Integrating Tumor-Intrinsic and Immunologic Factors to Identify Immunogenic Breast Cancers from a Low-Risk Cohort: Results from the Randomized SweBCG91RT Trial.

PURPOSE: The local immune infiltrate's influence on tumor progression may be closely linked to tumor-intrinsic factors. The study aimed to investigate whether integrating immunologic and tumor-intrinsic factors can identify patients from a low-risk cohort who may be candidates for radiotherapy (RT) de-escalation. EXPERIMENTAL DESIGN: The SweBCG91RT trial included 1,178 patients with stage I to IIA breast cancer, randomized to breast-conserving surgery with or without adjuvant RT, and followed for a median of 15.2 years. We trained two models designed to capture immunologic activity and immunomodulatory tumor-intrinsic qualities, respectively. We then analyzed if combining these two variables could further stratify tumors, allowing for identifying a subgroup where RT de-escalation is feasible, despite clinical indicators of a high risk of ipsilateral breast tumor recurrence (IBTR). RESULTS: The prognostic effect of the immunologic model could be predicted by the tumor-intrinsic model (Pinteraction = 0.01). By integrating measurements of the immunologic- and tumor-intrinsic models, patients who benefited from an active immune infiltrate could be identified. These patients benefited from standard RT (HR, 0.28; 95% CI, 0.09-0.85; P = 0.025) and had a 5.4% 10-year incidence of IBTR after irradiation despite high-risk genomic indicators and a low frequency of systemic therapy. In contrast, high-risk tumors without an immune infiltrate had a high 10-year incidence of IBTR despite RT treatment (19.5%; 95% CI, 12.2-30.3). CONCLUSIONS: Integrating tumor-intrinsic and immunologic factors may identify immunogenic tumors in early-stage breast cancer populations dominated by ER-positive tumors. Patients who benefit from an activated immune infiltrate may be candidates for RT de-escalation.

Development and Validation of a Genomic Profile for the Omission of Local Adjuvant Radiation in Breast Cancer.

PURPOSE: Adjuvant radiotherapy (RT) is used for women with early-stage invasive breast cancer treated with breast-conserving surgery. However, some women with low risk of recurrence may safely be spared RT. This study aimed to identify these women using a molecular-based approach. METHODS: We analyzed two randomized trials of women with node-negative invasive breast cancer to ± RT following breast-conserving surgery: SweBCG91-RT (stage I-II, no adjuvant systemic therapy) and Princess Margaret (age 50 years or older, T1-T2, adjuvant tamoxifen). Transcriptome-wide profiling was performed (Affymetrix Human Exon 1.0 ST microarray). Patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative tumors and with gene expression data were included. The SweBCG91-RT cohort was divided into training (N = 243) and validation (N = 354) cohorts. A 16-gene signature named Profile for the Omission of Local Adjuvant Radiation (POLAR) was trained to predict locoregional recurrence (LRR) using elastic net regression. POLAR was then validated in the SweBCG91-RT validation cohort and the Princess Margaret cohort (N = 132). RESULTS: Patients categorized as POLAR low-risk without RT had a 10-year LRR of 6% (95% CI, 2 to 16) and 7% (0 to 27) in SweBCG91-RT and Princess Margaret cohorts, respectively. There was no significant benefit from RT in POLAR low-risk patients (hazard ratio [HR], 1.1 [0.39 to 3.4], P = .81, and HR, 1.5 [0.14 to 16], P = .74, respectively). Patients categorized as POLAR high-risk had a significant decreased risk of LRR with RT (HR, 0.43 [0.24 to 0.78], P = .0055, and HR, 0.25 [0.07 to 0.92], P = .038, respectively). An exploratory analysis testing for interaction between RT and POLAR in the combined validation cohort was performed (P = .066). CONCLUSION: The novel POLAR genomic signature on the basis of LRR biology may identify patients with a low risk of LRR despite not receiving RT, and thus may be candidates for RT omission.

Prognosis Associated With Luminal and Basal Subtypes of Metastatic Prostate Cancer.

