Mouse models have been the workhorses of preclinical immuno-oncology (IO) research, and advances in mouse model development have expanded to applications for nearly all types of solid tumors and hematological malignancies. Preclinical evaluation of experimental immunotherapies has been advanced by syngeneic and humanized mouse models.
Mouse models have been the workhorses of preclinical immuno-oncology (IO) research, and advances in mouse model development have expanded to applications for nearly all types of solid tumors and hematological malignancies. Preclinical evaluation of experimental immunotherapies has been advanced by syngeneic and humanized mouse models. Syngeneic mice are one of the most established types of models used in cancer research, whereas humanized mice are a contemporary mouse model that has been critical to the screening of immunotherapeutic agents. Here we highlight features of syngeneic and humanized mouse models and define which models are most relevant to different phases of preclinical IO research.
Syngeneic Tumor Models
Syngeneic tumor models are created by transplantation of tumor cell lines into immunocompetent mice with the same genetic background as the cell line. Tumors can be transplanted intravenously or subcutaneously into mice and typically grow rapidly over several weeks. Different types of tumor cell lines can be used in this type of model, including spontaneous, transgenic, or carcinogen-induced tumor cell lines. Syngeneic mouse models are best suited for screening novel IO agents or gaining insight into anti-tumor responses in the context of an intact immune system. Given the rapid growth of tumors in syngeneic mice, these models are less well suited to studying early events in tumor growth associated with cancer stem cells or understanding the contributions of heterogeneous tumor microenvironments, and these models typically do not recapitulate the mutational heterogeneity observed in human tumors.
Humanized Tumor Models
Humanized tumor models are a more recent addition to preclinical IO research that provide valuable insight into how individual tumors from patients (xenografts) respond to experimental therapies. Prior to the development of humanized mouse models, human xenograft models were used for screening cytotoxic or immunotherapeutic agents like chimeric antigen receptor (CAR) T cells, and these models use human tumor cell lines or patient-derived specimens transplanted into immunocompromised host mice. Different immunocompromised models can be used, including athymic mice that lack T cells or severe combined immunodeficiency (SCID) models that lack all adaptive immune responses. Humanized mice have been engineered from immunocompromised mouse strains that include genetic mutations in other adaptive immune functions that allow for engraftment of human hematopoietic cells. The NOD/SCID IL2rγ chain knockout (NSG) mouse (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) is one of the most used combined immunodeficiency models that can be engrafted with human hematopoietic cells and primary human tumors. These patient-derived xenograft (PDX) models are useful for evaluated experimental IO therapies in the context of the human immune system and can use human immune cells from the same or different donor as the tumor source. PDX models are suited to evaluating experimental therapies in the context of a genetically heterogeneous tumor and better recapitulates aspects of the tumor microenvironment. Tumors can be grafted either orthotopically or subcutaneously and this also impacts how tumors grow and respond to experimental treatments. Given the heavily modified nature of the NSG immune system, these models do not always reflect responses observed in humans during clinical trials. Nonetheless, NSG mice and similarly modified humanized mice offer valuable insights into the efficacy of IO candidates.
Mouse models are constantly being refined and improved to better reflect human physiology. Both syngeneic and humanized mouse models serve as valuable tools to preclinical IO research and accelerate the screening and evaluation of novel therapeutics.
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DNA damage is one of the primary triggers of cancer development and has been linked to many types of cancers, including prostate, stomach, liver and skin cancers as well as leukemia. Within cells, the DNA sequence encodes all the instructions required for building proteins that are needed for cellular functions such as metabolism, replication, tissue and organ maintenance. The fidelity of the DNA sequence in a cell is maintained by multiple mechanisms but errors and mutations can occur, which sets off a chain of events that lead to tumor growth.
DNA damage can be caused by exogenous sources, such as UV radiation, chemical carcinogens, and infection with human papillomavirus or Helicobacter pylori. Endogenous DNA damage can also be caused by multiple factors, including unchecked metabolites like reactive oxygen species (ROS) and defects in DNA damage repair enzymes. Since DNA damage mechanisms have been known to cause numerous cancers, several drugs, particularly small molecule inhibitors, have been developed to target DNA repair pathways.
Improvements in animal models for cancer have revolutionized how anti-cancer drugs are evaluated and developed. Patient-derived xenograft (PDX) models have been particularly powerful tools since they use patient-derived tumor tissue engrafted into mice. Tumor cell lines, solid tumor tissue, or hematological tumors can be transplanted into immunodeficient mice. These immunocompromised mice can also be made to have “humanized” immune systems or express components of the human immune system, like immune checkpoint inhibitors, to better screen for the effectiveness of various anti-cancer treatments.
