Influence of cryoablation versus operation on circulating lymphocyte subsets in patients with early-stage renal cell carcinoma.

Immune response is known to play an important role in local tumor control especially in renal cell carcinoma (RCC), which is considered highly immunogenic. For localized tumors, operative resection or local ablative procedures such as cryoablation are common therapeutical options. For thermal ablative procedures such as cryoablation, additional immunological anti-tumor effects have been described.The purpose of this prospective study was to determine changes in peripheral blood circulating lymphocytes and various of their subsets in RCC patients treated with cryoablation or surgery in a longitudinal approach using extensive flow cytometry. Additionally, lymphocytes of RCC patients were compared to a healthy control group.We included 25 patients with RCC. Eight underwent cryoablation and 17 underwent surgery. Univariate and multivariable analysis revealed significantly lower values of B cells, CD4 and CD8 T cells, and various of their subsets in the treatment groups versus the healthy control group. Comparing the two different therapeutical approaches, a significant decline of various lymphocyte subsets with a consecutive normalization after three months was seen for the surgery group, whereas cryoablation led to increased values of CD69 + CD4 + and CD69 + CD8 + cell counts as well as memory CD8 + cells after three months.Treatment-naïve RCC patients showed lower peripheral blood lymphocyte counts compared to healthy controls. The post-treatment course revealed different developments of lymphocytes in the surgery versus cryoablation group, and only cryoablation seems to induce a sustained immunological response after three months.

Risk assessment for perfluorooctanoic acid (PFOA) in air, blood serum and water: mortality from liver and kidney disease.

BACKGROUND: Cancer and non-cancer associations have been observed with PFAS (perfluoroalkyl and polyfluoroalkyl) substances in the general population, in populations from locally contaminated environments and in exposed workers. METHODS: A quantitative risk assessment on the PFAS substance perfluorooctanoic acid (PFOA) was conducted for six outcomes using two occupational mortality studies that reported sufficient data to estimate exposure-relationships in relation to serum PFOA levels. Excess lifetime mortality risks were calculated using a life table procedure that applies an exposure response to time-dependent PFOA serum levels for a surviving hypothetical population from ages 20 to 85. Both occupational and general population exposures were described as serum levels, and as air and drinking water concentrations. RESULTS: The estimated occupational inhalation concentrations conferring the benchmark one-per-thousand lifetime risk were 0.21 µg/m3 for chronic kidney disease, 1.0 µg/m3 for kidney cancer and (from the two studies) 0.67 and 1.97 µg/m3 for chronic liver disease. Specific excess lifetime risks estimated in the general population at current PFOA serum levels (~ 1 ng/mL) range 1.5-32 per 100 000 which corresponds to drinking water concentrations of less than 10 ppt. CONCLUSION: Over eight outcome risk estimates, the serum PFOA concentrations conferring 1/1000 occupational lifetime risk ranged 44 to 416 ng/mL corresponding to air concentrations ranging 0.21 to 1.99 µg/m3. The analyses provide a preliminary PFOA quantitative risk assessment for liver and kidney disease mortality which, together with reported assessments for several other end-points, would inform policy on PFAS.

Genetically predicted 91 circulating inflammatory proteins in relation to risk of urological malignancies: a Mendelian randomization study.

BACKGROUND: Urological malignancies, including kidney, bladder, and prostate cancer, are major health concerns worldwide. Inflammation has been implicated in the pathogenesis of these cancers, and circulating inflammatory proteins may play a role in their development. However, the causal relationship between specific plasma proteins and urological malignancies remains unclear. METHODS: We performed a two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS). Instrumental variables representing genetic variants associated with circulating inflammatory proteins were used to infer causality on the risk of kidney, bladder, and prostate cancer. Four MR methods were utilized to provide robust effect estimates. RESULTS: Our analysis identified several plasma proteins associated with a lower risk of kidney and bladder cancer, including Eukaryotic translation initiation factor 4E-binding protein 1, Caspase 8, Natural killer cell receptor 2B4, and Tumor necrosis factor ligand superfamily member 12. However, after adjusting for multiple testing, these associations did not remain statistically significant. For prostate cancer, CUB domain-containing protein 1 and Interleukin-10 receptor subunit beta were found to be protective, while Glial cell line-derived neurotrophic factor and SIR2-like protein 2 were identified as risk factors. After FDR adjustment, none of the inflammatory proteins were found to be significantly associated with a lower risk of prostate cancer. CONCLUSION: Our findings suggest that certain plasma proteins may be involved in the development of urological malignancies. Mendelian randomization provides a useful framework for investigating causal relationships between inflammatory proteins and urological cancers, offering potential insights into their underlying biology and therapeutic targets.

