Clinical behavior of chromophobe renal cell carcinoma is less aggressive than that of clear cell renal cell carcinoma, independent of Fuhrman grade or tumor size

Lesion-aware cross-phase attention network for renal tumor subtype classification on multi-phase CT scans

Multi-phase computed tomography (CT) has been widely used for the preoperative diagnosis of kidney cancer due to its non-invasive nature and ability to characterize renal lesions. However, since enhancement patterns of renal lesions across CT phases are different even for the same lesion type, the visual assessment by radiologists suffers from inter-observer variability in clinical practice. Although deep learning-based approaches have been recently explored for differential diagnosis of kidney cancer, they do not explicitly model the relationships between CT phases in the network design, limiting the diagnostic performance. In this paper, we propose a novel lesion-aware cross-phase attention network (LACPANet) that can effectively capture temporal dependencies of renal lesions across CT phases to accurately classify the lesions into five major pathological subtypes from time-series multi-phase CT images. We introduce a 3D inter-phase lesion-aware attention mechanism to learn effective 3D lesion features that are used to estimate attention weights describing the inter-phase relations of the enhancement patterns. We also present a multi-scale attention scheme to capture and aggregate temporal patterns of lesion features at different spatial scales for further improvement. Extensive experiments on multi-phase CT scans of kidney cancer patients from the collected dataset demonstrate that our LACPANet outperforms state-of-the-art approaches in diagnostic accuracy.

External validation of a four-tiered grading system for chromophobe renal cell carcinoma

This study aimed to validate the prognostic value of a four-tiered grading system recently proposed by Avulova et al. and to explore the prognostic ability of another four-tiered classification grading system in which there is a separate Grade 3 for tumor necrosis. Grading of chromophobe renal cell carcinoma (ChRCC) by the Fuhrman system is not feasible because of the inherent nuclear atypia in ChRCC. We collected relevant data of 263 patients with ChRCC who had undergone surgery in our hospital from 2008 to 2020. The Kaplan-Meier method was used to calculate the survival rate and Cox proportional hazard regression models to assess associations with cancer-specific survival and distant metastasis-free survival by hazard ratios (HRs) and 95% confidence intervals (CIs). Ten patients died from ChRCC, and 12 developed metastases. The 5 year CSS rates were 95.9%. Grades 2 (HR = 10.9; CI 1.11-106.4; P = 0.04), 3 (HR = 33.6, CI 3.32-339.1; P = 0.003), and 4 (HR = 417.4, CI 35.0-4976.2; P < 0.001) in a four-tiered grading system were significantly associated with CSS in a multivariate setting. However, the difference in CSS between Grades 2 and 3 was not significant (HR = 2.14, 95% CI 0.43-10.63; P = 0.35). The HRs of the associations between an exploratory grading system that includes a separate Grade 3 for tumor necrosis and CSS were as follows: Grade 2, 10.2 (CI 1.06-97.9, P = 0.045); Grade 3, 11.4 (CI 1.18-109.6, P = 0.04); and Grade 4, 267.9 (CI 27.6-2603.3, P < 0.001). Similarly, Grades 2 and 3 did not differ significantly. The four-tiered grading system studied is useful for predicting death from ChRCC and metastasis. However, Grade 3 did not more accurately predict risk of death and metastasis than did Grade 2. This was also true for the novel exploratory grading system that classifies tumors with necrosis into a separate Grade 3.

The long-term outcomes of local tumor destruction versus partial nephrectomy for cT1a non-clear cell renal cell carcinoma and development of prognostic nomograms

PURPOSE

There is a lack of authoritative opinions on local tumor destruction (LTD) for clinical T1a (cT1a) non-clear cell renal cell carcinoma (nccRCC). We aim to compare the outcomes of cT1a nccRCC after partial nephrectomy (PN) or LTD and explore prognostic factors.

METHODS

Patients diagnosed with cT1a nccRCC receiving LTD or PN between 2000 and 2020 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. A 1:1 propensity score matching (PSM) was performed for patients receiving LTD and PN. Kaplan-Meier survival analysis, Cox regression analysis, competing risk regression models, and subgroup analysis were used to compare outcomes and identify prognostic factors. Prognostic nomograms were established and evaluated based on the multivariate models.