In this era of rapid, high-throughput DNA sequencing, individual tumors can be sequenced and specific defects in DNA damage repair pathways can be defined. This same tumor tissue can be engrafted into a PDX mouse model for screening of drugs or therapeutics that tackle the appropriate DNA damage repair defect. This approach is powerful for screening preclinical drug candidates for efficacy against a range of tumors and it also provides insights into potential off-target effects or toxicities. From the patient perspective, pre-screening potential treatment options in mice can lead to the selection of the most appropriate drug or therapeutic and helps avoid treatments that may be ineffective.
DNA damage events can lead to tumor growth and this area of research continues to inform drug development on the bench and patient care in the clinic.
Colorectal cancer (CRC) is a leading cause of cancer deaths globally. Advances in early detection have improved survival rates, but patients diagnosed with metastatic CRC still have stubbornly poor 5-year survival rates. Standard treatments for CRC include surgery, chemotherapy, and radiotherapy, but alternative immuno-oncology therapies are showing promising results in CRC patients. Here we highlight advances in immuno-oncology therapies that are being used to treat CRC patients or are being pursued in preclinical and clinical studies.
Molecular genetic analysis of CRC tumors is a critical diagnostic tool for classifying and treating this cancer. CRC tumors are typically classified as mismatch repair-deficient/microsatellite instability-high (dMMR—MSI-H) tumors, which have a high overall mutation burden, or mismatch repair-proficient/microsatellite instability-low (pMMR—MSI-L) tumors, which have a lower mutation burden. Defects in MMR are associated with the accumulation of mutations and are caused by defects in mismatch repair proteins, and these defects are typically detected by frame-shift mutations in DNA repeat regions known as microsatellites. Mutations in the BRAF oncogene, particularly the activating V600E mutation, comprise a distinct subset of CRC. BRAF is a component of the mitogen activated protein kinase (MAPK) pathway that normally functions downstream of the epidermal growth factor receptor to regulate transcription of genes involved in cellular growth and survival, but the BRAF-V600E mutation results in constitutive activation of BRAF and uncontrolled cellular proliferation and tumor growth.
Immuno-oncology approaches that target immune checkpoint blockade have proven effective for several cancers, including CRC. T cells can initiate effective anti-tumor responses under ideal conditions, but the immunosuppressive tumor microenvironment of some cancer types inhibits T cell activation, usually through engagement of immune checkpoint molecules like PD-1 and CTLA4. For more than a decade, the development and use of immune checkpoint inhibitors (ICIs) has transformed treatment of melanoma[3,4] and non-small cell lung cancer[5,6]. The first FDA-approved treatments include a monoclonal antibody (mAb) that targets CTLA4 (ipilimumab) and two mAbs that target PD-1 (pembrolizumab and nivolumab). These early studies suggested that tumors with high mutation burdens respond well to ICI, which may be due in part to the generation and presentation of tumor neoantigens that are recognized as non-self and can be targeted by cytotoxic T cells.
CRC tumors with the dMMR—MSI-H signature have a high mutational burden and typically have a high level CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs). These cells have shown elevated expression of PD-1, PD-L1 and CTLA4, which suggests that they may respond well to ICIs. Indeed, several recent clinical studies have shown improvements with overall survival and progression-free survival in patients treated with individual or combined ICIs that target PD-1. Of note, interim results from a phase II trial that enrolls patients with MMRd locally advanced rectal cancer to receive neoadjuvant dostarlimab, a PD-1 inhibitor, showed sustained complete response 1 year after the end of treatment in all patients. Other current studies are evaluating next-generation PD-1 inhibitors combined with chemotherapy and/or other biologics such as an anti-VEGF and anti-EGFR mAb.
In contrast, patients with pMMR–MSI-L have shown poor responses to PD-1 or CTLA4 blockade alone or in combination, which has led to the development of trials that explore different treatment combinations, including inhibitors of the MAPK pathway or angiogenesis. Promising results have been presented in a phase I/II clinical trial (NCT04017650) in which patients with MSI-L and BRAFV600E were treated with BRAF+EGFR inhibitors, to induce a transient MSI-H phenotype, plus anti-PD-1 antibody.
