Renal Carcinoma Research Articles

Meta-analysis of the diagnostic value of exosomal microRNAs in renal cell carcinoma

AimThis meta-analysis aims to evaluate the potential of exosomal microRNAs(Exo-miRs) as diagnostic biomarkers for renal cell carcinoma(RCC).MethodsClinical studies reporting the use of Exo-miRs in the diagnosis of RCC were retrieved from PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Chinese Biomedical Literature Database (SinoMed). After relevant data were screened and extracted, the quality of the included studies was assessed using the QUADAS-2 tool. The Meta-disc (version 1.4) software was used to analyze the heterogeneity of threshold/non-threshold effects in the included studies. The Stata MP (version 16.0) software was used to calculate sensitivity(Sen), specificity(Spe), positive likelihood ratio(+LR), negative likelihood ratio(-LR), area under the curve(AUC), diagnostic odds ratio(DOR), and publication bias.ResultsA total of 11 studies were included in this meta-analysis. Spearman correlation coefficient was 0.319 (P = 0.075; >0.05), indicating no threshold effects. The pooled Sen, Spe, +LR, -LR, DOR, and AUC were 0.73 (95% CI, 0.68–0.78), 0.81 (95% CI, 0.76–0.85), 3.80 (95% CI, 3.02–4.77), 0.33 (95% CI, 0.28–0.40), 11.48 (95% CI, 8.27–15.95), and 0.84 (95% CI, 0.80–0.87), respectively. No publication bias was detected among the included studies.ConclusionThe expression of Exo-miRs plays an important role in the diagnosis of RCC. However, owing to the limited number of included studies and heterogeneity among them, further clinical research is necessary to verify the findings of this meta-analysis.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42023445956.

First-line sunitinib treatment modification in patients with mRCC: nationwide analysis of the Swedish population.

Aim: Assess first-line sunitinib dosing for treatment of metastatic renal cell carcinoma in Swedish clinical practice (2006-2019).Materials & methods: Retrospective analysis of three sunitinib dosing regimens: 2-weeks on, 1-week off (2:1 Start); standard 4-weeks on, 2-weeks off (4:2) and 4:2 start with switch to 2:1 (2:1 Switch).Results: Time-to-treatment discontinuation (95% CI) differed significantly (p<0.001): 6.2 (5.6-7.2), 13.9 (8.1-20.6)and 4.6 (4.3-5.6) months for 2:1 Start (n=320), 2:1 Switch (n=71)and 4:2 (n=704), respectively. Overall survival (95% CI) differed significantly (p<0.001): 21.8 (18.1-26.1), 32.2 (25.1-48.3)and 13.5 (12.3-15.8) months for 2:1 Start (n=320), 2:1 Switch (n=71)and 4:2 (n=704), respectively.Conclusion: Alternative dosing does not compromise clinical efficacy and may provide advantages in terms of improved treatment outcomes. However, due to the changing treatment patterns during this long-term study, and the absence of patient risk category data, caution is required when interpreting the main outcomes.

Hypoxia-dependent recruitment of error-prone DNA polymerases to genome replication.

Hypoxia is common in tumors and is associated with cancer progression and drug resistance, driven, at least in part, by genetic instability. Little is known on how hypoxia affects Translesion DNA Synthesis (TLS), in which error-prone DNA polymerases bypass lesions, thereby maintaining DNA continuity at the price of increased mutations. Here we show that under acute hypoxia, PCNA monoubiquitination, a key step in TLS, and expression of error-prone DNA polymerases increased under regulation of the HIF1α transcription factor. Knocking-down expression of DNA polymerase η, or using PCNA ubiquitination-resistant cells, inhibited genomic DNA replication specifically under hypoxia, and iPOND analysis revealed massive recruitment of TLS DNA polymerases to nascent DNA under hypoxia, uncovering a dramatic involvement of error-prone DNA polymerases in genomic replication. Of note, expression of TLS-polymerases correlates with VEGFA (primary HIF1α target) in a database of renal cell carcinoma, a cancer which accumulates HIF1α. Our results suggest that the tumor microenvironment can lead the cell to forgo, to some extent, the fast and accurate canonical DNA polymerases, for the more flexible and robust, but low-fidelity TLS DNA polymerases. This might endow cancer cells with resilience to overcome replication stress, and mutability to escape the immune system and chemotherapeutic drugs.

