Cancer Biomarkers最新文献

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Breast cancer is a major cause of female deaths, especially in underdeveloped countries. It can be treated if diagnosed early and chances of survival are high if treated appropriately and timely. For timely and accurate automated diagnosis, machine learning approaches tend to show better results than traditional methods, however, accuracy lacks the desired level. This study proposes the use of an ensemble model to provide accurate detection of breast cancer. The proposed model uses the random forest and support vector classifier along with automatic feature extraction using an optimized convolutional neural network (CNN). Extensive experiments are performed using the original, as well as, CNN-based features to analyze the performance of the deployed models. Experimental results involving the use of the Wisconsin dataset reveal that CNN-based features provide better results than the original features. It is observed that the proposed model achieves an accuracy of 99.99% for breast cancer detection. Performance comparison with existing state-of-the-art models is also carried out showing the superior performance of the proposed model.

Background: Papillary thyroid carcinoma (PTC) is the most frequent thyroid malignancy. Histopathological examination is widely accepted as the gold standard test for the diagnosis of PTC. However, the histopathological examination sometimes can't differentiate PTC from other thyroid diseases. Differentiating PTC from other thyroid diseases is essential for a therapeutic approach and prognosis.

Objectives: The current study was performed to investigate the utility of TROP-2, SPL-2, and CXCL12 mRNA and protein expression in discriminating PTC from other thyroid diseases that mimic PTC.

Methods: The current study was performed on 75 cases of surgically resected thyroid glands. The cases were distributed in two groups: the PTC group and the non-PTC group. The PTC group consisted of 35 cases (25 patients of the classic PTC variant and 10 patients of the PTC follicular variant). The non-PTC group consisted of 40 cases (10 cases were multinodular goiter, 5 cases were Graves' disease, 5 cases were Hashimoto thyroiditis, 15 patients were follicular adenoma (FA) and 5 cases were follicular carcinoma). TROP-2, SPL-2, and CXCL12 mRNA expression were estimated by qRT-PCR, and protein expression was estimated by immunohistochemistry.

Results: There were upregulated TROP-2, SPL-2, and CXCL12 mRNA and protein expressions in PTC compared to non-PTC (P< 0.001, for each). There was a statistically significant upregulation in the mRNA expression of the three genes among PTC cases with larger tumor sizes (P< 0.001, for each), those with tumor stages III and IV (P= 0.008, 0.002 and < 0.001 respectively), and those with LN metastasis (P< 0.001, for each). Moreover, there was a statistically significant upregulation in CXCL-12 gene expression among PTC cases with extra-thyroid extension (P< 0.001).

Conclusion: mRNA expression of TROP-2, SPL-2, and CXCL12 among PTC cases increased in larger tumor size, tumor stages III and IV, and LN metastasis. Moreover, there was an increase in CXCL-12 gene expression among PTC cases with extra-thyroid extension. Thus, TROP-2, SPL-2, and CXCL12 expressions could be possible diagnostic and prognostic markers in PTC.

Background: FAM170B-AS1 is usually expressed low in all organs except for testicular tissues. No study was performed to explore its role in breast cancer (BC). Contradictory results were reported about hsa-miR-1202 and hsa-miR-146a-5p in BC.

Objective: The present study aimed to explore the involvement of FAM170B-AS1 in BC using bioinformatics predictive tools, followed by a practical validation besides exploring the impact of hsa-miR-1202 and hsa-miR-146a-5p in BC.

Methods: This study enrolled 96 female patients with BC, 30 patients with benign breast diseases (BBD), and 25 control subjects. The expressions of circulating FAM170B-AS1, hsa-miR-1202, and hsa-miR-146a-5p were quantified using qRT-PCR. These ncRNAs' associations, predictive, and diagnostic roles in BC were statistically tested. The underlying miRNA/mRNA targets of FAM170B-AS1 in BC were bioinformatically predicted followed by confirmation based on the GEPIA and TCGA databases.

Results: The expression of FAM170B-AS1 was upregulated in sera of BC patients and hsa-miR-1202 was upregulated in sera of BBD and BC patients while that of hsa-miR-146a-5p was downregulated in BC. These FAM170B-AS1 was significantly associated with BC when compared to BBD. FAM170B-AS1 and hsa-miR-1202 were statistically associated with the BC's stage, grade, and LN metastasis. FAM170B-AS1 and hsa-miR-146a-5p gave the highest specificity and sensitivity for BC. KRAS and EGFR were predicted to be targeted by FAM170B-AS1 through interaction with hsa-miR-143-3p and hsa-miR-7-5p, respectively. Based on the TCGA database, cancer patients having mutations in FAM170B show good overall survival.

