An epidemiological and clinicopathological study of type 1 vs. type 2 morphological subtypes of papillary renal cell carcinoma- results from a nation-wide study covering 50 years in Iceland.

INTRODUCTION: Papillary renal cell carcinoma (pRCC) is the second most common histology of renal cell carcinoma (RCC), accounting for 10-15% of cases. Traditionally, pRCC is divided into type 1 and type 2, although this division is currently debated as a prognostic factor of survival. Our aim was to investigate the epidemiology and survival of the pRCC subtypes in a whole nation cohort of patients during a 50-year period. MATERIALS AND METHODS: A Population based retrospective study including consecutive cases of RCC in Iceland from 1971-2020. Comparisons were made between histological classifications of RCC, with emphasis on pRCC subtypes (type 1 vs. 2) for outcome estimation. Changes in RCC incidence were analyzed in 5-year intervals after age standardization. The Kaplan-Meier method and Cox regression were used for outcome analysis. RESULTS: A total of 1.725 cases were identified, with 74.4%, 2.1% and 9.2% having clear cell (ccRCC), chromophobe (chRCC), and pRCC, respectively. The age standardized incidence (ASI) of pRCC was 1.97/100.000 for males and 0.5/100.000 for females, and the proportion of pRCC increased from 3.7% to 11.5% between the first and last intervals of the study (p < 0.001). Age standardized cancer specific mortality (ASCSM) of pRCC was 0.6/100.000 and 0.19/100.000 for males and females, respectively. The annual average increase in ASI was 3.6% for type 1 pRCC, but the ASI for type 2 pRCC and ASCSM for both subtypes did not change significantly. Male to female ratio was 4.4 for type 1 pRCC and 2.3 for type 2. The average tumor size for type 1 and 2 was 58.8 and 73.7 mm, respectively. Metastasis at diagnosis was found in 8.7% in the type 1 pRCC, compared to 30.0% of patients with type 2 pRCC (p < 0.001). Estimated 5-year cancer-specific survival (CSS) were 94.4%, 80.7%, and 69.3% for chRCC, pRCC and ccRCC, respectively (p < 0.001). For the pRCC subtypes, type 1 was associated with better 5-year CSS than type 2 (86.3% vs. 66.0%, p < 0.001), although this difference was not significant after adjusting for cancer stage and grading. CONCLUSIONS: pRCC histology was slightly less common in Iceland than in other countries. Males are more than three times more likely to be diagnosed with pRCC, compared to other RCC histologies. The subtype of pRCC was not found to be an independent risk factor for worse survival, and as suggested by the most recent WHO Classification of Urinary Tumors, grade and TNM-stage seem to be the most important factors for estimation of survival for pRCC patients.

Comprehensive characterization of alternative splicing in renal cell carcinoma.

Irregular splicing was associated with tumor formation and progression in renal cell carcinoma (RCC) and many other cancers. By using splicing data in the TCGA SpliceSeq database, RCC subtype classification was performed and splicing features and their correlations with clinical course, genetic variants, splicing factors, pathways activation and immune heterogeneity were systemically analyzed. In this research, alternative splicing was found useful for classifying RCC subtypes. Splicing inefficiency with upregulated intron retention and cassette exon was associated with advanced conditions and unfavorable overall survival of patients with RCC. Splicing characteristics like splice site strength, guanine and cytosine content and exon length may be important factors disrupting splicing balance in RCC. Other than cis-acting and trans-acting regulation, alternative splicing also differed in races and tissue types and is also affected by mutation conditions, pathway settings and the response to environmental changes. Severe irregular splicing in tumor not only indicated terrible intra-cellular homeostasis, but also changed the activity of cancer-associated pathways by different splicing effects including isoforms switching and expression regulation. Moreover, irregular splicing and splicing-associated antigens were involved in immune reprograming and formation of immunosuppressive tumor microenvironment. Overall, we have described several clinical and molecular features in RCC splicing subtypes, which may be important for patient management and targeting treatment.

Modified cancer TNM classification for localized renal cell carcinoma based on the prognostic analysis of 3748 cases from a single center.