IMPORTANCE: Luminal and basal subtypes of primary prostate cancer have been shown to be molecularly distinct and clinically important in predicting response to therapy. These subtypes have not been described in metastatic prostate cancer. OBJECTIVES: To identify clinical and molecular correlates of luminal and basal subtypes in metastatic castration-resistant prostate cancer (mCRPC) and investigate differences in survival, particularly after treatment with androgen-signaling inhibitors (ASIs). DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, a retrospective analysis was conducted of 4 cohorts with mCRPC (N = 634) across multiple academic centers. Treatment was at the physicians' discretion. Details of the study cohorts have been published elsewhere between 2016 and 2019. Data were analyzed from March 2018 to February 2021. MAIN OUTCOMES AND MEASURES: The primary clinical end point was overall survival from the date of tissue biopsy/molecular profiling. Luminal and basal subtypes were also stratified by postbiopsy ASI treatment. The primary molecular analyses included associations with small cell/neuroendocrine prostate cancer (SCNC), molecular pathways, and DNA alterations. RESULTS: In the 634 patients, 288 (45%) had tumors classified as luminal, and 346 (55%) had tumors classified as basal. However, 53 of 59 (90%) SCNC tumors were basal (P < .001). Similar to primary prostate cancer, luminal tumors exhibited overexpression of AR pathway genes. In basal tumors, a significantly higher rate of RB1 loss (23% basal vs 4% luminal; P < .001), FOXA1 alterations (36% basal vs 27% luminal; P = .03) and MYC alterations (73% basal vs 56% luminal; P < .001) were identified. Patients with basal tumors had worse overall survival compared with those with luminal tumors only in patients treated with an ASI postbiopsy (East Coast Dream Team: hazard ratio [HR], 0.39; 95% CI, 0.20-0.74; P = .004; West Coast Dream Team: HR, 0.57; 95% CI, 0.33-0.97; P = .04). Among patients with luminal tumors, those treated with an ASI had significantly better survival (HR, 0.27; 95% CI, 0.14-0.53; P < .001), whereas patients with basal tumors did not (HR, 0.62; 95% CI, 0.36-1.04, P = .07). The interaction term between subtype and ASI treatment was statistically significant (HR, 0.42; 95% CI, 0.20-0.89; P = .02). CONCLUSIONS AND RELEVANCE: These findings represent the largest integrated clinical, transcriptomic, and genomic analysis of mCRPC samples to date, and suggest that mCRPC can be classified as luminal and basal tumors. Analogous to primary prostate cancer, these data suggest that the benefit of ASI treatment is more pronounced in luminal tumors and support the use of ASIs in this population. In the basal tumors, a chemotherapeutic approach could be considered in some patients given the similarity to SCNC and the diminished benefit of ASI therapy. Further validation in prospective clinical trials is warranted.

Immune Infiltrate in the Primary Tumor Predicts Effect of Adjuvant Radiotherapy in Breast Cancer; Results from the Randomized SweBCG91RT Trial.

PURPOSE: Tumor-infiltrating immune cells play a key role in tumor progression. The purpose of this study was to analyze whether the immune infiltrate predicts benefit from postoperative radiotherapy in a large randomized breast cancer radiotherapy trial. EXPERIMENTAL DESIGN: In the SweBCG91RT trial, patients with stage I and II breast cancer were randomized to breast-conserving surgery (BCS) and postoperative radiotherapy or to BCS only and followed for a median time of 15.2 years. The primary tumor immune infiltrate was quantified through two independent methods: IHC and gene expression profiling. For IHC analyses, the absolute stromal area occupied by CD8+ T cells and FOXP3+ T cells, respectively, was used to define the immune infiltrate. For gene expression analyses, immune cells found to be prognostic in independent datasets were pooled into two groups consisting of antitumoral and protumoral immune cells, respectively. RESULTS: An antitumoral immune response in the primary tumor was associated with a reduced risk of breast cancer recurrence and predicted less benefit from adjuvant radiotherapy. The interaction between radiotherapy and immune phenotype was significant for any recurrence in both the IHC and gene expression analyses (P = 0.039 and P = 0.035) and was also significant for ipsilateral breast tumor recurrence in the gene expression analyses (P = 0.025). CONCLUSIONS: Patients with an antitumoral immune infiltrate in the primary tumor have a reduced risk of any recurrence and may derive less benefit from adjuvant radiotherapy. These results may impact decisions regarding postoperative radiotherapy in early breast cancer.

A Signature That May Be Predictive of Early Versus Late Recurrence After Radiation Treatment for Breast Cancer That May Inform the Biology of Early, Aggressive Recurrences.

PURPOSE: Unmet clinical needs in breast cancer (BC) management include the identification of patients at high risk of local failure despite adjuvant radiation and an understanding of the biology of these recurrences. We previously reported a radiation response signature and here extend those studies to identify a signature predictive of recurrence timing (before or after 3 years). METHODS AND MATERIALS: Two independent patient cohorts were used. The training cohort included 119 patients with in-breast tumor recurrence (343 total), and the validation testing cohort had 16 patients with recurrences (112 total). All patients received radiation treatment after breast-conserving surgery. Initial feature selection used Spearman rank correlation, and a linear model was trained and locked before testing and validation. Cox regression was used for univariate and multivariable analyses (UVA and MVA, respectively). Biologically related concepts were identified using gene set enrichment analysis. RESULTS: Spearman correlation identified 485 genes whose expression was significantly associated with recurrence time (early vs late). Feature reduction further refined the list to 41 genes retained within the signature. In training, the correlation of score to recurrence time was 0.85 (P value < 1.3 × 10-31) with an area under the curve (AUC) of 0.91. Application of this early versus late signature to an independent BC testing and validation set accurately identified patients with early versus late recurrences (Spearman correlation = 0.75, P value = .001, AUC = 0.92, sensitivity = 0.75, specificity = 1.0, positive predictive value = 1.0, and negative predictive value = 0.8). Unique associations of breast cancer intrinsic subtype to timing of local recurrence were identified. In UVA and MVA the early versus late recurrence signature remained the most significant factor associated with recurrence. Gene set enrichment analysis identified proliferation and epidermal growth factor receptor concepts associated with early recurrences and luminal and ER-signaling pathways associated with late recurrences. Knockdown of genes associated with the early and late recurrences demonstrated novel effects on proliferation and clonogenic survival, respectively. CONCLUSIONS: We report a breast cancer gene signature that may identify patients unlikely to respond to adjuvant radiation and may be used to predict timing of recurrences with implications for potential treatment intensification and duration of follow-up for women with breast cancer treated with radiation.

