Optimized Combination of HDACI and TKI Efficiently Inhibits Metabolic Activity in Renal Cell Carcinoma and Overcomes Sunitinib Resistance

Getting the right combination to break the epigenetic code

Rapid advances in the field of epigenetics have facilitated the development of novel therapeutics targeting epigenetic mechanisms that are hijacked by cancer cells to support tumour growth and progression. Several epigenetic agents have been approved by the FDA for the treatment of cancer; however, the efficacy of these drugs is dependent on the underlying biology and drivers of the disease, with inherent differences between solid tumours and haematological malignancies. The efficacy of epigenetic drugs as single agents remains limited across most cancer types, which has spurred the clinical development of combination therapies, with the hope of attaining synergistic activity and/or overcoming treatment resistance. In this Review we discuss clinical advances that have been achieved with the use of epigenetic agents in combination with chemotherapies, immunotherapies or other targeted agents, including epigenetic-epigenetic combinations, as well as limitations and challenges associated with these combinatorial strategies. So far, the success of combination therapies targeting epigenetic mechanisms has generally been confined to haematological malignancies, with limited efficacy observed in patients with solid tumours. Nevertheless, this Review captures the field of epigenetic combination therapies across the spectra of haematology and oncology, highlighting opportunities for precision therapy to effectively harness the potential of epigenetic agents and produce meaningful improvements in clinical outcomes.

Von Hippel-Lindau protein signalling in clear cell renal cell carcinoma

The distinct pathological and molecular features of kidney cancer in adaptation to oxygen homeostasis render this malignancy an attractive model for investigating hypoxia signalling and potentially developing potent targeted therapies. Hypoxia signalling has a pivotal role in kidney cancer, particularly within the most prevalent subtype, known as renal cell carcinoma (RCC). Hypoxia promotes various crucial pathological processes, such as hypoxia-inducible factor (HIF) activation, angiogenesis, proliferation, metabolic reprogramming and drug resistance, all of which contribute to kidney cancer development, growth or metastasis formation. A substantial portion of kidney cancers, in particular clear cell RCC (ccRCC), are characterized by a loss of function of Von Hippel-Lindau tumour suppressor (VHL), leading to the accumulation of HIF proteins, especially HIF2α, a crucial driver of ccRCC. Thus, therapeutic strategies targeting pVHL-HIF signalling have been explored in ccRCC, culminating in the successful development of HIF2α-specific antagonists such as belzutifan (PT2977), an FDA-approved drug to treat VHL-associated diseases including advanced-stage ccRCC. An increased understanding of hypoxia signalling in kidney cancer came from the discovery of novel VHL protein (pVHL) targets, and mechanisms of synthetic lethality with VHL mutations. These breakthroughs can pave the way for the development of innovative and potent combination therapies in kidney cancer.

HDAC8 Enhances the Function of HIF-2α by Deacetylating ETS1 to Decrease the Sensitivity of TKIs in ccRCC

Drug resistance after long-term use of Tyrosine kinase inhibitors (TKIs) has become an obstacle for prolonging the survival time of patients with clear cell renal cell carcinoma (ccRCC). Here, genome-wide CRISPR-based screening to reveal that HDAC8 is involved in decreasing the sensitivity of ccRCC cells to sunitinib is applied. Mechanically, HDAC8 deacetylated ETS1 at the K245 site to promote the interaction between ETS1 and HIF-2α and enhance the transcriptional activity of the ETS1/HIF-2α complex. However, the antitumor effect of inhibiting HDAC8 on sensitized TKI is not very satisfactory. Subsequently, inhibition of HDAC8 increased the expression of NEK1, and up-regulated NEK1 phosphorylated ETS1 at the T241 site to promote the interaction between ETS1 and HIF-2α by impeded acetylation at ETS1-K245 site is showed. Moreover, TKI treatment increased the expression of HDAC8 by inhibiting STAT3 phosphorylation in ccRCC cells is also found. These 2 findings highlight a potential mechanism of acquired resistance to TKIs and HDAC8 inhibitors in ccRCC. Finally, HDAC8-in-PROTACs to optimize the effects of HDAC8 inhibitors through degrading HDAC8 and overcoming the resistance of ccRCC to TKIs are synthesized. Collectively, the results revealed HDAC8 as a potential therapeutic candidate for resistance to ccRCC-targeted therapies.