The optimal cutoff point for evaluating the prognosis of localized renal cell carcinoma (LRCC) remains unclear. This study aimed to verify the efficacy of tumor diameter in the 2010 American Joint Committee on Cancer (AJCC) TNM staging system and contribute to the modification of TNM staging on the prognosis of this disease. A total of 3748 patients with LRCC were enrolled and grouped according to the 2010 AJCC TNM staging system. COX analysis was used to stratify the prognosis. The optimal cutoff point of the tumor diameter in the T1 and T2 prognosis was explored. There were 3330 (88.9%) patients in stage T1 and 418 (11.1%) in stage T2. The cancer-specific mortality rate was 2.7% (100/3748). The mean follow-up was 49.8 months. A tumor diameter of 7 cm can determine the prognosis of patients at stages T1 and T2; however, 4.5 cm and 11 cm as the cutoff points for T1 and T2 sub-classification of patients with LRCC might show better recognition ability than 4 cm and 10 cm, respectively. The 2010 AJCC TNM stage can predict the prognosis of LRCC in stages T1 and T2. In addition, a tumor diameter of 4.5 cm and 11 cm might be the optimal cutoff points for the sub-classification of stages T1 and T2.

Single-cell analysis reveals metastatic cell heterogeneity in clear cell renal cell carcinoma.

Renal cell carcinoma (RCC) is one of the leading causes of cancer-related death worldwide. Tumour metastasis and heterogeneity lead to poor survival outcomes and drug resistance in patients with metastatic RCC (mRCC). In this study, we aimed to assess intratumoural heterogeneity (ITH) in mRCC cells by performing a combined analysis of bulk data and single-cell RNA-sequencing data, and develop novel biomarkers for prognosis prediction on the basis of the potential molecular mechanisms underlying tumorigenesis. Eligible single-cell cohorts related to mRCC were acquired using the Gene Expression Omnibus (GEO) dataset to identify potential mRCC subpopulations. We then performed gene set variation analysis to understand the differential function in primary RCC and mRCC samples. Subsequently, we applied weighted correlation network analysis to identify coexpressing gene modules that were related to the external trait of metastasis. Protein-protein interactions were used to screen hub subpopulation-difference (sub-dif) markers (ACTG1, IL6, CASP3, ACTB and RAP1B) that might be involved in the regulation of RCC metastasis and progression. Cox regression analysis revealed that ACTG1 was a protective factor (HR < 1), whereas the other four genes (IL6, CASP3, ACTB and RAP1B) were risk factors (HR > 1). Kaplan-Meier survival analysis suggested the potential prognostic value of these sub-dif markers. The expression of sub-dif markers in mRCC was further evaluated in clinical samples by immunohistochemistry (IHC). Additionally, the genetic features of sub-dif marker expression patterns, such as genetic variation profiles, correlations with tumour-infiltrating lymphocytes (TILs), and targeted signalling pathway activities, were assessed in bulk RNA-seq datasets. In conclusion, we established novel subpopulation markers as key prognostic factors affecting EMT-related signalling pathway activation in mRCC, which could facilitate the implementation of a treatment for mRCC patients.

Differences in risk factors for molecular subtypes of clear cell renal cell carcinoma.

The ccA and ccB molecular subtypes of clear cell renal cell carcinoma (ccRCC) have well-characterized prognostic relevance. However, it is not known whether they possess distinct etiologies. We investigated the relationships between these subtypes and RCC risk factors within a case-control study conducted in Eastern Europe. We analyzed risk factor data for ccA (n = 144) and ccB (n = 106) cases and 1476 controls through case-only and case-control comparisons to assess risk factor differences across subtypes using logistic and polytomous regression models. We also performed a meta-analysis summarizing case-only results from our study and three patient cohorts. Patients with ccB tumors had poorer survival than those with ccA tumors and were more likely to be male (case-only odds ratio [OR] 2.68, 95% confidence interval [CI] 1.43-5.03). In case-control analyses, body mass index was significantly associated with ccA tumors (OR 2.45, 95% CI 1.18-5.10 for ≥35 vs <25 kg/m2 ) but not with ccB tumors (1.52, 0.56-4.12), while trichloroethylene was associated with ccB but not ccA (OR 3.09, 95% CI 1.11-8.65 and 1.25, 0.36-4.39 respectively for ≥1.58 ppm-years vs unexposed). A polygenic risk score of genetic variants identified from genome-wide association studies was associated with both ccA and, in particular, ccB (OR 1.82, 1.11-2.99 and 2.87, 95% CI 1.64-5.01 respectively for 90th vs 10th percentile). In a meta-analysis of case-only results including three patient cohorts, we still observed the ccB excess for male sex and the ccA excess for obesity. In conclusion, our findings suggest the existence of etiologic heterogeneity across ccRCC molecular subtypes for several risk factors.

