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Efficacy and safety of neoadjuvant therapy with tislelizumab plus axitinib for nonmetastatic renal cell carcinoma with inferior vena cava tumor thrombus: a retrospective study

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Title: Efficacy and safety of neoadjuvant therapy with tislelizumab plus axitinib for nonmetastatic renal cell carcinoma with inferior vena cava tumor thrombus: a retrospective study
Authors: Zhongjie Zhao, Zhengsheng Liu, Kaiyan Zhang, Wei Li, Lijian Zhang, Bingliang Jiang, Bin Chen, Jinchun Xing, Xuegang Wang
Source: Scientific Reports, Vol 15, Iss 1, Pp 1-8 (2025)
Publisher Information: Nature Portfolio, 2025.
Publication Year: 2025
Collection: LCC:Medicine
LCC:Science
Subject Terms: Tislelizumab, Axitinib, Renal cell carcinoma (RCC), Inferior vena cava (IVC) tumor thrombus, Neoadjuvant therapy, Medicine, Science
More Details: Abstract In renal cell carcinoma (RCC) patients with inferior vena cava (IVC) tumor thrombus, neoadjuvant therapy could alleviate the burden of tumor thrombus, enhance the safety and feasibility of surgical resection, and improve patient prognosis. The combination of tislelizumab and axitinib has demonstrated efficacy in the treatment of advanced RCC. Our study aimed to evaluate the efficacy and safety in the neoadjuvant therapy setting of tislelizumab and axitinib in RCC patients with IVC tumor thrombus. In this retrospective study, seven patients of nonmetastatic RCC with IVC tumor thrombus who received 3 cycles of neoadjuvant therapy with tislelizumab plus axitinib at the First Affiliated Hospital of Xiamen University from May 2020 to December 2023 were included. The main outcomes included objective response rate (ORR), reduction of tumor thrombus size and level, surgical outcomes, and adverse events (AEs). The median age was 66 (range, 50–72) years, and five (71.4%) patients were male. Five (71.4%) patients were diagnosed with clear cell carcinoma, and two (28.6%) patients were papillary type I carcinoma. Four (57.1%) patients had level II tumor thrombus and three (42.9%) patients had level III. The ORR of patients was 57.1%. The mean decrease in thrombus diameter and length was 5.8 (1.8–17.2) mm and 18.5 (4.4–41.5) mm, respectively. All patients showed a decrease in IVC tumor thrombus. The mean time from the end of neoadjuvant therapy to radical nephrectomy and thrombectomy was 31.7(range, 22–45) days. No intraoperative complications or postoperative Clavien-Dindo grade>3 complications occurred. The most common AEs were all grade 1–2, and only one patient had grade 4 hepatic impairment. No AEs delayed the surgery schedule. This study of RCC patients receiving neoadjuvant combination with tislelizumab and axitinib effectively reduced primary tumor and IVC tumor thrombus with the absence of serious AEs, demonstrating a promising neoadjuvant therapy.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-025-86712-6
Access URL: https://doaj.org/article/02cf6b9510d643249fcade91fa7fd54b
Accession Number: edsdoj.02cf6b9510d643249fcade91fa7fd54b
Database: Directory of Open Access Journals
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  Value: <anid>AN0182467219;[fkqs]25jan.25;2025Jan30.00:34;v2.2.500</anid> <title id="AN0182467219-1">Overexpression of PLCG2 and TMEM38A inhibit tumor progression in clear cell renal cell carcinoma </title> <p>Clear cell renal cell carcinoma is a prevalent urological malignancy, imposing substantial burdens on both patients and society. In our study, we used bioinformatics methods to select four putative target genes associated with EMT and prognosis and developed a nomogram model which could accurately predicting 5-year patient survival rates. We further analyzed proteome and single-cell data and selected PLCG2 and TMEM38A for the following experiments. Overexpression models of PLCG2 and TMEM38A were generated in Caki-1 and 786-O cell lines using plasmids. The in vitro experiments demonstrated that both of them exerted pro-apoptotic effects on Caki-1 and 786-O cells, inducing G2/M phase arrest, inhibiting proliferation, and suppressing EMT. In summary, we identified potential tumor suppressor factors and stratified ccRCC patients into high-risk and low-risk groups based on these factors. Furthermore, we elucidated the impact of PLCG2 and TMEM38A in Caki-1 and 786-O cell lines, offering novel avenues for therapeutic target exploration.</p> <p>Keywords: ccRCC; PLCG2; TMEM38A; TCGA; PDC; Medical and Health Sciences Oncology and Carcinogenesis</p> <p>Supplementary Information The online version contains supplementary material available at https://doi.org/10.1038/s41598-025-86644-1.</p> <hd id="AN0182467219-2">Introduction</hd> <p>Over the past two decades, there has been a gradual increase in the incidence of kidney cancer (KC), with nearly 400,000 new cases reported in 2020[<reflink idref="bib1" id="ref1">1</reflink>],[<reflink idref="bib2" id="ref2">2</reflink>]. Notably, clear cell renal cell carcinoma accounts for approximately 70% of these cases and represents a serious threat to human health[<reflink idref="bib3" id="ref3">3</reflink>],[<reflink idref="bib4" id="ref4">4</reflink>]. With the continuous enhancement of detection efficacy and treatment standards, the therapeutic outcomes for renal cell carcinoma have shown improvement[<reflink idref="bib5" id="ref5">5</reflink>],[<reflink idref="bib6" id="ref6">6</reflink>]. However, challenges persist in terms of limited effectiveness in advanced-stage surgeries and chemotherapy drug resistance[<reflink idref="bib7" id="ref7">7</reflink>].