Allele Loss and Reduced Expression of CYCLOPS Genes is a Characteristic Feature of Chromophobe Renal Cell Carcinoma

Clinicopathological, Immunohistochemical, and Molecular Characteristics of Pigmented Microcystic Chromophobe Renal Cell Carcinoma with Favorable Prognosis

Background. Pigmented microcystic chromophobe renal cell carcinoma (RCC) is a subtype of chromophobe RCC. Its distinct histopathologic features are microcystic and microtubular pattern, pigmentation, and microcalcifications. Pigmented microcystic chromophobe RCC has ultrastructure, immunophenotypic structure, and molecular results similar to chromophobe RCC. Methods. We report five tumors of pigmented microcystic chromophobe RCC. Morphological observation and immunohistochemical examination were performed, and clinical and molecular features were analyzed. Results. Microscopically, all five tumors showed brown pigmentation, microcystic, and tubular cystic structures, one tumor presented microscopic calcifications. All tumors were positive for EMA, AE1/AE3, PAX8, KRT7, KIT (CD117), claudin 7, KRT8, and E-cadherin, and three tumors expressed P504S. All tumors were negative for vimentin, CA9, KRT20, TFE3, TFEB, Melan-A, HMB45, FH, SDHB, and GATA3. Ki-67 index varied from less than 1% to 2%. In three tumors, next-generation sequencing of the 688 gene was performed, the results found gene variants with potential clinical significance such as JMJD1C, MYCL, TP53, PI3KCA, KRAS, APC, GLI1, LRRK2, and gene variants with unclear clinical significance such as NTRK1 and RAD50; All patients remained alive over a follow-up period of 8-46 months without tumor recurrence and sarcomatoid transformation. Conclusions. Pigmented microcystic chromophobe RCC has a relatively benign biological behavior, and distant metastases and sarcomatoid transformation are rare. This overview of five additional tumors of pigmented microcystic chromophobe RCC offers further insight into this special subtype of chromophobe RCC.

Identification and verification of prognostic cancer subtype based on multi-omics analysis for kidney renal papillary cell carcinoma

Background

Identifying Kidney Renal Papillary Cell Carcinoma (KIRP) patients with high-risk, guiding individualized diagnosis and treatment of patients, and identifying effective prognostic targets are urgent problems to be solved in current research on KIRP.

Methods

In this study, data of multi omics for patients with KIRP were collected from TCGA database, including mRNAs, lncRNAs, miRNAs, data of methylation, and data of gene mutations. Data of multi-omics related to prognosis of patients with KIRP were selected for each omics level. Further, multi omics data related to prognosis were integrated into cluster analysis based on ten clustering algorithms using MOVICS package. The multi omics-based cancer subtype (MOCS) were compared on biological characteristics, immune microenvironmental cell abundance, immune checkpoint, genomic mutation, drug sensitivity using R packages, including GSVA, clusterProfiler, TIMER, CIBERSORT, CIBERSORT-ABS, quanTIseq, MCPcounter, xCell, EPIC, GISTIC, and pRRophetic algorithms.

Results

The top ten OS-related factors for KIRP patients were annotated. Patients with KIRP were divided into MOCS1, MOCS2, and MOCS3. Patients in the MOCS3 subtype were observed with shorter overall survival time than patients in the MOCS1 and MOCS2 subtypes. MOCS1 was negatively correlated with immune-related pathways, and we found global dysfunction of cancer-related pathways among the three MOCS subtypes. We evaluated the activity profiles of regulons among the three MOCSs. Most of the metabolism-related pathways were activated in MOCS2. Several immune microenvironmental cells were highly infiltrated in specific MOCS subtype. MOCS3 showed a significantly lower tumor mutation burden. The CNV occurrence frequency was higher in MOCS1. As for treatment, we found that these MOCSs were sensitive to different drugs and treatments. We also analyzed single-cell data for KIRP.

Conclusion

Based on a variety of algorithms, this study determined the risk classifier based on multi-omics data, which could guide the risk stratification and medication selection of patients with KIRP.

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.

