Elevated levels of tumour apolipoprotein D independently predict poor outcome in breast cancer patients

Development and validation of an ARID1A-related immune genes risk model in evaluating prognosis and immune therapeutic efficacy for gastric cancer patients: a translational study

Background

Mutations in the ARID1A gene, an integral component of the SWI/SNF complex, are prevalent, affecting prognosis and immune response in several malignancies, including gastric cancer (GC). The aim of this study was to identify ARID1A mutation-associated immune genes to construct an ARID1A-related immune gene risk model (ARM).

Methods

GSEA and ssGSEA were used to explore the involved biological pathways and the degree of immune cell infiltration, respectively. The prognosis model was constructed by lasso-COX. Protein expression level in tissue was verified by immunohistochemistry. Small molecule compounds were screened using molecular docking techniques and their anticancer value was validated in vitro and in vivo experiment.

Results

This study revealed immune-related pathways and infiltration level of multiple immune cell types were enriched in the ARID1AMUT group compared to the ARID1AWT group. ARID1A mutations were correlated with an improved prognosis in individuals treated with immune checkpoint inhibitor (ICI) analyzed via Cbioportal website. TCGA-STAD cohort was randomly divided into a training-group and a testing-group. Additionally, ARM was developed in the training group, which identified APOD and PROC from ARID1A mutation-associated differential immunity genes. A significantly poorer prognosis in the high-risk group compared to the low-risk group, which was consistent across TCGA-training/testing/all cohorts, five GEO cohorts and 55 GC patients from Hainan General Hospital. Furthermore, the immune microenvironment components and ICI therapeutic efficacy markers were different between the two groups. Meanwhile, APOD and PROC expression was higher in GC tissues compared to para-cancerous tissues. Baicalin and capsaicin inhibited the proliferation and metastatic ability of GC cells.

Conclusion

ARM provides valuable insights into the prognosis and the effectiveness of ICI, thereby offering a novel strategy for clinical decision. Baicalin and capsaicin are promising potential drugs for GC treatment.

The analysis of transcriptomic signature of TNBC-searching for the potential RNA-based predictive biomarkers to determine the chemotherapy sensitivity

Neoadjuvant chemotherapy is the foundation treatment for triple-negative breast cancer (TNBC) and frequently results in pathological complete response (pCR). However, there are large differences in clinical response and survival after neoadjuvant chemotherapy of TNBC patients. The aim was to identify genes whose expression significantly associates with the efficacy of neoadjuvant chemotherapy in patients with TNBC. Transcriptomes of 46 formalin-fixed paraffin-embedded (FFPE) tumor samples from TNBC patients were analyzed by RNA-seq by comparing 26 TNBCs with pCR versus 20 TNBCs with pathological partial remission (pPR). Subsequently, we narrowed down the list of genes to those that strongly correlated with drug sensitivity of 63 breast cancer cell lines based on Dependency Map Consortium data re-analysis. Furthermore, the list of genes was limited to those presenting specific expression in breast tumor cells as revealed in three large published single-cell RNA-seq breast cancer datasets. Finally, we analyzed which of the selected genes were significantly associated with overall survival (OS) in TNBC TCGA dataset. A total of 105 genes were significantly differentially expressed in comparison between pPR versus pCR. As revealed by PLSR analysis in breast cancer cell lines, out of 105 deregulated genes, 42 were associated with sensitivity to docetaxel, doxorubicin, paclitaxel, and/or cyclophosphamide. We found that 24 out of 42 sensitivity-associated genes displayed intermediate or strong expression in breast malignant cells using single-cell RNAseq re-analysis. Finally, 10 out of 24 genes were significantly associated with overall survival in TNBC TCGA dataset. Our RNA-seq-based findings suggest that there might be transcriptomic signature consisted of 24 genes specifically expressed in tumor malignant cells for predicting neoadjuvant response in FFPE samples from TNBC patients prior to treatment initiation. Additionally, nine out of 24 genes were potential survival predictors in TNBC. This group of 24 genes should be further investigated for its potential to be translated into a predictive test(s).