A highly sensitive SERS substrate of porous membrane-Ag NPs for kidney cancer detection.

BACKGROUND: The substrate employed in surface-enhanced Raman spectroscopy (SERS) constitutes an essential element in the cancer detection methodology. In this research, we introduce a three-dimensional (3D) structured SERS substrate that integrates a porous membrane with silver nanoparticles to enhance SERS spectral signals through the utilization of the aggregation effect of silver nanoparticles. This enhancement is crucial because accurate detection results strongly depend on the intensity of specific peaks in Raman spectroscopy. A highly sensitive SERS substrate can significantly improve the accuracy of detection results. RESULTS: We collected 66 plasma samples from individuals with kidney cancer and control individuals, including both bladder cancer patients and healthy individuals. Then, we utilized substrates with and without porous membranes to acquire the SERS spectra of the samples, enabling us to evaluate the enhancement effect of our SERS substrate. The spectral analysis demonstrated enhanced peak intensities in the experimental group (with porous substrate) compared to the control group (without porous substrate). The uniformity and reproducibility of the SERS substrate are also significantly enhanced, which is very helpful for improving the accuracy of detection results. Additionally, the Principal Component Analysis-Linear Discriminant Analysis algorithm (PCA-LDA) was employed to classify the SERS spectra of both groups. In the experimental group, the classification accuracy was 98.5 % for kidney cancer, and 83.3 % for kidney and bladder cancer. Compared to the control group, it improved by 3 % and 12.6 % respectively. SIGNIFICANT: This indicates that our 3D structured SERS substrate combined with multivariate statistical algorithms PCA-LDA can not only improve the accuracy of SERS detection technology in single cancer detection, but also has great potential in multiple cancer detection. This 3D structured SERS substrate is expected to become a new auxiliary means for cancer detection.

Plasma Kidney Injury Molecule-1 for Preoperative Prediction of Renal Cell Carcinoma Versus Benign Renal Masses, and Association With Clinical Outcomes.

PURPOSE: Both clear cell and papillary renal cell carcinomas (RCCs) overexpress kidney injury molecule-1 (KIM-1). We investigated whether plasma KIM-1 (pKIM-1) may be a useful risk stratification tool among patients with suspicious renal masses. METHODS: Prenephrectomy pKIM-1 was measured in two independent cohorts of patients with renal masses. Cohort 1, from the prospective K2 trial, included 162 patients found to have clear cell RCC (cases) and 162 patients with benign renal masses (controls). Cohort 2 included 247 patients with small (cT1a) renal masses from an academic biorepository, of whom 184 had RCC. We assessed the relationship between pKIM-1, surgical pathology, and clinical outcomes. RESULTS: In Cohort 1, pKIM-1 distinguished RCC versus benign masses with area under the receiver operating curve (AUC-ROC, 0.81 [95% CI, 0.76 to 0.86]). In Cohort 2 (cT1a only), pKIM-1 distinguished RCC versus benign masses (AUC-ROC, 0.74 [95% CI, 0.67 to 0.80]) and the addition of pKIM-1 to an established nomogram for predicting malignancy improved the model AUC-ROC (0.65 [95% CI, 0.57 to 0.74] v 0.78 [95% CI, 0.72 to 0.85]). A pKIM-1 cutpoint identified using Cohort 2 demonstrated sensitivity of 92.5% and specificity of 60% for identifying RCC in Cohort 1. In long-term follow-up of RCC cases (Cohort 1), higher prenephrectomy pKIM-1 was associated with worse metastasis-free survival (multivariable MFS hazard ratio [HR] 1.29 per unit increase in log pKIM-1, 95% CI, 1.10 to 1.53) and overall survival (multivariable OS HR 1.31 per unit increase in log pKIM-1, 95% CI, 1.10 to 1.54). In long-term follow-up of Cohort 2, no metastatic events occurred, consistent with the favorable prognosis of resected cT1a RCC. CONCLUSION: Among patients with renal masses, pKIM-1 is associated with malignant pathology, worse MFS, and risk of death. pKIM-1 may be useful for selecting patients with renal masses for intervention versus surveillance.

Serum IgA as a Prognostic Beacon: Anticipating Systemic Therapy Efficacy in Metastatic Clear Cell Renal Cell Carcinoma.

