Abstract
The diagnosis of prostate cancer using histopathology is reliant on the accurate interpretation of prostate tissue sections. Current standards rely on the assessment of Haematoxylin and Eosin (H&E) staining, which can be difficult to interpret and introduce inter-observer variability. Here, we present a digital pathology atlas and online resource of prostate cancer tissue micrographs for both H&E and the reinterpretation of samples using a novel set of three biomarkers as an interactive tool, where clinicians and scientists can explore high resolution histopathology from various case studies. The digital pathology prostate cancer atlas when used in conjunction with the biomarkers, will assist pathologists to accurately grade prostate cancer tissue samples.
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Prostate cancer is the second most commonly diagnosed cancer in men with a global incidence of 1.41 million in 2020, which is expected to double by 20401. The Gleason scoring system has been used for more than half a century to assess prostate cancer pathology and to inform on decisions for patient management and therapeutic intervention. The current International Society of Urological Pathology (ISUP) guidelines for the diagnosis of prostate cancer are based upon a modified Gleason grading system2,3,4,5,6,7,8, where morphology and architecture of malignant prostate glands are evaluated by routine Haematoxylin and Eosin (H&E) staining and histological examination. There are several challenges pathologists face when applying ISUP grading to prostate cancer on H&E-stained biopsy slides. Some challenges include (1) the distinction between the Gleason score 3 + 3 with tangential cutting artifacts vs. the Gleason score 3 + 4 with poorly-formed or fused glands, (2) the determining the relative amounts of pattern 3 and 4 (Gleason scores 3 + 4 vs. 4 + 3), and (4) the identification of a tertiary component of Gleason pattern 59,10,11. Among these, differentiating ISUP 2 (3 + 4) versus ISUP 3 (4 + 3) is the most challenging due to disagreement of Gleason patterns 3 versus 49. Unfortunately, these challenges are confounded by problems with complex morphological interpretation and inter-observer variability, which can lead to poor management and treatment selection for patients8,12. To transform prostate cancer pathology assessment, a new panel of biomarkers, consisting of Appl1, Sortilin and Syndecan-1 using immunohistochemistry (IHC), have been developed to accurately interpret the cancer biology, and for the first time assist in Gleason grading13. This new biomarker technology provides reliable detection of prostate cancer in patient tissue samples, and improved risk class stratification for ISUP grade grouping13,14,15. Other technologies are available including Ki67, p6 and P63 / AMACR cocktails however they are not utilised to assist in the assignment of ISUP grade groups. The recent introduction of these biomarkers into clinical practice as a laboratory developed test (LDT) in the United States necessitates training and reference resources to support the clinical utility of this new technology16.
A comprehensive resource of digitised Appl1, Sortilin and Syndecan-1 biomarker IHC labelled and routine H&E-stained prostate cancer slide images was compiled, together with clinical pathology annotations (Fig. 1) and were critical for their recent implementation into clinical practice. Here, we present a complete dataset of case studies showing grade groups from benign, and ISUP 1 to ISUP 5 with H&E stained tissue sections. This dataset is then reinterpreted together with our biomarkers to assist and improve the accuracy of the grading. These micrographs will ideally be used as a pathology reference system, an educational interpretation guide, and as an advanced training tool for biomarker-assisted ISUP grading. This method for more accurate and reliable Gleason grading was needed to improve the prognostic assessment in patients with prostate cancer, which will provide a more rigorous evidence-base for decisions on therapeutic intervention5,6,7,8,12. The underlying problems with Gleason grading include its reliance on morphology, which is often confounding or lacks sufficient detail to facilitate accurate interpretation of the complex pathology, and this is compounded by H&E staining which is not specific for the cancer17,18.
Methods
Sample acquisition
Prostate adenocarcinoma tissue sections were cut from de-identified Formalin Fixed Paraffin Embedded (FFPE) tissue samples, which were collected as part of routine diagnosis and were obtained either from the Australian Prostate Cancer Bioresource (APCB, Australia), Prostate Cancer Research Consortium (PCRC, Ireland), Flinders Medical Centre (Adelaide, South Australia) or Aquesta Uropathology (Brisbane, Queensland). Serial sections of tissue were either stained with routine H&E or Appl1, Sortilin or Syndecan-1 labelled by IHC as outlined previously12. Each tissue sample was then digitised in high magnification (40 × objective) using the Carl ZEISS AxioScan Z.1 and manually reviewed to ensure scan quality. A subset of prostate cancer digital micrographs have been previously published13,14,15,19,20,21,22, and can be used to supplement this digital resource. Basic clinical pathological data consisting of age, tumour stage, biochemical and clinical recurrence status were acquired from either the deidentified local electronic health or the bioresource records where available (see Ethics approval and consent to participate).
