Development and validation of a quantitative reactive stroma biomarker (qRS) for prostate cancer prognosis

Morphologic patterns observed in prostate biopsy cases with discrepant grade group and molecular risk classification

BACKGROUND

Molecular-based risk classifier tests are increasingly being utilized by urologists and radiation oncologists to guide clinical decision making. The Decipher prostate biopsy test is a 22-gene RNA biomarker assay designed to predict likelihood of high-grade disease at radical prostatectomy and risk of metastasis and mortality. The test provides a risk category of low, intermediate, or high. We investigated histologic features of biopsies in which the Grade Group (GG) and Decipher risk category (molecular risk) were discrepant.

METHODS

Our institutional urologic outcomes database was searched for men who underwent prostate biopsies with subsequent Decipher testing from 2016 to 2020. We defined discrepant GG and molecular risk as either GG1-2 with high Decipher risk category or GG ≥ 3 with low Decipher risk category. The biopsy slide on which Decipher testing was performed was re-reviewed for GG and various histologic features, including % Gleason pattern 4, types of Gleason pattern 4 and 5, other "high risk" features (e.g., complex papillary, ductal carcinoma, intraductal carcinoma [IDC]), and other unusual and often "difficult to grade" patterns (e.g., atrophic carcinoma, mucin rupture, pseudohyperplastic carcinoma, collagenous fibroplasia, foamy gland carcinoma, carcinoma with basal cell marker expression, carcinoma with prominent vacuoles, and stromal reaction). Follow-up data was also obtained from the electronic medical record.

RESULTS

Of 178 men who underwent prostate biopsies and had Decipher testing performed, 41 (23%) had discrepant GG and molecular risk. Slides were available for review for 33/41 (80%). Of these 33 patients, 23 (70%) had GG1-2 (GG1 n = 5, GG2 n = 18) with high Decipher risk, and 10 (30%) had GG ≥ 3 with low Decipher risk. Of the 5 GG1 cases, one case was considered GG2 on re-review; no other high risk features were identified but each case showed at least one of the following "difficult to grade" patterns: 3 atrophic carcinoma, 1 collagenous fibroplasia, 1 carcinoma with mucin rupture, and 1 carcinoma with basal cell marker expression. Of the 18 GG2 high Decipher risk cases, 2 showed GG3 on re-review, 5 showed large cribriform and/or other high risk features, and 10 showed a "difficult to grade" pattern. Of the 10 GG ≥ 3 low Decipher risk cases, 5 had known high risk features including 2 with large cribriform, 1 with IDC, and 1 with Gleason pattern 5.

CONCLUSIONS

In GG1-2 high Decipher risk cases, difficult to grade patterns were frequently seen in the absence of other known high risk morphologic features; whether these constitute true high risk cases requires further study. In the GG ≥ 3 low Decipher risk cases, aggressive histologic patterns such as large cribriform and IDC were observed in half (50%) of cases; therefore, the molecular classifier may not capture all high risk histologic patterns.

Proposal for an optimised definition of adverse pathology (unfavourable histology) that predicts metastatic risk in prostatic adenocarcinoma independent of grade group and pathological stage

AIMS

Histological grading of prostate cancer is a powerful prognostic tool, but current criteria for grade assignment are not fully optimised. Our goal was to develop and test a simplified histological grading model, based heavily on large cribriform/intraductal carcinoma, with optimised sensitivity for predicting metastatic potential.

METHODS AND RESULTS

Two separate non-overlapping cohorts were identified: a 419-patient post-radical prostatectomy cohort with long term clinical follow-up and a 209-patient post-radical prostatectomy cohort in which all patients had pathologically confirmed metastatic disease. All prostatectomies were re-reviewed for high-risk histological patterns of carcinoma termed 'unfavourable histology'. Unfavourable histology is defined by any classic Gleason pattern 5 component, any large cribriform morphology (> 0.25 mm) or intraductal carcinoma, complex intraluminal papillary architecture, grade 3 stromogenic carcinoma and complex anastomosing cord-like growth. For the outcome cohort, Kaplan-Meier analysis compared biochemical recurrence, metastasis and death between subjects with favourable and unfavourable histology, stratified by pathological stage and grade group. Multivariable Cox proportional hazards models evaluated adding unfavourable histology to the Memorial Sloan Kettering Cancer Center (MSKCC) post-prostatectomy nomogram and stratification by percentage of unfavourable histology. At 15 years unfavourable histology predicted biochemical recurrence, with sensitivity of 93% and specificity of 88%, metastatic disease at 100 and 48% and death at 100 and 46%. Grade group 2 prostate cancers with unfavourable histology were associated with metastasis independent of pathological stage, while those without had no risk. Histological models for prediction of metastasis based on only large cribriform/intraductal carcinoma or increasing diameter of cribriform size improved specificity, but with lower sensitivity. Multivariable Cox proportional hazards models demonstrated that unfavourable histology significantly improved discriminatory power of the MSKCC post-prostatectomy nomogram for biochemical failure (likelihood ratio test P < 0.001). In the retrospective review of a separate RP cohort in which all patients had confirmed metastatic disease, none had unequivocal favourable histology.

