PDGFRα+ITGA11+ fibroblasts foster early-stage cancer lymphovascular invasion and lymphatic metastasis via ITGA11-SELE interplay.

Cancer-associated fibroblasts (CAFs) exhibit considerable heterogeneity in advanced cancers; however, the functional annotation and mechanism of CAFs in early-stage cancers remain elusive. Utilizing single-cell RNA sequencing and spatial transcriptomic, we identify a previously unknown PDGFRα+ITGA11+ CAF subset in early-stage bladder cancer (BCa). Multicenter clinical analysis of a 910-case cohort confirms that PDGFRα+ITGA11+ CAFs are associated with lymphovascular invasion (LVI) and poor prognosis in early-stage BCa. These CAFs facilitate LVI and lymph node (LN) metastasis in early-stage BCa, as evidenced in a PDGFRα+ITGA11+ CAFs-specific deficient mouse model. Mechanistically, PDGFRα+ITGA11+ CAFs promote lymphangiogenesis via recognizing ITGA11 surface receptor SELE on lymphatic endothelial cells to activate SRC-p-VEGFR3-MAPK pathway. Further, CHI3L1 from PDGFRα+ITGA11+ CAFs aligns the surrounding matrix to assist cancer cell intravasation, fostering early-stage BCa LVI and LN metastasis. Collectively, our study reveals the crucial role of PDGFRα+ITGA11+ CAFs in shaping metastatic landscape, informing the treatment of early-stage BCa LVI.

SUMOylation-triggered ALIX activation modulates extracellular vesicles circTLCD4-RWDD3 to promote lymphatic metastasis of non-small cell lung cancer.

Lymph node (LN) metastasis is one of the predominant metastatic routes of non-small cell lung cancer (NSCLC) and is considered as a leading cause for the unsatisfactory prognosis of patients. Although lymphangiogenesis is well-recognized as a crucial process in mediating LN metastasis, the regulatory mechanism involving lymphangiogenesis and LN metastasis in NSCLC remains unclear. In this study, we employed high-throughput sequencing to identify a novel circular RNA (circRNA), circTLCD4-RWDD3, which was significantly upregulated in extracellular vesicles (EVs) from LN metastatic NSCLC and was positively associated with deteriorated OS and DFS of patients with NSCLC from multicenter clinical cohort. Downregulating the expression of EV-packaged circTLCD4-RWDD3 inhibited lymphangiogenesis and LN metastasis of NSCLC both in vitro and in vivo. Mechanically, circTLCD4-RWDD3 physically interacted with hnRNPA2B1 and mediated the SUMO2 modification at K108 residue of hnRNPA2B1 by upregulating UBC9. Subsequently, circTLCD4-RWDD3-induced SUMOylated hnRNPA2B1 was recognized by the SUMO interaction motif (SIM) of ALIX and activated ALIX to recruit ESCRT-III, thereby facilitating the sorting of circTLCD4-RWDD3 into NSCLC cell-derived EVs. Moreover, EV-packaged circTLCD4-RWDD3 was internalized by lymphatic endothelial cells to activate the transcription of PROX1, resulting in the lymphangiogenesis and LN metastasis of NSCLC. Importantly, blocking EV-mediated transmission of circTLCD4-RWDD3 via mutating SIM in ALIX or K108 residue of hnRNPA2B1 inhibited the lymphangiogenesis and LN metastasis of NSCLC in vivo. Our findings reveal a precise mechanism underlying SUMOylated hnRNPA2B1-induced EV packaging of circTLCD4-RWDD3 in facilitating LN metastasis of NSCLC, suggesting that EV-packaged circTLCD4-RWDD3 could be a potential therapeutic target against LN metastatic NSCLC.

Physical activity and cancer risk: a dose-response analysis for the Global Burden of Disease Study 2019.