Integrating multi-omics data reveals function and therapeutic potential of deubiquitinating enzymes

Deubiquitinating enzymes (DUBs), ~100 of which are found in human cells, are proteases that remove ubiquitin conjugates from proteins, thereby regulating protein turnover. They are involved in a wide range of cellular activities and are emerging therapeutic targets for cancer and other diseases. Drugs targeting USP1 and USP30 are in clinical development for cancer and kidney disease respectively. However, the majority of substrates and pathways regulated by DUBs remain unknown, impeding efforts to prioritize specific enzymes for research and drug development. To assemble a knowledgebase of DUB activities, co-dependent genes, and substrates, we combined targeted experiments using CRISPR libraries and inhibitors with systematic mining of functional genomic databases. Analysis of the Dependency Map, Connectivity Map, Cancer Cell Line Encyclopedia, and multiple protein-protein interaction databases yielded specific hypotheses about DUB function, a subset of which were confirmed in follow-on experiments. The data in this paper are browsable online in a newly developed DUB Portal and promise to improve understanding of DUBs as a family as well as the activities of incompletely characterized DUBs (e.g. USPL1 and USP32) and those already targeted with investigational cancer therapeutics (e.g. USP14, UCHL5, and USP7).

Elevated SNRPA1, as a Promising Predictor Reflecting Severe Clinical Outcome via Effecting Tumor Immunity for ccRCC, Is Related to Cell Invasion, Metastasis, and Sunitinib Sensitivity

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma and is associated with poor prognosis and notorious for its immune dysfunction characteristic. SNRPA1 is a spliceosome component responsible for processing pre-mRNA into mRNA, while the biological effect of SNRPA1 in ccRCC remains elusive. The aim of this study was to decipher the effect of SNRPA1 on clinical effect and tumor immunity for ccRCC patients. Multi-databases were collected to evaluate the different expression, prognostic value, DNA methylation, tumor immune microenvironment, and drug sensitivity of SNRPA1 on ccRCC. IHC was utilized to validate the expression and prognostic value of SNRPA1 in ccRCC patients from the SMMU cohort. The knockout expression of SNRPA by sgRNA plasmid inhibited the cell proliferation, migration, and metastasis ability and significantly increased the sensitivity of sunitinib treatment. In addition, we explored the role of SNRPA1 in pan-cancer level. The results indicated that SNRPA1 was differentially expressed in most cancer types. SNRPA1 may significantly influence the prognosis of multiple cancer types, especially in ccRCC patients. Notably, SNRPA1 was significantly correlated with immune cell infiltration and immune checkpoint inhibitory genes. In addition, the aggressive and immune inhibitory effects shown in SNRPA1 overexpression and the effect of SNRPA1 on ccRCC cell line invasion, metastasis, and drug sensitivity in vitro were observed. Moreover, SNRPA1 was related to Myc, MTORC, G2M, E2F, and DNA repair pathways in various cancer types. In all, SNRPA1 may prove to be a new biomarker for prognostic prediction, effect tumor immunity, and drug susceptibility in ccRCC.

Probing Isoform Switching Events in Various Cancer Types: Lessons From Pan-Cancer Studies

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. In cancer, alternative splicing is frequently disturbed, leading to changes in the expression of alternatively spliced protein isoforms. Advances in sequencing technologies and analysis methods led to new insights into the extent and functional impact of disturbed alternative splicing events. In this review, we give a brief overview of the molecular mechanisms driving alternative splicing, highlight the function of alternative splicing in healthy tissues and describe how alternative splicing is disrupted in cancer. We summarize current available computational tools for analyzing differential transcript usage, isoform switching events, and the pathogenic impact of cancer-specific splicing events. Finally, the strategies of three recent pan-cancer studies on isoform switching events are compared. Their methodological similarities and discrepancies are highlighted and lessons learned from the comparison are listed. We hope that our assessment will lead to new and more robust methods for cancer-specific transcript detection and help to produce more accurate functional impact predictions of isoform switching events.

[Oncocytic tumours of the kidney-new differential diagnoses]

BACKGROUND

Recent developments in differential diagnosis have led to new knowledge about oncocytic renal neoplasms.

OBJECTIVES

Overview of differential diagnosis of oncocytic tumours.

MATERIALS AND METHODS

We performed a literature search on oncocytic renal tumours and mapped known tumour types. Possible differential diagnoses are discussed.

RESULTS

Besides the tumour types already acknowledged by the 2016 WHO classification, there is new evidence regarding the group of hard-to-classify oncocytic neoplasms. Findings point to immunohistochemical and molecular characteristics that may lead to the establishment of new entities in the future. In addition, important differential diagnosis can now be identified, facilitating specific therapies for oncocytic renal tumours.

CONCLUSION

A correct diagnosis of oncocytic renal tumours not only improves prognostic assessment (and, if necessary, specific therapies) but is also clinically relevant regarding a possible association with hereditary tumour syndromes.

