Identification of CD20, ECM, and ITGA as Biomarkers for Osteosarcoma by Integrating Transcriptome Analysis

Combined transcriptome and proteome analysis reveals MSN and ARFIP2 as biomarkers for trastuzumab resistance of breast cancer

PURPOSE

HER2-positive breast cancer (BC) accounts for 20-30% of all BC subtypes and is linked to poor prognosis. Trastuzumab (Tz), a humanized anti-HER2 monoclonal antibody, is a first-line treatment for HER2-positive breast cancer which faces resistance challenges. This study aimed to identify the biomarkers driving trastuzumab resistance.

METHODS

Differential expression analysis of genes and proteins between trastuzumab-sensitive (TS) and trastuzumab-resistant (TR) cells was conducted using RNA-seq and iTRAQ. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to study their functions. The prognostic significance and protein levels of ARFIP2 and MSN were evaluated using online tools and immunohistochemistry. Sensitivity of MSN and ARFIP2 to other therapies was assessed using public pharmacogenomics databases and the R language.

RESULTS

Five genes were up-regulated, and nine genes were down-regulated in TR cells at both transcriptional and protein levels. Low ARFIP2 and high MSN expression linked to poor BC prognosis. MSN increased and ARFIP2 decreased in TR patients, correlating with shorter OS. MSN negatively impacted fulvestrant and immunotherapy sensitivity, while ARFIP2 had a positive impact.

CONCLUSION

Our findings suggest that MSN and ARFIP2 could serve as promising biomarkers for predicting response to Tz, offering valuable insights for future research in the identification of diagnostic and therapeutic targets for BC patients with Tz resistance.

Clinical Significance and Potential Mechanisms of the RNA Methyltransferase KIAA1429 in Osteosarcoma

Background: KIAA1429, a member of the RNA methyltransferase complex, is involved in cancer progression; however, the clinical significance and underlying mechanism of KIAA1429 in osteosarcoma (OS) remains to be reported. Methods: We evaluated the clinical significance of KIAA1429 in OS by performing RT-qPCR, microarray, and RNA sequencing and using published data as a reference. Two KIAA1429-targeting siRNA constructs were transfected into SW1353 cells. CCK-8 assay, colony formation assays, flow cytometry and the xenograft mouse model were conducted to investigate the biological function of KIAA1429 in OS. Results: The mRNA expression of KIAA1429 was markedly upregulated in 250 OS samples as compared to that in 71 non-cancer samples (standardized mean difference = 0.67). Summary receiver operating characteristic curve analysis revealed that KIAA1429 exhibited reliable diagnostic capacity to differentiate OS samples from non-cancer samples (area under the curve = 0.83). Further, survival analysis indicated that KIAA1429 overexpression was associated with shorter overall survival time. Knocking down KIAA1429 reduced m6A methylation levels, inhibited proliferation, prevented the growth of tumors in vivo and accelerated apoptosis of OS cells. In total, 395 KIAA1429-related genes were identified among co-expressed genes and differentially expressed genes, which were enriched in the cell cycle pathway. Protein-protein interaction network analysis showed that CDK1, CCNA2, and CCNB1 were KIAA1429-related genes, serving as major network hubs in OS. Conclusions: Our findings indicate that KIAA1429 plays an oncogenic role in OS and potentially facilitates OS progression via a mechanism that involves regulating CDK1, CCNA2, and CCNB1.

Cracking the code: Deciphering the role of the tumor microenvironment in osteosarcoma metastasis

Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. It is characterized by a rapid progression, poor prognosis, and early pulmonary metastasis. Over the past 30 years, approximately 85% of patients with osteosarcoma have experienced metastasis. The five-year survival of patients with lung metastasis during the early stages of treatment is less than 20%. The tumor microenvironment (TME) not only provides conditions for tumor cell growth but also releases a variety of substances that can promote the metastasis of tumor cells to other tissues and organs. Currently, there is limited research on the role of the TME in osteosarcoma metastasis. Therefore, to explore methods for regulating osteosarcoma metastasis, further investigations must be conducted from the perspective of the TME. This will help to identify new potential biomarkers for predicting osteosarcoma metastasis and assist in the discovery of new drugs that target regulatory mechanisms for clinical diagnosis and treatment. This paper reviews the research progress on the mechanism of osteosarcoma metastasis based on TME theory, which will provide guidance for the clinical treatment of osteosarcoma.

The Clinical Significance and Potential Molecular Mechanism of Upregulated CDC28 Protein Kinase Regulatory Subunit 1B in Osteosarcoma

BACKGROUND

CDC28 Protein Kinase Regulatory Subunit 1B (CKS1B) is a member of cyclin-dependent kinase subfamily and the relationship between CKS1B and osteosarcoma (OS) remains to be explored.

METHODS

80 OS and 41 nontumor tissue samples were arranged to conduct immunohistochemistry (IHC) to evaluate CKS1B expression between OS and nontumor samples. The standard mean deviation (SMD) was calculated based on in-house IHC and tissue microarrays and exterior high-throughput datasets for further verification of CKS1B expression in OS. The effect of CKS1B expression on clinicopathological and overall survival of OS patients was measured through public high-throughput datasets, and analysis of immune infiltration and single-cell RNA-seq was applied to ascertain molecular mechanism of CKS1B in OS.