RESULTS

A total of 3664 cT1a nccRCC patients were included. The LTD group had poorer overall survival (OS) and similar cancer-specific survival (CSS) compared with the PN group before and after PSM (p < 0.05), while the other-cause mortality rate of the LTD group was higher than that of the PN group. Age, marital status, household income, prior tumor history, interval between diagnosis and treatment, treatments, and tumor size were identified as independent predictive factors for OS. Age, tumor size, prior tumor history, and histological type were identified as independent predictive factors for CSS. Then the nomograms predicting OS and CSS were constructed based on these prognostic factors, which showed excellent performance in risk stratification and accuracy.

CONCLUSION

LTD could achieve comparable cancer-control effects as PN among cT1a nccRCC patients. The OS and CSS nomograms worked effectively for prognosis assessment.

Leveraging diverse cell-death patterns to predict the prognosis, immunotherapy and drug sensitivity of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) poses clinical challenges due to its varied prognosis, tumor microenvironment attributes, and responses to immunotherapy. We established a novel Programmed Cell Death-related Signature (PRS) for ccRCC assessment, derived through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. We validated PRS using the E-MTAB-1980 dataset and created PCD-related clusters via non-negative matrix factorization (NMF). Our investigation included an in-depth analysis of immune infiltration scores using various algorithms. Additionally, we integrated data from the Cancer Immunome Atlas (TCIA) for ccRCC immunotherapy insights and leveraged the Genomics of Drug Sensitivity in Cancer (GDSC) database to assess drug sensitivity models. We complemented our findings with single-cell sequencing data and employed the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and qRT-PCR to compare gene expression profiles between cancerous and paracancerous tissues. PRS serves as a valuable tool for prognostication, immune characterization, tumor mutation burden estimation, immunotherapy response prediction, and drug sensitivity assessment in ccRCC. We identify five genes with significant roles in cancer promotion and three genes with cancer-suppressive properties, further validated by qRT-PCR and CPTAC analyses, showcasing gene expression differences in ccRCC tissues. Our study introduces an innovative PCD model that amalgamates diverse cell death patterns to provide accurate predictions for clinical outcomes, mutational profiles, and immune characteristics in ccRCC. Our findings hold promise for advancing personalized treatment strategies in ccRCC patients.

Comparative diagnostic performance of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging for differentiating clear cell and non-clear cell renal cell carcinoma

OBJECTIVE

To compare the diagnostic efficiency of contrast-enhanced ultrasound (CEUS) with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the differential diagnosis of clear and non-clear cell renal cell carcinoma, as confirmed by subsequent pathology.

METHODS

A total of 181 patients with 184 renal lesions diagnosed by both CEUS and DCE-MRI were enrolled in the study, including 136 clear cell renal cell carcinoma (ccRCC) and 48 non-clear cell renal cell carcinoma (non-ccRCC) tumors. All lesions were confirmed by histopathologic diagnosis after surgical resection. Interobserver agreement was estimated using a weighted kappa statistic. Diagnostic efficiency in evaluating ccRCC and non-ccRCC was compared between CEUS and DCE-MRI.

RESULTS

The weighted kappa value for interobserver agreement was 0.746 to 0.884 for CEUS diagnosis and 0.764 to 0.895 for DCE-MRI diagnosis. Good diagnostic performance in differential diagnosis of ccRCC and non-ccRCC was displayed by both CEUS and DCE-MRI: sensitivity was 89.7% and 91.9%, respectively; specificity was 77.1% and 68.8%, respectively; and area under the receiver operating curve was 0.834 and 0.803, respectively. No statistically significant differences were present between the two methods (p = 0.54).

CONCLUSIONS

Both CEUS and DCE-MRI imaging are effective for the differential diagnosis of ccRCC and non-ccRCC. Thus, CEUS could be an alternative to DCE-MRI as a first test for patients at risk of renal cancer, particularly where DCE-MRI cannot be carried out.

KEY POINTS

• CEUS and DCE-MRI features can help differentiate ccRCC and non-ccRCC. • The differential diagnosis of ccRCC and non-ccRCC by CEUS is comparable to that of DCE-MRI. • Interobserver agreement is generally high using CEUS and DCE-MRI.

