DNA hypomethylation patterns and their impact on the tumor microenvironment in colorectal cancer

BACKGROUND

Recent research underscores the pivotal role of immune checkpoints as biomarkers in colorectal cancer (CRC) therapy, highlighting the dynamics of resistance and response to immune checkpoint inhibitors. The impact of epigenetic alterations in CRC, particularly in relation to immune therapy resistance, is not fully understood.

METHODS

We integrated a comprehensive dataset encompassing TCGA-COAD, TCGA-READ, and multiple GEO series (GSE14333, GSE37892, GSE41258), along with key epigenetic datasets (TCGA-COAD, TCGA-READ, GSE77718). Hierarchical clustering, based on Euclidean distance and Ward's method, was applied to 330 primary tumor samples to identify distinct clusters. The immune microenvironment was assessed using MCPcounter. Machine learning algorithms were employed to predict DNA methylation patterns and their functional enrichment, in addition to transcriptome expression analysis. Genomic mutation profiles and treatment response assessments were also conducted.

RESULTS

Our analysis delineated a specific tumor cluster with CpG Island (CGI) methylation, termed the Demethylated Phenotype (DMP). DMP was associated with metabolic pathways such as oxidative phosphorylation, implicating increased ATP production efficiency in mitochondria, which contributes to tumor aggressiveness. Furthermore, DMP showed activation of the Myc target pathway, known for tumor immune suppression, and exhibited downregulation in key immune-related pathways, suggesting a tumor microenvironment characterized by diminished immunity and increased fibroblast infiltration. Six potential therapeutic agents-lapatinib, RDEA119, WH.4.023, MG.132, PD.0325901, and AZ628-were identified as effective for the DMP subtype.

CONCLUSION

This study unveils a novel epigenetic phenotype in CRC linked to resistance against immune checkpoint inhibitors, presenting a significant step toward personalized medicine by suggesting epigenetic classifications as a means to identify ideal candidates for immunotherapy in CRC. Our findings also highlight potential therapeutic agents for the DMP subtype, offering new avenues for tailored CRC treatment strategies.

Identification of RNA methylation-related lncRNAs for prognostic assessment and immunotherapy in bladder cancer-based on single cell/Bulk RNA sequencing data

Bladder cancer is a malignancy characterized by significant heterogeneity. RNA methylation has received an increasing amount of attention in recent years. RNA data were collected from the GEO database, and cell subsets were classified according to specific cell markers. Epithelial, immunological, and fibroblast cells were clustered individually to explore the tumor heterogeneity. To distinguish between malignant and benign cells, the InferCNV R package was employed. The monocle2 R package was used for pseudotime analysis. The Decouple R package was used for transcription factor analysis of each cell subgroup, and PROGENy was used to predict the activity of pathways related to tumors. The target lncRNA was screened for model construction. In addition, the qPCR experiment was used to detect the transcription level of lncRNA. Epithelial cells, fibroblasts, and T cells significantly differ in tumor and normal tissues. The lncRNAs related to m6A/m5C/m1A were intersected to construct the model. Finally, six model lncRNAs (PSMB8-AS1, THUMPD3-AS1, U47924.27, XXbac-B135H6.15, MIR99AHG, and C14orf132) were screened. High-risk individuals were shown to have a better prognosis. qPCR experiments showed that the model lncRNA was differentially expressed between normal and tumor cells. Immunotherapy will be more effective in treating individuals with lower risk than those with higher risk using 4 candidate drugs. The prognostic m6A/m5C/m1A-related lncRNA model was constructed for evaluating the clinical outcomes of bladder cancer patients and guiding clinical medication.

Use of in vivo Raman spectroscopy and cryoablation for diagnosis and treatment of bladder cancer

Transurethral resection of bladder tumor (TURBT) is the first-line treatment option for non-muscle invasive bladder cancer (NMIBC), but residual tumor often remains after TURBT, thereby leading to cancer recurrence. Here, we introduce combined use of in vivo Raman spectroscopy and in vivo cryoablation as a new approach to detect and remove residual bladder tumor during TURBT. Bladder cancer (BCa) patients treated with TURBT at our urological department between Dec 2019 and Jan 2021 were collected. First, Raman signals were collected from 74 BCa patients to build reference spectra of normal bladder tissue and of bladder cancers of different pathological types. Then, another 53 BCa patients were randomly categorized into two groups, 26 patients accepted traditional TURBT, 27 patients accepted TURBT followed by Raman scanning and cryoablation if Raman detected existence of residual tumor. The recurrence rates of the two groups until Oct 2022 were compared. Raman was capable of discriminating normal bladder tissue and BCa with a sensitivity and specificity of 90.5% and 80.8 %; and discriminating invasive (T1, T2) and noninvasive (Ta) BCa with a sensitivity and specificity of 83.3 % and 87.3 %. During follow-up, 2 in 27 patients had cancer recurrence in Raman-Cryoablation group, while 8 in 26 patients had cancer recurrence in traditional TURBT group. Combined use of Raman and cryoablation significantly reduced cancer recurrence (p = 0.0394). Raman and cryoablation can serve as an adjuvant therapy to TURBT to improve therapeutic effects and reduce recurrence rate.

Identification of a novel ferroptosis-inducing micropeptide in bladder cancer

Bladder cancer (BC) is a common malignancy in males, and currently lacks ideal therapeutic approaches. Exploring emerging therapeutic targets from the perspective of endogenous peptides to improve the prognosis of bladder cancer patients holds promise. In this study, we have identified CTSGDP-13, a novel endogenous peptide, which demonstrates potential anti-cancer effects in BC. Our findings reveal that CTSGDP-13 can promote ferroptosis in BC cells, both in vitro and in vivo, leading to the inhibition of BC progression. Furthermore, we have identified TRIM25 as a downstream regulatory target of CTSGDP-13. The expression of TRIM25 is significantly upregulated in BC, and its inhibition of ferroptosis promotes BC progression. Mechanistic studies have shown that CTSGDP-13 promotes the ubiquitination and subsequent degradation of TRIM25 by disrupting its interaction with the deubiquitinase USP7. Further investigations indicate that CTSGDP-13 promotes ferroptosis in BC by regulating the USP7/TRIM25/KEAP1 axis. The elucidation of the functional mechanisms of natural CTSGDP-13 and TRIM25 holds promise in providing valuable therapeutic targets for BC diagnosis and treatment.