OBJECTIVE: Adopting a healthy lifestyle, including regular physical activity, is widely believed to decrease cancer risk. This study aimed to quantitatively establish the dose-response relationships between total physical activity and the risk of breast, colon, lung, gastric, and liver cancers. METHODS: A systematic review and dose-response analysis were conducted using PubMed and Embase from January 1, 1980 to March 20, 2023. Prospective cohort studies that examined the association between physical activity and the risks of any of the 5 outcomes were included. The search was confined to publications in the English language with a specific focus on human studies. Physical activity is standardized by using the data from US National Health and Nutrition Examination Surveys (NHANES) and the Global Burden of Disease 2019 database. RESULTS: A total of 98 studies, involving a combined population of 16,418,361 individuals, were included in the analysis. Among the included studies, 57 focused on breast cancer, 17 on lung cancer, 23 on colon cancer, 5 on gastric cancer, and 7 on liver cancer. Overall, elevated levels of physical activity exhibited an inverse correlation with the risk of cancer. The dose-response curve for lung cancer exhibited a non-linear pattern, with the greatest benefit risk reduction observed at 13,200 MET-minutes/week of physical activity, resulting in a 14.7% reduction in risk (relative risk 0.853, uncertainty interval 0.798 to 0.912) compared to the inactive population. In contrast, the dose-response curves for colon, gastric, breast, and liver cancers showed linear associations, indicating that heightened levels of total physical activity were consistently associated with reduced cancer risks. However, the increase in physical activity yielded a smaller risk reduction for colon and gastric cancers compared to breast and liver cancers. Compared to individuals with insufficient activity (total activity level < 600 MET-minutes/week), individuals with high levels of activity (≥ 8,000 MET-minutes/week) experienced a 10.3% (0.897, 0.860 to 0.934) risk reduction for breast cancer; 5.9% (0.941, 0.884 to 1.001) for lung cancer; 7.1% (0.929, 0.909 to 0.949) for colon cancer; 5.1% (0.949, 0.908 to 0.992) for gastric cancer; 17.1% (0.829, 0.760 to 0.903) for liver cancer. CONCLUSIONS: This study demonstrated a significant inverse relationship between total physical activity and the risk of breast, gastric, liver, colon, and lung cancers.

Mutant KRAS Mediates circARFGEF2 Biogenesis to Promote Lymphatic Metastasis of Pancreatic Ductal Adenocarcinoma.

Circular RNAs (circRNA) contribute to cancer stemness, proliferation, and metastasis. The biogenesis of circRNAs can be impacted by the genetic landscape of tumors. Herein, we identified a novel circRNA, circARFGEF2 (hsa_circ_0060665), which was upregulated in KRASG12D pancreatic ductal adenocarcinoma (PDAC) and positively associated with KRASG12D PDAC lymph node (LN) metastasis. CircARFGEF2 overexpression significantly facilitated KRASG12D PDAC LN metastasis in vitro and in vivo. Mechanistically, circARFGEF2 biogenesis in KRASG12D PDAC was significantly activated by the alternative splicing factor QKI-5, which recruited U2AF35 to facilitate spliceosome assembly. QKI-5 bound the QKI binding motifs and neighboring reverse complement sequence in intron 3 and 6 of ARFGEF2 pre-mRNA to facilitate circARFGEF2 biogenesis. CircARFGEF2 sponged miR-1205 and promoted the activation of JAK2, which phosphorylated STAT3 to trigger KRASG12D PDAC lymphangiogenesis and LN metastasis. Importantly, circARFGEF2 silencing significantly inhibited LN metastasis in the KrasG12D/+Trp53R172H/+Pdx-1-Cre (KPC) mouse PDAC model. These findings provide insight into the mechanism and metastasis-promoting function of mutant KRAS-mediated circRNA biogenesis. SIGNIFICANCE: Increased splicing-mediated biogenesis of circARFGEF2 in KRAS-mutant pancreatic ductal adenocarcinoma activates JAK2-STAT3 signaling and triggers lymph node metastasis, suggesting circARFGEF2 could be a therapeutic target to inhibit pancreatic cancer progression.

