipoprotein B mediated the effects of FT4 on cholelithiasis risk. Patients with high FT4 levels should be given special attention because they may delay or limit the long-term impact on cholelithiasis risk.
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