Cancer Prognostic Biomarkers Research Articles

APOA1 mRNA and serum APOA1 protein as diagnostic and prognostic biomarkers in gastric cancer.

Gastric cancer (GC) remains a formidable challenge in oncology, ranking as a leading cause of cancer mortality globally. This underscores an urgent need for innovative prognostic markers that can revolutionize patient management and outcomes. Recent insights into cancer biology have spotlighted the profound influence of lipid metabolism alterations on tumorigenesis, tumor progression, and the tumor microenvironment. These alterations not only fuel cancer cell growth and proliferation but also play a strategic role in evading immune surveillance and promoting metastasis. The intricate web of lipid metabolism in cancer cells, characterized by deregulated uptake, synthesis, and oxidation of fatty acids (FAs), opens new avenues for targeted therapeutic interventions and prognostic evaluations. Specifically, this study zeroes in on apolipoprotein A-I (APOA1), a key player in lipid metabolism, to unearth its prognostic value in GC. By delving into the role of lipid metabolism-related genes, particularly APOA1, we aim to unveil their potential as groundbreaking biomarkers for GC prognosis. This endeavor not only aims to enhance our understanding of the molecular underpinnings of GC but also to spearhead the development of lipid metabolism-based strategies for improved diagnostic, prognostic, and therapeutic outcomes. Transcriptomic and clinical data from GC patients and healthy individuals were sourced from The Cancer Genome Atlas (TCGA) database, a comprehensive project that molecularly characterizes over 20,000 primary cancer and matched normal samples across 33 cancer types. Significantly differentially expressed lipid metabolism-related genes were identified using the "limma" package in R. Prognostic genes were selected via univariate Cox regression analysis. Differential gene enrichment analysis was performed using Metascape (http://www.metascape.org). The Human Protein Atlas (HPA, https://www.proteinatlas.org) provided information on APOA1 protein expression in GC and healthy tissues. Immune cell infiltration was analyzed using the CIBERSORT algorithm (http://cibersort.stanford.edu). Significant differences in lipid metabolism-related gene expression were observed between GC and normal tissues, closely linked to FA metabolism, oxidoreductase activity, and sphingolipid metabolism. APOA1 emerged as a potential prognostic biomarker by intersecting prognostic and differentially expressed lipid metabolism genes. Immunohistochemical analysis confirmed APOA1 downregulation in GC. The receiver operating characteristic (ROC) analysis demonstrated its predictive value, with the area under the curve (AUC) being 0.64 [95% confidence interval (CI): 0.52-0.76]. APOA1 expression correlated with immune cell infiltrations. Clinical serum APOA1 results revealed lower levels in GC patients (1.38 vs. 1.26; P<0.05), associated with poor prognosis (hazard ratio =1.50; P<0.001) and clinical characteristics. ROC analysis of serum APOA1 demonstrated good diagnostic ability (AUC: 0.63, 95% CI: 0.61-0.65). Serum APOA1 levels significantly increased after treatment. This study highlights lipid metabolism reprogramming in GC and identifies APOA1 as a potential diagnostic and prognostic biomarker, suggesting its clinical utility in managing GC.

Identification and validation of the TRHDE-AS1/hsa-miR-449a/ADAMTS5 axis as a novel prognostic biomarker in prostate cancer.

