RNA-Associated Co-expression Network Identifies Novel Biomarkers for Digestive System Cancer

ACP-CLB: An Anticancer Peptide Prediction Model Based on Multichannel Discriminative Processing and Integration of Large Pretrained Protein Language Models

MOTIVATION

Cancer affects millions globally, and as research advances, our understanding and treatment of cancer evolve. Compared to conventional treatments with significant side effects, anticancer peptides (ACPs) have gained considerable attention. Validating ACPs through wet-lab experiments is time-consuming and costly. However, numerous artificial intelligence methods are now used for ACP identification and classification. These methods typically apply a uniform strategy to all feature types, overlooking the potential benefits of more specialized processing for different feature types.

INNOVATION

In this paper, we propose a framework based on multichannel discriminative processing, where different neural networks are applied to process various feature types, optimizing their respective feature vectors. Additionally, we leverage Large Pretrained Protein Language Models to capture deeper sequence features, further enhancing the model's performance. Contributions: To better validate the overall performance and generalization ability of the model, we compared it with state-of-the-art models using four different data sets (AntiCp2Main, AntiCp2 Alternate, ACP740, cACP-DeepGram). The results show significant improvements across most metrics. Additionally, our proposed framework better assists researchers in distinguishing and identifying ACPs and further validates the need for distinct processing methods for different feature types.

The predictive value of miR-29b-2-5p on the prognosis of cervical cancer and its inhibitory effect on cervical cancer progression

OBJECTIVE

The poor prognosis of cervical cancer patients leads to an annual increase in mortality, while microRNAs are involved in various cancers, including cervical cancer. This study aimed to investigate the clinical value and possible effect of miR-29b-2-5p on the progression of cervical cancer.

METHODS

The expression level of miR-29b-2-5p in cervical cancer tissues and cells was analyzed by polymerase chain reaction. The Kaplan-Meier curve was used to evaluate the role of miR-29b-2-5p in cervical cancer prognosis. The independent prognostic factors of cervical cancer were explored by the multivariate Cox regression analysis. The effect of miR-29b-2-5p on the proliferation, migration, and invasion of cervical cancer cells was determined by in vitro cell experiments.

RESULTS

A significantly downregulated miR-29b-2-5p expression was observed in cervical cancer tumor tissues and cervical cancer cells compared with the adjacent tumor tissues (tissues of the negative surgical margin) and H8 cells, respectively. Higher miR-29b-2-5p expression correlated with a better 5-year progression-free survival of cervical cancer. MiR-29b-2-5p was also associated with the indicators (tumor size, tumor differentiation, FIGO (International Federation of Gynecology and Obstetrics) stage, and invasion depth) of the progression of cervical cancer tumors. And miR-29b-2-5p, along with tumor size, tumor differentiation, FIGO stage, histology type, and invasion depth, were independent prognostic factors for poor cervical cancer prognosis. MiR-29b-2-5p showed a suppressive effect on the proliferation, migration, and invasion of cervical cancer cells.

CONCLUSIONS

MiR-29b-2-5p was downregulated in cervical cancer tumor tissues and could serve as an independent prognostic factor for cervical cancer. The overexpressed miR-29b-2-5p could be considered a tumor suppressor to inhibit the progression of cervical cancer.

Novel miRNA markers and their mechanism of esophageal squamous cell carcinoma (ESCC) based on TCGA

MicroRNAs(miRNAs) are promising biomarkers for early esophageal squamous cell carcinoma (ESCC) detection and prognostic prediction. This study aimed to explore the potential biomarkers and molecular pathogenesis in the early diagnosis of ESCC. Firstly, 48 differentially expressed miRNAs (DEMs) and 1319 differentially expressed genes (DEGs) were identified between 94 ESCC tissues and 13 normal esophageal tissues in TCGA. From miRNA-mRNA regulatory network, there are 6558 target genes of the 48 DEMs, where 400 target genes are also among 1319 DEGs. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment indicate that the 400 DEGs significantly enriched in cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and oocyte meiosis. And there are 66 DEGs among these six biological pathways, which we called GO-DEGs. From miRNA-mRNA regulatory network, 32 DEMs regulated the 66 GO-DEGs, where 22 DEMs were verified by different types of experiments in ESCC tissues, cells, or serum from the literature. For the other novel 10 DEMs, single-factor Cox regression analysis show that only hsa-miR-34b-3p showed no significant correlation with the overall survival of ESCC patients. Finally, we obtained the novel 9 ESCC-related DEMs, where three are down-regulated, and six are up-regulated. We analyzed the expression trends of target genes for five miRNAs and identified three significantly different miRNAs (hsa-miR-205-3p, hsa-miR-452-3p, and hsa-miR-6499-3p) confirmed by qPCR. Moreover, the stage-specific miRNAs were also suggested. These three qPCR validated miRNAs are also specific to the early stages of ESCC: hsa-miR-452-3p is specific to Stage I, II and III; hsa-miR-205-3p is specific in Stage II and III; and hsa-miR-6499-3p is Stage II specific. They might be the potential biomarkers for ESCC stage diagnosis. This study identified three novel miRNA markers potentially related to the diagnosis of ESCC and participated in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway for oocyte meiosis.

