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Published in final edited form as: Prostate Cancer Prostatic Dis. 2022 May 14;26(1):105–112. doi: 10.1038/s41391-022-00547-0

High intratumoral plasma cells content in primary prostate cancer defines a subset of tumors with potential susceptibility to immune-based treatments

Adam B Weiner 1, Christina Y Yu 2, Mitali Kini 1, Yang Liu 3, Elai Davicioni 3, Antonina Mitrofanova 2,4, Tamara L Lotan 5, Edward M Schaeffer 1,✉
PMCID: PMC10353550  NIHMSID: NIHMS1914450  PMID: 35568781

Abstract

BACKGROUND:

Data on advanced prostate cancer (PCa) suggest more prior systemic therapies might reduce tumor immune responsiveness. In treatment-naïve primary PCa, recent work correlated intratumoral plasma cell content with enhanced tumor immune-responsiveness. We sought to identify features of localized PCa at a high risk of recurrence following local treatment with high plasma cell content to help focus future immune-based neoadjuvant trials.

METHODS:

We performed retrospective analyses of molecular profiles from three independent cohorts of over 1300 prostate tumors. We used Wilcoxon Rank Sum to compare molecular pathways between tumors with high and low intratumoral plasma cell content and multivariable Cox proportional hazards regression analyses to assess metastasis-free survival.

RESULTS:

We validated an expression-based signature for intratumoral plasma cell content in 113 primary prostate tumors with both RNA-expression data and digital image quantification of CD138+ cells (plasma cell marker) based on immunohistochemisty. The signature showed castration-resistant tumors (n = 101) with more prior systemic therapies contained lower plasma cell content. In high-grade primary PCa, tumors with high plasma cell content were associated with increased predicted response to immunotherapy and decreased response to androgen-deprivation therapy. Master regulator analyses identified upregulated transcription factors implicated in immune (e.g. SKAP1, IL-16, and HCLS1), and B-cell activity (e.g. VAV1, SP140, and FLI-1) in plasma cell-high tumors. Master regulators overactivated in tumors with low plasma cell content were associated with shorter metastasis-free survival following radical prostatectomy.

CONCLUSIONS:

Markers of plasma cell activity might be leveraged to augment clinical trial targeting and selection and better understand the potential for immune-based treatments in patients with PCa at a high risk of recurrence following local treatment.

INTRODUCTION

Despite major advancements in immunotherapies for cancer, immune-based treatments for prostate cancer (PCa) have demonstrated only limited benefits for a subset of patients with advanced, metastatic castration-resistant PCa (mCRPC) [1, 2]. Given the high prevalence of PCa worldwide [3], enthusiasm for investigating immunotherapies for PCa remains [4].

Recent work showed patients with PCa with increased intratumor immune content and activity were more likely to have favorable responses to anti-CTLA4 immunotherapy [5]. However, patients in that trial that demonstrated favorable responses to immunotherapy had previously received on average fewer lines of systemic therapy (10 treatments/9 patients = 1.1) compared to patients with minimal (16/8 = 2) or unfavorable responses (25/10 = 2.5). Additionally, anti-CTLA4 immunotherapy prior to radical prostatectomy for patients with high-grade, localized PCa can induce an increase in immune cell infiltration [6]. Together, these findings suggest one potential manner to optimize the benefits of immune-based treatments would be to assess their benefits in patients with earlier stage, treatment naïve disease who are at high risk of recurrence following definitive local therapy [7].

Recent studies have implicated the roles of B-cells and plasma cells within the tumor microenvironment as markers of predicted response to immunotherapies in multiple cancers [8]. For instance, multiple studies showed subgroups of sarcoma, melanoma, and renal cell carcinoma enriched with B-cells were more responsive to immunotherapies [9–11]. Our group’s evaluation of primary PCa showed high intratumoral plasma cell content, and not CD8+ T-cells, was associated with increased immune activity and favorable prognosis following radical prostatectomy in independent cohorts [12]. These findings justify further investigations into the value of quantifying intratumoral plasma cell content in PCa. The question remains whether intratumoral plasma cell content could identify patients who would benefit from immune-based treatments. In this work, we validate an expression-based measure of intratumor plasma cell content and characterize molecular pathways in high-grade, localized PCa with high plasma cell content. We hypothesized tumors with high plasma cell content would possess biologically distinct molecular characteristics and differential predicted response to various treatments.

