Features of increased malignancy in eosinophilic clear cell renal cell carcinoma

Loss of clear cell characteristics in aggressive clear cell odontogenic carcinoma: a case report

BACKGROUND

Clear cell odontogenic carcinoma (CCOC) is an odontogenic carcinoma characterized by sheets and islands of vacuolated and clear cells. The diagnosis of atypical CCOC can pose a challenge when tumor cells deviate from their characteristic clear morphology, even with the aid of genetic profiling for CCOC identification.

CASE PRESENTATION

In this manuscript, we detailed the inaugural instance of a recurrently recurring clear cell odontogenic carcinoma (CCOC) with pronounced squamous differentiation in a 64-year-old male. The primary tumor in this individual initially displayed a biphasic clear cell phenotype. However, subsequent to the third recurrence, the clear tumor cells were entirely supplanted by epidermoid cells characterized by eosinophilic cytoplasm, vesicular chromatin, and prominent nucleoli. Notable aggressive attributes such as necrosis, conspicuous cytological malignancy, perineural dissemination, and vascular invasion were noted. Additionally, the tumor progressed to manifest lung metastases. The tumor cells exhibited positive immunoreactivity for AE1/AE3, KRT19, Pan-CK, EMA, P40, P63, CK34βE12, and P53, while they tested negative for CK35βH11, KRT7, S-100, and neuroendocrine markers. The Ki-67 proliferation index was calculated at an average of 15%. Furthermore, FISH analysis unveiled the presence of the EWSR1::ATF1 gene fusion.

CONCLUSIONS

This case illustrated a rare and aggressive case of CCOC characterized by significant squamous differentiation upon recurrence of the tumor.

Mutated ASXL1 upregulates mTOR expression in renal cell carcinoma with fibromyomatous stroma

Renal cell carcinoma with fibromyomatous stroma (RCC FMS), defined as an "emerging entity" in the 2016 WHO classification and recommended to be a novel entity by GUPS, is represented by tumor cells with clear to mildly eosinophilic cytoplasm displaying elongated and branching tubules and papillae. A fibromyomatous stroma could be observed in these tumors. These tumors are immunopositive for CK7 and featured by ELOC and/or TSC/mTOR gene mutations. In the 2022 WHO classification, ELOC mutated RCC is classified as a molecularly defined RCCs as an individual renal entity. However, there are limited descriptions of TSC/mTOR alterations in RCC FMS. Herein, we reported a case of 28-year-old woman with RCC FMS with intact ELOC and TSC/mTOR genes but ASXL1 mutation. The tumor cells were positive for mTOR expression. This case may indicate that altered mTOR expression, but not limited to mutated TSC/mTOR gene, that participates in the pathogenesis of RCC FMS.

Dynamic changes of SCGN expression imply different phases of clear cell renal cell carcinoma progression

The secretagogin (SCGN) was originally identified as a secreted calcium-binding protein present in the cytoplasm. Recent studies have found that SCGN has a close relationship with cancer. However, its role in the occurrence, progression, and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. In this study, we utilized a mutual authentication method based on public databases and clinical samples to determine the role of SCGN in the progression and prognosis of ccRCC. Firstly, we comprehensively analyzed the expression characteristics of SCGN in ccRCC in several public databases. Subsequently, we systematically evaluated SCGN expression on 252 microarrays of ccRCC tissues from different grades. It was found that SCGN was absent in all the normal kidney tissues and significantly overexpressed in ccRCC tumor tissues. In addition, the expression level of SCGN gradually decreased with an increase in tumor grade, and the percentage of SCGN staining positivity over 50% was 86.7% (13/15) and 73.4% (58/79) in Grade1 and Grade2, respectively, while it was only 8.3% (12/144) in Grade3, and the expression of SCGN was completely absent in Grade4 (0/14) and distant metastasis group (0/4). Additionally, the expression of SCGN was strongly correlated with the patient's prognosis, with the higher the expression levels of SCGN being associated with longer overall survival and disease-free survival of patients. In conclusion, our results suggest that reduced expression of SCGN in cancer cells is correlated with the progression and prognosis of ccRCC.