Identification of a novel anoikis-related gene signature to predict prognosis and tumor microenvironment in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most prevalent histotype of non-small cell lung cancer. Anoikis, an alternative form of programmed cell death, plays a pivotal role in cancer invasion and metastasis, preventing the detached cancer cells from readhering to other substrates for abnormal proliferation. The aim of this study was to conduct a comprehensive analyses of the prognostic implications of anoikis-related genes (ARGs) in LUAD. METHODS: ARGs were selected from The Cancer Genome Atlas (TCGA) database and Genecards dataset using differential expression analysis. The signature incorporating ARGs was identified using univariate Cox regression analysis and LASSO regression analysis. Furthermore, a nomogram containing the signature and clinical information was developed through univariate and multivariate Cox regression analysis. Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were applied to evaluate the predictive validity of these risk models. Finally, functional analysis of the selected ARGs in signature and analysis of immune landscape were also conducted. RESULTS: A 16-gene signature was integrated to stratify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and TNM stage were identified as independent prognostic factors and utilized to develop a nomogram. Both the signature and the nomogram showed satisfactory prediction performance in predicting overall survival (OS) of LUAD patients. The ARGs were enriched in several biological functions and signaling pathways. Finally, differences of immune landscape were investigated among the high- and low-risk groups stratified by the signature. CONCLUSIONS: This study revealed potential relationships between ARGs and prognosis of LUAD. The prognostic predictors identified in present study could be utilized as potential biomarkers for clinical applications.

Identification of Novel Phenotypes Correlated with CKD: A Phenotype-Wide Association Study.

Background: A comprehensive understanding of phenotypes related to CKD will facilitate the identification and management of CKD. We aimed to panoramically test and validate associations between multiple phenotypes and CKD using a phenotype-wide association study (PheWAS). Methods: 15,815 subjects from cross-sectional cohorts of the National Health and Nutrition Examination Survey (1999-2006) were randomly 50:50 split into training and testing sets. CKD was defined as eGFR < 60 mL/min/1.73m2. We performed logistic regression analyses between each of 985 phenotypes with CKD in the training set (false discovery rate < 1%) and validated in the testing set (false discovery rate < 1% ). Random forest (RF) model, Nagelkerke's Pseudo-R2, and the area under the receiver operating characteristic (AUROC) were used to validate the identified phenotypes. Results: We identified 18 phenotypes significantly related to CKD, among which retinol, red cell distribution width (RDW), and C-peptide were less researched. The top 5 identified phenotypes were blood urea nitrogen (BUN), homocysteine (HCY), retinol, parathyroid hormone (PTH), and osmolality in RF importance ranking. Besides, BUN, HCY, PTH, retinol, and uric acid were the most important phenotypes based on Pseudo-R2. AUROC of the RF model was 0.951 (full model) and 0.914 (top 5 phenotypes). Conclusion: Our study demonstrated associations between multiple phenotypes with CKD from a holistic view, including 3 novel phenotypes: retinol, RDW, and C-peptide. Our findings provided valid evidence for the identification of novel biomarkers for CKD.

Construction of a Novel Prognostic Signature in Lung Adenocarcinoma Based on Necroptosis-Related lncRNAs.

