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

Genome-wide RNA-seq, DNA methylation and small RNA-seq analysis unraveled complex gene regulatory networks in psoriasis pathogenesis

Psoriasis is a complex inflammatory skin disease characterized by reversible albeit relapsing red scaly plaques in the skin of a patient. In addition to the genetic predisposition, involvement of epigenetic and non-coding RNAs have also been liked with the disease. Nevertheless, any comprehensive study involving transcriptomic, small-RNA and DNA methylation at the genomic level from same patients is lacking. To investigate the complex regulation of molecular pathways in psoriasis, we carried out multi-omics integrative analysis of RNA-sequencing, small RNA-sequencing and DNA methylation profiling from the psoriatic and adjacent normal skin tissues. Our multi-omics analysis identified the genes and biological processes regulated either independently or in combination by DNA methylation and microRNAs. We identified miRNAs that specifically regulated keratinocyte hyper-proliferation, and cell cycle progression and checkpoint signaling in psoriasis. On contrary, DNA methylation was found to be more predominant in regulating immune and inflammatory responses, another causative factor in psoriasis pathogenesis. Many characteristic pathways in psoriasis e.g., Th17 cell differentiation and JAK-STAT signaling, were found to be regulated by both miRNAs and DNA methylation. We carried out functional characterization of a downregulated miRNA hsa-let-7c-5p, predicted to target upregulated genes in psoriasis involved in cell cycle processes, Th17 cell differentiation and JAK-STAT signaling pathways. Overexpression of hsa-let-7c-5p in keratinocytes caused the downregulation of its target genes, resulting in reduced cell proliferation and migration rates, demonstrating potential of miRNAs in regulating psoriasis pathogenesis. In conclusion, our findings identified distinct and shared gene-networks regulated by DNA methylation and miRNAs of a complex disease with reversible phenotype.

Ferroptosis-Related lncRNA to Predict the Clinical Outcomes and Molecular Characteristics of Kidney Renal Papillary Cell Carcinoma

Kidney renal papillary cell carcinoma (KIRP) is a highly heterogeneous type of kidney cancer, resulting in limited effective prognostic targets for KIRP patients. Long non-coding RNAs (lncRNAs) have emerged as crucial regulators in the regulation of ferroptosis and iron metabolism, making them potential targets for the treatment and prognosis of KIRP. In this study, we constructed a ferroptosis-related lncRNA risk score model (FRM) based on the TCGA-KIRP dataset, which represents a novel subtype of KIRP not previously reported. The model demonstrated promising diagnostic accuracy and holds potential for clinical translation. We observed significant differences in metabolic activities, immune microenvironment, mutation landscape, ferroptosis sensitivity, and drug sensitivity between different risk groups. The high-risk groups exhibit significantly higher fractions of cancer-associated fibroblasts (CAFs), hematopoietic stem cells (HSC), and pericytes. Drugs (IC50) analysis provided a range of medication options based on different FRM typing. Additionally, we employed single-cell transcriptomics to further analyze the impact of immune invasion on the occurrence and development of KIRP. Overall, we have developed an accurate prognostic model based on the expression patterns of ferroptosis-related lncRNAs for KIRP. This model has the potential to contribute to the evaluation of patient prognosis, molecular characteristics, and treatment modalities, and can be further translated into clinical applications.

Association Between Diverse Cell Death Patterns Related Gene Signature and Prognosis, Drug Sensitivity, and Immune Microenvironment in Glioblastoma

Glioblastoma (GBM) is the most invasive type of glioma and is difficult to treat. Diverse programmed cell death (PCD) patterns have a significant association with tumor initiation and progression. A novel prognostic model based on PCD genes may serve as an effective tool to predict the prognosis of GBM. The study incorporated 11 PCD patterns, namely apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis, to develop the model. To construct and validate the model, both bulk and single-cell transcriptome data, along with corresponding clinical data from GBM cases, were obtained from the TCGA-GBM, REMBRANDT, CGGA, and GSE162631 datasets. A cell death-related signature containing 14 genes was constructed with the TCGA-GBM cohort and validated in the REMBRANDT and CGGA datasets. GBM patients with a higher cell death index (CDI) were significantly associated with poorer survival outcomes. Two separate clusters associated with clinical outcomes emerged from unsupervised analysis. A multivariate Cox regression analysis was conducted to examine the association of CDI with clinical characteristics, and a prognostic nomogram was developed. Drug sensitivity analysis revealed high-CDI GBM patients might be resistant to carmustine while sensitive to 5-fluorouracil. Less abundance of natural killer cells was found in GBM cases with high CDI and bulk transcriptome data. A cell death-related prognostic model that could predict the prognosis of GBM patients with good performance was established, which could discriminate between the prognosis and drug sensitivity of GBM.

