Molecular Dissection of the Renal Cell Carcinoma Tumor Microenvironment for the Discovery of Novel Therapeutic Targets
Conditions: Renal Cell Carcinoma
Sponsor: University Health Network, Toronto

 
 
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Renal cell carcinoma microenvironment discovery project (REMEDY) 
 
 
CAPCR 17-5204 
 
 
NCT 04005183 
 
 

 
 
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Title:   
Renal cell carcinoma microenvironment discovery project 
 
 
Nickname:  REMEDY 
 
Investigators:   
 
Dr. Antonio Finelli (Principal Investigator) 
Associate Professor of Surgery 
Head, Division of Urology, University Health Network 
University of Toronto 
Antonio.Finelli@uhn.ca 
416-946-2851   
 
Dr. Masoom Haider 
Professor of Medical Imaging 
University of Toronto 
Haider.Masoom@sinaihealthsystem.ca 
416-480-6100, ext. 4341 
 
Dr. Adrian Sacher 
Assistant Professor of Medicine 
University of Toronto 
Adrian.Sacher@uhn.ca 
416-946-4501, ext. 3550 
 
Dr. Trevor Pugh  
Assistant Professor of Medical Biophysics 
University of Toronto 
trevor.pugh@utoronto.ca 
416-581-7689 
 
Dr. Laurie Ailles 
Associate Professor of Medical Biophysics 
University of Toronto 
laurie.ailles@uhnresearch.ca 
416-581-7868 
 
Dr. Gary Bader 
Professor of Molecular Genetics 
University of Toronto 
gary.bader@utoronto.ca 
416-978-6888 
 
 

 
 
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Dr. Kieran Campbell 
Assistant Professor of Molecular Genetics 
University of Toronto 
Lunenfeld-Tanenbaum Research Institute 
kierancampbell@lunenfeld.ca 
416-586-4800, ext. 5824 
 
Dr. Neil Fleshner 
Staff Urologist 
Princess Margaret Cancer Centre 
Neil.Fleshner@uhn.ca 
416-946-2899 
 
Dr. Girish Kulkarni  
Staff Urologist 
Assistant Professor University of Toronto, Department of Surgery 
Princess Margaret Cancer Centre 
Mount Sinai Hospital 
Toronto General Hospital 
Toronto Western Hospital 
Girish.Kulkarni@uhn.ca 
416-946-2246 
 
Dr. Nathan Perlis  
Staff Urologist 
Assistant Professor University of Toronto, Department of Surgery 
Princess Margaret Cancer Centre 
Toronto General Hospital 
Nathan.Perlis@uhn.ca 
437-533-0228 
 
Dr. Rob Hamilton  
Staff Urologist 
Princess Margaret Cancer Centre 
Toronto General Hospital 
Rob.Hamilton@uhn.ca 
416-946-2909 
 
Dr. Jason Lee  
Staff Urologist 
Assistant Professor, University of Toronto, Department of Surgery 
Toronto General Hospital 
Jason.Lee2@uhn.ca 
416-340-3855 
 
 

 
 
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Study Overview  
 
Abstract:  To date, therapies that provoke an immune attack against the tumor, 
termed immunotherapies, are the only forms of treatment that can initiate long-
term durable responses in patients with metastatic renal cell carcinoma (RCC). 
However, as many patients do not respond to therapy, a significant need exists to 
identify new immunotherapy targets in order to extend the number of patients 
obtaining long-term benefit from these drugs.  
 
Background:  Historically, long-term cures for patients with metastatic RCC was 
only achieved with cytokine immunotherapies, such as high-dose interleukin-2. 
However, this was associated with a poor response rate (7-8% of patients) and 
high-toxicity including mortality risk (~5%), curbing enthusiasm for this 
approach.[1] More recently, interest in using immunotherapy for RCC has been re-
established with data demonstrating the efficacy and tolerability of drugs blocking 
immune checkpoints to reactivate anti-tumor T-cells, such as the PD-1.[2] 
However, resistance to these agents are common, with studies in murine models 
demonstrating the need to co-target many immune cell populations in order to 
obtain broad responses to immunotherapy.[3] These combination approaches 
require a comprehensive molecular characterization of the tumor immune 
microenvironment, in order to determine the complex cellular interactions at play 
currently limiting existing immunotherapy approaches. The feasibility of 
comprehensively dissecting the tumor immune microenvironment to determine 
novel drug targets has recently been established in mouse models and human 
tumors using a combination of flow cytometry and RNA sequencing.[4]  
Rationale: 
To date, while it is clear that a comprehensive molecular 
characterization of the RCC immune microenvironment is required to identify new 
immunotherapy targets to improve clinical responses, such studies are in their 
infancy. Herein, we propose to utilize established state-of-the-art multi-
dimensional 
technologies 
to 
characterize 
the 
RCC 
tumor 
immune 
microenvironment at a detailed molecular level. This discovery dataset will fuel the 
development of novel biomarkers and therapies.  
 
