A Novel Machine Learning Algorithm Combined With Multivariate Analysis for the Prognosis of Renal Collecting Duct Carcinoma

ObjectivesTo investigate the clinical and non-clinical characteristics that may affect the prognosis of patients with renal collecting duct carcinoma (CDC) and to develop an accurate prognostic model for this disease.MethodsThe characteristics of 215 CDC patients were obtained from the U.S. National Cancer Institute’s surveillance, epidemiology and end results database from 2004 to 2016. Univariate Cox proportional hazard model and Kaplan-Meier analysis were used to compare the impact of different factors on overall survival (OS). 10 variables were included to establish a machine learning (ML) model. Model performance was evaluated by the receiver operating characteristic curves (ROC) and calibration plots for predictive accuracy and decision curve analysis (DCA) were obtained to estimate its clinical benefits.ResultsThe median follow-up and survival time was 16 months during which 164 (76.3%) patients died. 4.2, 32.1, 50.7 and 13.0% of patients were histological grade I, II, III, and IV, respectively. At diagnosis up to 61.9% of patients presented with a pT3 stage or higher tumor, and 36.7% of CDC patients had metastatic disease. 10 most clinical and non-clinical factors including M stage, tumor size, T stage, histological grade, N stage, radiotherapy, chemotherapy, age at diagnosis, surgery and the geographical region where the care delivered was either purchased or referred and these were allocated 95, 82, 78, 72, 49, 38, 36, 35, 28 and 21 points, respectively. The points were calculated by the XGBoost according to their importance. The XGBoost models showed the best predictive performance compared with other algorithms. DCA showed our models could be used to support clinical decisions in 1-3-year OS models.ConclusionsOur ML models had the highest predictive accuracy and net benefits, which may potentially help clinicians to make clinical decisions and follow-up strategies for patients with CDC. Larger studies are needed to better understand this aggressive tumor.

A genomic mutation spectrum of collecting duct carcinoma in the Chinese population

Background Renal collecting duct carcinoma (CDC) is a rare and lethal subtype of renal cell carcinoma (RCC). The genomic profile of the Chinese population with CDC remains unclear. In addition, clinical treatments are contradictory. In this study, we aimed to identify the genomic mutation spectrum of CDC in the Chinese population. Methods Whole-exome sequencing was performed using the Illumina Novaseq™ 6000 platform. MuTect2 detects single-nucleotide variants (SNVs) and small scale insertions/deletions (INDELs). The identified mutations were annotated with ANNOVAR and validated by Sanger sequencing. Control-FREEC was used to detect copy number variation (CNV), and GISTIC was applied to detect frequently mutated altered regions. These data were compared with associated The Cancer Genome Atlas cohorts. Results Ten normal-matched CDC patients were included. The mean tumour mutation burden was 1.37 Mut/Mb. Six new recurrent somatic mutated genes were identified, including RBM14, MTUS1, GAK, DST, RNF213 and XIRP2 (20% and 2 of 10, respectively), and validated by Sanger sequencing. In terms of common mutated genes, SETD2 was altered in both CDC and other RCC subtypes but not in bladder urothelial carcinoma (BLCA); CDKN2A was a driver gene in both CDC (SNV: 10%, 1 of 10) and BLCA but not in other RCC subtypes. Next, 29 amplifications and 6 deletions of recurrent focal somatic CNVs were identified by GISTIC2.0, which displayed differences from kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP) and BLCA cohorts. Of note, CDKN2A (CNV alteration: 30%, 3 of 10) and CDKN2A-AS1 were the only overlapping genes of these four cohorts. Importantly, the CDKN2A mutation in our cohort differed from previous studies in urinary carcinomas. Moreover, CDKN2A-altered cases had significantly worse overall survival than wild-type cases in both KIRC and KIRP cohorts. In addition, the most frequently altered genomic pathway of our CDC cohort was the CDKN2A-mediated p53/RB1 pathway. Conclusions Our study offers the first genomic spectrum of the Chinese population with CDC, which differs from that of the Western population. The altered CDKN2A-mediated p53/RB1 pathway might provide new insight into potential therapeutic targets for CDC patients.

