Single-cell chromatin accessibility landscape in kidney identifies additional cell-of-origin in heterogenous papillary renal cell carcinoma

Papillary renal cell carcinoma (pRCC) is the most heterogenous renal cell carcinoma. Patient survival varies and no effective therapies for advanced pRCC exist. Histological and molecular characterization studies have highlighted the heterogeneity of pRCC tumours. Recent studies identified the proximal tubule (PT) cell as a cell-of-origin for pRCC. However, it remains elusive whether other pRCC subtypes have different cell-of-origin. Here, by obtaining genome-wide chromatin accessibility profiles of normal human kidney cells using single-cell transposase-accessible chromatin-sequencing and comparing the profiles with pRCC samples, we discover that besides PT cells, pRCC can also originate from kidney collecting duct principal cells. We show pRCCs with different cell-of-origin exhibit different molecular characteristics and clinical behaviors. Further, metabolic reprogramming appears to mediate the progression of pRCC to the advanced state. Here, our results suggest that determining cell-of-origin and monitoring origin-dependent metabolism could potentially be useful for early diagnosis and treatment of pRCC.

Characteristics of Clear Cell Papillary Renal Cell Carcinoma (ccpRCC)

Renal cell carcinomas (RCCs) is a group of various malignant tumours of the renal cortex displaying distinct clinical, morphologic, and genetic features. Clear cell papillary renal cell carcinoma (ccpRCC), belonging to this group, shares morphologic features with both clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC) and therefore, more strict diagnostic criteria should be developed to avoid misdiagnosis. Despite overlapping features, ccpRCC has also distinct clinical behaviour, histologic characteristics (morphologic and immunohistochemical), and genomic features. The concepts concerning this tumour are constantly developing since its biological potential and molecular basis remains to be fully unravelled. First reports indicated the presence of ccpRCC in end-stage renal disease, and they underlined the enriched development in this group of patients; however, currently, it is known that such tumours can also occur spontaneously in the normal kidney. Numerous studies have demonstrated that clinical outcomes and prognosis of ccpRCC patients is highly favourable. Till now, no convincing evidence of metastatic ccpRCC or death caused by the disease has been found. Therefore, it is of high importance to correctly differentiate ccpRCC from other subtypes of RCC with a much worse prognosis and to introduce appropriate management.

Automated Classification of Papillary Renal Cell Carcinoma and Chromophobe Renal Cell Carcinoma Based on a Small Computed Tomography Imaging Dataset Using Deep Learning

ObjectivesThis study was conducted in order to design and develop a framework utilizing deep learning (DL) to differentiate papillary renal cell carcinoma (PRCC) from chromophobe renal cell carcinoma (ChRCC) using convolutional neural networks (CNNs) on a small set of computed tomography (CT) images and provide a feasible method that can be applied to light devices.MethodsTraining and validation datasets were established based on radiological, clinical, and pathological data exported from the radiology, urology, and pathology departments. As the gold standard, reports were reviewed to determine the pathological subtype. Six CNN-based models were trained and validated to differentiate the two subtypes. A special test dataset generated with six new cases and four cases from The Cancer Imaging Archive (TCIA) was applied to validate the efficiency of the best model and of the manual processing by abdominal radiologists. Objective evaluation indexes [accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and area under the curve (AUC)] were calculated to assess model performance.ResultsThe CT image sequences of 70 patients were segmented and validated by two experienced abdominal radiologists. The best model achieved 96.8640% accuracy (99.3794% sensitivity and 94.0271% specificity) in the validation set and 100% (case accuracy) and 93.3333% (image accuracy) in the test set. The manual classification achieved 85% accuracy (100% sensitivity and 70% specificity) in the test set.ConclusionsThis framework demonstrates that DL models could help reliably predict the subtypes of PRCC and ChRCC.

The Identification of a Tumor Infiltration CD8+ T-Cell Gene Signature That Can Potentially Improve the Prognosis and Prediction of Immunization Responses in Papillary Renal Cell Carcinoma

BackgroundCD8+ T cells, vital effectors pertaining to adaptive immunity, display close relationships to the immunization responses to kill tumor cells. Understanding the effect exerted by tumor infiltration CD8+ T cells in papillary renal cell carcinoma (papRCC) is critical for assessing the prognosis process and responses to immunization therapy in cases with this disease.Materials and ApproachesThe single-cell transcriptome data of papRCC were used for screening CD8+ T-cell-correlated differentially expressed genes to achieve the following investigations. On that basis, a prognosis gene signature associated with tumor infiltration CD8+ T cell was built and verified with The Cancer Genome Atlas data set. Risk scores were determined for papRCC cases and categorized as high- or low-risk groups. The prognosis significance for risk scores was assessed with multiple-variate Cox investigation and Kaplan–Meier survival curves. In addition, the possible capability exhibited by the genetic profiles of cases to assess the response to immunization therapy was further explored.ResultsSix hundred twenty-one cell death-inhibiting RNA genes were screened using single-cell RNA sequencing. A gene signature consisting of seven genes (LYAR, YBX1, PNRC1, TCF25, MYL12B, MINOS1, and LINC01420) was then identified, and this collective was considered to be an independent prognosis indicator that could strongly assess overall survival in papRCC. In addition, the data allowed papRCC cases to fall to cohorts at high and low risks, exhibiting a wide range of clinically related features as well as different CD8+ T-cell immunization infiltration and immunization therapy responses.ConclusionsOur work provides a possible explanation for the limited response of current immunization checkpoint-inhibiting elements for combating papRCC. Furthermore, the researchers built a novel genetic signature that was able to assess the prognosis and immunotherapeutic response of cases. This may also be considered as a promising therapeutic target for the disease.

Metanephric Adenoma Associated with Unusual Urinary Candidiasis: A Challenging Morbidity from Postoperative Anastomotic Leak

Metanephric adenoma (MA) of the kidney is a rare benign neoplasm, which is mostly incidental-discovered during imaging studies for other clinical problems. However, this tumor may overlap in morphology with the papillary renal cell carcinoma and there are descriptions of metastatic disease. To date, fewer than 200 cases of MA have been reported worldwide and usually have a good prognosis. In the current report, a case of MA in a middle-aged lady is presented, which developed postoperative morbidity resulting from prolonged perinephric leakage secondary to urinary and perinephric fungus infection as a part of systemic candidiasis. The clinical, morphological and immunohistochemical features are presented together with a review of the current literature.