Background: Long non-coding RNAs (lncRNAs) are drawing increasing attention as promising predictors of prognosis for lung adenocarcinoma (LUAD) patients. Necroptosis, a novel regulated mechanism of necrotic cell death, plays an important role in the biological process of cancer. The aim of this study was to identify the necroptosis-related lncRNAs (NRLRs) in a LUAD cohort and establish a necroptosis-related lncRNA signature (NRLSig) to stratify LUAD patients. Methods: NRLRs were identified in LUAD patients from The Cancer Genome Atlas (TCGA) database using Pearson correlation analysis between necroptosis-related genes and lncRNAs. Then the NRLSig was identified using univariate Cox regression analysis and LASSO regression analysis. Assessments of the signature were performed based on survival analysis, receiver operating characteristic (ROC) curve analysis and clustering analysis. Next, a nomogram containing the NRLSig and clinical information was developed through univariate and multivariate Cox regression analysis. Further, functional enrichment analysis of the selected lncRNAs in NRLSig and the association between NRLSig and the immune infiltration were also evaluated. Results: A 4-lncRNA signature, incorporating LINC00941, AP001453.2, AC026368.1, and AC236972.3, was identified to predict overall survival (OS) and stratify LUAD patients into different groups. Survival analysis, ROC curve analysis and clustering analysis showed good performance in the prognostic prediction of the lncRNA signature. Then, a nomogram containing the NRLSig was developed and showed satisfactory predictive accuracy, calibration and clinical usefulness. The co-expressed genes of selected NRLRs were enriched in several biological functions and signaling pathways. Finally, differences in the abundance of immune cells were investigated among the high-risk group and low-risk group divided by the NRLSig. Conclusion: The proposed NRLSig may provide promising therapeutic targets or prognostic predictors for LUAD patients.

[Application and Progress of Electromagnetic Navigation Bronchoscopy in Department of Thoracic Surgery].

Lung cancer ranks the first cancer-related morbidity and mortality in China. With the development and penetration of imaging technology, increasing small pulmonary peripheral Nodules (SPPNs) have been detected. However, precise location and diagnosis of SPPNs is still a tough problem for clinical diagnosis and treatment in department of thoracic surgery. With the development of electromagnetic navigation bronchoscopy (ENB), it provides a novel minimally invasive method for the diagnosis and treatment of SPPNs. In this review, we summarized the application and progress of ENB in preoperative positioning, diagnosis, and local treatment, then, discussed the clinical application of ENB in the hybrid operating room.
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Development of a radiomics model to diagnose pheochromocytoma preoperatively: a multicenter study with prospective validation.

BACKGROUND: Preoperative diagnosis of pheochromocytoma (PHEO) accurately impacts preoperative preparation and surgical outcome in PHEO patients. Highly reliable model to diagnose PHEO is lacking. We aimed to develop a magnetic resonance imaging (MRI)-based radiomic-clinical model to distinguish PHEO from adrenal lesions. METHODS: In total, 305 patients with 309 adrenal lesions were included and divided into different sets. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, feature selection, and radiomics signature building. In addition, a nomogram incorporating the obtained radiomics signature and selected clinical predictors was developed by using multivariable logistic regression analysis. The performance of the radiomic-clinical model was assessed with respect to its discrimination, calibration, and clinical usefulness. RESULTS: Seven radiomics features were selected among the 1301 features obtained as they could differentiate PHEOs from other adrenal lesions in the training (area under the curve [AUC], 0.887), internal validation (AUC, 0.880), and external validation cohorts (AUC, 0.807). Predictors contained in the individualized prediction nomogram included the radiomics signature and symptom number (symptoms include headache, palpitation, and diaphoresis). The training set yielded an AUC of 0.893 for the nomogram, which was confirmed in the internal and external validation sets with AUCs of 0.906 and 0.844, respectively. Decision curve analyses indicated the nomogram was clinically useful. In addition, 25 patients with 25 lesions were recruited for prospective validation, which yielded an AUC of 0.917 for the nomogram. CONCLUSION: We propose a radiomic-based nomogram incorporating clinically useful signatures as an easy-to-use, predictive and individualized tool for PHEO diagnosis.

An Artificial Intelligence System for the Detection of Bladder Cancer via Cystoscopy: A Multicenter Diagnostic Study.