WHO 2022 landscape of papillary and chromophobe renal cell carcinoma

The 5th edition of the WHO Classification of Tumours of the Urinary and Male Genital Systems contains relevant revisions and introduces a group of molecularly defined renal tumour subtypes. Herein we present the World Health Organization (WHO) 2022 perspectives on papillary and chromophobe renal cell carcinoma with emphasis on their evolving classification, differential diagnosis, and emerging entities. The WHO 2022 classification eliminated the type 1/2 papillary renal cell carcinoma (pRCC) subcategorization, given the recognition of frequent mixed tumour phenotypes and the existence of entities with a different molecular background within the type 2 pRCC category. Additionally, emerging entities such as biphasic squamoid alveolar RCC, biphasic hyalinising psammomatous RCC, papillary renal neoplasm with reverse polarity, and Warthin-like pRCC are included as part of the pRCC spectrum, while additional morphological and molecular data are being gathered. In addition to oncocytomas and chromophobe renal cell carcinoma (chRCC), a category of 'other oncocytic tumours' with oncocytoma/chRCC-like features has been introduced, including emerging entities, most with TSC/mTOR pathway alterations (eosinophilic vacuolated tumour and so-called 'low-grade' oncocytic tumour), deserving additional research. Eosinophilic solid and cystic RCC was accepted as a new and independent tumour entity. Finally, a highly reproducible and clinically relevant universal grading system for chRCC is still missing and is another niche of ongoing investigation. This review discusses these developments and highlights emerging morphological and molecular data relevant for the classification of renal cell carcinoma.

The quantitative evaluation of contrast-enhanced ultrasound in the differentiation of small renal cell carcinoma subtypes and angiomyolipoma

Background

Contrast-enhanced ultrasound (CEUS) has been widely used for renal lesion diagnosis and differential diagnosis. However, qualitative analysis of CEUS is subject to examinations with low reproducibility. This study aims to investigate the diagnostic value of CEUS quantitative parameters in differentiating small renal cell carcinoma (RCC) subtypes and angiomyolipoma (AML).

Methods

A retrospective analysis was performed on 97 cases of a small renal mass undergoing a CEUS before a radical or partial nephrectomy procedure. A region of interest (ROI) was placed in the tumor's maximum enhanced region (ROI_max) as much as possible, and adjacent renal cortex (ROI_refer) was selected from normal renal tissue around a mass of the same depth. The time-intensity curve (TIC) was used to analyze the ROI_max and the ROI_refer of the tumors quantitatively. Then the parameters of the ROI_max and the ROI_refer, including the differences between the parameters of the ROI_max and the ROI_refer, were analyzed statistically.

Results

In RCC and clear cell renal cell carcinoma (ccRCC), the peak intensity (PI), slope (SL), area under the curve (AUC), area under the wash-in curve (AWI), area under the wash-out curve (AWO), time to peak intensity (TTP) and the mean transit time (MTT) were statistically significant between ROI_max and ROI_refer (all P=0.000). The △PI (△PI = PI_max - PI_refer), △SL (△SL = SL_max - SL_refer), △AUC (△AUC = AUC_max - AUC_refer), △AWI (△AWI = AWI_max - AWI_refer) and △AWO (△AWO = AWO_max - AWO_refer) of RCC were significantly higher than in AML (P=0.007, 0.000, 0.003, 0.048, 0.009, respectively), while the TTP (△TTP = TTP_max - TTP_refer) and △MTT (△MTT = MTT_max - MTT_refer) of RCC were significantly lower (both P=0.000). In comparison with papillary renal cell carcinoma (pRCC) and chromophobe renal cell carcinoma (chRCC), the △PI, △SL, △AUC and △AWO of ccRCC were all larger (all P<0.05). The sensitivity, specificity, and AUC of the combination of parameter difference for differentiating RCC from AML were 100%, 81.2%, and 0.965, respectively, and for differentiating ccRCC from pRCC and chRCC, 85.71%, 85.92% and 0.911, respectively.

Conclusions

CEUS quantitative parameters have value in differentiating small RCC from AML and distinguishing ccRCC from pRCC and chRCC.

Development and evaluation of a deep neural network for histologic classification of renal cell carcinoma on biopsy and surgical resection slides