</p> <p>Phosphoinositide-specific phospholipase Cs (PLCs) are ubiquitously expressed in mammalian cells and play important roles in mediating signal transduction pathways which comprise PLCβ[<reflink idref="bib1" id="ref8">1</reflink>], [<reflink idref="bib2" id="ref9">2</reflink>], [<reflink idref="bib3" id="ref10">3</reflink>]–[<reflink idref="bib4" id="ref11">4</reflink>], PLCγ[<reflink idref="bib1" id="ref12">1</reflink>],[<reflink idref="bib2" id="ref13">2</reflink>], PLCδ[<reflink idref="bib1" id="ref14">1</reflink>],[<reflink idref="bib3" id="ref15">3</reflink>],[<reflink idref="bib4" id="ref16">4</reflink>], PLCε, PLCζ, PLCη[<reflink idref="bib1" id="ref17">1</reflink>],[<reflink idref="bib2" id="ref18">2</reflink>] and PLC-XD[<reflink idref="bib1" id="ref19">1</reflink>], [<reflink idref="bib2" id="ref20">2</reflink>]–[<reflink idref="bib3" id="ref21">3</reflink>],[<reflink idref="bib8" id="ref22">8</reflink>],[<reflink idref="bib9" id="ref23">9</reflink>]. As one of the 16 members within phospholipase C family, PLCG2 (phospholipase C gamma 2, phospholipase C γ 2) is a membrane-associated enzyme and was found associated with multiple diseases such as Alzheimer's disease (AD)[<reflink idref="bib10" id="ref24">10</reflink>],[<reflink idref="bib11" id="ref25">11</reflink>], inflammatory bowel disease (IBD)[<reflink idref="bib12" id="ref26">12</reflink>] and steroid-sensitive nephrotic syndrome (SSNS)[<reflink idref="bib13" id="ref27">13</reflink>],[<reflink idref="bib14" id="ref28">14</reflink>]. It was activated by external stimuli and hydrolyzed phospholipid PIP2 (1-phosphatidyl-1D-myoinositol 4,5-bisphosphate) to generate IP3 (1D-myo-inositol 1,4,5-trisphosphate) and DAG (diacylglycerol)[<reflink idref="bib15" id="ref29">15</reflink>]. Both products further exert their effects within cells and mediate the conduction of signaling pathways. <emph>Yang yongfeng</emph> et al. found that the expression of PLCG2 was significantly upregulated in lung cancer and it facilitated metastasis of non-small cell lung cancer by promoting mitochondrial function[<reflink idref="bib16" id="ref30">16</reflink>]. A recent study demonstrated that, the expression of PLCG2 in soft tissue sarcoma was positively correlated with prognosis of the patients and acts as a tumor suppressor gene in the tumor microenvironment[<reflink idref="bib17" id="ref31">17</reflink>]. However, its role and function have not been investigated in ccRCC.</p> <p>Transmembrane (TMEM) family is constituted by more than 300 proteins that have at least one or more transmembrane domains inserted into biological membrane[<reflink idref="bib18" id="ref32">18</reflink>]. TMEMs exhibit widespread expression across diverse tissues and plays an important role in the regulation of various physiological functions, encompassing ion channels, apoptosis, autophagy, immune responses etc.[<reflink idref="bib18" id="ref33">18</reflink>], [<reflink idref="bib19" id="ref34">19</reflink>], [<reflink idref="bib20" id="ref35">20</reflink>], [<reflink idref="bib21" id="ref36">21</reflink>]–[<reflink idref="bib22" id="ref37">22</reflink>]. Simultaneously, recent studies have revealed a strong correlation between the expression level of TMEM and tumorigenesis, with certain members being classified as oncogenes (TMEM 14A, 45A) while others are recognized as tumor suppressor genes (TMEM 7, 25, 176A)[<reflink idref="bib23" id="ref38">23</reflink>], [<reflink idref="bib24" id="ref39">24</reflink>], [<reflink idref="bib25" id="ref40">25</reflink>], [<reflink idref="bib26" id="ref41">26</reflink>], [<reflink idref="bib27" id="ref42">27</reflink>], [<reflink idref="bib28" id="ref43">28</reflink>]–[<reflink idref="bib29" id="ref44">29</reflink>]. However, as a member of the TMEM family, the functional role of TMEM38A remains to be elucidated.</p> <p>In our study, we constructed a risk score by EMT related prognostic genes on the foundation of genome data, then we assessed its associations with multiple clinical features and evaluated its prognostic value as an independent prognostic factor, for better prediction of patients' survival, we constructed a nomogram model via these independent factors. Furthermore, we investigated the proteome data and found PLCG2 and TMEM38A decreased in kidney tumor samples. We also checked the distribution of these genes and their potential sensitive targeted chemotherapies. Finally, we utilized overexpressed plasmids to explore the functions of PLCG2 and TMEM38A in 786-O and Caki-1 cell lines.</p> <hd id="AN0182467219-3">Methods</hd> <p></p> <hd id="AN0182467219-4">Data acquisition</hd> <p>Source data for gene expression analyses was obtained from The Cancer Genome Atlas (TCGA) datasets and Genotype-Tissue Expression (GTEx) via the online database UCSC Xena[<reflink idref="bib30" id="ref45">30</reflink>], where we selected the data type "RSEM tpm". TCGA "count" data was downloaded from TCGA portal[<reflink idref="bib31" id="ref46">31</reflink>]. For further validation, mRNA expression array data of GSE36895, GSE40435, GSE53000, GSE53757, GSE66672 and GSE68417 were obtained from the Gene Expression Omnibus (GEO)[<reflink idref="bib32" id="ref47">32</reflink>].</p> <hd id="AN0182467219-5">Visualization</hd> <p>Differential expression and correlation analyses, lasso model and nomogram model construction, survival analysis receiver operating characteristic (ROC) curves were all visualized by R software (v 4.3.1) through various R packages, detailed information of packages used for each step was shown in Table S1. Gene Set Enrichment Analysis (GSEA) software (v. 4.3.2) was utilized for enrichment results generation.