The single-cell evolution trajectory presented different hypoxia heterogeneity to reveal the carcinogenesis of genes in clear cell renal cell carcinoma: Based on multiple omics and real experimental verification

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is the most prevalent and aggressive subtype of renal cell carcinoma, originating from renal tubular epithelial cells in the kidney. Hypoxia proves to be a feature commonly observed in solid tumors, leading to increased resistance to treatment and tumor progression.

METHODS

scRNA-seq data were procured from GSE159115 data set. We utilized UMAP and NMF algorithm for clustering and dimensionality reduction. The FindAllMarkers function was used to compare various groups and identify potential hypoxia marker genes. A series of in vitro experiments, including CFA, flow cytometry targeting cell cycle, CCK-8, and EDU, was applied to investigate how ANGPTL4 regulated the ccRCC progression. Two cell lines of ccRCC cells, 786-O and Caki, were used for si-ANGPTL4 transfection.

RESULTS

We annotated a total of a total of 6 cell clusters, namely ccRCC malignant cells, T cells, endothelial cells, myeloid cells, smooth muscle cells, and B cells. We observed higher levels of hypoxia-score in the ccRCC malignant cells, while lowest hypoxia-score in T and B cells. We detected multiple hypoxia-related subclusters of TME cells in ccRCC, among which S100A4 CD8+ T cells and nonhypoxia CD8+ T cells were found with a marked elevation of T cell inhibitory gene score. We identified that ANGPTL4+ endothelial cells might function as an integrative role in tumor angiogenesis. Multiple TME subclusters showed high potency in stratification of the prognosis of ccRCC patients. Moreover, by a series of in vitro experiment, we found ANGPTL4 regulated the ccRCC cell proliferation, probably through ERK/P38 pathway.

CONCLUSION

We discerned multiple hypoxia-related subclusters of TME cells in ccRCC, which displayed distinct functional features and great potency in predicting prognosis of ccRCC patients. We identified the role of ANGPTL4 in regulating ccRCC proliferation via ERK/p38 pathway.

Coordinating single-cell and bulk RNA-seq in deciphering the intratumoral immune landscape and prognostic stratification of prostate cancer patients

INTRODUCTION

Prostate cancer is a common cancer among male population. The aberrant expression of histone modifiers has been identified as a potential driving force in numerous cancer types. However, the mechanism of histone modifiers in the development of prostate cancer remains unknown.

METHODS

Expression profiles and clinical data were obtained from GSE70769, GSE46602, and GSE67980. Seruat R package was utilized to calculate the gene set enrichment of the histone modification pathway and obtain the Histone score. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were employed to identify marker genes with prognostic value. Kaplan-Meier survival analysis was conducted to assess the efficacy of the prognostic model. In addition, microenvironment cell populations counter (MCPcounter), single-sample gene set enrichment analysis (ssGSEA), and xCell algorithms were employed for immune infiltration analysis. Drug sensitivity prediction was performed using oncoPredict R package.

RESULTS

We screened differentially expressed genes (DEGs) between Histone-high score (Histone-H) and Histone-low score (Histone-L) groups, which were enriched in RNA splicing and DNA-binding transcription factor binding pathways. We retained four prognostic marker genes, including TACC3, YWHAH, TAF1C and TTLL5. The risk model showed significant efficacy in stratification of the prognosis of prostate cancer patients in both internal and external cohorts (p < .0001 and p = .032, respectively). In addition, prognostic gene YWHAH was infiltrated in abundance of fibroblasts and highly correlated with Entinostat_1593 drug sensitivity score and the value of risk score.

CONCLUSION

We innovatively developed a histone modification-related prognostic model with high prognostic potency and identified YWHAH as possible diagnostic and therapeutic biomarkers for prostate cancer. It provides novel insights to address prostate cancer and enhance clinical outcomes, thereby opening up a new avenue for customized treatment alternatives.

Integration analysis of PLAUR as a sunitinib resistance and macrophage related biomarker in ccRCC, an in silicon and experimental study

Sunitinib remains the preferred systemic treatment option for specific patients with advanced RCC who are ineligible for immune therapy. However, it's essential to recognize that Sunitinib fails to elicit a favourable response in all patients. Moreover, most patients eventually develop resistance to Sunitinib. Therefore, identifying new targets associated with Sunitinib resistance is crucial. Utilizing multiple datasets from public cohorts, we conducted an exhaustive analysis and identified a total of 8 microRNAs and 112 mRNAs displaying significant expression differences between Sunitinib responsive and resistant groups. A particular set of six genes, specifically NIPSNAP1, STK40, SDC4, NEU1, TBC1D9, and PLAUR, were identified as highly significant via WGCNA. To delve deeper into the resistance mechanisms, we performed additional investigations using cell, molecular, and flow cytometry tests. These studies confirmed PLAUR's pivotal role in fostering Sunitinib resistance, both in vitro and in vivo. Our findings suggest that PLAUR could be a promising therapeutic target across various cancer types. In conclusion, this investigation not only uncovers vital genes and microRNAs associated with Sunitinib resistance in RCC but also introduces PLAUR as a prospective therapeutic target for diverse cancers. The outcomes contribute to advancing personalized healthcare and developing superior therapeutic strategies.Communicated by Ramaswamy H. Sarma.

Unveiling Anoikis-related genes: A breakthrough in the prognosis of bladder cancer

BACKGROUND

Bladder cancer (BLCA) is a prevalent malignancy worldwide. Anoikis remains a new form of cell death. It is necessary to explore Anoikis-related genes in the prognosis of BLCA.

METHODS

We obtained RNA expression profiles from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases for dimensionality reduction analysis and isolated epithelial cells, T cells and fibroblasts for copy number variation analysis, pseudotime analysis and transcription factor analysis based on R package. We integrated machine-learning algorithms to develop the artificial intelligence-derived prognostic signature (AIDPS).

RESULTS

The performance of AIDPS with clinical indicators was stable and robust in predicting BLCA and showed better performance in every validation dataset compared to other models. Mendelian randomization analysis was conducted. Single nucleotide polymorphism (SNP) sites of rs3100578 (HK2) and rs66467677 (HSP90B1) exhibited significant correlation of bladder problem (not cancer) and bladder cancer, whereasSNP sites of rs3100578 (HK2) and rs947939 (BAD) had correlation between bladder stone and bladder cancer. The immune infiltration analysis of the TCGA-BLCA cohort was calculated via the ESTIMATE (i.e. Estimation of STromal and Immune cells in MAlignantTumours using Expression data) algorithm which contains stromal, immune and estimate scores. We also found significant differences in the IC50 values of Bortezomib_1191, Docetaxel_1007, Staurosporine_1034 and Rapamycin_1084 among the high- and low-risk groups.