Characteristics and outcome of pediatric renal cell carcinoma patients registered in the International Society of Pediatric Oncology (SIOP) 93-01, 2001 and UK-IMPORT database: A report of the SIOP-Renal Tumor Study Group.

In children, renal cell carcinoma (RCC) is rare. This study is the first report of pediatric patients with RCC registered by the International Society of Pediatric Oncology-Renal Tumor Study Group (SIOP-RTSG). Pediatric patients with histologically confirmed RCC, registered in SIOP 93-01, 2001 and UK-IMPORT databases, were included. Event-free survival (EFS) and overall survival (OS) were analyzed using the Kaplan-Meier method. Between 1993 and 2019, 122 pediatric patients with RCC were registered. Available detailed data (n = 111) revealed 56 localized, 30 regionally advanced, 25 metastatic and no bilateral cases. Histological classification according to World Health Organization 2004, including immunohistochemical and molecular testing for transcription factor E3 (TFE3) and/or EB (TFEB) translocation, was available for 65/122 patients. In this group, the most common histological subtypes were translocation type RCC (MiT-RCC) (36/64, 56.3%), papillary type (19/64, 29.7%) and clear cell type (4/64, 6.3%). One histological subtype was not reported. In the remaining 57 patients, translocation testing could not be performed, or TFE-cytogenetics and/or immunohistochemistry results were missing. In this group, the most common RCC histological subtypes were papillary type (21/47, 44.7%) and clear cell type (11/47, 23.4%). Ten histological subtypes were not reported. Estimated 5-year (5y) EFS and 5y OS of the total group was 70.5% (95% CI = 61.7%-80.6%) and 84.5% (95% CI = 77.5%-92.2%), respectively. Estimated 5y OS for localized, regionally advanced, and metastatic disease was 96.8%, 92.3%, and 45.6%, respectively. In conclusion, the registered pediatric patients with RCC showed a reasonable outcome. Survival was substantially lower for patients with metastatic disease. This descriptive study stresses the importance of full, prospective registration including TFE-testing.

Differential diagnostic ability of 18F-FDG PET/CT radiomics features between renal cell carcinoma and renal lymphoma.

BACKGROUND: The aim of this study is to determine the differential diagnostic value of texture parameters of PET/CT on renal cell carcinoma and renal lymphoma. METHODS: Twenty renal lymphoma and 18 renal cell carcinoma (RCC) patients were analyzed in this study. The pathological information and basic characteristics were extracted from the electronic medical record system of our hospital. We used LIFEx package to extract data from the radiomics images. Receiver operating characteristic analysis and binary logistic regression analysis was applied in determining the diagnostic accuracy of texture parameters as well as the synthetic parameter, of which the sensitivity and specificity was improved. RESULTS: There were 14 (two in Histogram, two in Grey Level Co-occurrence Matrix, five in Grey-Level Run Length Matrix, five in Grey-Level Zone Length Matrix) out of the texture parameters showing an area under the curve (AUC) >0.7 and P<0.05. Synthesized parameters of each section showed even higher differentiation ability, with AUC varying from 0.725 to 1.000. CONCLUSIONS: Texture analysis of 18F-FDG PET/CT could effectively differentiate between RCCs and renal lymphomas.

Malignant melanotic Xp11 neoplasms exhibit a clinicopathologic spectrum and gene expression profiling akin to alveolar soft part sarcoma: a proposal for reclassification.