Whole slide image processing
All image data was recorded in RGB (red, green and blue) colour format with a bit depth of 24-bit (8-bit per colour channel). Images were viewed using 0.45 gamma, with a maximum function applied, mimicking that of viewing slides under a physical microscope.
Case study interpretation
The biomarkers Appl1, Sortilin and Syndecan-1 were selected for their unique pathological significance in prostate cancer and are designed to be used in a combinatorial assessment13,14,15, where specific examples can be found in the digital pathology prostate cancer atlas23 (https://doi.org/10.5061/dryad.v9s4mw749) and are described in depth below. In prostate tissue, Appl1 is detected within basal cells of benign prostatic glands, often found within the nucleus of dysplastic cells in prostatic intraepithelial neoplasia (PIN), and has a cytoplasmic and diffuse labelling pattern within the malignant epithelial cells of the adenocarcinoma13,14,15,22,24. Clinically, Appl1 is intended to aid in confirming any suspicion of malignant prostatic glands identified during routine H&E screening and to identify regions of interest for grading when using the other two biomarkers, Sortilin and Syndecan-1. Specific examples of Appl1 labelling can be seen in the prostate cancer atlas within all presented cases23. IHC-assisted grading is performed using the biomarkers Sortilin and Syndecan-1; in PIN, Sortilin labelling is punctate and has a supranuclear distribution. In prostate adenocarcinoma, the labelling and distribution of Sortilin can be used to interpret differences between well-formed (intense granular and supranuclear location) and poorly-formed malignant glands (diffuse and disseminated labelling pattern, or absent). Syndecan-1 is detected within basal cells of benign prostatic glands and in malignant prostatic glands with poor-formed gland morphology. Syndecan-1 can also highlight inconspicuous lesions (e.g. small pockets of cancer) and single cancer cells with a differing intracellular distribution, compared to plasma cells (respectively cytoplasmic vs membranous labelling). Specific case study examples are outlined below and can be visualised from the Dryad data repository23. An example of this interpretation is illustrated in Fig. 2.
Benign Case Study: This case showed atrophy and seminal vesicles, but no cancerous glands were identified in the H&E stained section. Observing the serial sections using the biomarkers, the lack of cancerous glands was confirmed. It should be noted, that although this section is benign, distant blocks of the radical prostatectomy have cancerous glands present, and the patient was diagnosed with a tumour stage T3A. This patient did not biochemically relapse during the first 77 months post radical prostatectomy.
ISUP 1 Case Study: For this case, H&E grading showed mainly well-formed glands with poorly-formed glands also present, leading to a grade group of ISUP 2. Reinterpretation using the biomarkers showed the case only presented well-formed glands, with no poorly-formed features, indicating grade group ISUP 1 (Fig. 3). The patient was diagnosed with a tumour stage T2C from a radical prostatectomy.
ISUP 2 Case Study: The H&E stained section for this case displayed both perineural and neural invasion, along with cribriform glands (poorly-formed gland morphology). Inflammatory infiltration was also present as well as glands with glomeruloid features. Upon reinterpretation with the biomarkers, these features were confirmed, both Sortilin and Syndecan-1 labelling intensity was high in the cancerous regions, indicating a grade grouping of ISUP 2. The patient had extracapsular extension and extensive neural involvement and did not biochemically relapse during the first 107 months post radical prostatectomy.
ISUP 3 Case Study: This case showed perineural invasion, with poorly-formed glands forming nests in the H&E stained section, with the tumour infiltrating extra prostatic adipose tissue, leading to an assessment grade group of ISUP 3. When observing with the biomarkers, these features were confirmed, showing a greater portion of poorly-formed glands over well-formed glands, reconciling the initial grade group of ISUP 3 (Fig. 4). The patient had a tumour stage T2C and did not biochemically relapse nor clinically recur during the first 125 months post radical prostatectomy.