Proteomics analysis of histone deacetylase inhibitor-resistant solid tumors reveals resistant signatures and potential drug combinations

Histone deacetylase inhibitors (HDACis) are important drugs for cancer therapy, but the indistinct resistant mechanisms of solid tumor therapy greatly limit their clinical application. In this study we conducted HDACi-perturbated proteomics and phosphoproteomics analyses in HDACi-sensitive and -resistant cell lines using a tandem mass tag (TMT)-based quantitative proteomic strategy. We found that the ribosome biogenesis proteins MRTO4, PES1, WDR74 and NOP16 vital to tumorigenesis might regulate the tumor sensitivity to HDACi. By integrating HDACi-perturbated protein signature with previously reported proteomics and drug sensitivity data, we predicted and validated a series of drug combination pairs potentially to enhance the sensitivity of HDACi in diverse solid tumor. Functional phosphoproteomic analysis further identified the kinase PDK1 and ROCK as potential HDACi-resistant signatures. Overall, this study reveals the potential HDACi-resistant signatures and may provide promising drug combination strategies to attenuate the resistance of solid tumor to HDACi.

Resveratrol affects ccRCC cell senescence and macrophage polarization by regulating the stability of CCNB1 by RBM15

Aim: The present study sought to investigate the therapeutic effect of resveratrol on clear cell renal cell carcinoma. Materials & methods: Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine assays were used to verify the cell proliferation. Transwell, real-time quantitative transcription PCR, western blot and β-galactosidase staining were used to verify the migration, macrophage polarization and senescence. The tumor inhibitory effect of resveratrol on clear cell renal cell carcinoma was verified in vivo. Results: This study confirmed that resveratrol could affect the stability of CCNB1 mRNA mediated by RBM15 and inhibit the cancer process by inhibiting the expression of EP300/CBP from the perspective of cell senescence. Conclusion: Resveratrol is able to treat clear cell renal cell carcinoma through RBM15-induced cell senescence.

Advanced in vitro models for renal cell carcinoma therapy design

Renal cell carcinoma (RCC) and its principal subtype, clear cell RCC, are the most diagnosed kidney cancer. Despite substantial improvement over the last decades, current pharmacological intervention still fails to achieve long-term therapeutic success. RCC is characterized by a high intra- and inter-tumoral heterogeneity and is heavily influenced by the crosstalk of the cells composing the tumor microenvironment, such as cancer-associated fibroblasts, endothelial cells and immune cells. Moreover, multiple physicochemical properties such as pH, interstitial pressure or oxygenation may also play an important role. These elements are often poorly recapitulated in in vitro models used for drug development. This inadequate recapitulation of the tumor is partially responsible for the current lack of an effective and curative treatment. Therefore, there are needs for more complex in vitro or ex vivo drug screening models. In this review, we discuss the current state-of-the-art of RCC models and suggest strategies for their further development.

Identification of novel and potent dual-targeting HDAC1/SPOP inhibitors using structure-based virtual screening, molecular dynamics simulation and evaluation of in vitro and in vivo antitumor activity