METHODS

Data sources

Study cohorts included in this work consisted of three datasets of molecular and clinical data: two from tumors sampled from radical prostatectomy (RP) specimens and one from biopsies of men with metastatic castration-resistant PCa (mCRPC). The first RP cohort from Johns Hopkins Medical Institute (JHMI; n = 498) was comprised of patients who underwent RP between 1995 and 2010 with no adjuvant treatments until end of follow-up or development of metastatic disease (Supplementary table 1) [13, 14]. The second RP cohort from the Decipher Genomic Resource Information Database (GRID; NCT02609269) was comprised of tumors collected prospectively from the clinical use of the Decipher RP test from December 2015 through September 2017 [15]. In this group, the study focused on those with high-grade (grade groups 4 or 5) tumors given the inherent interest in adjuvant treatments for this group of patients who are at high risk of recurrence following definitive treatment (n = 785; Supplementary table 2). Detailed information on these two cohorts including expression profiling and clinical outcomes has been previously described [16].

The mCRPC cohort was derived from the publicly available information describing the 2019 iteration of the Stand Up To Cancer (SU2C2019) dataset [17]. This study focused on patients in SU2C2019 with known information on previous exposures to taxane chemotherapy or androgen receptor signaling inhibitors (ARSi; abiraterone or enzalutamide) and only those with biopsies from bone to minimize the heterogeneity in tumor immune content related to biopsy site (n = 101; Supplementary table 3). Expression data from SU2C2019 was quantile matched to the microarray platform used for the GRID cohort.

Immune cell content

Tumor immune content was calculated using the ESTIMATE R package version 2.0.0 [18]. Tumor-invading lymphocytes were deconvoluted using the MySort tool (default version) implemented in an R function [19, 20]. The MySort tool produces the proportions of each immune cell type in each tumor. To apply these proportions to the immune content from ESTIMATE and avoid negative values, total immune content was the final immune score from ESTIMATE plus the constant of the minimum score in each cohort plus one.

CD138+ densities

Immunohistochemistry for CD138/syndecan-1, a marker of plasma cells, within the Johns Hopkins Medical Institute (JHMI) cohort (n = 113) was conducted using mouse monoclonal antibodies (B-A38, Ventana/Roche, pre-dilute) on the Ventana Benchmark platform in a CLIA-accredited laboratory. As previously described, we performed a manual quantification of CD138+ cell density blinded to clinical and patient characteristics [12]. Individual cells positive for CD138 were counted in each 0.6 mm diameter tissue core of tumors (average of four spots sampled per case), normalized by the total mm2 of tissue analyzed for each core calculated in QuPath version 0.1.2 [21], taking the mean across the four tumor cores for each patient. The manual quantification was done due to the observed patchy expression of CD138 in benign prostatic epithelium.

Expression-based signatures

Two signatures predictive of responses to immunotherapy were used. “Immunotherapy score 1” [22] and “Immunotherapy score 2” [23] were both developed and validated to predict clinical response to anti-programmed cell death protein 1 (anti-PD-1) therapies. The androgen receptor (AR) activity signature was based on the weighted expression of nine canonical androgen receptor transcriptional target genes (KLK3, KLK2, FKBP5, STEAP1, STEAP2, PPAP2A, RAB3B, ACSL3, and NKX3-1) validated to measure tumors androgen receptor output and response to androgen deprivation therapy [24]. Radiation therapy response score was based on the Post-Operative RadioTherapy Outcomes Score (PORTOS) [25]. Genomic risk classifier was defined as an expression-based score validated specifically for PCa to predict risk of disease recurrence following local treatment with higher scores (0.0–1.0) predicting an increased risk [26]. Tumor immunophenoscores and their major and minor parameters were calculated as previously described [27].

