Targeting the Proteasome in Advanced Renal Cell Carcinoma: Complexity and Limitations of Patient-Individualized Preclinical Drug Discovery

Bortezomib advanced mechanisms of action in multiple myeloma, solid and liquid tumors along with its novel therapeutic applications

Bortezomib (BTZ) is a first-in-class reversible and selective proteasome inhibitor. It inhibits the ubiquitin proteasome pathway that leads to the degradation of many intracellular proteins. Initially, BTZ was FDA approved for the treatment of refractory or relapsed multiple myeloma (MM) in 2003. Later, its usage was approved for patients with previously untreated MM. In 2006, BTZ was approved for the treatment of relapsed or refractory Mantle Cell Lymphoma (MCL) and, in 2014, for previously untreated MCL. BTZ has been extensively studied either alone or in combination with other drugs for the treatment of different liquid tumors especially in MM. However, limited data evaluated the efficacy and safety of using BTZ in patients with solid tumors. In this review, we will discuss the advanced and novel mechanisms of action of BTZ documented in MM, solid tumors and liquid tumors. Moreover, we will shed the light on the newly discovered pharmacological effects of BTZ in other prevalent diseases.

Complexity in radiological morphology predicts worse prognosis and is associated with an increase in proteasome component levels in clear cell renal cell carcinoma

Background

We previously reported preoperative radiological morphology (RM) as an independent predictor for pathological upstaging after partial nephrectomy in patients with T1 renal cell carcinoma (RCC).

Purpose

To investigate the prognostic importance of RM in all stages and the molecular characteristics underlying the differences between each type of RM in patients with clear cell RCC (ccRCC).

Design setting and participants

The Cancer Imaging Archive datasets (TCIA), comprising CT images and RNA-sequencing data, were used (n = 163). Specimens from 63 patients with ccRCC at our institution and their CT images were used. All images were divided into three types according to RM classification.

Outcome measurements and statistical analysis

Relationships with outcome were analyzed using Cox regression analysis and log-rank test.

Results and limitations

The irregular type was a significant independent predictor of worse disease-free survival (odds ratio: 2.22, p = 0.037) compared to round and lobular types in TCIA datasets. The irregular type showed a significant increase in both mRNA and protein expression of proteasome components, PSMB1 and PSMB3. Moreover, high expression of their coding genes shortened the progression-free survival of the patients with ccRCC who received sunitinib or avelumab plus axitinib therapy. The study limitations include the qualitative classification of RM and the need for novel radiomics and texture analysis techniques.

Conclusions

Investigating RM on pre-treatment CT scans can effectively predict worse prognosis. Increased RM complexity may indirectly predict drug sensitivity via increased expression of PSMB1 and PSMB3 in patients with ccRCC. Specific targeting of the ubiquitin-proteasome system might be a novel treatment strategy for ccRCC with increased RM complexity.

Patient summary

The clinical and morphological characteristics of patients with ccRCC vary greatly according to cancer staging. In this study, we built upon our prior findings of the prognostic importance of RM in T1 RCC and expanded it to encompass all stages of RCC, using a series of patients from a Japanese hospital.

New Therapeutic Interventions for Kidney Carcinoma: Looking to the Future

Simple Summary

Renal cell carcinoma (RCC) in metastatic form is a lethal pathology difficult to treat; therefore, the research of new therapeutic options for the treatment of metastatic patients is crucial to improve quality of life and overall survival. Recently, new signaling pathways and biological processes involved in cancer development and progression by scientific research community have been identified. These components including factors affecting angiogenesis, cell migration and invasion, autophagy and ferroptosis that are dysregulated in kidney cancer represent novel possible target molecules. In this work, we discuss current and new therapies for kidney cancer treatment; in particular, agents targeting new molecules involved in renal carcinogenesis that in future might become more powerful drugs for the cure of metastatic RCC.