ISUP 4 Case Study: In this case study, the H&E section showed the adenocarcinoma infiltrating extra prostatic adipose and fibrous tissue, with perineural invasion, along with poorly-formed glands. Adjacent sections labelled with the biomarkers showed single cells and cords were present (Gleason pattern 5) and confirmed perineural invasion along with perivascular invasion. The additional single cell and cord features as well as the predominant poorly-formed morphology indicated grade group ISUP 4 (Gleason grade 5 + 3) over the initial H&E grading of ISUP 3 (Gleason grade 4 + 3) (Fig. 5). This prostate tissue sample was obtained from a patient who had undergone a radical prostatectomy and had disease that was originally assessed, based on pathological examination, as tumour stage T3B (with extension of tumour into the seminal vesicles) without nodal involvement. The patient had developed non-metastatic biochemical relapse in 23 months and, following radiation therapy, had clinical recurrence of prostate cancer in 53 months after initial diagnosis. Prostatectomy findings confirmed that the patient had high-grade cancer.
ISUP 5 Case Study: The H&E stained section displayed both perineural and perivascular invasion, single cells and sheets, with intraductal carcinoma present. With the biomarker labelled sections, these features were also confirmed. As with the ISUP 4 case above, the intensity levels of Sortilin were low, while Syndecan-1 intensity was high. This prostate tissue sample was obtained from a patient who had undergone a radical prostatectomy and had disease that was originally assessed, based on pathological examination, as tumour stage T3B (with extension of tumour into the left seminal vesicles) without nodal involvement. The patient had developed non-metastatic biochemical relapse in 2.7 months and, following radiation therapy, had clinical recurrence of prostate cancer in 25 months after initial diagnosis. Prostatectomy findings confirmed that the patient had ISUP grade 5 prostate cancer.
Biomarker utility
Figure 6 and the digital pathology prostate cancer atlas23 present digital micrographs of the biomarker labelling in prostatectomy tissue samples and exemplifies the clinical utility in confirming the cancer pathology and grading after surgical ressection13,14. Other types of tissue samples, such as needle biopsies, tissue micro arrays (TMAs), transurethral resection of the prostate (TURPs) blocks (e.g. needle cores and microarrays in Fig. 6), may also be assessed using these biomarkers, and offer significant advantages in clinical practice25,26,27,28. This biomarker panel enables accurate and consistent grading of tissue samples, reducing inter-observer variability13,14,15, to make more precise diagnoses and treatment decisions. The biomarkers are easily adapted to different tissue processing protocols employing well established IHC techniques, thus enabling their utility on different technology platforms (Ventana, Omnis and Agilent platform technologies). The atlas and online resource highlight many cases where histopathology assessment using H&E in isolation can be challenging using morphology alone, and the biomarkers enable higher clarity and objectivity to assist with grading (see Dryad data repository, cases benign, and ISUP grade groups 1 to 523). The digital pathology prostate cancer atlas is a comprehensive resource supported by an online database which allows for enhanced learning by comparing observations made using traditional H&E staining and biomarker guided technology, minimising problems with inter-observer variation.
Imaging
For the digital pathology prostate cancer atlas (and Figures), whole slides of H&E stained or Appl1, Sortilin and Syndecan-1 labelled serial tissue sections were imaged using a digital slide scanner (Carl ZEISS AxioScan Z.1), at 40× magnification (Carl Zeiss Plan-Apochromat 40× NA 0.95) in brightfield. This magnification provided a good trade-off between acquisition speed, image data size and morphological resolution. All images were captured using the same scanning profile to ensure that the white balance, light illumination intensity and exposure times were identically acquired for each set of slides.
Data Records
All images were recorded using the Carl Zeiss Image format (*.CZI) using ZEISS Zen Blue software (version 3.7, Carl Zeiss GmbH, Jena, Germany) with the supplied acquisition workstation computer. Viewing and editing of images was also performed using Zen Blue software. All images, file names and metadata were de-identified from patient data, and a unique identifier was assigned to each image set, maintaining data integrity and separation. Patient outcome data was recorded in a secure password-protected and user access-restricted Microsoft Excel spreadsheet document (version 2302, Redmond, USA).