Comprehensive Transcriptomic Profiling Identifies Breast Cancer Patients Who May Be Spared Adjuvant Systemic Therapy.

PURPOSE: There is currently no molecular signature in clinical use for adjuvant endocrine therapy omission in breast cancer. Given the unique trial design of SweBCG91-RT, where adjuvant endocrine and chemotherapy were largely unadministered, we sought to evaluate the potential of transcriptomic profiling for identifying patients who may be spared adjuvant endocrine therapy. EXPERIMENTAL DESIGN: We performed a whole-transcriptome analysis of SweBCG91-RT, a randomized phase III trial of ± radiotherapy after breast-conserving surgery for node-negative stage I-IIA breast cancer. Ninety-two percent of patients were untreated by both adjuvant endocrine therapy and chemotherapy. We calculated 15 transcriptomic signatures from the literature and combined them into an average genomic risk, which was further used to derive a novel 141-gene signature (MET141). All signatures were then independently examined in SweBCG91-RT and in the publicly available METABRIC cohort. RESULTS: In SweBCG91-RT, 454 patients were node-negative, postmenopausal, and systemically untreated with ER-positive, HER2-negative cancers, which constitutes a low-risk subgroup and potential candidates for therapy omission. Most transcriptomic signatures were highly prognostic for distant metastasis, but considerable discordance was observed on the individual patient level. Within the MET141 low-risk subgroup (lowest 25th percentile of scores), 95% of patients were free of metastasis at 15 years, even in the absence of adjuvant endocrine therapy. In a clinically low-risk subgroup of the METABRIC cohort not treated with systemic therapy, no breast cancer death occurred among the MET141 low-risk patients. CONCLUSIONS: Transcriptomic profiling identifies patients with an excellent outcome without any systemic adjuvant therapy in clinically low-risk patients of the SweBCG91-RT and METABRIC cohorts.

Clinicogenomic Radiotherapy Classifier Predicting the Need for Intensified Locoregional Treatment After Breast-Conserving Surgery for Early-Stage Breast Cancer.

PURPOSE: Most patients with early-stage breast cancer are treated with adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) to prevent locoregional recurrence (LRR). However, no genomic tools are used currently to select the optimal RT strategy. METHODS: We profiled the transcriptome of primary tumors on a clinical grade assay from the SweBCG91-RT trial, in which patients with node-negative breast cancer were randomly assigned to either whole-breast RT after BCS or no RT. We derived a new classifier, Adjuvant Radiotherapy Intensification Classifier (ARTIC), comprising 27 genes and patient age, in three publicly available cohorts, then independently validated ARTIC for LRR in 748 patients in SweBCG91-RT. We also compared previously published genomic signatures for ability to predict benefit from RT in SweBCG91-RT. RESULTS: ARTIC was highly prognostic for LRR in patients treated with RT (hazard ratio [HR], 3.4; 95% CI, 2.0 to 5.9; P < .001) and predictive of RT benefit (Pinteraction = .005). Patients with low ARTIC scores had a large benefit from RT (HR, 0.33 [95% CI, 0.21 to 0.52], P < .001; 10-year cumulative incidence of LRR, 6% v 21%), whereas those with high ARTIC scores benefited less from RT (HR, 0.73 [95% CI, 0.44 to 1.2], P = .23; 10-year cumulative incidence of LRR, 25% v 32%). In contrast, none of the eight previously published signatures were predictive of benefit from RT in SweBCG91-RT. CONCLUSION: ARTIC identified women with a substantial benefit from RT as well as women with a particularly elevated LRR risk in whom whole-breast RT was not sufficiently effective and, thus, in whom intensified treatment strategies such as tumor-bed boost, and possibly regional nodal RT, should be considered. To our knowledge, ARTIC is the first classifier validated as predictive of benefit from RT in a phase III clinical trial with patients randomly assigned to receive or not receive RT.

DNA-Dependent Protein Kinase Drives Prostate Cancer Progression through Transcriptional Regulation of the Wnt Signaling Pathway.

