Prediction of World Health Organization /International Society of Urological Pathology (WHO/ISUP) Pathological Grading of Clear Cell Renal Cell Carcinoma by Dual-Layer Spectral CT

Targeted delivery of circPDHK1 siRNA via aptamer functionalized lipid nanoparticles inhibits ccRCC growth and migration

Clear Cell Renal Cell Carcinoma (ccRCC) is a common malignancy with high mortality in China, requiring innovative treatments. Recent advances in nucleic acid drugs, notably small interfering RNAs (siRNAs), show promise for therapeutic applications. Circular RNAs (circRNAs) play vital roles in cancer progression, and our previous work has identified that upregulated circPDHK1 can promote ccRCC growth and migration. However, the delivery strategies of si circPDHK1 targeting the circPDHK1 against ccRCC are not thoroughly investigated. Here, we developed a novel nucleic acid drug delivery system, AS1411/LNP-si circPDHK1, utilizing lipid nanoparticles (LNPs) encapsulated with siRNA targeting circPDHK1 and modified with the AS1411 aptamer for precise tumor targeting. In vitro and in vivo studies demonstrated that AS1411/LNP-si circPDHK1 efficiently delivered si circPDHK1 to ccRCC cells, resulting in a significant reduction in circPDHK1 expression. This delivery system exhibited superior tumor-targeting capabilities and prolonged circulation time compared with non-targeted formulations. Notably, AS1411/LNP-si circPDHK1 successfully inhibited the phosphorylation of the mTOR-AKT pathway, suppressed the proliferation and migration of ccRCC cells, and exhibited minimal side effects in vital organs. Taken together, the aptamer-guided LNP loaded siRNA targeting circPDHK1 (AS1411/LNP-si circPDHK1) displays great potential for ccRCC therapy.

Dual-energy computed tomography for predicting histological grading and survival in patients with pancreatic ductal adenocarcinoma

OBJECTIVES

We evaluated the value of dual-energy computed tomography (DECT) parameters derived from pancreatic ductal adenocarcinoma (PDAC) to discriminate between high- and low-grade tumors and predict overall survival (OS) in patients.

METHODS

Data were retrospectively collected from 169 consecutive patients with pathologically confirmed PDAC who underwent third-generation dual-source DECT enhanced dual-phase scanning before surgery between January 2017 and March 2023. Patients with prior treatments, other malignancies, small tumors, or poor-quality scans were excluded. Two radiologists evaluated three clinical and seven radiological features and measured sixteen DECT-derived parameters. Univariate and multivariate analyses were applied to select independent predictors. A prediction model and a corresponding nomogram were developed, and the area under the curve (AUC), calibration, and clinical applicability were assessed. The correlations between factors and OS were evaluated using Kaplan-Meier survival and Cox regression analyses.

RESULTS

One hundred sixty-nine patients were randomly divided into training (n = 118) and validation (n = 51) cohorts, among which 43 (36.4%) and 19 (37.3%) had high-grade PDAC confirmed by pathology, respectively. The vascular invasion, normalized iodine concentration in the venous phase, and effective atomic number in the venous phase were independent predictors for histological grading. A nomogram was constructed to predict the risk of high-grade tumors in PDAC, with AUCs of 0.887 and 0.844 in the training and validation cohorts, respectively. The nomogram exhibited good calibration and was more beneficial than a single parameter in both cohorts. Pathological- and nomoscore-predicted high-grade PDACs were associated with poor OS (all p < 0.05).

CONCLUSIONS

The nomogram, which combines DECT parameters and radiological features, can predict the histological grade and OS in patients with PDAC before surgery.

KEY POINTS

Question Preoperative determination of histological grade in PDAC is crucial for guiding treatment, yet current methods are invasive and limited. Findings A DECT-based nomogram combining vascular invasion, normalized iodine concentration, and effective atomic number accurately predicts histological grade and OS in PDAC patients. Clinical relevance The DECT-based nomogram is a reliable, non-invasive tool for predicting histological grade and OS in PDAC. It provides essential information to guide personalized treatment strategies, potentially improving patient management and outcomes.