CONCLUSIONS

In conclusion, these findings indicated Anoikis-related prognostic genes in BLCA and constructed an innovative machine-learning model of AIDPS with high prognostic value for BLCA.

Blood lipids, lipid-regulatory medications, and risk of bladder cancer: a Mendelian randomization study

Background

The influences of blood lipids and lipid-regulatory medications on the risk of bladder cancer have long been suspected, and previous findings remain controversial. We aimed to assess the causality between blood lipids or lipid-regulatory medications and bladder cancer susceptibility by means of a comprehensive Mendelian Randomization (MR) study.

Methods

Genetic proxies from genome-wide association studies (GWAS) of four blood lipid traits and lipid-lowering variants in genes encoding the targets of lipid-regulatory medications were employed. The largest ever GWAS data of blood lipids and bladder cancer involving up to 440,546 and 205,771 individuals of European ancestry were extracted from UK Biobank and FinnGen Project Round 6, respectively. A two-sample bidirectional MR study was performed using the inverse variance weighted as the main method. The heterogeneity, horizontal pleiotropy, MR Steiger, and leave-one-out analyses were also conducted as sensitivity tests.

Results

There was indicative evidence that genetically predicted low-density lipoprotein cholesterol (LDL-C) affected bladder cancer susceptibility based on 146 single nucleotide polymorphisms (SNPs) with an odds ratio (OR) of 0.776 (95% confidence interval [CI] = 0.625-0.965, p = 0.022). However, this result became non-significant after two SNPs that possibly drove the effect were removed as demonstrated by leave-one-out analysis. The reversed MR analysis suggested that bladder cancer could not affect serum lipid levels. No causal relationship was found between the lipid-lowering effect of lipid-regulatory medications (fibrates, probucol, statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors, and evinacumab) and the risk of bladder cancer. No heterogeneity or pleiotropy was found (all p > 0.05).

Conclusion

This MR study revealed for the first time, using the most recent and comprehensive GWAS data to date, that genetically predicted total cholesterol (TC) and the lipid-lowering effect of lipid-regulatory medications had no causal association with bladder cancer susceptibility. We also verified claims from early studies that low-density lipoprotein cholesterol (HDL-C), LDL-C, and triglyceride (TG) are not related to bladder cancer susceptibility either. The current study indicated that lipid metabolism may not be as important in the tumorigenesis of bladder cancer as previously believed.

[A preliminary study on the establishment of a subcutaneous allergen-specific immunotherapy center]

Allergic diseases can notably affect a patient's quality of life. World Health Organization (WHO) has identified these diseases as one of the key areas for research and prevention in the 21st century. Currently, allergen-specific immunotherapy is viewed as a potential treatment approach that could modify the natural progression of allergic diseases, thus being recognized as a crucial tactic in their prevention and treatment. Nonetheless, the broad implementation of allergen-specific immunotherapy in clinical settings continues to confront challenges. One significant issue is the absence of standardized centers for subcutaneous allergen-specific immunotherapy. This article presents several perspectives and recommendations for establishing a standardized subcutaneous allergen-specific immunotherapy center.

Collaborating single-cell and bulk RNA sequencing for comprehensive characterization of the intratumor heterogeneity and prognostic model development for bladder cancer

INTRODUCTION

Gaining a deeper insight into the single-cell RNA sequencing (scRNA-seq) results of bladder cancer (BLCA) provides a transcriptomic profiling of individual cancer cells, which may disclose the molecular mechanisms involved in BLCA carcinogenesis.

METHODS

scRNA data were obtained from GSE169379 dataset. We used the InferCNV software to determine the copy number variant (CNV) with normal epithelial cells serving as the reference, and performed the pseudo-timing analysis on subsets of epithelial cell using Monocle3 software. Transcription factor analysis was conducted using the Dorothea software. Intercellular communication analysis was performed using the Liana software. Cox analysis and LASSO regression were applied to establish a prognostic model.

RESULTS

We investigated the heterogeneity of tumors in four distinct cell types of BLCA cancer, namely immune cells, endothelial cells, epithelial cells, and fibroblasts. We evaluated the transcription factor activity of different immune cells in BLCA and identified significant enrichment of TCF7 and TBX21 in CD8+ T cells. Additionally, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs), namely iCAFs and myoCAFs, which exhibited distinct communication patterns. Using sub-cluster and cell trajectory analyses, we identified different states of normal-to-malignant cell transformation in epithelial cells. TF analysis further revealed high activation of MYC and SOX2 in tumor cells. Finally, we identified five model genes (SLCO3A1, ANXA1, TENM3, EHBP1, LSAMP) for the development of a prognostic model, which demonstrated high effectiveness in stratifying patients across seven different cohorts.

CONCLUSIONS

We have developed a prognostic model that has demonstrated significant efficacy in stratifying patients with BLCA.

Exploring oncogenes for renal clear cell carcinoma based on G protein-coupled receptor-associated genes

G protein-coupled receptors (GPCRs) are a class of receptors on cell membranes that regulate various biological processes in cells, such as cell proliferation, differentiation, migration, apoptosis, and metabolism, by interacting with G proteins. However, the role of G protein-coupled receptors in predicting the prognosis of renal clear cell carcinoma is still unknown. The transcriptome data and clinical profiles of renal clear cell carcinoma patients, were downloaded from TCGA databases, and the validation group data were downloaded from number GSE167573, including 63 tumor samples and 14 normal samples. Single-cell RNA sequencing data were downloaded from the GEO database, No. GSE152938 and selected samples were used for GSEA enrichment analysis, WGCNA subgroup analysis, single-cell data analysis, and mutation analysis to explore the role of G protein-coupled receptor-related genes in the diagnosis and prognosis of renal clear cell carcinoma and to verify their reliability with cellular experiments. Finally, this study establishes a disease model based on G protein-coupled receptor-related genes, which may help to propose targeted therapeutic regimens in different strata of renal cell carcinoma patients.Author names: Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author: Given name [Lisa Jia] Last name [Tran].It's ok!

A Machine Learning Method to Predict Pathological Complete Response of Esophageal Cancer after Neoadjuvant Chemoradiotherapy with Clinicohematological Markers and MR Radiomics: A Multi-Center Study

PURPOSE/OBJECTIVE(S)

Nearly 30% of patients with local advanced esophageal cancer achieved pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT), who may benefit from organ-preservation strategy under accurate prediction of pCR. We aimed to develop and validate machine learning models based on clinicohematological markers and MR radiomics to accurately predict pCR of esophageal cancer after nCRT.

