The current state of digital pathology, molecular diagnostics and biobanking in renal cancer: Kidney Cancer Association Consensus Statement

INTRODUCTION

Despite the progress made in the treatment of renal cell carcinoma (RCC), particularly with the advent of VEGF-directed tyrosine kinase inhibitors (TKIs) and Immune Checkpoint Inhibitors (ICPIs)¹, and more recent developments in adjuvant immunotherapy², there remain several key questions and areas of unmet need in the treatment of people suffering from RCC. These questions cross the spectrum of stages of the disease, including how to improve early detection, who to treat with a small renal mass and which treatment to use, selection of patients for adjuvant therapy, optimal treatment sequencing for patients with incurable disease, and the management of non-clear cell RCC subtypes. The development of molecular diagnostics and digital pathology are two active areas of research that might be directly translated into clinical practice to improve treatment in these areas.

Digital pathology can be defined as “the acquisition, management, sharing and interpretation of pathology information in a digital environment”³. The development of digital pathology may offer several benefits. In routine care, the digital format may allow faster sharing between hospitals to achieve primary diagnosis or second opinion. It may allow access to new methods for quantitative image analysis, or the development of AI-assisted diagnostic systems. The wider sampling area captured by these AI methods may counter the issue of intratumoral heterogeneity that can limit some biopsy-based approaches⁴, though the adoption of digital pathology approaches has to be underpinned by standardised tumour sampling methods. Sharing in digital format also overcomes the physical limits of tissue availability, especially for rare conditions or cases where biopsies are not recommended. There may also be wider benefits, such as improved education of doctors in training in the key specialties involved⁵, and less need for on-site storage of glass slides.

Molecular diagnostics is the use of molecular biology techniques (analysis of DNA, RNA and proteins) to aid diagnosis, predict disease course, select treatment and monitor the effectiveness of therapies. While some molecular markers have been shown to have prognostic importance in research settings, none have made it to routine care in RCC⁶. Other markers have shown promise for treatment selection, particularly RNA signatures^7,8 which are being assessed in prospective studies such as BIONIKK⁹ & OPTIC-RCC¹⁰, and circulating KIM-1 in the IMmotion010 study¹¹. However, at present there is no consensus on the signatures used, and these remain a research tool. Adjuvant immunotherapy is a relatively new development in RCC, however, based on the clinical likelihood of benefit a significant number of patients will be overtreated with the associated risk of ICPI toxicity, so research is needed to improve patient selection². In non-clear cell RCC, the use of molecular tests is essential to diagnose some rarer subtypes, such as those in the WHO category of molecularly defined tumours^12,13. These are available at some centres, but clarity is needed on when these tests should be done to balance the risk of missing rare cases against the cost of widespread testing.

Biobanking efforts underpin laboratory research into kidney cancer. However, these studies are often locally organised and differ in the samples they collect, subsets targeted, and associated clinical data. Sharing and collation of samples into larger sets to increase the power to answer a particular research question can be challenging, both within the same country, and internationally.

Digital pathology and molecular diagnostics are known to augment research and routine clinical care^14–17, however, they seem aspirational in RCC and are yet to be widely implemented. Coordination of biobanking efforts may streamline progress in kidney cancer research. Participants invited to the Kidney Cancer Association (KCA) Think Tanks during the European International Kidney Cancer Symposium (IKCS) meeting in 2023 (Edinburgh, UK) and 2024 (Sitges, Spain) discussed how these strategies might be utilised for renal cancer, to set international priorities and facilitate future research collaborations.

Materials and METHODS

The KCA Think Tank coalition brings together a select group of prominent thought leaders in kidney cancer. The aim is to share expertise in the RCC field and identify gaps in resources and knowledge that limit advances in RCC care. Participants of the KCA Think Tank ahead of the 2023 IKCS: Europe Edinburgh, Scotland considered the status of digital pathology, molecular diagnostics and biobanking in kidney cancer. Following the meeting, an online survey was advertised to clinicians working on kidney cancer via the KCA email list and social media August-October 2023, to capture wider opinions on these issues. As part of the KCA Think Tank ahead of the 2024 IKCS: Europe Sitges, Spain, the panel considered which molecular diagnostic and pathology techniques should be prioritised, how availability of molecular diagnostic and digital pathology techniques should be advanced and how coordinated biobanking might be achieved. A diverse group of stakeholders was involved including oncologists, surgeons, pathologists, scientists, representatives from patient advocacy groups and pharmaceutical companies.