Cancer is one of the important factors threatening human health. Hence, it is essential to create novel potent drugs to treat it. Due to the strong correlation among histone deacetylase1 (HDAC1), speckle-type POZ protein (SPOP) and cancers, dual inhibition of HDAC1 and SPOP may be a promising strategy for cancer treatment. In this study, we successfully identified four potential dual-targeting HDAC1/SPOP candidate compounds with structure-based virtual screening. In vitro inhibition experiments confirmed that the four compounds had dual inhibitory effects on HDAC1 and SPOP. Among them, compound HS-2 had a stronger inhibitory effect on HDAC1 and SPOP than the positive controls. Further molecular dynamics simulations indicated that HS-2 could stably bind to HDAC1 and SPOP. In addition, MTT assay indicated that HS-2 inhibited the growth of tumor cells in the micromolar range. In vivo evaluation showed that HS-2 could obviously inhibit the growth of tumor in nude mice without obvious toxicity. These findings suggest that HS-2 is a novel and potent dual-targeting HDAC1/SPOP inhibitor for cancer treatment.

Platform combining statistical modeling and patient-derived organoids to facilitate personalized treatment of colorectal carcinoma

BACKGROUND

We propose a new approach for designing personalized treatment for colorectal cancer (CRC) patients, by combining ex vivo organoid efficacy testing with mathematical modeling of the results.

METHODS

The validated phenotypic approach called Therapeutically Guided Multidrug Optimization (TGMO) was used to identify four low-dose synergistic optimized drug combinations (ODC) in 3D human CRC models of cells that are either sensitive or resistant to first-line CRC chemotherapy (FOLFOXIRI). Our findings were obtained using second order linear regression and adaptive lasso.

RESULTS

The activity of all ODCs was validated on patient-derived organoids (PDO) from cases with either primary or metastatic CRC. The CRC material was molecularly characterized using whole-exome sequencing and RNAseq. In PDO from patients with liver metastases (stage IV) identified as CMS4/CRIS-A, our ODCs consisting of regorafenib [1 mM], vemurafenib [11 mM], palbociclib [1 mM] and lapatinib [0.5 mM] inhibited cell viability up to 88%, which significantly outperforms FOLFOXIRI administered at clinical doses. Furthermore, we identified patient-specific TGMO-based ODCs that outperform the efficacy of the current chemotherapy standard of care, FOLFOXIRI.

CONCLUSIONS

Our approach allows the optimization of patient-tailored synergistic multi-drug combinations within a clinically relevant timeframe.

Network-informed discovery of multidrug combinations for ERα+/HER2-/PI3Kα-mutant breast cancer

Breast cancer is a persistent threat to women worldwide. A large proportion of breast cancers are dependent on the estrogen receptor α (ERα) for tumor progression. Therefore, targeting ERα with antagonists, such as tamoxifen, or estrogen deprivation by aromatase inhibitors remain standard therapies for ERα + breast cancer. The clinical benefits of monotherapy are often counterbalanced by off-target toxicity and development of resistance. Combinations of more than two drugs might be of great therapeutic value to prevent resistance, and to reduce doses, and hence, decrease toxicity. We mined data from the literature and public repositories to construct a network of potential drug targets for synergistic multidrug combinations. With 9 drugs, we performed a phenotypic combinatorial screen with ERα + breast cancer cell lines. We identified two optimized low-dose combinations of 3 and 4 drugs of high therapeutic relevance to the frequent ERα + /HER2-/PI3Kα-mutant subtype of breast cancer. The 3-drug combination targets ERα in combination with PI3Kα and cyclin-dependent kinase inhibitor 1 (p21). In addition, the 4-drug combination contains an inhibitor for poly (ADP-ribose) polymerase 1 (PARP1), which showed benefits in long-term treatments. Moreover, we validated the efficacy of the combinations in tamoxifen-resistant cell lines, patient-derived organoids, and xenograft experiments. Thus, we propose multidrug combinations that have the potential to overcome the standard issues of current monotherapies.