Advances in research on malignant tumors and targeted agents for TOP2A (Review)

The DNA topoisomerase isoform topoisomerase IIα (TOP2A) is essential for the condensation and segregation of cellular mitotic chromosomes and the structural maintenance. It has been demonstrated that TOP2A is highly expressed in various malignancies, including lung adenocarcinoma (LUAD), hepatocellular carcinoma (HCC) and breast cancer (BC), associating with poor prognosis and aggressive tumor behavior. Additionally, TOP2A has emerged as a promising target for cancer therapy, with widespread clinical application of associated chemotherapeutic agents. The present study explored the impact of TOP2A on malignant tumor growth and the advancements in research on its targeted drugs. The fundamental mechanisms of TOP2A have been detailed, its specific roles in tumor cells are analyzed, and its potential as a biomarker for tumor prognosis and therapeutic targeting is highlighted. Additionally, the present review compiles findings from the latest clinical trials of relevant targeted agents, information on newly developed inhibitors, and discusses future research directions and clinical application strategies in cancer therapy, aiming to propose novel ideas and methods.

STAT2/SLC27A3/PINK1-Mediated Mitophagy Remodeling Lipid Metabolism Contributes to Pazopanib Resistance in Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is a prevalent malignant tumor of the urinary system. While tyrosine kinase inhibitors (TKIs) are currently the first-line treatments for advanced/metastatic ccRCC, patients often develop resistance after TKI therapy. Lipid metabolic reprogramming, a hallmark of tumor progression, contributes to acquired drug resistance in various malignant tumors. Mitophagy, a process that maintains mitochondrial homeostasis, aids tumor cells in adapting to microenvironmental changes and consequently developing drug resistance. Solute carrier family 27 member 3 (SLC27A3), highly expressed in lipid-rich tumors like ccRCC, has been associated with poor prognosis. However, the impact of SLC27A3 and the transcription factor complex containing STAT2 on lipid metabolic reprogramming, mitophagy in ccRCC, and their role in TKI resistance remain unexplored. Methods: 786-O to pazopanib resistance was induced by gradient increase of concentration, and the genes related to lipid metabolism were screened by RNA sequencing. Bioinformatics was used to analyze the differential expression of SLC27A3 and its effect on patient prognosis, and to predict the activated pathway in pazopanib-resistant cells. Lipid droplets (LDs) were detected by Red Oil O and BODIPY probe. Micro-targeted lipidomic of acyl-coenzyme A (CoA) and lipid metabolomics were performed to screen potential metabolites of SLC27A3. The differential expression of SLC27A3 was detected in clinical samples. The differential expression of SLC27A3 and its effect on drug resistance of ccRCC tumor were detected in vitro and in vivo. Mitophagy was detected by electron microscopy, Mtphagy probe, and Western blot. The mitochondrial membrane potential (MMP) and reactive oxygen species (ROS) levels were detected by JC-1 and DCF probes. The binding site of the transcription factor complex to the SLC27A3 promoter was detected by dual-luciferase reporter gene assay. Results: SLC27A3, highly expressed in lipid-rich tumors such as ccRCC and glioblastoma, predicts poor prognosis. SLC27A3 expression level also increased in pazopanib-resistant 786-O cells (786-O-PR) with more LD accumulation compared to parental cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis from RNA sequencing showed that PINK1/Parkin-mediated mitophagy pathway was enriched in 786-O-PR. Knockdown of SLC27A3 markedly suppressed LD accumulation and mitophagy, and overcame pazopanib resistance in vitro and in vivo. Moreover, SLC27A3 functions as an acyl-CoA ligase catalyzing the formation of acyl-CoA, which refers to fatty acid oxidation accompanied by ROS production and synthesis of lipid. Overproduced acyl-CoA oxidation in mitochondria resulted in MMP decrease and amounts of ROS production, subsequently triggering PINK1/Parkin-mediated mitophagy. Moreover, mitophagy inhibition led to more ROS accumulation and cell death, indicating that mitophagy can keep ROS at an appropriate level by negative feedback. Mitophagy, simultaneously, prevented fatty acid oxidation in mitochondria by consuming CPT1A, forcing synthesis of triglycerides and cholesterol esters stored in LDs by transforming acyl-CoA, to support ccRCC progression. Besides, we found that STAT2 expression was positively correlated to SLC27A3. Transcriptional factor complex containing STAT2 could bind to the promoter of SLC27A3 mRNA to promote SLC27A3 transcription proved by dual-luciferase reporter assay, which also regulated LD metabolism and activated mitophagy during pazopanib resistance. Conclusion: SLC27A3 is up-regulated in pazopanib-resistant ccRCC and predicts poor prognosis. High expression of SLC27A3 produces excessive metabolites of various long-chain fatty acyl-CoA (12:0-, 16:0-, 17:0-, 20:3-CoA) to enter mitochondria for β-oxidation and produce amounts of ROS activating mitophagy. Subsequent mitophagy/ROS negative feedback controls ROS homeostasis and consumes CPT1A protein within mitochondria to suppress fatty acid β-oxidation, forcing acyl-CoA storage in LDs, mediating pazopanib resistance in ccRCC. Furthermore, STAT2 was identified as a core component of a potential upstream transcriptional factor complex for SLC27A3. Our findings shed new light on the underlying mechanism of SLC27A3 in ccRCC TKI resistance, which may provide a novel therapeutic target for the management of ccRCC.