RESULTS

Survey of Digital Pathology and Molecular Diagnostics

There were 40 individual responses to the survey, from surgeons (14), oncologists (15), pathologists (7) and other specialties (4) (Fig 1A). Over 90% of responses were from tertiary centres or dedicated cancer hospitals (Fig 1B). 16 responders were from the UK, 18 were from 11 different European nations, 4 from the USA and 2 from Pakistan (Fig 1C). There was wide variation in case volume in both localised and metastatic disease, with 8 centres treating fewer than 25 cases of RCC each year, and 5 centres treating over 200 cases (Fig 1D).

Figure 1: Survey response demographics



Over 60% of centres reported having access to digital pathology facilities (Fig 2A), though only 10% used it routinely (in over half of cases) in standard care (Fig 2B). 49% of centres were using digital pathology to some extent in research studies (Fig 2C), and over 80% of responders were interested in contributing to wider digital pathology research (Fig 2D). Cost and staffing were the leading barriers to introducing digital pathology in either research or routine clinical practice (Fig 2E).

Molecular diagnostics were only used to aid diagnosis routinely in three centres, and in just one to aid treatment selection (Fig 2F&G). Specialist IHC stains, translocation studies and tumour DNA sequencing are the most widely available (Fig 2H). The majority of responders felt that better access to molecular diagnostics would help the management of RCC (Fig 2I). Cost and staffing were again identified as key barriers (Fig 2J).

Figure 2: Survey responses on digital pathology and molecular diagnostics

Most centres contributed to an existing RCC biobank collecting a wide range of samples (Fig 3A). Encouragingly, 80% of responders were interested in contributing to coordinated biobanking efforts (Fig 3B). Staffing and funding were the leading barriers to setting up local biobanking, while legal and intellectual property considerations were more important when international data and sample sharing were considered (Fig 3C&D).

Figure 3: Survey responses on biobanking



At the 2024 Think Tank Meeting, the discussion aimed to establish a consensus regarding which diagnostic techniques should be prioritised based on their potential to be widely implemented and offer significant clinical value. The aim was to ensure investment in these technologies would yield practical benefits for diagnosis and treatment at a broader scale. Participants were asked to rank diagnostic methods considering their clinical utility and practicality, the outcome is summarised in Figure 4. This approach highlighted the balance between the complexity of the technologies and their potential to improve patient outcomes significantly. Blood-based biomarkers were felt to have excellent utility and practicality if they can be developed. The following statements were also developed from discussions at the 2024 Think Tank.

Figure 4: Priorities for development

Consensus Statements

• Statement 1: The adoption of digital pathology should be prioritised in RCC
• Statement 2: Prospective validation and standardisation are needed for predictive molecular testing in clear cell RCC
• Statement 3: Molecular diagnostics may fulfil unmet needs in non-clear cell RCC
• Statement 4: Artificial Intelligence has the potential to improve multiple aspects of RCC diagnosis & management
• Statement 5: International cooperation would facilitate the introduction of digital pathology and molecular diagnostics
• Statement 6: Standardised approaches to biobanking will facilitate high-quality RCC research

Statement 1: The adoption of digital pathology should be prioritised in RCC

There was strong agreement that digital pathology is a critical area of development, seen as a necessary evolution to meet the current and future needs of pathology services. While not the most advanced technology, digitization of Haematoxylin and Eosin (H&E) stains was recognised as foundational for further pathological analysis. It was deemed one of the more practical steps towards digital pathology due to its scalability and the potential to enhance the accessibility and quality of diagnostic reviews. Furthermore, the integration of artificial intelligence (AI) and machine learning was discussed as a transformative element that could leverage digitised images to not only enhance diagnostic precision but potentially predict patient outcomes¹⁸. This prediction capability could reduce the need for more invasive and costly tests, thus democratizing advanced diagnostic capabilities, especially in underserved regions or smaller healthcare facilities lacking specialised pathology expertise.

Statement 2: Prospective validation and standardisation are needed for predictive molecular testing in clear cell RCC

In clear cell RCC, current diagnostic methods (particularly H&E supported by IHC for protein markers) are usually sufficient to achieve the diagnosis. The primary research focus is on predictive markers that can be used to assign patients to current or emerging treatment combinations. Tumour DNA testing may identify mutations in genes including VHL, BAP1 or PBRM1, though these findings are not necessarily actionable, and so of limited value⁶. The development of RNA signatures is exciting, but consensus on the signatures used and validation in prospective trials is needed before wider use. General use may then be limited by heterogeneity^4,7–10. Blood-based biomarkers, including protein and cfDNA-ased^19,20, were identified as key priorities for further research; if they could be implemented, they would be practical and have widespread utility in clear cell RCC, avoiding the need for tissue re-sampling or the risk of tumour heterogeneity confounding the results. Given the complex intratumoral, immune and metabolic heterogeneity of RCC, new developments in single-cell and spatial transcriptomics may help to better understand aetiology, stratify patients, guide management strategies, and identify therapeutic targets^21–23. This area is the subject of much research interest, however, cost, time, access to tissue (particularly if assessing via renal biopsy) and identification of clinically actionable results will remain a challenge to widespread integration into healthcare pathways.