BACKGROUND: Cystoscopy plays an important role in bladder cancer (BCa) diagnosis and treatment, but its sensitivity needs improvement. Artificial intelligence has shown promise in endoscopy, but few cystoscopic applications have been reported. We report a Cystoscopy Artificial Intelligence Diagnostic System (CAIDS) for BCa diagnosis. METHODS: In total, 69 204 images from 10 729 consecutive patients from 6 hospitals were collected and divided into training, internal validation, and external validation sets. The CAIDS was built using a pyramid scene parsing network and transfer learning. A subset (n = 260) of the validation sets was used for a performance comparison between the CAIDS and urologists for complex lesion detection. The diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values and 95% confidence intervals (CIs) were calculated using the Clopper-Pearson method. RESULTS: The diagnostic accuracies of the CAIDS were 0.977 (95% CI = 0.974 to 0.979) in the internal validation set and 0.990 (95% CI = 0.979 to 0.996), 0.982 (95% CI = 0.974 to 0.988), 0.978 (95% CI = 0.959 to 0.989), and 0.991 (95% CI = 0.987 to 0.994) in different external validation sets. In the CAIDS vs urologists' comparisons, the CAIDS showed high accuracy and sensitivity (accuracy = 0.939, 95% CI = 0.902 to 0.964; sensitivity = 0.954, 95% CI = 0.902 to 0.983) with a short latency of 12 seconds, much more accurate and quicker than the expert urologists. CONCLUSIONS: The CAIDS achieved accurate BCa detection with a short latency. The CAIDS may provide many clinical benefits, from increasing the diagnostic accuracy for BCa, even for commonly misdiagnosed cases such as flat cancerous tissue (carcinoma in situ), to reducing the operation time for cystoscopy.

[Progress in the Mechanism of Lymphangiogenesis and Lymphatic Metastasis 
of Non-small Cell Lung Cancer].

Lung cancer ranks the first cancer-related morbidity and mortality in China. Tumor metastasis always predicts the poor prognosis for patients. Moreover, lymphatic metastasis is one of the most significant predictors of poor prognosis in patients with non-small cell lung cancer (NSCLC) and lymphangiogenesis represents the bridge that functionally facilitates tumor lymphatic metastasis. In this review, we first discussed the molecular mechanisms of tumor-associated lymphangiogenesis and the interaction between tumor microenvironment and lymphatic endothelial cells, then, summarized the role of non-coding RNA in regulating tumor-associated lymphangiogenesis in recent frontier studies, with the aim to provide some novel insights on NSCLC-related lymphangiogenesis research, diagnosis and treatment.
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Identification and validation of an individualized prognostic signature of lung squamous cell carcinoma based on ferroptosis-related genes.

BACKGROUND: Lung squamous cell carcinoma (LUSC), one of the main pathological types of lung cancer, has led to consequential socioeconomic burden. Ferroptosis is an iron-dependent form of cell death process with potentials for therapeutic target in various kinds of tumors. However, whether ferroptosis-related genes (FRGs) are associated with the prognosis of LUSC patients is still unclear. The aim of this study was to establish a FRGs-based signature which could stratify patients with LUSC. METHODS: The RNA sequencing profiles and corresponding clinical data of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) dataset. A FRG-based signature was developed using the TCGA-LUSC cohort and validated in the GEO cohort. Gene set enrichment analysis (GSEA) and analysis of immune cell characteristics were conducted to assess the relationship between FRGs and biological function or immune status. A nomogram based on selected clinical factors and the risk scores which were generated from the FRG-based signature was developed using the TCGA cohort and validated in the GEO cohort. RESULTS: A set of 16 FRGs, significantly associated with overall survival (OS) in the TCGA cohort, was identified and could classify LUSC patients into two risk groups. Kaplan-Meier analysis illustrated that the survival rate of the high-risk group was significantly lower than the low-risk group. Assessment and external validation of the signature showed that the survival predictive performance of this signature was adequate. Additionally, multiple pathways and functions were enriched through GSEA and the analysis of immune cell characteristics showed significantly different abundances of immune cells among the two risk groups. Finally, a nomogram integrating the FRG-based signature and selected clinical factors was also developed and assessed in both the TCGA and GEO cohort. CONCLUSION: This study indicated the association between the FRGs and prognosis of patients with LUSC. Targeting ferroptosis may serve as a novel potential therapeutic alternative for LUSC.