Molecular mechanisms of resistance to tyrosine kinase inhibitor in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Loss of von Hippel-Lindau tumor suppressor gene is frequently observed in ccRCC and increases the expression of hypoxia-inducible factors and their targets, including epidermal growth factor, vascular endothelial growth factor, and platelet-derived growth factor. Tyrosine kinase inhibitors (TKIs) offer a survival benefit in metastatic renal cell carcinoma (mRCC). Recently, immune checkpoint inhibitors have been introduced in mRCC. Combination therapy with TKIs and immune checkpoint inhibitors significantly improved patient outcomes. Therefore, TKIs still play an essential role in mRCC treatment. However, the clinical utility of TKIs is compromised when primary and acquired resistance are encountered. The mechanism of resistance to TKI is not fully elucidated. Here, we comprehensively reviewed the molecular mechanisms of resistance to TKIs and a potential strategy to overcome this resistance. We outlined the involvement of angiogenesis, non-angiogenesis, epithelial-mesenchymal transition, activating bypass pathways, lysosomal sequestration, non-coding RNAs, epigenetic modifications and tumor microenvironment factors in the resistance to TKIs. Deep insight into the molecular mechanisms of resistance to TKIs will help to better understand the biology of RCC and can ultimately help in the development of more effective therapies.

Endoplasmic Reticulum Stress-Related Signature Predicts Prognosis and Drug Response in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. The maximum number of deaths associated with kidney cancer can be attributed to ccRCC. Disruption of cellular proteostasis results in endoplasmic reticulum (ER) stress, which is associated with various aspects of cancer. It is noteworthy that the role of ER stress in the progression of ccRCC remains unclear. We classified 526 ccRCC samples identified from the TCGA database into the C1 and C2 subtypes by consensus clustering of the 295 ER stress-related genes. The ccRCC samples belonging to subtype C2 were in their advanced tumor stage and grade. These samples were characterized by poor prognosis and malignancy immune microenvironment. The upregulation of the inhibitory immune checkpoint gene expression and unique drug sensitivity were also observed. The differentially expressed genes between the two clusters were explored. An 11-gene ER stress-related prognostic risk model was constructed following the LASSO regression and Cox regression analyses. In addition, a nomogram was constructed by integrating the clinical parameters and risk scores. The calibration curves, ROC curves, and DCA curves helped validate the accuracy of the prediction when both the TCGA dataset and the external E-MTAB-1980 dataset were considered. Moreover, we analyzed the differentially expressed genes common to the E-MTAB-1980 and TCGA datasets to screen out new therapeutic compounds. In summary, our study can potentially help in the comprehensive understanding of ER stress in ccRCC and serve as a reference for future studies on novel prognostic biomarkers and treatments.

Advances in Renal Cell Carcinoma Drug Resistance Models

Renal cell carcinoma (RCC) is the most common form of kidney cancer. Systemic therapy is the preferred method to eliminate residual cancer cells after surgery and prolong the survival of patients with inoperable RCC. A variety of molecular targeted and immunological therapies have been developed to improve the survival rate and prognosis of RCC patients based on their chemotherapy-resistant properties. However, owing to tumor heterogeneity and drug resistance, targeted and immunological therapies lack complete and durable anti-tumor responses; therefore, understanding the mechanisms of systemic therapy resistance and improving clinical curative effects in the treatment of RCC remain challenging. In vitro models with traditional RCC cell lines or primary cell culture, as well as in vivo models with cell or patient-derived xenografts, are used to explore the drug resistance mechanisms of RCC and screen new targeted therapeutic drugs. Here, we review the established methods and applications of in vivo and in vitro RCC drug resistance models, with the aim of improving our understanding of its resistance mechanisms, increasing the efficacy of combination medications, and providing a theoretical foundation for the development and application of new drugs, drug screening, and treatment guidelines for RCC patients.

Prediction of drug candidates for clear cell renal cell carcinoma using a systems biology-based drug repositioning approach

BACKGROUND

The response rates of the clinical chemotherapies are still low in clear cell renal cell carcinoma (ccRCC). Computational drug repositioning is a promising strategy to discover new uses for existing drugs to treat patients who cannot get benefits from clinical drugs.