Conclusions: The present study reported that for the first time, FAM170B-AS1 may be a potential risk factor, predictive, and diagnostic marker for BC. In addition, FAM170B-AS1 might be involved in BC by interacting with hsa-miR-143-3p/KRAS and hsa-miR-7-5p/EGFR through enhancement or repression that may present a new therapeutic option for BC.

Background: Osteosarcoma (OS) is a relatively rare malignant bone tumor in teenagers; however, its molecular mechanisms are not yet understood comprehensively.

Objective: The study aimed to use necroptosis-related genes (NRGs) and their relationships with immune-related genes to construct a prognostic signature for OS.

Methods: TARGET-OS was used as the training dataset, and GSE 16091 and GSE 21257 were used as the validation datasets. Univariate regression, survival analysis, and Kaplan-Meier curves were used to screen for hub genes. The immune-related targets were screened using immune infiltration assays and immune checkpoints. The results were validated using nomogram and decision curve analyses (DCA).

Results: Using univariate Cox regression analysis, TNFRSF1A was screened from 14 NRGs as an OS prognostic signature. Functional enrichment was analyzed based on the median expression of TNFRSF1A. The prognosis of the TNFRSF1A low-expression group in the Kaplan-Meier curve was notably worse. Immunohistochemistry analysis showed that the number of activated T cells and tumor purity increased considerably. Furthermore, the immune checkpoint lymphocyte activation gene 3 (LAG-3) is a possible target for intervention. The nomogram accurately predicted 1-, 3-, and 5-year survival rates. DCA validated the model (C = 0.669).

Conclusion: TNFRSF1A can be used to elucidate the potential relationship between the immune microenvironment and NRGs in OS pathogenesis.

Background: Long-chain noncoding RNA (lncRNA), LINC01569, is important for regulating the extracellular matrix, which affects cell migration. However, its involvement in the occurrence and development of triple-negative breast cancer (TNBC) remains unclear.

Objective: This study is aimed to investigate the role of LINC01569 on TNBC.

Methods: Online database was used for clinical data analysis. Cell viability and migration capability were monitored using cell counting kit-8 and transwell assays, respectively. Luciferase reporter assay and RNA pull-down were used to confirm the binding capability between noncoding RNAs and filamin A-interacting protein 1-like (FILIP1L). Western blotting was used to determine the protein content.

Results: Compared with normal breast tissue, LINC01569 was significantly reduced in patients with TNBC subtype, and LINC01569 expression gradually decreased with the progression of tumor stage. Patients with TNBC with high lncRNA LINC01569 levels had a better prognosis than did patients with low LINC01569 levels. LINC01569 overexpression inhibited the migration capability, whereas siRNA-mediated LINC01569 downregulation promoted the migration capability in TNBC cells. Using ENCORI and lncRNA SNP online databases, miR-300 was screened as the potential sponge of LINC01569. The binding of LINC01569 to miR-300 was confirmed using the dual-luciferase reporter and RNA pull-down assays. miR-300 was negatively correlated with LINC01569, and miR-300 mimics eliminated the anti-proliferation and anti-migration effects of LINC01569 on TNBC cells. Additionally, FILIP1L was further verified as the downstream target of miR-300. miR-300 mimics blocked LINC01569 upregulation-mediated elevation of FILIP1L. Importantly, the anti-tumor effects mediated by LINC01569 overexpression were abolished by miR-300 mimics and further restored by FILIP1L upregulation.

Conclusions: LINC01569 was expressed at a low level in TNBC and could sponge miR-300 to promote FILIP1L expression, reducing the proliferation and metastasis capability of TNBC. Thus, LINC01569 might be a useful biomarker in the diagnosis and prognosis of metastatic TNBC.

Background: Our study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis.

Methods: The data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis. GEPIA was used to verify the expression of Hub genes and evaluate its prognostic value. The protein expression of Hub gene in CRC was analyzed using the Human Protein Atlas database. The cBioPortal was used to analyze the type and frequency of Hub gene mutations, and the effects of mutation on the patients' prognosis. The TIMER database was used to study the correlation between Hub genes and immune infiltration in CRC. Gene set enrichment analysis (GSEA) was used to explore the biological function and signal pathway of the Hub genes and corresponding co-expressed genes.