Microvascular invasion is associated with poor prognosis in renal cell carcinoma: a retrospective cohort study and meta-analysis

Background

This retrospective cohort study and meta-analysis aims to explore the association between microvascular invasion (MVI) and clinicopathologiccal features, as well as survival outcomes of patients with renal cell carcinoma (RCC).

Material and methods

The retrospective cohort study included 30 RCC patients with positive MVI and another 75 patients with negative MVI as controls. Clinicopathological features and follow-up data were compiled. The meta-analysis conducted searches on PubMed, Cochrane Library, Web of Science, Embase, and WanFang Data from the beginning to 30 September 2023, for comparative studies relevant to MVI patients. The Newcastle-Ottawa Scale and Egger Test were used to assess the risk of biases and certainty of evidence in the included studies.

Results

The cohort study showed that MVI was associated with advanced primary tumor stage, high pathological grades, high tumor size, high clinical symptoms and lymph node invasion (P <0.05). Kaplan-Meier analyses demonstrated MVI was associated with worse CSS rates when compared to MVI negative group (P <0.05). However, in the multivariate analysis it was not presented as an independent predictor of cancer survival mortality (P >0.05). The meta-analysis part included 11 cohort studies. The results confirmed that patients with MVI positive had worse 12 and 60 mo CSS rates (HR12mo = 0.86, 95%CI 0.80-0.92; HR60mo = 0.63, 95% CI 0.55-0.72; P < 0.00001). Moreover, the meta-analysis also confirmed that MVI group was associated with higher rate of advanced tumor stage, pathological grades, tumor size diameter, higher rate of clinical symptoms and lymph node invasion (P <0.05).

Conclusions

The presence of MVI in renal cell carcinoma patients is linked to poorer survival outcomes and worse clinicopathological features. In spite of this, it does not seem to be an independent predictor for cancer survival mortality in renal cell carcinoma.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023470640, identifier CRD42023470640.

Development and Validation of a Diagnostic Model for Identifying Clear Cell Renal Cell Carcinoma in Small Renal Masses Based on CT Radiological Features: A Multicenter Study

RATIONALE AND OBJECTIVES

This study aimed to develop a diagnostic model based on clinical and CT features for identifying clear cell renal cell carcinoma (ccRCC) in small renal masses (SRMs).