The classification of the distinct group of mesenchymal neoplasms, first described as 'Xp11 translocation perivascular epithelioid cell tumor (PEComa)' and for which the term 'melanotic Xp11 neoplasm' or 'Xp11 neoplasm with melanocytic differentiation' has recently been proposed, remains challenging and controversial. We collected 27 melanotic Xp11 neoplasms, the largest series to date, for a comprehensive evaluation. Fourteen of the cases, together with eight alveolar soft part sarcomas (ASPS), nine conventional PEComas and a control group of seven normal tissues were submitted to RNA sequencing. Follow-up available in 22 patients showed 5-year overall survival and 5-year disease-free survival of 47.6 and 35.7%, respectively, which were similar to ASPS and significantly worse than conventional PEComa. Univariate analysis of location (occurring in the kidney versus not kidney), infiltrative growth pattern, nuclear pleomorphism, mitotic activity ≥2/50 high-power fields (HPF), necrosis and lymphovascular invasion were found to be associated with overall survival and/or disease-free survival. Multivariate analysis identified that location was the only factor found to independently correlate with disease-free survival. More importantly, RNA sequencing-based clustering analysis segregated melanotic Xp11 neoplasm and ASPS from other tumors, including conventional PEComa and Xp11 translocation renal cell carcinoma, and formed a compact cluster representative of the largely similar expression signature. Here we clearly define the true biologic nature of melanotic Xp11 neoplasms which are distinctive malignant mesenchymal tumors, rather than simply PEComa variants with occasionally unpredictable behavior. Meanwhile, melanotic Xp11 neoplasm and ASPS more likely represent phenotypic variants of the same entity, which is distinct from conventional PEComa and Xp11 translocation renal cell carcinoma. Based on these important findings, melanotic Xp11 neoplasm might be reclassified into a distinctive entity together with ASPS, independent from PEComa, in future revisions of the current WHO categories of tumors of soft tissue and bone for the improved reclassification. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Current Trends in Management of Renal Cell Carcinoma with Venous Thrombus Extension.

PURPOSE OF REVIEW: To review the evidence regarding the current trends in surgical management of renal cell carcinoma (RCC) with inferior vena cava (IVC) thrombosis. Recent published series have shown the role of minimally invasive surgery in IVC thrombectomy. This review article evaluates the present RCC with venous extent literature to assess the role of open and minimally invasive surgery in this scenario. RECENT FINDINGS: Robotic urological surgery has shown to have known benefits in radical prostatectomy, partial nephrectomy, and pyeloplasty. Recent published series showed feasibility of robotic IVC thrombectomy even for level IV cases. With growing number of robot-assisted and laparoscopic surgeries worldwide, there is a current tendency to treat this complex and challenging pathology with a minimally invasive approach, without compromising oncological outcomes.

Undifferentiated and dedifferentiated urological carcinomas: lessons learned from the recent developments.

Loss of the morphological and immunophenotypic characteristics of a neoplasm is a well-known phenomenon in surgical pathology and occurs across different tumor types in almost all organs. This process may be either partial, characterized by transition from well differentiated to undifferentiated tumor component (=dedifferentiated carcinomas) or complete (=undifferentiated carcinomas). Diagnosis of undifferentiated carcinoma is significantly influenced by the extent of sampling. Although the concept of undifferentiated and dedifferentiated carcinoma has been well established for other organs (e.g. endometrium), it still has not been fully defined for urological carcinomas. Accordingly, undifferentiated/ dedifferentiated genitourinary carcinomas are typically lumped into the spectrum of poorly differentiated, sarcomatoid, or unclassified (NOS) carcinomas. In the kidney, dedifferentiation occurs across all subtypes of renal cell carcinoma (RCC), but certain genetically defined RCC types (SDH-, FH- and PBRM1- deficient RCC) seem to have inherent tendency to dedifferentiate. Histologically, the undifferentiated component displays variable combination of four patterns: spindle cells, pleomorphic giant cells, rhabdoid cells, and undifferentiated monomorphic cells with/without prominent osteoclastic giant cells. Any of these may occasionally be associated with heterologous mesenchymal component/s. Their immunophenotype is often simple with expression of vimentin and variably pankeratin or EMA. Precise subtyping of undifferentiated (urothelial versus RCC and the exact underlying RCC subtype) is best done by thorough sampling supplemented as necessary by immunohistochemistry (e.g. FH, SDHB, ALK) and/ or molecular studies. This review discusses the morphological and molecular genetic spectrum and the recent develoments on the topic of dedifferentiated and undifferentiated genitourinary carcinomas.

Nephrometry Scores: Can Preoperative Assessment of Sectional Imaging Really Mirror Intraoperative Renal Tumor Anatomy?