Comparative Proteomics of ccRCC Cell Lines to Identify Kidney Cancer Progression Factors.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, accounting for approximately 75% of kidney cancers. The objective of this study was to identify novel progression markers for ccRCC based on proteomics, with the goal of stage determination and early diagnosis of kidney cancer patients. We performed quantitative global proteomics coupled with Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and high-resolution tandem mass spectrometry on kidney-derived cells, including HEK-293, 786-O (primary ccRCC), and Caki-1 (metastatic ccRCC) cells, to investigate the novel progression factors of ccRCC. In this study, a total of 1,106 proteins were quantified. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for differentially expressed proteins (DEPs) that were increased in ccRCC cells compared to HEK-293 cells. Ultimately, 99 DEPs including 75 up-regulated and 24 down-regulated proteins, that were significantly altered in both ccRCC cells, were identified. Among DEPs, vimentin was identified as the most significantly changed protein. Its increased expression in ccRCC was verified through immunoblotting in ccRCC cell lines and immunohistochemistry in kidney tumors. From the global proteomics data detected in ccRCC, we propose 99 DEPs including vimentin as progression factors.

Correction to "Advances in the management of renal cell carcinoma".

Correction to "Advances in the management of renal cell carcinoma".

Development and verification of a novel risk model related to ubiquitination linked with prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC.

Atractylenolide I inhibits angiogenesis and reverses sunitinib resistance in clear cell renal cell carcinoma through ATP6V0D2-mediated autophagic degradation of EPAS1/HIF2α

ABSTRACT Clear cell renal cell carcinoma (ccRCC) is tightly associated with VHL (von Hippel-Lindau tumor suppressor) mutation and dysregulated angiogenesis. Accumulating evidence indicates that antiangiogenic treatment abolishing tumor angiogenesis can achieve longer disease-free survival in patients with ccRCC. Atractylenolide I (ATL-I) is one of the main active compounds in Atractylodes macrocephala root extract and exhibits various pharmacological effects, including anti-inflammatory and antitumor effects. In this study, we revealed the potent antitumor activity of ATL-I in ccRCC. ATL-I exhibited robust antiangiogenic capacity by inhibiting EPAS1/HIF2α-mediated VEGFA production in VHL-deficient ccRCC, and it promoted autophagic degradation of EPAS1 by upregulating the ATPase subunit ATP6V0D2 (ATPase H+ transporting V0 subunit d2) to increase lysosomal function and facilitated fusion between autophagosomes and lysosomes. Mechanistically, ATP6V0D2 directly bound to RAB7 and VPS41 and promoted the RAB7-HOPS interaction, facilitating SNARE complex assembly and autophagosome-lysosome fusion. Moreover, ATP6V0D2 promoted autolysosome degradation by increasing the acidification and activity of lysosomes during the later stages of macroautophagy/autophagy. Additionally, we found that ATL-I could decrease the level of EPAS1, which was upregulated in sunitinib-resistant cells, thus reversing sunitinib resistance. Collectively, our findings demonstrate that ATL-I is a robust antiangiogenic and antitumor lead compound with potential clinical application for ccRCC therapy.

Decitabine Enhances Sorafenib Sensitivity in Renal Cell Carcinoma by Promoting BIN1 and SYNE1 Expressions.

