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Identification of Nephrogenic Therapeutic Biomarkers of Wilms Tumor Using Machine Learning.

ABSTRACT: Wilms tumor is the most common renal malignancy in children, with a survival rate of more than 90%; however, treatment outcomes for certain patient subgroups, such as those with bilateral and recurrent diseases, remain significantly below this survival rate. Therefore, it remains essential to identify new biomarkers and develop effective therapeutic strategies. Based on the Therapeutically Applicable Research to Generate Effective Treatments and Gene Expression Omnibus RNA microarray datasets, we have identified eight differentially expressed genes in Wilms tumors as renal-specific in 33 randomly selected adult tumors. The risk model, constructed using survival forest and multivariate Cox regression, can effectively predict the prognosis; the risk score is an independent prognostic factor in Wilms tumor. Gene set enrichment analysis showed that most of the signature genes were involved in regulating human development-related pathways. At the same time, patients in the high-risk group exhibited more sensitive immunological and chemotherapeutic properties than those in the low-risk group. These results provide new insights into personalized and precise Wilms tumor treatment strategies.

SUBMITTER: Liu H

PROVIDER: S-EPMC8371641 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Wilms tumor (WT) is the most frequently diagnosed malignant renal tumor in children. With current treatments, ~90% of children diagnosed with WT survive and generally present with tumors characterized by favorable histology (FHWT), whereas prognosis is poor for the remaining 10% of cases where the tumors are characterized by cellular diffuse anaplasia (DAWT). Relatively few studies have investigated microRNA-related epigenetic regulation and its relationship with altered gene expression in WT. Here, we aim to identify microRNAs differentially expressed in WT and describe their expression in terms of cellular anaplasia, metastasis, and association with the main genetic alterations in WT to identify potential prognostic biomarkers. Expression profiling using TaqMan low-density array was performed in a discovery cohort consisting of four DAWT and eight FHWT samples. Relative quantification resulted in the identification of 109 (48.7%) microRNAs differentially expressed in both WT types. Of these, miR-10a-5p, miR-29a-3p, miR-181a-5p, miR-200b-3p, and miR-218-5p were selected and tested by RT-qPCR on a validation cohort of 53 patient samples. MiR-29a and miR-218 showed significant differences in FHWT with low (P = 0.0018) and high (P = 0.0131) expression, respectively. To discriminate between miRNA expression FHWTs and healthy controls, the receiver operating characteristic (ROC) curves were obtained; miR-29a AUC was 0.7843. Furthermore, low expression levels of miR-29a and miR-200b (P = 0.0027 and P = 0.0248) were observed in metastatic tumors. ROC curves for miR-29a discriminated metastatic patients (AUC = 0.8529) and miR-200b (AUC = 0.7757). To confirm the differences between cases with poor prognosis, we performed in situ hybridization for three microRNAs in five DAWT and 17 FHWT samples, and only significant differences between adjacent tissues and FHWT tumors were found for miR-181a, miR-200b, and miR-218, in both total pixels and nuclear analyses. Analysis of copy number variation in genes showed that the most prevalent alterations were WTX (47%), IGF2 (21%), 1q (36%) gain, 1p36 (16%), and WTX deletion/1q duplicate (26%). The five microRNAs evaluated are involved in the Hippo signaling pathway and participate in Wilms tumor development through their effects on differentiation, proliferation, angiogenesis, and metastasis.

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Identification of Nephrogenic Therapeutic Biomarkers of Wilms Tumor Using Machine Learning.

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