Towards a new WHO classification of renal cell tumor: what the clinician needs to know-a narrative review

In 1952, renal cell carcinomas had been divided into 2 categories—clear cell or granular cell—depending upon their cytoplasmic staining characteristics. In the following years, the inventory of renal epithelial tumors has expanded by the addition of tumors named by their architectural pattern (i.e., papillary RCC, tubulocystic RCC), anatomic location (i.e., collecting duct carcinoma, renal medullary carcinoma), associated diseases (i.e., acquired cystic disease-associated RCCs). With the extensive application of molecular diagnostic techniques, it becomes possible to detect genetic distinctions between various types of renal neoplasm and discover new entities, otherwise misdiagnosed or diagnosed as unclassified RCC. Some tumors such as ALK rearrangement-associated RCC, MiT family translocation renal carcinomas, SDH-deficient renal cancer or FH-deficient RCC, are defined by their molecular characteristics. The most recent World Health Organization (WHO) classification of renal neoplasms account for more than 50 entities and provisional entities. New entities might be included in the upcoming WHO classification. The aim of this review is to summarise and discuss the newly acquired data and evidence on the clinical, pathological, molecular features and on the prognosis of new RCC entities, which will hopefully increase the awareness and the acceptance of these entities among clinicians and improve prognostication for individual patients.

Chromophobe renal cell carcinoma: current and controversial issues

It has been 35 years since Professor Thoenes and his colleagues discovered chromophobe renal cell carcinoma (RCC). Since then, our knowledge about this tumour entity has changed and novel tumour entities have been discovered. The aim of this review is to discuss recent molecular findings and open questions in diagnosing chromophobe-like/oncocytic neoplasms. The broader differential diagnosis of chromophobe-like and oncocytoma-like neoplasms includes SDH-deficient renal cell carcinoma, fumarate hydratase (FH) deficient RCC, epitheloid angiomyolipoma ('oncocytoma like'), MiT family translocation RCC and the emerging entity of eosinophilic solid and cystic renal cell carcinoma. After separation of these tumours from chromophobe RCC, it becomes evident that chromophobe RCC are low malignant tumours with a 5-6% risk of metastasis. Recent next generation sequencing (NGS) and DNA methylation profiling studies have confirmed Thoenes' theory of a distal tubule derived origin of chromophobe RCC and renal oncocytomas. Comprehensive genomic analyses of chromophobe RCC have demonstrated a low somatic mutation rate and identified TP53 and PTEN as the most frequently mutated genes, whereas 'unclassified' RCC with oncocytic or chromophobe-like features can show somatic inactivating mutations of TSC2 or activating mutations of MTOR as the primary molecular alterations. For the future, it would be desirable to create a category of 'oncocytic/chromophobe RCC, NOS' with the potential of further molecular studies for identification of TSC1/2 mutations in these rare tumours.

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses

Background

A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the Tree-based Pipeline Optimization Tool (TPOT) constitute an appealing approach to this end. However, in biomedical data, there are often baseline characteristics of the subjects in a study or batch effects that need to be adjusted for in order to better isolate the effects of the features of interest on the target. Thus, the ability to perform covariate adjustments becomes particularly important for applications of AutoML to biomedical big data analysis.

Results

We developed an approach to adjust for covariates affecting features and/or target in TPOT. Our approach is based on regressing out the covariates in a manner that avoids ‘leakage’ during the cross-validation training procedure. We describe applications of this approach to toxicogenomics and schizophrenia gene expression data sets. The TPOT extensions discussed in this work are available at https://github.com/EpistasisLab/tpot/tree/v0.11.1-resAdj.

Conclusions

In this work, we address an important need in the context of AutoML, which is particularly crucial for applications to bioinformatics and medical informatics, namely covariate adjustments. To this end we present a substantial extension of TPOT, a genetic programming based AutoML approach. We show the utility of this extension by applications to large toxicogenomics and differential gene expression data. The method is generally applicable in many other scenarios from the biomedical field.