Hypothesis : 
1) A comprehensive molecular characterization of human RCC tumor specimens 
is feasible through a combination of single-cell RNA sequencing, cell surface 
proteomics, whole genome sequencing as well as radiological and pathological 
assessment. 
 
2) A comprehensive molecular characterization of human RCC tumor specimens 
will identify novel protein targets that can be targeted to improve immunotherapy.   
 
 
 
Study Aims : 
 

 
 
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1) To assess the molecular profile, including 
differential gene expression 
and unique protein epitopes
, of RCC tumor microenvironment  cell 
populations  through single -cell RNA sequencing .  
 
2. To relate data obtained from the
 tumor microenvironment
 molecular 
profile of each RCC to its pathological and 
radiological imaging features.
 
 
3. To relate the data obtained from the tumor microenvironment 
molecular  
profile of each RCC to its genetic mutational profile.
 
 
4. To generate patient -derived cell lines and xenograft models of studied 
samples to facilitate  the discovery of new biomarkers and therapies.
 
 
Significance:  This study will identify new targets on cells within the RCC tumor 
microenvironment that could be perturbed to improve anti-tumor immune 
responses. This knowledge would allow for the development of new 
immunotherapeutic strategies for RCC, with the potential to improve long-term 
cure rates for this disease. The study plans to enroll 300 participants.   
 
Experimental Overview  
 
Aim  1: To assess the molecular profile, including differential gene 
expression and unique protein epitopes, of RCC tumor microenvironment 
cell populations through single
-cell RNA sequencing.  Rationale: In order to 
profile the transcriptome and cell surface proteome, fresh viable cells are required 
in order to minimize ischemic changes and ensure cell state, viability and 
phenotype are maintained. To achieve this, a renal mass incisional or needle core 
biopsy will be performed after nephrectomy (radical or partial) and tissue will be 
immediately and rapidly processed for downstream experimental applications 
including flow cytometry, single cell RNAseq and cell surface proteomics.  
 
 
Experimental Design:  
 
1. Tumor, blood and urine sample collection
:  
 
Tumor  : After nephrectomy, the specimen will be transported to the Surgical 
Pathology suite by Sally Zhang.  One or more incisional biopsy (~2 cm x 2 cm) 
will be taken by the UHN Biobank PA on shift.  The biopsies will be performed in 
a manner that will not interfere with final pathological assessment of the tumor. 
To facilitate this, all cases will be discussed prior to surgery with the study 
pathologist Dr. Christopher Ma. This protocol has been reviewed and approved 
by our previous and current study pathologists Drs. Andrew Evans, Joan 
Sweet,Christopher Ma, and Susan Prendeville. The biopsy specimens will be 
placed immediately in culture media (M199), or snap-frozen in liquid nitrogen, 
and transported to the laboratory on ice. Sally Zhang will transport samples. 

 
 
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Laboratory work will be performed in Laurie Ailles lab, conducted by Jalna Meens 
and Sally Zhang (Biosafety #56597).  
 
Blood and urine : In order to determine tumor specific gene expression changes 
within the tumor tissue we will also perform single-cell RNA sequencing on blood 
(i.e buffy coat) and urine tissue from each patient. These samples will be 
collected at the time of surgery from each patient while they are anesthetized. 
This will be a one-time sample collection. These samples will be processed for 
single-cell RNA sequencing in an analogous manner to the tumor tissue. 
Consent for these samples is not optional, and the patient cannot participate in 
this study if they do not consent for collection of blood and urine.    
 
Note, a portion of each tumor, blood and urine sample will also be snap frozen 
for subsequent DNA sequencing (described below). 
 
Additionally, if a patient enrolled in this study is undergoing renal tumor biopsy as 
part of their standard of care diagnostic work-up, we will obtain an additional biopsy 
core to be used for research purposes. The rationale is that this tissue can be 
subjected to the molecular characterization described here and aid in the 
development of precision medicine approaches. Obtainment of these specimens 
will not interfere with the normal pathology assessment of the kidney tumor and 
will only be obtained if adequate diagnostic tissue has been collected. Patients will 
be consented for this as outlined in our consent form. Once the biopsy core is 
obtained, the tissue will be processed in an analogous fashion to the samples 
obtained during surgery as described above.   
 
