All bone metastases are not created equal: Revisiting treatment resistance in renal cell carcinoma

Characterization of FOLH1 Expression in Renal Cell Carcinoma

PURPOSE

Given the emergence of PSMA-targeted diagnostic agents and therapeutics, we sought to investigate patterns of FOLH1 expression in RCC and their impacts on RCC outcomes.

METHODS

We conducted a pooled multi-institutional analysis of patients with RCC having undergone DNA and RNA next-generation sequencing. FOLH1-high/low expression was defined as the ≥75th/<25th percentile of RNA transcripts per million (TPM). Angiogenic, T-effector, and myeloid expression signatures were calculated using previously defined gene sets. Kaplan-Meier estimates were calculated from the time of tissue collection or therapy start.

RESULTS

We included 1,724 patients in the analysis. FOLH1 expression was significantly higher in clear cell (71%) compared to non-clear cell RCC tumors (19.0 versus 3.3 TPM, p < 0.001) and varied by specimen site (45% primary kidney/55% metastasis, 13.6 versus 9.9 TPM, p < 0.001). FOLH1 expression was correlated with angiogenic gene expression (Spearman = 0.76, p < 0.001) and endothelial cell abundance (Spearman = 0.76, p < 0.001). While OS was similar in patients with FOLH1-high versus -low ccRCC, patients with FOLH1-high clear cell tumors experienced a longer time on cabozantinib treatment (9.7 versus 4.6 months, respectively, HR 0.57, 95% CI 0.35-0.93, p < 0.05).

CONCLUSIONS

We observed differential patterns of FOLH1 expression based on histology and tumor site in RCC. FOLH1 was correlated with angiogenic gene expression, increased OS, and a longer duration of cabozantinib treatment.

Bone mimetic environments support engineering, propagation, and analysis of therapeutic response of patient-derived cells, ex vivo and in vivo

Bone metastases are the most common milestone in the lethal progression of prostate cancer and prominent in a substantial portion of renal malignancies. Interactions between cancer and bone host cells have emerged as drivers of both disease progression and therapeutic resistance. To best understand these central host-epithelial cell interactions, biologically relevant preclinical models are required. To achieve this goal, we here established and characterized tissue-engineered bone mimetic environments (BME) capable of supporting the growth of patient-derived xenograft (PDX) cells, ex vivo and in vivo. The BME consisted of a polycaprolactone (PCL) scaffold colonized by human mesenchymal stem cells (hMSCs) differentiated into osteoblasts. PDX-derived cells were isolated from bone metastatic prostate or renal tumors, engineered to express GFP or luciferase and seeded onto the BMEs. BMEs supported the growth and therapy response of PDX-derived cells, ex vivo. Additionally, BMEs survived after in vivo implantation and further sustained the growth of PDX-derived cells, their serial transplant, and their application to study the response to treatment. Taken together, this demonstrates the utility of BMEs in combination with patient-derived cells, both ex vivo and in vivo. STATEMENT OF SIGNIFICANCE: Our tissue-engineered BME supported the growth of patient-derived cells and proved useful to monitor the therapy response, both ex vivo and in vivo. This approach has the potential to enable co-clinical strategies to monitor bone metastatic tumor progression and therapy response, including identification and prioritization of new targets for patient treatment.

Natural history of bone-only metastasis in renal cell carcinoma

BACKGROUND

Bone metastasis (BM) is considered a poor prognostic factor of renal cell carcinoma (RCC). Confusion exists regarding how to deal with RCC patients with bone-only metastasis.

PATIENTS AND METHODS

The clinical data of consecutive RCC patients with bone-only metastasis at Peking University Cancer Hospital between 2006 and 2018 were retrospectively collected and analyzed.

RESULTS

Fifty-four eligible patients were screened from an RCC database of 1,878 metastatic patients. After a median follow-up of 43.6 m, 61.1% of the patients were presented with progression of prior BM or new BM. The progression-free survival (PFS) and overall survival (OS) was 16.2 m (95%CI: 11.4-21.0) and 65.2 m, respectively. For the 30 patients with oligo-metastasis (≤3 loci) and 24 ones with multiple-metastasis (>3 loci), the median OS was not reached and 42.0m (95%CI: 12.7-71.2) with statistical difference (P < 0.001). In the oligo-metastasis group, the median PFS of the 15 patients treated with local therapy and of the 13 patients treated with systemic therapy was 14.2 m (95%CI: 5.3-23.3) and 18.0 m (95%CI:15.4-20.6), respectively. In the multiple-metastasis group, the median PFS and OS of the 18 patients treated with systemic therapy was 16.6 m (95%CI: 7.5-25.7) and 63.9 m (95%CI: 21.8-106.0), respectively. Univariate analysis and multivariate analysis showed that the number of metastatic sites (oligo/multiple) and International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) score, RCC pathological subtype were significantly associated with prognosis (P < 0.05).