Quantification of eosinophilic area and its potential molecular feature in clear cell renal cell carcinoma

OBJECTIVE

Previous studies have acknowledged the presence of eosinophilic cytoplasm in clear cell renal cell carcinoma, yet the precise quantification method and potential molecular attributes in clear cell renal cell carcinoma remain elusive. This study endeavours to precisely quantify the eosinophilic attribute and probe into the molecular mechanisms governing its presence in clear cell renal cell carcinoma.

METHODS

Data from cohorts of clear cell renal cell carcinoma patients who underwent nephrectomy, comprising The Cancer Genome Atlas cohort (n = 475) and Sun Yat-sen University Cancer Center cohort (n = 480), were aggregated to assess the eosinophilic attribute. Additionally, Omics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) (n = 58) were leveraged to explore the potential molecular features associated with eosinophilic clear cell renal cell carcinoma. Employing receiver operating characteristic curve analysis, the proportion of tumour cells with eosinophilic cytoplasm was determined, leading to the classification of each cohort into distinct groups: a clear group (<5%) and an eosinophilic group (≥5%).

RESULTS

In both cohorts, the eosinophilic feature consistently correlated with higher International Society of Urological Pathology (ISUP) grade, elevated tumor stage, and the presence of necrosis. Furthermore, the Kaplan-Meier method demonstrated that patients in the eosinophilic group exhibited shorter overall survival or disease-free survival compared with those in the clear group, a pattern reaffirmed in various stratified survival analyses. Intriguingly, within The Cancer Genome Atlas cohort, the pathological characterization of cell cytoplasm (eosinophilic vs. clear) emerged as an independent risk factor for overall survival (hazard ratio = 2.507 [95% confidence interval: 1.328-4.733], P = 0.005) or disease-free survival (hazard ratio = 1.730 [95% confidence interval: 1.062-2.818], P = 0.028) via Cox regression analysis. Moreover, multi-Omics data unveiled frequent BAP1 mutations and down-regulation of Erythroblast Transformation-Specific-Related Gene associated with the eosinophilic feature in clear cell renal cell carcinoma. Additionally, patients with low expression of Erythroblast Transformation-Specific-Related Gene showed worse overall survival (P < 0.001).

CONCLUSIONS

The quantification of the eosinophilic feature serves as a robust predictor of clinical prognosis in clear cell renal cell carcinoma. Furthermore, the manifestation of this feature may be linked to BAP1 mutations and the down-regulation of Erythroblast Transformation-Specific-Related Gene in clear cell renal cell carcinoma. Significantly, the expression levels of Erythroblast Transformation-Specific-Related Gene manifest as an exemplary prognostic marker, providing exceptional predictive accuracy for the clinical prognosis in clear cell renal cell carcinoma.

Exploration of Morphological Features of Clear Cell Renal Cell Carcinoma With PBRM1, SETD2, BAP1, or KDM5C Mutations

The last decade has seen great advances in genomic profiling and prognosis-associated factors of clear cell renal cell carcinoma (RCC), the most common entity in kidney cancer. Following VHL, PBRM1, SETD2, BAP1, and KDM5C have been validated as the most common co-occurring gene mutations in clear cell RCC by multicenter studies. However, the morphological features of clear cell RCC with co-occurring gene mutations remain unclear. In this study, we presented 20 clear cell RCCs that underwent next-generation sequencing, of which 1 tumor was reclassified as ELOC-mutated RCC. PBRM1, SETD2, BAP1, and KDM5C were the most common mutations, following VHL. Morphologically, clear cell RCC with PBRM1 or KDM5C mutation usually displayed a low-grade pattern. Cystic changes and hyalinized stroma were often observed. The Ki67 index was <10%. These observations indicated good prognosis. However, mutated SETD2 may increase the malignancy of clear cell RCC with PBRM1 mutation. Two clear cell RCCs with mutated PBRM1 and SETD2 developed local or distant metastases. Clear cell RCC with BAP1 mutations always had high-grade patterns, and rhabdoid differentiation was also observed, indicating that BAP1 mutation was associated with poor outcomes. Papillary architecture was often a feature of BAP1 mutation, which is uncommon in clear cell RCC. PDL1 was positive in only one tumor with BAP1 mutation, and the positivity rate was limited to 5%. B7H3 was negative in all tumors. Morphologic findings in this small cohort may suggest why PBRM1 mutation does not correlate with decreased survival, whereas BAP1 mutation usually predicts poor outcomes.

