Prioritization of cancer marker candidates based on the immunohistochemistry staining images deposited in the human protein atlas

Emerging Biohybrids of Aptamer-Based Nano-Biosensing Technologies for Effective Early Cancer Detection

Cancer is a leading global cause of mortality, which underscores the imperative of early detection for improved patient outcomes. Biorecognition molecules, especially aptamers, have emerged as highly effective tools for early and accurate cancer cell identification. Aptamers, with superior versatility in synthesis and modification, offer enhanced binding specificity and stability compared with conventional antibodies. Hence, this article reviews diagnostic strategies employing aptamer-based biohybrid nano-biosensing technologies, focusing on their utility in detecting cancer biomarkers and abnormal cells. Recent developments include the synthesis of nano-aptamers using diverse nanomaterials, such as metallic nanoparticles, metal oxide nanoparticles, carbon-derived substances, and biohybrid nanostructures. The integration of these nanomaterials with aptamers significantly enhances sensitivity and specificity, promising innovative and efficient approaches for cancer diagnosis. This convergence of nanotechnology with aptamer research holds the potential to revolutionize cancer treatment through rapid, accurate, and non-invasive diagnostic methods.

Using biological information to analyze potential miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer

Background

Lung cancer is the most common malignant tumor, and it has a high mortality rate. However, the study of miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer (NSCLC) is insufficient. Therefore, this study explored the differential expression of mRNA and miRNA in the plasma of NSCLC patients.

Methods

The Gene Expression Omnibus (GEO) database was used to download microarray datasets, and the differentially expressed miRNAs (DEMs) were analyzed. We predicted transcription factors and target genes of the DEMs by using FunRich software and the TargetScanHuman database, respectively. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for GO annotation and KEGG enrichment analysis of downstream target genes. We constructed protein-protein interaction (PPI) and DEM-hub gene networks using the STRING database and Cytoscape software. The GSE20189 dataset was used to screen out the key hub gene. Using The Cancer Genome Atlas (TCGA) and UALCAN databases to analyze the expression and prognosis of the key hub gene and DEMs. Then, GSE17681 and GSE137140 datasets were used to validate DEMs expression. Finally, the receiver operating characteristic (ROC) curve was used to verify the ability of the DEMs to distinguish lung cancer patients from healthy patients.

Results

Four upregulated candidate DEMs (hsa-miR199a-5p, hsa-miR-186-5p, hsa-miR-328-3p, and hsa-let-7d-3p) were screened from 3 databases, and 6 upstream transcription factors and 2253 downstream target genes were predicted. These genes were mainly enriched in cancer pathways and PI3k-Akt pathways. Among the top 30 hub genes, the expression of KLHL3 was consistent with the GSE20189 dataset. Except for let-7d-3p, the expression of other DEMs and KLHL3 in tissues were consistent with those in plasma. LUSC patients with high let-7d-3p expression had poor overall survival rates (OS). External validation demonstrated that the expression of hsa-miR-199a-5p and hsa-miR-186-5p in peripheral blood of NSCLC patients was higher than the healthy controls. The ROC curve confirmed that the DEMs could better distinguish lung cancer patients from healthy people.

Conclusion

The results showed that miR-199a-5p and miR-186-5p may be noninvasive diagnostic biomarkers for NSCLC patients. MiR-199a-5p-KLHL3 may be involved in the occurrence and development of NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09281-1.

FURIN correlated with immune infiltration serves as a potential biomarker in SARS-CoV-2 infection-related lung adenocarcinoma

FURIN, as a proprotein convertase, has been found to be expressed in a variety of cancers and plays an important role in cancer. In addition, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires FURIN to enter human cells. However, the role of FURIN in lung adenocarcinoma remains unclear. And the expression of SARS-CoV-2 related gene in lung adenocarcinoma has not been clarified. Therefore, in order to explore the prognostic value and mechanism of FURIN in lung adenocarcinoma, we performed bioinformatics analysis with Oncomine, Tumor Immune Estimation Resource, Gene Expression Profiling Interactive Analysis, human protein atlas, UALCAN, PrognoScan, Kaplan–Meier plotter, cBioPortal and LinkedOmics databases. And then we used GSE44274 in the GEO (Gene Expression Omnibus) database to analyze the expression of FURIN in LUAD patients who infected with SARS-CoV. FURIN was highly expressed in lung adenocarcinoma and was significantly associated with poor overall survival. FURIN expression was found to be correlated with six major permeable immune cells and with macrophage immune marker in LUAD patients. In addition, SARS-CoV-2 infection might affect the expression of FURIN. FURIN can be used as a promising biomarker for determining prognosis and immune infiltration in LUAD patients.

Aptamers as Diagnostic Tools in Cancer

Cancer is the second leading cause of death worldwide. Researchers have been working hard on investigating not only improved therapeutics but also on early detection methods, both critical to increasing treatment efficacy, and developing methods for disease prevention. The use of nucleic acids, or aptamers, has emerged as more specific and accurate cancer diagnostic and therapeutic tools. Aptamers are single-stranded DNA or RNA molecules that recognize specific targets based on unique three-dimensional conformations. Despite the fact aptamer development has been mainly restricted to laboratory settings, the unique attributes of these molecules suggest their high potential for clinical advances in cancer detection. Aptamers can be selected for a wide range of targets, and also linked with an extensive variety of diagnostic agents, via physical or chemical conjugation, to improve previously-established detection methods or to be used as novel biosensors for cancer diagnosis. Consequently, herein we review the principal considerations and recent updates in cancer detection and imaging through aptamer-based molecules.

Omics Profiling in Precision Oncology

Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology.

Twist-1 up-regulation in carcinoma correlates to poor survival

Epithelial-to-mesenchymal transition (EMT) facilitates tumor metastasis. Twist is a basic helix-loop-helix protein that modulates many target genes through E-box-responsive elements. There are two twist-like proteins, Twist-1 and Twist-2, sharing high structural homology in mammals. Twist-1 was found to be a key factor in the promotion of metastasis of cancer cells, and is known to induce EMT. Twist-1 participation in carcinoma progression and metastasis has been reported in a variety of tumors. However, controversy exists concerning the correlation between Twist-1 and prognostic value with respect to carcinoma. A systematic review and meta-analysis were performed to determine whether the expression of Twist-1 was associated with the prognosis of carcinoma patients. This analysis included 17 studies: four studies evaluated lung cancer, three evaluated head and neck cancer, two evaluated breast cancer, two evaluated esophageal cancer, two evaluated liver cancer and one each evaluated osteosarcoma, bladder, cervical and ovarian cancer. A total of 2006 patients were enrolled in these studies, and the median trial sample size was 118 patients. Twist-1 expression was associated with worse overall survival (OS) at both 3 years (hazard ratio "HR" for death = 2.13, 95% CI = 1.86 to 2.45, p < 0.001) and 5 years (HR for death = 2.01, 95% CI = 1.76 to 2.29, p < 0.001). Expression of Twist-1 is associated with worse survival in carcinoma.