CONCLUSION

RCC patients with bone-only metastases have a favorable prognosis. The number of metastatic sites, IMDC, RCC pathological subtype could serve as survival predictors, which might provide clue of treatment modality.

Identification of a novel 5-methylcytosine-related signature for prognostic prediction of kidney renal papillary cell carcinoma and a Putative target for drug repurposing

BACKGROUND

Many studies have demonstrated the crucial roles of 5-methylcytosine (m5C) RNA methylation in cancer pathogenesis.

METHODS

Two datasets, including TCGA-KIRP and ICGC, and related clinical information were downloaded, where the expression of 13 m5C regulators was examined. We applied LASSO regression to construct a multi-m5C-regulator-based signature in the TCGA cohort, which was further validated using the ICGC cohort. Univariate and multivariate Cox regressions were applied to evaluate the independent prognostic value of our model. The differences in biological functions and immune characterizations between high and low-risk groups divided based on the risk scores were also investigated via multiple approaches, such as enrichment analyses, mutation mining, and immune scoring. Finally, the sensitivities of commonly used targeted drugs were tested, and the connectivity MAP (cMAP) was utilized to screen potentially effective molecules for patients in the high-risk group. Experimental validation was done following qPCR tests in Caki-2 and HK-2 cell lines.

RESULTS

3 m5C regulators, including ALYREF, DNMT3B and YBX1, were involved in our model. Survival analysis revealed a worse prognosis for patients in the high-risk group. Cox regression results indicated our model's superior predictive performance compared to single-factor prognostic evaluation. Functional enrichment analyses indicated a higher mutation frequency and poorer tumor microenvironment of patients in the high-risk group. qPCR-based results revealed that ALYREF, DNMT3B, and YBX1 were significantly up-regulated in Caki-2 cell lines compared with HK-2 cell lines. Molecules like BRD-K72451865, Levosimendan, and BRD-K03515135 were advised by cMAP for patients in the high-risk group.

CONCLUSION

Our study presented a novel predictive model for KIRP prognosis. Furthermore, the results of our analysis provide new insights for investigating m5C events in KIRP pathogenesis.

Bone Metastases in Renal Cell Carcinoma: Impact of Immunotherapy on Survival

Background/Aim

We performed a multicenter retrospective observational study to investigate the impact of immune checkpoint inhibitors (ICIs) on the survival of patients with bone metastases (BMs) from renal cell cancer (RCC).

Patients and Methods

A total of 98 patients with metastatic RCC (mRCC) treated with ICIs were retrospectively enrolled. All patients received standard treatments with nivolumab alone or in combination with ipilimumab from December 2015 to March 2022. The primary endpoint was median overall survival (OS).

Results

Forty-three patients (44%) had radiological evidence of BMs. No statistically significant difference in OS was reported between the BM population and the entire population (p=0.254).

Conclusion

Our study suggests some degree of ICI activity to treat patients with BMs from RCC, historically associated with a poorer prognosis.

Alkaline phosphatase combines with CT factors for differentiating small (≤ 4 cm) fat-poor angiomyolipoma from renal cell carcinoma: a multiple quantitative tool

PURPOSE

This study aimed to evaluate the diagnostic value of serum and CT factors to establish a convenient diagnostic method for differentiating small (≤ 4 cm) fat-poor angiomyolipoma (AML) from renal cell carcinoma (RCC).

MATERIALS AND METHODS

This study analyzed the preoperative serum laboratory data and CT data of 32 fat-poor AML patients and 133 RCC patients. The CT attenuation value of tumor (AVT), relative enhancement ratio (RER), and heterogeneous degree of tumor were detected using region of interest on precontrast phase (PCP) and the corticomedullary phase. Multivariate regression was performed to filter the main factors. The main factors were selected to establish the prediction models. The area under the curve (AUC) was measured to evaluate the diagnostic efficacy.