Role of anoikis-related gene PLK1 in kidney renal papillary cell carcinoma: a bioinformatics analysis and preliminary verification on promoting proliferation and migration

Background: Kidney renal papillary cell carcinoma (KIRP) is a rare malignancy with a very poor prognosis. Anoikis is a specific form of apoptosis involved in carcinogenesis, but the role of anoikis in KIRP has not been explored. Methods: Anoikis-related genes (ARGs) were obtained from the GeneCards database and Harmonizome database and were used to identify different subtypes of KIRP and construct a prognostic model of KIRP. In addition, we also explored the immune microenvironment and enrichment pathways among different subtypes by consensus clustering into different subtypes. Drug sensitivity analysis was used to screen for potential drugs. Finally, we verified the mRNA and protein expression of the independent prognostic gene PLK1 in patient tissues and various cells and further verified the changes in relevant prognostic functions after constructing a PLK1 stable knockdown model using ShRNA. Results: We identified 99 differentially expressed anoikis-related genes (DEGs) associated with KIRP survival, and selected 3 genes from them to construct a prognostic model, which can well predict the prognosis of KIRP patients. Consensus clustering divided KIRP into two subtypes, and there was a significant difference in survival rates between the two subtypes. Immune profiling revealed differing immune statuses between the two subtypes, and functional analysis reveals the differential activity of different functions in different subtypes. Drug sensitivity analysis screened out 15 highly sensitive drugs in the high-risk group and 11 highly sensitive drugs in the low-risk group. Univariate and multivariate Cox regression analysis confirmed that PLK1 was an independent prognostic factor in KIRP, and its mRNA and protein expression levels were consistent with gene differential expression levels, both of which were highly expressed in KIRP. Functional verification of PLK1 in KIRP revealed significant results. Specifically, silencing PLK1 inhibited cell proliferation, clonogenicity, and migration, which indicated that PLK1 plays an important role in the proliferation and migration of KIRP. Conclusion: The prognosis model constructed by ARGs in this study can accurately predict the prognosis of KIRP patients. ARGs, especially PLK1, play an important role in the development of KIRP. This research can help doctors provide individualized treatment plans for KIRP patients and provide researchers with new research ideas.

Leveraging diverse cell-death patterns to predict the prognosis and drug sensitivity of triple-negative breast cancer patients after surgery

BACKGROUND

Postoperative progression and chemotherapy resistance is the major cause of treatment failure in patients with triple-negative breast cancer (TNBC). Currently, there is a lack of an ideal predictive model for the progression and drug sensitivity of postoperative TNBC patients. Diverse programmed cell death (PCD) patterns play an important role in tumor progression, which has the potential to be a prognostic and drug sensitivity indicator for TNBC after surgery.

MATERIALS AND METHODS

Twelve PCD patterns (apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis) were analyzed for model construction. Bulk transcriptome, single-cell transcriptome, genomics, and clinical information were collected from TCGA-BRCA, METABRIC, GSE58812, GSE21653, GSE176078, GSE75688, and KM-plotter cohorts to validate the model.

RESULTS

The machine learning algorithm established a cell death index (CDI) with a 12-gene signature. Validated in five independent datasets, TNBC patients with high CDI had a worse prognosis after surgery. Two molecular subtypes of TNBC with distinct vital biological processes were identified by an unsupervised clustering model. A nomogram with high predictive performance was constructed by incorporating CDI with clinical features. Furthermore, CDI was associated with immune checkpoint genes and key tumor microenvironment components by integrated analysis of bulk and single-cell transcriptome. TNBC patients with high CDI are resistant to standard adjuvant chemotherapy regimens (docetaxel, oxaliplatin, etc.); however, they might be sensitive to palbociclib (an FDA-approved drug for luminal breast cancer).

CONCLUSION

Generally, we established a novel CDI model by comprehensively analyzing diverse cell death patterns, which can accurately predict clinical prognosis and drug sensitivity of TNBC after surgery. A user-friendly website was created to facilitate the application of this prediction model (https://tnbc.shinyapps.io/CDI_Model/).