Loss of CDKN1A mRNA and Protein Expression Are Independent Predictors of Poor Outcome in Chromophobe Renal Cell Carcinoma Patients

Chromophobe renal cell carcinoma (chRCC) patients have good prognosis. Only 5%-10% patients die of metastatic disease after tumorectomy, but tumor progression cannot be predicted by histopathological parameters alone. chRCC are characterized by losses of many chromosomes, whereas gene mutations are rare. In this study, we aim at identifying genes indicating chRCC progression. A bioinformatic approach was used to correlate chromosomal loss and mRNA expression from 15287 genes from The Cancer Genome Atlas (TCGA) database. All genes in TCGA chromophobe renal cancer dataset (KICH) for which a significant correlation between chromosomal loss and mRNA expression was shown, were identified and their associations with outcome was assessed. Genome-wide DNA copy-number alterations were analyzed by Affymetrix OncoScan^® CNV FFPE Microarrays in a second cohort of Swiss chRCC. In both cohorts, tumors with loss of chromosomes 2, 6, 10, 13, 17 and 21 had signs of tumor progression. There were 4654 genes located on these chromosomes, and 13 of these genes had reduced mRNA levels, which was associated with poor outcome in chRCC. Decreased CDKN1A expression at mRNA (p = 0.02) and protein levels (p = 0.02) were associated with short overall survival and were independent predictors of prognosis (p <0.01 and <0.05 respectively). CDKN1A expression status is a prognostic biomarker independent of tumor stage. CDKN1A immunohistochemistry may be used to identify chRCC patients at greater risk of disease progression.

Knockdown of SF3B1 inhibits cell proliferation, invasion and migration triggering apoptosis in breast cancer via aberrant splicing

BACKGROUND

Splicing factor 3b subunit 1 (SF3B1) was frequently reported to be significantly mutated in breast cancer. However, the status of SF3B1 expression, its function and molecular consequence in breast cancer remained unreported.

METHODS

Immunohistochemistry was used to assess SF3B1expression in 110 breast cancer samples. SF3B1 knock‑down in ZR-75-30 and MDA-MB-231 cells was performed by shRNA transfection. The expression of SF3B1 in cells was detected by quantitative real‑time PCR and western blot. Cell proliferation ability was determined by MTT and colony formation assay. Migration and invasion were determined by transwell assay. Flow cytometry was performed to investigate cell cycle and apoptosis. RNA-sequencing was performed to examine differentially expressed genes and affected alternative splicing events.

RESULTS

SF3B1 is overexpressed in breast cancer tissues compared with normal tissues. Overexpression of SF3B1 is associated with lymph node metastasis. SF3B1 knockdown in MDA-MB-231 and ZR-75-30 breast cancer cells significantly induced the suppression of proliferation, migration, invasion and also enhancement of apoptosis. RNA-sequencing data revealed that 860 genes were significantly up-regulated and 776 genes were significantly down-regulated upon SF3B1 knockdown. Differentially expressed genes enriched in the signaling pathways including Ras signaling pathway; cytokine receptor interaction; tight junction; MAPK signaling pathway, Glycine, serine and threonine metabolism. Alternative splicing analysis revealed that exon skipping (SKIP) and cassette exons (MSKIP) were the most common molecular effect upon SF3B1 knockdown.

CONCLUSIONS

Our study suggests that SF3B1 may be an important molecular target for breast cancer treatment and provides a new clue for clinical treatment of breast cancer.

Classic Chromophobe Renal Cell Carcinoma Incur a Larger Number of Chromosomal Losses Than Seen in the Eosinophilic Subtype

Chromophobe renal cell carcinoma (chRCC) is a renal tumor subtype with a good prognosis, characterized by multiple chromosomal copy number variations (CNV). The World Health Organization (WHO) chRCC classification guidelines define a classic and an eosinophilic variant. Large cells with reticular cytoplasm and prominent cell membranes (pale cells) are characteristic for classic chRCC. Classic and eosinophilic variants were defined in 42 Swiss chRCCs, 119 Japanese chRCCs and in whole-slide digital images of 66 chRCCs from the Cancer Genome Atlas (TCGA) kidney chromophobe (KICH) dataset. 32 of 42 (76.2%) Swiss chRCCs, 90 of 119 (75.6%) Japanese chRCCs and 53 of 66 (80.3%) TCGA-KICH were classic chRCCs. There was no survival difference between eosinophilic and classic chRCC in all three cohorts. To identify a genotype/phenotype correlation, we performed a genome-wide CNV analysis using Affymetrix OncoScan^® CNV Assay (Affymetrix/Thermo Fisher Scientific, Waltham, MA, USA) in 33 Swiss chRCCs. TCGA-KICH subtypes were compared with TCGA CNV data. In the combined Swiss and TCGA-KICH cohorts, losses of chromosome 1, 2, 6, 10, 13, and 17 were significantly more frequent in classic chRCC (p < 0.05, each), suggesting that classic chRCC are characterized by higher chromosomal instability. This molecular difference justifies the definition of two chRCC variants. Absence of pale cells could be used as main histological criterion to define the eosinophilic variant of chRCC.