INTRODUCTION: To compare RENAL, preoperative aspects and dimensions used for an anatomical (PADUA) classification, and Mayo Adhesive Probability (MAP) scores with the respective intraoperative findings and surgeon's assessment in predicting surgical outcome of patients undergoing partial nephrectomy. METHODS: Data of 150 eligible patients treated at the University Medical Center Mannheim between 2016 and 2018 were analyzed. Tumors were radiologically and intraoperatively assessed by PADUA, RENAL, and MAP scores and surgeon's assessment. Correlations and regression models were created to predict ischemia time (IT), major complications, and Trifecta (negative surgical margin, IT < 25 min, and absence of major complications). RESULTS: There were strong correlations between radiological and intraoperative RENAL (r = 0.68; p < 0.001) and PADUA scores (r = 0.72; p < 0.001). Radiological RENAL, PADUA, and MAP scores and surgeon's assessment were independent predictors of Trifecta (OR = 0.71, p = 0.015; OR = 0.77, p = 0.035; OR = 0.65, p = 0.012; OR = 0.40, p = 0.005, respectively). IT showed significant associations with radiological RENAL, PADUA, and surgeon's assessment (OR = 1.41, p = 0.033; OR = 1.34, p = 0.044; OR = 3.04, p = 0.003, respectively). MAP score proved as only independent predictor of major complications (OR = 2.12, p = 0.002). CONCLUSION: Radiologically and intraoperatively assessed scores correlated well with each other. Intraoperative nephrometry did not outperform radiological scores in predicting outcome confirming the value of the existing systems. MAP score correlates well with surgeon's assessment of perirenal fat and major complications underlining the importance of perirenal fat characteristics.

Renal cell carcinoma, part 2.

ABSTRACT: Renal cell carcinoma (RCC) accounts for most renal malignancies. This article, the second in a three-part series, addresses how renal masses are classified, signs and symptoms of RCC, medical treatments for RCC, and priority nursing interventions for patients with RCC.

Carbonic anhydrase IX (CA9) expression in multiple renal epithelial tumour subtypes.

AIMS: Renal epithelial neoplasms (RENs) can be difficult to subclassify, owing to overlapping morphological features. Carbonic anhydrase 9 (CA9) is a common biomarker for clear cell renal cell carcinoma (CCRCC); however, the sensitivity and specificity across REN subtypes are less clear. The aim of this study was to investigate CA9 expression in RENs, especially those in the differential diagnosis with CCRCC and less common entities, to determine its reliability as a diagnostic biomarker. METHODS AND RESULTS: CA9 immunostaining was performed on 262 RENs, including 119 CCRCCs and 143 non-CCRCC. Immunostaining was evaluated as negative (0%), rare (1+, 1-10%), focal (2+, 11-50%), or diffuse (3+, >50%). CCRCCs were 3+ CA9-positive in 93% of cases; 4% were CA9-negative. Sixty-seven percent of papillary renal cell carcinomas (RCCs) were 1+/2+ CA9-positive, whereas 33% were CA9-negative. Chromophobe RCCs were nearly always CA9-negative (93%), with 7% showing rare cell reactivity. Clear cell tubulopapillary RCCs (CCTPRCCs) were consistently 3+ CA9-positive, but with a cup-like staining pattern. Fifty-three percent of Xp11.2 RCCs were CA9-negative; however, 6% were 3+ CA9-positive and 12% were 2+ CA9-positive. Two of eight fumarate hydratase-deficient RCCs were 3+ CA9-positive. A small subset of the remaining RCCs showed rare to focal CA9 expression. All oncocytomas and eosinophilic solid and cystic RCCs were CA9-negative. CONCLUSIONS: Overall, diffuse CA9 expression was identified in nearly all CCRCCs and in all CCTPRCCs (high sensitivity); however, CA9 was not entirely specific. At least focal CA9 expression can been seen in a subset of many RCCs, and such findings should be taken into consideration with other morphological, immunophenotypic and clinical findings.

Accuracy of magnetic resonance imaging to identify pseudocapsule invasion in renal tumors.