OBJECTIVE: Immunotherapy-tyrosine kinase inhibitor (IO-TKI) therapy has revolutionized the treatment landscape for metastatic clear cell renal cell carcinoma (mccRCC); however, the absence of effective biomarkers poses a challenge in predicting the efficacy of these regimens. This study aims to explore the predictive and prognostic value of serum immunoglobulin A (IgA) in mccRCC patients undergoing IO-TKI therapy. METHODS: Ninety-six mccRCC patients treated with IO-TKI therapy from 2019 to 2023 were enrolled and serum IgA levels were assessed at the pretreatment baseline and after 3 months of treatment. RESULTS: Notably, baseline levels of IgA showed no correlation with the objective response rate. However, patients achieving complete or partial responses exhibited a remarkable decrease in IgA levels, while those with stable or progressive disease displayed an increase in IgA levels after 3 months of treatment. Furthermore, the dynamic alteration in IgA levels after 3 months of treatment demonstrated predictive value for both progression-free survival (PFS) and overall survival (OS). The time-dependent receiver operating characteristic curves exhibited outstanding performance in predicting PFS (AUC 0.793) and OS (AUC 0.738). CONCLUSION: Taken together, this study demonstrates that dynamic alteration of serum IgA after 3 months of treatment was significantly correlated with prognosis and therapeutic efficacy in mccRCC patients.

Association of Elevated C-Reactive Protein with Worsened Outcomes in Different Histologies of Renal Cortical Tumors: Analysis of the INMARC Registry.

BACKGROUND: To evaluate relationship between histological subtypes of renal cell carcinoma (RCC) and preoperative c-reactive protein (CRP). PATIENTS AND METHODS: We queried the International Marker Consortium for Renal Cancer database for patients affected by RCC. Patients were classified according to their histology: benign tumors, clear cell (cc) RCC, chromophobe (ch) RCC, papillary (p) RCC, and variant histology (vh) RCC; and according to CRP (mg/L): low CRP ≤5 and high CRP >5. Primary outcome was all-cause mortality (ACM). Secondary outcomes were cancer-specific mortality (CSM), recurrence and association between CRP and histology. Multivariable analysis (MVA) via Cox regression and multivariable logistic regression were fitted to elucidate predictors of outcomes. RESULTS: Total 3902 patients (high CRP n = 1266) were analyzed; median follow up 51 (IQR 20-91) months. On MVA elevated CRP was an independent risk factor associated with increased risk of ACM in benign tumors (HR 5.98, P < .001), ccRCC (HR 2.69, P < .001), chRCC (HR 3.99, P < .001), pRCC (HR 1.76, P = .009) and vhRCC (HR 2.97, P =.007). MVA for CSM showed CRP as risk factor in ccRCC (HR 2.77, P < .001), chRCC (HR 6.16, P = .003) and pRCC (HR 2.29, P = .011), while in vhRCC was not (P = .27). MVA for recurrence reported CRP as risk factor for ccRCC (HR 1.30, P = .013), while in chRCC (P = .33), pRCC (P = .34) and vhRCC (P = .52) was not. On multivariable logistic regression CRP was a predictor of pRCC (OR 1.003, P = .002), while decreasing CRP was associated with benign tumors (OR 0.994, P = .048). CONCLUSION: Elevated CRP was a robust predictor of worsened ACM in all renal cortical neoplasms. While most frequently observed in pRCC patients, elevated CRP was independently associated with worsened CSM in non-vhRCC. Conversely, elevated CRP was least likely to be noted in benign tumors, and elevation in this subgroup of patients should prompt further consideration for surveillance given increased risk of ACM. Further investigation is requisite.

miRNA-27b-3p, let-7f-5p and miRNA-142-5p can be Used in a Novel Serum Diagnostic Panel for Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a prevalent malignant tumor affecting the urinary system. Due to its unfavorable prognosis, there is a pressing need to discover effective approaches for early diagnosis and treatment of ccRCC. Extensive research has consistently demonstrated the presence of stable microRNAs (miRNAs) in human serum. Accordingly, the objective of this study was to identify a specific panel of miRNAs in serum that can serve as a reliable and non-invasive biomarker for the early detection of ccRCC. METHODS: The study comprised of training and validation phases to identify potential biomarkers. In the training phase, a total of 10 miRNAs exhibiting the most significant differential expression among 28 ccRCC patients and 28 healthy controls (HCs) were identified using quantitative reverse transcription polymerase chain reaction (qRT-PCR). In the subsequent validation phase, these 10 miRNAs were assessed in serum samples obtained from an additional 80 ccRCC patients and 84 HCs using RT-qPCR. To construct a panel with optimal diagnostic capability, backward stepwise logistic regression analysis was conducted. Furthermore, bioinformatics analysis was performed on this selected miRNA panel. RESULTS: In ccRCC patients, the serum expression level of miRNA-142-5p was found to be significantly elevated compared to healthy controls (HCs), whereas the expression levels of let-7f-5p, miRNA-27b-3p, miRNA-212-3p, and miRNA-216-5p were significantly reduced. To assess their diagnostic potential for ccRCC, receiver operating characteristic (ROC) curve analysis was performed. The analysis revealed that miRNA-27b-3p, let-7f-5p, and miRNA-142-5p exhibited moderate diagnostic capabilities for ccRCC, with area under the curve (AUC) values of 0.826, 0.828, and 0.643, respectively. To further enhance diagnostic accuracy, a final diagnostic panel consisting of these three miRNAs was constructed, demonstrating good diagnostic value with an AUC of 0.952. CONCLUSIONS: The miRNA serum biomarker panel (miRNA-27b-3p, let-7f-5p, and miRNA-142-5p) identified in this study holds promise for early, non-invasive, and accurate diagnosis of ccRCC. This panel could potentially provide a valuable tool in clinical settings to aid in the timely detection and management of ccRCC.