MATERIAL AND METHODS

This retrospective multi-centre study enroled patients with pathologically confirmed SRMs. Data from three centres were used as training set (n = 229), with data from one centre serving as an independent test set (n = 81). Univariate and multivariate logistic regression analyses were utilised to screen independent risk factors for ccRCC and build the classification and regression tree (CART) diagnostic model. The area under the curve (AUC) was used to evaluate the performance of the model. To demonstrate the clinical utility of the model, three radiologists were asked to diagnose the SRMs in the test set based on professional experience and re-evaluated with the aid of the CART model.

RESULTS

There were 310 SRMs in 309 patients and 71% (220/310) were ccRCC. In the testing cohort, the AUC of the CART model was 0.90 (95% CI: 0.81, 0.97). For the radiologists' assessment, the AUC of the three radiologists based on the clinical experience were 0.78 (95% CI:0.66,0.89), 0.65 (95% CI:0.53,0.76), and 0.68 (95% CI:0.57,0.79). With the CART model support, the AUC of the three radiologists were 0.93 (95% CI:0.86,0.97), 0.87 (95% CI:0.78,0.95) and 0.87 (95% CI:0.78,0.95). Interobserver agreement was improved with the CART model aids (0.323 vs 0.654, P < 0.001).

CONCLUSION

The CART model can identify ccRCC with better diagnostic efficacy than that of experienced radiologists and improve diagnostic performance, potentially reducing the number of unnecessary biopsies.

Preoperative prediction of renal fibrous capsule invasion in clear cell renal cell carcinoma using CT-based radiomics model

OBJECTIVES

To develop radiomics-based classifiers for preoperative prediction of fibrous capsule invasion in renal cell carcinoma (RCC) patients by CT images.

METHODS

In this study, clear cell RCC (ccRCC) patients who underwent both preoperative abdominal contrast-enhanced CT and nephrectomy surgery at our hospital were analysed. By transfer learning, we used base model obtained from Kidney Tumour Segmentation challenge dataset to semi-automatically segment kidney and tumours from corticomedullary phase (CMP) CT images. Dice similarity coefficient (DSC) was measured to evaluate the performance of segmentation models. Ten machine learning classifiers were compared in our study. Performance of the models was assessed by their accuracy, precision, recall, and area under the receiver operating characteristic curve (AUC). The reporting and methodological quality of our study was assessed by the CLEAR checklist and METRICS score.

RESULTS

This retrospective study enrolled 163 ccRCC patients. The semiautomatic segmentation model using CMP CT images obtained DSCs of 0.98 in the training cohort and 0.96 in the test cohort for kidney segmentation, and DSCs of 0.94 and 0.86 for tumour segmentation in the training and test set, respectively. For preoperative prediction of renal capsule invasion, the AdaBoost had the best performance in batch 1, with accuracy, precision, recall, and F1-score equal to 0.8571, 0.8333, 0.9091, and 0.8696, respectively; and the same classifier was also the most suitable for this classification in batch 2. The AUCs of AdaBoost for batch 1 and batch 2 were 0.83 (95% CI: 0.68-0.98) and 0.74 (95% CI: 0.51-0.97), respectively. Nine common significant features for classification were found from 2 independent batch datasets, including morphological and texture features.

CONCLUSIONS

The CT-based radiomics classifiers performed well for the preoperative prediction of fibrous capsule invasion in ccRCC.

ADVANCES IN KNOWLEDGE

Noninvasive prediction of renal fibrous capsule invasion in RCC is rather difficult by abdominal CT images before surgery. A machine learning classifier integrated with radiomics features shows a promising potential to assist surgical treatment options for RCC patients.

Nomogram combining pre-operative clinical characteristics and spectral CT parameters for predicting the WHO/ISUP pathological grading in clear cell renal cell carcinoma

PURPOSE

To develop a novel clinical-spectral-computed tomography (CT) nomogram incorporating clinical characteristics and spectral CT parameters for the preoperative prediction of the WHO/ISUP pathological grade in clear cell renal cell carcinoma (ccRCC).