Screening and identification of prognostic genes associated with eosinophilic features of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma, which is characterized by transparent cytoplasm. However, some ccRCC also show eosinophilic cytoplasm, and the molecular difference between eosinophilic and clear subtypes is unclear. In this study, we uncovered that under an optical microscope ccRCC with eosinophilic features has a poor prognosis. Eosinophilic ccRCC tends to have a higher histologic grade. Eosinophilic ccRCC has 16 genes significantly up-regulated compared with ccRCC, of which seven genes have multi-cohort validation prognostic value. Immune infiltration analysis suggested a low number of M1 macrophages and NK tissue-resident cells in eosinophilic ccRCC. Enrichment analysis suggests that ccRCC with eosinophilic features may be closely associated with the transport and metabolism of many substances. The findings of this study have important implications for the study of the malignant transformation of ccRCC.

Exploration of clinicopathological features of rearranged renal cell carcinoma and TFE3, TFEB, and ALK staining performance in renal entities

Rearranged renal cell carcinomas (RCC) are rare types of kidney cancer. The clinicopathological features of rearranged RCC require further validation. The pathological diagnosis usually depends on immunohistochemistry and molecular analysis. This study aimed to explore the expression features of anti-TFE3, TFEB, and ALK in different renal entities. In addition, we collected thirty-six TFE3-rearranged RCC, two TFEB-altered RCC, and one ALK-rearranged RCC to explore their clinicopathological features. We observed that TFE3 can sometimes be weakly expressed in non-TFE3-rearranged RCC. TFE3-rearranged RCC usually exhibited strong TFE3 expression. However, clear cell RCC and FH-deficient RCC also displayed strong TFE3 expression. TFEB also can be weakly expressed in clear cell RCC. However, ALK IHC showed a relatively high specificity and was negative for all non-ALK-rearranged RCC. The ALK-rearranged RCC was analyzed using next generation sequencing to explore gene alterations, and we identified a novel gene partner, SLIT1. ALK-rearranged RCC appears to have eosinophilic cytoplasm. Tumor cells with clear cytoplasm may exclude this diagnosis. Psammomatous bodies (22/38) and pattern multiplicity (35/38) were observed in more than half of the patients. In conclusion, weak TFE3 expression did not indicate TFE3 rearrangement. Strong TFE3 expression had a higher value for indicating TFE3-rearranged RCC, although other entities can also exhibit a strong pattern. Young age combined with morphological features (psammomatous calcification and pattern multiplicity) may indicate the diagnosis of rearranged RCC.

Deep learning-based predictions of clear and eosinophilic phenotypes in clear cell renal cell carcinoma