Renal cell carcinoma (RCC), especially clear cell RCC (ccRCC), significantly impacts health, and results in particularly poor outcomes in patients at the advanced stage. Resistance to vascular endothelial growth factor (VEGF) pathway-targeting tyrosine kinase inhibitors (TKIs) is a major barrier in effective ccRCC treatment. Herein, we aim to explore how decitabine mediates bridging integrator 1 (BIN1) and spectrin repeat containing nuclear envelope protein 1 (SYNE1) to impact resistance of ccRCC to sorafenib. Employing bioinformatics on datasets GSE64052 and CancerSea, we identified genes linked to TKI resistance, ultimately focusing on SYNE1. We assessed influences of SYNE1 overexpression and BIN1 knockdown via quantitative real-time PCR (qRT-PCR) and Western blot. Assessment of cell viability and apoptosis was accomplished using cell counting kit-8 (CCK-8) assays and flow cytometry. The investigation into the potential interactions between SYNE1 and BIN1, as well as their impacts on sorafenib sensitivity was accomplished by Co-Immunoprecipitation (Co-IP) and Glutathione-S-transferase (GST) Pull-down. SYNE1 was substantially down-regulated in sorafenib-resistant ccRCC cells, and its overexpression increased sorafenib sensitivity, decreased viability and enhanced apoptosis. Interaction between BIN1 and SYNE1 was confirmed, with BIN1 level lower in resistant cells. BIN1 knockdown reduced the beneficial effects of SYNE1 overexpression on sorafenib sensitivity. Decitabine treatment elevated both SYNE1 and BIN1, while boosting apoptosis and reducing sorafenib resistance. SYNE1 contributes to the modulation of sorafenib resistance in ccRCC cells through interacting with BIN1. Decitabine treatment enhances expressions of these two proteins to improve TKI response, suggesting a potential strategy for counteracting resistance and bettering patient outcomes.

A Randomized Controlled Trial Assessing the Release of Circulating Tumor and Mesenchymal Cells in No-Touch Radical Nephrectomy.

Circulating tumor cells (CTCs) may be the missing renal cell carcinoma (RCC) biomarker. No-touch (NT) resection has shown benefit in several tumors. A randomized controlled trial comparing CTC and circulating mesenchymal cell (CMC) release in no-touch (NT) vs. conventional (C) laparoscopic RN. Blood samples were collected at operation room arrival (S0), specimen extraction (S1), postoperative D1, and D30. CTCs were isolated and analyzed using RUBYchip™. Thirty-four patients were included. No significant differences were found between groups in CTC and CMC counts, count variations between time points, complications, and survival. The total circulating cell detection rates in the NT, C, and overall RCC groups were 58.3%, 80.0%, and 70.4% at S0; 41.6%, 86.7%, and 66.7% at S1; 50.0%, 64.3%, and 60.0% at D1; and 54.5%, 42.9%, and 44.0% at D30, respectively. A progressive decrease in CMCs was observed in the C group after surgery, especially at D1 (4.78 to 1.64 CMCs/7.5 mL blood, p = 0.035). Healthy controls had no circulating cells; however, high CMC counts were found in chronic inflammation controls and oncocytoma patients, with no significant difference from RCC patients (p = 0.460). NT RN did not reduce circulating cell release nor improve survival compared to C RN.

Estimated cost of VEGFR TKI associated adverse events in metastatic renal cell carcinoma patients

IntroductionThe majority of metastatic renal cell carcinoma (mRCC) patients receive one or more VEGFR TKI agents, alone or in combination with an immune-oncology (IO) agent or an mTOR inhibitor. To date, the cost of adverse events (AEs) common to VEGFR TKIs has not been quantified. This study estimated the potential impact of differences in VEGFR TKI AE profiles on treatment cost efficiency in the relapsed/refractory (R/R) setting.MethodsPatients with documented mRCC who were treated with VEGFR TKI therapies between Jan 2015 and Mar 2021 were identified using EMR. ICD-10 diagnosis codes were used to identify the first occurrence of each class effect AE. Patients were matched to 3rd party insurance claims, and costs associated to TKI AEs within 90 days of index event were captured. Average per patient AE cost data was calculated and applied to published incidence data to estimate regimen-specific AE total cost burden within a hypothetical commercial plan for mRCC patients undergoing treatment in the R/R setting.ResultsThe highest total cost for AE management was attributed to lenvatinib and everolimus use at $13,303, followed closely by sunitinib at $13,092. Tivozanib treatment was associated with the lowest total cost of AE management at $7,523, driven by the relatively lower incidence of certain high-cost AEs.ConclusionsThe estimated costs of managing VEGFR TKI class-effect AEs were lowest with tivozanib, and highest with lenvatinib and everolimus, indicating potentially differential healthcare resource burden by TKI regimen. The use of tivozanib in the 3 L + mRCC setting suggests potential costs offsets when compared to other TKI regimens.