CONCLUSIONS

Unfavourable histology at radical prostatectomy is associated with metastatic risk, predicted adverse outcomes better than current grading and staging systems and improved the MSKCC post-prostatectomy nomogram. Most importantly, unfavourable histology stratified grade group 2 prostate cancers into those with and without metastatic potential, independent of stage. While unfavourable histology is driven predominantly by large cribriform/intraductal carcinoma, the recognition and inclusion of other specific architectural patterns add to the sensitivity for predicting metastatic disease. Moreover, a simplified dichotomous model improves communication and could increase implementation.

Overexpression of Fibroblast Activation Protein (FAP) in stroma of proliferative inflammatory atrophy (PIA) and primary adenocarcinoma of the prostate

Fibroblast activation protein (FAP) is a serine protease upregulated at sites of tissue remodeling and cancer that represents a promising therapeutic and molecular imaging target. In prostate cancer, studies of FAP expression using tissue microarrays are conflicting, such that its clinical potential is unclear. Furthermore, little is known regarding FAP expression in benign prostatic tissues. Here we demonstrated, using a novel iterative multiplex IHC assay in standard tissue sections, that FAP was nearly absent in normal regions, but was increased consistently in regions of proliferative inflammatory atrophy (PIA). In carcinoma, FAP was expressed in all cases, but was highly heterogeneous. High FAP levels were associated with increased pathological stage and cribriform morphology. We verified that FAP levels in cancer correlated with CD163+ M2 macrophage density. In this first report to quantify FAP protein in benign prostate and primary tumors, using standard large tissue sections, we clarify that FAP is present in all primary prostatic carcinomas, supporting its potential clinical relevance. The finding of high levels of FAP within PIA supports the injury/regeneration model for its pathogenesis and suggests that it harbors a protumorigenic stroma. Yet, high levels of FAP in benign regions could lead to false positive FAP-based molecular imaging results in clinically localized prostate cancer.

Stroma-specific gene expression signature identifies prostate cancer subtype with high recurrence risk

Current prognostic tools cannot clearly distinguish indolent and aggressive prostate cancer (PC). We hypothesized that analyzing individual contributions of epithelial and stromal components in localized PC (LPC) could improve risk stratification, as stromal subtypes may have been overlooked due to the emphasis on malignant epithelial cells. Hence, we derived molecular subtypes of PC using gene expression analysis of LPC samples from prostatectomy patients (cohort 1, n = 127) and validated these subtypes in two independent prostatectomy cohorts (cohort 2, n = 406, cohort 3, n = 126). Stroma and epithelium-specific signatures were established from laser-capture microdissection data and non-negative matrix factorization was used to identify subtypes based on these signatures. Subtypes were functionally characterized by gene set and cell type enrichment analyses, and survival analysis was conducted. Three epithelial (E1-E3) and three stromal (S1-S3) PC subtypes were identified. While subtyping based on epithelial signatures showed inconsistent associations to biochemical recurrence (BCR), subtyping by stromal signatures was significantly associated with BCR in all three cohorts, with subtype S3 indicating high BCR risk. Subtype S3 exhibited distinct features, including significantly decreased cell-polarity and myogenesis, significantly increased infiltration of M2-polarized macrophages and CD8 + T-cells compared to subtype S1. For patients clinically classified as CAPRA-S intermediate risk, S3 improved prediction of BCR. This study demonstrates the potential of stromal signatures in identification of clinically relevant PC subtypes, and further indicated that stromal characterization may enhance risk stratification in LPC and may be particularly promising in cases with high prognostic ambiguity based on clinical parameters.