Next Generation Treatments
Several cutting-edge immuno-oncology therapies are being explored for the treatment of CRC. Beyond combinations of individual antibodies, researchers are engineering bispecific antibodies that bind to tumor cells and T cells simultaneously to enhance anti-tumor T cell responses. One such bispecific antibody, CEA-TCB, is being tested in phase I trials alone or in combination with anti-PD-L1 to treat metastatic CRC. Another novel approach includes adoptive cell therapies like chimeric antigen receptor (CAR) T cells, which are T cells collected from the tumor tissue or peripheral blood of a patient and engineered to bind to tumor antigens and potentiate anti-tumor responses. Oncolytic virus and bacteria-based vaccines are also being studied as potential CRC treatments.
Besides treatments designed on the tumor intrinsic genetic background, a lot of effort is being put to decipher tumor microenvironment, with particular focus on its interplay with the gut microbiota to modulate inflammation and immune response, known to be involved in the metastatic onset. These studies are leading to the identification of inflammatory/immune signatures that inform the therapeutic agents to be used to target the pro-oncogenic microenvironment and reactivate the immune system.
The advancement of immuno-oncology is already transforming the treatment of CRC and will contribute to better outcomes for all types of CRC in the decades to come.
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2. Bond CE, Whitehall VLJ. How the BRAF V600E mutation defines a distinct subgroup of colorectal cancer: molecular and clinical implications. Gastroenterol Res Pract. 2018; 2018:9250757.
3. Hodi FS, O'Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma [published correction appears in N Engl J Med. 2010 Sep 23;363(13):1290]. N Engl J Med. 2010;363(8):711-723.
4. Robert C, Long GV, Brady B, Dutriaux C, et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med. 2015 Jan 22;372(4):320-30.
5. Garon EB, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N. Engl. J. Med. 2015; 372:2018–2028.
6. Brahmer J, et al. Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N. Engl. J. Med. 2015; 373:123–135.
7. Rizvi NA, et al. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science. 2015; 348: 124-128.
8. Llosa NJ, et al. The vigorous immune microenvironment of microsatellite instable colon cancer is balanced by multiple counter-inhibitory checkpoints. Cancer Discovery. 2015; 43-51.
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Western blotting is a decades-old laboratory technique that is used to detect specific proteins from cell culture, tissue, or blood specimen. The term “western blot” is a twist on the Southern blotting method developed by Edwin Southern, which is used to detect DNA and shares methodological similarities with western blotting. The western blot method was first described by Harry Towbin in 1979 but the term “western blot” was coined by W. Neal Burnette in 1981,. Since its initial description, western blotting has been used in all fields of biological and biomedical research because it is a straightforward and robust method for detecting specific proteins. Here we provide an overview of the western blot method and highlight its current applications in preclinical oncology research.
Western Blot Basics
The western blot technique can be used to separate and identify a specific protein using three major steps: 1. Size separation using gel electrophoresis, 2. Transfer to a solid membrane, and 3. Detection with a specific antibody. Most western blot methods begin with a lysate of cells or tissue, which releases a mix of proteins that are separated by molecular weight using gel electrophoresis. Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) is the most common type of gel electrophoresis for western blotting and includes a protein denaturation step prior to gel electrophoresis such that proteins are separated by molecular weight. The SDS buffer causes proteins to become negatively charged so electrophoresis allows for migration of proteins from smallest to largest weight towards a positive charge. After gel electrophoresis, proteins are transferred to a solid membrane, usually polyvinylidene difluoride or nitrocellulose, using electroblotting or a slower alternative method based on capillary action. This membrane can now be probed with a primary antibody specific to a protein of interest and the primary antibody is visualized using a secondary antibody that recognizes a species-specific region of the primary antibody and is conjugated with a chemiluminescence substrate for visualization. Other less common visualization methods use colorimetric substrates or radioactive labels on secondary antibodies.
Western Blot and Preclinical Studies
Why is western blotting a method that is still used after more than forty years since its development? Western blotting remains a reliable, affordable, and practical method for detecting specific proteins. In preclinical oncology research, western blotting is used to validate high throughput single-cell RNA sequencing or proteomics methods that detect elevated proteins associated with specific cancers. Western blotting can also validate tissue microarray and immunohistochemistry findings with respect to specific proteins that are overexpressed in tumor tissue. Together these data can be used toward developing prognostic biomarkers for cancers, such as measuring overexpression of Kin of IRRE-like Protein 1 (KIRREL) in breast cancer and precancerous tissue. Western blotting is also a useful tool for understanding molecular mechanisms that drive cancer progression by measuring expression of critical proteins such as HMGB1, cyclins, and various oncogenes,.
