Moving Beyond Gleason Scoring.
But by the 1950s, prostate cancer (PCa) research was behind that of tumors from other sites. Loss of "basement membrane" or "basal cell layer loss" and perineural and vascular invasion were identified as aggressive features for PCa. Eventually, several histologic differentiation classifications evolved. The MD Anderson classification (MDAH) was a 4-tiered system based on the percentage of tumor that formed glands (based on the Broders system). (3) Mostofi proposed a 3-grade system that used both degree of glandular differentiation and nuclear atypia. (3) Bocking used 4 histologic patterns and 3 degrees of nuclear atypia. (3) But it was not until Gleason proposed his classification that clinicians and pathologists eventually coalesced around 1 standardized system.
Over many years Gleason created a very significant body of work. His early work in 1966 identified that his patterns were associated to survival rates (n = 270). (4) But his collaboration with G. T. Mellinger in the Veterans Affairs Cooperative Urological Research Group provided him with a unique resource to validate his findings. His seminal 1974 article (5) remains the only large prospective biomarker development study for PCa. The article clearly showed the potential of the Gleason scoring (GL). The emphasis was on the combination with staging, and the study population received different treatments. Gleason's work was validated by most of the preeminent urologic pathology groups, (6-10) and the Gleason system became accepted as the preferred grading method for PCa. There is no question that the Gleason grading system carries significant predictive information in the preoperative and postoperative settings.
LIMITATIONS OF THE GLEASON SYSTEM
Like most other cancer grading systems, GL concentrates on the characteristics of the cancer cell and how it resembles the prostate glandular differentiation. A low Gleason grade shows the greatest similarity to the glandular tissue of origin, while high Gleason grades show the greatest divergence from glandular forms. The emphasis is clearly on the cancer cell and its patterns.
There have been many attempts to improve the Gleason system in the last 3 decades. Most have refined or redefined Gleason's criteria. (6,8,9) Others have added information to the Gleason-based models into tables or nomograms, which are the current standard of care. (11-18) Other current attempts to improve the models use additional molecular information, either at the DNA, RNA, or methylation level. (19-22) These have been moderately successful, because at the core, they measure the characteristics of the cancer cell, where GL excels. Prediction of PCa is almost exclusively based on looking at the characteristics of the cancer cell proper, either at its ability to resemble tissues of origin or at the molecular level.
The validity of GL as a predictive biomarker has been clearly demonstrated in numerous studies. It has been repeatedly shown that having a high GL (8-10) carries a much higher risk than having a lower GL (6-7). In other words, a higher percentage of patients with a GL of 8 to 10 will die of PCa than those with GL 6 or 7. This risk assessment information is clearly important for an individual with PCa. But, if we analyze the patient population that died of PCa in our database, the results are puzzling. Almost 60% of those who died specifically of PCa had glandular tumors, GL 6 or 7 (Figure 1).
This finding reflects the fact that a clear majority of patients with PCa have a GL 6 or 7 tumor (only 10%-15% have GL 8-10). Although a small percentage of the patients with GL 6 or 7 die of PCa, most of the patients who die of PCa have GL 6 or 7 tumors, as the patients with GL 6 or 7 vastly outnumber the others. We will demonstrate in subsequent sections that stromogenic carcinoma identifies, independently of GL, the patients at risk in the largest category of patients with PCa. Gleason scoring allows for variability in the GL 7 subset (3+4 and 4+3), but this distinction losses predictive model significance when incorporating stromogenic carcinoma. (23) Hence, while the Gleason scoring system has been of critical importance, there is a need for development beyond its reach.