PURPOSE: To evaluate accuracy of MRI in detecting renal tumor pseudocapsule (PC) invasion and to propose a classification based on imaging of PC status in patients with renal cell carcinoma. METHODS: From January 2017 to June 2018, 58 consecutive patients with localized renal cell carcinoma were prospectively enrolled. MRI was performed preoperatively and PC was classified, according to its features, as follows: MRI-Cap 0 (absence of PC), MRI-Cap 1 (presence of a clearly identifiable PC), MRI-Cap 2 (focally interrupted PC), and MRI-Cap 3 (clearly interrupted and infiltrated PC). A 3D image reconstruction showing MRI-Cap score was provided to both surgeon and pathologist to obtain complete preoperative evaluation and to compare imaging and pathology reports. All patients underwent laparoscopic partial nephrectomy. In surgical specimens, PC was classified according to the renal tumor capsule invasion scoring system (i-Cap). RESULTS: A concordance between MRI-Cap and i-Cap was found in 50/58 (86%) cases. ρ coefficient for each MRI-cap and iCap categories was: MRI-Cap 0: 0.89 (p < 0.0001), MRI-Cap1: 0.75 (p < 0.0001), MRI-Cap 2: 0.76 (p < 0.0001), and MRI-Cap3: 0.87 (p < 0.0001). Sensitivity, specificity, positive predictive value, negative predictive value, and AUC were: MRI-Cap 0: Se 97.87% Spec 83.3%, PPV 95.8%, NPV 90.9%, and AUC 90.9; MRI-Cap 1: Se 77% Spec 95.5%, PPV 83.3%, NPV 93.5%, and AUC 0.86; MRI-Cap 2- iCap 2: Se 88% Spec 90%, PPV 79%, NPV 95%, and AUC 0.89; MRI-Cap 3: Se 94% Spec 95%, PPV 88%, NPV 97%, and AUC 0.94. CONCLUSIONS: MRI-Cap classification is accurate in evaluating renal tumor PC features. PC features can provide an imaging-guided landmark to figure out where a minimal margin could be preferable during nephron-sparing surgery.

Differentiation of renal cell carcinoma subtypes through MRI-based radiomics analysis.

OBJECTIVES: To explore whether clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (pRCC), and chromophobe renal cell carcinoma (cRCC) can be distinguished using radiomics features extracted from magnetic resonance (MR) images. METHODS: Seventy-seven patients (ccRCC = 32, pRCC = 23, cRCC = 22) underwent MRI before surgery between May 2013 and August 2018 in this retrospective study. Thirty-nine radiomics features were extracted from tumor volumes on three sequences (T2WI, EN-T1WI CMP, and EN-T1WI NP). The Kruskal-Wallis test with Bonferonni correction and variance threshold were used for feature selection among the three RCC subtypes. ROC curves for the three subtypes were generated based on radiomics features. AUC, accuracy, sensitivity, and specificity for subtype differentiation are reported. Linear discriminant analysis (LDA) was used to assess the discriminative ability of these radiomics features. RESULTS: Significant radiomics features among the three subtypes were identified, and ROC curves achieved excellent AUCs for T2WI, EN-T1WI CMP, EN-T1WI NP, and combined three MR sequences (0.631, 0.790, 0.959, and 0.959 between ccRCC and cRCC; 0.688, 0.854, 0.909, and 0.955 between pRCC and cRCC; 0.747, 0.810, 0.814, and 0.890 between ccRCC and pRCC). In addition, LDA demonstrated the three RCC subtypes were correctly classified by radiomics analysis (66.2% for EN-T1WI CMP, 71.4% for EN-T1WI NP, 55.8% for T2WI, and 71.4% for the combined three MR sequences). CONCLUSIONS: Radiomics analysis can be used to differentiate among ccRCC, pRCC, and cRCC based on radiomics features extracted from multiple-sequence MRI and may help diagnose and treat RCC patients in the future, while further study is still needed. KEY POINTS: • Radiomics features on multiple-sequence MRI can help differentiate the three subtypes of renal cell carcinoma (clear cell, papillary renal cell, and chromophobe renal cell carcinoma). • Radiomics features based on MRI indicate greater textural heterogeneity on ccRCCs than pRCCs and cRCCs (the highest AUCs on EN-T1WI NP are 0.814 for ccRCCs vs pRCCs and 0.959 for ccRCCs vs cRCCs, respectively). • There is a significant difference in the textural heterogeneity of radiomics features between pRCCs and cRCCs (the AUC is 0.909, 0.854, and 0.688 on EN-T1WI NP, EN-T1WI CMP, and T2WI, respectively).

Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.

OBJECTIVE: To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (< 4 cm) renal angiomyolipoma without visible fat (AMLwvf) and renal cell carcinoma (RCC). METHODS: This study retrospectively collected 163 patients with pathologically proven small renal mass, including 118 RCC and 45 AMLwvf patients. Target region of interest (ROI) delineation, followed by texture feature extraction, was performed on a representative slice with the largest lesion area on each phase of the four-phase CT images. Fifteen concatenations of the four-phasic features were fed into 224 classification models (built with 8 classifiers and 28 feature selection methods), classification performances of the 3360 resultant discriminative models were compared, and the top-ranked features were analyzed. RESULTS: Image features extracted from the unenhanced phase (UP) CT image demonstrated dominant classification performances over features from other three phases. The two discriminative models "SVM + t_score" and "SVM + relief" achieved the highest classification AUC of 0.90. The 10 top-ranked features from UP included 1 shape feature, 5 first-order statistics features, and 4 texture features, where the shape feature and the first-order statistics features showed superior discriminative capabilities in differentiating RCC vs. AMLwvf through the t-SNE visualization. CONCLUSION: Image features extracted from UP are sufficient to generate accurate differentiation between AMLwvf and RCC using machine learning-based classification model. KEY POINTS: • Radiomics extracted from unenhanced CT are sufficient to accurately differentiate angiomyolipoma without visible fat and renal cell carcinoma using machine learning-based classification model. • The highest discriminative models achieved an AUC of 0.90 and were based on the analysis of unenhanced CT, alone or in association with images obtained at the nephrographic phase. • Features related to shape and to histogram analysis (first-order statistics) showed superior discrimination compared with gray-level distribution of the image (second-order statistics, commonly called texture features).

The impact of neutrophil-lymphocyte ratio on risk reclassification of patients with advanced renal cell cancer to guide risk-directed therapy.

Background: An elevated neutrophil-lymphocyte ratio (NLR) is associated with poor prognosis in advanced renal cell carcinoma (RCC). We examined whether the addition of NLR improves the risk reclassification of advanced RCC using current prognostic tools from the Memorial Sloan Kettering Cancer Center (MSKCC) and International Metastatic Renal Cell Carcinoma Database Consortium (IMDC).Methods: Using randomised data from the COMPARZ trial of first-line pazopanib vs. sunitinib in advanced RCC, we constructed multivariable models containing MSKCC and IMDC predictor variables with and without NLR. We evaluated model discrimination using the concordance index (C-index). We computed net reclassification improvement to quantify patient reclassification into low/intermediate/poor risk groups with the addition of NLR.Results: Of 1102 patients, NLR ≥ 5 (16%) was associated with shorter survival adjusting for MSKCC variables (adjusted HR 1.89, p < .001). Adding NLR to MSKCC variables increased the C-index by 0.01. Among patients who died before 24 months (N = 415), adding NLR reclassified 8% and 2% to a higher and lower risk category, respectively. Among those alive at 24 months (N = 636), adding NLR reclassified 4% and 1% to a higher and lower risk category, respectively. This finding translates to a net benefit of eight additional patients who die within 24 months correctly identified as poor risk per 1000 patients tested. We obtained similar results when evaluating NLR with IMDC variables.Conclusions: NLR does not substantially improve risk reclassification over pre-existing prognostic tools. MSKCC and IMDC classifications remain the standard for guiding risk-directed therapy and trial stratification of patients with advanced RCC.

8q24 clear cell renal cell carcinoma germline variant is associated with VHL mutation status and clinical aggressiveness.