MATERIALS/METHODS

In this multi-center study, eligible patients with esophageal cancer who received baseline MR scan (T2-weighted image) and nCRT plus surgery were enrolled between September 2014 and September 2022 at institution 1 (training set) and between December 2017 and August 2021 at institution 2 (testing set). Pre-nCRT and post-nCRT blood test results were collected to calculate hematological markers. Models were constructed by machine learning based on clinicohematological markers and MR radiomics to predict pCR. Area under the curve (AUC) and cut-off analysis were used to evaluate model performances.

RESULTS

Totally 154 patients (81 in the training set and 73 in the testing set) were enrolled. The combined model integrating pre-nCRT monocyte-to-lymphocyte ratio and 6 radiomics features achieved AUC of 0.800 (95% CI 0.671-0.918) in the testing set, with sensitivity of 79.2% (95% CI 62.5%-95.8%), specificity of 83.7% (95% CI 73.5%-93.9%), positive predictive value of 76.0% (95% CI 62.5%-90.0%), and negative predictive value of 89.6% (95% CI 82.0%-95.8%).

CONCLUSION

A machine learning model based on clinicohematological markers and MR radiomics to predict pCR after nCRT for patients with esophageal cancer was developed and validated, providing a novel tool for personalized treatment. It is necessary to further validate in more large datasets.

Single-cell transcriptome analysis revealing the intratumoral heterogeneity of ccRCC and validation of MT2A in pathogenesis

Clear-cell renal cell carcinoma (ccRCC) appears as the most common type of kidney cancer, the carcinogenesis of which has not been fully elucidated. Tumor heterogeneity plays a crucial role in cancer progression, which could be largely deciphered by the implement of scRNA-seq. The bulk and single-cell RNA expression profile is obtained from TCGA and study conducted by Young et al. We utilized UMAP, TSNE, and clustering algorithm Louvain for dimensionality reduction and FindAllMarkers function for determining the DEGs. Monocle2 was utilized to perform pseudo-time series analysis. SCENIC was implemented for transcription factor analysis of each cell subgroup. A series of WB, CFA, CCK-8, and EDU analysis was utilized for the validation of the role of MT2A in ccRCC carcinogenesis. We observed higher infiltration of T/NK and B cells in tumorous tissues, indicating the role of immune cells in ccRCC carcinogenesis. Transcription factor analysis revealed the activation of EOMES and ETS1 in CD8 + T cells, while CAFs were divided into myo-CAFs and i-CAFs, with i-CAFs showing distinct enrichment of ATF3, JUND, JUNB, EGR1, and XBP1. Through cell trajectory analysis, we discerned three distinct stages of cellular evolution, where State2 symbolizes normal renal tubular cells that underwent transitions into State1 and State3 as the CNV score ascended. Functional enrichment examination revealed an amplification of interferon gamma and inflammatory response pathways within tumor cells. The consensus clustering algorithm yielded two molecular subtypes, with cluster 2 being associated with advanced tumor stages and an abundance of infiltrated immune cells. We identified 17 prognostic genes through Cox and LASSO regression models and used them to construct a prognostic model, the efficacy of which was verified in multiple cohorts. Furthermore, we investigated the role of MT2A, one of our hub genes, in ccRCC carcinogenesis, and found it to regulate proliferation and migration of malignant cells. We depicted a detailed single-cell landscape of ccRCC, with special focus on CAFs, endothelial cells, and renal tubular cells. A prognostic model of high stability and accuracy was constructed based on the DEGs. MT2A was found to be actively implicated in ccRCC carcinogenesis, regulating proliferation and migration of the malignant cells.

Gut microbiota-derived short-chain fatty acids promote prostate cancer progression via inducing cancer cell autophagy and M2 macrophage polarization

We have previously demonstrated abnormal gut microbial composition in castration-resistant prostate cancer (CRPC) patients, here we revealed the mechanism of gut microbiota-derived short-chain fatty acids (SCFAs) as a mediator linking CRPC microbiota dysbiosis and prostate cancer (PCa) progression. By using transgenic TRAMP mouse model, PCa patient samples, in vitro PCa cell transwell and macrophage recruitment assays, we examined the effects of CRPC fecal microbiota transplantation (FMT) and SCFAs on PCa progression. Our results showed that FMT with CRPC patients' fecal suspension increased SCFAs-producing gut microbiotas such as Ruminococcus, Alistipes, Phascolarctobaterium in TRAMP mice, and correspondingly raised their gut SCFAs (acetate and butyrate) levels. CRPC FMT or SCFAs supplementation significantly accelerated mice's PCa progression. In vitro, SCFAs enhanced PCa cells migration and invasion by inducing TLR3-triggered autophagy that further activated NF-κB and MAPK signalings. Meanwhile, autophagy of PCa cells released higher level of chemokine CCL20 that could reprogramme the tumor microenvironment by recruiting more macrophage infiltration and simultaneously polarizing them into M2 type, which in turn further strengthened PCa cells invasiveness. Finally in a cohort of 362 PCa patients, we demonstrated that CCL20 expression in prostate tissue was positively correlated with Gleason grade, pre-operative PSA, neural/seminal vesical invasion, and was negatively correlated with post-operative biochemical recurrence-free survival. Collectively, CRPC gut microbiota-derived SCFAs promoted PCa progression via inducing cancer cell autophagy and M2 macrophage polarization. CCL20 could become a biomarker for prediction of prognosis in PCa patients. Intervention of SCFAs-producing microbiotas may be a useful strategy in manipulation of CRPC.

Evolution of magnetic surfboards and spin glass behavior in (Fe1-pGap)2TiO5

The unusual anisotropy of the spin glass (SG) transition in the pseudobrookite system Fe2TiO5has been interpreted as arising from an induced, van der Waals-like, interaction among magnetic clusters. Here we present susceptibility (χ) and specific heat data (C) for Fe2TiO5diluted with non-magnetic Ga, (Fe1-pGap)2TiO5, for disorder parameterp= 0, 0.11, and 0.42, and elastic neutron scattering data forp= 0.20. A uniform suppression ofTgis observed upon increasingp, along with a value ofχTgthat increases asTgdecreases, i.e.dχ(Tg)/dTg<0We also observeCT∝T2in the low temperature limit. The observed behavior places (Fe1-pGap)2TiO5in the category of a strongly geometrically frustrated SG.