We have recently shown that histological phenotypes focusing on clear and eosinophilic cytoplasm in clear cell renal cell carcinoma (ccRCC) correlated with prognosis and the response to angiogenesis inhibition and checkpoint blockade. This study aims to objectively show the diagnostic utility of clear or eosinophilic phenotypes of ccRCC by developing an artificial intelligence (AI) model using the TCGA-ccRCC dataset and to demonstrate if the clear or eosinophilic predicted phenotypes correlate with pathological factors and gene signatures associated with angiogenesis and cancer immunity. Before the development of the AI model, histological evaluation using hematoxylin and eosin whole-slide images of the TCGA-ccRCC cohort (n = 435) was performed by a urologic pathologist. The AI model was developed as follows. First, the highest-grade area on each whole slide image was captured for image processing. Second, the selected regions were cropped into tiles. Third, the AI model was trained using transfer learning on a deep convolutional neural network, and clear or eosinophilic predictions were scaled as AI scores. Next, we verified the AI model using a validation cohort (n = 95). Finally, we evaluated the accuracy of the prognostic predictions of the AI model and revealed that the AI model detected clear and eosinophilic phenotypes with high accuracy. The AI model stratified the patients' outcomes, and the predicted eosinophilic phenotypes correlated with adverse clinicopathological characteristics and high immune-related gene signatures. In conclusion, the AI-based histologic subclassification accurately predicted clear or eosinophilic phenotypes of ccRCC, allowing for consistently reproducible stratification for prognostic and therapeutic stratification.

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.

Predicting Clear Cell Renal Cell Carcinoma Survival Using Kurtosis of Cytoplasm in the Hematoxylin Channel from Histology Slides

Purpose

Grade-dependent decrease of lipid storage in clear cell renal cell carcinoma (ccRCC) leads to morphology changes in HE sections. This study investigated the role of cytoplasmic features in frozen sections of ccRCC on prognosis using the digital pathology approach.

Methods

We established an automatic pipeline that performed tumor region selection, stain vector normalization, nuclei segmentation, and feature extraction based on the pathologic data from Shanghai General Hospital and The Cancer Genome Atlas database. Extracted features were subjected to survival analysis.

Results

Kurtosis of the cytoplasm in the hematoxylin channel was correlated with progression-free survival (HR 0.10, 95% CI: 0.04–0.24, p=6.52^∗10⁻⁷) and overall survival (HR 0.11, 95% CI: 0.05–0.31, p=1.72^∗10⁻⁵) in ccRCC, which outperformed other texture features in this analysis. Multivariate Cox regression analysis revealed that low kurtosis of cytoplasm in the hematoxylin channel was an independent predictor for a shorter progression-free survival time (p=0.044) and overall survival time (p = 0.01). Kaplan–Meier survival analysis of progression-free survival and overall survival also showed a significantly worse prognosis in patients with low kurtosis of the cytoplasm in the hematoxylin channel (both p < 0.0001). Lower kurtosis of cytoplasm in the hematoxylin channel was associated with higher pathologic grade, less cholesterol ester, and more mitochondrial DNA content.

Conclusion

Kurtosis of the cytoplasm in the hematoxylin channel predicts survival in clear cell renal cell carcinoma.

Integration of NRP1, RGS5, and FOXM1 expression, and tumour necrosis, as a postoperative prognostic classifier based on molecular subtypes of clear cell renal cell carcinoma

Molecular mechanisms of progression of clear cell renal cell carcinoma (ccRCC) have been proven with recent genomic or transcriptional analyses. However, it is still difficult to apply these analyses to daily clinical practice owing to economical and practical issues. Here, we established a pathology-based, postoperative prognostic classification based on the well-validated transcriptional classifier, ClearCode34, in ccRCC. A total of 342 cases with available tissue were identified and randomly allocated into a discovery cohort (n = 138) and a validation cohort (n = 204). Levels of mRNA were quantified using a nCounter Digital Analyzer, and the ccA/ccB subtypes were determined. Histological and immunohistochemistry (IHC) analyses were subsequently performed to establish a pathology-based classification based on the mRNA levels. Finally, the prognostic ability of the new classifier was evaluated in both the discovery and validation cohorts. Of 138 cases in the discovery cohort, 78 (56.5%) and 60 (43.5%) were assigned to the ccA and ccB subtypes, respectively. Proangiogenic genes, neuropilin 1 (NRP1) and regulator of G protein signalling 5 (RGS5), were especially overexpressed in all ccRCC samples and were enriched in ccA-assigned tumours. Histologically, tumour necrosis and the sarcomatoid feature were associated with the ccB subtype. In IHC analyses, expression of NRP1, RGS5, and forkhead box M1 (FOXM1), an epithelial-mesenchymal transition-related factor, significantly correlated with the ccA/ccB subtypes. Combining these three IHC factors and tumour necrosis, we developed the IHC/histology-based classifier, which showed good concordance with the ClearCode34 classifier with an accuracy of 0.80. The established classification significantly stratified relapse-free, cancer-specific, and overall survival rates in both the discovery and validation cohorts. The novel molecular pathology classifier integrating NRP1, RGS5, FOXM1, and tumour necrosis may enable the stratification of oncological outcomes for patients with ccRCC undergoing resection surgery.

Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients.

Methods

The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics.

Results

According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage.

Conclusion

We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

Eosinophilic features in clear cell renal cell carcinoma correlate with outcomes of immune checkpoint and angiogenesis blockade

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) displays heterogeneity in appearance-a distinctive pale clear to eosinophilic cytoplasm; however, little is known about the underlying mechanisms and clinical implications. We investigated the role of these eosinophilic features in ccRCC on oncological outcomes and response to tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs).

METHODS

One-hundred and thirty-eight ccRCC cases undergoing radical surgery (cohort 1) and 54 metastatic ccRCC cases receiving either TKIs or ICIs (cohort 2) were included. After histological evaluation, all cases were divided into three phenotypes based on the eosinophilic features at the highest-grade area: clear, mixed, or eosinophilic type. Gene expression and immunohistochemical analyses were performed to explore the potential mechanisms of these phenotypes in cohort 1. Further, the association of the three phenotypes with the best objective response to TKI or ICI, clinical benefit (complete/partial response or stable disease), and overall survival (OS) was assessed in cohort 2.

RESULTS

The clear type was significantly associated with increased hypoxia as well as angiogenesis gene signatures compared with the eosinophilic type. Gene signatures and protein expression related to effector T cell and immune checkpoint molecules were elevated to a greater extent in the eosinophilic type, followed by the mixed and clear types. The mixed and eosinophilic types exhibited greater PBRM1-negativity and increased prevalence of the epithelial-mesenchymal transition gene signature than the clear type. In the mixed/eosinophilic types of cohort 2, significant clinical benefit was observed in the ICI therapy group versus the TKI therapy group (p=0.035), and TKI therapy vs ICI therapy was an independent factor for worse prognosis of OS (HR 3.236; p=0.012).

CONCLUSION

The histological phenotype based on the eosinophilic features, which are linked to major immunological mechanisms of ccRCC, was significantly correlated with therapeutic efficacy.

Comprehensive characterization of alternative splicing in renal cell carcinoma

Irregular splicing was associated with tumor formation and progression in renal cell carcinoma (RCC) and many other cancers. By using splicing data in the TCGA SpliceSeq database, RCC subtype classification was performed and splicing features and their correlations with clinical course, genetic variants, splicing factors, pathways activation and immune heterogeneity were systemically analyzed. In this research, alternative splicing was found useful for classifying RCC subtypes. Splicing inefficiency with upregulated intron retention and cassette exon was associated with advanced conditions and unfavorable overall survival of patients with RCC. Splicing characteristics like splice site strength, guanine and cytosine content and exon length may be important factors disrupting splicing balance in RCC. Other than cis-acting and trans-acting regulation, alternative splicing also differed in races and tissue types and is also affected by mutation conditions, pathway settings and the response to environmental changes. Severe irregular splicing in tumor not only indicated terrible intra-cellular homeostasis, but also changed the activity of cancer-associated pathways by different splicing effects including isoforms switching and expression regulation. Moreover, irregular splicing and splicing-associated antigens were involved in immune reprograming and formation of immunosuppressive tumor microenvironment. Overall, we have described several clinical and molecular features in RCC splicing subtypes, which may be important for patient management and targeting treatment.