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. Reorganization and classification of complex histologic patterns of RCC on biopsy and surgical resection slides under a microscope remains a heavily specialized, error-prone, and time-consuming task for pathologists. In this study, we developed a deep neural network model that can accurately classify digitized surgical resection slides and biopsy slides into five related classes: clear cell RCC, papillary RCC, chromophobe RCC, renal oncocytoma, and normal. In addition to the whole-slide classification pipeline, we visualized the identified indicative regions and features on slides for classification by reprocessing patch-level classification results to ensure the explainability of our diagnostic model. We evaluated our model on independent test sets of 78 surgical resection whole slides and 79 biopsy slides from our tertiary medical institution, and 917 surgical resection slides from The Cancer Genome Atlas (TCGA) database. The average area under the curve (AUC) of our classifier on the internal resection slides, internal biopsy slides, and external TCGA slides is 0.98 (95% confidence interval (CI): 0.97-1.00), 0.98 (95% CI: 0.96-1.00) and 0.97 (95% CI: 0.96-0.98), respectively. Our results suggest that the high generalizability of our approach across different data sources and specimen types. More importantly, our model has the potential to assist pathologists by (1) automatically pre-screening slides to reduce false-negative cases, (2) highlighting regions of importance on digitized slides to accelerate diagnosis, and (3) providing objective and accurate diagnosis as the second opinion.

Grading Chromophobe Renal Cell Carcinoma: Evidence for a Four-tiered Classification Incorporating Coagulative Tumor Necrosis

BACKGROUND

Although grading systems have been proposed for chromophobe renal cell carcinoma (ChRCC), including a three-tiered system by Paner et al (Paner GP, Amin MB, Alvarado-Cabrero I, et al. A novel tumor grading scheme for chromophobe renal cell carcinoma: prognostic utility and comparison with Fuhrman nuclear grade. Am J Surg Pathol 2010;34:1233-40), none have gained clinical acceptance, and the World Health Organization (WHO) currently recommends against grading ChRCC.

OBJECTIVE

To validate a previously published grading scheme and propose a scheme that includes tumor necrosis.

DESIGN, SETTING, AND PARTICIPANTS

A total of 266 patients who underwent nephrectomy for nonmetastatic ChRCC between 1970 and 2012 were reviewed for ChRCC grade according to the Paner system and coagulative tumor necrosis.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations with cancer-specific survival (CSS) were evaluated using Cox proportional hazard regression models and summarized with hazard ratios (HRs).

RESULTS AND LIMITATIONS

Twenty-nine patients died from RCC; the median follow-up was 11.0 (interquartile range 7.9-15.9) yr. ChRCC grade according to the Paner system was significantly associated with CSS, including the difference in outcome between grade 1 and 2 tumors. Among patients with grade 2 tumors, the presence of tumor necrosis helped delineate patients with worse CSS. As such, the Paner system was expanded to four tiers separating grade 2 into those with and without tumor necrosis. HRs for associations of the proposed grade 2, 3, and 4 tumors with CSS were 4.63 (p=0.007), 17.8 (p<0.001), and 20.9 (p<0.001), respectively. The study is limited by the lack of multivariable analysis including additional pathologic features.

CONCLUSIONS

The expansion of a previously reported ChRCC grading system from three to four tiers by the inclusion of tumor necrosis helps further delineate patient outcome and can, therefore, enhance patient counseling following surgery. It also aligns the number of ChRCC grades with the WHO/International Society of Urologic Pathology four-tiered grading systems for clear cell and papillary RCC.

PATIENT SUMMARY

Chromophobe renal cell carcinoma is the third most common type of renal cancer, and unlike other renal cancers, there is no accepted prognostic grading system. In this study, we found that a grading system that included a pathologic feature of tumor necrosis could better define outcomes for patients with chromophobe renal cell carcinoma.

Grading of Clear Cell Renal Cell Carcinomas by Using Machine Learning Based on Artificial Neural Networks and Radiomic Signatures Extracted From Multidetector Computed Tomography Images

RATIONALE AND OBJECTIVES

To evaluate the ability of artificial neural networks (ANN) fed with radiomic signatures (RSs) extracted from multidetector computed tomography images in differentiating the histopathological grades of clear cell renal cell carcinomas (ccRCCs).

MATERIALS AND METHODS

The multidetector computed tomography images of 227 ccRCCs were retrospectively analyzed. For each ccRCC, 14 conventional image features (CIFs) were extracted manually by two radiologists, and 556 texture features (TFs) were extracted by a free software application, MaZda (version 4.6). The high-dimensional dataset of these RSs was reduced using the least absolute shrinkage and selection operator. Five minimum mean squared error models (minMSEMs) for predicting the ccRCC histopathological grades were constructed from the CIFs, the TFs of the corticomedullary phase images (CMP), and the TFs of the parenchyma phase (PP) images and their combinations, respectively abbreviated as CIF-minMSEM, CMP-minMSEM, PP-minMSEM, CIF+CMP-minMSEM, and CIF+PP-minMSEM. The RSs of each model were fed 30 times consecutively into an ANN for machine learning, and the predictive accuracy of each time ML was recorded for the statistical analysis.