EARLY WORKS ON HOST RESPONSE AS A BIOMARKER
In most human cancer types, invasion is defined by the host's response upon extension of the cancer cells beyond the basal membrane. But the breach of basal membrane is not visible on hematoxylin-eosin staining at light microscopic magnifications. Therefore, invasion is defined by the desmoplastic stromal response that follows the breach of the basement layer. The visible event is therefore modification in host response to the cancer. And this change is manifested to our eyes by changes in structure and color. In a fatty lamina propria (Figure 2, A), the presence of a myofibroblastic cellular component and accumulation of extracellular matrix (Figure 2, B) is visible as a simple change from white to pink (Figure 2, D and E). The prostate is different. It does not have a fatty lamina propria. The smooth muscle fibers surround prostate glands almost directly (Figure 2, C) (in the absence of inflammation). The change in color associated with desmoplasia in the prostate is not as obvious, from magenta to pink (Figure 2, E and F). It follows that desmoplastic response in the prostate is best identified by using structure, rather than color (Figure 3). Figure 3A shows a glandular cancer sitting in smooth muscle and without host response. Figure 3B shows a glandular cancer with exuberant desmoplastic reactive stroma, yet the lack of significant color changes makes it difficult to assess. The structural changes are best noted in the black and white versions of 3A and 3B in 3C and 3D, respectively. A detailed description of reactive stroma in PCa is presented in the article by De Vivar et al. (24) Suffice it to say that reactive stroma has 2 main transformations. The smooth muscle with its characteristic well-defined cytoplasmic borders is replaced by myofibroblasts (tumor-associated fibroblasts), which have a syncytial growth pattern (Figure 4, A and C). Additionally, there are deposits of varying extracellular matrix material, which varies in color from pink (Figure 4, A) to blue (Figure 4, B and D). We described 3 histologic subtypes for easy identification:
1. Extracellular matrix rich, or the classically described stromogenic carcinoma, characterized by the angularity of the cancerous glands and the accumulation of extensive amounts of extracellular matrix.
2. Myofibroblastic reactive stroma, characterized by the presence of a cellular stroma, with features of muscle differentiation organized in a wispy pattern, but at loss of muscle architecture (bundling).
3. Edematous reactive stroma with edematous areas within the reactive stroma.
We have not identified any independent prognostic value for these histologic subtypes.
The host's response, desmoplasia or reactive stroma, is biologically critical to PCa. The literature on biology of reactive stroma (the myofibroblast or tumor-activated fibroblasts in PCa) far outweighs what we have been able to identify in the pathology literature. Reactive stromal cells have been associated with increased tumor growth in vitro and in vivo. (25,26)
In late 1998 we started collaborating with one of the authors (D. R.) who had made significant scientific accomplishments on the biology of prostate gland stromal cells and myofibroblasts. However, there was no translation to human disease. We reported that reactive stroma initiated early, during high-grade prostatic intraepithelial neoplasia in approximately 50% of sites, and that reactive stroma was composed of fibroblasts and myofibroblasts with different marker expression profiles and matrix production. This was the first report showing that reactive stroma in prostate cancer was defined by the presence of myofibroblasts and altered extracellular matrix. Subsequent studies showed that reactive stroma was associated with an elevated rate of angiogenesis and was tumor-promoting. (27)
The histologic changes associated with reactive stroma in prostate cancer are subtle, owing to the limitations stated previously, but they are evident upon a focused examination of the stroma. In 1990 we started a project using trichrome stains, which make the reactive stroma changes more visible. In this study, a priori and based on preliminary observations, we created a reactive stroma grading (RSG) system. We learned that reactive stroma is highly variable in PCa, with most cases having little or no reactive stroma. In this initial study we used the Baylor College of Medicine cohort, with greater than 600 patients with more than 20 years of follow-up. Tumors with 0% to 5% stroma were given an RSG of 0. Tumors with 5% to 15% reactive stroma were assigned RSG 1 and from 15% to 50%, RSG 2. Tumors with greater than 50% reactive stroma were given RSG 3. Hence, RSG 3 exhibits at least a 1:1 ratio of reactive stroma to epithelium. We identified that patients with RSG 0 (no stroma) or patients with RSG 3 had a mean survival time of 69.02 months as compared to 106. (33) months for RSG 1 or 2.28 This distinction was independently significant in the patients with GL 7.
We concentrated our efforts on RSG 3, since the clear majority of patients with RSG 0 had a high Gleason grade. We consequently converted a 4-tiered grading system into a binary system. RSG 3 was either present or not. We subsequently termed the RSG 3 as stromogenic carcinoma. Stromogenic carcinoma is a rare event, and cases with more than 50% reactive stroma are even more rare, but so are patients who die of PCa using our current definition of cancer. It is important to note that we have tested other thresholds such as 30% and the presence of any reactive stroma, without success.
We used quantification of stromogenic carcinoma on hematoxylin-eosin sections (Figure 4) to demonstrate that it was an independent predictor of recurrence (hazard ratio = 1.953; P = .02) on preoperative biopsies, independent of Gleason subset 4+3 and 3+4 in patients with a GL of 7.23 Finally, we measured the percentage of stromogenic carcinoma on more than 800 whole-mounted radical prostatectomy specimens to identify the percentage of tumor that had stromogenic carcinoma. Patients with higher RSG 3 percentages (larger tumor areas with RSG 3) had a significantly decreased biochemical recurrence-free survival and PCa-specific death-free survival than those with a lower RSG 3 percentage, even within the GL 7 subset of patients. (29) We created nomograms for both biopsies and radical prostatectomies. We later described the transcriptomic changes found in reactive stroma. (30) This is the scope of our published data on stromogenic carcinoma, with other validation studies of our own in new populations forthcoming soon.