The lymphocyte-to-monocyte ratio as a significant inflammatory marker associated with survival of patients with metastatic renal cell carcinoma treated using nivolumab plus ipilimumab therapy.

BACKGROUND: Nivolumab plus ipilimumab (NIVO + IPI) is the first-line treatment for patients with metastatic renal cell carcinoma (mRCC). While approximately 40% of patients treated with NIVO + IPI achieve a durable response, 20% develop primary resistance with severe consequences. Therefore, there is a clinical need for criteria to select patients suitable for NIVO + IPI therapy to optimize its therapeutic efficacy. Accordingly, our aim was to evaluate the association between candidate biomarkers measured before treatment initiation and survival. METHODS: This was a multi-institutional, retrospective, cohort study of 183 patients with mRCC treated with systematic therapies between August 2015 and July 2023. Of these, 112 received NIVO + IPI as first-line therapy: mean age, 68 years; men, 83.0% (n = 93), and clear cell histology, 80.4% (n = 90). Univariable and multivariable analyses were used to evaluate associations between biomarkers and survival. RESULTS: On univariate analysis, high C-reactive protein and systemic index, a high neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio, and a low lymphocyte-to-monocyte ratio (LMR) were associated with shorter overall survival (OS). On multivariable analysis, a LMR ≤ 3 was retained as an independent factor associated to shorter OS with the highest accuracy (C-index, 0.656; hazard ratio, 7.042; 95% confidence interval, 2.0-25.0; p = 0.002). CONCLUSION: A low LMR may identify patients who would be candidate for NIVO + IPI therapy for mRCC.

Optical biomarker analysis for renal cell carcinoma obtained from preoperative and postoperative patients using ATR-FTIR spectroscopy.

Renal cell carcinoma (RCC) is the most common malignant tumor in the urinary system, accounting for 80 % to 90 % for all renal malignancies. Traditional diagnostic methods like magnetic resonance imaging (MRI) and computed tomography (CT) lack the sensitivity and specificity as they lack specific biomarkers. These limitations impede effective monitoring of tumor recurrence. This study aims to employ Attenuated Total Reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy, an optical technology sensitive to molecular groups, to analyze the potential optical biomarkers in urine and plasma samples from RCC patients pre- and post-surgery. The results reveal distinctive spectral information from both plasma and urine samples. Post-surgery urine spectra exhibit complexity compared to plasma, showing reduced content at 1072 cm-1, 1347 cm-1 and 1654 cm-1 bands, while increased content at 1112 cm-1, 1143 cm-1, 1447 cm-1, 3334 cm-1 and 3420 cm-1 bands. Utilizing machine learning models such as eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), partial least squares (PLS), and artificial neural network (ANN), the study evaluated plasma and urine samples pre- and post-surgery. Remarkably, the XGBoost method excelled in distinguishing between tumor conditions and recovery, achieving an impressive AUC value of 0.99. These results underscore the potential of ATR-FTIR technology in identifying RCC optical biomarkers, with XGBoost showing promise as a valuable screening tool for RCC recurrence diagnosis.

Automated Machine Learning and Explainable AI (AutoML-XAI) for Metabolomics: Improving Cancer Diagnostics.