METHODS

We proposed a systematic approach which included the target prediction based on the co-expression network analysis of transcriptomics profiles of ccRCC patients and drug repositioning for cancer treatment based on the analysis of shRNA- and drug-perturbed signature profiles of human kidney cell line.

FINDINGS

First, based on the gene co-expression network analysis, we identified two types of gene modules in ccRCC, which significantly enriched with unfavorable and favorable signatures indicating poor and good survival outcomes of patients, respectively. Then, we selected four genes, BUB1B, RRM2, ASF1B and CCNB2, as the potential drug targets based on the topology analysis of modules. Further, we repurposed three most effective drugs for each target by applying the proposed drug repositioning approach. Finally, we evaluated the effects of repurposed drugs using an in vitro model and observed that these drugs inhibited the protein levels of their corresponding target genes and cell viability.

INTERPRETATION

These findings proved the usefulness and efficiency of our approach to improve the drug repositioning researches for cancer treatment and precision medicine.

FUNDING

This study was funded by Knut and Alice Wallenberg Foundation and Bash Biotech Inc., San Diego, CA, USA.

Drug Repurposing to Identify a Synergistic High-Order Drug Combination to Treat Sunitinib-Resistant Renal Cell Carcinoma

Simple Summary

In this study, drug combination screening was used to design a multidrug combination consisting of repurposed drugs to treat sunitinib-resistant clear cell renal cell carcinoma. In the frame of this project, the multidrug combination has been optimized and validated and an insight into the mechanism of action is given. The multidrug combinations significantly altered the transcription of genes related to apoptosis and metabolic pathways. Further analysis of the metabolism revealed strong upregulation of the presence of sphingolipids after multidrug combination treatment. Final evaluation for translation of the multidrug combination in ex vivo organoid-like cultures demonstrated significant anti-cancer efficacy.

Abstract

Repurposed drugs have been evaluated for the management of clear cell renal cell carcinoma (ccRCC), but only a few have influenced the overall survival of patients with advanced disease. To combine repurposed non-oncology with oncological drugs, we applied our validated phenotypic method, which consisted of a reduced experimental part and data modeling. A synergistic optimized multidrug combination (ODC) was identified to significantly reduce the energy levels in cancer remaining inactive in non-cancerous cells. The ODC consisted of Rapta-C, erlotinib, metformin and parthenolide and low doses. Molecular and functional analysis of ODC revealed a loss of adhesiveness and induction of apoptosis. Gene-expression network analysis displayed significant alterations in the cellular metabolism, confirmed by LC-MS based metabolomic analysis, highlighting significant changes in the lipid classes. We used heterotypic in vitro 3D co-cultures and ex vivo organoids to validate the activity of the ODC, maintaining an efficacy of over 70%. Our results show that repurposed drugs can be combined to target cancer cells selectively with prominent activity. The strong impact on cell adherence and metabolism indicates a favorable mechanism of action of the ODC to treat ccRCC.

Molecular and Functional Analysis of Sunitinib-Resistance Induction in Human Renal Cell Carcinoma Cells

Resistance in clear cell renal cell carcinoma (ccRCC) against sunitinib is a multifaceted process encompassing numerous molecular aberrations. This induces clinical complications, reducing the treatment success. Understanding these aberrations helps us to select an adapted treatment strategy that surpasses resistance mechanisms, reverting the treatment insensitivity. In this regard, we investigated the dominant mechanisms of resistance to sunitinib and validated an optimized multidrug combination to overcome this resistance. Human ccRCC cells were exposed to single or chronic treatment with sunitinib to obtain three resistant clones. Upon manifestation of sunitinib resistance, morphometric changes in the cells were observed. At the molecular level, the production of cell membrane and extracellular matrix components, chemotaxis, and cell cycle progression were dysregulated. Molecules enforcing the cell cycle progression, i.e., cyclin A, B1, and E, were upregulated. Mass spectrometry analysis revealed the intra- and extracellular presence of N-desethyl sunitinib, the active metabolite. Lysosomal sequestration of sunitinib was confirmed. After treatment with a synergistic optimized drug combination, the cell metabolic activity in Caki-1-sunitinib-resistant cells and 3D heterotypic co-cultures was reduced by >80%, remaining inactive in non-cancerous cells. These results demonstrate geno- and phenotypic changes in response to sunitinib treatment upon resistance induction. Mimicking resistance in the laboratory served as a platform to study drug responses.