Master regulator analysis

Master regulator (MR) analyses were performed using the MARINa algorithm [28, 29] on the plasma cell signature and VIPER algorithm [30] on single-patient level which are available for download at http://califano.c2b2.columbia.edu/software/ and as viper R package from Bioconductor, using the same parameters as described previously [30, 31]. MARINa and VIPER analyses were applied in Decipher Genomic Resource Information Database (GRID; n = 784) and JHMI (n = 498) cohorts, separately. Note that one sample (DPR011934.CEL) from GRID was removed from the analysis as an outlier identified from principal components analysis (PCA) using the prcomp function in R.

For MARINa analysis, the plasma cell signature was used to define as a ranked list of genes based on their differential expression (two-sides Welch t-test) between plasma cell-high (content greater than mean + 1 standard deviation) and plasma cell-low tumors in the GRID cohort and utilized to query prostate-cancer-specific regulatory network (interactome), as reconstructed in Aytes et al. [31]. VIPER analysis was applied to GRID and JHMI datasets separately, where in each dataset, patient samples were scaled (z-scored) on a gene-level prior to conducting the analyses, which allowed applying VIPER algorithm on a single patient level. MR activity levels expressed as normalized enrichment scores from VIPER analysis on the JHMI cohort were utilized for multivariable Cox proportional hazards survival analysis, with metastatic recurrence as the endpoint. In survival analyses, high MR activity was defined as any tumor above the upper quartile of activity within the JHMI cohort.

REMARK reporting

This study complied with REMARK reporting guidelines for prognostic tumor biomarkers (Appendix) [32].

Statistics

All statistical tests were conducted using R Studio version 1.2.5019 (Boston, MA) and only two-sided p values were generated. Following MR analysis and calculation of MR activity level (see above), each tumor in JHMI was divided by low versus high activity level based on the upper quartile of activity level for each regulator. Multivariable Cox proportional hazards regression analyses were performed to calculate the hazard ratio (HR) and 95% confidence interval (CI) for high versus low activity for each master regulator adjusting for grade group, log-transformed serum prostate-specific antigen (PSA), and organ confined versus not organ confined disease as noted in Supplementary table 1.

RESULTS

Expression-based signature for plasma cells content validated by immunohistochemistry

CD138+ density, an immune cell marker specific to plasma cells on immunohistochemistry was quantified in 113 tumors from the JHMI cohort (Materials). Spearman’s correlation ρ and false discovery rate (FDR)-adjusted P values were calculated between CD138+ density and each immune cell type content deconvoluted (Fig. 1 and Supplementary table 4). Plasma cell content was the only cell type significantly associated with CD138+ density validating the expression-based signature as a marker of plasma cell content in PCa.

Fig. 1. Immunohistochemistry validation of the plasma cell signature.

Fig. 1

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In primary prostate tumors from the JHMI cohort with immunohistochemistry data (n = 113), plasma cell content based on an expression signature was the only immune cell type that correlated significantly with CD138+ density (Shading is 95% confidence level interval for predictions from a linear model). Abbreviations: JHMI Johns Hopkins Medical Institute, FDR false discovery rate.

Plasma cell content decreases following systemic therapies and defines a biologically distinct subgroup of high-risk tumors

In advanced PCa, tumors from patients who received fewer systemic treatments had more pre-treatment tumor immune content and favorable responses to anti-CTLA4 immunotherapy [5]. In bone biopsies of mCRPC in the SU2C2019 cohort, tumors from patients who were not previously exposed to taxane chemotherapy or androgen receptor signaling inhibitors (ARSi; abiraterone or enzalutamide) possessed higher plasma cell content than those with previous treatment exposures (Fig. 2a and Supplementary table 5). Prior work in advanced PCa have implicated B-cells in immunosuppression and tumor immune evasion [33, 34]. We previously showed increased intratumoral plasma cell content was associated with increased immune activity within primary PCa [12]. Discrepancies in the tumor microenvironments inflammatory cytokine milieu which induce differential antibody isotype switch could account for the heterogeneous (pro-tumorogenic versus anti-tumorogenic) roles of plasma cells in PCa [12]. Guo et al. showed increasing expression of CD38 (a marker of many immune-cells including mature, plasma cells) was associated with immunosuppressive pathways and worse oncologic outcomes for patients with CRPC [34]. In primary PCa, CD38 expression only weakly correlated with CD138+ density and deconvoluted plasma cell content (Fig. 2b, c). Together, these findings in advanced PCa suggest systemic therapies or tumor progression coincide with a relative resistance to anti-tumor immune responses and upregulation of immunosuppressive pathways.