Note, all patients will be consented in the surgeon’s office prior to surgery. 
 
2. Single cell suspension generation:
 A single cell suspension will be generated 
from the tumor biopsy specimen by first mincing the tissue with scalpels and 
digested with 500U/ml collagenase IV, 100U/ml collagenase I and 200 mg/ml 
DNAase I for 30 minutes in a 25 ml Erlenmeyer flask (continuous stirring) at 37C 
and 5% CO2. Cells will then be passed through a strainer (70 um), separating 
isolated single cells from remaining tissue fragments. The single cell suspension 
will be kept on ice to minimize ischemic changes. A portion of the biopsied sample 
will be persevered and snap frozen using liquid nitrogen for subsequent 
pathological assessment and whole genome sequencing. Urine and blood 
samples are already in single cell suspension format and do not require the above 
processing step. 
 
3. Flow c ytometry:  Cells isolated in aim 1 will be subjected to multi-color flow 
cytometry sorting, using an established panel of antibodies. Cell surface staining 
will be completed in the presence of anti-Fc receptor antibodies and 2% fetal calf 
serum to prevent non-specific binding. Fixable live/dead zombie dye will be used 
to assess cell viability. Following cell surface staining, cell sorting will be performed 
using a BD FACSAria sorter to isolate populations of interest.  

 
 
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4. Single Cell RNA sequencing:  200,000 cells for each tumor single cell 
suspension, blood or urine sample will be sorted (as above) and maintained at 4 
degrees to minimize ischemic changes. Samples will be delivered to the Princess 
Margaret Genomics Core facility and technicians within the facility will prepare and 
perform single-cell RNA sequencing using the 10X genomics platform via 
established protocols. There will be no left over patient material after this step.  
 
5. Illumina sequencing : scRNAseq libraries will be submitted to the Princess 
Margaret Cancer Centre for sequencing. Sequencing will be performed on an 
Illumina Novaseq according to established protocols. All samples will be de-
identified prior to submission. Samples and data generated prior to this version of 
the protocol will continue to be shared with Celsius as per collaboration contract 
states. No further testing of the samples will be conducted by Celsius. All sample 
information that will be shared with Celsius including the single-cell genomics data 
is outlined in Appendix 1. Note, there will be no sharing of any personal health 
information. This has been reviewed and approved by the UHN legal office (Lesley 
Rapport). 
6. Cell surface proteomics
: Tumor infiltrating cell sub-populations will be isolated 
by flow cytometry as described above and assessed for cell surface protein 
composition through standard proteomics approaches. This will include both liquid 
chromatography mass spectrometry, high throughput flow cytometry, and CITE-
seq as previously described.[5-7]  
 
7. Data analysis : Functional genomic and proteomic sequencing results will be 
analyzed using computational approaches at the Bader Lab in the Donnelly 
Centre. The raw gene counts from the tissue samples will first be input into an 
informatics pipeline to identify various cell populations present with the tumours. 
Dr. Bader’s computational team will perform deeper analysis on these cell 
populations to reveal tangible molecular characteristics such as cellular states, 
mutation profiles, and cell-cell interactions. These aspects are crucial to 
understanding the disease and guiding further research.  
 
 
 
 
 
Aim 2 . To determine the radiological and pathological features associated 
with the derived tumor microenvironment molecular data from aims 1
-2. 
 
Experimental overview:
 
 
1. Radiological assessment overview:
 A comprehensive radiological 
assessment of each tumor will be obtained  
 

 
 
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Following nephrectomy, the tumor sample will be taken for an MRI at Mount Saini 
Hospital in order to map geographically where the tumor biopsies were obtained 
(details described below in section 2). Radiomic features will be extracted from 
the MRI images and established machine learning algorithms will be employed to 
determine features associated with our derived tumor microenvironment 
molecular signatures from aim 1-2. 
 
Note, post-op tumor MRIs, will be performed at the MSH MRI facility under the 
supervision of Dr. Masoom Haider.  
 
