EPV132/#552 The prognostic impact of lower uterine segment involvement in women with low-risk endometrial carcinoma: a multicenter study

Endometrial cancer is one of the most common gynecological malignancies, and DNA methylation plays a vital role in its occurrence and development. In this study, we collected the relevant data on endometrial cancer from the Cancer Genome Atlas database and UCSC website. By screening and processing the data, we obtained 410 samples and 16,381 methylation sites. Endometrial carcinoma can be divided into seven molecular subtypes using consensus clustering method. Based on the analysis of the differences among subtypes, the methylation degree of different sites was obtained, and the prognosis model of methylation sites was established. Based on the median value of the train group, the train and test groups were divided into high and low-risk groups. The survival between the high and low-risk groups was different. It also showed that this model can predict the survival of patients, with better accuracy. In conclusion, the tumor subtypes based on methylation sites can provide a better guidance for treatment, relapse, and prognosis of endometrial cancer. In this study, magnetic nanoparticles can be used to extract genomic DNA and total RNA due to their paramagnetism and biocompatibility, then transcriptome high-throughput sequencing was performed. It may serve as potential cancer immune biomarker targets for developing future oncological treatments.

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Identification of Molecular Biomarkers and Pathways for Risk Stratification in Human Papilloma Virus-Associated Cancers

10.21203/rs.3.rs-641999/v1 ◽

2021 ◽

Author(s):

Eun Jung Kwon ◽

Hye Ran Lee ◽

Ju Ho Lee ◽

Mihyang Ha ◽

Yun Hak Kim ◽

...

Keyword(s):

High Risk ◽

Risk Stratification ◽

Expression Patterns ◽

Risk Groups ◽

Molecular Biomarkers ◽

Low Risk ◽

Receptor Interaction ◽

Prognostic Impact ◽

Tumor Microenvironments ◽

Cell Immunity

Abstract Background: Human papillomavirus (HPV) is the major cause of cervical cancer (CC) etiology; its contribution to head and neck cancer (HNC) incidence is steadily increasing. As individual patients’ response to the treatment of HPV-associated cancer is variable, there is a pressing need for the identification of biomarkers for risk stratification that can help determine the intensity of treatment. Methods: We have previously reported a novel prognostic and predictive indicator (HPPI) scoring system in HPV-associated cancers regardless of the anatomical locations by analyzing the TCGA and GEO databases. In this study, we comprehensively investigated the association of group-specific expression patterns of common differentially expressed genes (DEGs) between high-risk and low-risk groups in HPV-associated CC and HNC, identifying a molecular biomarkers and pathways for the risk stratification. Results: Among the identified 174 DEGs, expression of the genes associated with extracellular matrix (ECM)-receptor interaction pathway (ITGA5, ITGB1, LAMB1, LAMC1) were increased in high-risk groups in both HPV-associated CC and HNC while expression of the genes associated with the T-cell immunity (CD3D, CD3E, CD8B, LCK, and ZAP70) were decreased vise versa. The individual genes showed statistically significant prognostic impact on HPV-associated cancers but not on HPV-negative cancers. The expression levels of identified genes were similar between HPV-negative and HPV-associated high-risk groups with distinct expression patterns only in HPV-associated low-risk groups. Each group of genes showed negative correlations, and distinct patterns of immune cell infiltration in tumor microenvironments. Conclusion: These results identify molecular biomarkers and pathways for risk stratification in HPV-associated cancers regardless of anatomical locations. The identified targets are selectively working in only HPV-associated cancers, but not in HPV-negative cancers indicating possibility of the selective targets governing HPV-infective tumor microenvironments.

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