Statement 3: Molecular diagnostics are of particular value in non-clear cell RCC

In non-clear cell RCC, molecular testing has potential given the current unmet need. It may confirm the subtype of non-clear cell RCC, especially in borderline cases and in the ‘molecularly defined’ subtypes from the WHO 2022 classification^24,25. The correct identification of the subtype may provide prognostic information for the patient and clinician, particularly if aggressive variants are found, such as some adult MiT family translocation RCC²⁶. There may be hereditary variants, such as in FH or SDH genes, which may guide further screening of the patient or family members²⁷. There may be actionable mutations, for example in ALK-rearranged RCC, or MET in papillary RCC^25,28. Correct identification of non-clear cell RCC variants, underpinned by molecular methods, is also critical for access to prospective clinical trials, which may provide novel treatment for these under-represented subtypes of RCC. A proposed approach is summarised in Figure 5.

Figure 5: Framework for the use of molecular testing in RCC

Statement 4: Artificial Intelligence has the potential to improve multiple aspects of RCC diagnosis & management

The integration of AI and machine learning in digital pathology was unanimously seen as a transformative shift. This consensus reflects a broad recognition of the potential for AI to not only speed up the diagnostic process but also to provide deeper insights into complex pathological images, potentially supporting personalised treatment plans and improving outcomes. The combination of digital pathology and machine learning has, for example, shown potential in inferring mutation status and quantitating vascularity, which correlates with angiogenesis gene expression clusters and has the potential to personalise treatment selection^29,30. The use of AI in digital pathology could also facilitate remote diagnostics, making expert pathological analysis available even in geographically isolated regions.

There are substantial challenges with integrating AI into existing medical infrastructures; the need for substantial data sets to train algorithms and the importance of ensuring tools are reliable and transparent. There is also a need for robust data infrastructure, the integration of AI tools into existing medical workflows, and ensuring the security and privacy of sensitive medical data.

Statement 5: International cooperation would facilitate the introduction of digital pathology and molecular diagnostics

Great emphasis should be placed on the importance of collaborative research efforts to pool resources, share data, and standardise procedures across institutions and borders. Such collaboration could accelerate the development of new diagnostic tools and therapeutic strategies, increasing the pace at which scientific discoveries are translated into clinical applications.

Statement 6: Standardised approaches to biobanking will facilitate high-quality RCC research

Biobanking can benefit significantly from national and international collaboration. By pooling resources and expertise, researchers can access a diverse array of biological samples and associated data, crucial for studies on diseases that vary significantly across different populations and ethnic groups. International collaboration can particularly help in standardising methodologies for collection, storage and analysis; essential for ensuring the compatibility and comparability of research outcomes. Examples like the UK Biobank³¹ and the All of Us Research Program³² in the USA illustrate successful large-scale biobanking initiatives that support a wide range of research aimed at improving the prevention, diagnosis, and treatment of various diseases. However, challenges to data sharing and privacy regulations complicate international collaboration. Standardisation is particularly required to reduce variability in protocols for sample collection, storage, and data recording which can lead to issues in data quality and reproducibility of research findings. Sharing standard-operating procedures and expansion of existing successful kidney-specific biobanking initiatives (for example TRACERx Renal³³ or the Scottish Collaboration On Translational Research into Renal Cell Cancer (SCOTRRCC)³⁴) may facilitate even greater translational research into the unanswered questions eluded to above. In addition, specialised biobanks of live-preserved tumour tissues and tumour grafts in mice may enable functional studies and accelerate drug development³⁵.

Barriers to the implementation of digital pathology and molecular diagnostics

Several barriers were identified across broad themes by the survey and Think Tanks. Many centres have however shown how digital pathology can be integrated into clinical workflows effectively, allowing pathologists to review cases efficiently, in a similar way to the review of radiology images^36–39.