Fig. 2. Plasma cell content in mCRPC.

Fig. 2

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a In bone biopsy specimens from the Stand Up to Cancer 2019 cohort, tumors without prior exposure to taxane chemotherapy or ARSi had increased plasma cell content (Wilcoxon Rank Sum; center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range). b, c In previous studies of mCRPC, higher intratumoral CD38 expression was associated with increased immune suppression. However, in primary tumors CD38 expression did not correlate with quantified CD138+ density on immunohistochemistry or plasma cell content based on the expression signature (Shading is 95% confidence level interval for predictions from a linear model). Abbreviations: mCRPC metastatic castration-resistant prostate cancer, ARSi androgen receptor signaling inhibitor, JHMI Johns Hopkins Medical Institute.

In that context, we sought to characterize plasma cell content in early stage, treatment naïve, high-grade PCa. This disease group has a significant potential for progression to lethal disease following definitive treatment and may benefit from neoadjuvant treatments [7]. Within the GRID cohort (n = 785), high-grade tumors with high plasma cell content possessed similar genomic risk scores based on a validated expression-based score suggesting similar phenotype in terms of predicted aggressiveness (Methods and Fig. 3a, b). Patients with high genomic risk scores might benefit from adjuvant or early salvage treatments following radical prostatectomy. Notably, despite similar genomic risk scores, tumors with high plasma cell content had predicted increased responses to immunotherapy and radiation therapy, and lower androgen receptor output suggesting differential benefits from certain treatments (Fig. 3b). These findings suggest despite having similarly aggressive phenotypes compared to primary high-grade tumors with low plasma cell content, tumors with high plasma cell content might benefit more from immune-based treatments and less from androgen deprivation therapy following initial definitive treatment.

Fig. 3. Expression-based biomarkers in high-grade localized prostate cancer based on plasma cell content.

Fig. 3

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a Within the Genomic Resource Information Database (GRID) cohort (high-grade primary prostate cancer; n = 785), tumors with high plasma cell content were defined as content greater than the mean expression + 1 standard deviation. b Despite having similar genomic risk scores, tumors with high plasma cell content were predicted to have more favorable responses to immunotherapies and RT and lower AR-activity suggesting greater resistance to androgen deprivation therapy (all Wilcoxon Rank Sum; center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range). Abbreviations: AR androgen receptor, RT radiation therapy.

Immune-based pathways are upregulated in tumors with high plasma cell content

Using the validated components of the immunophenoscore (Methods), high-grade tumors within the GRID cohort were noted to be associated with immune pathways associated with increased immune activity (e.g. increased HLA expression; Fig. 4a). Accordingly, tumors with high plasma cell content were associated with increased pathways in effector cells and antigen presentation, decreased pathways in checkpoint/immunomodulators and suppressor cells, and overall high immunophenoscores suggesting predicted increased response to immunotherapy (Fig. 4b).

Fig. 4. Immune pathways in high-grade localized prostate cancer based on plasma cell content.

Fig. 4

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a Within the Genomic Resource Information Database (GRID) cohort (high-grade primary prostate cancer; n = 785), tumors with high plasma cell content expressed increased pathways in immune activation (Wilcoxon Rank Sum FDR P values; above dashed line represents FDR P < 0.05) resulting in immunophenoscores suggestive of increased susceptibilities to immunotherapies (b); Wilcoxon Rank Sum; center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range). Abbreviation: FDR false discovery rate.