Quantification of collagen content and stromal cellularity within reactive stroma is predictive of prostate cancer biochemical recurrence and specific death

Semiquantitative reactive stromal grading has been shown to be a predictor of biochemical recurrence and prostate cancer (PCa) specific death. It has been extensively validated. In this study we tested novel technologies to introduce quantitative measures of host response, in particular collagen content and stromal cellularity. We use 3 large retrospective cohorts, the Baylor College of Medicine cohort, the Brady cohort and the Pound cohort. Slides were stained and digitized using image deconvolution and analyzed using image segmentation and image analyses. PicroSirius red stain histochemical stains were used for collagen quantification. Area of cancer and stroma were measured independently, without regard to quality of stroma. Cellularity, in each compartment, was measured using image deconvolution, image segmentation and image analysis. Two biomarkers were tested in 3 independent cohorts with two endpoints, biochemical recurrence and prostate cancer specific death. Stromal cellularity (qCollCell) and stromal collagen area (qCollArea) are independently predictive biochemical recurrence in the Hopkins Brady cohort, particularly in Gleason 6-7 patients. Multivariate analysis demonstrated that increased stroma cellularity (qCollCell) was a significant predictor of PCa specific death, when compared to an established model of PCa, in the Baylor cohort. Stromal collagen (qCollArea) independently predicts PCa-specific death in the Hopkins Pound cohort. The introduction of a computerized quantitative test of the host response increases the probability that this test will be reproducible in other cohorts. The ability to improve prediction of prostate cancer specific death might lie in the study of the host and its response.

'High proliferative cribriform prostate cancer' defines a patient subgroup with an inferior prognosis

AIMS

A cribriform pattern, reactive stroma (RS), PTEN, Ki67 and ERG are promising prognostic biomarkers in primary prostate cancer (PCa). We aim to determine the relative contribution of these factors and the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) score in predicting PCa prognosis.

METHODS AND RESULTS

We included 475 patients who underwent radical prostatectomy (2010-12, median follow-up = 8.7 years). Cribriform pattern was identified in 57% of patients, PTEN loss in 55%, ERG expression in 51%, RS in 39% and high Ki67 in 9%. In patients with multiple samples from the same malignant focus and either PTEN loss or high Ki67, intrafocal heterogeneity for PTEN and Ki67 expression was detected in 55% and 89%, respectively. In patients with samples from two or more foci, interfocal heterogeneity was detected in 46% for PTEN and 6% for Ki67. A cribriform pattern and Ki67 were independent predictors of biochemical recurrence (BCR) and clinical recurrence (CR), whereas ERG expression was an independent predictor of CR. Besides CAPRA-S, a cribriform pattern provided the highest relative proportion of explained variation for predicting BCR (11%), and Ki67 provided the highest relative proportion of explained variation for CR (21%). In patients with a cribriform pattern, high Ki67 was associated with a higher risk of BCR [hazard ratio (HR) = 2.83, P < 0.001] and CR (HR = 4.35, P < 0.001).

CONCLUSIONS

High Ki67 in patients with a cribriform pattern identifies a patient subgroup with particularly poor prognosis, which we termed 'high proliferative cribriform prostate cancer'. These results support reporting a cribriform pattern in pathology reports, and advocate implementing Ki67.

"Stromal cells in prostate cancer pathobiology: friends or foes?"

The genomic, epigenetic and metabolic determinants of prostate cancer pathobiology have been extensively studied in epithelial cancer cells. However, malignant cells constantly interact with the surrounding environment-the so-called tumour microenvironment (TME)-which may influence tumour cells to proliferate and invade or to starve and die. In that regard, stromal cells-including fibroblasts, smooth muscle cells and vasculature-associated cells-constitute an essential fraction of the prostate cancer TME. However, they have been largely overlooked compared to other cell types (i.e. immune cells). Indeed, their importance in prostate physiology starts at organogenesis, as the soon-to-be prostate stroma determines embryonal epithelial cells to commit toward prostatic differentiation. Later in life, the appearance of a reactive stroma is linked to the malignant transformation of epithelial cells and cancer progression. In this Review, we discuss the main mesenchymal cell populations of the prostate stroma, highlighting their dynamic role in the transition of the healthy prostate epithelium to cancer. A thorough understanding of those populations, their phenotypes and their transcriptional programs may improve our understanding of prostate cancer pathobiology and may help to exploit prostate stroma as a biomarker of patient stratification and as a therapeutic target.