Metabolomics generates complex data necessitating advanced computational methods for generating biological insight. While machine learning (ML) is promising, the challenges of selecting the best algorithms and tuning hyperparameters, particularly for nonexperts, remain. Automated machine learning (AutoML) can streamline this process; however, the issue of interpretability could persist. This research introduces a unified pipeline that combines AutoML with explainable AI (XAI) techniques to optimize metabolomics analysis. We tested our approach on two data sets: renal cell carcinoma (RCC) urine metabolomics and ovarian cancer (OC) serum metabolomics. AutoML, using Auto-sklearn, surpassed standalone ML algorithms like SVM and k-Nearest Neighbors in differentiating between RCC and healthy controls, as well as OC patients and those with other gynecological cancers. The effectiveness of Auto-sklearn is highlighted by its AUC scores of 0.97 for RCC and 0.85 for OC, obtained from the unseen test sets. Importantly, on most of the metrics considered, Auto-sklearn demonstrated a better classification performance, leveraging a mix of algorithms and ensemble techniques. Shapley Additive Explanations (SHAP) provided a global ranking of feature importance, identifying dibutylamine and ganglioside GM(d34:1) as the top discriminative metabolites for RCC and OC, respectively. Waterfall plots offered local explanations by illustrating the influence of each metabolite on individual predictions. Dependence plots spotlighted metabolite interactions, such as the connection between hippuric acid and one of its derivatives in RCC, and between GM3(d34:1) and GM3(18:1_16:0) in OC, hinting at potential mechanistic relationships. Through decision plots, a detailed error analysis was conducted, contrasting feature importance for correctly versus incorrectly classified samples. In essence, our pipeline emphasizes the importance of harmonizing AutoML and XAI, facilitating both simplified ML application and improved interpretability in metabolomics data science.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability.

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer-driven tissue factors in shaping nutrient availability in these tumors.

Cancer cells convert nutrients into energy differently compared to healthy cells. This difference in metabolism allows them to grow and divide more quickly and sometimes to migrate to different areas of the body. The environment around cancer cells ­ known as the tumor microenvironment ­ contains a variety of different cells and blood vessels, which are bathed in interstitial fluid. This microenvironment provides nutrients for the cancer cells to metabolize, and therefore influences how well a tumor grows and how it might respond to treatment. Recent advances with techniques such as mass spectrometry, which can measure the chemical composition of a substance, have allowed scientists to measure nutrient levels in the tumor microenvironments of mice. However, it has been more difficult to conduct such studies in humans, as well as to compare the tumor microenvironment to the healthy tissue the tumors arose from. Abbott, Ali, Reinfeld et al. aimed to fill this gap in knowledge by using mass spectrometry to measure the nutrient levels in the tumor microenvironment of 55 patients undergoing surgery to remove kidney tumors. Comparing the type and levels of nutrients in the tumor interstitial fluid, the neighboring healthy kidney and the blood showed that nutrients in the tumor and healthy kidney were more similar to each other than those in the blood. For example, both the tumor and healthy kidney interstitial fluids contained less glucose than the blood. However, the difference between nutrient composition in the tumor and healthy kidney interstitial fluids was insignificant, suggesting that the healthy kidney and its tumor share a similar environment. Taken together, the findings indicate that kidney cancer cells must adapt to the nutrients available in the kidney, rather than changing what nutrients are available in the tissue. Future studies will be required to investigate whether this finding also applies to other types of cancer. A better understanding of how cancer cells adapt to their environments may aid the development of drugs that aim to disrupt the metabolism of tumors.

Characterization of extrachromosomal circular DNAs in plasma of patients with clear cell renal cell carcinoma.

BACKGROUND AND PURPOSE: Extrachromosomal circular DNAs (eccDNAs) have been recognized for their significant involvement in numerous biological processes. Nonetheless, the existence and molecular characteristics of eccDNA in the peripheral blood of patients diagnosed with clear cell renal cell carcinoma (ccRCC) have not yet been reported. Our aim was to identify potentially marked plasma eccDNAs in ccRCC patients. METHODS AND MATERIALS: The detection of plasma eccDNA in ccRCC patients and healthy controls was performed using the Tn5-tagmentation and next-generation sequencing (NGS) method. Comparisons were made between ccRCC patients and healthy controls regarding the distribution of length, gene annotation, pattern of junctional nucleotide motif, and expression pattern of plasma eccDNA. RESULTS: We found 8,568 and 8,150 plasma eccDNAs in ccRCC patients and healthy controls, respectively. There were no statistical differences in the length distribution, gene annotation, and motif signature of plasma eccDNAs between the two groups. A total of 701 differentially expressed plasma eccDNAs were identified, and 25 plasma eccDNAs with potential diagnostic value for ccRCC have been successfully screened. These up-regulated plasma eccDNAs also be indicated to originate from the genomic region of the tumor-associated genes. CONCLUSION: This work demonstrates the characterization of plasma eccDNAs in ccRCC and suggests that the up-regulated plasma eccDNAs could be considered as a promising non-invasive biomarker in ccRCC.