A framework for target discovery in rare cancers.

While large-scale functional genetic screens have uncovered numerous cancer dependencies, rare cancers are poorly represented in such efforts and the landscape of dependencies in many rare cancers remains obscure. We performed genome-scale CRISPR knockout screens in an exemplar rare cancer, TFE3- translocation renal cell carcinoma (tRCC), revealing previously unknown tRCC-selective dependencies in pathways related to mitochondrial biogenesis, oxidative metabolism, and kidney lineage specification. To generalize to other rare cancers in which experimental models may not be readily available, we employed machine learning to infer gene dependencies in a tumor or cell line based on its transcriptional profile. By applying dependency prediction to alveolar soft part sarcoma (ASPS), a distinct rare cancer also driven by TFE3 translocations, we discovered and validated that MCL1 represents a dependency in ASPS but not tRCC. Finally, we applied our model to predict gene dependencies in tumors from the TCGA (11,373 tumors; 28 lineages) and multiple additional rare cancers (958 tumors across 16 types, including 13 distinct subtypes of kidney cancer), nominating potentially actionable vulnerabilities in several poorly-characterized cancer types. Our results couple unbiased functional genetic screening with a predictive model to establish a landscape of candidate vulnerabilities across cancers, including several rare cancers currently lacking in potential targets.

Plain language summary of quality of life in CheckMate 9ER: Cabozantinib plus nivolumab in advanced renal cell carcinoma.

Plain language summary of quality of life in CheckMate 9ER: Cabozantinib plus nivolumab in advanced renal cell carcinoma.

Identification of exosomal ceRNA networks as prognostic markers in clear cell renal cell carcinoma.

Aggressive clear cell renal cell carcinoma (ccRCC) has a bad prognosis. We seek new ccRCC biomarkers for diagnosis and treatment. We used exoRBase and The Cancer Genome Atlas Database to compare DEmRNAs, DEmiRNAs, DElncRNAs, and DEcircRNAs in ccRCC and normal renal tissues. CircRNAs and circRNAs targeting microRNAs (miRNAs) were anticipated and taken intersections, and several databases assessed the targeted link between common miRNAs and messenger RNAs (mRNAs). The Cancer Genome Atlas database was used to create a predictive mRNA signature that was validated in E-MTAB-1980. Finally, we examined competing endogenous RNA network miRNAs and long noncoding RNAs for ccRCC predictive biomarkers using overall survival analysis. We built the first competing endogenous RNA regulation network of circRNA-lncRNA-miRNA-mRNA and found that it substantially correlates with ccRCC prognosis. We unveiled ccRCC's posttranscriptional regulation mechanism in greater detail. Our findings identified novel biomarkers for ccRCC diagnosis, therapy, and prognosis.

Comprehensive assessment of the association between tumor-infiltrating immune cells and the prognosis of renal cell carcinoma.