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.

Do we need an updated classification of oncocytic renal tumors? : Emergence of low-grade oncocytic tumor (LOT) and eosinophilic vacuolated tumor (EVT) as novel renal entities

The category of "oncocytic renal tumors'' includes well-recognized entities, such as renal oncocytoma (RO) and eosinophilic variant of chromophobe renal cell carcinoma (eo-ChRCC), as well as a group of "gray zone" oncocytic tumors, with overlapping features between RO and eo-ChRCC that create ongoing diagnostic and classification problems. These types of renal tumors were designated in the past as "hybrid oncocytoma-chromophobe tumors". In a recent update, the Genitourinary Pathology Society (GUPS) proposed the term "oncocytic renal neoplasm of low malignant potential, not further classified", for such solitary and sporadic, somewhat heterogeneous, but relatively indolent tumors, with equivocal RO/eo-ChRCC features. GUPS also proposed that the term "hybrid oncocytic tumor" be reserved for tumors found in a hereditary setting, typically arising as bilateral and multifocal ones (as in Birt-Hogg-Dubé syndrome). More recent developments in the "gray zone" of oncocytic renal tumors revealed that potentially distinct entities may have been "hidden" in this group. Recent studies distinguished two new entities: "Eosinophilic Vacuolated Tumor" (EVT) and "Low-grade Oncocytic Tumor" (LOT). The rapidly accumulated evidence on EVT and LOT has validated the initial findings and has expanded the knowledge on these entities. Both are uniformly benign and are typically found in a sporadic setting, but rarely can be found in patients with tuberous sclerosis complex. Both have readily distinguishable morphologic and immunohistochemical features that separate them from similar renal tumors, without a need for detailed molecular studies. These tumors very frequently harbor TSC/MTOR mutations that are however neither specific nor restricted to these two entities. In this review, we outline a proposal for a working framework on how to classify such low-grade oncocytic renal tumors. We believe that such framework will facilitate their handling in practice and will stimulate further discussions and studies to fully elucidate their spectrum.

Two case reports of immune checkpoint therapy on chromophobe renal cell carcinoma with sarcomatoid differentiation

Renal cell carcinoma (RCC) is the most predominant type of kidney cancer in adults and comprises several histological subtypes. Among them, the chromophobe RCC (ChRCC) with sarcomatoid differentiation is a rare subtype, and its therapeutic strategy remains unclear. Hence, to provide more information on effective therapeutic strategies against ChRCC, we report two cases of ChRCC with sarcomatoid differentiation treated with nivolumab monotherapy or ipilimumab-nivolumab combination therapy. One patient was treated with nivolumab monotherapy after the failure of sunitinib, while the other was treated with ipilimumab-nivolumab combination therapy as a first-line option. The therapeutic strategies adopted in both cases were effective, but the patients experienced immune-related adverse events such as interstitial nephritis and colitis. Thus, our report indicates that immune checkpoint therapy is effective for ChRCCs with sarcomatoid differentiation.

Development and validation of a vascularity-based architectural classification for clear cell renal cell carcinoma: correlation with conventional pathological prognostic factors, gene expression patterns, and clinical outcomes

The prognostic significance of an architectural grading system for clear cell renal cell carcinoma (ccRCC) has recently been demonstrated. The present study aimed to establish a vascularity-based architectural classification using the cohort of 436 patients with localized ccRCC who underwent extirpative surgery and correlated the findings with conventional pathologic factors, gene expression, and prognosis. First, we assessed architectural patterns in the highest-grade area on hematoxylin and eosin-stained slides, then separately evaluated our surrogate score for vascularity. We grouped nine architectural patterns into three categories based on the vascular network score. "Vascularity-based architectural classification" was defined: category 1: characterized by enrichment of the vascular network, including compact/small nested, macrocyst/microcystic, and tubular/acinar patterns; category 2: characterized by a widely spaced-out vascular network, including alveolar/large nested, thick trabecular/insular, papillary/pseudopapillary patterns; category 3: characterized by scattered vascularity without a vascular network, including solid sheets, rhabdoid and sarcomatoid patterns. Adverse pathological prognostic factors such as TNM stage, WHO/ISUP grade, and necrosis were significantly associated with category 3, followed by category 2 (all p < 0.001). We successfully validated the classification using The Cancer Genome Atlas (TCGA) cohort (n = 162), and RNA-sequencing data available from TCGA showed that the angiogenesis gene signature was significantly enriched in category 1 compared to categories 2 and 3, whereas the immune gene signature was significantly enriched in category 3 compared to categories 1 and 2. In univariate analysis, vascularity-based architectural classification showed the best accuracy in pathological prognostic factors for predicting recurrence-free survival (c-index = 0.786). The predictive accuracy of our model which integrated WHO/ISUP grade, necrosis, TNM stage, and vascularity-based architectural classification was greater than conventional risk models (c-index = 0.871 vs. 0.755-0.843). Our findings suggest that the vascularity-based architectural classification is prognostically useful and may help stratify patients appropriately for management based on their likelihood of post-surgical recurrence.