High serum sodium predicts immunotherapy response in metastatic renal cell and urothelial carcinoma.

OBJECTIVES: The development of reliable biomarkers for the prediction of immune checkpoint inhibition (ICI) response in patients with metastatic renal cell carcinoma (mRCC) and urothelial carcinoma (mUC) remains an unresolved challenge. Conventional ICI biomarkers typically focus on tumor-related factors such as PD-L1 expression. However, a comprehensive evaluation of the predictive value of serum electrolyte levels, a so far widely unexplored area, is still pending. METHODS: We conducted a post-hoc analysis of baseline sodium, potassium, chloride, magnesium and calcium levels in two independent phase 3 clinical trials: IMvigor211 for mUC comparing atezolizumab to chemotherapy, and IMmotion151 for mRCC comparing atezolizumab+bevacizumab to sunitinib. This analysis aimed to evaluate the prognostic and predictive value of these electrolyte levels in these clinical settings. A total of 1787 patients (IMvigor211 n = 901; IMmotion151 n = 886) were analyzed. RESULTS: We found a linear correlation of baseline serum sodium and chloride with prognosis across both trials, which was not found for potassium, magnesium and calcium. In multivariate analysis, the prognostic capacity of sodium was limited to patients receiving ICI as compared to the control group. Interestingly, in both studies, the chance of achieving an objective response was highest in the patient subgroup with high baseline serum sodium levels of > 140 mmol/L (IMmotion151: Complete response in 17.9% versus 2.0% in patients with mRCC with baseline sodium < 135 mmol/L). Serum sodium outperformed tumor PD-L1 expression as a predictor for immunotherapy efficacy. CONCLUSIONS: Patients exhibiting elevated serum sodium levels derive the greatest benefit from immunotherapy, suggesting that baseline serum concentration could serve as a valuable and cost-effective predictive biomarker for immunotherapy across entities.

The prognostic impact of peripheral blood eosinophil counts in metastatic renal cell carcinoma patients treated with nivolumab.

Although immune checkpoint inhibitors (ICIs) have gained approval for metastatic renal cell carcinoma (mRCC), the response rate is still limited. Therefore, it is urgent to explore novel markers of responses to ICIs that can help assess clinical benefits. Recently, it has been noted that peripheral blood eosinophil counts are an independent factor correlated with clinical outcome of ICIs in some types of cancer. We investigated peripheral blood absolute eosinophil counts (AECs) at baseline and 4 weeks after the initiation of nivolumab for mRCC patients between February 2016 and May 2022. In addition, we examined clinicopathological features including irAEs and analyzed the correlation between AECs and clinical efficacy of nivolumab. The median progression-free survival (PFS) and overall survival (OS) for all patients were 5.7 and 25.5 months, respectively. The median AECs in patients with irAEs were significantly higher at baseline and 4 weeks after the treatment compared to those without irAEs (p < 0.001 and p = 0.001). With the cutoff value of AECs of 329 cells/µL at 4 weeks after the treatment for prediction of irAEs, high-AECs groups had significantly higher number of responders compared with that in low-AECs group (p < 0.001). Accordingly, the PFS and OS were significantly better in patients with high-AECs group than those in low-AECs group (p = 0.03 and p = 0.009). High-AECs at 4 weeks after the treatment serve as the prominent surrogate marker associated with the incidence of irAEs and better clinical outcome in mRCC patients receiving nivolumab.

NLR Outperforms Low Hemoglobin and High Platelet Count as Predictive and Prognostic Biomarker in Metastatic Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors.