All digital micrographs used in the presented case studies are freely available via the online repository Dryrad23, along with the digital pathology prostate cancer atlas and an instructional video on how to fully utilise and interact with the atlas. Sample interpretation data from a panel of medical scientists is also available in comma-separated value (*.CSV) format for all the presented case studies.
Technical Validation
All cases were initially selected based upon the health records held directly by the bioresource manager or through the authorized custodian of the tissue samples. To ensure conformity with the Royal College of Pathologists of Australasia (RCPA) prostate cancer assessment guidelines (reported within the American Joint Committee on Cancer (AJCC) 2018 and guidelines updated by ISUP in the congress meeting of 2018), tissue sections were reviewed at two time points by independent clinical pathologists who were experienced in genitourinary cancers and focused particularly on prostate cancer. The first review was conducted by the pathologist associated with each bioresource, before sample inclusion into the study. Upon receipt of the samples for the research program, a tumour board (n = 11, chaired by J.J.O’L) also reviewed the pathology within each patient sample using routine pathology techniques before several pathologists (n = 6; Australia, New Zealand and Ireland), scientists (n = 4) and the tumour board (n = 11) assessed the same samples using the biomarkers Appl1, Sortilin and Syndecan-113,14.
Usage Notes
Our specially developed digital pathology prostate cancer atlas comprised of micrographs from the APCB cohort is designed to be user interactive, highlighting key cancer features for H&E and IHC-assisted ISUP grade group assessment; hence is presented as an interactive portable document format (PDF) and online resource. The digital pathology prostate cancer atlas is best viewed using Adobe Acrobat Reader software (Adobe Inc, San Jose, USA) to make full use of the PDF document’s functionality. The atlas begins with a front page, where users can select and click to access representative images of benign through to ISUP grade group 5 cases of prostate cancer. The supporting material for the atlas can be accessed at the bottom of the front page with a button linking to the back matter (Fig. 7A)23. After selecting a case, the overview page of the case will be shown along with de-identified information on the patient background. The user can then hover a cursor over the biomarkers Appl1, Sortilin and Syndecan-1 or the H&E buttons to view the respective staining or IHC biomarker labelling of the prostatectomy tissue samples (Fig. 7B). On the left-hand panel, the highlights button can be clicked, along with links to other cases and the home button to bring the user back to the front page. Moving to the highlights page, users can hover the cursor over specific cancer features listed on the left-hand panel, or over the prostatectomy to view a magnified image (Fig. 7C). Clicking on either the feature name on the left-hand panel or the highlighted square on the prostatectomy will bring the user to the selected highlights page, showing the user a more detailed higher magnification view of the cancer feature. A zoom in or zoom out button is centrally located on the feature page, and users can see lower or higher-powered magnifications of the selected feature (Fig. 7D).
The novel biomarkers, Appl1, Sortilin and Syndecan-1 have been proven to assist with H&E diagnosis, with improved grading and prognostic prediction accuracy of patient outcomes13,14,15,22. In addition, the biomarkers are able to assist with more accurate determination of specific histopathology, such as intraductal carcinoma of the prostate15 and high-grade prostatic intraepithelial neoplasia22. The biomarkers have been developed as an LDT, and are now currently used in clinical practise in the United States of America16. The digital pathology prostate cancer atlas acts as an interactive tool to help educate and assist clinicians to better diagnose patients with prostate cancer and achieve improved outcomes.
The biomarker technology is amenable to a digital pathology Artificial Intelligence (AI) solution to further remove subjective inter-observer variability and to assess specific aspects of prostate cancer pathology. Preliminary algorithms to improve the efficacy of an AI solution are already under development and algorithms will be integrated with machine learning to produce a precision medicine solution for prostate cancer tissue pathology assessment.
The digital pathology prostate cancer atlas was developed using Adobe InDesign (Adobe Inc, San Jose, USA). There was no custom code generated for this manuscript and is therefore not available. The digital micrographs can be opened using any imaging software able to open the BigTIFF image format.
Ethics approval and consent to participate
Approval was obtained from the Human Research Ethics Committee of the University of South Australia (Application IDs: 201907 and 36070). Patients with prostate cancer were accessed from several bioresources where their custodians, obtained informed consent to provide their samples to the bioresource.