Incidence, Clinical Characteristics, and Survival of Collecting Duct Carcinoma of the Kidney: A Population-Based Study

ObjectiveTo investigate the exact age‐adjusted incidence (AAI), clinical characteristics, and survival data of collecting duct carcinoma of the kidney (CDCK) recorded in the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute.MethodsPatients with CDCK confirmed by microscopic examination from 2004 to 2018 were selected from the SEER database. AAI rates were calculated using SEER*Stat software (version 8.3.9). The Kaplan‐Meier method was used to evaluate cancer-specific survival (CSS) rates according to tumor size, tumor stage, and treatment methods, and differences among these variables were assessed by the log‐rank test. Cox regression analysis was employed to identify variables independently related to CSS.ResultsA total of 286 patients with CDCK were identified from the database. The majority of the patients were white (69.2%), male (67.5%), and married (60.5%), and the median age was 59 years. Most patients with CDCK (74.4%) presented with stages III or IV disease. The diameter of most (59.4%) tumors was less than 7 cm, and the tumors were more commonly found on the left than on the right (55.2% vs. 44.8%). The incidence of CDCK decreased over time. The median CSS time was 17 months. In terms of the treatment modalities used, 83.9% of the patients underwent surgery; 32.9% underwent chemotherapy, and 13.6% underwent radiotherapy. The CSS rates at 1, 2, and 5 years were 57.3%, 43.2%, and 30.7%, respectively. In patients with stage IV CDCK treated with surgery alone, chemotherapy alone, and surgery plus chemotherapy, the median survival time was 5 months, 9 months, and 14 months, respectively (P =0.024). Multivariate Cox regression analysis showed surgery, chemotherapy, stage, regional lymph node metastasis, and distant metastasis were independent prognostic factors for patients with CDCK.ConclusionsCDCK is an uncommon malignant renal carcinoma, and its incidence is decreasing based on the analysis of current data. CDCK is a high stage, regional lymph-nodes positive, and metastatic disease. Compared with surgery alone or chemotherapy alone, patients with stage IV could gain survival benefit from surgery combined with chemotherapy.

CT and MRI findings of cystic renal cell carcinoma: comparison with cystic collecting duct carcinoma

Background Cystic renal cell carcinoma (CRCC) and cystic collecting duct carcinoma (CCDC) share similar oncogeni and some imaging findings. The aim of this study was to characterize the clinical and CT imagings features of CRCC and CCDC. Methods Thirty-three patients with CRCC and thirteen patients with CCDC with pathologically proven were retrospectively studied. Tumor characteristics were assessed. Results On CT imaging, 33 patients(100 %) with CRCC and 13 patients(100 %) with CCDC, tumors calcifications (8 vs. 9, P < 0.0001), had a clear boundary (capsule sign, 30 vs. 2, P < 0.0001), infiltrative appearance (1 vs. 13, P < 0.0001), exogenous appearance (29 vs. 3, P < 0.0001), invaded the renal pelvis or ureter (1 vs. 10, P < 0.0001), hemorrhage (1 vs. 10, P < 0.0001), had retroperitoneal lymph node or distant metastasis (2 vs. 10, P < 0.0001), thickened enhancing internal septations (31 vs. 2, P < 0.0001), and mural soft-tissue nodules (21 vs. 1, P < 0.0001). On MR imaging,13 patients(39 %) with CRCC and 4 patients(31 %) with CCDC, all CRCCs appeared hypointense on T1-weighted images and hyperintense on T2-weighted images, however, all CCDCs appeared hypointense on T1-weighted images and hypointense on T2-weighted images(P < 0.0001). 33 patients with CRCC, they were all alive from3 years to 10 years follow-up, however, 13 patients with CCDC, of which 11 patients were able to be followed up, and 9 patients expired within 5 years of the initial diagnosis and the others are currently still alive. Conclusions Distinguishing features of CRCC and CCDC included calcifications, capsule signs, infiltrative appearance, metastasis, internal septations, mural nodules and signal on CT or MR images. These imaging features may help in differentiating the two renal tumor types.

Integrative Transcriptomic Analysis Reveals Distinctive Molecular Traits and Novel Subtypes of Collecting Duct Carcinoma

Collecting duct carcinoma (CDC) is a rare and highly aggressive kidney cancer subtype with poor prognosis and no standard treatments. To date, only a few studies have examined the transcriptomic portrait of CDC. Through integration of multiple datasets, we compared CDC to normal tissue, upper-tract urothelial carcinomas, and other renal cancers, including clear cell, papillary, and chromophobe histologies. Association between CDC gene expression signatures and in vitro drug sensitivity data was evaluated using the Cancer Therapeutic Response Portal, Genomics of Drug Sensitivity in Cancer datasets, and connectivity map. We identified a CDC-specific gene signature that predicted in vitro sensitivity to different targeted agents and was associated to worse outcome in clear cell renal cell carcinoma. We showed that CDC are transcriptionally related to the principal cells of the collecting ducts providing evidence that this tumor originates from this normal kidney cell type. Finally, we proved that CDC is a molecularly heterogeneous disease composed of at least two subtypes distinguished by cell signaling, metabolic and immune-related alterations. Our findings elucidate the molecular features of CDC providing novel biological and clinical insights. The identification of distinct CDC subtypes and their transcriptomic traits provides the rationale for patient stratification and alternative therapeutic approaches.