PURPOSE: Protein kinases are known to play a prominent role in oncogenic progression across multiple cancer subtypes, yet their role in prostate cancer progression remains underexplored. The purpose of this study was to identify kinases that drive prostate cancer progression.Experimental Design: To discover kinases that drive prostate cancer progression, we investigated the association between gene expression of all known kinases and long-term clinical outcomes in tumor samples from 545 patients with high-risk disease. We evaluated the impact of genetic and pharmacologic inhibition of the most significant kinase associated with metastatic progression in vitro and in vivo. RESULTS: DNA-dependent protein kinase (DNAPK) was identified as the most significant kinase associated with metastatic progression in high-risk prostate cancer. Inhibition of DNAPK suppressed the growth of both AR-dependent and AR-independent prostate cancer cells. Gene set enrichment analysis nominated Wnt as the top pathway associated with DNAPK. We found that DNAPK interacts with the Wnt transcription factor LEF1 and is critical for LEF1-mediated transcription. CONCLUSIONS: Our data show that DNAPK drives prostate cancer progression through transcriptional regulation of Wnt signaling and is an attractive therapeutic target in aggressive prostate cancer.

Xenograft-based, platform-independent gene signatures to predict response to alkylating chemotherapy, radiation, and combination therapy for glioblastoma.

BACKGROUND: Predictive molecular biomarkers to select optimal treatment for patients with glioblastoma and other cancers are lacking. New strategies are needed when large randomized trials with correlative molecular data are not feasible. METHODS: Gene signatures (GS) were developed from 31 orthotopic glioblastoma patient-derived xenografts (PDXs), treated with standard therapies, to predict benefit from radiotherapy (RT-GS), temozolomide (Chemo-GS), or the combination (ChemoRT-GS). Independent validation was performed in a heterogeneously treated clinical cohort of 502 glioblastoma patients with overall survival as the primary endpoint. Multivariate Cox analysis was used to adjust for confounding variables and evaluate interactions between signatures and treatment. RESULTS: PDX models recapitulated the clinical heterogeneity of glioblastoma patients. RT-GS, Chemo-GS, and ChemoRT-GS were correlated with benefit from treatment in the PDX models. In independent clinical validation, higher RT-GS scores were associated with increased survival only in patients receiving RT (P = 0.0031, hazard ratio [HR] = 0.78 [0.66-0.92]), higher Chemo-GS scores were associated with increased survival only in patients receiving chemotherapy (P < 0.0001, HR = 0.66 [0.55-0.8]), and higher ChemoRT-GS scores were associated with increased survival only in patients receiving ChemoRT (P = 0.0001, HR = 0.54 [0.4-0.74]). RT-GS and ChemoRT-GS had significant interactions with treatment on multivariate analysis (P = 0.0009 and 0.02, respectively), indicating that they are bona fide predictive biomarkers. CONCLUSIONS: Using a novel PDX-driven methodology, we developed and validated 3 platform-independent molecular signatures that predict benefit from standard of care therapies for glioblastoma. These signatures may be useful to personalize glioblastoma treatment in the clinic and this approach may be a generalizable method to identify predictive biomarkers without resource-intensive randomized trials.

The Immune Landscape of Prostate Cancer and Nomination of PD-L2 as a Potential Therapeutic Target.

BACKGROUND: Immunotherapy has been less successful in treating prostate cancer than other solid tumors. We sought to better understand the immune landscape in prostate cancer and identify immune-related biomarkers and potential therapeutic targets. METHODS: We analyzed gene expression data from 7826 prospectively collected prostatectomy samples (2013-2016), and 1567 retrospective samples with long-term clinical outcomes, for a total of 9393 samples, all profiled on the same commercial clinical platform in a CLIA-certified lab. The primary outcome was distant metastasis-free survival (DMFS). Secondary outcomes included biochemical recurrence-free survival (bRFS), prostate cancer-specific survival (PCSS), and overall survival (OS). All statistical tests were two-sided. RESULTS: Unsupervised hierarchical clustering of hallmark pathways demonstrated an immune-related tumor cluster. Increased estimated immune content scores based on immune-specific genes from the literature were associated with worse bRFS (hazard ratio [HR] = 1.26 [95% confidence interval [CI] = 1.12 to 1.42]; P < .001), DMFS (HR = 1.34 [95% CI = 1.13 to 1.58]; P < .001), PCSS (HR = 1.53 [95% CI = 1.21 to 1.92]; P < .001), and OS (HR = 1.27 [95% CI = 1.07 to 1.50]; P = .006). Deconvolution using Cibersort revealed that mast cells, natural killer cells, and dendritic cells conferred improved DMFS, whereas macrophages and T-cells conferred worse DMFS. Interestingly, while PD-L1 was not prognostic, consistent with its low expression in prostate cancer, PD-L2 was expressed at statistically significantly higher levels (P < .001) and was associated with worse bRFS (HR = 1.17 [95% CI = 1.03 to 1.33]; P = .01), DMFS (HR = 1.25 [95% CI = 1.05 to 1.49]; P = .01), and PCSS (HR = 1.45 [95% CI = 1.13 to 1.86]; P = .003). PD-L2 was strongly associated with immune-related pathways on gene set enrichment analysis suggesting that it is playing an important role in immune modulation in clinical prostate cancer samples. Furthermore, PD-L2 was correlated with radiation response pathways, and also predicted response to postoperative radiation therapy (PORT) on multivariable interaction analysis (P = .03). CONCLUSION: In the largest study of its kind to date, these results illustrate the complex relationship between the tumor-immune interaction, prognosis, and response to radiotherapy, and nominate PD-L2 as a potential novel therapeutic target in prostate cancer, potentially in combination with radiotherapy.