METHODS

Seventy-three ccRCC patients who underwent spectral CT were included in this retrospective analysis from December 2020 to June 2023. The subjects were pathologically divided into low- and high-grade groups (WHO/ISUP 1/2, n = 52 and WHO/ISUP 3/4, n = 21, respectively). Information on clinical characteristics, conventional CT imaging features, and spectral CT parameters was collected. Multivariate logistic regression analyses were conducted to create a nomogram combing clinical data and image data for preoperatively predicting the pathological grade of ccRCC, and the area under the curve (AUC) was utilized to assess the predictive performance of the model.

RESULTS

Multivariate logistic regression analyses revealed that age, systemic immune-inflammation index (SII), and the slope of the spectrum curve in the cortex phase (CP-K) were independent predictors for predicting high-grade ccRCC. The clinical-spectral-CT model exhibited high evaluation efficacy, with an AUC of 0.933 (95% confidence interval [CI]: 0.878-0.998; sensitivity: 0.810; specificity: 0.923). The calibration curve revealed that the predicted probability of the clinical-spectral-CT nomogram could better fit the actual probability, with high calibration. The Hosmer-Lemeshow test showed that the model had a good fitness (χ2 = 5.574, p = 0.695).

CONCLUSION

The clinical-spectral-CT nomogram has the potential to predict WHO/ISUP grading of ccRCC preoperatively.

A novel peptide PDHK1-241aa encoded by circPDHK1 promotes ccRCC progression via interacting with PPP1CA to inhibit AKT dephosphorylation and activate the AKT-mTOR signaling pathway

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer with high aggressive phenotype and poor prognosis. Accumulating evidence suggests that circRNAs have been identified as pivotal mediators in cancers. However, the role of circRNAs in ccRCC progression remains elusive.

METHODS

The differentially expressed circRNAs in 4 paired human ccRCC and adjacent noncancerous tissues ccRCC were screened using circRNA microarrays and the candidate target was selected based on circRNA expression level using weighted gene correlation network analysis (WGCNA) and the gene expression omnibus (GEO) database. CircPDHK1 expression in ccRCC and adjacent noncancerous tissues (n = 148) were evaluated along with clinically relevant information. RT-qPCR, RNase R digestion, and actinomycin D (ActD) stability test were conducted to identify the characteristics of circPDHK1. The subcellular distribution of circPDHK1 was analyzed by subcellular fractionation assay and fluorescence in situ hybridization (FISH). Immunoprecipitation-mass spectrometry (IP-MS) and immunofluorescence (IF) were employed to evaluate the protein-coding ability of circPDHK1. ccRCC cells were transfected with siRNAs, plasmids or lentivirus approach, and cell proliferation, migration and invasion, as well as tumorigenesis and metastasis in nude mice were assessed to clarify the functional roles of circPDHK1 and its encoded peptide PDHK1-241aa. RNA-sequencing, western blot analysis, immunoprecipitation (IP) and chromatin immunoprecipitation (ChIP) assays were further employed to identify the underlying mechanisms regulated by PDHK1-241aa.

RESULTS

CircPDHK1 was upregulated in ccRCC tissues and closely related to WHO/ISUP stage, T stage, distant metastasis, VHL mutation and Ki-67 levels. CircPDHK1 had a functional internal ribosome entry site (IRES) and encoded a novel peptide PDHK1-241aa. Functionally, we confirmed that PDHK1-241aa and not the circPDHK1 promoted the proliferation, migration and invasion of ccRCC. Mechanistically, circPDHK1 was activated by HIF-2A at the transcriptional level. PDHK1-241aa was upregulated and interacted with PPP1CA, causing the relocation of PPP1CA to the nucleus. This thereby inhibited AKT dephosphorylation and activated the AKT-mTOR signaling pathway.

CONCLUSIONS

Our data indicated that circPDHK1-encoded PDHK1-241aa promotes ccRCC progression by interacting with PPP1CA to inhibit AKT dephosphorylation. This study provides novel insights into the multiplicity of circRNAs and highlights the potential use of circPDHK1 or PDHK1-241aa as a therapeutic target for ccRCC.