Monoallelic Heb/Tcf12 Deletion Reduces the Requirement for NOTCH1 Hyperactivation in T-Cell Acute Lymphoblastic Leukemia

Early T-cell development is precisely controlled by E proteins, that indistinguishably include HEB/TCF12 and E2A/TCF3 transcription factors, together with NOTCH1 and pre-T cell receptor (TCR) signalling. Importantly, perturbations of early T-cell regulatory networks are implicated in leukemogenesis. NOTCH1 gain of function mutations invariably lead to T-cell acute lymphoblastic leukemia (T-ALL), whereas inhibition of E proteins accelerates leukemogenesis. Thus, NOTCH1, pre-TCR, E2A and HEB functions are intertwined, but how these pathways contribute individually or synergistically to leukemogenesis remain to be documented. To directly address these questions, we leveraged Cd3e-deficient mice in which pre-TCR signaling and progression through β-selection is abrogated to dissect and decouple the roles of pre-TCR, NOTCH1, E2A and HEB in SCL/TAL1-induced T-ALL, via the use of Notch1 gain of function transgenic (Notch1ICtg) and Tcf12+/- or Tcf3+/- heterozygote mice. As a result, we now provide evidence that both HEB and E2A restrain cell proliferation at the β-selection checkpoint while the clonal expansion of SCL-LMO1-induced pre-leukemic stem cells in T-ALL is uniquely dependent on Tcf12 gene dosage. At the molecular level, HEB protein levels are decreased via proteasomal degradation at the leukemic stage, pointing to a reversible loss of function mechanism. Moreover, in SCL-LMO1-induced T-ALL, loss of one Tcf12 allele is sufficient to bypass pre-TCR signaling which is required for Notch1 gain of function mutations and for progression to T-ALL. In contrast, Tcf12 monoallelic deletion does not accelerate Notch1IC-induced T-ALL, indicating that Tcf12 and Notch1 operate in the same pathway. Finally, we identify a tumor suppressor gene set downstream of HEB, exhibiting significantly lower expression levels in pediatric T-ALL compared to B-ALL and brain cancer samples, the three most frequent pediatric cancers. In summary, our results indicate a tumor suppressor function of HEB/TCF12 in T-ALL to mitigate cell proliferation controlled by NOTCH1 in pre-leukemic stem cells and prevent NOTCH1-driven progression to T-ALL.

Identification and Validation of a Ferroptosis-Related Signature for Predicting Prognosis and Immune Microenvironment in Papillary Renal Cell Carcinoma

Objective

We aimed to explore the prognostic patterns of ferroptosis-related genes in papillary renal cell carcinoma (PRCC) and investigate the relationship between ferroptosis-related genes and PRCC tumor immune microenvironment.

Methods

We obtained the mRNA expression and corresponding clinical data of PRCC from the public tumor cancer genome atlas database (TCGA). The PRCC patients were randomly divided into two cohort, training cohort and verification cohort, respectively. Univariate Cox regression, LASSO Cox regression, multivariate Cox regression analysis were utilized to construct ferroptosis signature for PRCC patients. And then, risk prognostic model was established and verified. The correlation of ferroptosis-related signature with survival and immune microenvironment was systematically analyzed.