</p> <hd id="AN0182467219-6">Online tools utilization</hd> <p>The DepMap Portal[<reflink idref="bib33" id="ref48">33</reflink>] was used to observe Single cell profiles obtained from TISCH2 (<ulink href="http://tisch.comp-genomics.org/home/">http://tisch.comp-genomics.org/home/</ulink>) and CZ CELL × GENE Discover (https://cellxgene.cziscience.com/)[<reflink idref="bib34" id="ref49">34</reflink>]. The protein levels in tumor tissues were compared to their normal counterparts using proteome and phosphoproteome data obtained from the Protein Data Commons (PDC) study PDC000127 and PDC000128 available on the PDC portal (https://pdc.cancer.gov).</p> <hd id="AN0182467219-7">Cell Counting Kit-8 assay</hd> <p>The transfected cells were counted, and an equivalent number of cells were seeded into 96-well plates. Cell Counting Kit-8 (CCK8) reagents (Cat.MA0218, Meilun Biotechnology Co., Ltd. in Dalian, China) were introduced at various time points, and the absorbance at 450 nm was measured (Thermo Labsystems, Vantaa, Finland) after one hour of incubation.</p> <hd id="AN0182467219-8">Flow cytometry analysis</hd> <p>Cell cycle and apoptosis were assessed using flow cytometry. After transfection for 48 h, cells were trypsinized and harvested (cell culture medium was also collected upon detection of apoptosis), followed by centrifugation to discard the supernatant and subsequent washing with PBS. Subsequently, the cells were stained using the Cell Cycle Staining Kit (Cat.CCS012) and Annexin V-FITC/PI Apoptosis Kit (Cat.AP101-100) as per the provided instructions, followed by subsequent detection post-incubation. All flow cytometry experiments were independently repeated three times in triplicate.</p> <hd id="AN0182467219-9">qRT-PCR analysis and Western blotting</hd> <p>The qRT-PCR and western-blotting experimental method was performed as previously described[<reflink idref="bib35" id="ref50">35</reflink>],[<reflink idref="bib36" id="ref51">36</reflink>]. Following cell treatment, total RNA was extracted and cDNA synthesized by reverse transcription. qRT-PCR analysis was conducted according to manufacturer's instructions and data was analyzed using the 2<sups>-△△CT</sups> method. All experiments were independently repeated three times in triplicate. All primer sequences are listed in Table S2. All primary and secondary antibodies for western blotting were summarized in Table S3 and Table S4, respectively.</p> <hd id="AN0182467219-10">Acquisition of tissue microarray (TMA) of ccRCC and Immunohistochemistry (IHC) staining</hd> <p>We utilized a ccRCC TMA purchased from Outdo Biotech (HKidE020PG01; Shanghai, China). This microarray consists of ten pairs of ccRCC and adjacent normal kidney tissues, which facilitated us to compare the gene enrichment between them, we performed IHC analyses on the TMAs to evaluate the expression levels of PLCG2 and TMEM38A, we drew on the identical experimental methods of previous studies that used the ccRCC TMAs from the same company[<reflink idref="bib37" id="ref52">37</reflink>]. And analyzed the mean grey value of the results.</p> <hd id="AN0182467219-11">Cell culture</hd> <p>The human clear cell renal cell carcinoma cell lines 789-O and Caki-1 were utilized in our experiment, cultured separately in RPMI-1640 medium (Gibco, Australia) and McCoy's 5A medium (Procell, China). The culture media were supplemented with 10% fetal bovine serum (FBS) (Gibco, Waltham, Massachusetts, USA) and 1% penicillin G sodium/streptomycin sulfate. Both 786-O and Caki-1 cell lines were obtained from Cell Bank, Chinese Academy of Sciences (Shanghai, China) and the cell lines were identified at the China Center for Type Culture Collection (Wuhan, China).</p> <hd id="AN0182467219-12">Clone-formation assay</hd> <p>The treated cells were seeded in six-well plates (approximately 1500 cells/well) and cultured in the cell incubator for 10 days. Subsequently, the culture medium was aspirated, and the cells were fixed with 4% paraformaldehyde (PFA). Following fixation, the cells were stained with 0.1% crystal violet solution and imaged. The clone's number were counted with Image J software.</p> <hd id="AN0182467219-13">Results</hd> <p></p> <hd id="AN0182467219-14">Four target genes were selected based on EMT, survival analysis and M stages</hd> <p>TCGA tpm data was used for pearson correlation analyses, we filtered targets that expressed more in normal kidney tissues which were positively correlated with CDH1 (E-cadherin) and negatively correlated with vimentin and CDH2 (N-cadherin) (Table S5). Among these targets, we performed survival analyses to select genes that could predict overall survival (OS) and progression free survival (PFS) (Table S6). Given the strong correlation between EMT and distant metastasis, we conducted a comparative analysis of prognostic genes and differentially expressed genes among patients with varying M stages (Table S7). Eventually, four genes (PLCG2, SLC16A11, TMEM38A and TMEM213) were identified as our targets.</p> <hd id="AN0182467219-15">Validation of target genes via open access datasets</hd> <p>By analyzing exon expression data, we observed not only were the mRNA levels of these genes highly expressed in normal kidney tissues, but also all of their exons showed the same trend (Table S8). To validate the differential expression of these target genes, a comparative analysis of their expression profiles was conducted across six GEO datasets (Fig. 1A–F). Remarkably, the validation results were consistent with those obtained from the TCGA dataset. At the same time, according to data from DepMap, the gene effects were consistently higher than -0.5 (Figure S1A-D) when our targets were knocked out using Crisper in ccRCC cell lines, suggesting that these genes may not promote the progression of tumor cells, which were consistent with our findings. In addition, for the conciseness of the figures, we summarized all the numbers of patients or samples in Table S9.