According to current statistics, renal cancer accounts for 3% of all cancers worldwide. Renal cell carcinoma (RCC) is the most common solid lesion in the kidney and accounts for approximately 90% of all renal malignancies. Increasing evidence has shown an association between immune infiltration in RCC and clinical outcomes. To discover possible targets for the immune system, we investigated the link between tumor-infiltrating immune cells (TIICs) and the prognosis of RCC. To investigate the effects of 22 TIICs on the prognosis of RCC patients and identify potential therapeutic targets for RCC immunotherapy. The CIBERSORT algorithm partitioned the 22 TIICs from the Cancer Genome Atlas cohort into proportions. Cox regression analysis was employed to evaluate the impact of 22 TIICs on the probability of developing RCC. A predictive model for immunological risk was developed by analyzing the statistical relationship between the subpopulations of TIICs and survival outcomes. Furthermore, multivariate Cox regression analysis was used to investigate independent factors for the prognostic prediction of RCC. A value of P < 0.05 was regarded as statistically significant. Compared to normal tissues, RCC tissues exhibited a distinct infiltration of immune cells. An immune risk score model was established and univariate Cox regression analysis revealed a significant association between four immune cell types and the survival risk connected to RCC. High-risk individuals were correlated to poorer outcomes according to the Kaplan-Meier survival curve (P = 1E-05). The immunological risk score model was demonstrated to be a dependable predictor of survival risk (area under the curve = 0.747) via the receiver operating characteristic curve. According to multivariate Cox regression analysis, the immune risk score model independently predicted RCC patients' prognosis (hazard ratio = 1.550, 95%CI: 1.342-1.791; P < 0.001). Finally, we established a nomogram that accurately and comprehensively forecast the survival of patients with RCC. TIICs play various roles in RCC prognosis. The immunological risk score is an independent predictor of poor survival in kidney cancer cases.

Aggressiveness classification of clear cell renal cell carcinoma using registration-independent radiology-pathology correlation learning.

Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Clear cell RCC (ccRCC) is the most common RCC subtype, with both aggressive and indolent manifestations. Indolent ccRCC is often low-grade without necrosis and can be monitored without treatment. Aggressive ccRCC is often high-grade and can cause metastasis and death if not promptly detected and treated. While most RCCs are detected on computed tomography (CT) scans, aggressiveness classification is based on pathology images acquired from invasive biopsy orsurgery. CT imaging-based aggressiveness classification would be an important clinical advance, as it would facilitate non-invasive risk stratification and treatment planning. Here, we present a novel machine learning method, Correlated Feature Aggregation By Region (CorrFABR), for CT-based aggressiveness classification ofccRCC. CorrFABR is a multimodal fusion algorithm that learns from radiology and pathology images, and clinical variables in a clinically-relevant manner. CorrFABR leverages registration-independent radiology (CT) and pathology image correlations using features from vision transformer-based foundation models to facilitate aggressiveness assessment on CT images. CorrFABR consists of three main steps: (a) Feature aggregation where region-level features are extracted from radiology and pathology images at widely varying image resolutions, (b) Fusion where radiology features correlated with pathology features (pathology-informed CT biomarkers) are learned, and (c) Classification where the learned pathology-informed CT biomarkers, together with clinical variables of tumor diameter, gender, and age, are used to distinguish aggressive from indolent ccRCC using multi-layer perceptron-based classifiers. Pathology images are only required in the first two steps of CorrFABR, and are not required in the prediction module. Therefore, CorrFABR integrates information from CT images, pathology images, and clinical variables during training, but for inference, it relies solely on CT images and clinical variables, ensuring its clinical applicability. CorrFABR was trained with heterogenous, publicly-available data from 298 ccRCC tumors (136 indolent tumors, 162 aggressive tumors) in a five-fold cross-validation setup and evaluated on an independent test set of 74 tumors with a balanced distribution of aggressive and indolent tumors. Ablation studies were performed to test the utility of each component ofCorrFABR. CorrFABR outperformed the other classification methods, achieving an ROC-AUC (area under the curve) of 0.855±0.0005 (95% confidence interval: 0.775, 0.947), F1-score of 0.793±0.029, sensitivity of 0.741±0.058, and specificity of 0.876±0.032 in classifying ccRCC as aggressive or indolent subtypes. It was found that pathology-informed CT biomarkers learned through registration-independent correlation learning improves classification performance over using CT features alone, irrespective of the kind of features or the classification model used. Tumor diameter, gender, and age provide complementary clinical information, and integrating pathology-informed CT biomarkers with these clinical variables further improvesperformance. CorrFABR provides a novel method for CT-based aggressiveness classification of ccRCC by enabling the identification of pathology-informed CT biomarkers, and integrating them with clinical variables. CorrFABR enables learning of these pathology-informed CT biomarkers through a novel registration-independent correlation learning module that considers unaligned radiology and pathology images at widely varying imageresolutions.