Despite advancements in cancer research, the prognostic implications of competing endogenous RNA (ceRNA) networks in prostate cancer (PCa) remain incompletely understood. This study aimed to elucidate the prognostic relevance of ceRNA networks in PCa, utilizing a comprehensive bioinformatics approach alongside experimental validation. After searching The Cancer Genome Atlas (TCGA) database, RNA sequencing (RNA-Seq) data were extracted to identify differentially expressed RNAs (DERs) between 491 PCa samples and 51 normal prostate tissues, following which a comprehensive bioinformatics strategy was implemented to construct a ceRNA network. An optimal prognostic signature comprising these DERs was then established and validated using TCGA data. In addition, functional validation was performed through RNA pull-down, dual-luciferase reporter assays, quantitative real-time PCR, and western blot analysis conducted in PC-3 and DU145 cell lines, thereby complementing the bioinformatics analysis. A total of 613 DERs, comprising 103 long noncoding RNAs (lncRNAs), 60 microRNAs (miRNAs), and 450 messenger RNAs (mRNAs), were identified and utilized in constructing a ceRNA network, which encompassed 23 lncRNAs, 9 miRNAs, and 52 mRNAs. An optimal prognostic signature was established, including VPS9D1 antisense RNA 1 (VPS9D1-AS1), miR-449a, cyclin-dependent kinase 5 regulatory subunit 1 (CDK5R1), targeting protein for Xklp2 (TPX2), solute carrier family 7 member 11 (SLC7A11), copine7 (CPNE7), and maternal embryonic leucine zipper kinase (MELK), yielding area under the curve (AUC) values exceeding 0.8 across training, validation, and entire datasets. Our experiments results revealed an interaction between lncRNA TRHDE antisense RNA 1 (TRHDE-AS1) and miR-449a and that miR-449a could target the ADAM metallopeptidase with thrombospondin type 1 motif 5 (ADAMTS5) mRNA. Knockdown of miR-449a significantly impeded cell proliferation, G1/S transition, migration and invasion, and promoted apoptosis in PC-3 and DU145 cells. Furthermore, knockdown of miR-449a notably downregulated protein expression of CDK4, cyclin D1, N-cadherin and vimentin, while upregulating protein expression of cleaved caspase-3 and E-cadherin. This study contributes to a deeper understanding of the prognostic-linked ceRNA network in PCa, providing fundamental insights that could improve diagnostic and therapeutic approaches for PCa management.

Interleukin-1α as a Potential Prognostic Biomarker in Pancreatic Cancer.

We assessed the prognostic role of pro-inflammatory cytokines of the IL-1 superfamily in patients with pancreatic cancer. This retrospective study was performed using two independent cohorts of patients with pancreatic cancer: the International Cancer Genome Consortium (ICGC, N = 267) cohort and The Cancer Genome Atlas (TCGA, N = 178) cohort. Univariate Cox regressions were used to identify prognosis-related pro-inflammatory cytokines of the IL-1 superfamily. Cytokines associated with outcome were included in a multivariate Cox model with relevant clinicopathological variables to identify prognostic biomarkers. IL-1α was the only pro-inflammatory cytokine of the IL-1 superfamily that was significantly associated with prognosis in both cohorts. In the training cohort (ICGC), the decile of patients with the lowest IL1A expression had better overall survival (HR = 1.99 [1.01-3.93], p = 0.05) and better relapse-free survival (HR = 1.85 [1.02-3.34], p = 0.04) than the group with the highest IL1A expression. The validation cohort (TCGA) confirmed these results: the decile with the lowest IL1A expression had better overall survival (HR = 3.00 [1.14-7.90], p = 0.03) and a lower risk of progression (HR = 3.11 [1.24-7.80], p = 0.01). IL1A is an independent prognostic marker and could be considered a potential therapeutic target in pancreatic cancer patients.

Multiomics Analysis of the PHLDA Gene Family in Different Cancers and Their Clinical Prognostic Value.

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein-protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer.

ADAMTSL2 is a potential prognostic biomarker and immunotherapeutic target for colorectal cancer: Bioinformatic analysis and experimental verification.