Single-cell profiling transcriptomic reveals cellular heterogeneity and cellular crosstalk in breast cancer lymphatic node, bone, and brain metastases

Breast cancer is the most common malignant tumor in the world, and its metastasis is the main cause of death in breast cancer patients. However, the differences between primary breast cancer tissue and lymphatic node, bone, and brain metastases at the single-cell level are not fully understood. We analyzed the microenvironment heterogeneity in samples of primary breast cancer (n = 4), breast cancer lymphatic node metastasis (n = 4), breast cancer brain metastasis (n = 3), and breast cancer bone metastasis (n = 2) using single-cell sequencing data from the GEO database. The malignant epithelial cells were characterized by InferCNV algorithm. The cell-cell communication was analyzed using CellChat package. The biological function of cell subpopulations was analyzed using gene set variation analysis. The expression of STMN1 was analyzed using immunohistochemical staining. The proportion of pCAFs in breast cancer was explored using multispectral immunohistochemical staining. We identified seven cell clusters in primary and metastatic breast cancer (Lymphatic node, brain, and bone metastases) by analyzing single-cell transcriptomic profiles. T-NK and B cells dominated breast cancer with lymphatic node metastasis, whereas fibroblasts were prevalent in brain metastases and primary breast cancer. We identified five T cells (T memory, CD8 + T cells, regulatory T cells, natural killer cells, CD4 + T cells), three B cells (naïve B cells, memory B cells, plasma B cells), and five cancer-associated fibroblasts (CAFs) subpopulations (Smooth muscle cells (SMC), pericyte, antigen-presenting CAFs (apCAFs), proliferative CAFs (pCAFs), and matrix CAFs (mCAFs)). Notably. pCAFs dominated breast cancer with lymphatic node, bone, and brain metastasis. Furthermore, we identified four malignant epithelial cell subpopulations: G0, G1, G2, and G3. The G2 cell population exhibited strong invasion ability, it can differentiate into G3 with strong proliferative ability and proliferation-related G1 cell population after metastasis. Cell-cell communication demonstrated an interaction between pCAFs and metastasis-associated malignant epithelial cells. Finally, we discovered that in advanced breast cancer, the proportion of pCAF increased and was associated with a poor prognosis of breast cancer. This study elucidated the potential cellular origins and drivers of breast cancer metastases to lymphatic nodes, brain, and bone, utilizing single-cell transcriptomic profiles. Furthermore, it demonstrated that increased pCAFs were associated with advanced breast cancer and a poor prognosis.

Role of disulfide death in cancer (Review)

The research field of regulated cell death is growing extensively. Following the recognition of ferroptosis, other unique and distinct forms of regulated cell death, including cuproptosis and disulfide death, have been identified. Disulfide death occurs due to the abnormal accumulation of disulfides within cells in environments lacking glucose, leading to contraction of the actin cytoskeleton, which ultimately triggers various signaling pathways and cell death. The induction of disulfide death in the treatment of cancer may exhibit significant therapeutic potential. Therefore, in the present review, a comprehensive and critical analysis of the current understanding of the molecular mechanisms and regulatory networks of disulfide death is presented. In addition, the potential physiological functions of disulfide death in tumor suppression and immune surveillance as well as its pathological roles and therapeutic potential are described. The core focus areas for future research into this form of cell death are also explored. Given the current lack of extensive clinical findings and well-defined key concepts, these may be regarded as pivotal points of interest in future studies.

Uncovering the potential of APOD as a biomarker in gastric cancer: A retrospective and multi-center study

Gastric cancer (GC) poses a significant health challenge worldwide, necessitating the identification of predictive biomarkers to improve prognosis. Dysregulated lipid metabolism is a well-recognized hallmark of tumorigenesis, prompting investigation into apolipoproteins (APOs). In this study, we focused on apolipoprotein D (APOD) following comprehensive analyses of APOs in pan-cancer. Utilizing data from the TCGA-STAD and GSE62254 cohorts, we elucidated associations between APOD expression and multiple facets of GC, including prognosis, tumor microenvironment (TME), cancer biomarkers, mutations, and immunotherapy response, and identified potential anti-GC drugs. Single-cell analyses and immunohistochemical staining confirmed APOD expression in fibroblasts within the GC microenvironment. Additionally, we independently validated the prognostic significance of APOD in the ZN-GC cohort. Our comprehensive analyses revealed that high APOD expression in GC patients was notably associated with unfavorable clinical outcomes, reduced microsatellite instability and tumor mutation burden, alterations in the TME, and diminished response to immunotherapy. These findings provide valuable insights into the potential prognostic and therapeutic implications of APOD in GC.