NiSi: New Venue for Antiferromagnetic Spintronics

Envisaging antiferromagnetic spintronics pivots on two key criteria of high transition temperature and tuning of underlying magnetic order using straightforward application of magnetic field or electric current. Here, we show that NiSi metal can provide suitable new platform in this quest. First, our study unveils high temperature antiferromagnetism in single crystal NiSi with T_N ⩾ 700 K. Antiferromagnetic order in NiSi is accompanied by the non-centrosymmetric magnetic character with small ferromagnetic component in a-c plane. Second, we find that NiSi manifests distinct magnetic and electronic hysteresis responses to field applications due to the disparity in two moment directions. While magnetic hysteresis is characterized by one-step switching between ferromagnetic states of uncompensated moment, electronic behavior is ascribed to metamagnetic switching phenomena between non-collinear spin configurations. Importantly, the switching behaviors persist to high temperature. The properties underscore the importance of NiSi in the pursuit of antiferromagnetic spintronics. This article is protected by copyright. All rights reserved.

Observation of Linear and Nonlinear Light Localization at the Edges of Moiré Arrays

We observe linear and nonlinear light localization at the edges and in the corners of truncated moiré arrays created by the superposition of periodic mutually twisted at Pythagorean angles square sublattices. Experimentally exciting corner linear modes in the femtosecond-laser written moiré arrays we find drastic differences in their localization properties in comparison with the bulk excitations. We also address the impact of nonlinearity on the corner and bulk modes and experimentally observe the crossover from linear quasilocalized states to the surface solitons emerging at the higher input powers. Our results constitute the first experimental demonstration of localization phenomena induced by truncation of periodic moiré structures in photonic systems.

Repair of the Urethral Mucosa Defect Model Using Adipose-Derived Stem Cell Sheets and Monitoring the Fate of Indocyanine Green-Labeled Sheets by Near Infrared-II

Treatment of urethral mucosa defects is a major challenge in urology. Synthetic materials or autologous mucosa does not provide satisfactory treatment options for long-term or large urethral mucosa defects. In response to this problem, we used autologous adipose-derived stem cells (ADSCs) to synthesize cell sheets in vitro for repairing urethral mucosa defect models. In order to monitor the localization and distribution of cell sheets in vivo, cells and sheets were labeled with indocyanine green (ICG) and the second near-infrared (NIR-II) fluorescence imaging was performed. ICG-based NIR-II imaging can successfully track ADSCs and sheets in vivo up to 8 W. Then, rabbit urethral mucosa defect models were repaired with ICG-ADSCs sheets. At 3 months after operation, retrograde urethrography showed that ADSC sheets could effectively repair urethral mucosa defect and restore urethral patency. Histological analysis showed that in ADSC sheet groups, continuous epithelial cells covered the urethra at the transplantation site, and a large number of vascular endothelial cells could also be seen. In the cell-free sheet group, there was no continuous epithelial cell coverage at the repair site of the urethra, and the expression of pro-inflammatory factor TNF-α was increased. It shows that the extracellular matrix alone without cells is not suitable for repairing urethral defects. Surviving ADSCs in the sheets may play a key role in the repair process. This study provides a new tracing method for tissue engineering to dynamically track grafts using an NIR-II imaging system. The ADSC sheets can effectively restore the structure and function of the urethra. It provides a new option for the repair of urethral mucosa defects.

A radiogenomics biomarker based on immunological heterogeneity for non-invasive prognosis of renal clear cell carcinoma

Background

Tumor immunological heterogeneity potentially influences the prognostic disparities among patients with clear cell renal cell carcinoma (ccRCC); however, there is a lack of macroscopic imaging tools that can be used to predict immune-related gene expression in ccRCC.

Methods

A novel non-invasive radiogenomics biomarker was constructed for immune-related gene expression in ccRCC. First, 520 ccRCC transcriptomic datasets from The Cancer Genome Atlas (TCGA) were analyzed using a non-negative matrix decomposition (NMF) clustering to identify immune-related molecular subtypes. Immune-related prognostic genes were analyzed through Cox regression and Gene Set Enrichment Analysis (GSEA). We then built a risk model based on an immune-related gene subset to predict prognosis in patients with ccRCC. CT images corresponding to the ccRCC patients in The Cancer Imaging Archive (TCIA) database were used to extract radiomic features. To stratify immune-related gene expression levels, extracted radiogenomics features were identified according to standard consecutive steps. A nomogram was built to combine radiogenomics and clinicopathological information through multivariate logistic regression to further enhance the radiogenomics model. Mann–Whitney U test and ROC curves were used to assess the effectiveness of the radiogenomics marker.

Results

NMF methods successfully clustered patients into diverse subtypes according to gene expression levels in the tumor microenvironment (TME). The relative abundance of 10 immune cell populations in each tissue was also analyzed. The immune-related genomic signature (consisting of eight genes) of the tumor was shown to be significantly associated with survival in patients with ccRCC in TCGA database. The immune-related genomic signature was delineated by grouping the signature expression as either low- or high-risk. Using TCIA database, we constructed a radiogenomics biomarker consisting of 11 radiomic features that were optimal predictors of immune-related gene signature expression levels, which demonstrated AUC (area under the ROC curve) values of 0.76 and 0.72 in the training and validation groups, respectively. The nomogram built by combining radiomics and clinical pathological information could further improve the predictive efficacy of the radiogenomics model (AUC = 0.81, 074).

Conclusions

The novel prognostic radiogenomics biomarker achieved excellent correlation with the immune-related gene expression status of patients with ccRCC and could successfully stratify the survival status of patients in TCGA database. It is anticipated that this work will assist in selecting precise clinical treatment strategies. This study may also lead to precise theranostics for patients with ccRCC in the future.

Cross-talk of four types of RNA modification proteins with adenosine reveals the landscape of multivariate prognostic patterns in breast cancer

Background: Breast cancer (BC) is the most common malignant tumour, and its heterogeneity is one of its major characteristics. N6-methyladenosine (m6A), N1-methyladenosine (m1A), alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) RNA editing constitute the four most common adenosine-associated RNA modifications and represent the most typical and critical forms of epigenetic regulation contributing to the immunoinflammatory response, tumorigenesis and tumour heterogeneity. However, the cross-talk and potential combined profiles of these RNA-modified proteins (RMPs) in multivariate prognostic patterns of BC remain unknown.