RESULTS

Fat-poor AML was more common found in younger (47.91 ± 2.09 years vs 53.63 ± 1.17 years, P = 0.02) and female (70.68 vs 28.13%, P < 0.001) patients. Alkaline phosphatase (ALP) was higher in RCC patients (81.80 ± 1.75 vs 63.25 ± 2.95 U/L, P < 0.01). For CT factors, fat-poor AML was higher in PCP_AVT (40.30 ± 1.49 vs 32.98 ± 0.69Hu, P < 0.01) but lower in RER (67.17 ± 3.17 vs 84.64 ± 2.73, P < 0.01). Gender, ALP, PCP_AVT and RER was found valuable for the differentiation. When compared with laboratory-based or CT-based diagnostic models, the combination model integrating gender, ALP, PCP_AVT and RER shows the best diagnostic performance (AUC = 0.922).

CONCLUSION

ALP was found higher in RCC patients. Female patients with ALP < 70.50U/L, PCP_AVT > 35.97Hu and RER < 82.66 are more likely to be diagnose as fat-poor AML.

Dual targeting with 224Ra/212Pb-conjugates for targeted alpha therapy of disseminated cancers: A conceptual approach

Metastases are the primary cause of death among cancer patients and efficacious new treatments are sorely needed. Targeted alpha-emitting radiopharmaceuticals that are highly cytotoxic may fulfill this critical need. The focus of this paper is to describe and explore a novel technology that may improve the therapeutic effect of targeted alpha therapy by combining two radionuclides from the same decay chain in the same solution. We hypothesize that the dual targeting solution containing bone-seeking 224Ra and cell-directed complexes of progeny 212Pb is a promising approach to treat metastatic cancers with bone and soft tissue lesions as well as skeletal metastases of mixed lytic/osteoblastic nature. A novel liquid 224Ra/212Pb-generator for rapid preparation of a dual targeting solution is described. Cancer cell targeting monoclonal antibodies, their fragments, synthetic proteins or peptides can all be radiolabeled with 212Pb in the 224Ra-solution in transient equilibrium with daughter nuclides. Thus, 224Ra targets stromal elements in sclerotic bone metastases and 212Pb-chelated-conjugate targets tumor cells of metastatic prostate cancer or osteosarcoma. The dual targeting solution may also be explored to treat metastatic breast cancer or multiple myeloma after manipulation of bone metastases to a more osteoblastic phenotype by the use of bisphosphonates, denosumab, bortezomib or hormone therapy prior to treatment. This may improve targeting of bone-seeking 224Ra and render an augmented radiation dose deposited within metastases. Our preliminary preclinical studies provide conceptual evidence that the dual 224Ra-solution with bone or tumor-targeted delivery of 212Pb has potential to inhibit cancer metastases without significant toxicity. In some settings, the use of a booster dose of purified 212Pb-conjugate alone could be required to elevate the effect of this tumor cell directed component, if needed, e.g., in a fractionated treatment regimen, where the dual targeting solution will act as maintenance treatment.

The novel m6A writer METTL5 as prognostic biomarker probably associating with the regulation of immune microenvironment in kidney cancer

Nowadays, among all urinary system cancers, the mortality of kidney cancer (KC) has risen to the first, and the incidence has been keeping on the third. Many recent studies have demonstrated that m6A modification regulated by the methyltransferases (writers) is closely related to the tumorigenesis of multiple cancers. In our previous study, we found that the methyltransferase METTL5 had a stronger association with the hazard ratio of KC more than most tumors, indicating its special function in carcinogenesis of KC. Until now, the expression, functions and mechanism of METTL5 in KC are still unclear. In this study, we analyzed the mRNA expression of METTL5 using the data sets from public databases, and revealed that the METTL5 expression was significantly up-regulated in tumor tissues of kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) compared to normal tissues. Also, the METTL5 expression was correlated with the tumor stage and grade, indicating the potential involvement of METTL5 in tumor progression. Additionally, the higher expression of METTL5 predicted poorer prognosis of KIRC and KIRP patients. Subsequently, we revealed that the functions of METTL5 in KIRC might be related to immune modulation, because its co-expressed gene were enriched in immune-relevant pathways including Th17 cell differentiation, Th1 and Th2 cell differentiation, and phosphatidylinositol 3-kinase activity. Next, we disclosed that the METTL5 expression was correlated to the microenvironment score and immune score of KIRC and KIRP, and associated with the infiltration ratios of 25 types of immune cells. Besides, we demonstrated a wide difference of the METTL5's effect on the survival of patients with high and low immune infiltration, further suggesting METTL5 might affect tumor development via modulating the immune microenvironment. The findings of our study provide a novel potential prognostic biomarker and immune drug target for KC.

