1 Introduction
One common cancer of the urinary tract that has a high morbidity and mortality rate is bladder cancer (BCa) [
1]. It ranks tenth among common malignancies, encompassing non-muscle-invasive and muscle-invasive tumors [
2,
3]. Although many possible biomarkers for BCa diagnosis and treatment have been identified, their effectiveness differs throughout patients despite breakthroughs in bioinformatics and sequencing [
4,
5]. Therapy choices are still guided by radiographic and pathologic examinations [
6]. BCa progression is influenced by multiple biological pathways, with cell cycle progression (CCP) playing a pivotal role [
7]. Bladder cancer cells acquire resistance through a myriad of mechanisms intertwined with the cell cycle, enabling them to persistently divide even when subjected to drug treatments [
8,
9].
For cells to function properly, four phases of the carefully controlled cell cycle are required [
10]. Inappropriate cell cycle progression can lead to unchecked cell proliferation and the advancement of cancer, particularly at critical checkpoints like G1/S and G2/M [
11]. Dysregulation of CCP is implicated in various diseases, including cancer [
12‐
14]. Aberrations in genes governing CCP and apoptotic pathways contribute to tumorigenesis and progression [
15,
16]. Clinical and basic research has revealed CCP-related genes as prognostic indicators across cancer types [
17‐
19]. Previous studies have described that the CCP-related ANLN is abnormally expressed in kidney cancer and promotes carcinogenesis by activating PI3K/Akt/mTOR signaling [
20]. CCP-related genes exhibit abnormal expression patterns across a spectrum of human tumors, presenting significant potential as prognostic markers.[
21‐
23]. These CCP-related genes haven’t been fully examined, yet, and further research is needed to fully understand the immunological and clinical significance of bladder cancer.
Even with this understanding, it is still unclear exactly what functions, prognosis, and immunological environment CCP-related gene markers play in BCa. Through thorough bioinformatics research, a CCP-related risk model is to be built in our study to systematically predict the immunological landscape and prognosis of BCa.
4 Discussion
Because of its high mortality, morbidity, and burden of medical treatment, BCa is a serious health concern, having more than doubled in occurrence worldwide in the last two decades [
34,
35]. A concentrated effort has been made over the last thirty years to investigate novel therapeutic, prognostic, and diagnostic biomarkers for BCa patients in an attempt to determine which patients could benefit the most from treatment. Individual or combined genomes that identify unique patterns of gene expression inside disease processes have been found to be useful for prognostic prediction and disease classification [
36,
37]. Anomalies in a number of cellular pathways, most notably the disruption of cell cycle control, are thought to play a role in the carcinogenesis and development of BCa [
38,
39]. According to earlier studies, CCP-related gene malfunctions can influence immune cell infiltration during the initiation and spread of cancer as well as cause unchecked cell proliferation [
38,
40]. Aberrations in CCP-related genes have been associated with unfavorable prognostic outcomes across various human neoplastic diseases [
41,
42]. Three selected genes (RAD43B, KPNA2, and TPM1) were used to create a risk model, and CCP-related genes were evaluated using various bioinformatics databases and techniques to evaluate their biological function, predictive power, and relationship to the immune microenvironment in BCa.
The cell cycle process is intimately associated with the three genes connected to CCP. According to earlier studies, homologous recombination repair is inhibited by RAD54B knockdown, and ovarian tumor tissues with RAD54B mutations have been shown to have more DNA double-strand breaks than normal tissues [
43]. KPNA2 normally expresses itself at a low level in normal tissues, but in some carcinomas, it has been shown to be overexpressed, which can affect the immune system, tumor cell proliferation, and differentiation [
44‐
46]. There has been discussion on the physiological function of TPM1 in various malignancies; tumor types have been linked to metastasis and cancer progression at both higher and lower expression levels [
47,
48]. The results of our investigation show that, in BCa, the CCP-related risk model has better predictive efficacy than the TNM stage. Furthermore, using both univariate and multivariate Cox regression analysis, the CCP-related risk model has been found to be an independent prognostic factor for predicting survival in BCa patients. The prognosis risk score from the CCP-related risk model was combined with a number of clinical characteristics to create nomogram prognostic models, which were then verified, in order to improve prognostic accuracy. In BCa patients, the nomogram showed better predictive accuracy than T stage, N stage, and clinical stage.
GO, KEGG, and GSVA enrichment analyses were used to perform a functional enrichment analysis of the CCP-related risk model. The findings demonstrated that the CCP-related risk model is involved in multiple cellular immunological activities, especially those linked to leukocytes, and impacts a broad spectrum of cell cycle-related processes. Natural killer cells and cytotoxic T cells are examples of immune surveillance cells that are crucial in identifying and destroying aberrant cells, including those that show dysregulated cell cycle progression [
49].Moreover, immune cell activation and proliferation include closely controlled cell cycle activities, which include fast cell division and the production of immunological responses. Immune dysfunction may arise from any malfunction in this complex process [
50].
Certain elements of the cell cycle apparatus, such as regulators and checkpoint proteins, may be targets for immunotherapy. For BCa patients, immune checkpoint inhibitors show good treatment outcomes [
51,
52]. Subsequent analysis of immune infiltration patterns showed that the high-risk group had reduced infiltration of regulatory T cells and activated dendritic cells, but increased infiltration of M2 macrophages, neutrophils, and activated CD4 + memory T cells. Furthermore, the high-risk group had considerably greater enrichment scores for immunological pathways when compared to the low-risk group, with the exception of the type 2 interferon response pathway. Additionally, these risk genes were positively or negatively correlated with immune checkpoint genes. Our findings imply that CCP-related gene markers could be useful targets for immune treatment since they could contribute to an immunologically active state. Unchecked proliferation and disturbed cell cycle control are hallmarks of cancer cells. Through the direct targeting of cyclins within tumor cells or the indirect induction of an immune response against them, immunotherapy can take advantage of these abnormalities [
53,
54].
The abnormal cell cycle progression can be targeted for therapeutic intervention and modulates immune responses against tumors or pathogens. Understanding how these systems interact is essential to creating cancer and other disease-fighting treatments. There are a few restrictions on this study, though. First of all, clinical trials are required for validation because to the retrospective nature of the data acquired from public sources. Second, there was insufficient clarity provided by the basic molecular pathways underpinning the CCP-related risk model in the progression of BCa, which calls for more investigation in subsequent research.
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