The ADAMTS Like 2 (ADAMTSL2) mutation has been identified to be associated with different human genetic diseases. The role of ADAMTSL2 is unclear in colorectal cancer (CRC). The study investigated the expression of ADAMTSL2 in both pan cancer and CRC, using data from The Cancer Genome Atlas (TCGA) database to assess its diagnostic value. The study examined the correlation between ADAMTSL2 expression levels and clinical characteristics, as well as prognosis in CRC. The study explored potential regulatory networks involving ADAMTSL2, including its association with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB) / microsatellite instability (MSI), tumor stemness index (mRNAsi), and drug sensitivity in CRC. ADAMTSL2 expression was validated using GSE71187 and quantitative real-time PCR (qRT-PCR). ADAMTSL2 was aberrantly expressed in pan cancer and CRC. An increased level of ADAMTSL2 expression in patients with CRC was significantly associated with the pathologic N stage (p < 0.001), pathologic stage (p < 0.001), age (p < 0.001), histological type (p < 0.001), and neoplasm type (p = 0.001). The high expression of ADAMTSL2 in patients with CRC was found to be significantly associated with a poorer overall survival (OS) (HR: 1.67; 95% CI: 1.18-2.38; p = 0.004), progression-free survival (PFS) (HR: 1.55; 95% CI: 1.14-2.11; p = 0.005) and disease-specific survival (DSS) (HR: 1.83; 95% CI: 1.16-2.89; p = 0.010). The expression of ADAMTSL2 in patients with CRC (p = 0.009) was identified as an independent prognostic determinant. ADAMTSL2 was associated with extracellular matrix receptor (ECM-receptor) interaction, transforming growth factor β (TGF-β) signaling pathway, and more. ADAMTSL2 expression was correlated with immune infiltration, immune checkpoint genes, TMB / MSI and mRNAsi in CRC. ADAMTSL2 expression was significantly and negatively correlated with 1-BET-762, Trametinib, and WZ3105 in CRC. ADAMTSL2 was significantly upregulated in CRC cell lines. The high expression of ADAMTSL2 is significantly correlated with lower OS and immune infiltration of CRC. ADAMTSL2 may be a potential prognostic biomarker and immunotherapeutic target for CRC patients.

Exploring the neutrophil-to-lymphocyte ratio as a prognostic biomarker in triple-negative breast cancer

Triple-negative breast cancer is a subtype characterized by the absence of estrogen receptor, progesterone Receptor, and Human Epidermal Growth Factor Receptor 2 receptors, limiting treatment options primarily to chemotherapy due to lack of targeted therapies typically used for other breast cancer types, hence necessitating research for improved therapeutic strategies and outcomes. The neutrophil and lymphocyte percentages, absolute counts, and the ratio of neutrophils to lymphocytes were evaluated in peripheral blood of 81 patients with triple-negative breast cancer (TNBC) and 25 healthy controls. This study observed trend of high neutrophil percentage was observed in patients with positive lymph node status as compared to negative lymph node status. Significant high absolute neutrophil count was observed in patients with positive LN status, High BR score and presence of metastasis. A trend of high neutrophil to lymphocyte ratio was observed in patients with presence of perineural invasion, presence of necrosis, and patients with presence of metastasis.

Bioinformatics analysis of markers based on m6A related to prognosis combined with immune invasion of rectal adenocarcinoma.

Colorectal cancer (CRC) is a common form of cancer, with rectal cancer accounting for approximately one-third of all cases. Among rectal cancers, 95% are classified as rectal adenocarcinoma (READ). Emerging evidence suggests that long noncoding RNAs (lncRNAs) play a significant role in the development and progression of various cancers. In our study, we aimed to identify differentially expressed lncRNAs potentially associated with m6A and establish a risk assessment model to predict clinical outcomes for READ patients. The READ dataset from the TCGA database was utilized in this study to synergistically and logically integrate m6A and lncRNA, while employing bioinformatics technology for the identification of suitable biomarkers. A risk prediction model comprising m6A-associated lncRNAs was constructed to investigate the prognostic, diagnostic, and biological functional relevance of these m6A-related lncRNAs. Our research builds a composed of three related to m6A lncRNA rectal gland cancer prognosis model, and the model has been proved in the multi-dimensional can serve as the potential of the prognosis of rectal gland cancer biomarkers. Our study constructed a prognostic model of rectal adenocarcinoma consisting of three related m6A lncRNAs: linc00702, ac106900.1 and al583785.1. The model has been validated as a potential prognostic biomarker for rectal cancer in multiple dimensions, aiming to provide clinicians with an indicator to assess the duration of straight adenocarcinoma. This enables early detection of rectal cancer and offers a promising target for immunotherapy.

MIF as a potential diagnostic and prognostic biomarker for triple-negative breast cancer that correlates with the polarization of M2 macrophages.

Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that plays a crucial role in antitumor immunity. However, the role of MIF in influencing the tumor microenvironment (TME) and prognosis of triple-negative breast cancer (TNBC) remains to be elucidated. Using R, we analyzed single-cell RNA sequencing (scRNA-seq) data of 41 567 cells from 10 TNBC tumor samples and spatial transcriptomic data from two patients. Relationships between MIF expression and immune cell infiltration, clinicopathological stage, and survival prognosis were determined using samples from The Cancer Genome Atlas (TCGA) and validated in a clinical cohort using immunohistochemistry. Analysis of scRNA-seq data revealed that MIF secreted by epithelial cells in TNBC patients could regulate the polarization of macrophages into the M2 phenotype, which plays a key role in modulating the TME. Spatial transcriptomic data also showed that epithelial cells (tumor cells) and MIF were proximally located. Analysis of TCGA samples confirmed that tumor tissues of patients with high MIF expression were enriched with M2 macrophages and showed a higher T stage. High MIF expression was significantly associated with poor patient prognosis. Immunohistochemical staining showed high MIF expression was associated with younger patients and worse clinicopathological staging. MIF secreted by epithelial cells may represent a potential biomarker for the diagnosis and prognosis of TNBC and may promote TNBC invasion by remodeling the tumor immune microenvironment.

Identification of NR3C2 as a functional diagnostic and prognostic biomarker and potential therapeutic target in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC), including the lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes, is a malignant tumor type with a poor 5-year survival rate. The identification of new powerful diagnostic biomarkers, prognostic biomarkers, and potential therapeutic targets in NSCLC is urgently required. The UCSC Xena, UALCAN, and GEO databases were used to screen and analyze differentially expressed genes, regulatory modes, and genetic/epigenetic alterations in NSCLC. The UCSC Xena database, GEO database, tissue microarray, and immunohistochemistry staining analyses were used to evaluate the diagnostic and prognostic values. Gain-of-function assays were performed to examine the roles. The ESTIMATE, TIMER, Linked Omics, STRING, and DAVID algorithms were used to analyze potential molecular mechanisms. NR3C2 was identified as a potentially important molecule in NSCLC. NR3C2 is expressed at low levels in NSCLC, LUAD, and LUSC tissues, which is significantly related to the clinical indexes of these patients. Receiver operating characteristic curve analysis suggests that the altered NR3C2 expression patterns have diagnostic value in NSCLC, LUAD, and especially LUSC patients. Decreased NR3C2 expression levels can help predict poor prognosis in NSCLC and LUAD patients but not in LUSC patients. These results have been confirmed both with database analysis and real-world clinical samples on a tissue microarray. Copy number variation contributes to low NR3C2 expression levels in NSCLC and LUAD, while promoter DNA methylation is involved in its downregulation in LUSC. Two NR3C2 promoter methylation sites have high sensitivity and specificity for LUSC diagnosis with clinical application potential. NR3C2 may be a key participant in NSCLC development and progression and is closely associated with the tumor microenvironment and immune cell infiltration. NR3C2 co-expressed genes are involved in many cancer-related signaling pathways, further supporting a potentially significant role of NR3C2 in NSCLC. NR3C2 is a novel potential diagnostic and prognostic biomarker and therapeutic target in NSCLC.

Biological functions and therapeutic potential of SRY related high mobility group box 5 in human cancer.

Cancer is a heavy human burden worldwide, with high morbidity and mortality. Identification of novel cancer diagnostic and prognostic biomarkers is important for developing cancer treatment strategies and reducing mortality. Transcription factors, including SRY associated high mobility group box (SOX) proteins, are thought to be involved in the regulation of specific biological processes. There is growing evidence that SOX transcription factors play an important role in cancer progression, including tumorigenesis, changes in the tumor microenvironment, and metastasis. SOX5 is a member of SOX Group D of Sox family. SOX5 is expressed in various tissues of human body and participates in various physiological and pathological processes and various cellular processes. However, the abnormal expression of SOX5 is associated with cancer of various systems, and the abnormal expression of SOX5 acts as a tumor promoter to promote cancer cell viability, proliferation, invasion, migration and EMT through multiple mechanisms. In addition, the expression pattern of SOX5 is closely related to cancer type, stage and adverse clinical outcome. Therefore, SOX5 is considered as a potential biomarker for cancer diagnosis and prognosis. In this review, the expression of SOX5 in various human cancers, the mechanism of action and potential clinical significance of SOX5 in tumor, and the therapeutic significance of Sox5 targeting in cancer were reviewed. In order to provide a new theoretical basis for cancer clinical molecular diagnosis, molecular targeted therapy and scientific research.

Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression. Meanwhile, we constructed a multi-omics prognostic model that suggested the patients exhibiting downregulated expression of NETs may have an unfavorable outcome. We also confirmed TLR2 as a potent prognosis factor and patients with low TLR2 expression had more effective T cells and an overall survival extension for 6 months. Targeting TLR2 might be a promising strategy to reverse immunosuppression and control tumor progression for an improved prognosis.

Integrative analyses identified gap junction beta-2 as a prognostic biomarker and therapeutic target for breast cancer.

Increasing evidence has shown that connexins are involved in the regulation of tumor development, immune escape, and drug resistance. This study investigated the gene expression patterns, prognostic values, and potential mechanisms of connexins in breast cancer. We conducted a comprehensive analysis of connexins using public gene and protein expression databases and clinical samples from our institution. Connexin mRNA expressions in breast cancer and matched normal tissues were compared, and multiomics studies were performed. Gap junction beta-2 mRNA was overexpressed in breast cancers of different pathological types and molecular subtypes, and its high expression was associated with poor prognosis. The tumor membrane of the gap junction beta-2 mutated group was positive, and the corresponding protein was expressed. Somatic mutation and copy number variation of gap junction beta-2 are rare in breast cancer. The gap junction beta-2 transcription level in the p110α subunit of the phosphoinositide 3-kinase mutant subgroup was higher than that in the wild-type subgroup. Gap junction beta-2 was associated with the phosphoinositide 3-kinase-Akt signaling pathway, extracellular matrix-receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, gap junction beta-2 overexpression may be associated with phosphoinositide 3-kinase and histone deacetylase inhibitor resistance, and its expression level correlated with infiltrating CD8+ T cells, macrophages, neutrophils, and dendritic cells. Gap junction beta-2 may be a promising therapeutic target for targeted therapy and immunotherapy and may be used to predict breast cancer prognosis.

A novel aptamer-antibody sandwich electrochemical sensor for detecting ADAR1 in complex biological samples

Human adenosine deaminase acting on RNA1 (ADAR1) is an adenosine-to-inosine (A-to-I) RNA-editing enzyme involved in various types of cancer progression. ADAR1 has emerged as a novel prognostic biomarker for cancer. This study describes the application of a newly identified 70-nt DNA aptamer (Apt38483) against ADAR1 to develop a portable and simple electrochemical biosensor platform for the rapid and sensitive detection of ADAR1 in cell lysates. We selected an ADAR1-specific DNA aptamer from a randomized 70-nt single-stranded DNA library using a competitive in vitro selection method. ADAR1 in the cell lysate was sandwiched onto a bare carbon working electrode of an electro-chemically printed chip between the ADAR1 antibody and gold nanoparticles (40 nm) conjugated with Apt38483, followed by electrochemical analysis using differential pulse voltammetry (DPV) for sensor demonstration. A highly sensitive change in current was observed for as little as 0.53 nM ADAR1 in human embryonic kidney cell lysate. Thus, the merging of a novel DNA aptamer probe for ADAR1 with an electrochemical transduction method enabled the development of a simple, low-cost, and rapid method for the direct measurement of ADAR1 in cell lysates and indicated great potential for the development of an ADAR1 analysis platform, which would be useful in cancer prognosis.

Evaluation of the Immunohistochemical Scoring System of CDX2 Expression as a Prognostic Biomarker in Colon Cancer.