Western blot has made a leap into the twenty-first century with advancements in process workflow and sensitivity using new platforms like ProteinSimple’s JESS System. Western blot will continue to be a workhorse for detecting and monitoring specific protein expression and continues to have broad applications in preclinical and clinical oncology studies related to understanding oncogenesis and defining potential tumor biomarkers.
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 Burnette WN. "Western blotting": electrophoretic transfer of proteins from sodium dodecyl sulfate--polyacrylamide gels to unmodified nitrocellulose and radiographic detection with antibody and radioiodinated protein A. Anal. Biochem. 1981 Apr;112(2):195-203.
 Meftahi GH, Bahari Z, Zarei Mahmoudabadi A, Iman M, Jangravi Z. Applications of western blot technique: From bench to bedside. Biochem. Mol. Biol. Educ. 2021 Jul;49(4):509-517.
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In vivo models for numerous diseases and conditions have endpoints that have involved animals being gravely ill or dying. As researchers have sought to utilize animal models in more humane and practical ways, surrogate endpoints have been developed that prevent animals from suffering and provide critical research data. Flow cytometry has been instrumental to these advances. Consider these aspects of preclinical flow cytometry endpoint analysis as you develop new protocols.
1. What are the immune system features of your disease state?
Flow cytometry provides the most useful data when the cell subsets of interest are well-defined and robust. You may need to analyze existing research literature or do pilot studies to define the immune cell subsets of interest for a particular disease state, be it changes in regulatory T cells in the tumor microenvironment, or the proliferation of plasmablasts in different leukemias. You must identify which profound changes in different cell populations are most closely correlated with morbidity and mortality in your animal model.
2. What is the desired treatment outcome?
Preclinical studies with surrogate endpoints are valuable for screening potential therapeutic candidates. These drugs or biologics may have undesirable off target effects as well. In designing a flow cytometry assay for alternative endpoints, it is critical to identify the changes in immune cell subsets that reflect therapeutic improvements or indicate potential toxicity or off target effects.
3. Can this be translated into a clinical flow cytometry protocol?In some disease models, particularly models using humanized mice, flow cytometry endpoints can be used in both preclinical screens and to evaluate clinical trial specimens. This consideration is valuable as protocols are developed and cell phenotypes are identified as predictors of good or poor prognoses.
Flow cytometry endpoint analysis not only advances the humane use of animal models but can be translated into informative clinical protocols that are critical for the evaluation of potential therapies.
Next-generation sequencing (NGS) technology has transformed the biomedical research landscape. Only a few years ago, high resolution genome or exome sequencing would be cumbersome and cost-restrictive, but current NGS technology platforms now allow for basic and clinical researchers to include these approaches for routine DNA and RNA sequencing needs. What are the different NGS sequencing approaches and how are they applied to oncology research?
1. Whole Genome Sequencing (WGS): NGS technology can be used for WGS of human genomes and tumor-specific genomes, as well as animal model and microbial genomes. WGS produces high resolution genomic sequences of expressed genomic regions as well as unexpressed regulatory regions. For preclinical oncology research, WGS is critical for characterizing genomic profiles associated with tumor progression or potential responsiveness to targeted drug therapies. WGS can detect single nucleotide variants, copy number variants, and insertions/deletions in tumor cells. The comprehensive scope of WGS makes it well suited for detecting mutations in both coding and non-coding regions. WGS is also useful for population level oncology studies that evaluate genetic susceptibility to specific cancers and potential heritability.
2. Whole Exome Sequencing (WES): WES techniques focus on sequencing the exome, which are comprised of protein expressing regions, or exons, within the genome. WES is an appropriate method for identifying genetic mutations that alter protein sequences, and WES data can be used toward measuring the tumor mutational burden (TMB) and predicting treatment efficacy. WES data can also be used to identify potential new drug targets or mechanisms of drug resistance.
3. Targeted Sequencing: This method focuses on defined gene regions and is typically used in diagnostic applications or for validation of WGS or WES results. Targeted sequencing works well for screening tumor samples for well characterized mutations, such as those associated with BCL2, BRCA-1/2, BRAF, and EGFR, and can be used for identifying appropriate targeted therapies.
4. RNA sequencing: RNA sequencing is now emerging as a powerful tool that complements NGS DNA methods because the transcriptional profile of a single cell can be measured and used to bridge genomic data with cellular phenotypes. Single-cell RNA sequencing (scRNA-seq) has specifically emerged as a powerful method for understanding the heterogeneity of cell populations within a tumor. Together with histological data, scRNA-seq data can be used to distinguish between neoplastic cells, immune cells, and healthy cells from the surrounding tissue, and it can also be used to evaluate how experimental treatments alter the tumor microenvironment.
