Fatty Acid Binding Protein 6 Inhibition Decreases Cell Cycle Progression, Migration and Autophagy in Bladder Cancers

Identification of bladder cancer subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes

Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.

Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction

Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.

Genes involved in the cholecystokinin receptor signaling map were differentially expressed in the jejunum of steers with variation in residual feed intake

The jejunum is a critical site for nutrient digestion and absorption, and variation in its ability to take up nutrients within the jejunum is likely to affect feed efficiency. The purpose of this study was to determine differences in gene expression in the jejunum of beef steers divergent for residual feed intake (RFI) in one cohort of steers (Year 1), and to validate those genes in animals from a second study (Year 2). Steers from Year 1 (n = 16) were selected for high and low RFI. Jejunum mucosal tissue was obtained for RNA-seq. Thirty-two genes were differentially expressed (PFDR≤0.15), and five were over-represented in pathways including inflammatory mediator, cholecystokinin receptor (CCKR) signaling, and p38 MAPK pathways. Several differentially expressed genes (ALOX12, ALPI, FABP6, FABP7, FLT1, GSTA2, MEF2B, PDK4, SPP1, and TTF2) have been previously associated with RFI in other studies. Real-time qPCR was used to validate nine differentially expressed genes in the Year 1 steers used for RNA-seq, and in the Year 2 validation cohort. Six genes were validated as differentially expressed (P < 0.1) using RT-qPCR in the Year 1 population. In the Year 2 population, five genes displayed the same direction of expression as the Year 1 population and 3 were differentially expressed (P < 0.1). The CCKR pathway is involved in digestion, appetite control, and regulation of body weight making it a compelling candidate for feed efficiency in cattle, and the validation of these genes in a second population of cattle is suggestive of a role in feed efficiency.

Prognostic significance and immune landscape of a cell cycle progression-related risk model in bladder cancer

BACKGROUND

A greater emphasis has been placed on the part of cell cycle progression (CCP) in cancer in recent years. Nevertheless, the precise connection between CCP-related genes and bladder cancer (BCa) has remained elusive. This study endeavors to establish and validate a reliable risk model incorporating CCP-related factors, aiming to predict both the prognosis and immune landscape of BCa.

METHODS

Clinical information and RNA sequencing data were collected from the GEO and TCGA databases. Univariate and multivariate Cox regression analyses were conducted to construct a risk model associated with CCP. The performance of the model was assessed using ROC and Kaplan-Meier survival analyses. Functional enrichment analysis was employed to investigate potential cellular functions and signaling pathways. The immune landscape was characterized using CIBERSORT algorithms. Integration of the risk model with various clinical variables led to the development of a nomogram.

RESULTS

To build the risk model, three CCP-related genes (RAD54B, KPNA2, and TPM1) were carefully chosen. ROC and Kaplan-Meier survival analysis confirm that our model has good performance. About immunological infiltration, the high-risk group showed decreased levels of regulatory T cells and dendritic cells coupled with increased levels of activated CD4 + memory T cells, M2 macrophages, and neutrophils. Furthermore, the nomogram showed impressive predictive power for OS at 1, 3, and 5 years.

CONCLUSION

This study provides new insights into the association between the CCP-related risk model and the prognosis of BCa, as well as its impact on the immune landscape.

Recent Advances on Small-Molecule Inhibitors of Lipocalin-like Proteins

Lipid transfer proteins (LTPs) are crucial players in nonvesicular lipid trafficking. LTPs sharing a lipocalin lipid transfer domain (lipocalin-like proteins) have a wide range of biological functions, such as regulating immune responses and cell proliferation, differentiation, and death as well as participating in the pathogenesis of inflammatory, metabolic, and neurological disorders and cancer. Therefore, the development of small-molecule inhibitors targeting these LTPs is important and has potential clinical applications. Herein, we summarize the structure and function of lipocalin-like proteins, mainly including retinol-binding proteins, lipocalins, and fatty acid-binding proteins and discuss the recent advances on small-molecule inhibitors for these protein families and their applications in disease treatment. The findings of our Perspective can provide guidance for the development of inhibitors of these LTPs and highlight the challenges that might be faced during the procedures.

Genome-wide DNA methylation analysis identifies potent CpG signature for temzolomide response in non-G-CIMP glioblastomas with unmethylated MGMT promoter: MGMT-dependent roles of GPR81

PURPOSES

To identify potent DNA methylation candidates that could predict response to temozolomide (TMZ) in glioblastomas (GBMs) that do not have glioma-CpGs island methylator phenotype (G-CIMP) but have an unmethylated promoter of O-6-methylguanine-DNA methyltransferase (unMGMT).

METHODS

The discovery-validation approach was planned incorporating a series of G-CIMP-/unMGMT GBM cohorts with DNA methylation microarray data and clinical information, to construct multi-CpG prediction models. Different bioinformatic and experimental analyses were performed for biological exploration.