</p> <p>Graph: Fig. 1 Validation of differential expression of EMT related prognostic genes. Violin plots of mRNA expression profiles of PLCG2, TMEM38A, SLC16A11 and TMEM213 in ccRCC patients from six GEO microarrays, it was observed that they were descended in tumor tissues in most of the validation sets (A–F). NS means no significant difference, *p < 0.05, **p < 0.01, ***p < 0.001.</p> <hd id="AN0182467219-16">Construction of risk score model</hd> <p>We then constructed a risk score model from these four genes by least absolute shrinkage and selection operator regression (LASSO) analysis (Figure S2). For the purpose of enhancing research quality, only patients with a follow-up duration longer than one month were incorporated for model consideration. After regression, three targets (PLCG2, SLC16A11, TMEM38A) were enrolled in the score, which was derived from the calculation of (-0.191562309536912) * (PLCG2 expression) + (-0.156907360696619) * (TMEM38A expression) + (-0.185625702222363) * (SLC16A11 expression). To evaluate the prognostic ability of our scoring system, we divided patients into high and low risk groups based on the medians of risk score and its components, for example, high-PLCG2 group means half of the patients (n = 255) whose PLCG2 levels were higher than the other half (n = 255, low-PLCG2 group). Our risk score model has significantly stronger ability to predict overall survival in ccRCC patients (Fig. 2A–D). Besides patients' survival, our risk score model (Fig. 2E–L) as well as its three members (Figure S3) demonstrated strong associations with other clinical features, suggesting the potential significance of our model.</p> <p>Graph: Fig. 2 Prognostic analyses and correlation analyses of risk score and its components. (A–D) K-M plots suggesting the prognostic values of risk score and its compositions. The prognostic value of risk score was obviously better those of its components. (E–L) Correlation analyses indicated that higher risk score had stronger associations with M stage, tumor grade and new events (distant metastasis, recurrence etc.). NS means no significant difference, *p < 0.05, **p < 0.01, ***p < 0.001.</p> <hd id="AN0182467219-17">Establishing nomogram model</hd> <p>According to univariate and multivariate cox regression analyses, despite that risk score model could act as an independent prognostic factor in ccRCC patients (Fig. 3A, B), it had poorer predictive ability than certain clinicopathological features such as M stage. To better predict ccRCC patients' overall survival, we integrated three independent factors (Risk score, M stage and T stage) and established a nomogram model (Fig. 3C) and calculated the total points according to the model (for instance, a patients who was M0 stage, T2 stage and lower risk score had about 10 points and possessed 80–90% probability to survive longer than 5-years), furthermore, on the basis of TCGA data, the accuracy of nomogram model was validated by 3 and 5-year calibration curves (Fig. 3D, E), the lines mapped by predicted survival were uniformed with the lines of actual survival. Survival analysis of nomogram model demonstrated remarkably lower <emph>p</emph>-value than risk score (Fig. 3F), furthermore, 3 and 5-year ROC curves of nomogram model showed obviously large area under curves (AUC) (Fig. 3G), besides, nomogram model had better accuracy than its components in predicting 5-year overall survival in KIRC (kidney clear cell carcinoma) patients.</p> <p>Graph: Fig. 3 Evaluation of risk score and construction of nomogram model. (A, B) The results of univariate and multivariate cox analyses revealed that risk score could act as an independent prognostic factor. (C) Then we constructed a nomogram model by independent prognostic factors and (D, E) assessed its prognostic ability by 3 and 5-year calibration curves. (F–H) Survival analysis suggested that nomogram model could better predict ccRCC patients' overall survival.</p> <hd id="AN0182467219-18">Proteome and single cell analyses</hd> <p>By investigating the proteomic data (110 tumor tissues and 84 normal adjacent tissues were applied) of these targets, we observed consistent results with those originated from genomic data mentioned above (Figure S4A-C). Nonetheless, only the protein abundances of PLCG2 and TMEM38A were available. Furthermore, it revealed significantly elevated phosphorylation levels at multiple sites on PLCG2 in adjacent normal kidney tissues. We further explored the correlation between target genes and infiltrating immune cells through eight different classic tools, including MCPCOUNTER, EPIC and CIBERSORT. However, it should be noted that the results obtained from these tools exhibited slight discrepancies among each other. Therefore, we employe a more direct manner, namely single cell analysis, to visualize expression levels of targets in different cells using data from TISCH2 (Figure S4 D-F). We found that all targets, particularly TMEM38A, possessed a relative low abundance in immune and stromal cells within ccRCC tissues. Additionally, PLCG2 was mostly enriched in B cells and plasma cells, while SLC16A11 expression was preferentially higher in proliferating T cells and CD8+ exhausted T cells. According to data from CZ CELLxGENE, significantly higher expression of PLCG2 was observed in normal kidney tissues compared to ccRCC tissues, specifically in endothelial cells, macrophages, and B cells. The expression of PLCG2 and SLC16A11 in normal and ccRCC samples showed similar results in T cells. Due to extremely low level of TMEM38A in ccRCC tissues, it was hard to make comparison of their expressions (Figure S5).