Challenges and advances for the treatment of renal cancer patients with brain metastases: From immunological background to upcoming clinical evidence on immune-checkpoint inhibitors

The introduction of checkpoint inhibitors (ICIs) in renal cell carcinoma (RCC) treatment landscape, resulted in improvements in overall survival (OS) in metastatic patients. Brain metastases (BMs) are a specific metastatic site of interest representing a predictive factor of poor prognosis. Patients with BMs were usually excluded from prospective clinical trials in the past. Despite recent evidence suggest the efficacy and safety of ICIs, the BMs treatment remains a challenge; the immunotherapy responsiveness seems to be multifactorial and dependent on several factors, such as the genetic intratumor heterogeneity and the immunosuppressive role of the brain tumor microenvironment. This review, starting from the immunological background in RCC BMs, provide an overview of the upcoming evidence from clinical trials, address the issues related to the neuroradiological immunotherapy response evaluation and, with a look to the future, describes how the epigenetic modulation of immune evasion could represent a background for new therapeutic strategies.

Forcing dividing cancer cells to die; low-dose drug combinations to prevent spindle pole clustering

Mitosis, under the control of the microtubule-based mitotic spindle, is an attractive target for anti-cancer treatments, as cancer cells undergo frequent and uncontrolled cell divisions. Microtubule targeting agents that disrupt mitosis or single molecule inhibitors of mitotic kinases or microtubule motors kill cancer cells with a high efficacy. These treatments have, nevertheless, severe disadvantages: they also target frequently dividing healthy tissues, such as the haematopoietic system, and they often lose their efficacy due to primary or acquired resistance mechanisms. An alternative target that has emerged in dividing cancer cells is their ability to "cluster" the poles of the mitotic spindle into a bipolar configuration. This mechanism is necessary for the specific survival of cancer cells that tend to form multipolar spindles due to the frequent presence of abnormal centrosome numbers or other spindle defects. Here we discuss the recent development of combinatorial treatments targeting spindle pole clustering that specifically target cancer cells bearing aberrant centrosome numbers and that have the potential to avoid resistance mechanism due their combinatorial nature.

Characterization of Renal Cell Carcinoma Heterotypic 3D Co-Cultures with Immune Cell Subsets

Two-dimensional cell culture-based platforms are easy and reproducible, however, they do not resemble the heterotypic cell-cell interactions or the complex tumor microenvironment. These parameters influence the treatment response and the cancer cell fate. Platforms to study the efficacy of anti-cancer treatments and their impact on the tumor microenvironment are currently being developed. In this study, we established robust, reproducible, and easy-to-use short-term spheroid cultures to mimic clear cell renal cell carcinoma (ccRCC). These 3D co-cultures included human endothelial cells, fibroblasts, immune cell subsets, and ccRCC cell lines, both parental and sunitinib-resistant. During spheroid formation, cells induce the production and secretion of the extracellular matrix. We monitored immune cell infiltration, surface protein expression, and the response to a treatment showing that the immune cells infiltrated the spheroid co-cultures within 6 h. Treatment with an optimized drug combination or the small molecule-based targeted drug sunitinib increased immune cell infiltration significantly. Assessing the therapeutic potential of this drug combination in this platform, we revealed that the expression of PD-L1 increased in 3D co-cultures. The cost- and time-effective establishment of our 3D co-culture model and its application as a pre-clinical drug screening platform can facilitate the treatment validation and clinical translation.