An individualized immune prognostic signature in nasopharyngeal carcinoma

BACKGROUND

Immune-related characteristics can serve as reliable prognostic biomarkers in various cancers. Herein, we aimed to construct an individualized immune prognostic signature in nasopharyngeal carcinoma (NPC).

METHODS

This study retrospectively included 455 NPC samples and 39 normal healthy nasopharyngeal tissue specimens. Samples from Gene Expression Omnibus (GEO) were obtained as discovery cohort to screen candidate prognostic immune-related gene pairs based on relative expression ordering of the genes. Quantitative real-time reverse transcription-PCR was used to detect the selected genes to construct an immune-related gene pair signature in training cohort, which comprised 118 clinical samples, and was then validated in validation cohort 1, comprising 92 clinical samples, and validation cohort 2, comprising 88 samples from GEO.

RESULTS

We identified 26 immune-related gene pairs as prognostic candidates in discovery cohort. A prognostic immune signature comprising 11 immune gene pairs was constructed in training cohort. In validation cohort 1, the immune signature could significantly distinguish patients with high or low risk in terms of progression-free survival (PFS) (hazard ratio [HR] 2.66, 95 % confidence interval (CI) 1.17-6.02, P=0.015) and could serve as an independent prognostic factor for PFS in multivariate analysis (HR 2.66, 95 % CI 1.17-6.02, P=0.019). Similar results were obtained using validation cohort 2, in which PFS was significantly worse in high risk group than in low risk group (HR 3.02, 95 % CI 1.12-8.18, P=0.022).

CONCLUSIONS

The constructed immune signature showed promise for estimating prognosis in NPC. It has potential for translation into clinical practice after prospective validation.

Identification of angiogenesis-related subtypes and risk models for predicting the prognosis of gastric cancer patients

Gastric cancer (GC) is a leading cause of cancer-related mortality and is characterized by significant heterogeneity, highlighting the need for further studies aimed at personalized treatment strategies. Tumor angiogenesis is critical for tumor development and metastasis, yet its role in molecular subtyping and prognosis prediction remains underexplored. This study aims to identify angiogenesis-related subtypes and develop a prognostic model for GC patients. Using data from The Cancer Genome Atlas (TCGA), we performed consensus cluster analysis on differentially expressed angiogenesis-related genes (ARGs), identifying two patient subtypes with distinct survival outcomes. Differentially expressed genes between the subtypes were analyzed via Cox and LASSO regression, leading to the establishment of a subtype-based prognostic model using a machine learning algorithm. Patients were classified into high- and low-risk groups based on the risk score. Validation was performed using independent datasets (ICGC and GSE15459). We utilized a deconvolution algorithm to investigate the tumor immune microenvironment in different risk groups and conducted analyses on genetic profiling, sensitivity and combination of anti-tumor drug. Our study identified ten prognostic signature genes, enabling the calculation of a risk score to predict prognosis and overall survival. This provides critical data for stratified diagnosis and treatment upon patient admission, monitoring disease progression throughout the entire course, evaluating immunotherapy efficacy, and selecting personalized medications for GC patients.

Deciphering Breast Cancer Metastasis Cascade: A Systems Biology Approach Integrating Transcriptome and Interactome Insights for Target Discovery

Breast cancer is the lead cause of cancer-related deaths among women globally. Breast cancer metastasis is a complex and still inadequately understood process and a key dimension of mortality attendant to breast cancer. This study reports dysregulated genes across metastatic stages and tissues, shedding light on their molecular interplay in disease pathogenesis and new possibilities for drug discovery. Comprehensive analyses of gene expression data from primary breast tumor, circulating tumor cells, and distant metastatic sites in the brain, lung, liver, and bone were conducted. Genes dysregulated across multiple stages and tissues were identified as metastatic cascade genes, and are further classified based on functional associations with metastasis-related mechanisms. Their interactions with HUB genes in interactome networks were scrutinized, followed by pathway enrichment analysis. Validation for their potential as targets included assessments for survival, druggability, prognostic marker status, secretome annotation, protein expression, and cell type marker association. Results displayed critical genes in the metastatic cascade and those specific to metastatic sites, revealing the involvement of the collagen degradation and assembly of collagen fibrils and other multimeric structure pathways in driving metastasis. Notably, pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 emerged with high metastatic potential, linked to significant druggability and survival scores, establishing them as potential molecular targets. The significance of this research lies in its potential to uncover novel biomarkers for early detection, therapeutic targets, and a deeper understanding of the molecular mechanisms underpinning the metastatic cascade in breast cancer, and with an eye to precision/personalized medicine.