</p> <hd id="AN0182467219-19">Overexpression of PLCG2 and TMEM38A inhibits cell proliferation</hd> <p>As for in vitro experiments, we constructed gene overexpression cell models with PLCG2 and TMEM38A plasmids to investigate their corresponding effects in renal clear cell carcinoma cell lines. The overexpression efficiency of both PLCG2 and TMEM38A in 786-O and Caki-1 cell lines were quantified at the mRNA level (Fig. 4A–D). The CCK8 results demonstrated that the overexpression of PLCG2 and TMEM38A in the 786-O cell line significantly inhibited the proliferation of 786-O cells within a span of 24 h (Fig. 4E). The Caki cell line exhibited a similar effect, wherein the overexpression of the gene significantly impeded cellular proliferation (Fig. 4F). The colony formation experiments also demonstrated the inhibitory effect of PLCG2 and TMEM38A overexpression on the proliferation of two clear cell renal cell carcinoma cell lines (Fig. 4G–I).</p> <p>Graph: Fig. 4 The efficacy of plasmid and the proliferation change caused by overexpression in 786-O and Caki-1 cell line. (A) The relative expression of PLCG2 in 786-O cell line after transfected with plasmid at the mRNA level. (B) The relative expression of PLCG2 in Caki-1 cell line after transfected with plasmid at the mRNA level. (C) The relative expression of TMEM38A in PLCG2 cell line after transfected with plasmid at the mRNA level. (D) The relative expression of TMEM38A in Caki-1 cell line after transfected with plasmid at the mRNA level. (E) The cell viability of 786-O cell line after transfection at different time points (0, 24, 48, 72, 96 h) detected by CCK-8 assay. *: TMEM38A vs vector. #: PLCG2 vs vector. (F) The cell viability of Caki-1 cell line after transfection at different time points (0, 24, 48, 72, 96 h) detected by CCK-8 assay. *: TMEM38A vs vector. #: PLCG2 vs vector. (G) The results of colony-formation assay after overexpression of PLCG2 and TMEM38A in both 786-O and Caki-1 cell line. (H) Statistical results of colony-formation assay in 786-O cell line. (I)Statistical results of colony-formation assay in Caki-1 cell line. ##/**p < 0.01, ###/***p < 0.001.</p> <hd id="AN0182467219-20">Overexpression of PLCG2 and TMEM38A elicits apoptosis and induces G2/M phase cell cycle arres...</hd> <p>The flow cytometry results demonstrated that the overexpression of PLCG2 significantly augmented apoptosis levels in 786-O and Caki-1 cells (Fig. 5A–D). Similarly, overexpression of TMEM38A also showed the same results, with an increased apoptosis level of 786-O and Caki-1 cells (Fig. 5E–H). As for the cell cycle, both 786-O and Caki-1 cell lines showed G2/M phase arrest after overexpression of PLCG2 and TMEM38A (Fig. 6A–H). The experimental results concurrently demonstrated that the overexpression of these two genes in the Caki-1 cell line also induced S-phase arrest (Fig. 6C, D, G, H).</p> <p>Graph: Fig. 5 Overexpression of PLCG2 and TMEM38A promote cell apoptosis in 786-O and Caki-1 cell line. (A, B) After transfected with either PLCG2 plasmid and vector, the apoptotic cells staining with Annexin V and PI were detected by flow cytometry. (C, D) Flow cytometry analysis and statistical findings of apoptosis following PLCG2 overexpression in the Caki-1 cell line. (E, F) Flow cytometry analysis and statistical findings of apoptosis following TMEM38A overexpression in the 786-O cell line. (G, H) Flow cytometry analysis and statistical findings of apoptosis following TMEM38A overexpression in the Caki-1 cell line. **p < 0.01.</p> <p>Graph: Fig. 6 The overexpression of PLCG2 and TMEM38A resulted in G2 phase arrest in 786-O and Caki-1 cell line. (A) Cell cycle results detected by flow cytometry in 786-O cells transfected with PLCG2 plasmid. (B) The percentage of cell population (%) at different cell cycle stages (G0/G1, S, G2/M). (C, D) The effect of PLCG2 overexpression on cell cycle in Caki-1 cell line. (E, F) The effect of TMEM38A overexpression on cell cycle in 786-O cell line. (G, H) The effect of TMEM38A overexpression on cell cycle in Caki-1 cell line. *p < 0.05, **p < 0.01.</p> <hd id="AN0182467219-21">Overexpression of PLCG2 and TMEM38A attenuates epithelial-mesenchymal transition in Caki-1 ce...</hd> <p>After overexpressing PLCG2 and TMEM38A, we quantified the mRNA levels of genes associated with EMT in 786-O and Caki-1 cells. The experimental results demonstrated that the expression of E-cadherin was upregulated, whereas Vimentin exhibited downregulation. No statistically significant disparity was observed in the expression levels of Snail and N-cadherin in 786-O cell line. (Fig. 7A). The overexpression of PLCG2 and TMEM38A led to an upregulation of epithelial cell marker (E-cadherin) and a significant downregulation of mesenchymal cell markers (Vimentin, Snail, N-cadherin) in Caki-1 cells (Fig. 7B).</p> <p>Graph: Fig. 7 Changes in the expression of EMT-associated markers following overexpression of PLCG2 and TMEM38A. (A) The relative profiles of E-cadherin, Vimentin, snail and N-cadherin in 786-O cell line at the mRNA level. (B) The relative expression of E-cadherin, Vimentin, snail and N-cadherin in Caki-1 cell line at the mRNA level. (C, D) The relative protein levels as well as the corresponding quantitative data of EMT markers (N-cadherin, E-cadherin and Vimentin), apoptosis markers (Bcl-2 and Bax) and target proteins (PLCG2 and TMEM38A) in both cell lines following the elevation of PLCG2 and TMEM38A. *p < 0.05***p < 0.001, NS means no significant difference.