Abstract

Patients suffering from metastatic renal cell carcinoma (mRCC) show an overall survival rate of lower than 10% after 5 years from diagnosis. Currently, the first-line treatment for mRCC patients is based on antiangiogenic drugs that are able to inhibit tyrosine kinase receptors (TKI) in combination with immuno-oncology (IO) therapy or IO-IO treatments. Second-line therapy involves the use of other TKIs, immunotherapeutic drugs, and mTOR inhibitors. Nevertheless, many patients treated with mTOR and TK inhibitors acquire drug resistance, making the therapy ineffective. Therefore, the research of new therapeutic targets is crucial for improving the overall survival and quality of life of mRCC patients. The investigation of the molecular basis of RCC, especially in clear cell renal cell carcinoma (ccRCC), has led to the identification of different signaling pathways that are involved in renal carcinogenesis. Most of ccRCCs are associated with mutation in VHL gene, which mediates the degradation of hypoxia-inducible factors (HIFs), that, in turn, regulate the pathways related to tumorigenesis, including angiogenesis and invasion. Renal tumorigenesis is also associated with the activation of tyrosine kinases that modulate the PI3K-Akt-mTOR pathway, promoting cell proliferation and survival. In ccRCC, the abnormal activity of mTOR activates the MDM2 protein, which leads to the degradation of tumor suppressor p53 via proteasome machinery. In addition, p53 may be degraded by autophagy in a mechanism involving the enzyme transglutaminase 2 (TG2). Suppression of wild-type p53 promotes cell growth, invasion, and drug resistance. Finally, the activation of ferroptosis appears to inhibit cancer progression in RCC. In conclusion, these pathways might represent new therapeutic targets for mRCC.

Kidney Cancer Models for Pre-Clinical Drug Discovery: Challenges and Opportunities

Renal cell carcinoma (RCC) is among the most lethal urological malignancies once metastatic. The introduction of immune checkpoint inhibitors has revolutionized the therapeutic landscape of metastatic RCC, nevertheless, a significant proportion of patients will experience disease progression. Novel treatment options are therefore still needed and in vitro and in vivo model systems are crucial to ultimately improve disease control. At the same time, RCC is characterized by a number of molecular and functional peculiarities that have the potential to limit the utility of pre-clinical model systems. This includes not only the well-known genomic intratumoral heterogeneity (ITH) of RCC but also a remarkable functional ITH that can be shaped by influences of the tumor microenvironment. Importantly, RCC is among the tumor entities, in which a high number of intratumoral cytotoxic T cells is associated with a poor prognosis. In fact, many of these T cells are exhausted, which represents a major challenge for modeling tumor-immune cell interactions. Lastly, pre-clinical drug development commonly relies on using phenotypic screening of 2D or 3D RCC cell culture models, however, the problem of “reverse engineering” can prevent the identification of the precise mode of action of drug candidates thus impeding their translation to the clinic. In conclusion, a holistic approach to model the complex “ecosystem RCC” will likely require not only a combination of model systems but also an integration of concepts and methods using artificial intelligence to further improve pre-clinical drug discovery.

Bioinformatic Analysis Identifying PSMB 1/2/3/4/6/8/9/10 as Prognostic Indicators in Clear Cell Renal Cell Carcinoma

Renal cancer incidence has been increasing across the world, clear cell renal cell carcinoma (ccRCC) represents the major subtype of renal cancer. The proteasome is involved in onset, metabolism and survival of tumor and has been recognized as a therapeutic target for various malignancies, while the role of β subunits of proteasome, PSMB gene family, in ccRCC has not been fully unveiled. Herein we investigated the expression and the prognostic role of PSMBs in ccRCC by analyzing a series of databases, including ONCOMINE, UALCAN, cBioPortal, STRING, GEPIA, GO and KEGG. Over-expressions of PSMB1/2/4/7/8/9/10 mRNA were found in ccRCC tissues compared to normal tissues, transcriptional levels of PSMB2/3/4/6/8/9/10 were significantly positively associated with patients' individual cancer stages and grades. Similar or higher levels of proteins encoded by PSMB1/2/3/7/8/9/10 were observed in tumor tissues compared to normal renal tissues. Further, high mRNA levels of PSMB1/2/3/4/6/10 were correlated with shorter overall survival in univariate analysis. Taken together, the results of our analysis implied that overexpression of PSMB1/2/3/4/6/8/9/10 were indicative of worse prognosis of ccRCC. However, further researches were required to validate our findings.

Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer

The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan–Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.