VALIDATION OF STROMOGENIC CARCINOMA
These data, although substantial, need external validation. And this validation has come from several independent studies. The most recent is from the Canary group. McKenney and colleagues (31) showed, in 1275 patients with GL 6 and GL7 carcinomas, that reactive stromal patterns were associated with worse recurrence-free survival. They concluded that "a reactive stromal response was the strongest histologic prognostic factor in grade 3+3=6 and 3+4=7 groups by multivariable analysis" and that "As stromal response is not currently evaluated in the routine histologic assessment of prostate cancer, its unrecognized presence leads to a significant underestimate of risk in this aggressive set of prostate cancers." (31)
Another excellent study from Norway used a population strategy approach, this being one of the most difficult tasks in biomarker development. The authors (32) identified 318 patients with biopsy-proven PCa and without evidence of systemic metastasis at the time of diagnosis in Aust-Agder County (100,000 inhabitants) in the period 1991-1999. The 10-year PCa-specific survival rate for RSGs of 0, 1, 2, and 3 was 96%, 81%, 69%, and 63%, respectively (P < .005). RSG remained independently associated with PCa-specific death in a multivariate Cox regression analysis adjusting for prostatic specific antigen (PSA), clinical stage, Gleason score, and mode of treatment. (32) The authors also published on the relationship between reactive stroma grading and perineural invasion (33) and lymphovascular invasion. (34) Like our results, a group from Brazil (35) found that stromogenic carcinoma predicts biochemical recurrence on univariate but not multivariate analysis (266 patients). Unfortunately, a GL7 subset was not included in their analysis. Finally, a group from China (36) has shown a significant association between reactive stroma grade in tumors and the occurrence of castration-resistant PCa in patients with a Gleason score of 6 or 7 (P < .00).
Stromogenic carcinoma occurs with high Gleason grades but data are inconsistent as to its risk profile, at our current definition (50%). It is likely that higher Gleason grades will need greater reactive stroma to be clinically significant, as our unpublished data suggest. Therefore, at this time we suggest that the proven value of stromogenic carcinoma is best identified in patients with GL 6 and 7, and therefore this is the patient population that would benefit most from its use.
There are sufficient data, currently published, or to be published soon, about reactive stroma grading or stromogenic carcinoma to support its incorporation in clinical practice. Stromogenic carcinoma has been validated by 5 independent groups, in at least 3 continents (Europe, Asia, and the Americas) and with more than 4000 patients. Clearly, stromogenic carcinoma has predictive ability for PCa. The presence of stromogenic carcinoma in a biopsy specimen significantly increases risk recurrence or PCa-specific death.
ON THE RATIONALE FOR COMBINING GLEASON AND STROMOGENIC CARCINOMA
We conclude that differential alterations in the tumor microenvironment may explain PCa diversity and aggressiveness. We have shown that the microenvironment provides significant predictive information that can help define indolent and lethal phenotypes of PCa. Distinction of indolent PCa (GL 6-7 without stromogenic carcinoma) from stroma-independent (GL 8-10) and stroma-dependent or stromogenic PCa (Gleason 6-7 with stromogenic pattern) can only be done by incorporating measures of the stromal response to current predictive tools (Figure 5). Neither system alone can capture information that is present in both. More importantly, lack of recognition of stromogenic carcinoma in GL 6 or 7 tumors greatly underestimates the risk of patients with PCa.
Further studies will look at the reproducibility of this biomarker. We believe that recognizing stromogenic carcinoma is straightforward, since we have made it into a binary test with an easily recognizable cutoff, at least a 1:1 ratio between the amount of reactive stroma and cancer cells. The Canary cohort slides were reviewed independently at The Cleveland Clinic (Cleveland, Ohio) and the McGovern School of Medicine (Houston, Texas). We individually reached almost identical statistical results. However, like all other semiquantitative studies they will have known limitations. Most other semiquantitative biomarkers have issues with reproducibility, including high grade prostatic intraepithelial neoplasia and GL. (7,37) For this reason, our current studies are looking at technologic advancements to improve on reproducibility. The results are very encouraging.
The biological reasoning behind developing a predictive model of PCa, based on the tumor microenvironment, is based on several key publications. So was D. F. Gleason's work. We propose that combining the information from the cancer and the host response is critical for improving prediction. We find a strong historical background to support this merger. Broders' response to Dukes' article on cancer staging was to publish a new article showing that the combination of his cancer grading and Dukes' cancer staging provided better prognostication than either method alone. (38) The time has come for us to incorporate measures of host response into the arsenal of elements we use to predict cancer survival, without abandoning what we know works.