Methods: A total of 48 published RMPs were analysed and found to display significant expression alterations and genomic mutation rates between tumour and normal tissues in the TCGA-BRCA cohort. Data from 4188 BC patients with clinical outcomes were downloaded from the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), normalized and merged into one cohort. The prognostic value and interconnections of these RMPs were also studied. The four prognosis-related genes (PRGs) with the greatest prognostic value were then selected to construct diverse RMP-associated prognostic models through univariate Cox (uniCox) regression analysis, differential expression analysis, Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox (multiCox) regression. Alterations in biological functional pathways, genomic mutations, immune infiltrations, RNAss scores and drug sensitivities among different models, as well as their prognostic value, were then explored.

Results: Utilizing a large number of samples and a comprehensive set of genes contributing to adenosine-associated RNA modification, our study revealed the joint potential bio-functions and underlying features of these diverse RMPs and provided effective models (PRG clusters, gene clusters and the risk model) for predicting the clinical outcomes of BC. The individuals with higher risk scores showed poor prognoses, cell cycle function enrichment, upregulation of stemness scores, higher tumour mutation burdens (TMBs), immune activation and specific drug resistance. This work highlights the significance of comprehensively examining post-transcriptional RNA modification genes.

Conclusion: Here, we designed and verified an advanced forecasting model to reveal the underlying links between BC and RMPs and precisely predict the clinical outcomes of multivariate prognostic patterns for individuals.

The potential mechanism of Longsheyangquan Decoction on the treatment of bladder cancer: Systemic network pharmacology and molecular docking

Our goal was to explore the bioactive constituents of Longsheyangquan (LSYQ) Decoction and elucidate its mechanisms on the treatment of bladder cancer (BCa). A total of 38 compounds were selected based on their pharmacokinetic properties in three large traditional Chinese medicine (TCM) databases. 654 putative targets of LSYQ Decoction were predicted using a structure-based, reverse-docking algorithm online, of which 343 overlapped with BCa-related protein-coding genes. The protein-protein interaction (PPI) network was constructed to perform module analysis for further Gene Ontology (GO) annotations and Kyoto Encyclopedia Genes and Genomes (KEGG) pathway enrichment analysis, which identified CDK2, EGFR, MMP9 and PTGS2 as hub targets. The TCM-compound-target network and compound-target-pathway network together revealed that quercetin, diosmetin, enhydrin and luteolin were the main components of LSYQ Decoction. Finally, molecular docking showed the affinity between the key compounds and the hub target proteins to verify the accuracy of drug target prediction in the first place. The present study deciphered the core components and targets of LSYQ Decoction on the treatment of BCa in a comprehensive systemic pharmacological manner.

[Value of dual-layer spectral detector CT in preoperative prediction of lymph node metastasis of gastric cancer]

Objective: To investigate the value of dual-layer spectral detector CT(SDCT) in preoperative prediction of lymph node (LN) metastasis of gastric cancer. Methods: From January 2019 to January 2021, the clinical and imaging data of 130 gastric cancer patients(93 males and 37 females, aged from 37 to 84 years)confirmed by pathology in the Zhongshan hospital of Xiamen University were retrospectively collected. According to the status of lymph node metastasis, those patients were divided into metastatic LNs group (n=104) and nonmetastatic LNs group (n=26). The maximum diameter of gastric cancer on spectral CT images, CT Values of lesions in 40, 50, 60, 70. KeV monoenergetic image of arterial and Venous phase (CT_{40 keV}, CT_{50 keV}, CT_{60 keV}, CT_{70 keV}), iodine concentration (IC) and effective atomic number (Z_eff) were measured, then the normalized IC(NIC) and spectral curve(K_(40-70)) value were calculated. The differences of each parameter derived from spectral CT between the two groups were compared, and a logistic regression model was constructed. The ROC curves and area under the curve (AUC) were conducted to evaluate the diagnostic performance of each parameter and Delong test was used to compare the difference of each AUC. Results: Compared to nonmetastatic LNs group, metastatic LNs group had higher maximum diameter of tumor, CT_{40 keV}, CT_{50 keV}, CT_{60 keV}, CT_{70 keV}, IC, NIC, Zeff, and K_(40-70) values on venous phase (the representative parameter is Z_eff: 8.4 (8.2, 8.5) vs 8.2 (8.1, 8.3)) (all P<0.05). The proportion of patients with lower histology differentiated degree, higher T grade and positive carcino embryonic antigen (CEA)were higher than that in nonmetastatic LNs (the representative parameter was CEA: 34.6%(36/104) vs 7.7%(2/26) (all P<0.05). The regression model constructed by CEA and Zeff had the highest predictive value in predicting metastatic LNs, with an AUC of 0.835(0.759-0.894), sensitivity and specificity of 83.65% and 73.08%, respectively. Conclusion: SDCT quantitative parameters on venous phase and CEA facilitate the accurate prediction of metastatic LNs in patients with gastric cancer, and the multi-parameter regression model has the highest diagnostic performance.

Immunological Characteristics of Alternative Splicing Profiles Related to Prognosis in Bladder Cancer

Several studies have found that pathological imbalance of alterative splicing (AS) events is associated with cancer susceptibility. carcinogenicity. Nevertheless, the relationship between heritable variation in AS events and carcinogenicity has not been extensively explored. Here, we downloaded AS event signatures, transcriptome profiles, and matched clinical information from The Cancer Genome Atlas (TCGA) database, identified the prognostic AS-related events via conducting the univariate Cox regression algorism. Subsequently, the prognostic AS-related events were further reduced by the least absolute shrinkage and selection operator (LASSO) logistic regression model, and employed for constructing the risk model. Single-sample (ssGSEA), ESTIMATE, and the CIBERSORT algorithms were conducted to evaluate tumor microenvironment status. CCK8, cell culture scratch, transwell invasion assays and flow cytometry were conducted to confirm the reliability of the model. We found 2751 prognostic-related AS events, and constructed a risk model with seven prognostic-related AS events. Compared with high-risk score patients, the overall survival rate of the patients with low-risk score was remarkably longer. Besides, we further found that risk score was also closely related to alterations in immune cell infiltration and immunotherapeutic molecules, indicating its potential as an observation of immune infiltration and clinical response to immunotherapy. In addition, the downstream target gene (DYM) could be a promising prognostic factor for bladder cancer. Our investigation provided an indispensable reference for ulteriorly exploring the role of AS events in the tumor microenvironment and immunotherapy efficiency, and rendered personalized prognosis monitoring for bladder cancer.