</p> <hd id="AN0182467219-22">Observation of the protein levels modified by the elevation of target genes</hd> <p>The results of western-blotting and the quantitative data (Fig. 7C, D) analysis were in line with our results obtained from PCR, (the <emph>p</emph>-value of all proteins were < 0.05, however there were too many columns in Fig. 7D, so we declare it over here), so we observed increasements of VIM and N-cadherin, while reduction of E-cadherin, suggesting the occurrence of EMT after overexpressing the target genes. On the other hand, we also found more cell mortalities and less cell proliferation in both cell lines by investigating the protein levels of BAX and Bcl-2.</p> <hd id="AN0182467219-23">Validation of protein levels of PLCG2 and TMEM38A in Chinese human tissues</hd> <p>Finally, we did IHC analyses in two TMAs to separately explore the protein levels of these two genes in 10 pairs of Chinese human tissues, according to our results, the protein level of PLCG2 was drastically low in ccRCC tissues compared to its paired normal tissues (Fig. 8A). Nevertheless, despite the trend of higher TMEM38A in normal tissues, the protein levels of TMEM38A did not represent significant difference (Fig. 8B). Besides, we performed correlation analysis of PLCG2 and TMEM38A with EMT-markers in proteomic level, the results were in line that of previous in silico and in vitro experiments (Figure S6).</p> <p>Graph: Fig. 8 Immunostaining of PLCG2 and TMEM38A in native human ccRCC and adjacent non-tumor kidney tissues tissues. (A) Representative IHC images and quantitative analysis of PLCG2 in ccRCC and normal kidney tissues (B) Representative IHC images and quantitative analysis of TMEM38A in ccRCC and normal kidney tissues. ***p < 0.01, NS means no significant difference.</p> <hd id="AN0182467219-24">Discussion</hd> <p>In this experiment, tumor suppressor genes related to EMT and prognosis of renal clear cell carcinoma were screened through bioinformatics technology, and the roles of PLCG2 and TMEM38A in renal clear cell carcinoma cell lines were explored through cell experiments, providing a new possible perspective for the diagnosis and treatment of renal clear cell carcinoma in the future. Although early studies have extensively investigated CCRCC-related genes and pathways[<reflink idref="bib38" id="ref53">38</reflink>], [<reflink idref="bib39" id="ref54">39</reflink>]–[<reflink idref="bib40" id="ref55">40</reflink>], the research on tumor suppressor genes associated with CCRCC primarily focuses on VHL mutations[<reflink idref="bib41" id="ref56">41</reflink>],[<reflink idref="bib42" id="ref57">42</reflink>], while investigations into EMT and prognosis remain relatively limited.</p> <p>In the current study, four genes (PLCG2, SLC16A11, TMEM38A and TMEM213) were selected as potential tumor suppressor genes that related to EMT. In line with our findings, <emph>Wesoly</emph> et al. demonstrated a significant downregulation of TMEM213 expression in renal clear cell carcinoma[<reflink idref="bib43" id="ref58">43</reflink>], while <emph>Bao Juan</emph> et al. reported a similar significant reduction in its expression among HIV-infected patients with renal malignant tumors[<reflink idref="bib44" id="ref59">44</reflink>]. SLC16A11 has been identified as a key factor related with triacylglycerol metabolism in the treatment of type 2 diabetes[<reflink idref="bib45" id="ref60">45</reflink>], [<reflink idref="bib46" id="ref61">46</reflink>]–[<reflink idref="bib47" id="ref62">47</reflink>], however, its relationship with cancer remains unexplored. For more precise screening, we also adopted differentially expressed genes between patients with distinct metastasis situation. After that we validated their mRNA expression profiles in multi-array and further investigated their differential expression in exon, crisper gene effect and proteome levels, whose results justified their lower expression in ccRCC tissues.</p> <p>To assess the prognostic value of these genes, we constructed a prognostic model including three EMT-related genes (PLCG2, SLC16A11, TMEM38A) via LASSO analysis. Subsequently, through Cox analyses, we identified this model as an independent prognostic factor and combined it with other independent factors as a nomogram model, which showed extraordinarily enhanced 3 and 5-year prognostic capability. The accuracy of this model was proved by ROC and calibration curves.</p> <p>Clear cell renal cell carcinoma is highly immune-invasive, and its tumor microenvironment contains a variety of immune cell infiltrates, such as T cells, B cells, and tumor killer cells[<reflink idref="bib38" id="ref63">38</reflink>],[<reflink idref="bib44" id="ref64">44</reflink>]. For deeper investigation of our targets, we selected single cell analyses to explore the targets expression in diverse cell types, especially immune cells and stromal cells. Our findings revealed that these targets, notably PLCG2, exhibited higher expression levels in immune cells, particularly in normal tissues compared to their corresponding tumor counterparts. And in other pathological conditions, a significant correlation has been discovered between PLCG2 and immune response by clinical sequencing of patients. PLCG2 could cause 2 related forms of autosomal-dominant immune dysregulation (ID), PLCG2-associated antibody deficiency and immune dysregulation (PLAID) and autoinflammatory PLAID (APLAID)[<reflink idref="bib48" id="ref65">48</reflink>], [<reflink idref="bib49" id="ref66">49</reflink>]–[<reflink idref="bib50" id="ref67">50</reflink>]. However, the precise mechanism underlying the immunoregulatory role of PLCG2 in renal clear cell carcinoma remains elusive and necessitates further exploration through comprehensive experimental investigations.