Homologous recombination deficiency reflects the heterogeneity and monitoring treatment response for patients with breast cancer

BACKGROUND

In breast cancer (BC), homologous recombination defect (HRD) is a common carcinogenic mechanism. It is meaningful to classify BC according to HRD biomarkers and to develop a platform for identifying BC molecular features, pathological features and therapeutic responses.

METHODS

In total, 109 HRD genes were collected and screened by univariate Cox regression analysis to determine the prognostic genes, which were used to construct a consensus matrix to identify BC subtype. Differentially expressed genes (DEGs) were filtered by the Limma package and screened by random forest analysis to build a model to analyze the immunotherapy response and sensitivity and prognosis of patients suffering from BC to different drugs.

RESULTS

Thirteen out of 109 HRD genes were prognostic genes of BC, and BC was classified into two subgroups based on their expression. Cluster 1 had a significantly backward survival outcome and a significantly higher adaptive immunity score relative to cluster 2. Six genes were identified by random forest analysis as factors for developing the model. The model provided a prediction called risk score, which showed a significant stratification effect on BC prognosis, immunotherapy response and IC50 values of 62 drugs.

CONCLUSIONS

In the present study, two HRD subtypes of BC were successfully identified, for which mutation and immunological features were determined. A model based on differential genes of HRD subtypes was established, which was a potential predictor of prognosis, immunotherapy response and drug sensitivity of BC.

Deciphering a proteomic signature for the early detection of breast cancer from breast milk: the role of quantitative proteomics

INTRODUCTION

Breast cancer is one of the most prevalent cancers among women in the United States. Current research regarding breast milk has been focused on the composition and its role in infant growth and development. There is little information about the proteins, immune cells, and epithelial cells present in breast milk which can be indicative of the emergence of BC cells and tumors.

AREAS COVERED

We summarize all breast milk studies previously done in our group using proteomics. These studies include 1D-PAGE and 2D-PAGE analysis of breast milk samples, which include within woman and across woman comparisons to identify dysregulated proteins in breast milk and the roles of these proteins in both the development of BC and its diagnosis. Our projected outlook for the use of milk for cancer detection is also discussed.

EXPERT OPINION

Analyzing the samples by multiple methods allows one to interrogate a set of samples with various biochemical methods that complement each other, thus providing a more comprehensive proteome. Complementing methods like 1D-PAGE, 2D-PAGE, in-solution digestion and proteomics analysis with PTM-omics, peptidomics, degradomics, or interactomics will provide a better understanding of the dysregulated proteins, but also the modifications or interactions between these proteins.

NNAT is a novel mediator of oxidative stress that suppresses ER + breast cancer

BACKGROUND

Neuronatin (NNAT) was recently identified as a novel mediator of estrogen receptor-positive (ER+) breast cancer cell proliferation and migration, which correlated with decreased tumorigenic potential and prolonged patient survival. However, despite these observations, the molecular and pathophysiological role(s) of NNAT in ER + breast cancer remains unclear. Based on high protein homology with phospholamban, we hypothesized that NNAT mediates the homeostasis of intracellular calcium [Ca2+]i levels and endoplasmic reticulum (EndoR) function, which is frequently disrupted in ER + breast cancer and other malignancies.

METHODS

To evaluate the role of NNAT on [Ca2+]i homeostasis, we used a combination of bioinformatics, gene expression and promoter activity assays, CRISPR gene manipulation, pharmacological tools and confocal imaging to characterize the association between ROS, NNAT and calcium signaling.

RESULTS

Our data indicate that NNAT localizes predominantly to EndoR and lysosome, and genetic manipulation of NNAT levels demonstrated that NNAT modulates [Ca2+]i influx and maintains Ca2+ homeostasis. Pharmacological inhibition of calcium channels revealed that NNAT regulates [Ca2+]i levels in breast cancer cells through the interaction with ORAI but not the TRPC signaling cascade. Furthermore, NNAT is transcriptionally regulated by NRF1, PPARα, and PPARγ and is strongly upregulated by oxidative stress via the ROS and PPAR signaling cascades.