1. Cost: High implementation costs are a significant barrier to the widespread implementation of molecular diagnostics. Strategic financial support is required, both for acquiring the necessary technology and for sustaining and updating systems, and training personnel to use them effectively. While the adoption of whole-genome sequencing might offer comprehensive data, high cost and complex data management might limit its immediate practicality compared to more straightforward technologies like digital H&E staining, which could be more rapidly integrated into clinical practice at a lower cost.
2. Education and Training: Ongoing education is required to keep pace with the rapid advancements in technology. This education should not only cover technical skills but also focus on analytical aspects, enhancing the ability of medical professionals to interpret complex data effectively.
3. Integration within existing healthcare infrastructure: Ensuring compatibility between new digital systems and older medical record systems can be complex and requires careful planning and execution. Interdisciplinary teams are crucial in addressing the technical challenges of integrating new diagnostic technologies into existing healthcare frameworks. For instance, pathologists and IT specialists need to work together to ensure that digital pathology systems are compatible with electronic health records and other clinical information systems, facilitating seamless workflows that support rather than disrupt clinical operations.
4. Data management and security: robust systems need to be in place to store, manage, and protect patient information. This includes adhering to data protection regulations, which vary by region and can complicate the sharing of digital images across platforms and borders. Ensuring compliance with international data protection laws and maintaining the highest standards of data security is imperative to protect patient information from unauthorised access.
5. Ethical considerations: Adoption of widespread genetic testing or technologies that might significantly alter patient interactions with healthcare systems requires careful consideration. One of the primary ethical concerns raised was the potential for genetic and molecular diagnostics to generate results that might not have clear clinical implications, for example identifying genetic markers without established therapeutic strategies or prognostic significance could cause unnecessary anxiety or confusion. A patient-centred approach is required, ensuring that technological advancements lead to genuine improvements in patient care, such as more precise diagnostics, personalised treatment plans, or better disease management. By focusing on these aspects, the adoption of new technologies can enhance rather than complicate the patient care process.

Challenges to Biobanking

Similarly, key challenges to Biobanking were identified, and exemplar projects are summarised in box 1.

1. Sample collection, preservation and data management: High-quality sample collection and preservation are prerequisites for a successful biobank, often requiring sophisticated equipment and facilities. Each sample must be associated with accurate and comprehensive metadata to provide context for researchers, such as the health status of the donor, the conditions under which the sample was collected, and any treatments the donor was undergoing at the time. Robust data systems are required to handle the vast amounts of information generated. Furthermore, as the field of biomedicine advances, techniques for analysing biobank samples are also evolving; decisions on when and how to analyse finite tissue resources are important considerations.
2. Local, National and International Regulation- Biobanks must adhere to strict regulations like the EU's General Data Protection Regulation (GDPR) and the US's Health Insurance Portability and Accountability Act (HIPAA), which safeguard privacy and personal data. While ethical concerns, particularly regarding informed consent and the rights of donors, are central to biobanking operations, these laws can create barriers, particularly to international collaboration. Donors must be fully informed about the use of their samples and data, with the ability to withdraw consent at any time. Ethical oversight, typically managed by institutional review boards or ethics committees, ensures compliance with ethical standards and helps maintain public trust.
3. Centralised vs Decentralised structures: These two approaches carry benefits and compromises. Decentralisation allows for tailored approaches that meet specific regional or institutional needs, promoting innovation and specialisation, with unique methodologies tailored to specific research goals. Centralisation can lead to significant efficiencies in terms of resource use, funding, and data management, and can facilitate larger-scale research studies by providing a consistent and comprehensive collection of samples and data.
4. Funding and infrastructure: These are critical for both facility set-up and maintenance (particularly given the specialised equipment required), along with sample processing, storage, and data management. Government funding is particularly crucial as it typically provides the foundational support for many national and international biobanking initiatives. However, securing consistent funding can be challenging due to budgetary constraints and shifting research priorities.

Box 1: National and international approaches to biobanking

Germany	A decentralised approach, with regions or institutions developing their own biobank with distinct processes and standards. This diversity can lead to rich, localised collections but also poses challenges for standardization and data sharing on a national scale40. Accompanying patient registries are particularly useful for survival data.
Denmark	A well-integrated model within the healthcare system, the country has a centralised biobank41. This integration allows for high-quality sample collection and storage, as well as meticulous data management, standardised across the country. Danish biobanks are particularly noted for their comprehensive ethical oversight and systematic patient consent processes, which are streamlined to facilitate research while protecting donor rights.
USA	Several large-scale biobanking initiatives exist, such as the All of Us Research Program, which aims to collect and analyze biological samples from one million participants to advance personalised medicine32. The U.S. also hosts disease-specific biobanks, such as those supported by the National Cancer Institute Cooperative Group Program and National Clinical Trials Network (https://nctnbanks.cancer.gov/) and the Cancer Genome Atlas Program42. These biobanks often focus on collecting a range of data types, from genomic data to detailed clinical information, supported by substantial technological and financial resources.
European Union	Cross-border research collaborations are supported through initiatives like BBMRI-ERIC (Biobanking and BioMolecular resources Research Infrastructure - European Research Infrastructure Consortium, https://www.bbmri-eric.eu/), which facilitates access to biobanks across Europe, enhancing their utility for multinational research studies.
Scotland	The Scottish Collaboration On Translational Research into Renal Cell Cancer (SCOTRRCC) is an example of a urological surgery lead bioresource which utilised standard operating procedures across seven centres in Scotland to collect renal tissue, blood and urine, along with high-quality clinical information34.
UK	TRACERx Renal is a prospective translational research study, combining the multicentre collection of kidney tissue, blood and urine with cutting-edge basic science research to understand the evolution of renal cancer and develop future biomarkers33.