We then sought to identify immune-related transcriptional regulatory programs to explain the increased immune pathways in tumors with high plasma cell content. For this, we categorized tumors in the GRID cohort as plasma cell-high and plasma cell-low (Methods). This signature was then subjected to Master Regulator (MR) MARINa analysis, which utilized prostate-cancer specific transcriptional regulatory network (interactome) and identified MRs based on enrichment (differential expression) of their transcriptional targets (Methods). From the top 10 MRs, this analysis identified seven MRs with increased activity in plasma cell-high tumors and three with decreased activity (Fig. 5a). To confirm the MR activity patterns across patients in plasma cell-high and plasma cell-low patient groups, we performed single-patient VIPER analyses in the GRID cohort. While there was some heterogeneity in the differentially activated MRs among tumors with high plasma cell content, most expressed a similar pattern (Fig. 5b).

Fig. 5. Master regulators in primary prostate cancer with high plasma cell content.

Fig. 5

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a Within the GRID cohort (n = 784), MR analysis revealed transcription factors with activated (red bars) and repressed (blue bars) activity in tumors with high plasma cell content. Differential activity is computed based on the expression of transcriptional targets of a given MR. Differential expression is based on the expression of the MR itself. Red, white, and blue indicate increased, none, and low activity or expression in tumors with high plasma cell content, respectively. b There was minimal heterogeneity in the plasma cell-high tumors related to differentially activated MRs. c Multivariable Cox proportional hazards regressions within the Johns Hopkins Medical Institute cohort (n = 498), adjusting for serum prostate-specific antigen, tumors stage, and tumors grade (Methods), showed the three MRs overactivated in plasma cell-low tumors were associated with shorter time to development of metastases following radical prostatectomy. Abbreviations: MR master regulator, HR hazard ratio, CI confidence interval, GRID Genomic Resource Information Database.

The MR most over-activated in plasma cell-high tumors was VAV1 (Vav Guanine Nucleotide Exchange Factor 1) which has been implicated in B-cell maturation [35]. The MR most over-activated in plasma cell-low tumors was TRIM24 (tripartite motif-containing protein 24) which has previously been shown to augment androgen receptor output in SPOP mutant PCa [36]. To explore association of the activity levels of the 10 MRs with tumor aggressiveness, we estimated activity levels for these 10 MRs on a single-patient level in the JHMI cohort using VIPER algorithm and utilized them as inputs into Cox proportional hazards models with metastatic recurrence as the end-point. In multivariable Cox proportional hazards regressions adjusting for tumor grade and stage, and serum PSA, the three MRs with increased activity in tumors with low plasma cell content, including TRIM24, were each significantly associated with shorter time to metastatic recurrence following surgery (Fig. 5c).

DISCUSSION

PCa possesses many immunosuppressive mechanisms and is often deemed immunogenically “cold” [4]. Immunotherapy responsiveness has recently been associated with intratumoral plasma cells in many tumor types [8]. Increased intratumoral plasma cell content in primary PCa is associated with IgG expression in the tumor microenvironment and improved oncologic outcomes following surgery [12]. In the context of continued enthusiasm to investigate immune-based treatments for PCa, we characterized the molecular pathways within PCa from patients with high-grade, localized disease with high plasma cell content. In this group of patients, adjuvant treatments are of clinical interest to reduce the high risk of cancer recurrence following definitive treatment [7]. Our results indicate intratumoral plasma cell content defines primary PCa with distinct treatment vulnerabilities, upregulated immunogenic pathways, and differentially activated MRs. Together these results suggest measuring intratumoral plasma cells could optimize patient selection for immune-based treatments in clinical trials. Characterizing pathways to engage plasma cell activity in PCa might augment tumor immune responsiveness.

In this work, we validated an expression-based marker of intratumoral plasma cell content with immunohistochemistry. In prostatectomy specimens, CD138+ density correlated significantly only with the expression-based marker of plasma cells and no other cell types suggesting the marker was specific for plasma cells in PCa. Importantly, in mCRPC we showed tumors from patients who received fewer systemic treatments expressed higher plasma cell content. These findings should encourage further investigation of plasma cell content in earlier stage PCa. Notably, however, the SU2C2019 dataset did not include data on time between treatment and biopsy which limits assessing the relation between timing of systematic therapies and plasma cell content.