Encoded by the CDX2 homeobox gene, the CDX2 protein assumes the role of a pivotal transcription factor localized within the nucleus of intestinal epithelial cells, orchestrating the delicate equilibrium of intestinal physiology while intricately guiding the precise development and differentiation of epithelial tissue. Emerging research has unveiled that positive immunohistochemical expression of this protein shows that the CDX2 gene exerts a potent suppressive impact on tumor advancement in colorectal cancer, impeding the proliferation and distant dissemination of tumor cells, while the inhibition or suppression of CDX2 frequently correlates with aggressive behavior in colorectal cancer. In this study, we conducted an immunohistochemical assessment of CDX2 expression on a cohort of 43 intraoperatively obtained tumor specimens from patients diagnosed with colon cancer at Colțea Clinical Hospital in Bucharest, between April 2019 and December 2023. Additionally, we shed light on the morphological diversity within colon tumors, uncovering varying differentiation grades within the same tumor, reflecting the variations in CDX2 expression as well as the genetic complexity underlying these tumors. Based on the findings, we developed an innovative immunohistochemical scoring system that addresses the heterogeneous nature of colon tumors. Comprehensive statistical analysis of CDX2 immunohistochemical expression unveiled significant correlations with known histopathological parameters such as tumor differentiation grades (p-value = 0.011) and tumor budding score (p-value = 0.002), providing intriguing insights into the complex involvement of the CDX2 gene in orchestrating tumor progression through modulation of differentiation processes, and highlighting its role in metastatic predisposition. The compelling correlation identified between CDX2 expression and conventional histopathological parameters emphasizes the prognostic significance of the CDX2 biomarker in colon cancer. Moreover, our novel immunohistochemical scoring system reveals a distinct subset of colon tumors exhibiting reserved prognostic outcomes, distinguished by their "mosaic" CDX2 expression pattern.

EMP1 correlated with cancer progression and immune characteristics in pan-cancer and ovarian cancer.

This study examines the prognostic role and immunological relevance of EMP1 (epithelial membrane protein-1) in a pan-cancer analysis, with a focus on ovarian cancer. Utilizing data from TCGA, CCLE, and GTEx databases, we assessed EMP1 mRNA expression and its correlation with tumor progression, prognosis, and immune microenvironment across various cancers. Our results indicate that EMP1 expression is significantly associated with poor prognosis in multiple cancer types, including ovarian, bladder, testicular, pancreatic, breast, brain, and uveal melanoma. Immune-related analyses reveal a positive correlation between EMP1 and immune cell infiltration, particularly neutrophils, macrophages, and dendritic cells, as well as high expression of immune checkpoint such as CD274, HAVCR2, IL10, PDCD1LG2, and TGFB1 in most tumors. In vivo experiments confirm that EMP1 promotes ovarian cancer cell proliferation, metastasis, and invasion. In conclusion, EMP1 emerges as a potential prognostic biomarker and therapeutic target in various cancers, particularly ovarian cancer, due to its influence on tumor progression and immune cell dynamics. Further research is warranted to elucidate the precise mechanisms of EMP1 in cancer biology and to translate these findings into clinical applications.

A comprehensive evaluation of serum circCSPP1 as a novel diagnostic and prognostic biomarker for gastric cancer

PurposeGastric cancer (GC) has high incidence and mortality due to its low early screening efficiency. Circular RNAs (CircRNAs) are a new class of non-coding RNAs which is closely related to GC. Nevertheless, the clinical application value of circRNAs in GC are largely unknown. Therefore, we studied the role of a novel circRNA named circCSPP1 in patients with GC. MethodsCircRNA sequencing was performed to screen out the target molecule. Real-time fluorescent quantitative PCR (RT-qPCR) was utilized to detect the expression level of circCSPP1 in GC tissues, cells, and serum. Gel and Sanger sequencing were utilized to verify the ring structure of circCSPP1. RNase R enzyme digestion experiment and actinomycin D experiment were verifed the advantage of circCSPP1 as a diagnostic biomarker in patients with GC when that compared with linear RNA. The correlation between the expression level of serum circCSPP1 and clinicopathological data of GC patients was further analyzed. Receiver operating characteristic curve (ROC) and the area under ROC curve (AUC) were utilied to evaluate the diagnostic performance. ResultsCircCSPP1 has a circular structure which with resistance to RNA exonuclease digestion and long half-life compared with linear RNA. In our study, circCSPP1 was first found up-regulated in patients with GC. Serum circCSPP1 level was decreased significantly after surgical resection whereas increased after recurrence. High expression of circCSPP1 was associated with poor survival rates. The expression level of circCSPP1 was significantly correlated to tumor size, T stage, lymph node metastasis, and TNM stage. The AUC of serum circCSPP1 was 0.834, with high sensitivity and specificity in discriminating patients with GC from healthy donors. More importantly, the combined diagnosis of circCSPP1, CEA, and CA19–9 achieved the superior AUC of 0.882, with the highest specificity. ConclusionSerum circCSPP1 may prove to be a potential non-invasive auxiliary diagnostic biomarker for patients with GC.