CONCLUSION

Collectively, these data suggest that NNAT expression is mediated by oxidative stress and acts as a regulator of Ca2+ homeostasis to impact ER + breast cancer proliferation, thus providing a molecular link between the longstanding observation that is accumulating ROS and altered Ca2+ signaling are key oncogenic drivers of cancer.

Comprehensive in-silico analysis of deleterious SNPs in APOC2 and APOA5 and their differential expression in cancer and cardiovascular diseases conditions

Genetic variations in APOC2 and APOA5 genes involve activating lipoprotein lipase (LPL), responsible for the hydrolysis of triglycerides (TG) in blood and whose impaired functions affect the TG metabolism and are associated with metabolic diseases. In this study, we investigate the biological significance of genetic variations at the DNA sequence and structural level using various computational tools. Subsequently, 8 (APOC2) and 17 (APOA5) non-synonymous SNPs (nsSNPs) were identified as high-confidence deleterious SNPs based on the effects of the mutations on protein conservation, stability, and solvent accessibility. Furthermore, based on our docking results, the interaction of native and mutant forms of the corresponding proteins with LPL depicts differences in root mean square deviation (RMSD), and binding affinities suggest that these mutations may affect their function. Furthermore, in vivo, and in vitro studies have shown that differential expression of these genes in disease conditions due to the influence of nsSNPs abundance may be associated with promoting the development of cancer and cardiovascular diseases. Preliminary screening using computational methods can be a helpful start in understanding the effects of mutations in APOC2 and APOA5 on lipid metabolism; however, further wet-lab experiments would further strengthen the conclusions drawn from the computational study.

Apolipoproteins: New players in cancers

Apolipoproteins (APOs), the primary protein moiety of lipoproteins, are known for their crucial role in lipid traffic and metabolism. Despite extensive exploration of APOs in cardiovascular diseases, their roles in cancers did not attract enough attention. Recently, research focusing on the roles of APOs in cancers has flourished. Multiple studies demonstrate the interaction of APOs with classical pathways of tumorigenesis. Besides, the dysregulation of APOs may indicate cancer occurrence and progression, thus serving as potential biomarkers for cancer patients. Herein, we summarize the mechanisms of APOs involved in the development of various cancers, their applications as cancer biomarkers and their genetic polymorphism associated with cancer risk. Additionally, we also discuss the potential anti-cancer therapies by virtue of APOs. The comprehensive review of APOs in cancers may advance the understanding of the roles of APOs in cancers and their potential mechanisms. We hope that it will provide novel clues and new therapeutic strategies for cancers.

A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma

Background

Gastric cancer (GC) represents a major global clinical problem with very limited therapeutic options and poor prognosis. Necroptosis, a recently discovered inflammatory form of cell death, has been implicated in carcinogenesis and inducing necroptosis has also been considered as a therapeutic strategy.

Objective

We aim to evaluate the role of this pathway in gastric cancer development, prognosis and immune aspects of its tumor microenvironment.

Methods and results

In this study, we evaluated the gene expression of 55 necroptosis-related genes (NRGs) that were identified via carrying out a comprehensive review of the medical literature. Necroptosis pathway was deregulated in gastric cancer samples (n=375) as compared to adjacent normal tissues (n=32) obtained from the “The Cancer Genome Atlas (TCGA)”. Based on the expression of these NRGs, two molecular subtypes were obtained through consensus clustering that also showed significant prognostic difference. Differentially expressed genes between these two clusters were retrieved and subjected to prognostic evaluation via univariate cox regression analysis and LASSO cox regression analysis. A 13-gene risk signature, termed as necroptosis-related genes prognostic index (NRGPI), was constructed that comprehensively differentiated the gastric cancer patients into high- and low-risk subgroups. The prognostic significance of NRGPI was validated in the GEO cohort (GSE84437: n=408). The NRGPI-high subgroup was characterized by upregulation of 10 genes (CYTL1, PLCL1, CGB5, CNTN1, GRP, APOD, CST6, GPX3, FCN1, SERPINE1) and downregulation of 3 genes (EFNA3, E2F2, SOX14). Further dissection of these two risk groups by differential gene expression analysis indicated involvement of signaling pathways associated with cancer cell progression and immune suppression such as WNT and TGF-β signaling pathway. Para-inflammation and type-II interferon pathways were activated in NRGPI-high patients with an increased infiltration of Tregs and M2 macrophage indicating an exhausted immune phenotype of the tumor microenvironment. These molecular characteristics were mainly driven by the eight NRGPI oncogenes (CYTL1, PLCL1, CNTN1, GRP, APOD, GPX3, FCN1, SERPINE1) as validated in the gastric cancer cell lines and clinical samples. NRGPI-high patients showed sensitivity to a number of targeted agents, in particular, the tyrosine kinase inhibitors.