We chose to limit molecular pathway analyses to high-grade PCa since these men experience higher rates of disease recurrence warranting adjuvant or salvage treatments [7]. The current work is limited by the use of expression-based markers and signatures to define molecular pathways. While each marker used was previously validated in prior works, the conclusions drawn here should be interpreted as justification for future prospective clinical and experimental evaluation.

Additionally, expression data in the GRID cohort, which is derived from the commercial use of a genomic risk classifier for PCa, represents a high scale platform for future assessment of immune-based expression markers. Previous work has already applied the GRID platform to data from major clinical trial data [37, 38]. While RNA degradation in formalin-fixed paraffin-embedded tumor samples is a concern and another inherent limitation for creating a quantifiable cut-off for any expression biomarker [39], creating the cut-off on the GRID platform and applying it prospectively in the same platform could optimize uniformity.

Within the GRID cohort, high-grade tumors were predicted to have similarly aggressive phenotype based on a genomic risk classifier. Yet, plasma cell-high tumors were predicted to be more susceptible to immunotherapies and radiation therapy. Accordingly, plasma cell-high tumors were enriched with immune-activating pathways while plasma cell-low tumors were enriched for immunosuppressing pathways. In MR analyses, plasma cell-high tumors possessed greater activity of many transcription factors previously associated with increased immune activity (e.g. SKAP1, IL-16, and HCLS1) [40–42] and specifically B cell maturity and activity (e.g. VAV1, SP140, and FLI-1) [35, 43, 44]. Previous trial data has shown treatment with anti-CTLA4 therapy can induce an increase in tumor immune infiltration prior to prostatectomy, however the tumor microenvironment demonstrates resultant immunosuppressive responses [6]. These MRs represent potential targets for augmenting the tumor immune response in PCa in the setting of immune-based treatments.

Plasma cell-high tumors also expressed less androgen receptor activity suggesting lower responsiveness to androgen deprivation therapy, a commonly used adjuvant or salvage therapy [45]. Accordingly, the most differentially activated MR in plasma cell-low tumors was TRIM24 which has previously been associated with augmented androgen receptor output in PCa [36]. SND1 (Staphylococcal nuclease domain-containing protein (1) and SLC30A9 (Solute carrier family 30A9) were also over activated in plasma cell-low tumors and have been previously associated with increasing grade in PCa [46, 47]. In this work, overexpression of each MR overactivated in plasma cell-low tumors was associated with shorter time to metastatic disease following surgery. Further characterization of these transcription factors in experimental design could further elucidate the root of the aggressive phenotype noted in plasma cell-low tumors [12].

In conclusion, these results provide further insight into the prognostic value of intratumoral plasma cell content in primary PCa. Given recent work demonstrating a connection between intratumoral B-cell content and response to immunotherapy in other tumor types, [9–11] future work investigating their role in PCa treatment response is warranted. The expression-based marker validated here or other markers of plasma cell activity might be leveraged to augment and better understand the potential for immune-based treatments in patients with primary PCa at a high risk for recurrence following definitive local treatment.

Supplementary Material

Supplementary Material
Appendix

ACKNOWLEDGEMENTS

This work was supported in part by the National Institutes of Health grants 5U01CA196390 (EMS) and R01LM013236 (AM), the Prostate Cancer Foundation (EMS), Department of Defense grant W81XWH-15-1-0661 (EMS and TLL), American Cancer Society grant RSG-21-023-01-TBG (AM, EMS), and New Jersey Commission on Cancer Research grant COCR21RBG00 (AM).

Footnotes

COMPETING INTERESTS

YL and ED are employees of Veracyte, Inc. The remaining authors declare no potential conflicts of interest.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

The study was performed in accordance with the Declaration of Helsinki.

Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41391-022-00547-0.

DATA AVAILABILITY

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material
NIHMS1914450-supplement-Supplementary_Material.pdf (35KB, pdf)
Appendix
NIHMS1914450-supplement-Appendix.docx (23.1KB, docx)

Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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