</p> <p>To further illustrate the potential molecular mechanism of two related genes PLCG2 and TMEM38A in ccRCC, we conducted in vitro experiments to investigate its impact on cellular proliferation, apoptosis, cell cycle progression, and EMT. The cell viability of both cell lines was significantly reduced after gene overexpression, as evidenced by CCK8 and colony formation experiments which may be attributed to the induction of apoptosis and alterations in the cell cycle. Interestingly, the experimental results demonstrated a significant increase in the apoptotic trend upon overexpression of two genes in distinct cell lines. Our experiments have revealed for the first time the impact of TMEM38A on cell apoptosis. The TMEM family proteins play pivotal roles in diverse cellular processes, including cell migration, differentiation, aggregation, adhesion, lysis, and regulation of signal transduction. As for apoptosis, the experimental findings have demonstrated that miR-421 exerts its pro-apoptotic effects through the inhibition of TMEM48 in A549 cell line[<reflink idref="bib51" id="ref68">51</reflink>]. TMEM168 promotes the apoptosis of U87 cells and inhibits the proliferation of U87 cells by inhibiting Wnt/β-catenin activation[<reflink idref="bib52" id="ref69">52</reflink>]. In addition, <emph>Chen Xiaoguang</emph> et al. found that PLCG2 can induce apoptosis of rat hepatocytes through P38 and JNK MAPK pathways[<reflink idref="bib53" id="ref70">53</reflink>], and <emph>Hu Xiao</emph> et al. found that PLCG2 can regulate apoptosis of rat neurons after oxidative stress as a member of the CSF1R/PLCG2/PKA/UCP2 signaling pathway[<reflink idref="bib54" id="ref71">54</reflink>]. These experimental results are consistent with our in vitro study. Simultaneously, after overexpressing the two genes, we observed a significant G2/M phase arrest in both 786-O and Caki-1 cell lines. Interestingly, our findings revealed that the upregulation of PLCG2 and TMEM38A expression also induced S-phase arrest in the Caki-1 cell line, thereby suggesting their influence on DNA replication[<reflink idref="bib55" id="ref72">55</reflink>]. Tumour growth depends on continued cell proliferation[<reflink idref="bib56" id="ref73">56</reflink>], the modulation of PLCG2 and TMEM38A on the cell cycle presents a promising therapeutic target.</p> <p>The process of EMT plays a pivotal role in determining the most aggressive characteristics of cancer, including the formation of metastases and resistance to chemotherapy[<reflink idref="bib57" id="ref74">57</reflink>]. The results of our in vitro experiments were consistent with the findings from bioinformatics analysis, demonstrating that the overexpression of these two genes could upregulate E-cadherin as well as reduce Vimentin and N-cadherin in protein level, which subsequently suppressing the EMT process in both two types of renal clear cell carcinoma cells. Although we have conducted preliminary investigations, the precise mechanisms underlying drug resistance and metastasis remain to be elucidated. In order to gain further insights, we intend to employ cellular experiments and animal models to fulfill xenograft transplantation experiment[<reflink idref="bib58" id="ref75">58</reflink>] in our future studies for a comprehensive exploration of the two genes' involvement.</p> <hd id="AN0182467219-25">Conclusions</hd> <p>Overall, by applying bioinformatics analyses, we have discovered potential prognostic tumor suppressors and utilized them to stratify ccRCC patients into high and low risk groups. Our in vitro experiments revealed the effects of overexpressing PLCG2 and TMEM38A on cell proliferation, apoptosis, cell cycle, and EMT in Caki-1 and 786-O cell lines, and found that they can be used as one of the potential therapeutic targets for renal clear cell carcinoma in the future.</p> <hd id="AN0182467219-26">Author contributions</hd> <p>Yiqiao Zhao: Software, Methodology, Writing—Original Draft, Visualization, Project administration. Liang Yang: Investigation, Methodology, Resources, Writing—Original Draft, Conceptualization, Project administration. Xiaojie Bai: Methodology, Resources. Lu Du: Validation, Formal analysis. Huan Lai: Data Curation. Yiyang Liu: Software. Ping Chen: Funding acquisition, Resources. Michael E DiSanto: Project administration. Xinhua Zhang: Funding acquisition, Resources, Conceptualization, Project administration.</p> <hd id="AN0182467219-27">Funding</hd> <p>This work was supported by the National Natural Science Foundation of China (Grant Numbers 82270814, 82100817).</p> <hd id="AN0182467219-28">Data availability</hd> <p>The data generated or analyzed in this study are available in the UCSC xena (https://xena.ucsc.edu/), GEO (https://<ulink href="http://www.ncbi.nlm.nih.gov/geo),">www.ncbi.nlm.nih.gov/geo),</ulink> Depmap portal (https://depmap.org), TISCH2 (<ulink href="http://tisch.comp-genomics.org/home/">http://tisch.comp-genomics.org/home/</ulink>), CZ CELLxGENE (https://cellxgene.cziscience.com/gene-expression), and PDC dataset (https://pdc.cancer.gov).</p> <hd id="AN0182467219-29">Declarations</hd> <p></p> <hd id="AN0182467219-30">Competing interests</hd> <p>The authors declare no competing interests.</p> <hd id="AN0182467219-31">Electronic supplementary material</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary Material 1</p> <p>Graph: Supplementary Material 2</p> <p>Graph: Supplementary Material 3</p> <p>Graph: Supplementary Material 4</p> <p>Graph: Supplementary Material 5</p> <p>Graph: Supplementary Material 6</p> <p>Graph: Supplementary Material 7</p> <p>Graph: Supplementary Material 8</p> <p>Graph: Supplementary Material 9</p> <p>Graph: Supplementary Material 10</p> <p>Graph: Supplementary Material 11</p> <p>Graph: Supplementary Material 12</p> <p>Graph: Supplementary Material 13</p> <p>Graph: Supplementary Material 14</p> <p>Graph: Supplementary Material 15</p> <p>Graph: Supplementary Material 16</p> <p>Graph: Supplementary Material 17</p> <hd id="AN0182467219-32">Publisher's note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0182467219-33"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A. 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  Data: Efficacy and safety of neoadjuvant therapy with tislelizumab plus axitinib for nonmetastatic renal cell carcinoma with inferior vena cava tumor thrombus: a retrospective study