In Silico Design of Novel Piperazine-Based mTORC1 Inhibitors Through DFT, QSAR and ADME Investigations

Mammalian target of rapamycin complex 1 (mTORC1) is an important and promising alternative biological target for the treatment of different types of cancer including breast, lung and renal cell carcinoma. This study contributed to the development of mathematical models highlighting the quantitative structure-activity relationship of a series of piperazine derivatives reported as mTORC1 inhibitors. Various molecular descriptors were calculated using Gaussian 09, Chemsketch, and ChemOffice software. The density funcional theory (DFT) method at the level B3LYP/6-31G+(d, p) was applied to determine the structural, electronic and energetic parameters associated with the studied molecules. The predictive ability of the built models, which is obtained by two methods (MLR and MNLR), showed that the built models are statistically significant. The QSAR modeling results revealed that the six molecular descriptors of lowest unoccupied molecular orbital energy (ELUMO), electrophilicity index (ω), molar refractivity (MR), aqueous solubility (Log S), topological polar surface area (PSA), and refractive index (n) significantly correlated to the biological inhibitory activity of piperazine derivatives. Using QSAR models and in silico pharmacokinetic profiles predictions, five new candidate compounds are selected as potential inhibitors against cancer.

Update on Tumor Genetics and Molecular Biology of Selected Renal Cell Carcinomas: Implications on Diagnosis and Management

Recent advances in genetics, molecular pathology and oncology have led to discovery of specific genetic changes and distinctive metabolic pathways that contribute to tumorigenesis as well as determine the biological behavior and imaging findings of a multitude of renal cell carcinomas. Multiphase CT and multiparametric MRI play major roles in the detection, localization, characterization, staging, surveillance, and follow-up of kidney cancers. While some imaging features are characteristic enough to suggest a tissue diagnosis, histopathology is required for definitive diagnosis, treatment, and prognostication.

Knockout of the Carbohydrate Responsive Element Binding Protein Enhances Proliferation and Tumorigenesis in Renal Tubules of Mice.

Glycogen-storing so-called clear cell kidney tubules (CCTs), precursor lesions of renal cell carcinoma, have been described in diabetic rats and in humans. The lesions show upregulation of the Akt/mTOR-pathway and the related transcription factor carbohydrate responsive element binding protein (ChREBP), which is supposedly pro-oncogenic. We investigated the effect of ChREBP-knockout on nephrocarcinogenesis in streptozotocin-induced diabetic and normoglycemic mice. Diabetic, but not non-diabetic mice, showed CCTs at 3, 6 and 12 months of age. Glycogenosis was confirmed by periodic acid schiff reaction and transmission electron microscopy. CCTs in ChREBP-knockout mice consisted of larger cells and occurred more frequently compared to wildtype mice. Progression towards kidney tumors was observed in both diabetic groups but occurred earlier in ChREBP-knockout mice. Proliferative activity assessed by BrdU-labeling was lower in 1-week-old but higher in 12-month-old diabetic ChREBP-knockout mice. Surprisingly, renal neoplasms occurred spontaneously in non-diabetic ChREBP-knockout, but not non-diabetic wildtype mice, indicating an unexpected tumor-suppressive function of ChREBP. Immunohistochemistry showed upregulated glycolysis and lipogenesis, along with activated Akt/mTOR-signaling in tumors of ChREBP-knockout groups. Immunohistochemistry of human clear cell renal cell carcinomas revealed reduced ChREBP expression compared to normal kidney tissue. However, the molecular mechanisms by which loss of ChREBP might facilitate tumorigenesis require further investigation.

