New Preoperative Nomogram Using the Centrality Index to Predict High Nuclear Grade Clear Cell Renal Carcinoma

A multi-model based on radiogenomics and deep learning techniques associated with histological grade and survival in clear cell renal cell carcinoma

OBJECTIVES

This study aims to evaluate the efficacy of multi-model incorporated by radiomics, deep learning, and transcriptomics features for predicting pathological grade and survival in patients with clear cell renal cell carcinoma (ccRCC).

METHODS

In this study, data were collected from 177 ccRCC patients, including radiomics features, deep learning (DL) features, and RNA sequencing data. Diagnostic models were then created using these data through least absolute shrinkage and selection operator (LASSO) analysis. Additionally, a multi-model was developed by combining radiomics, DL, and transcriptomics features. The prognostic performance of the multi-model was evaluated based on progression-free survival (PFS) and overall survival (OS) outcomes, assessed using Harrell's concordance index (C-index). Furthermore, we conducted an analysis to investigate the relationship between the multi-model and immune cell infiltration.

RESULTS

The multi-model demonstrated favorable performance in discriminating pathological grade, with area under the ROC curve (AUC) values of 0.946 (95% CI: 0.912-0.980) and 0.864 (95% CI: 0.734-0.994) in the training and testing cohorts, respectively. Additionally, it exhibited statistically significant prognostic performance for predicting PFS and OS. Furthermore, the high-grade group displayed a higher abundance of immune cells compared to the low-grade group.

CONCLUSIONS

The multi-model incorporated radiomics, DL, and transcriptomics features demonstrated promising performance in predicting pathological grade and prognosis in patients with ccRCC.

CRITICAL RELEVANCE STATEMENT

We developed a multi-model to predict the grade and survival in clear cell renal cell carcinoma and explored the molecular biological significance of the multi-model of different histological grades.

KEY POINTS

1. The multi-model achieved an AUC of 0.864 for assessing pathological grade. 2. The multi-model exhibited an association with survival in ccRCC patients. 3. The high-grade group demonstrated a greater abundance of immune cells.

ANXA13 promotes cell proliferation and invasion and attenuates apoptosis in renal cell carcinoma

Purpose

Emerging evidences have demonstrated that annexin A13 (ANXA13) is closely related to the occurrence and development of malignant tumors. However, the functions and underlying molecular mechanisms of ANXA13 in Clear cell renal cell carcinoma (ccRCC) have not been defined. Therefore, this study aimed to clarify the potential role of ANXA13 in regulating the proliferation, migration, invasion, cell cycle, and apoptosis of ccRCC cells.

Patients and methods

The quantitative real-time PCR (qRT-PCR) and western blotting was performed for detecting the ANXA13 expression in ccRCC tissues at the mRNA and protein levels, respectively. The GEPIA2 databases were used to derive data for analyzing the ANXA13 expression in pan-cancer and ccRCC clinical features. Cell Counting and colony formation assays, as well as flow cytometry, were used to detect cell proliferation, apoptosis, or cell cycle. The wound healing assay was used to evaluate the migration ability of cells, and the Trans-well assay was conducted to determine the cell invasiveness.

Results

ANXA13 was upregulated in ccRCC cells and human ccRCC tissues. Furthermore, siANXA13 inhibited ccRCC cell proliferation, migration, invasion and induced cell apoptosis.

Conclusion

ANXA13 was upregulated in ccRCC. ANXA13 promotes tumorigenic traits of ccRCC cell lines in vitro. ANXA13 is a potential novel biomarker and a potential therapeutic target in ccRCC.

Long noncoding RNA-LINC00478 promotes the progression of clear cell renal cell carcinoma through PBX3

Long noncoding RNAs play an important regulatory role in the development and progression of tumors. Our study found that LINC00478 was upregulated in clear cell renal cell carcinoma (ccRCC), so we made an in-depth exploration into its mechanism. In Caki-2 cells, we established the oe-LINC00478 cell line overexpressing LINC00478, and established underexpressing sh-LINC00478 cell line by short hairpin RNA silencing. The abilities of oe-LINC00478 cell invasion and metastasis were significantly enhanced, and the cell proliferative potential was also improved. The cellular expressions of PBX3, CDCA8, and CDK2 were upregulated, while in the sh-LINC00478 cells, the proliferative potential and metastatic and invasive abilities were weakened. Similarly, we established the PBX3-overexpressing oe-PBX3 cell line and the PBX3-underexpressing sh-PBX3 cell line, finding that the PBX3 overexpression enhanced the metastatic and invasive abilities of Caki-2 cells. When we overexpressed LINC00478 in PBX3-knockout Caki-2-PBX3^{- / -} cells, no significant changes were noted in the metastatic or invasive ability. Through RNA pull-down and RNA-binding protein immunoprecipitation assays, we found that LINC00478 could facilitate the transcription-translation processes of PBX3 by binding to it, thus further promoting the expression of downstream cyclins to exert its action. In animal experimentation, the oe-LINC00478 and sh-LINC00478 Caki-2 cells were separately seeded, revealing that the tumor volume was significantly larger in the oe-LINC00478 group than in the sh-LINC00478 group. This study finds that by promoting the PBX3 transcription, LINC00478 can further regulate the expressions of downstream cyclins, thereby facilitating the metastasis and invasion of ccRCC.

2-[18F]FDG PET/CT parameters associated with WHO/ISUP grade in clear cell renal cell carcinoma

PURPOSE

To explore the potential parameters from preoperative 2-[¹⁸F]FDG PET/CT that might associate with the World Health Organization/the International Society of Urological Pathology (WHO/ISUP) grade in clear cell renal cell carcinoma (ccRCC).

METHODS

One hundred twenty-five patients with newly diagnosed ccRCC who underwent 2-[¹⁸F]FDG PET/CT prior to surgery or biopsy were retrospectively reviewed. The metabolic parameters and imaging features obtained from 2-[¹⁸F]FDG PET/CT examinations were analyzed in combination with clinical characteristics. Univariate and multivariate logistic regression analyses were performed to identify the predictive factors of WHO/ISUP grade.

RESULTS

Metabolic parameters of primary tumor maximum standardized uptake value (SUVmax), tumor-to-liver SUV ratio (TLR), and tumor-to-kidney SUV ratio (TKR) were significantly different between any two of the four different WHO/ISUP grades, except those between the WHO/ISUP grade 3 and grade 4. The optimal cutoff values to predict high WHO/ISUP grade for SUVmax, TLR, and TKR were 4.15, 1.63, and 1.59, respectively. TLR (AUC: 0.841) was superior to TKR (AUC: 0.810) in distinguishing high and low WHO/ISUP grades (P = 0.0042). In univariate analysis, SUVmax, TLR, TKR, primary tumor size, tumor thrombus, distant metastases, and clinical symptoms could discriminate between the high and low WHO/ISUP grades (P < 0.05). In multivariate analysis, TLR (P < 0.001; OR: 1.732; 95%CI: 1.289-2.328) and tumor thrombus (P < 0.001; OR: 6.199; 95%CI: 2.499-15.375) were significant factors for differentiating WHO/ISUP grades.

CONCLUSION

Elevated TLR (> 1.63) and presence of tumor thrombus from preoperative 2-[¹⁸F]FDG PET/CT can distinguish high WHO/ISUP grade ccRCC effectively. 2-[¹⁸F]FDG PET/CT may be a feasible method for noninvasive assessment of WHO/ISUP grade.