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  Data: <searchLink fieldCode="AR" term="%22Zhongjie+Zhao%22">Zhongjie Zhao</searchLink><br /><searchLink fieldCode="AR" term="%22Zhengsheng+Liu%22">Zhengsheng Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Kaiyan+Zhang%22">Kaiyan Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Wei+Li%22">Wei Li</searchLink><br /><searchLink fieldCode="AR" term="%22Lijian+Zhang%22">Lijian Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Bingliang+Jiang%22">Bingliang Jiang</searchLink><br /><searchLink fieldCode="AR" term="%22Bin+Chen%22">Bin Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Jinchun+Xing%22">Jinchun Xing</searchLink><br /><searchLink fieldCode="AR" term="%22Xuegang+Wang%22">Xuegang Wang</searchLink>
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  Data: Scientific Reports, Vol 15, Iss 1, Pp 1-8 (2025)
– Name: Publisher
  Label: Publisher Information
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  Data: Nature Portfolio, 2025.
– Name: DatePubCY
  Label: Publication Year
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  Data: 2025
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  Data: LCC:Medicine<br />LCC:Science
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Tislelizumab%22">Tislelizumab</searchLink><br /><searchLink fieldCode="DE" term="%22Axitinib%22">Axitinib</searchLink><br /><searchLink fieldCode="DE" term="%22Renal+cell+carcinoma+%28RCC%29%22">Renal cell carcinoma (RCC)</searchLink><br /><searchLink fieldCode="DE" term="%22Inferior+vena+cava+%28IVC%29+tumor+thrombus%22">Inferior vena cava (IVC) tumor thrombus</searchLink><br /><searchLink fieldCode="DE" term="%22Neoadjuvant+therapy%22">Neoadjuvant therapy</searchLink><br /><searchLink fieldCode="DE" term="%22Medicine%22">Medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Science%22">Science</searchLink>
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  Data: Abstract In renal cell carcinoma (RCC) patients with inferior vena cava (IVC) tumor thrombus, neoadjuvant therapy could alleviate the burden of tumor thrombus, enhance the safety and feasibility of surgical resection, and improve patient prognosis. The combination of tislelizumab and axitinib has demonstrated efficacy in the treatment of advanced RCC. Our study aimed to evaluate the efficacy and safety in the neoadjuvant therapy setting of tislelizumab and axitinib in RCC patients with IVC tumor thrombus. In this retrospective study, seven patients of nonmetastatic RCC with IVC tumor thrombus who received 3 cycles of neoadjuvant therapy with tislelizumab plus axitinib at the First Affiliated Hospital of Xiamen University from May 2020 to December 2023 were included. The main outcomes included objective response rate (ORR), reduction of tumor thrombus size and level, surgical outcomes, and adverse events (AEs). The median age was 66 (range, 50–72) years, and five (71.4%) patients were male. Five (71.4%) patients were diagnosed with clear cell carcinoma, and two (28.6%) patients were papillary type I carcinoma. Four (57.1%) patients had level II tumor thrombus and three (42.9%) patients had level III. The ORR of patients was 57.1%. The mean decrease in thrombus diameter and length was 5.8 (1.8–17.2) mm and 18.5 (4.4–41.5) mm, respectively. All patients showed a decrease in IVC tumor thrombus. The mean time from the end of neoadjuvant therapy to radical nephrectomy and thrombectomy was 31.7(range, 22–45) days. No intraoperative complications or postoperative Clavien-Dindo grade>3 complications occurred. The most common AEs were all grade 1–2, and only one patient had grade 4 hepatic impairment. No AEs delayed the surgery schedule. This study of RCC patients receiving neoadjuvant combination with tislelizumab and axitinib effectively reduced primary tumor and IVC tumor thrombus with the absence of serious AEs, demonstrating a promising neoadjuvant therapy.
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  Data: 10.1038/s41598-025-86712-6
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      – Type: doi
        Value: 10.1038/s41598-025-86712-6
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 8
        StartPage: 1
    Subjects:
      – SubjectFull: Tislelizumab
        Type: general
      – SubjectFull: Axitinib
        Type: general
      – SubjectFull: Renal cell carcinoma (RCC)
        Type: general
      – SubjectFull: Inferior vena cava (IVC) tumor thrombus
        Type: general
      – SubjectFull: Neoadjuvant therapy
        Type: general
      – SubjectFull: Medicine
        Type: general
      – SubjectFull: Science
        Type: general
    Titles:
      – TitleFull: Efficacy and safety of neoadjuvant therapy with tislelizumab plus axitinib for nonmetastatic renal cell carcinoma with inferior vena cava tumor thrombus: a retrospective study
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            NameFull: Zhongjie Zhao
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            NameFull: Zhengsheng Liu
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              M: 01
              Type: published
              Y: 2025
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