Conclusions

Necroptosis appears to play a critical role in the development of gastric cancer, prognosis and shaping of its tumor immune microenvironment. NRGPI can be used as a promising prognostic biomarker to identify gastric cancer patients with a cold tumor immune microenvironment and poor prognosis who may response to selected molecular targeted therapy.

Integrated analysis of 1804 samples of six centers to construct and validate a robust immune-related prognostic signature associated with stromal cell abundance in tumor microenvironment for gastric cancer

Background

Stromal cells in tumor microenvironment could promote immune escape through a variety of mechanisms, but there are lacking research in the field of gastric cancer (GC).

Methods

We identified differential expressed immune-related genes (DEIRGs) between the high- and low-stromal cell abundance GC samples in The Cancer Genome Atlas and GSE84437 datasets. A risk score was constructed basing on univariate cox regression analysis, LASSO regression analysis, and multivariate cox regression analysis in the training cohort (n=772). The median value of the risk score was used to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE26253, n=432; GSE62254, n=300; GSE15459, n=191; GSE26901, n=109) from the Gene Expression Omnibus (GEO) database. The immune cell infiltration was quantified by the CIBERSORT method.

Results

The risk score contained 6 genes (AKT3, APOD, FAM19A5, LTBP3, NOV, and NOX4) showed good performance in predicting 5-year overall survival (OS) rate and 5-year recurrence-free survival (RFS) rate of GC patients. The risk death and recurrence of GC patients growing with the increasing risk score. The patients were clustered into three subtypes according to the infiltration of 22 kinds of immune cells quantified by the CIBERSORT method. The proportion of cluster A with the worst prognosis in the high-risk group was significantly higher than that in the low-risk group; the risk score of cluster C subtype with the best prognosis was significantly lower than that of the other two subtypes.

Conclusion

This study established and validated a robust prognostic model for gastric cancer by integrated analysis 1804 samples of six centers, and its mechanism was explored in combination with immune cell infiltration characterization.

Phospholipid Phosphatase 4 as a Driver of Malignant Glioma and Pancreatic Adenocarcinoma

Glioma and pancreatic cancer are tumors with a high degree of malignancy, morbidity, and mortality. The present study explored possible molecular mechanisms and potential diagnostic and prognostic biomarker-PLPP4 of glioma and PAAD. PLPP4 is differentially elevated in glioma and PAAD tissues. Statistical analysis from TCGA demonstrated that high expression of PLPP4 significantly and positively correlated with clinicopathological features, including pathological grade and poor overall survival in glioma and PAAD patients. Following this, the methylation levels of PLPP4 also affected overall survival in clinical tissue samples. Silencing PLPP4 inhibited proliferation, invasion, and migration in LN229 cells and PANC-1 cells. Moreover, the combination of multiple proteins for the prognosis prediction of glioma and PAAD was evaluated. These results were conducted to elaborate on the potential roles of the biomarker-PLPP4 in clonability and invasion of glioma and PAAD cells.

The Lipocalin Apolipoprotein D Functional Portrait: A Systematic Review

Apolipoprotein D is a chordate gene early originated in the Lipocalin protein family. Among other features, regulation of its expression in a wide variety of disease conditions in humans, as apparently unrelated as neurodegeneration or breast cancer, have called for attention on this gene. Also, its presence in different tissues, from blood to brain, and different subcellular locations, from HDL lipoparticles to the interior of lysosomes or the surface of extracellular vesicles, poses an interesting challenge in deciphering its physiological function: Is ApoD a moonlighting protein, serving different roles in different cellular compartments, tissues, or organisms? Or does it have a unique biochemical mechanism of action that accounts for such apparently diverse roles in different physiological situations? To answer these questions, we have performed a systematic review of all primary publications where ApoD properties have been investigated in chordates. We conclude that ApoD ligand binding in the Lipocalin pocket, combined with an antioxidant activity performed at the rim of the pocket are properties sufficient to explain ApoD association with different lipid-based structures, where its physiological function is better described as lipid-management than by long-range lipid-transport. Controlling the redox state of these lipid structures in particular subcellular locations or extracellular structures, ApoD is able to modulate an enormous array of apparently diverse processes in the organism, both in health and disease. The new picture emerging from these data should help to put the physiological role of ApoD in new contexts and to inspire well-focused future research.