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Acknowledgements
The authors would like to acknowledge the contributions of Ms Olivia Cameron and Ms Kyla Mount for their contributions in acquiring images for the digital pathology atlas.
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Intellectual input and concept development: C.M., J.M.L., A.S., B.S.-Y.U., M.C.C., I.R.D.J., L.K., R.D.B., J.L., C.R.M., S.Pra., S.K., H.S., B.D., P.T., K.M., L.M.B., J.J.O’L., D.A.B. Experimental design: C.M., J.M.L., A.S., C.G., I.R.D.J., S.K., L.M.B., J.J.O’L., D.A.B. Study coordination and funding: C.M., J.M.L., A.S., B.S.-Y.U., L.K., L.M.B., J.J.O’L., D.A.B. Data collection and interpretation, IHC, image analysis, figure preparation: C.M., J.M.L., A.S., B.S.-Y.U., M. C.C., C.R.M., I.R.D.J., L.K., C.H., R.D.B., J.L., S.M.H., S.Pra., S.K., H.S., B.D., K.M., L.M.B., J.J.O’L., D.A.B. Pathology interpretation: S.H., S.Pra., S.K., H.S., B.D., J.J.O’L. Biobank coordination, cohorts and patient information: L.M.B., S.Pra., C.R M., S.K., P.T., J.J.O’L. Manuscript drafting: B.S.-Y.U.*, C.M., J.M.L., L.K., M.C.C., C.R.M., S.M.H., S.Pra., B.D., H.S., S.S., P.T., L.M.B., J.J.O’L., D.A.B.*. Manuscript editing: All authors.
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Funding for this project was provided by Envision Sciences Pty Ltd, the University of South Australia, a Cancer Council SA Beat Cancer Grant, Movember Foundation/Prostate Cancer Foundation of Australia’s Research Program and the Australian Federal Government [NHMRC development grant GNT1092904 and MTP Connect Biomedical Translation Bridge Program grant BTBR200074]. L.M.B. was supported by a Beat Cancer SA Beat Cancer Project Principal Cancer Research Fellowship (PRF1117). D.A.B and I R.D.J. are from the University of South Australia, and L.M.B. is from the University of Adelaide and hold a patent WO2014197937A1 ‘Methods for Detecting Prostate Cancer’, which involves this manuscript (Original Patent). The Original Patent holders have appointed, UniSA Ventures Pty Ltd, the wholly owned commercialisation arm of the University of South Australia, to manage the commercialisation of the Original Patent. UniSA Ventures Pty Ltd has entered into arm’s length arrangements with Envision Sciences Pty Ltd under which UniSA Ventures will receive financial benefits from the successful commercialisation of the Original Patent. Envision Sciences Pty Ltd is a privately owned Australian company which is commercialising its work in the field of cancer diagnostics and holds additional patents including PCT/AU2020/050925 “Methods for Confirming Detection and Evaluating the Progression of a Prostate Cancer” involving the invention reported in this manuscript and is using this with the Original Patent under licence. Envision Sciences Pty Ltd has engaged the University of South Australia on arm’s length terms to conduct research and development work, including subject matter in this manuscript. D.A.B. is a professor and leader of the Mechanisms in Cell Biology and Disease Research Group in Clinical and Health Sciences at the University of South Australia. D.A.B. is a founding shareholder for Envision Sciences Pty Ltd and benefits from Envision Sciences Pty Ltd research funding. J. O’L is a shareholder and benefits from Envision Sciences Pty Ltd research funding. D.A.B., L.K., J.M.L., C.M., M.C.C., A.S., B.S.U., S.Pra., C. R. M., I.R.D.J., C.H., S.M.H., R.D.B., are employees of the University of South Australia, L.M.B. is an employee of Adelaide University and P. T. and J.J.O’L. is an employees of Trinity College Dublin and each receive benefit from the funding provided by Envision Sciences Pty Ltd, the University of South Australia and the Australian Federal Government, for their research work.
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Logan, J.M., Martini, C., Sorvina, A. et al. Reinterpretation of prostate cancer pathology by Appl1, Sortilin and Syndecan-1 biomarkers. Sci Data 11, 852 (2024). https://doi.org/10.1038/s41597-024-03696-0
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DOI: https://doi.org/10.1038/s41597-024-03696-0
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