BACKGROUND: The four most commonly-mutated genes in clear cell renal cell carcinoma (ccRCC) tumors are BAP1, PBRM1, SETD2 and VHL. And, there are currently 14 known RCC germline variants that have been reproducibly shown to be associated with RCC risk. However, the association of germline genetics with tumor genetics and clinical aggressiveness are unknown. METHODS: We analyzed 420 ccRCC patients from The Cancer Genome Atlas. Molecular subtype was determined based on acquired mutations in BAP1, PBRM1, SETD2 and VHL. Aggressive subtype was defined clinically using Mayo SSIGN score and molecularly using the ccA/ccB gene expression subtype. Publically-available Hi-C data were used to link germline risk variants with candidate target genes. RESULTS: The 8q24 variant rs35252396 was significantly associated with VHL mutation status (OR = 1.6, p = 0.0037) and SSIGN score (OR = 1.9, p = 0.00094), after adjusting for multiple comparisons. We observed that, while some germline variants have interactions with nearby genes, some variants demonstrate long-range interactions with target genes. CONCLUSIONS: These data further demonstrate the link between rs35252396, HIF pathway and ccRCC clinical aggressiveness, providing a more comprehensive picture of how germline genetics and tumor genetics interact with respect to tumor development and progression.

Comparison of clinicopathologic parameters and oncologic outcomes between type 1 and type 2 papillary renal cell carcinoma.

BACKGROUND: To compare the clinicopathologic parameters and oncologic outcomes between type 1 and type 2 papillary renal cell carcinoma (PRCC). METHODS: This study was approved by the review board (NO.XYFY2019-KL032-01). Between 2007 and 2018, 52 consecutive patients who underwent surgery at a single tertiary referral hospital were included. Clinicopathologic and survival data were collected and entered into a database. The Kaplan-Meier method, and univariate and multivariate Cox proportional hazard regression analyses were performed to estimate progression-free survival (PFS) and cancer-specific survival (CSS). RESULTS: Of the 52 patients, 24 (46.2%) were diagnosed with type 1 PRCC, and 28 (53.8%) had type 2 PRCC. The mean tumor size was 4.8 ± 2.5 cm. The two subtypes displayed different morphological features: foamy macrophages were more common in type 1 PRCC, while eosinophils and microvascular angiolymphatic invasion were more frequent in type 2 PRCC. Type 2 cases showed higher tumor stage and World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade than type 1 cases (T3-T4: 43% vs 17%, P = 0.041; G3-G4: 43% vs 8%, P = 0.005). In univariate analysis, type 2 PRCC had a lower probability for PFS and CSS than patients with type 1 PRCC (P = 0.016, P = 0.049, log-rank test, respectively). In multivariate analysis, only WHO/ISUP grade (HR 11.289, 95% CI 2.303-55.329, P = 0.003) and tumor size (HR 1.244, 95% CI 1.034-1.496, P = 0.021) were significantly associated with PFS. CONCLUSIONS: PRCC subtype displayed different morphological features: foamy macrophages, eosinophils and microvascular angiolymphatic invasion are pathologic features that may aid in the distinction of the two subtypes. Histologic subtype of PRCC is not an independent prognostic factor and only WHO/ISUP grade and tumor size were independent predictors for PFS.

Immune associated LncRNAs identify novel prognostic subtypes of renal clear cell carcinoma.

Kidney Renal Clear Cell Carcinoma (KIRC) is a significant cause of cancer-related deaths. Here, we aim to identify the LncRNAs associated with the immune system and characterise their clinical utility in KIRC. A total of 504 patients' data was used from TCGA-GDC. In silico correlation analysis identified 143 LncRNAs associated with immune-related genes (r > 0.7, P < 0.05). K-means consensus method clustered KIRC samples in three immune clusters, namely cluster C1, C2, and C3 based on the expression of 143 immune-related LncRNAs. Kaplan-Meier analysis showed that C3 patients survived significantly worse than the other two clusters (P < 0.0001). A comparison of TCGA miRNA, mRNA cluster with immune cluster showed the independence and robustness of immune clusters (HR = 2.02 and P = 2.12 × 10-8 ). The GSEA and CIBERSORT analysis showed high enrichment of poorly activated T-cells in C3 patients. To define LncRNA immune prognostic signature, we randomly divided the TCGA sample into discovery and validation sets. By utilising multivariate Cox regression analysis, we identified and validated a seven LncRNA immune prognostic signature score (LIPS score) (HR = 1.43 and P = 2.73 × 10-6 ) in KIRC. Comparison of LIPS score with all the clinical factors validated its independence and superiority in KIRC prognosis. In summary, we identified LncRNAs associated with the immune system and showed the presence of prognostic subtypes of KIRC patients based on immune-related LncRNA expression. We also identified a novel immune LncRNA based gene-signature for KIRC patients' prognostication.