DNA Methylation Modification Map to Predict Tumor Molecular Subtypes and Efficacy of Immunotherapy in Bladder Cancer

Background: Considering the heterogeneity and complexity of epigenetic regulation in bladder cancer, the underlying mechanisms of global DNA methylation modification in the immune microenvironment must be investigated to predict the prognosis outcomes and clinical response to immunotherapy. Methods: We systematically assessed the DNA methylation modes of 985 integrated bladder cancer samples with the unsupervised clustering algorithm. Subsequently, these DNA methylation modes were analyzed for their correlations with features of the immune microenvironment. The principal analysis algorithm was performed to calculate the DMRscores of each samples for qualification analysis. Findings: Three DNA methylation modes were revealed among 985 bladder cancer samples, and these modes are related to diverse clinical outcomes and several immune microenvironment phenotypes, e.g., immune-desert, immune-inflamed, and immune-excluded ones. Then patients were classified into high- and low-DMRscore subgroups according to the DMRscore, which was calculated based on the expression of DNA methylation related genes (DMRGs). Patients with the low-DMRscore subgroup presented a prominent survival advantage that was significantly correlated to the immune-inflamed phenotype. Further analysis revealed that patients with low DMRscores exhibited less TP53 wild mutation, lower cancer stage and molecular subtypes were mainly papillary subtypes. In addition, an independent immunotherapy cohort confirmed that DMRscore could serve as a signature to predict prognosis outcomes and immune responses. Conclusion: Global DNA methylation modes can be used to predict the immunophenotypes, aggressiveness, and immune responses of bladder cancer. DNA methylation status assessments will strengthen our insights into the features of the immune microenvironment and promote the development of more effective treatment strategies.

Radiogenomics Map Reveals the Landscape of m6A Methylation Modification Pattern in Bladder Cancer

We aimed to develop a noninvasive radiomics approach to reveal the m6A methylation status and predict survival outcomes and therapeutic responses in patients. A total of 25 m6A regulators were selected for further analysis, we confirmed that expression level and genomic mutations rate of m6A regulators were significantly different between cancer and normal tissues. Besides, we constructed methylation modification models and explored the immune infiltration and biological pathway alteration among different models. The m6A subtypes identified in this study can effectively predict the clinical outcome of bladder cancer (including m6AClusters, geneClusters, and m6Ascore models). In addition, we observed that immune response markers such as PD1 and CTLA4 were significantly corelated with the m6Ascore. Subsequently, a total of 98 obtained digital images were processed to capture the image signature and construct image prediction models based on the m6Ascore classification using a radiomics algorithm. We constructed seven signature radiogenomics models to reveal the m6A methylation status, and the model achieved an area under curve (AUC) degree of 0.887 and 0.762 for the training and test datasets, respectively. The presented radiogenomics models, a noninvasive prediction approach that combined the radiomics signatures and genomics characteristics, displayed satisfactory effective performance for predicting survival outcomes and therapeutic responses of patients. In the future, more interdisciplinary fields concerning the combination of medicine and electronics remains to be explored.

A Novel Radiogenomics Biomarker Based on Hypoxic-Gene Subset: Accurate Survival and Prognostic Prediction of Renal Clear Cell Carcinoma

Purpose

To construct a novel radiogenomics biomarker based on hypoxic-gene subset for the accurate prognostic prediction of clear cell renal cell carcinoma (ccRCC).

Materials and Methods

Initially, we screened for the desired hypoxic-gene subset by analysis using the GSEA database. Through univariate and multivariate cox regression hazard ratio analysis, survival-related hypoxia genes were identified, and a genomics signature was constructed in the TCGA database. Building on this, a hypoxia-gene related radiogenomics biomarker (prediction of hypoxia-genes signature by contrast-enhanced CT radiomics) was constructed in the TCIA-KIRC database by extracting features in the venous phase of contrast-enhanced CT images, selecting features using the mRMR and LASSO algorithms, and building logistic regression models. Finally, we validated the prognostic capability of the new biomarker for patients with ccRCC in an independent validation cohort at Huashan Hospital of Fudan University, Shanghai, China.

Results

The hypoxia-related genomics signature consisting of five genes (IFT57, PABPN1, RNF10, RNF19B and UBE2T) was shown to be significantly associated with survival for patients with ccRCC in the TCGA database, delineated by grouping of the signature expression as either low- or high-risk. In the TCIA database, we constructed a radiogenomics biomarker consisting of 13 radiomics features that were optimal predictors of hypoxia-gene signature expression levels (low- or high-risk) in patients at each institution, that demonstrated AUC values of 0.91 and 0.91 in the training and validation groups, respectively. In the independent validation cohort at Huashan Hospital, our radiogenomics biomarker was significantly associated with prognosis in patients with ccRCC (p=0.0059).

Conclusions

The novel prognostic radiogenomics biomarker that was constructed achieved excellent correlation with prognosis in both the cohort of TCGA/TCIA-KIRC database and the independent validation cohort of Huashan hospital patients with ccRCC. It is anticipated that this work may assist in clinical preferential treatment decisions and promote the process of precision theranostics in the future.

SARS-CoV-2 RNAemia and clinical outcomes in children with COVID-19

The burden of COVID-19 in children represents a fraction of cases worldwide, yet a subset of those infected are at risk for severe disease. We measured plasma SARS-CoV-2 RNA in a cohort of 103 children hospitalized with COVID-19 with diverse clinical manifestations. SARS-CoV-2 RNAemia was detected in 27 (26%) of these children, lasted for a median of 6 [2-9] days, and it was associated with higher rates of oxygen administration, admission to the intensive care unit, and longer hospitalization.

A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer

Background

The effective treatment and prognosis prediction of bladder cancer (BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis is closely related to tumour occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified an FRG signature with potential prognostic value for patients with BLCA.

Methods

The corresponding clinical data and mRNA expression profiles of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, and a Cox regression model was used to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation.

Results

Clinical traits were combined with FRGs, and 15 prognosis-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD was related to poor survival in BLCA patients. Multivariate Cox regression was used to construct a prognostic model with 7 FRGs that divided patients into two risk groups. Compared with that in the low-risk group, the overall survival (OS) of patients in the high-risk group was significantly lower (P < 0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR = 1.772, P < 0.01). Receiver operating characteristic (ROC) curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in ssGSEA and different distributed patterns in PCA.

Conclusion

Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08687-7.