Ferroptosis-related gene signature predicts prognosis in kidney renal papillary cell carcinoma

Ferroptosis, an iron-dependent form of selective cell death, is involved in the development of many cancers. However, the role of ferroptosis-related genes (FRGs) in kidney renal papillary cell carcinoma (KIRP) is unclear. In this study, we examined the mRNA expression profiles and clinical data of patients with KIRP from the TCGA cohort. Consequently, 41 differentially-expressed FRGs were screened using the limma package, and 17 prognostic-related FRGs were identified by survival analysis and univariate Cox regression analyses. Thereafter, a ferroptosis-related gene prognostic index (FRGPI) was constructed based on five FRGs (AKR1C3, SAT1, FANCD2, HSBP1 and SQLE), using lasso Cox and multivariate Cox regression analyses. KIRP patients with high FRGPI scores displayed worse outcomes. Furthermore, the FRGPI was shown to be a reliable independent prognostic factor in both the training and testing cohorts. Comprehensive analysis also showed that the FRGPI can distinguish gene mutation, functional enrichment of immune cells and molecular function-related pathways. Interestingly, low FRGPI score could be more benefit from immune checkpoint inhibitors (ICIs) therapy. Then, the two hub prognostic genes (AKR1C3 and FANCD2) as a risk gene for KIRP were identified based on the FRGPI module, and the expression profiles of these two genes were validated using human KIRP cells, besides, we furthermore discovered that Fancd2 is significantly up-regulated in most cancers and is associated with prognosis. In conclusion, these findings showed that FRGPI can accurately predict the prognosis of patients with KIRP, suggesting that this risk model is a promising prognostic biomarker for these patients. Moreover, targeting ferroptosis (FANCD2) could be a potential therapeutic alternative for various cancers.

Establishment and Validation of a Machine Learning Prediction Model Based on Big Data for Predicting the Risk of Bone Metastasis in Renal Cell Carcinoma Patients

Purpose

Since the prognosis of renal cell carcinoma (RCC) patients with bone metastasis (BM) is poor, this study is aimed at using big data to build a machine learning (ML) model to predict the risk of BM in RCC patients.

Methods

A retrospective study was conducted on 40,355 RCC patients in the SEER database from 2010 to 2017. LASSO regression and multivariate logistic regression analysis was performed to determine independent risk factors of RCC-BM. Six ML algorithm models, including LR, GBM, XGB, RF, DT, and NBC, were used to establish risk models for predicting RCC-BM. The prediction performance of ML models was weighed by 10-fold cross-validation.

Results

The study investigated 40,355 patients diagnosed with RCC in the SEER database, where 1,811 (4.5%) were BM patients. Independent risk factors for BM were tumor grade, T stage, N stage, liver metastasis, lung metastasis, and brain metastasis. Among the RCC-BM risk prediction models established by six ML algorithms, the XGB model showed the best prediction performance (AUC = 0.891). Therefore, a network calculator based on the XGB model was established to individually assess the risk of BM in patients with RCC.

Conclusion

The XGB risk prediction model based on the ML algorithm performed a good prediction effect on BM in RCC patients.

A Novel Pyroptosis-Related Gene Signature for Predicting Prognosis in Kidney Renal Papillary Cell Carcinoma

Pyroptosis is defined as an inflammatory form of programmed cell death. Increasing studies have demonstrated that pyroptosis is closely related to tumor development and antitumor process. However, the role of pyroptosis in kidney renal papillary cell carcinoma (KIRP) remains obscure. In this study, we analyzed the expression of 52 pyroptosis-related genes (PRGs) in KIRP, of which 20 differentially expressed PRGs were identified between tumor and normal tissues. Consensus clustering analysis based on these PRGs was used to divided patients into two clusters, from which a significant difference in survival was found (p = 0.0041). The prognostic risk model based on six PRGs (CASP8, CASP9, CHMP2A, GPX4, IL6, and IRF1) was built using univariate Cox regression and LASSO–Cox regression analysis, with good performance in predicting one-, three-, and five-year overall survival. Kaplan–Meier survival analysis showed that the high-risk group had a poor survival outcome (p &lt; 0.001) and risk score was an independent prognostic factor (HR: 2.655, 95% CI 1.192–5.911, p = 0.016). Immune profiling revealed differences in immune cell infiltration between the two groups, and the infiltration of M2 macrophages was significantly upregulated in the tumor immune microenvironment, implying that tumor immunity participated in the KIRP progression. Finally, we identified two hub genes in tumor tissues (IL6 and CASP9), which were validated in vitro. In conclusion, we conducted a comprehensive analysis of PRGs in KIRP and tried to provide a pyroptosis-related signature for predicting the prognosis.