Identification of the RP11-21C4.1/SVEP1 gene pair associated with FAT2 mutations as a potential biomarker in gastric cancer

Gastric cancer (GC) is one of the most common malignancies worldwide. Despite rapid advances in systemic therapy, GC remains the third leading cause of cancer-related deaths. We aimed to identify a novel prognostic signature associated with FAT2 mutations in GC. We analyzed the expression levels of FAT2-mutant and FAT2-wildtype GC samples obtained from The Cancer Genome Atlas (TCGA). The Kaplan–Meier survival curve showed that patients with FAT2 mutations showed better prognosis than those without the mutation. Sixteen long non-coding RNAs (lncRNAs) and 62 messenger RNAs (mRNAs) associated with FAT2 mutations were correlated with the prognosis of GC. We then constructed a 4-mRNA signature and a 5-lncRNA signature for GC. Finally, we identified the most relevant RP11-21 C4.1/SVEP1 gene pair as a prognostic signature of GC that exhibited superior predictive performance in comparison with the 4-mRNA or 5-lncRNA signature by weighted gene correlation network analysis (WGCNA) and Cox proportional hazards regression analysis. In this study, we constructed a prognostic signature of GC by integrative genomics analysis, which also provided insights into the molecular mechanisms linked to FAT2 mutations in GC.

A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer

BACKGROUND

Gastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed.

METHODS

Weighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients.

RESULTS

WGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients.

CONCLUSIONS

Our results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.

Comprehensive analysis of tumor mutation burden and immune microenvironment in gastric cancer

Tumor mutation burden (TMB) was a promising marker for immunotherapy. We aimed to investigate the prognostic role of TMB and its relationship with immune cells infiltration in gastric cancer (GC). We analyzed the mutation landscape of all GC cases and TMB of each GC patient was calculated and patients were divided into TMB-high and TMB-low group. Differentially expressed genes (DEGs) between the two groups were identified and pathway analysis was performed. The immune cells infiltration in each GC patient was evaluated and Kaplan-Meier analysis was performed to investigate the prognostic role of immune cells infiltration. At last, hub immune genes were identified and a TMB prognostic risk score (TMBPRS) was constructed to predict the survival outcome of GC patients. The relationships between mutants of hub immune genes and immune infiltration level in GC was investigated. We found higher TMB was correlated with better survival outcome and female patients, patients with T1-2 and N0 had higher TMB score. Altogether 816 DEGs were harvested and pathway analysis demonstrated that patients in TMB-high group were associated with neuroactive ligand-receptor interaction, cAMP signaling pathway, calcium signaling pathway. The infiltration of activated CD4+ memory T cells, follicular helper T cells, resting NK cells, M0 and M1 macrophages and neutrophils in TMB-high group were higher compared than that in TMB-low group and high macrophage infiltration was correlated with inferior survival outcome of GC patients. Lastly, the TMBPRS was constructed and GC patients with high TMBPRS had poor prognosis.

Apolipoprotein D

ApoD is a 25 to 30 kDa glycosylated protein, member of the lipocalin superfamily. As a transporter of several small hydrophobic molecules, its known biological functions are mostly associated to lipid metabolism and neuroprotection. ApoD is a multi-ligand, multi-function protein that is involved lipid trafficking, food intake, inflammation, antioxidative response and development and in different types of cancers. An important aspect of ApoD's role in lipid metabolism appears to involve the transport of arachidonic acid, and the modulation of eicosanoid production and delivery in metabolic tissues. ApoD expression in metabolic tissues has been associated positively and negatively with insulin sensitivity and glucose homeostasis in a tissue dependent manner. ApoD levels rise considerably in association with aging and neuropathologies such as Alzheimer's disease, stroke, meningoencephalitis, moto-neuron disease, multiple sclerosis, schizophrenia and Parkinson's disease. ApoD is also modulated in several animal models of nervous system injury/pathology.