RESULTS

By analyzing discovery sets with radiotherapy (RT) plus TMZ versus RT alone, we identified a panel of 64 TMZ efficacy-related CpGs, from which a 10-CpG risk signature was further constructed. Both the 64-CpG panel and the 10-CpG risk signature were validated showing significant correlations with overall survival of G-CIMP-/unMGMT GBMs when treated with RT/TMZ, rather than RT alone. The 10-CpG risk signature was further observed for aiding TMZ choice by distinguishing differential outcomes to RT/TMZ versus RT within each risk subgroup. Functional studies on GPR81, the gene harboring one of the 10 CpGs, indicated its distinct impacts on TMZ resistance in GBM cells, which may be dependent on the status of MGMT expression.

CONCLUSIONS

The 64 TMZ efficacy-related CpGs and in particular the 10-CpG risk signature may serve as promising predictive biomarker candidates for guiding optimal usage of TMZ in G-CIMP-/unMGMT GBMs.

Fatty-Acid-Binding Proteins: From Lipid Transporters to Disease Biomarkers

Fatty-acid-binding proteins (FABPs) serve a crucial role in the metabolism and transport of fatty acids and other hydrophobic ligands as an intracellular protein family. They are also recognized as a critical mediator in the inflammatory and ischemic pathways. FABPs are found in a wide range of tissues and organs, allowing them to contribute to various disease/injury developments that have not been widely discussed. We have collected and analyzed research journals that have investigated the role of FABPs in various diseases. Through this review, we discuss the findings on the potential of FABPs as biomarkers for various diseases in different tissues and organs, looking at their expression levels and their roles in related diseases according to available literature data. FABPs have been reported to show significantly increased expression levels in various tissues and organs associated with metabolic and inflammatory diseases. Therefore, FABPs are a promising novel biomarker that needs further development to optimize disease diagnosis and prognosis methods along with previously discovered markers.

The Multifunctional Family of Mammalian Fatty Acid-Binding Proteins

Fatty acid-binding proteins (FABPs) are small lipid-binding proteins abundantly expressed in tissues that are highly active in fatty acid (FA) metabolism. Ten mammalian FABPs have been identified, with tissue-specific expression patterns and highly conserved tertiary structures. FABPs were initially studied as intracellular FA transport proteins. Further investigation has demonstrated their participation in lipid metabolism, both directly and via regulation of gene expression, and in signaling within their cells of expression. There is also evidence that they may be secreted and have functional impact via the circulation. It has also been shown that the FABP ligand binding repertoire extends beyond long-chain FAs and that their functional properties also involve participation in systemic metabolism. This article reviews the present understanding of FABP functions and their apparent roles in disease, particularly metabolic and inflammation-related disorders and cancers.

Autophagy in Cell Survival and Death

Autophagy is a degradative process to remove damaged or unnecessary cellular components, and it has been implicated in many biological processes during cell survival and death [...].

A bile acid-related prognostic signature in hepatocellular carcinoma

Due to the high mortality of hepatocellular carcinoma (HCC), its prognostic models are urgently needed. Bile acid (BA) metabolic disturbance participates in hepatocarcinogenesis. We aim to develop a BA-related gene signature for HCC patients. Research data of HCC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) online databases. After least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a BA-related prognostic signature in TCGA cohort based on differentially expressed prognostic BA-related genes. Then, the predictive performance of the signature was evaluated and verified in TCGA and ICGC cohort respectively. We obtained the risk score of each HCC patient according to the model. The differences of immune status and drug sensitivity were compared in patients that were stratified based on risk score. The protein and mRNA levels of the modeling genes were validated in the Human Protein Atlas database and our cell lines, respectively. In TCGA cohort, we selected 4 BA-related genes to construct the first BA-related prognostic signature. The risk signature exhibited good discrimination and predictive ability, which was verified in ICGC cohort. Patients were classified into high- and low-risk groups according to their median scores. The occurrence of death increased with increasing risk score. Low-risk patients owned favorable overall survival. High-risk patients possessed high immune checkpoint expression and low IC50 values for sorafenib, cisplatin and doxorubicin. Real-time quantitative PCR and immunohistochemical results validate expression of modeling genes in the signature. We constructed the first BA-related gene signature, which might help to identify HCC patients with poor prognosis and guide individualized treatment.

Identification of Immune-Related Subtypes and Construction of a Novel Prognostic Model for Bladder Urothelial Cancer

The purpose of this study was to explore the relationship between bladder urothelial cancer (BLCA) and immunity, to screen prognosis-related immune genes (PIGs), and to construct an immune-related prognosis model (IRPM). We processed the relevant data of The Cancer Genome Atlas (TCGA-BLCA) and GSE13507 using R software and Perl. We divided BLCA into high-immunity and low-immunity subtypes. There were significant differences in the two subtypes. In addition, we identified 13 PIGs of BLCA by jointly analyzing the gene expression data and survival information of GSE13507 and TCGA-BLCA, and constructed IRPM through nine of them. The low-risk group had better survival outcome than the high-risk group. We also constructed a nomogram based on clinicopathological information and risk scores of the patients. Moreover, the prognosis of BLCA patients was significantly impacted by the expression of almost every gene used to calculate the risk score. The result of real-time fluorescence quantitative polymerase chain reaction revealed that all the genes used to calculate the risk score were differentially expressed between BLCA and adjacent normal tissues, except PDGFRA. Our research provided potential targets for the treatment of BLCA and a reference for judging the prognosis of BLCA.