RESULTS

The five predictive models were constructed from 12, 19, and 10 features selected from the CIFs, the TFs of the CMP images, and that of PP images, respectively. On the basis of their accuracy across the whole cohort, the five models were ranked as follows: CIF+CMP-minMSEM (accuracy: 94.06% ± 1.14%), CIF + PP-minMSEM (accuracy: 93.32% ± 1.23%), CIF-minMSEM (accuracy: 92.26% ± 1.65%), CMP-minMSEM (accuracy: 91.76% ± 1.74%), and PP-minMSEM (accuracy: 90.89% ± 1.47%).

CONCLUSION

Machine learning based on ANN helped establish an optimal predictive model, and TFs contributed to the development of high accuracy predictive models. The CIF+CMP-minMSEM showed the greatest accuracy for differentiating low- and high-grade ccRCCs.

Clinicopathologic and Genomic Factors Associated With Oncologic Outcome in Patients With Stage III to IV Chromophobe Renal Cell Carcinoma

BACKGROUND

Chromophobe renal cell carcinoma (chRCC) is known as an indolent tumor; however, mortality still occurs. We sought to determine the clinicopathologic and genomic factors associated with aggressive chRCC.

PATIENTS AND METHODS

Two different datasets were used to identify patients with clinical stage III and IV chRCC. Eighteen patients from The Cancer Genome Atlas (TCGA) database and 1693 patients from the American College of Surgeons National Cancer Database (NCDB) were used for analysis. From the TCGA, RNA-Seq expression analysis of 18,745 genes was conducted between the recurrent (n = 5; 27.8%) and nonrecurrent patients (n = 13; 72.2%). Biological significance was identified via pathway enrichment and gene function analyses. From the NCDB, Cox proportion hazards regression models were used to identify variables associated with overall survival (OS) at a median follow-up of 41.4 months.

RESULTS

Between the 2 groups, 2182 genes were differentially expressed. The most commonly overexpressed pathways were neuroactive ligand-receptor interactions and cytokine-cytokine receptor interactions. The most activated gene functions were cellular, metabolic, and multicellular organismal processes. In the NCDB, multivariable analysis, age (hazard ratio [HR], 1.04; 95% confidence interval [CI], 1.03-1.05; P < .001), TNM stage IV versus III (HR, 3.86; 95% CI, 2.98-5.00; P < .001), and positive surgical margin (HR, 1.68; 95% CI, 1.45-1.96; P < .001) were associated with worse OS at a median follow-up of 41.4 months. Five-year OS was significantly lower for stage IV patients compared with stage III patients (80.0% vs. 29.9%; P < .001).

CONCLUSIONS

Patients with recurrent chRCC demonstrated a differential gene expression of specific biochemical pathways. Clinical parameters associated with worse OS included age, stage, and positive surgical margin.

Predictive models composed by radiomic features extracted from multi-detector computed tomography images for predicting low- and high- grade clear cell renal cell carcinoma: A STARD-compliant article

To evaluate the values of conventional image features (CIFs) and radiomic features (RFs) extracted from multi-detector computed tomography (MDCT) images for predicting low- and high-grade clear cell renal cell carcinoma (ccRCC).Two hundred twenty-seven patients with ccRCC were retrospectively recruited. Five hundred seventy features including 14 CIFs and 556 RFs were extracted from MDCT images of each ccRCC. The CIFs were extracted manually and RFs by the free software-MaZda. Least absolute shrinkage and selection operator (Lasso) was applied to shrink the high-dimensional data set and select the features. Five predictive models for predicting low- and high-grade ccRCC were constructed by the selected CIFs and RFs. The 5 models were as follows: model of minimum mean squared error (minMSE) of CIFs (CIF-minMSE), minMSE of cortico-medullary phase (CMP) of kidney (CMP-minMSE), minMSE of parenchyma phase (PP) of kidney (PP-minMSE), the combined model of CIF-minMSE and CMP-minMSE (CIF-CMP-minMSE), and the combined model of CIF-minMSE and PP-minMSE (CIF-PP-minMSE). The Lasso regression equation of each model was constructed, and the predictive values were calculated. The receiver operating characteristic (ROC) curves of predictive values of the 5 models were drawn by SPSS19.0, and the areas under the curves (AUCs) were calculated.According to Lasso regression, 12, 19 and 10 features were respectively selected from the CIFs, RFs of CMP image and that of PP images to construct the 5 predictive models. The models ordered by their AUCs from large to small were CIF-CMP-minMSE (AUC: 0.986), CIF-PP-minMSE (AUC: 0.981), CIF-minMSE (AUC: 0.980), CMP-minMSE (AUC: 0.975), and PP-minMSE (AUC: 0.963). The maximum diameter of the largest axial section of ccRCC had a maximum weight in predicting the grade of ccRCC among all the features, and its cutoff value was 6.15 cm with a sensitivity of 0.901, a specificity of 0.963, and an AUC of 0.975.When combined with CIFs, RFs extracted from MDCT images contributed to the larger AUC of the predictive model, but were less valuable than CIFs when used alone. The CIF-CMP-minMSE was the optimal predictive model. The maximum diameter of the largest axial section of ccRCC had the largest weight in all features.