Oncogenic role of SKA2 and its ceRNA network in hepatocellular carcinoma based on a comprehensive analysis

Background

Genetic alterations have important roles in cancer development and progression. SKA2 (spindle and kinetochore associated complex subunit 2) is a mitotic component that plays a critical role in maintaining the silence of the metaphase plate and spindle checkpoint. However, the exact role of SKA2 in hepatocellular carcinoma (HCC) remains unclear. The current study aimed to comprehensively identify the function of SKA2 in HCC.

Methods

We utilized various databases and bioinformatics tools, such as The Cancer Genome Atlas (TCGA), survminer package, Tumor Immune Estimation Resource (TIMER), cBioPortal website, clusterProfiler package, gene set enrichment analysis (GSEA), miRWalk, TargetScanHuman8.0, miRDB, DIANA and Cytoscape to identify the role of SKA2 in HCC.

Results

Our results showed that patients with HCC exhibited a high SKA2 expression. Further, the SKA2 high expression group had a worse overall survival (OS). And SKA2 was associated with tumor stage and the immune system. In addition, 188 co-expression genes of SKA2 participated in some processes including cell cycle, DNA replication and so on. The tumor had a lower hsa-miR-19b-1-5p and hsa-miR-378a-5p expression, and these two microRNAs (miRNAs) were also correlated with OS. SNHG14, SNHG15, and SPCA6P-AS were significantly negatively correlated with hsa-378a-5p, and these three long non-coding RNAs (lncRNAs) showed a positive correlation with SKA2 (P<0.05). SKA2 is a member of competing endogenous RNA (ceRNA). Moreover, it is related to SPACA6P-AS/hsa-miR-378a-5p/SKA2, SNHG14/hsa-miR-378a-5p/SKA2, and SNHG15/hsa-miR-378a-5p/SKA2, which play significant roles in tumor progression.

Conclusions

SKA2 is associated with OS, tumor stage, and immune infiltrating cells in HCC. Thus, we propose that SKA2 functions as a ceRNA and influences tumorigenesis. These findings lay the foundation for future research in the field of HCC.

Identification of Long Noncoding RNAs Expression Profiles Between Gallstone and Gallbladder Cancer Using Next-Generation Sequencing Analysis

Background

Gallstone disease (GS) is an important risk factor for Gallbladder cancer (GBC). However, the mechanisms of the progression of GS to GBC remain unclear. Long non-coding RNA (lncRNA), modulates DNA/RNA/proteins at epigenetic, pre-transcriptional, transcriptional and posttranscriptional levels, and plays a potential therapeutic role in various diseases. This study aims to identify lncRNAs that have a potential impact on GS-promoted GBC progression.

Methods and Results

Six GBC patients without GS, six normal gallbladder tissues, nine gallstones and nine GBC patients with GS were admitted to our hospital. The next-generation RNA-sequencing was performed to analyze differentially expressed (DE) lncRNA and messenger RNA (mRNA) in four groups. Then overlapping and specific molecular signatures were analyzed. We identified 29 co-DEGs and 500 co-DElncRNAs related to gallstone or GBC. The intersection and concatenation of co-DEGs and co-DElncRNA functionally involved in focal adhesion, Transcriptional misregulation in cancers, Protein digestion and absorption, and ECM-receptor interaction signaling pathways may contribute to the development of gallbladder cancer. Further exploration is necessary for early diagnosis and the potential treatment of GBC. FXYD2, MPZL1 and PAH were observed in both co-DEGs and co-DElncRNA and validated by qRT-PCR.

Conclusion

Our data identified a series of DEGs and DElncRNAs, which were involved in the progression of GBC and GS-related metabolism pathways. Compared to GBC, the GS profile was more similar to para-tumor tissues in transcriptome level and lower risk of cancer. Further exploration is necessary from GBC patients with different periods of follow-up gallstone.