Clinical and Genomic Implications of Luminal and Basal Subtypes Across Carcinomas.

PURPOSE: Carcinomas originate from epithelial tissues, which have apical (luminal) and basal orientations. The degree of luminal versus basal differentiation in cancer has been shown to be biologically important in some carcinomas and impacts treatment response. EXPERIMENTAL DESIGN: Although prior studies have focused on individual cancer types, we used a modified clinical-grade classifier (PAM50) to subtype 8,764 tumors across 22 different carcinomas into luminal A, luminal B, and basal-like tumors. RESULTS: We found that all epithelial tumors demonstrated similar gene expression-based luminal/basal subtypes. As expected, basal-like tumors were associated with increased expression of the basal markers KRT5/6 and KRT14, and luminal-like tumors were associated with increased expression of the luminal markers KRT20. Luminal A tumors consistently had improved outcomes compared with basal across many tumor types, with luminal B tumors falling between the two. Basal tumors had the highest rates of TP53 and RB1 mutations and copy number loss. Luminal breast, cervical, ovarian, and endometrial tumors had increased ESR1 expression, and luminal prostate, breast, cervical, and bladder tumors had increased androgen receptor (AR) expression. Furthermore, luminal B tumors had the highest rates of AR and ESR1 mutations and had increased sensitivity in vitro to bicalutamide and tamoxifen. Luminal B tumors were more sensitive to gemcitabine, and basal tumors were more sensitive to docetaxel. CONCLUSIONS: This first pan-carcinoma luminal/basal subtyping across epithelial tumors reveals global similarities across carcinomas in the transcriptome, genome, clinical outcomes, and drug sensitivity, emphasizing the biological and translational importance of these luminal versus basal subtypes.

Development and Validation of a Prostate Cancer Genomic Signature that Predicts Early ADT Treatment Response Following Radical Prostatectomy.

Purpose: Currently, no genomic signature exists to distinguish men most likely to progress on adjuvant androgen deprivation therapy (ADT) after radical prostatectomy for high-risk prostate cancer. Here we develop and validate a gene expression signature to predict response to postoperative ADT.Experimental Design: A training set consisting of 284 radical prostatectomy patients was established after 1:1 propensity score matching metastasis between adjuvant-ADT (a-ADT)-treated and no ADT-treated groups. An ADT Response Signature (ADT-RS) was identified from neuroendocrine and AR signaling-related genes. Two independent cohorts were used to form three separate data sets for validation (set I, n = 232; set II, n = 435; set III, n = 612). The primary endpoint of the analysis was postoperative metastasis.Results: Increases in ADT-RS score were associated with a reduction in risk of metastasis only in a-ADT patients. On multivariable analysis, ADT-RS by ADT treatment interaction term remained associated with metastasis in both validation sets (set I: HR = 0.18, Pinteraction = 0.009; set II: HR = 0.25, Pinteraction = 0.019). In a matched validation set III, patients with Low ADT-RS scores had similar 10-year metastasis rates in the a-ADT and no-ADT groups (30.1% vs. 31.0%, P = 0.989). Among High ADT-RS patients, 10-year metastasis rates were significantly lower for a-ADT versus no-ADT patients (9.4% vs. 29.2%, P = 0.021). The marginal ADT-RS by ADT interaction remained significant in the matched dataset (Pinteraction = 0.035).Conclusions: Patients with High ADT-RS benefited from a-ADT. In combination with prognostic risk factors, use of ADT-RS may thus allow for identification of ADT-responsive tumors that may benefit most from early androgen blockade after radical prostatectomy. We discovered a gene signature that when present in primary prostate tumors may be useful to predict patients who may respond to early ADT after surgery. Clin Cancer Res; 24(16); 3908-16. ©2018 AACR.

Multigene Profiling of CTCs in mCRPC Identifies a Clinically Relevant Prognostic Signature.