Results: We identified 346 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. Four Hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and differential expression validation. The protein and mRNA expression levels of AURKA, CCNB1, EXO1 and CCNA2 were higher in CRC tissues than in adjacent tissues. There were varying degrees of immune cell infiltration and gene mutation of Hub genes, especially B cells and CD8+ T cells. The results of GSEA showed that Hub genes and their co-expressed genes mainly participated in chromosome segregation, DNA replication, translational elongation and cell cycle.

Conclusion: Overexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis for CRC and this effect was correlation with gene mutation and infiltration of immune cells.

Background: Gastric cancer (GC) is one of the most common tumors. There were several classifications of GC recently. The value of Lauren classification in evaluating the prognosis after radical gastrectomy was still unclear and the prognosis of gastric cancer remained relatively poor in the absence of prognostic biomarkers. This study aimed to explore microRNA (miRNA) in the prognosis of GC with different Lauren classification.

Methods: A retrospective study of 1144 patients was performed in this study. Quantificational reverse transcription-PCR (qRT-PCR) was used to examine the expression of miRNAs. Univariate and multivariate analysis were performed to evaluate prognosis value of Lauren classification.

Results: Total 1144 GC patients were recruited in this cohort, including 302 diffuse type (26.4%), 436 intestinal type (38.1%) and 406 mixed type (35.5%) GC. Multivariate analysis showed that Lauren classification, patients' age, tumor size, tumor infiltrating depth, vascular nerve infiltrating and metastatic lymph nodes ration were significantly correlated with GC patients' OS and DFS. The miR-141-3p, miR-200b-3p and miR-133a-5p were significantly down-regulated in diffuse type compared to intestinal type GC tissues, the miR-105-5p had significant lower expression in diffuse type compared with intestinal type and mixed type GC tissues. As a consequence of univariate analysis, low miR-141-3p in diffuse type GC showed significant worse OS and DFS than high miR-141-3p.

Conclusions: Lauren classification was an independent prognostic factor in GC. MiR-141-3p was an independent prognostic factor and a promising prognostic biomarker in Lauren classification GC.

Objective: This article aims to investigate the clinical value of hemoglobin/red cell distribution width ratio (Hb/RDW), C-reactive protein/albumin ratio (CAR) and plateletcrit (PCT) combined with carcinoembryonic antigen (CEA) in colorectal cancer (CRC) auxiliary diagnosis.

Methods: We retrospectively analyzed in 718 subjects (212 with CRC, 209 with benign colorectal lesions (BCL), 111 with other cancers, and 186 healthy controls).

Results: The CAR, PCT, and CEA in the CRC group were higher than those in the BCL, other cancers, and the healthy control group. However, Hb/RDW in the CRC group was lower than the other three groups. Moreover, there were significant differences in Hb/RDW and CEA among different T-N-M stages (all P< 0.05). Multivariate logistic regression showed that low level of Hb/RDW and high level of CAR, CEA, PCT were risk factors for CRC, and are correlated with CRC stage. Additionally, the area under the receiver operating characteristic curve (AUC) of Hb/RDW+CEA (AUC: 0.735), CAR+CEA (AUC: 0.748), PCT+CEA (AUC: 0.807) was larger than that of Hb/RDW (AUC: 0.503), CAR (AUC: 0.614), or PCT (AUC: 0.713) alone (all P< 0.001) in distinguishing CRC from BCL.

Conclusions: Hb/RDW, CAR, PCT, and CEA are independent risk factors for CRC. Hb/RDW, CAR, and PCT combined with CEA have significant value for auxiliary differential diagnosis of CRC and BCL.

Background: Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that seriously threatens human health. Rho GTPase-activating protein 4 (ARHGAP4) plays an important role in the occurrence and development of tumors.

Objective: The purpose of this study was to explore the role of ARHGAP4 in the progression of KIRC and its diagnostic and prognostic value.

Methods: Multiple analytical methods and in vitro cell assays were used to explore the expression of ARHGAP4 and its value in the progression, diagnosis and prognosis of KIRC. The biological function of ARHGAP4 was studied by GO analysis and KEGG pathway analysis, and then the relationship between ARHGAP4 and immune infiltration was analyzed.

Results: The expression of ARHGAP4 was significantly up-regulated in KIRC. We found that the high expression of ARHGAP4 was related to the progression of KIRC and suggested a poor prognosis. Compared with normal tissues, ARHGAP4 had a better diagnostic value in KIRC. The biological function of ARHGAP4 was related to immunity, and its expression was also closely related to tumor immune infiltration and immune checkpoints.

Conclusions: Our study demonstrated that ARHGAP4 may be a biomarker, which is related to the progression, diagnosis and prognosis of KIRC. Its biological functions are related to tumor immune infiltration.