CONCLUSION

While the implementation of digital pathology and molecular diagnostics presents several challenges, these can be addressed through strategic planning, investment in infrastructure, and a focus on training and change management. Overcoming these hurdles is essential for leveraging the full potential of these technologies to enhance diagnostic accuracy, improve patient outcomes, and facilitate more collaborative approaches in medical diagnostics.

Biobanking is also seen to have huge potential. Utilisation is challenging due to the lack of transparent and well-publicised processes of proposal application and review, and many biobanks not having well-annotated clinical data, including therapy and outcome information. Despite the hurdles to international collaboration in biobanking, the potential benefits of such efforts are immense. By working together, countries and institutions can leverage the strengths of diverse populations to gain insights that would be challenging to obtain in isolation, crucial for the advancement of global health and precision medicine. Integration of biobanks with electronic health record systems is potentially game-changing, enabling enrichment of the value of samples with detailed clinical annotations and ensuring that research can provide insights into disease progression and treatment efficacy.

Conflict of interest

IKCS (Europe) and the KCA Think Thanks were supported by Eisai and Pfizer. GDS has received educational grants from Pfizer, AstraZeneca and Intuitive Surgical; consultancy fees from Pfizer, MSD, EUSA Pharma and CMR Surgical; Travel expenses from MSD and Pfizer; Speaker fees from Pfizer; Clinical lead (urology) National Kidney Cancer Audit and Topic Advisor for the NICE kidney cancer guideline. GP receives fees for advisory board or speaking lectures from Amgen, AstraZeneca, Bayer, BMS, Eisai, Ipsen, Janssen, Lilly, Merck, MSD, Novartis, Pfizer and Roche, and research grants from Janssen, Ipsen, MSD, and Gilead. No other conflicts of interest are to be declared.

FUNDING

No funding sources to declare.

Think Tank participants and contributors

Blackmur, James P; Jones, James O; Laird, Alexander; Warren, Anne; Monroe, Kendall; Vaughan, Gretchen; Chitale, Radha; Leibovich, Bradley; George, Daniel; La Rosa, Salvatore; Pickering, Lisa; Stewart, Grant D; Albiges, Laurence; Barata, Pedro; Battle, Dena; Beisland, Christian; Bex, Axel; Brugarolas, James; Bukavina, Laura; Charnley, Natalie; Escudier, Bernard; Fendler, Annika; Grünwald, Viktor; Henske, Elizabeth P; Julian, Juan Carlos; Lund, Lars; Kapur, Payal; Malouf, Gabriel; McDermott, David; McNee, Karen; Msaouel, Pavlos; Nilssen, Frode; Porta, Camillo; Procopio, Giuseppe; Staehler, Michael; Suarez, Cristina; Thorlund, Mie; Toma, Marieta; Turajlic, Samra; Vaishampayan, Ulka; Verkarre, Virginia; Voss, Martin; Young, Kate.

Acknowledgements

Conceptualisation: JPB, JOJ, GDS, LP, SLR; Methodology: JPB, JOJ, AL, GDS, LP, SLR, DG; Writing original draft: JPB, JOJ; Editing draft: JPB, JOJ, AL, AYW, BL, DG, SLR, LP, GDS; Final review and editing: JPB, JOJ, AL, AYW, KM, GV, RC, BL, DG, SLR, GDS, LA, PB, DB, CB, AB, JB, LB, NC, BE, AF, VG, EPH, JJC, LL, PK, GM, DM, KM, PM, FN, CP, GP, MS, CS, MTh, MTo, ST, UV, VV, MV, KY; Supervision: GDS, LP, SLR, DG.

JPB and JOJ act as guarantors for the contents of the article.

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Posted on 17 October 202418 October 2024