Kidney damage causally affects the brain cortical structure: A Mendelian randomization study.

BACKGROUND: Alterations in the brain cortical structures of patients with chronic kidney disease (CKD) have been reported; however, the cause has not been determined yet. Herein, we used Mendelian randomization (MR) to reveal the causal effect of kidney damage on brain cortical structure. METHODS: Genome-wide association studies summary data of estimated glomerular filtration rate (eGFR) in 480,698 participants from the CKDGen Consortium were used to identify genetically predicted eGFR. Data from 567,460 individuals from the CKDGen Consortium were used to assess genetically determined CKD; 302,687 participants from the UK Biobank were used to evaluate genetically predicted albuminuria. Further, data from 51,665 patients from the ENIGMA Consortium were used to assess the relationship between genetic predisposition and reduced eGFR, CKD, and progressive albuminuria with alterations in cortical thickness (TH) or surficial area (SA) of the brain. Magnetic resonance imaging was used to measure the SA and TH globally and in 34 functional regions. Inverse-variance weighted was used as the primary estimate whereas MR Pleiotropy RESidual Sum and Outlier, MR-Egger and weighted median were used to detect heterogeneity and pleiotropy. FINDINGS: At the global level, albuminuria decreased TH (ß = -0.07 mm, 95% CI: -0.12 mm to -0.02 mm, P = 0.004); at the functional level, albuminuria reduced TH of pars opercularis gyrus without global weighted (ß = -0.11 mm, 95% CI: -0.16 mm to -0.07 mm, P = 3.74×10-6). No pleiotropy was detected. INTERPRETATION: Kidney damage causally influences the cortex structure which suggests the existence of a kidney-brain axis. FUNDING: This study was supported by the Science and Technology Planning Project of Guangdong Province (Grant No. 2020A1515111119 and 2017B020227007), the National Key Research and Development Program of China (Grant No. 2018YFA0902803), the National Natural Science Foundation of China (Grant No. 81825016, 81961128027, 81772719, 81772728), the Key Areas Research and Development Program of Guangdong (Grant No. 2018B010109006), Guangdong Special Support Program (2017TX04R246), Grant KLB09001 from the Key Laboratory of Malignant Tumor Gene Regulation and Target Therapy of Guangdong Higher Education Institutes, and Grants from the Guangdong Science and Technology Department (2020B1212060018).

Depression and prostate cancer risk: A Mendelian randomization study.

BACKGROUND: The association between depression and prostate carcinogenesis has been reported in observational studies but the causality from depression on prostate cancer (PCa) remained unknown. We aimed to assess the causal effect of depression on PCa using the two-sample Mendelian randomization (MR) method. METHODS: Two sets of genetics instruments were used for analysis, derived from publicly available genetic summary data. One was 44 single-nucleotide polymorphisms (SNPs) robustly associated with major depressive disorder (MDD) and the other was two SNPs related with depressive status as ever depressed for a whole week. Inverse-variance weighted method, weighted median method, MR-Egger regression, MR Pleiotropy RESidual Sum, and Outlier test were used for MR analyses. RESULTS: No evidence for an effect of MDD on PCa risk was found in inverse-variance weighted (OR: 1.12, 95% CI: 0.97-1.30, p = 0.135), MR-Egger (OR 0.89, 95% CI: 0.29-2.68, p = 0.833), and weighted median (OR: 1.08, 95% CI: 0.92-1.27, p = 0.350). Also, no strong evidence for an effect of depressive status on PCa incidence was found using the inverse-variance weighted method (OR 0.72, 95% CI: 0.35-1.47, p = 0.364). CONCLUSIONS: The large MR analysis indicated that depression may not be causally associated with a risk of PCa.