RSV Specific Antibodies in Pregnant Women and Subsequent Risk of RSV Hospitalization in Young Infants

Background

The fusion (F) glycoprotein of respiratory syncytial virus (RSV) represents the major neutralizing antigen, and antibodies against the pre-F conformation have the most potent neutralizing activity. This study aimed to assess the correlation between maternal antibody titers against the pre-F, post-F, and G glycoproteins and the child’s risk of developing severe RSV bronchiolitis early in infancy.

Methods

We identified previously healthy term infants <3 months of age hospitalized with RSV bronchiolitis from December 2015 to March 2016. We measured IgG antibody titers to pre-F, post-F, and G proteins in maternal sera obtained at 9–12 weeks of pregnancy of these hospitalized infants’ mothers (n = 94) and compared them with serum antibody titers of control pregnant mothers (n = 130) whose children were not hospitalized.

Results

All maternal samples (n = 224) had detectable pre-F antibodies. Pre-F antibody titers were significantly lower in mothers whose infants were hospitalized with RSV bronchiolitis compared with those mothers whose infants were not hospitalized (23.9 [range (or antibody titer range), 1.4–273.7] µg/L vs 30.6 [XXX, 3.4–220.0] µg/L; P = .0026). There were no significant differences in maternal post-F and G antibody titers between hospitalized and nonhospitalized infants.

Conclusions

Our findings indicate that maternal pre-F antibodies are fundamental for providing immune protection to the infant.

Mechanisms of primary and acquired resistance to PD-1/PD-L1 blockade and the emerging role of gut microbiome

As a very promising immunotherapy, PD-1/PD-L1 blockade has revolutionized the treatment of a variety of tumor types, resulting in significant clinical efficacy and lasting responses. However, these therapies do not work for a large proportion of patients initially, which is called primary resistance. And more frustrating is that most patients eventually develop acquired resistance after an initial response to PD-1/PD-L1 blockade. The mechanisms that lead to primary and acquired resistance to PD-1/PD-L1 inhibition have remained largely unclear. Recently, the gut microbiome has emerged as a potential regulator for PD-1/PD-L1 blockade. This review elaborates on the current understanding of the mechanisms in terms of PD-1 related signaling pathways and necessary factors. Moreover, this review discusses new strategies to increase the efficacy of immunotherapy from the perspectives of immune markers and gut microbiome.

Retraction notice to "30MO ORIENT-3: A randomized, open-label, phase III study of sintilimab versus docetaxel in previously treated advanced/metastatic squamous non-small cell lung cancer (sqNSCLC)": [Annals of Oncology Volume 31, Supplement 7, December 2020, Page S1428]

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article was retracted at the request of the authors. The authors of this abstract have advised that full agreement between authors and sponsors on publication of the abstract has not been reached and they are therefore unable to publish this data at present.

[Value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging and diffusion-weighted MR imaging in predicting microvascular invasion in hepatocellular carcinoma and the prognostic significance]

Objective: To investigate the combined value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in predicting pathological microvascular invasion (pMVI) preoperatively, and to determine the relationship between prediction results and prognosis in hepatocellular carcinoma (HCC) patients. Methods: A total of 181 newly diagnosed HCC patients were enrolled in this study. Imaging characteristics and the apparent diffusion coefficient (ADC) value of DWI were analyzed. The differences of imaging characteristics and ADC values between different pMVI groups were analyzed.Multivariate logistic regression and receiver operating characteristic (ROC) curve were used to analyze the value for pMVI prediction by using significant parameters. The patients were grouped based on MRI predicted MVI (mrMVI), and the relationship between mrMVI and recurrence free survival time (RFS) was analyzed. Results: Fifty-one patients were pMVI positive and 130 patients were pMVI negative. The ADC value in pMVI positive group were (1.10±0.17)×10(-3) mm(2)/s, significantly lower than (1.27±0.22)×10(-3) mm(2)/s of pEMVI negative group (P<0.001). The incidence rates of incomplete enhancing "capsule" , non-smooth tumor margin, arterial peritumoral enhancement, mosaic architecture and peritumoral hypointensity on hepatobiliary phase (HBP) in pMVI positive group were significantly higher than those of negative group (all P<0.05). Multivariate logistic regression analysis showed that tumor margin, arterial peritumoral enhancement, peritumoral hypointensity on HBP and ADC value were independently associated with pMVI. ROC analysis showed that the area under curve, sensitivity and specificity of pMVI predicted by combined parameters were 0.830, 76.5% and 81.5%, respectively. The median RFS of mrMVI positive group was 23.6 months, significantly lower than 38.2 months of mrEMVI negative group (P=0.004). Conclusion: Tumor margin, arterial peritumoral enhancement, peritumoral hypointensity on HBP and ADC value are independent predictors of pMVI in HCC, and mrMVI is related with RFS.

[The change of quality of life in 52 patients with non-severe aplastic anemia after cyclosporine A therapy]

目的

研究非重型再生障碍性贫血（NSAA）患者接受环孢素A（CsA）治疗前后生活质量的变化，并分析生活质量改善的影响因素。

方法

收集2014年1月至2016年1月在北京协和医院门诊初次治疗、仅使用CsA的NSAA患者，在治疗前和治疗2年后分别填写SF-36量表，与正常中国人模型（常模）比较；并调查评估患者的年龄、性别、文化程度、家庭年收入、付费方式、依从性、治疗前一般健康状况及治疗2年后的疗效，分析其与生活质量改善的关系。

结果

共52例患者符合入组条件，其中男性27例（51.9％），女性25例（48.1％），中位年龄48（21～85）岁。CsA治疗2年，完全治疗反应（CR）15例（28.8％），部分治疗反应（PR）25例（48.1％），无治疗反应（NR）12例（23.1％），治疗总有效率（CR+PR）76.9％。患者治疗前SF-36量表躯体和心理健康得分差于常模（P值均<0.05）。治疗后，躯体方面及总体生活质量虽仍然低于常模（P值均<0.05），但心理健康与常模比较差异无统计学意义（P值均>0.05），精力（VT）、精神健康（MH）得分高于常模［VT：（58.8±20.1）分对（52.3±20.9）分，P＝0.023；MH：（65.9±17.6）分对（59.7±22.9）分，P＝0.014］。不同社会背景与生活质量改善均无显著相关性。起病时体能状况评分（ECOG评分）较低者生活质量改善更大。CsA治疗有效者生活质量均得到显著改善。

结论

NSAA患者生活质量低于常人，CsA治疗可以改善患者的生活质量，尤其是心理健康情况。不同社会背景的患者均可从治疗中获益，而起病较重者获益更大。