BACKGROUND: Reliable biomarkers in renal cell carcinoma (RCC) remain elusive. While several markers have been shown to be associated with prognosis, and may aid in risk assessment, predictive biomarkers of response to immune checkpoint inhibitors (ICIs) have not been established. Previous studies have shown that a high pretreatment neutrophil-lymphocyte ratio (NLR) is a negative prognostic factor in RCC. However, a clinically useful cut-off for the predictive and prognostic value of NLR has not been well defined. METHODS: We conducted a retrospective analysis of 132 patients with previously untreated metastatic clear cell RCC (ccRCC) who received first line ICI-based therapy. ICI-based therapy included anti-PD-1/PD-L1 alone or in combination with anti-CTLA-4 or VEGF-TKI. Platelet, haemoglobin, neutrophil and lymphocyte counts were collected prior to treatment and at 12-weeks after treatment initiation. Radiologic response at 12-weeks and overall survival (OS) data was also collected. RESULTS: Low haemoglobin, high platelet count, and NLR ≥3 were statistically significant negative predictive biomarkers when assessed at 12-weeks, but not at baseline. Median OS was shorter in patients with low haemoglobin (20.3 months vs. 51.6 months, P = .009), high platelet count (14.3 months vs. 43.8 months, P = .003), and NLR ≥ 3 (17.5 months vs. 40.3 months, P < .001) at 12-weeks. In an IMDC-risk adjusted analysis, only NLR ≥3 at 12-weeks remained statistically significant (OR of 2.11, P = .003) A dynamic change towards lower absolute NLR overtime was associated with longer OS. In patients who had baseline NLR ≥ 3, those who achieved NLR < 3 at 12-weeks demonstrated significant longer median OS compared to those whose NLR remained persistently ≥ 3 (40.3 months vs. 14.7 months, P = .004). CONCLUSION: NLR ≥3, low haemoglobin and elevated platelet count after 12-weeks of ICI-based first line therapy were negatively prognostic and predictive in patients with metastatic RCC. Normalization of NLR in patients with baseline elevation was associated with longer median OS and response to therapy. These results suggest that monitoring of routine haematologic biomarkers during therapy may provide important predictive and prognostic information, beyond what is available with baseline risk assessment scoring systems.

Increased level of serum leucine-rich-alpha-2-glycoprotein 1 in patients with clear cell renal cell carcinoma.

BACKGROUND: Currently, no useful serum markers exist for clear cell renal cell carcinoma (ccRCC), making early detection challenging as diagnosis relies solely on imaging tests. Radiation exposure is also a concern due to multiple required CT examinations during treatment. Renal cell carcinoma (RCC) histological types include ccRCC and non-clear cell RCC (non-ccRCC); however, treatment response to medications varies which necessitates accurate differentiation between the two. Therefore, we aimed to identify a novel serum marker of RCC. Increased LRG1 expression in the serum has been demonstrated in multiple cancer types. However, the expression of LRG1 expression in the serum and cancer tissues of patients with RCC has not been reported. Since ccRCC is a hypervascular tumor and LRG1 is capable of accelerating angiogenesis, we hypothesized that the LRG1 levels may be related to ccRCC. Therefore, we examined LRG1 expression in sera from patients with RCC. METHODS: Using an enzyme-linked immunosorbent assay, serum levels of leucine-rich-alpha-2-glycoprotein 1 (LRG1) were measured in 64 patients with ccRCC and 22 patients non-ccRCC who underwent radical or partial nephrectomy, as well as in 63 patients without cancer. RESULTS: Median values of serum LRG1 and their inter-quartile ranges were 63.2 (42.8-94.2) µg/mL in ccRCC, 23.4 (17.7-29.6) µg/mL in non-ccRCC, and 36.0 (23.7-56.7) µg/mL in patients without cancer, respectively (ccRCC vs. non-ccRCC or patients without cancer: P < 0.001). C-reactive protein (CRP) levels (P = 0.002), anemia (P = 0.037), hypercalcemia (P = 0.023), and grade (P = 0.031) were independent predictors of serum LRG1 levels in ccRCC. To assess diagnostic performance, the area under the receiver operating characteristic curve of serum LRG1 was utilized to differentiate ccRCC from non-cancer and non-ccRCC, with values of 0.73 (95% CI, 0.64-0.82) and 0.91 (95% CI, 0.82-0.96), respectively. CONCLUSIONS: LRG1 served as a serum marker associated with inflammation, indicated by CRP, anemia, hypercalcemia, and malignant potential in ccRCC. Clinically, serum LRG1 levels may assist in differentiating ccRCC from non-ccRCC with excellent diagnostic accuracy.

Bioinformatic Analysis and Clinical Case Studies Identify CD276 as a Promising Diagnostic Biomarker for Clear Cell Renal Cell Carcinoma.