The trend toward precision-based therapeutic approaches dictated by molecular alterations offers substantial promise for men with metastatic castration-resistant prostate cancer (mCRPC). However, current approaches for molecular characterization are primarily tissue based, necessitating serial biopsies to understand changes over time and are limited by the challenges inherent to extracting genomic material from predominantly bone metastases. Therefore, a circulating tumor cell (CTC)-based assay was developed to determine gene expression across a panel of clinically relevant and potentially actionable prostate cancer-related genes. CTCs were isolated from the whole blood of mCRPC patients (n = 41) and multiplex qPCR was performed to evaluate expression of prostate cancer-related target genes (n = 78). A large fraction of patients (27/41, 66%) had detectable CTCs. Increased androgen receptor (AR) expression (70% of samples) and evidence of Wnt signaling (67% of samples) were observed. The TMPRSS2:ERG fusion was expressed in 41% of samples, and the aggressive prostate cancer-associated long noncoding RNA SChLAP1 was upregulated in 70%. WNT5a [HR 3.62, 95% confidence interval (CI), 1.63-8.05, P = 0.002], AURKA (HR 5.56, 95% CI, 1.79-17.20, P = 0.003), and BMP7 (HR 3.86, 95% CI, 1.60-9.32, P = 0.003) were independently predictive of overall survival (FDR < 10%) after adjusting for a panel of previously established prognostic variables in mCRPC (Halabi nomogram). A model including Halabi, WNT5a, and AURKA expression, termed the miCTC score, outperformed the Halabi nomogram alone (AUC = 0.89 vs. AUC = 0.70). Understanding the molecular landscape of CTCs has utility in predicting clinical outcomes in patients with aggressive prostate cancer and provides an additional tool in the arsenal of precision-based therapeutic approaches in oncology.Implications: Analysis of CTC gene expression reveals a clinically prognostic "liquid biopsy" signature in patients with metastatic castrate-resistance prostate cancer. Mol Cancer Res; 16(4); 643-54. ©2018 AACR.

Associations of Luminal and Basal Subtyping of Prostate Cancer With Prognosis and Response to Androgen Deprivation Therapy.

Importance: There is a clear need for a molecular subtyping approach in prostate cancer to identify clinically distinct subgroups that benefit from specific therapies. Objectives: To identify prostate cancer subtypes based on luminal and basal lineage and to determine associations with clinical outcomes and response to treatment. Design, Setting, and Participants: The PAM50 classifier was used to subtype 1567 retrospectively collected (median follow-up, 10 years) and 2215 prospectively collected prostate cancer samples into luminal- and basal-like subtypes. Main Outcomes and Measures: Metastasis, biochemical recurrence, overall survival, prostate cancer­specific survival, associations with biological pathways, and clinicopathologic variables were the main outcomes. Results: Among the 3782 samples, the PAM50 classifier consistently segregated prostate cancer into 3 subtypes in both the retrospective and prospective cohorts: luminal A (retrospective, 538 [34.3%]; prospective, 737 [33.3%]), luminal B (retrospective, 447 [28.5%]; prospective, 723 [32.6%]), and basal (retrospective, 582 [37.1%]; prospective, 755 [34.1%]). Known luminal lineage markers, such as NKX3.1 and KRT18, were enriched in luminal-like cancers, and the basal lineage CD49f signature was enriched in basal-like cancers, demonstrating the connection between these subtypes and established prostate cancer biology. In the retrospective cohort, luminal B prostate cancers exhibited the poorest clinical prognoses on both univariable and multivariable analyses accounting for standard clinicopathologic prognostic factors (10-year biochemical recurrence-free survival [bRFS], 29%; distant metastasis-free survival [DMFS], 53%; prostate cancer-specific survival [PCSS], 78%; overall survival [OS], 69%), followed by basal prostate cancers (10-year bRFS, 39%; DMFS, 73%; PCSS, 86%; OS, 80%) and luminal A prostate cancers (10-year bRFS, 41%; DMFS, 73%; PCSS, 89%; OS, 82%). Although both luminal-like subtypes were associated with increased androgen receptor expression and signaling, only luminal B prostate cancers were significantly associated with postoperative response to androgen deprivation therapy (ADT) in a subset analysis in our retrospective cohorts (n = 315) matching patients based on clinicopathologic variables (luminal B 10-year metastasis: treated, 33% vs untreated, 55%; nonluminal B 10-year metastasis: treated, 37% vs untreated, 21%; P = .006 for interaction). Conclusions and Relevance: Luminal- and basal-like prostate cancers demonstrate divergent clinical behavior, and patients with luminal B tumors respond better to postoperative ADT than do patients with non­luminal B tumors. These findings contribute novel insight into prostate cancer biology, providing a potential clinical tool to personalize ADT treatment for prostate cancer by predicting which men may benefit from ADT after surgery.

Correction: Cell, Isoform, and Environment Factors Shape Gradients and Modulate Chemotaxis.

[This corrects the article DOI: 10.1371/journal.pone.0123450.].

Development and validation of a 24-gene predictor of response to postoperative radiotherapy in prostate cancer: a matched, retrospective analysis.