WHO/ISUP classification, grading and pathological staging of renal cell carcinoma: standards and controversies

PURPOSE

Pathological parameters assessed on biopsies and resection specimens have a pivotal role in the diagnosis, prognosis and management of patients with renal cell carcinoma (RCC).

METHODS

A non-systematic literature search was performed, updated to January 2018, to identify key standards and controversies in the pathological classification, grading and staging of RCC.

RESULTS

Although most RCCs exhibit characteristic morphology that enables easy categorisation, RCCs show considerable morphological heterogeneity and it is not uncommon for there to be difficulty in assigning a tumour type, especially with rarer tumour subtypes. The differentiation between benign and malignant oncocytic tumours remains a particular challenge. The development of additional immunohistochemical and molecular tests is needed to facilitate tumour typing, because of the prognostic and therapeutic implications, and to enable more reliable identification of poorly differentiated metastatic tumours as being of renal origin. Any new tests need to be applicable to small biopsy samples, to overcome the heterogeneity of renal tumours. There is also a need to facilitate identification of tumour types that have genetic implications, to allow referral and management at specialist centres. Digital pathology has a potential role in such referral practice.

CONCLUSION

Much has been done to standardise pathological assessment of renal cell carcinomas in recent years, but there still remain areas of difficulty in classification and grading of these heterogeneous tumours.

Differentiation of subtypes of renal cell carcinoma with contrast-enhanced ultrasonography

We aimed to assess the difference of enhancement patterns among the three RCC subtypes with contrast-enhanced ultrasound (CEUS). Two hundreds cases of pathologically proved clear cell renal cell carcinomas (ccRCC), 58 papillary renal cell carcinomas (pRCC) and 51 chromophobe renal cell carcinomas (chRCC) underwent preoperative conventional ultrasound and CEUS. The wash-in and wash-out pattern, peak enhancement degree and homogeneity, and the presence of pseudocapsule were evaluated by two blinded observers respectively. The interreader agreement in the characterization of CEUS features between two observers was good (κ  = 0.649-0.775). Compared with pRCCs and chRCCs, ccRCCs demonstrated higher frequency of simultaneous wash-in pattern, hyperenhancement and heterogeneity with necrotic areas. Most pRCCs and chRCCs manifested hypoenhancement, homogeneity, fast wash-out and presence of pseudocapsule. The only difference we obtained between pRCC and chRCC was the wash-in pattern, with slow wash-in in pRCC and simultaneous wash-in in chRCC. In small lesions with long diameter≤3 cm, the majority of the three subtypes of RCC showed homogeneous enhancement and there was no difference among them. CEUS was a useful method to preoperatively differentiate the ccRCC from non-ccRCC subtypes. There were no distinguishing features identifid on CEUS that allowed reliable differentiation of pRCC from chRCC.

Extraordinarily Large Renal Cell Carcinoma With Metasynchronous Neuroendocrine Tumor of the Ileocecal Valve: A Rare Presentation of Disease

A 71-year-old female presented with a large, protuberant abdominal mass, and was found to have both a left renal mass and a biopsy-proven neuroendocrine tumor of the ileocecal valve. Ultimately, right hemicolectomy revealed a well-differentiated and low-grade neuroendocrine tumor of the ileocecal valve, whereas left radical nephrectomy revealed a 23 cm × 22 cm × 15 cm renal cell carcinoma, chromophobe-type (RCC-CT) weighing 3564 g. RCC-CT represents a small portion of diagnosed RCC, and generally portends a more favorable prognosis than other variants. Modern reports of renal tumors exceeding 20 cm are exceedingly rare. In spite of massive size, favorable histology may allow for surgical cure.