Additionally, standard of care radiological images including post-operative 
CT/MRI scans may be utilized to facilitate radiological-pathological-genomic 
correlations. In particular, these images will aid in co-registration of spatial 
regions within the tumor, and provide information on MRI-CT correlations. This 
will improve the translatability of any derived radiological biomarker signatures 
that we develop. Patients will be asked to provide consent for us to utilize these 
images. In addition, we will ask patients for their consent to utilize these images 
in future research. This will ensure that the information collected in this study can 
be utilized to its full potential. 
 
2. Post -operative tumor MRI : Following biopsy and surgical extirpation of the 
renal tumor, it will be placed in a sealed container in normal saline and 
transported to the MRI facility at Mount Sinai Hospital. The specimen will be 
transported by a designated UHN Biobank staff as well as our study Radiologist 
(Dr. Masoom Haider). The specimen will be submerged in saline, and an MRI will 
be performed. The specimen will then be transported back to the Toronto 
General Hospital pathology department. The maximum time from surgical 
extirpation to delivery at the Toronto General Hospital pathology department will 
be 90 minutes. This delay in clinical pathological assessment for research MRI 
purpose has been approved by the study pathologist (Drs. Andrew Evans and 
Joan Sweet, Christopher Ma previously) Dr. Susan Prendeville, and the TGH 
pathology chief Dr. Theo Van Der Kwast.  
 
Imaging will be obtained in an orientation that include the biopsy sheath in plane. 
Quantitative T1, T2, diffusion and susceptibility mapping sequences will be 
performed for further co-registration with ex-vivo pathology. Using an appropriate 
marking device, a line will be drawn indicating the plane of sectioning for 
pathology. Once transported back to pathology sectioning will be done by a 
dedicated PA along the indicated plane of section to give a 5-6mm slice. Blocks 
will be taken with a grid pattern through the slice and labelled so that after 
staining they can be scanned and reconstructed back to a large field section. 
This will then be co-registered to the in vivo and ex vivo MRI for radiologic-
pathologic correlation. A trial run will be done with a cadaveric bovine/porcine 
kidney to demonstrate feasibility. An example of this paradigm is shown in a liver 
study done ten years ago at UHN (Fig 1). Co-registration with ex vivio liver MRI 
of this colorectal metastases is shown in Fig 2.  

 
 
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Fig 1. Example of path processing: Grid overlay with liver section further cut 
into squares to fit on standard slides and then reconstructed after scanning.  
 
 
Fig 2.  Example of path processing with imaging co-registration: T2 images of the 
sample plan as the pathologic section in Fig 1 showing the T2 signal correlates of 
areas of acinar necrosis in colorectal cancer 
 
 
3. Pathological assessment
 of biopsy specimens
: For each biopsy taken, a 
portion of the tumor material will be preserved, snap frozen in liquid nitrogen and 
submitted for standard pathological assessment. Digital images of the tumor 

 
 
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sections will be obtained and machine learning algorithms will be employed to 
determine digital pathology features associated with our derived tumor 
microenvironment molecular signatures from aim 1-2. This pathological 
assessment will be conducted for research purposes only. 
 
4. Pathological assessment of renal tumor
 (surgic al) specimen:  Following 
surgical extirpation and obtainment of an MRI image (Aim 3.3), the surgical 
specimen will be delivered to the Toronto General Hospital pathology 
department. Under the supervision of the study pathologist (Dr. Susan 
Prendeville), the specimen will be fixed and sectioned in a manner that matches 
the MRI imaging plane as close as possible. Histological sections will be scanned 
and reconstructed into whole tumor slices to facilitate radiological-pathological-
genomic correlations. This pathological assessment will be conducted for 
research and clinical purposes, this protocol has been reviewed and approved by 
the study pathologist (Drs. Andrew Evans and Joan Sweet, Dr. Christopher Ma) 
Dr. Susan Prendeville.  
 
 
 
Aim 3 . To determine the genomic features associated with the derived 
tumor microenvironment molecular data from aims 1
-2. 
 
Experimental overview:
 
 
1. Whole genome sequencing
 on biopsy tissue , blood and urine . A portion of 
the tumor biopsy, urine and blood samples will be preserved and snap frozen in 
liquid nitrogen. In order to determine tumor specific mutations whole genome 
sequencing will also be performed on blood (i.e buffy coat) and urine tissue from 
each patient. These samples will be collected at the time of surgery from each 
patient while they are anesthetized. DNA will be extracted from all samples via 
established methods, and sequencing libraries will be prepared and sequenced 
at through the Princess Margaret Genomics Centre. All patient material storage 
will be organized through the UHN Biospecimen Services for this experimental 
aim. In addition, to ensure quick accessibility when needed, frozen tissue 
samples will be kept first in Ailles Lab, and later on moved to biobank for long 
term storage. 
 