OBJECTIVE: This study aimed to explore the relationship between CD276 and clear cell renal carcinoma (ccRCC) and assess the diagnostic value of CD276 in ccRCC. METHODS: Expression levels of CD276 in ccRCC and para-cancer tissues were compared and analyzed retrospectively using data obtained from TCGA and GEO databases. The clinical data was analyzed prospectively. Immunohistochemistry and RT-PCR analyses were used to analyze the expression of CD276 at the mRNA and protein levels. These analyses compared the expression between ccRCC tissues and para-cancer tissues obtained from 70 patients with ccRCC. Next, ELISA was used to analyze peripheral blood samples from 70 patients with ccRCC and 72 healthy individuals, facilitating the differentiation of ccRCC patients from normal controls. Finally, we utilized the Kaplan-Meier method to generate ROC curves for assessing the diagnostic value of CD276 for ccRCC. RESULTS: Analysis of TCGA and GEO data revealed that the mRNA expression of CD276 was higher in ccRCC tissues than in para-cancer tissues (P < .05). Clinical validation using IHC and RT-PCR confirmed that the expression of CD276 was higher in ccRCC tissues than in para-cancer tissues, both at the mRNA and protein levels (P < .05). ELISA demonstrated that the expression of CD276 was higher in ccRCC patients than in normal individuals, and patients with a higher pathological grade showed higher expression of CD276 in the peripheral blood than those with a lower pathological grade (P < .05). ROC curves drawn from the above three datasets demonstrated that CD276 had a high diagnostic value for ccRCC (AUC = .894, .795, .938, respectively). CONCLUSION: The expression of CD276 was higher in ccRCC tissues and positively associated with the pathological grade. Therefore, CD276 may serve as a molecular biomarker for ccRCC prediction.

ctDNA predicts clinical T1a to pathological T3a upstaging after partial nephrectomy.

Most patients diagnosed with clear cell renal cell carcinoma (ccRCC) are also detected with small and organ-confined tumors, and the majority of these are classified as clinical tumor stage 1a (cT1a). A considerable proportion of patients with cT1 RCC shows tumor upstaging to pathological stage 3a (pT3a), and these patients have worse oncological outcomes. The role of circulating tumor DNA (ctDNA) in RCC has been limited to monitoring treatment response and resistance. Therefore, the present study aimed to evaluate the potential of ctDNA in predicting pT3a upstaging in cT1a ccRCC. We sequenced plasma samples preoperatively collected from 48 patients who had undergone partial nephrectomy for cT1a ccRCC using data from a prospective cohort RCC. The ctDNA were profiled and compared with clinicopathological ccRCC features to predict pT3a upstaging. Associations between ctDNA, tumor complexity, and pT3a upstaging were evaluated. Tumor complexity was assessed using the anatomical classification system. Univariate analysis used chi-squared and Student's t-tests; multivariate analysis considered significant factors from univariate analyses. Of the 48 patients with cT1a ccRCC, 12 (25%) were upstaged to pT3a, with ctDNA detected in 10 (20.8%), predominantly in patients with renal sinus fat invasion (SFI; n = 8). Among the pT3a group, ctDNA was detected in 75%, contrasting with only 2.8% in patients with pT1a (1/36). Detection of ctDNA was the only significant preoperative predictor of pT3a upstaging, especially in SFI. This study is the first to suggest ctDNA as a preoperative predictor of pT3a RCC upstaging from cT1a based on preoperative radiological images.

Diagnostic and prognostic value of circulating tumor cells in renal cell cancer: A systematic review and meta-analysis.

Renal cell carcinoma (RCC) is a type of tumor with high morbidity and recurrence rates. The application of circulating tumor cells (CTCs) in RCC remains controversial. Hence, we performed a meta-analysis to elucidate the diagnostic and prognostic value of CTCs in RCC. To obtain a precise conclusion, a systematic search was conducted in Pubmed, Cochrane Database, Embase and Web of Science up to Dec 01, 2022. We also further identified the references in relevant studies. The diagnostic accuracy variables (sensitivity, specificity) and odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were used to access precise of CTCs and relationship between CTCs and disease stages, respectively. Heterogeneity test, sensitivity analysis, meta-regression and publishing bias were also applied. A total of 12 studies involving 767 patients were considered to be included in the final meta-analysis. The results revealed that the overall sensitivity, specificity of CTC detection in RCC were 45% (95%CI, 32-60%) and 99% (95%CI, 97-100%), respectively. In subgroup analysis, diagnostic sensitivity of CTCs in clear cell renal cell carcinoma (ccRCC) (69%, 95%CI; 50-88%) was significantly higher than other RCC subtypes (34%, 95%CI; 21-48%) (p<0.05). Meanwhile, advanced diseases (stage III-IV) were more likely to find CTCs than localized diseases (stage I-II) (OR, 2.29; 95%CI, 1.37-3.83; p = 0.002). This systematic review and meta-analysis demonstrated that CTC detection could be considered as a promising auxiliary diagnostic and staging method for RCC, especially ccRCC subtype. Meanwhile, the presence of cytokeratin-positive CTCs is highly likely associated with increased risk of poor prognosis in RCC.