RESULTS

A total of 197 OS samples and 83 nontumor samples (including tissue and cell line) were obtained from in-house IHC, microarrays, and exterior high-throughput datasets. The analysis of integrated expression status demonstrated upregulation of CKS1B in OS (SMD = 1.38, 95% CI [0.52-2.25]) and the significant power of CKS1B expression in distinguishing OS samples from nontumor samples (Area under the Curve (AUC) = 0.89, 95% CI [0.86-0.91]). Clinicopathological and prognosis analysis indicated no remarkable significance but inference of immune infiltration and single-cell RNA-seq prompted that OS patients with overexpressed CKS1B were more likely to suffer OS metastasis while MYC Protooncogene may be the upstream regulon of CKS1B in proliferating osteoblastic OS cells.

CONCLUSIONS

In this study, sufficient evidence was provided for upregulation of CKS1B in OS. The advanced effect of CKS1B on OS progression indicates a foreground of CKS1B as a biomarker for OS.

Identification of a Two-Gene (PML-EPB41) Signature With Independent Prognostic Value in Osteosarcoma

Background: Osteosarcoma (OSA) is the most prevalent form of malignant bone cancer and it occurs predominantly in children and adolescents. OSA is associated with a poor prognosis and highest cause of cancer-related death. However, there are a few biomarkers that can serve as reasonable assessments of prognosis.

Methods: Gene expression profiling data were downloaded from dataset GSE39058 and GSE21257 from the Gene Expression Omnibus database as well as TARGET database. Bioinformatic analysis with data integration was conducted to discover the significant biomarkers for predicting prognosis. Verification was conducted by qPCR and western blot to measure the expression of genes.

Results: 733 seed genes were selected by combining the results of the expression profiling data with hub nodes in a human protein-protein interaction network with their gene functional enrichment categories identified. Following by Cox proportional risk regression modeling, a 2-gene (PML-EPB41) signature was developed for prognostic prediction of patients with OSA. Patients in the high-risk group had significantly poorer survival outcomes than in the low-risk group. Finally, the signature was validated and analyzed by the external dataset along with Kaplan–Meier survival analysis as well as biological experiment. A molecular gene model was built to serve as an innovative predictor of prognosis for patients with OSA.

Conclusion: Our findings define novel biomarkers for OSA prognosis, which will possibly aid in the discovery of novel therapeutic targets with clinical applications.

Differentially expressed gene profile and relevant pathways of the traditional Chinese medicine cinobufotalin on MCF‑7 breast cancer cells

Cinobufotalin is a chemical compound extracted from the skin of dried bufo toads that may have curative potential for certain malignancies through different mechanisms; however, these mechanisms remain unexplored in breast cancer. The aim of the present study was to investigate the antitumor mechanism of cinobufotalin in breast cancer by using microarray data and in silico analysis. The microarray data set GSE85871, in which cinobufotalin exerted influences on the MCF‑7 breast cancer cells, was acquired from the Gene Expression Omnibus database, and the differentially expressed genes (DEGs) were analyzed. Subsequently, protein interaction analysis was conducted, which clarified the clinical significance of core genes, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to analyze cinobufotalin‑related pathways. The Connectivity Map (CMAP) database was used to select existing compounds that exhibited curative properties similar to those of cinobufotalin. A total of 1,237 DEGs were identified from breast cancer cells that were treated with cinobufotalin. Two core genes, SRC proto‑oncogene non‑receptor tyrosine kinase and cyclin‑dependent kinase inhibitor 2A, were identified as serving a vital role in the onset and development of breast cancer, and their expression levels were markedly reduced following cinobufotalin treatment as detected by the microarray of GSE85871. It also was revealed that the 'neuroactive ligand‑receptor interaction' and 'calcium signaling' pathways may be crucial for cinobufotalin to perform its functions in breast cancer. Conducting a matching search in CMAP, miconazole and cinobufotalin were indicated to possessed similar molecular mechanisms. In conclusion, cinobufotalin may serve as an effective compound for the treatment of a subtype of breast cancer that is triple positive for the presence of estrogen, progesterone and human epidermal growth factor receptor‑2 receptors, and its mechanism may be related to different pathways. In addition, cinobufotalin is likely to exert its antitumor influences in a similar way as miconazole in MCF‑7 cells.

Identification of Key Genes Affecting Results of Hyperthermia in Osteosarcoma Based on Integrative ChIP-Seq/TargetScan Analysis

Background

The purpose of this study was to research the effects of hyperthermia on osteosarcoma (OS) by integrating the Chromatin Immunoprecipitation with the generation sequencing (ChIP-Seq) and TargetScan analysis of heat shock transcription factor 1 (HSF1).

Material/Methods

The HSF1 ChIP-seq dataset of GSE60984 was downloaded from the Gene Expressed Omnibus (GEO) database. The HSF1-binding sites were screened by MACS2 in OS cells after 10 and 20 min of hyperthermia, and they were annotated using the ChIPseeker package. The overlapped genes were selected out when HSF1-binding sites were located in the promoter region. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the overlaps. The miRNA-gene pairs of the overlaps were screened out via TargetScan, and the miRNA-gene-regulated network was constructed by Cytoscape software.

Results

1880 and 1283 genes of promoter regions were obtained in the osteosarcoma cells after 10 and 20 min of hyperthermia, respectively, and 889 of them were overlapped. The overlapped genes were enriched in 122 GO terms and 3 KEGG pathways. There were 13 657 pairs involved in the miRNA-gene regulated network of the overlaps.

Conclusions

Some biomarkers were identified for OS treated with hyperthermia. Moreover, some GO terms (regulation of programmed cell death and regulation of cell death) and pathways (p53 signaling pathway, methane metabolism, and viral myocarditis) might be involved.