Aim 4. To generate patient -derived cell lines and xenograft models of studied 
samples to facilitate the discovery of new biomarkers and therapies.
 
 
Experimental overview:
 
 
1. Isolation of tumor fragments and cell lines from biopsy sam
ple. At the 
time of final pathological assessment, a portion of the surgical specimen not 
required for pathological diagnosis will be dissected and placed in culture media 
(M199). This specimen will be transported to Dr. Laurie Ailles laboratory 

 
 
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(Princess Margaret Research Tower) and subjected to established protocols for 
generation of tumor fragments and cell lines [8, 9]. This will be performed by 
Jalna Meens and Sally Zhang under biosafety certificate # 56597.  
 
Consent Procedure.  Patients will be consented for this study prior to surgery or 
renal biopsy.  
 
Inclusion Criteria 
1. RCC or suspicious of RCC 
6.   5mm slices, digital image available, biphasic CT. Di-com images available.  
 
Exclusion Criteria 
2. Pregnancy or Breast Feeding 
3. Pheochromocytoma 
 
 
 
Patient Risks 
No risks exist for enrolment into this study. 
 
 
 
 
References:  
1. 
McDermott DF. Immunotherapy of metastatic renal cell carcinoma. Cancer 
2009; 115: 2298-2305. 
2. 
Motzer RJ, Escudier B, McDermott DF et al. Nivolumab versus Everolimus 
in Advanced Renal-Cell Carcinoma. N Engl J Med 2015; 373: 1803-1813. 
3. 
Moynihan KD, Opel CF, Szeto GL et al. Eradication of large established 
tumors in mice by combination immunotherapy that engages innate and adaptive 
immune responses. Nat Med 2016; 22: 1402-1410. 
4. 
Broz ML, Binnewies M, Boldajipour B et al. Dissecting the tumor myeloid 
compartment reveals rare activating antigen-presenting cells critical for T cell 
immunity. Cancer Cell 2014; 26: 638-652. 
5. 
Elschenbroich S KY, Medin JA, Kislinger T. Isolation of cell surface proteins 
for mass spectrometry-based proteomics. Expert Rev Proteomics. 2010; 7: 141-
154. 
6. 
Gedye CA, Hussain A, Paterson J et al. Cell surface profiling using high-
throughput flow cytometry: a platform for biomarker discovery and analysis of 
cellular heterogeneity. PLoS One 2014; 9: e105602. 
7. 
Stoeckius M, Hafemeister C, Stephenson W et al. Simultaneous epitope 
and transcriptome measurement in single cells. Nat Methods 2017; 14: 865-868. 
8. 
Gedye C, Sirskyj D, Lobo NC et al. Cancer stem cells are underestimated 
by standard experimental methods in clear cell renal cell carcinoma. Sci Rep 2016; 
6: 25220. 

 
 
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9. 
Lobo NC, Gedye C, Apostoli AJ et al. Efficient generation of patient-
matched malignant and normal primary cell cultures from clear cell renal cell 
carcinoma patients: clinically relevant models for research and personalized 
medicine. BMC Cancer 2016; 16: 485. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Appendix 1 Data elements collected in the study 
All samples and information will be de-identified. 
 
Clinical 
Age 
Sex 
Co-morbidities 
Relevant family history 
BMI 
Smoking status 
Drinking status 
Relevant disease history (previous and current) 
- 
Previous renal tumour diagnoses and treatments 
- 
Disease progression 
- 
Metastatic status  
- 
Others 
Relevant treatment history  
- 
Surgeries and physical procedures (e.g. renal biopsy) 
- 
Radiation therapy: type, cycle/dose, location, duration, response 
- 
Chemotherapy: type, cycle/dose, duration, response 
- 
Systemic therapy: type, cycle/dose, duration, response 
- 
Others 
 
Radiological 
CT of chest, abdomen, and pelvis  
MRI of chest, abdomen, and pelvis  
Ultrasound of chest, abdomen, and pelvis 
Additional imaging (e.g. bone scans) in the case of metastasis  
 

 
 
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Pathological 
Tumor location 
Histology 
Dimensions 
Grade 
Stage 
Multifocality 
Margin 
Tumour extension and invasion  
Tumor complexity 
Additional features: sarcomatoid, rhabdoid, cystic, necrosis 
Histological tissue staining features 
Adjacent kidney tissue status