POLD1 as a Prognostic Biomarker Correlated with Cell Proliferation and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Abstract

DNA polymerase delta 1 catalytic subunit (POLD1) plays a vital role in genomic copy with high fidelity and DNA damage repair processes. However, the prognostic value of POLD1 and its relationship with tumor immunity in clear cell renal cell carcinoma (ccRCC) remains to be further explored. Transcriptional data sets and clinical information were obtained from the TCGA, ICGC, and GEO databases. Differentially expressed genes (DEGs) were derived from the comparison between the low and high POLD1 expression groups in the TCGA–KIRC cohort. KEGG and gene ontology (GO) analyses were performed for those DEGs to explore the potential influence of POLD1 on the biological behaviors of ccRCC. The prognostic clinical value and mutational characteristics of patients were described and analyzed according to the POLD1 expression levels. TIMER and TISIDB databases were utilized to comprehensively investigate the potential relevance between the POLD1 levels and the status of the immune cells, as well as the tumor infiltration of immune cells. In addition, RT-qPCR, Western blot, immunohistochemistry and several functional and animal experiments were performed for clinical, in vitro and in vivo validation. POLD1 was highly expressed in a variety of tumors including ccRCC, and further verified in a validation cohort of 60 ccRCC samples and in vitro cell line experiments. POLD1 expression levels in the ccRCC samples were associated with various clinical characteristics including pathologic tumor stage and histologic grade. ccRCC patients with high POLD1 expression have poor clinical outcomes and exhibit a higher rate of somatic mutations than those with low POLD1 expression. Cox regression analysis also showed that POLD1 could act as a potential independent prognostic biomarker. The DEGs associated with POLD1 were significantly enriched in the immunity-related pathways. Moreover, further immune infiltration analysis indicated that high POLD1 expression was associated with high NK CD56bright cells, Treg cells, and myeloid-derived suppressor cells’ (MDSCs) infiltration scores, as well as their marker gene sets of immune cell status. Meanwhile, POLD1 exhibited resistance to various drugs when highly expressed. Finally, the knockdown of POLD1 inhibited the proliferation and migration, and promoted the apoptosis of ccRCC cells in vitro and in vivo, as well as influenced the activation of oncogenic signaling. Our current study demonstrated that POLD1 is a potential prognostic biomarker for ccRCC patients. It might create a tumor immunosuppressive microenvironment and inhibit the susceptibility to ferroptosis leading to a poor prognosis.

Race, Prevalence of POLE and POLD1 Alterations, and Survival Among Patients With Endometrial Cancer

“…POLE and POLD1 are essential for proofreading in DNA replication, the alteration of which will cause DNA hyperalteration and often indicate better response to immunotherapy across many cancer types . The expression levels of POLD1 have been incorporated in prognosis of many cancers that were not treated with immunotherapy . In the absence of immunotherapy, POLD1 is not always associated with favorable prognosis .…”

“… 40 , 52 , 53 , 54 The expression levels of POLD1 have been incorporated in prognosis of many cancers that were not treated with immunotherapy. 55 , 56 In the absence of immunotherapy, POLD1 is not always associated with favorable prognosis. 40 However, in the present study, the presence of POLD1 alteration in EC appeared to be associated with excellent clinical outcomes regardless of racial, histological, and TP53 alteration status disparities.…”

CRYL1 is a Potential Prognostic Biomarker of Clear Cell Renal Cell Carcinoma Correlated with Immune Infiltration and Cuproptosis

“…Additionally, POLD1 might contribute to the tumor immune-suppressive microenvironment and diminish the sensitivity of tumors to ferroptosis, providing a novel understanding of the mechanisms underlying renal cancer development. 24 Similarly, Kunpeng Luo established a metabolic reprogramming assessment model using various machine learning algorithms, demonstrating its superior efficacy compared to traditional prognostic indicators. Moreover, based on these findings, a potential targeted drug was identified, offering new perspectives for the future treatment and prognosis prediction of renal cancer.…”