NGS methods are transforming both basic oncology research and clinical care, from identifying novel mutations to pinpointing personalized cancer therapies. Each method is suited to specific applications, so working with experts in NGS technology is critical to method selection and data analysis.
1 Bewicke-Copley F et al. Applications and Analysis of Targeted Genomic Sequencing in Cancer Studies. Comput. Struct. Biotechnol. 2019;17: 1348-1359.
2 Nakagawa H, Fujita M. Whole Genome Sequencing Analysis for Cancer Genomics and Precision Medicine. Cancer Sci. 2018;109(3):513-522.
3 Rotunno M et al. A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer. Cancer Epidemiology and Prevention Biomarkers. 2020;29(8):1519-34.
4 Klempner SJ et al. Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence. Oncologist. 2020 Jan;25(1): e147-e159.
5 Beltran H et al. Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response. JAMA Oncol. 2015;1(4):466-474.
6 Vestergaard LK et al. Next Generation Sequencing Technology in the Clinic and Its Challenges. Cancers (Basel). 2021;13(8):1751.
7 Fan J et al. Single-Cell Transcriptomics in Cancer: Computational Challenges and Opportunities. Exp Mol Med. 2020; (52)1452–1465.
Importance of the Dataset
Sarcoma is a malignant tumor of the mesenchymal cells forming the connective tissue. Champions Oncology currently has 135 Sarcoma PDX models available to oncology pharmacology studies and drug development. Champions’ Sarcoma models represent several disease subtypes, both pediatric and adult, including Ewing Sarcoma, Leiomyosarcoma, Liposarcoma, Angiosarcoma, Synovial Sarcoma, and others. These models are well characterized with patient clinical annotations, disease status, treatment history, and in vivo and ex vivo drug responses to standard of care therapies, such as cisplatin, doxorubicin, docetaxel, ifosfamide, and many more. Champions’ Sarcoma model cohort encompass mutations in numerous key pathways including DNA repair, cell cycle, cell proliferation and invasion, and angiogenesis.
Each model included in this cohort was characterized by NGS sequencing (WES and RNA-Seq), proteomics and phospho-proteomics analyses. Our NGS workflow is a multi-step procedure; specifically, a primary sample undergoes preparation by thawing and subsequent extraction of gDNA and RNA. A library is then prepared and NGS sequencing (WES and RNA-Seq) is performed using Illumina Nextseq2000. Subsequently, raw data is collected, processed, and analyzed. The data must meet Champions’ Quality Control requirements, including sample QC, library QC and sequencing data QC. Finally, data is uploaded and stored in the user’s unique Lumin instance, where it can be visualized and further analyzed in various modules.
Champions has partnered with BGI Genomics to obtain proteomics and phospho-proteomics data; specifically, proteins are extracted from cells and/or tissues to obtain a protein mixture, which are broken down by digestion enzymes to yield a peptide mixture. This peptide mixture undergoes phospho-peptide enrichment to give a phospho-peptide mixture, which is then analyzed by LC/MS, using either data-dependent acquisition (DDA) or label-free data-independent acquisition (DIA) for data quantification.
Applications of the Dataset
The Sarcoma model cohort dataset has been integrated into our revolutionary visualization and data analytics software, Lumin Bioinformatics. With a Lumin Bioinformatics or Workspaces subscription, you can access multi-omic data from our Sarcoma model cohort.
The following modules can be used in Lumin Bioinformatics to access proteomics and phospho-proteomics data:
- Clustergrammer: Create hierarchical clustered heatmaps using gene expression, protein abundance, phosphorylation intensity or kinase activity. Users can also overlay %TGI values and mutation status for model cohorts.
- Molecular Graphing: Quickly create box plots to show protein abundance of your proteins of interest across different indications.
- Network Viewer: Within the network viewer, users can color protein nodes based on gene expression, mutational status, quantitative protein expression or include molecular signatures. This tool overlays proteomics data from Champions’ PDX models or the public CPTAC database. Users can then evaluate quantitative protein abundance, kinase activity and specific phosphorylation status across cancer types or within a defined tumor model.
- Mutation Mapper: Researchers can visualize protein amino acid domains and mutations identified within Champions' PDX models. Through Champions’ phospho-proteomic sequencing, phosphorylation sites identified within our tumor bank were detected, and are aligned within the context of protein amino acid domains. Users can also visualize phosphorylation sites detected within the public CPTAC database as well as those predicted by PhosphositePlus.