Finally, the Surveillance, Epidemiology, and End Results Program (SEER) data for cancer-type death rates show that PCa has one of the lowest cancer-specific mortalities of all cancers (1.4% at 5 years). We must wonder if the lack of host response elements to define a cancer as truly invasive, as happens in most other cancers, could be hindering our ability to define actual prostate cancer. Further studies are required.
Accepted for publication October 11, 2018.
Published as an Early Online Release March 13, 2019.
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Brian Miles, MD; Michael Ittmann, MD, PhD; Thomas Wheeler, MD; Mohammad Sayeeduddin, BS; Antonio Cubilla, MD; David Rowley, PhD; Ping Bu, MD; Yi Ding, PhD; Yan Gao, MD; MinJae Lee, PhD; Gustavo E. Ayala, MD
From the Department of Urology, The Methodist Hospital, Houston, Texas (Dr Miles); the Departments of Pathology & Immunology (Drs Ittmann and Wheeler and Mr Sayeeduddin) and Molecular and Cell Biology (Dr Rowley), Baylor College of Medicine, Houston, Texas; Instituto de Patologia e Investigacion, Asuncion, Paraguay (Dr Cubilla); Biostatistics/Epidemiology/Research Design (BERD) Core, Departments of Internal Medicine (Dr Lee) and Pathology and Laboratory Medicine (Drs Bu, Ding, Gao, and Ayala), University of Texas Health Sciences Center Medical School, Houston.
Dr Ayala is owner of the company Stromont, which will hold property over automated biomarker systems. This company is currently being developed. The other authors have no relevant financial interest in the products or companies described in this article.
Corresponding author: Gustavo E. Ayala, MD, Department of Pathology and Laboratory Medicine, University of Texas Health Sciences Center Medical School, 6431 Fannin Street, Houston, TX 77030 (email: Gustavo.E.Ayala@uth.tmc.edu).
Caption: Figure 2. A, Adipose tissue present in the lamina propria of most epithelia, with (D) capturing the predominant color in (A), namely, white. B, Reactive stroma, generic, with (E) capturing the most common color, namely, pink. C, Smooth muscle stroma in the prostate, with (F) showing the predominant color in (C), namely, magenta. The human eye can easily identify a change from white to pink, while the change from magenta to pink is more difficult to detect (hematoxylin-eosin, original magnifications X100 [A and B] and X200 [C]).
Caption: Figure 3. A, Prostate cancer (PCa) gland sitting in smooth muscle, without reactive stroma. B, A malignant prostate gland with surrounding reactive stroma. C and D, Black-and-white images of (A) and (B), respectively. They demonstrate that the histologic changes associated with reactive stroma in PCa are best seen when based on structure, rather than color (hematoxylin-eosin, original magnification X400 [A through D]).
Caption: Figure 4. Four representative cases of stromogenic prostate cancer. The desmoplastic response is at least 50% of the tumor and characterized by the presence of myofibroblasts, where the well-defined cytoplasmic borders of smooth muscle are replaced by a syncytial growth pattern of myofibroblast (best seen in [C]). Additionally, there are deposits of varying extracellular matrix material, which varies in color from pink (A) to blue (B and D) (hematoxylin-eosin, original magnification X200 [A through D]).
Caption: Figure 5. Indolent prostate cancer (PCa) is characterized by glandular tumors, sitting in muscle, without a host response. In contrast, there are 2 types of lethal PCas. The classic lethal PCa can be identified by Gleason scoring and molecular tests and is characterized by loss of glandular differentiation. Additionally, glandular tumors (Gleason score 6-7) with intense stromal response, or stromogenic carcinoma, are as lethal as the previous category. Lack of recognition of this category greatly underestimates the risk of patients with PCa.
Figure 1. Population of patients who have died specifically of prostate cancer in the Baylor Prostate SPORE database. Most patients had glandular tumors, Gleason score 6 or 7 (red). Gleason 8 18% Gleason 9 14% Gleason 10 7% Gleason 6 14% Gleason 7 47% Note: Table made from pie chart.
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|Author:||Miles, Brian; Ittmann, Michael; Wheeler, Thomas; Sayeeduddin, Mohammad; Cubilla, Antonio; Rowley, Da|
|Publication:||Archives of Pathology & Laboratory Medicine|
|Date:||May 1, 2019|
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