Identification of a Twelve-microRNA Signature with Prognostic Value in Stage II Microsatellite Stable Colon Cancer

We aimed to identify and validate a set of miRNAs that could serve as a prognostic signature useful to determine the recurrence risk for patients with COAD. Small RNAs from tumors of 100 stage II, untreated, MSS colon cancer patients were sequenced for the discovery step. For this purpose, we built an miRNA score using an elastic net Cox regression model based on the disease-free survival status. Patients were grouped into high or low recurrence risk categories based on the median value of the score. We then validated these results in an independent sample of stage II microsatellite stable tumor tissues, with a hazard ratio of 3.24, (CI_95% = 1.05-10.0) and a 10-year area under the receiver operating characteristic curve of 0.67. Functional analysis of the miRNAs present in the signature identified key pathways in cancer progression. In conclusion, the proposed signature of 12 miRNAs can contribute to improving the prediction of disease relapse in patients with stage II MSS colorectal cancer, and might be useful in deciding which patients may benefit from adjuvant chemotherapy.

Anti-CXCL8 Autoantibody: A Potential Diagnostic Biomarker for Esophageal Squamous Cell Carcinoma

Background and Objectives: Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies. Anti-tumor associated antigen autoantibodies (TAAbs) can be used as biomarkers for tumor detection. The aim of this study was to identify a reliable TAAb as the diagnostic marker for ESCC. Materials and Methods: The Cancer Genome Atlas (TCGA) database was used to screen candidate genes. The mRNA expression of the key gene was then verified by micro array dataset GSE44021 from the Gene Expression Omnibus (GEO) database and the diag nostic value of the corresponding autoantibody to the key gene in ESCC was detected by enzyme-linked im muno sorbent assay (ELISA). Results: CXCL8 was identified as the key gene. The dataset GSE44021 showed that CXCL8 mRNA expression was prominently over-expressed in ESCC tissues compared with normal tissues. ELISA results showed that the level of anti-CXCL8 autoantibody in ESCC patients was significantly higher than in normal controls and the receiver operating char ac teristic (ROC) curve indicated that anti-CXCL8 autoantibody could discriminate ESCC patients from normal controls, with the area under the ROC curve (AUC) for the verification cohort, and the validation cohort were 0.713 and 0.751, respectively. Conclusions: Our study illustrated that anti-CXCL8 autoantibody had good diagnostic value, and may become a candidate biomarker for ESCC.

Long Non-Coding RNA AL513318.2 as ceRNA Binding to hsa-miR-26a-5p Upregulates SLC6A8 Expression and Predicts Poor Prognosis in Non-Small Lung Cancer

Background

Studies have demonstrated that the regulatory role of competitive endogenous RNA (ceRNA) networks is closely related to tumorigenesis, which provides new targets for tumor therapy. In this study, the focus was to explore the ceRNA networks that regulate SLC6A8 expression and their prognosis in non-small cell lung cancer (NSCLC).

Methods

Firstly, the Cancer Genome Atlas (TCGA) data combined with immunohistochemical staining was used to compare SLC6A8 expression in NSCLC tissues and normal tissues. Thereafter, samples from the immunohistochemical staining of NSCLC were integrated with clinical follow-up data for prognostic analysis. The Starbase database was employed to search for SLC6A8-targeted miRNAs and lncRNAs, and survival analysis was performed using clinical data from TCGA to obtain SLC6A8 expression and prognosis-related ceRNA networks. Finally, the prognostic and therapeutic prospects of SLC6A8 in NSCLC were further analyzed from methylation sites and the immune microenvironment.

Results

The study results revealed that SLC6A8 was significantly overexpressed in NSCLC tissues compared to normal tissues, and clinical follow-up data showed that the overexpression group was associated with poor prognosis. In addition, the Starbase data combined with TCGA clinical data analysis demonstrated that the AL513318.2/hsa-miR-26a-5p/SLC6A8 network regulates SLC6A8 overexpression in NSCLC and is associated with poor prognosis. Methylation analysis revealed that 11 methylation sites were closely associated with the prognosis of NSCLC. In addition, the immune prognostic risk model showed that the high-risk group was associated with a poorer prognosis than the low-risk group, despite showing a better immunotherapy outcome.

Conclusion

In summary, the AL513318.2/hsa-miR-26a-5p/SLC6A8 network upregulates SLC6A8 expression in NSCLC and is associated with poor prognosis. Therefore it may be a prognostic biomarker of NSCLC and a potential therapeutic target.