Results

A 4-genes ferroptosis signature (CDKN1A, MIOX, PSAT1, and RRM2) was constructed. Multivariate Cox regression assay indicates that the risk score of ferroptosis signature was an independent prognostic indicator (HR=1.391, p<0.001). The survival curve shows that the high-risk group has a poorer prognosis than the low-risk group (p<0.001). The risk prognostic model was established based on prognostic factors of clinical-stage, hemoglobin, and risk score. The time-dependent receiver operating characteristic curve (ROC) analysis proves the predictive capacity of the ferroptosis signature, the 3 years area under the curve (AUC) is 0.890, and the 5 years AUC is 0.733. Further analysis suggested that cell cycle, pentose phosphate pathway, P53 signaling pathway were significantly enriched in the high-risk group. The significantly different fractions of dendritic cells resting, macrophage cells, and T cells follicular helper were observed in risk groups.

Conclusion

This study implicates a ferroptosis signature which has a good predict capacity of the prognosis in PRCC patients. Ferroptosis-related genes may have a key role in the process of anti-tumor and serve as therapeutic targets for PRCC.

Construction and Validation of a Prognostic Risk Model for Triple-Negative Breast Cancer Based on Autophagy-Related Genes

Background

Autophagy plays an important role in triple-negative breast cancer (TNBC). However, the prognostic value of autophagy-related genes (ARGs) in TNBC remains unknown. In this study, we established a survival model to evaluate the prognosis of TNBC patients using ARGs signature.

Methods

A total of 222 autophagy-related genes were downloaded from The Human Autophagy Database. The RNA-sequencing data and corresponding clinical data of TNBC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed autophagy-related genes (DE-ARGs) between normal samples and TNBC samples were determined by the DESeq2 package. Then, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were performed. According to the LASSO regression results based on univariate Cox, we identified a prognostic signature for overall survival (OS), which was further validated by using the Gene Expression Omnibus (GEO) cohort. We also found an independent prognostic marker that can predict the clinicopathological features of TNBC. Furthermore, a nomogram was drawn to predict the survival probability of TNBC patients, which could help in clinical decision for TNBC treatment. Finally, we validated the requirement of an ARG in our model for TNBC cell survival and metastasis.

Results

There are 43 DE-ARGs identified between normal and tumor samples. A risk model for OS using CDKN1A, CTSD, CTSL, EIF4EBP1, TMEM74, and VAMP3 was established based on univariate Cox regression and LASSO regression analysis. Overall survival of TNBC patients was significantly shorter in the high-risk group than in the low-risk group for both the training and validation cohorts. Using the Kaplan–Meier curves and receiver operating characteristic (ROC) curves, we demonstrated the accuracy of the prognostic model. Multivariate Cox regression analysis was used to verify risk score as an independent predictor. Subsequently, a nomogram was proposed to predict 1-, 3-, and 5-year survival for TNBC patients. The calibration curves showed great accuracy of the model for survival prediction. Finally, we found that depletion of EIF4EBP1, one of the ARGs in our model, significantly reduced cell proliferation and metastasis of TNBC cells.

Conclusion

Based on six ARGs (CDKN1A, CTSD, CTSL, EIF4EBP1, TMEM74, and VAMP3), we developed a risk prediction model that can help clinical doctors effectively predict the survival status of TNBC patients. Our data suggested that EIF4EBP1 might promote the proliferation and migration in TNBC cell lines. These findings provided a novel insight into the vital role of the autophagy-related genes in TNBC and may provide new therapeutic targets for TNBC.

Histologic-Based Tumor-Associated Immune Cells Status in Clear Cell Renal Cell Carcinoma Correlates with Gene Signatures Related to Cancer Immunity and Clinical Outcomes

The three-tier immunophenotype (desert, excluded, and inflamed) and the four-tier immunophenotype (cold, immunosuppressed, excluded, and hot) have been linked to prognosis and immunotherapy response. This study aims to evaluate whether immunophenotypes of clear cell renal cell carcinoma, identified on hematoxylin and eosin-stained slides, correlate with gene expression signatures related to cancer immunity, and clinical outcomes. We evaluated tumor-associated immune cells (TAICs) status using three methodologies: three-tier immunophenotype based on the location of TAICs, four-tier immunophenotype considering both the location and degree of TAICs and inflammation score focusing only on the degree of TAICs, using a localized clear cell renal cell carcinoma cohort (n = 436) and The Cancer Genome Atlas (TCGA)-KIRC cohort (n = 162). We evaluated the association of the TAICs status assessed by three methodologies with CD8 and PD-L1 immunohistochemistry and immune gene expression signatures by TCGA RNA-sequencing data. All three methodologies correlated with immunohistochemical and immune gene expression signatures. The inflammation score and the four-tier immunophenotype showed similarly higher accuracy in predicting recurrence-free survival and overall survival compared to the three-tier immunophenotype. In conclusion, a simple histologic assessment of TIACs may predict clinical outcomes and immunotherapy responses.