Gender differences in incidence and outcomes of urothelial and kidney cancer

A gender discrepancy exists in the incidence of both urothelial and kidney carcinomas, with more men presenting with these cancers than women. Men have a threefold greater risk of developing bladder cancer than women, but female gender has been identified as an independent adverse prognostic factor for both recurrence and progression of this disease. In particular, women with bladder cancer are often diagnosed with a higher tumour stage than men. Conclusive data on the influence of gender on outcomes of patients with upper tract urothelial carcinoma are currently lacking, although men seem to have a higher disease incidence, whereas survival outcomes might be independent of gender. Patients with renal cell carcinoma are more often men and they typically have larger tumours and higher stage and grade disease than women with this cancer. Smoking habits, tumour biology, occupational risk factors and sex steroid hormones and their receptors could have a role in these observed gender disparities. The majority of data support the theory that gender influences incidence and prognosis of urothelial and kidney cancers; men and women are different genetically and socially, making the consideration of gender a key factor in the clinical decision-making process. Thus, the inclusion of this variable in validated prognostic tables and nomograms should be discussed as a matter of importance.

MicroRNA-877 acts as a tumor suppressor by directly targeting eEF2K in renal cell carcinoma

MicroRNAs (miRNAs) are involved in tumorigenesis. However, little is known about their role in renal cell carcinoma (RCC). In the present study, the function of the miRNA miR-877 in RCC was investigated, and its expression levels in blood and paired RCC tissues were measured by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Bioinformatics analysis predicted eukaryotic elongation factor-2 kinase (eEF2K) to be the potential mRNA target of miR-877, which was verified by luciferase assay. The expression levels of eEF2K in RCC tissues were evaluated by western blot analysis and qPCR. The proliferation and migration abilities of RCC cells were measured by MTT and in vitro wound healing assays, respectively. The present results indicated that the expression levels of miR-877 were downregulated in blood and paired RCC tissues, whereas the expression levels of eEF2K were upregulated in RCC tissues. In addition, overexpression of miR-877 and knockdown of eEF2K significantly reduced the proliferation and migration abilities of RCC cells in vitro. Furthermore, miR-877 affected the eEF2K/eEF2 signaling pathway in these cells. In conclusion, the present study has demonstrated that miR-877 suppresses the proliferation and migration abilities of RCC cells by modulating the eEF2K/eEF2 signaling cascade. Therefore, miR-877 may be considered a potential biomarker for the diagnosis of RCC.

Does chromophobe renal cell carcinoma have better survival than clear cell renal cell carcinoma? A clinical-based cohort study and meta-analysis

BACKGROUND

It is controversial whether chromophobe renal cell carcinoma (chRCC) or clear cell renal cell carcinoma (ccRCC) is associated with better survival. We conducted a clinical-based cohort study and meta-analysis to evaluate the prognostic role of histology between chRCC and ccRCC.

METHODS

A cohort of 1540 patients (166 with chRCC and 1374 with ccRCC) were selected from Sun Yat-sen University and The Cancer Genome Atlas databases. The clinicopathological parameters and overall survival (OS) were compared between patients with chRCC and those with ccRCC. For the meta-analysis, we searched the PubMed, Cochrane Library, and Ovid databases for studies comparing OS or cancer-specific survival (CSS) between chRCC and ccRCC.

RESULTS

The cohort study revealed that patients with chRCC were younger (median 52 vs. 55 years, P < 0.001), were more commonly female (47.0 vs. 33.0%, P < 0.001), and had a larger tumor size (mean 7.1 vs. 5.9 cm, P < 0.001), and they had a lower stage compared with those with ccRCC. Five-year OS rates for chRCC and ccRCC were 90.3 and 75.3%, respectively (P < 0.001). We found significantly better survival for chRCC in stratification analysis by age, sex, tumor size, and stage. Similar results were observed on both univariate [hazard ratio (HR), 0.30; 95% confidence interval (CI) 0.16-0.55, P < 0.001] and multivariate analyses (HR 0.42; 95% CI 0.23-0.79, P = 0.006). Ten studies were included in our meta-analysis. Eight of them provided data on univariate analysis. The pooled HR was statistically significant for OS (pooled HR 0.49; 95% CI 0.30-0.79, P = 0.004) and CSS (pooled HR 0.49; 95% CI 0.37-0.64, P < 0.001). Seven studies reported the HR on multivariate analysis. The pooled HR was also statistically significant for OS (pooled HR 0.63; 95% CI 0.51-0.77, P < 0.001) and CSS (pooled HR 0.72; 95 % CI 0.57-0.90, P = 0.003). These data indicate that patients with chRCC had better outcomes than those with ccRCC.