BACKGROUND: Postoperative radiotherapy has an important role in the treatment of prostate cancer, but personalised patient selection could improve outcomes and spare unnecessary toxicity. We aimed to develop and validate a gene expression signature to predict which patients would benefit most from postoperative radiotherapy. METHODS: Patients were eligible for this matched, retrospective study if they were included in one of five published US studies (cohort, case-cohort, and case-control studies) of patients with prostate adenocarcinoma who had radical prostatectomy (with or without postoperative radiotherapy) and had gene expression analysis of the tumour, with long-term follow-up and complete clinicopathological data. Additional treatment after surgery was at the treating physician's discretion. In each cohort, patients who had postoperative radiotherapy were matched with patients who had not had radiotherapy using Gleason score, prostate-specific antigen concentration, surgical margin status, extracapsular extension, seminal vesicle invasion, lymph node invasion, and androgen deprivation therapy. We constructed a matched training cohort using patients from one study in which we developed a 24-gene Post-Operative Radiation Therapy Outcomes Score (PORTOS). We generated a pooled matched validation cohort using patients from the remaining four studies. The primary endpoint was the development of distant metastasis. FINDINGS: In the training cohort (n=196), among patients with a high PORTOS (n=39), those who had radiotherapy had a lower incidence of distant metastasis than did patients who did not have radiotherapy, with a 10-year metastasis rate of 5% (95% CI 0-14) in patients who had radiotherapy (n=20) and 63% (34-80) in patients who did not have radiotherapy (n=19; hazard ratio [HR] 0·12 [95% CI 0·03-0·41], p<0·0001), whereas among patients with a low PORTOS (n=157), those who had postoperative radiotherapy (n=78) had a greater incidence of distant metastasis at 10 years than did their untreated counterparts (n=79; 57% [44-67] vs 31% [20-41]; HR 2·5 [1·6-4·1], p<0·0001), with a significant treatment interaction (pinteraction<0·0001). The finding that PORTOS could predict outcome due to radiotherapy treatment was confirmed in the validation cohort (n=330), which showed that patients who had radiotherapy had a lower incidence of distant metastasis compared with those who did not have radiotherapy, but only in the high PORTOS group (high PORTOS [n=82]: 4% [95% CI 0-10] in the radiotherapy group [n=57] vs 35% [95% CI 7-54] in the no radiotherapy group [n=25] had metastasis at 10 years; HR 0·15 [95% CI 0·04-0·60], p=0·0020; low PORTOS [n=248]: 32% [95% CI 19-43] in the radiotherapy group [n=108] vs 32% [95% CI 22-40] in the no radiotherapy group [n=140]; HR 0·92 [95% CI 0·56-1·51], p=0·76), with a significant interaction (pinteraction=0·016). The conventional prognostic tools Decipher, CAPRA-S, and microarray version of the cell cycle progression signature did not predict response to radiotherapy (pinteraction>0·05 for all). INTERPRETATION: Patients with a high PORTOS who had postoperative radiotherapy were less likely to have metastasis at 10 years than those who did not have radiotherapy, suggesting that treatment with postoperative radiotherapy should be considered in this subgroup. PORTOS should be investigated further in additional independent cohorts. FUNDING: None.

Patient-Level DNA Damage and Repair Pathway Profiles and Prognosis After Prostatectomy for High-Risk Prostate Cancer.

IMPORTANCE: A substantial number of patients diagnosed with high-risk prostate cancer are at risk for metastatic progression after primary treatment. Better biomarkers are needed to identify patients at the highest risk to guide therapy intensification. OBJECTIVE: To create a DNA damage and repair (DDR) pathway profiling method for use as a prognostic signature biomarker in high-risk prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: A cohort of 1090 patients with high-risk prostate cancer who underwent prostatectomy and were treated at 3 different academic institutions were divided into a training cohort (n = 545) and 3 pooled validation cohorts (n = 232, 130, and 183) assembled for case-control or case-cohort studies. Profiling of 9 DDR pathways using 17 gene sets for GSEA (Gene Set Enrichment Analysis) of high-density microarray gene expression data from formalin-fixed paraffin-embedded prostatectomy samples with median 10.3 years follow-up was performed. Prognostic signature development from DDR pathway profiles was studied, and DDR pathway gene mutation in published cohorts was analyzed. MAIN OUTCOMES AND MEASURES: Biochemical recurrence-free, metastasis-free, and overall survival. RESULTS: Across the training cohort and pooled validation cohorts, 1090 men were studied; mean (SD) age at diagnosis was 65.3 (6.4) years. We found that there are distinct clusters of DDR pathways within the cohort, and DDR pathway enrichment is only weakly correlated with clinical variables such as age (Spearman ρ [ρ], range, -0.07 to 0.24), Gleason score (ρ, range, 0.03 to 0.20), prostate-specific antigen level (ρ, range, -0.07 to 0.10), while 13 of 17 DDR gene sets are strongly correlated with androgen receptor pathway enrichment (ρ, range, 0.33 to 0.82). In published cohorts, DDR pathway genes are rarely mutated. A DDR pathway profile prognostic signature built in the training cohort was significantly associated with biochemical recurrence-free, metastasis-free, and overall survival in the pooled validation cohorts independent of standard clinicopathological variables. The prognostic performance of the signature for metastasis-free survival appears to be stronger in the younger patients (HR, 1.67; 95% CI, 1.12-2.50) than in the older patients (HR, 0.77; 95% CI, 0.29-2.07) on multivariate Cox analysis. CONCLUSIONS AND RELEVANCE: DNA damage and repair pathway profiling revealed patient-level variations and the DDR pathways are rarely affected by mutation. A DDR pathway signature showed strong prognostic performance with the long-term outcomes of metastasis-free and overall survival that may be useful for risk stratification of high-risk prostate cancer patients.