TSC/mTOR Pathway Mutation Associated Eosinophilic/Oncocytic Renal Neoplasms: A Heterogeneous Group of Tumors with Distinct Morphology, Immunohistochemical Profile, and Similar Genetic Background

A number of recently described renal tumor entities share an eosinophilic/oncocytic morphology, somewhat solid architectural growth pattern, and tendency to present as low-stage tumors. The vast majority of such tumors follow a non-aggressive clinical behavior. In this review, we discuss the morphological, immunohistochemical, and molecular genetic profiles of the three most recent novel/emerging renal entities associated with TSC/mTOR pathway mutations. These are eosinophilic solid and cystic renal cell carcinoma, eosinophilic vacuolated tumors, and low-grade oncocytic tumors, which belong to a heterogeneous group of renal tumors, demonstrating mostly solid architecture, eosinophilic/oncocytic cytoplasm, and overlapping morphological and immunohistochemical features between renal oncocytoma and chromophobe renal cell carcinoma. All three tumors also share a molecular genetic background with mutations in the mTORC1 pathway (TSC1/TSC2/mTOR/RHEB). Despite the common genetic background, it appears that the tumors with TSC/mTOR mutations represent a diverse group of distinct renal neoplasms.

[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.

Genomic Analysis Reveals Novel Specific Metastatic Mutations in Chinese Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for more than 75% of renal cell carcinoma. Nearly 25% of ccRCC patients were diagnosed with metastasis. Though the genomic profile of ccRCC has been widely studied, the difference between localized and metastatic ccRCC was not clarified. Primary tumor samples and matched whole blood were collected from 106 sporadic patients diagnosed with renal clear cell carcinoma at Qilu Hospital of Shandong University from January 2017 to November 2019, and 17 of them were diagnosed with metastasis. A hybridization capture-based next-generation sequencing of 618 cancer-related genes was performed to investigate the somatic and germline variants, tumor mutation burden (TMB), and microsatellite instability (MSI). Five genes with significantly different prevalence were identified in the metastatic group, especially TOP1 (17.65% vs. 0%) and SNCAIP (17.65% vs. 0%). The altered frequency of PBRM1 (0% vs. 27%) and BAP1 (24% vs. 10%) differed between the metastatic and nonmetastatic groups, which may relate to the prognosis. Of these 106 patients, 42 patients (39.62%) had at least one alteration in DNA damage repair (DDR) genes, including 58.82% of metastatic ccRCC patients and 35.96% of ccRCC patients without metastasis. Ten pathogenic or likely pathogenic (P/LP) variants were identified in 11 sporadic clear cell renal cell carcinoma patients (10.38%), including rarely reported ATM (n=1), MUTYH (n=1), NBN (n=1), RAD51D (n=1), and BRCA2 (n=1). No significant difference in the ratio of P/LP variant carriers or TMB was identified between the metastatic and nonmetastatic groups. We found a unique genomic feature of Chinese metastatic ccRCC patients with a higher prevalence of alterations in DDR, TOP1, and SNCAIP. Further investigated studies and drug development are needed in the future.

Prognostic and Predictive Factors in Metastatic Renal Cell Carcinoma: Current Perspective and a Look Into the Future

Metastatic renal cell carcinoma (mRCC) comprises a highly heterogeneous group of diseases with varied clinical outcomes. As a result, models to estimate prognosis were developed in an attempt to aid patient counseling, treatment selection, and clinical trial design. Contemporary prognostic models have been mostly generated based on clinical factors because of their ease of use. Recent advances in molecular techniques have allowed unprecedented molecular profiling of RCC and the discovery of genomic and proteotranscriptomic factors that may contribute to disease trajectory. With the advent of multiple systemic therapies in mRCC in recent years, predictive biomarkers have become increasingly relevant in treatment selection. In this review, we discuss the existing staging systems and prognostic models in mRCC. We also highlight various promising molecular biomarkers according to the subtypes of RCC and explore their integration into the traditional prognostic models. In addition, we discuss emerging predictive biomarkers in the era of immuno-oncology. Lastly, we explore future directions with a focus on liquid biopsies and composite biomarkers.