Watch our quick video to discover more about Champions’ Sarcoma Models in Lumin Bioinformatics:
Renal cell carcinoma (RCC) is a common cancer of the genitourinary tract that has very poor survival outcomes if metastatic. RCC is now understood to be composed of several different types of cancer with different genetic features and varied clinical responses. Histological diagnosis has been the primary method to diagnose RCC and has been used to define three major RCC subtypes, including the most common subtype, clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC; further divided into two subtypes), and chromophobe renal cell carcinoma (ChRCC). More recent comparative genomic and phenotypic analysis has identified mutations and epigenetic modifications associated with different histological subtypes. Across all subtypes, increased DNA hypermethylation and gene alterations in CDKN2A were associated with a poor prognosis as was an increased Th2 immune gene signature. For ccRCC, increased levels of mRNA transcripts associated with ribose metabolism and the immune response were associated with poor survival. ccRCC is also defined by the early loss of chromosome 3p, which in turn causes a loss of heterozygosity for the VHL, PBRM1, SETD2, and BAP1 tumor suppressor genes and subsequent mutation of these genes that leads to tumorigenesis. There is also a subset of ChRCC with a unique metabolic expression pattern that is associated with extremely poor survival2. PRCC can be classified as type 1, for which PBRM1 mutations are linked to poor survival but type 2 PRCC has increased expression of glycolysis and metabolism related mRNA transcripts2.
ccRCC tumors with VHL mutations show overexpression of vascular endothelial growth
factor (VEGF) and hypoxia-inducible factors (HIFs), which can contribute to angiogenesis and cancer progression. Similarly, some RCC show hyperactivation of the serine/threonine kinase mammalian target of rapamycin (mTOR), which can lead to overproduction of VEGF. VEGFR inhibitors and anti-VEGF antibodies have been tested as therapies for RCC, and the anti-VEGF antibody bevacizumab has been approved for use in combination with IFN-α for metastatic RCC. The mTOR inhibitors everolimus and temsirolimus have also been approved for the treatment of RCC, typically in combination with tyrosine kinase inhibitors (TKIs). Combination therapies that target VEGF and mTOR are considered more effective since they work in concert to target tumor growth and vascularization, whereas sequential treatments are typically associated with a greater likelihood of tumors developing resistance. Unfortunately, these combination therapies are associated with undesirable toxicities and have not been linked with durable responses.
Advances in immunotherapy have led to transformative treatment options for RCC. Immune checkpoint blockade (ICB) has been one promising treatment strategy, and the FDA approved the use of anti-PD-1/PD-L1 (nivolumab) for the treatment of advanced ccRCC in 2015. A follow up study showed that anti-PD-1 was associated with the best clinical benefit in ccRCC carrying loss-of-function mutations in PBRM1, which appears to affect tumor expression profiles in such a way to maintain responsiveness to checkpoint blockade. Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is another checkpoint molecule that has been targeted for checkpoint blockade with the monoclonal antibody ipilimumab. Similar to PD-L1 blockade, CTLA-4 blockade was associated with a partial response against metastatic RCC. Combination therapies have shown much more durable responses in patients with advanced RCC, and the FDA approved the use of nivolumab plus ipilimumab for the treatment of intermediate or high risk metastatic RCC in 2018. ICB blockade in combination with TKI are also under investigation as alternative first or second line treatments. Unfortunately, PD-1/PD-L1 blockade has been less successful for PRCC and ChRCC, and further studies are needed to identify therapeutic targets in these forms of RCC. Clinical studies with other checkpoint blockade targets are currently underway and are likely to provide new treatment options to RCC patients.
The future of RCC therapies relies on the identification of new molecules or pathways in tumor cells that can be targeted therapeutically without causing toxicity or promoting resistance. Advances in single-cell omics are leading the way in terms of target identification and understanding how different forms of RCC progress.
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 Hammers HJ, Plimack ER, Infante JR, Rini BI, McDermott DF, Lewis LD, Voss MH, Sharma P, Pal SK, Razak ARA, Kollmannsberger C, Heng DYC, Spratlin J, McHenry MB, Amin A. Safety and Efficacy of Nivolumab in Combination With Ipilimumab in Metastatic Renal Cell Carcinoma: The CheckMate 016 Study. J Clin Oncol. 2017 Dec 1;35(34):3851-3858.
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