Cell, isoform, and environment factors shape gradients and modulate chemotaxis.

Chemokine gradient formation requires multiple processes that include ligand secretion and diffusion, receptor binding and internalization, and immobilization of ligand to surfaces. To understand how these events dynamically shape gradients and influence ensuing cell chemotaxis, we built a multi-scale hybrid agent-based model linking gradient formation, cell responses, and receptor-level information. The CXCL12/CXCR4/CXCR7 signaling axis is highly implicated in metastasis of many cancers. We model CXCL12 gradient formation as it is impacted by CXCR4 and CXCR7, with particular focus on the three most highly expressed isoforms of CXCL12. We trained and validated our model using data from an in vitro microfluidic source-sink device. Our simulations demonstrate how isoform differences on the molecular level affect gradient formation and cell responses. We determine that ligand properties specific to CXCL12 isoforms (binding to the migration surface and to CXCR4) significantly impact migration and explain differences in in vitro chemotaxis data. We extend our model to analyze CXCL12 gradient formation in a tumor environment and find that short distance, steep gradients characteristic of the CXCL12-γ isoform are effective at driving chemotaxis. We highlight the importance of CXCL12-γ in cancer cell migration: its high effective affinity for both extracellular surface sites and CXCR4 strongly promote CXCR4+ cell migration. CXCL12-γ is also more difficult to inhibit, and we predict that co-inhibition of CXCR4 and CXCR7 is necessary to effectively hinder CXCL12-γ-induced migration. These findings support the growing importance of understanding differences in protein isoforms, and in particular their implications for cancer treatment.

CXCR7 controls competition for recruitment of ß-arrestin 2 in cells expressing both CXCR4 and CXCR7.

Chemokine CXCL12 promotes growth and metastasis of more than 20 different human cancers, as well as pathogenesis of other common diseases. CXCL12 binds two different receptors, CXCR4 and CXCR7, both of which recruit and signal through the cytosolic adapter protein ß-arrestin 2. Differences in CXCL12-dependent recruitment of ß-arrestin 2 in cells expressing one or both receptors remain poorly defined. To quantitatively investigate parameters controlling association of ß-arrestin 2 with CXCR4 or CXCR7 in cells co-expressing both receptors, we used a systems biology approach combining real-time, multi-spectral luciferase complementation imaging with computational modeling. Cells expressing only CXCR4 maintain low basal association with ß-arrestin 2, and CXCL12 induces a rapid, transient increase in this interaction. In contrast, cells expressing only CXCR7 have higher basal association with ß-arrestin 2 and exhibit more gradual, prolonged recruitment of ß-arrestin 2 in response to CXCL12. We developed and fit a data-driven computational model for association of either CXCR4 or CXCR7 with ß-arrestin 2 in cells expressing only one type of receptor. We then experimentally validated model predictions that co-expression of CXCR4 and CXCR7 on the same cell substantially decreases both the magnitude and duration of CXCL12-regulated recruitment of ß-arrestin 2 to CXCR4. Co-expression of both receptors on the same cell only minimally alters recruitment of ß-arrestin 2 to CXCR7. In silico experiments also identified ß-arrestin 2 as a limiting factor in cells expressing both receptors, establishing that CXCR7 wins the "competition" with CXCR4 for CXCL12 and recruitment of ß-arrestin 2. These results reveal how competition for ß-arrestin 2 controls integrated responses to CXCL12 in cells expressing both CXCR4 and CXCR7. These results advance understanding of normal and pathologic functions of CXCL12, which is critical for developing effective strategies to target these pathways therapeutically.

A Comprehensive Analysis of CXCL12 Isoforms in Breast Cancer1,2.

CXCL12-CXCR4-CXCR7 signaling promotes tumor growth and metastasis in breast cancer. Alternative splicing of CXCL12 produces isoforms with distinct structural and biochemical properties, but little is known about isoform-specific differences in breast cancer subtypes and patient outcomes. We investigated global expression profiles of the six CXCL12 isoforms, CXCR4, and CXCR7 in The Cancer Genome Atlas breast cancer cohort using next-generation RNA sequencing in 948 breast cancer and benign samples and seven breast cancer cell lines. We compared expression levels with several clinical parameters, as well as metastasis, recurrence, and overall survival (OS). CXCL12-α, -ß, and -γ are highly co-expressed, with low expression correlating with more aggressive subtypes, higher stage disease, and worse clinical outcomes. CXCL12-δ did not correlate with other isoforms but was prognostic for OS and showed the same trend for metastasis and recurrence-free survival. Effects of CXCL12-δ remained independently prognostic when taking into account expression of CXCL12,CXCR4, and CXCR7. These results were also reflected when comparing CXCL12-α, -ß, and -γ in breast cancer cell lines. We summarized expression of all CXCL12 isoforms in an important chemokine signaling pathway in breast cancer in a large clinical cohort and common breast cancer cell lines, establishing differences among isoforms in multiple clinical, pathologic, and molecular subgroups. We identified for the first time the clinical importance of a previously unstudied isoform, CXCL12-δ.