EFFICACY OF NEOADJUVANT TARGETED THERAPY IN TREATMENT OF PATIENTS WITH LOCALISED CLEAR-CELL RENAL CELL CARCINOMA

Clear-cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, accounting for approximately 75-80% of all renal malignancies. Objectives: The main objective of the study is to find the efficacy of neoadjuvant targeted therapy in the treatment of patients with localised clear-cell renal cell carcinoma. Methods: This prospective study was conducted at Mardan Medical Complex from June 2023 to January 2024. Data were collected from 85 patients. Patients aged&gt;18 years and have a histologically confirmed diagnosis of localized ccRCC were included in the study. Tumor size was required to be 4 cm or larger, but confined to the kidney, corresponding to Stage I to III disease. Results: Data were collected from 85 patients with an average baseline tumour size for the entire cohort was 7.5 cm, and after 12 weeks of treatment, tumours shrank to an average of 5.6 cm, resulting in a mean tumour reduction of 25%. In the sunitinib group, the tumour size decreased from 7.5 cm to 5.55 cm, reflecting a 26% reduction. Similarly, in the pazopanib group, the tumour size was reduced from 7.5 cm to 5.65 cm, with an average reduction of 24%. Conclusion: It is concluded that neoadjuvant targeted therapy, using agents such as sunitinib and pazopanib, effectively reduces tumour size and improves surgical outcomes in patients with localized clear-cell renal cell carcinoma.

Predicting the prognosis of patients with renal cell carcinoma based on the systemic immune inflammation index and prognostic nutritional index

The aim of the study was to analyze and discuss the value of preoperative systemic immune inflammation index (SII) and prognostic nutritional index (PNI) in predicting the prognosis of patients with renal cell carcinoma (RCC) after operation, and to establish a nomogram prediction model for patients with RCC after operation based on SII and PNI. From January 2014 to December 2018, 210 patients with RCC who underwent surgical treatment at the Xuzhou Central Hospital were selected as the research object. The receiver operating characteristic curve (ROC) was used to determine the optimal cut-off value for preoperative SII, PNI, LMR, PLR, NLR and the patients were divided into groups according to the optimal cutoff values. The survival rate of patients was evaluated. The risk factors that affect the prognosis of patients with RCC were determined by LASSO and Cox regression analysis, and a prognostic nomogram was constructed based on this result. The bootstrap method was used for internal verification of the nomogram model. The prediction efficiency and discrimination of the nomogram model were evaluated by the calibration curve and index of concordance (C-index), respectively. The average overall survival (OS) of all patients was 75.385 months, and the 1-, 2-and 3-year survival rates were 95.5%, 86.6% and 77.2%, respectively. The survival curve showed that the 5-year OS rate of low SII group was significantly higher than that of high SII group (89.0% vs. 64.5%; P < 0.05), and low PNI group was significantly lower than those in high PNI group (43.4% vs. 87.9%; p < 0.05). There were significant differences between preoperative SII and CRP, NLR, PLR, LMR, postoperative recurrence, pathological type and AJCC stage (P < 0.05). There were significant differences between preoperative PNI and BMI, platelet, NLR, PLR, LMR, postoperative recurrence, surgical mode and Fuhrman grade (P < 0.05). The ROC curve analysis showed that the AUC of PNI (AUC = 0.736) was higher than that of other inflammatory indicators, followed by the AUC of SII (0.718), and the difference in AUC area between groups was statistically significant (P < 0.05). The results from multivariate Cox regression analysis showed that SII, PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade were independent risk factors for postoperative death of patients with RCC. According to the results of Cox regression analysis, a prediction model for the prognosis of RCC patients was established, and the C-index (0.918) showed that the model had good calibration and discrimination. The subject’s operating characteristic curve indicates that the nomogram has good prediction efficiency (the AUC = 0.953). Preoperative SII and PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade are closely related to the postoperative prognosis of patients with renal cell carcinoma. The nomogram model based on SII, PNI, tumor size, tumor necrosis, surgical mode, pathological type, CRP, AJCC stage and Fuhrman grade has good accuracy, discrimination and clinical prediction efficiency.