CONCLUSIONS

Our large cohort study and meta-analysis confirmed that chRCC had better survival than ccRCC.

Large-scale RNA-Seq Transcriptome Analysis of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types

The Cancer Genome Atlas (TCGA) has accrued RNA-Seq-based transcriptome data for more than 4000 cancer tissue samples across 12 cancer types, translating these data into biological insights remains a major challenge. We analyzed and compared the transcriptomes of 4043 cancer and 548 normal tissue samples from 21 TCGA cancer types, and created a comprehensive catalog of gene expression alterations for each cancer type. By clustering genes into co-regulated gene sets, we identified seven cross-cancer gene signatures altered across a diverse panel of primary human cancer samples. A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively. A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively. These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer.

Xp11.2 translocation renal cell carcinomas in young adults

BACKGROUND

Little is known about the biological behavior of Xp11.2 translocation renal cell carcinomas (RCCs) as few clinical studies have been performed using a large sample size.

METHODS

This study included 103 consecutive young adult patients (age ≤ 45 years) with RCC who underwent partial or radical nephrectomy at our institution from 2008 to 2013. Five patients without complete clinical data were excluded. Of the 98 remaining patients, 16 and 82 patients were included in the Xp11.2 translocation and non-Xp11.2 translocation groups, respectively. Clinicopathologic data were collected, including age, gender, tumor size, laterality, symptoms at diagnosis, surgical procedure, pathologic stage, tumor grade, time of recurrence and death.

RESULTS

Xp11.2 translocation RCCs were associated with higher tumor grade and pathologic stage (P < 0.05, Fisher's exact test). During the median follow-up of 36 months (range: 3-71 months), the number of cancer-related deaths was 4 (4.9%) and 3 (18.7%) in the non-Xp11.2 translocation and Xp11.2 translocation groups, respectively. The Kaplan-Meier cancer specific survival curves revealed a significant difference between non-Xp11.2 translocation RCCs and Xp11.2 translocation RCCs in young adults (P = 0.042).

CONCLUSIONS

Compared with non-Xp11.2 translocation RCCs, the Xp11.2 translocation RCCs seemingly showed a higher tumor grade and pathologic stage and have similar recurrence-free survival rates but poorer cancer-specific survival rates in young adults.

Renal cell carcinoma in children, adolescents and young adults: a National Cancer Database study

PURPOSE

We compared the presentation and outcomes of patients younger than 21 years with renal cell carcinoma and determined risk factors associated with mortality.

MATERIALS AND METHODS

We searched the National Cancer Database for patients diagnosed with renal cell carcinoma between 1998 and 2011. We evaluated patients younger than 30 years with renal cell carcinoma, including clear cell, chromophobe, papillary and not otherwise specified subcategories. We used logistic regression to compare presenting cancer, demographics and treatment variables in patients 0 to 15 years, 15 to 21 years and 21 to 30 years old. Cox regression analysis was used to determine risk factors for mortality in patients younger than 21.

RESULTS

Of 3,658 patients younger than 30 years included in the study 161 were younger than 15 and 337 were 15 to 21 years old. A higher proportion of younger patients had renal cell carcinoma not otherwise specified and papillary histology compared to those 21 to 30 years (p < 0.001). Younger patients presented with higher stage (p < 0.0001), higher grade (p < 0.0001) and larger tumors (p < 0.0001) than those 21 to 30 years. A higher percentage of younger patients underwent lymph node dissection (p < 0.0001) or chemotherapy as first-line treatment (p < 0.0001) compared to those 21 to 30 years. Cox regression analysis demonstrated that stage 4 presentation, government insurance status, nonchromophobic pathology results and not undergoing surgery as first-line treatment were independently associated with increased mortality in patients younger than 21 years.

CONCLUSIONS

Children and adolescents with renal cell carcinoma present with more advanced disease than those 21 to 30 years old. In patients younger than 21 years mortality was associated with the nonchromophobe histological subtype, stage 4 disease, government insurance and not undergoing surgery as first-line therapy.