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer.

Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized. We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease. There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947). Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

CXCL10 could be a prognostic and immunological biomarker in bladder cancer

IntroductionAs proteins that promote immune cell differentiation, chemokines have attracted great interest regarding their role in anti-tumor immune responses within the cancer environment. However, the exact role of CXCL10, a chemokine, in bladder cancer (BLCA) is still not fully elucidated.MethodIn the present study, we employed bioinformatics approaches to examine the expression pattern, prognostic value, and immune infiltration of CXCL10 in BLCA. Furthermore, we focused on examining the impact of CXCL10 on immune therapy in BLCA. Additionally, we validated the expression of CXCL10 in various BLCA cell lines using PCR techniques.ResultsWe observed an upregulation of CXCL10 in BLCA tissues as well as in different cell lines. Additionally, upregulation of CXCL10 indicates a better prognosis for BLCA patients. ESTIMATE and CIBERSORT algorithms suggest that CXCL10 is closely associated with the immune microenvironment of BLCA. Through multiple immune therapy cohorts, we also identified that CXCL10 has shown promising predictive value for assessing the efficacy of immune therapy in in BLCA.ConclusionOur study indicates that CXCL10 has the potential to serve as a favorable prognostic factor and is strongly associated with immune infiltration in BLCA.Graphical

Prognostic Value of B7H4 Expression in Patients with Solid Cancers: A Systematic Review and Meta-Analysis.

V-set domain-containing T-cell activation inhibitor 1 (aliases VTCN1, B7H4) participates in tumour immune escape by delivering inhibitory signals to T cells. The purpose of this article was to assess the B7H4 prognostic value in solid cancers. Three databases were searched for relevant articles. The main endpoints were overall survival (OS), disease-specific survival (DSS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-free survival (DFS). Appropriate hazard ratios (HRs) were pooled. The R studio software (version 4.0.3) was used for data analysis. Thirty-one studies met the inclusion criteria. High expression of B7H4 was associated with worse OS (HR = 1.52, 95% CI: 1.37-1.68) but not with DSS (HR = 1.14, 95% CI: 0.49-2.63), RFS (HR = 1.77, 95% CI: 0.75-4.18), DFS (HR = 1.29, 95% CI: 0.8-2.09), or PFS (HR = 1.71, 95% CI: 0.91-3.2) in patients with solid cancers. High expression of B7H4 is associated with a poorer prognosis in patients with solid cancers. B7H4 is a promising prognostic biomarker and immunotherapeutic target for various solid cancers because of its activity in cancer immunity and tumourigenesis.

Utility of neutrophil-to-lymphocyte ratio as an indicator of tumor immune status in non-small cell lung cancer.

Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic biomarker in non-small cell lung cancer (NSCLC); however, the underlying biological rationale remains unclear. The present study aimed to explore the potential utility of NLR as a surrogate biomarker for immune response to cancer and to elucidate the underlying mechanism. This retrospective study included the medical records of 120 patients with NSCLC who underwent surgery at the study institution in 2012. NLR in peripheral blood was determined from blood test within 30days before surgery. Tumor immune status was evaluated using immunohistochemical staining to identify CD3+, CD8+ and FOXP3+ tumor-infiltrating lymphocytes (TILs), and the relationship of NLR, with clinicopathologic characteristics including 5-year overall survival (OS), and the tumor immune status was investigated. The median values of NLR and TIL count were used as cutoff points. The 5-year OS was significantly better in patients with low NLR (<2.2) than in those with high NLR (≥2.2) (70.1% vs. 56.8%, P=0.042) and in patients with high CD3+ TIL count (≥242) than in those with low CD3+ TIL count (<242) (70% vs. 56.8%, P=0.019). Additionally, the CD3+ TIL count was negatively correlated with preoperative NLR (P=0.005). NLR might potentially reflect the immune status of tumor microenvironment, explaining its impact on prognosis of patients with NSCLC.