Optimizing Precision Medicine for Breast Cancer Brain Metastases with Functional Drug Response Assessment.

The development of novel therapies for brain metastases is an unmet need. Brain metastases may have unique molecular features that could be explored as therapeutic targets. A better understanding of the drug sensitivity of live cells coupled to molecular analyses will lead to a rational prioritization of therapeutic candidates. We evaluated the molecular profiles of 12 breast cancer brain metastases (BCBM) and matched primary breast tumors to identify potential therapeutic targets. We established six novel patient-derived xenograft (PDX) from BCBM from patients undergoing clinically indicated surgical resection of BCBM and used the PDXs as a drug screening platform to interrogate potential molecular targets. Many of the alterations were conserved in brain metastases compared with the matched primary. We observed differential expressions in the immune-related and metabolism pathways. The PDXs from BCBM captured the potentially targetable molecular alterations in the source brain metastases tumor. The alterations in the PI3K pathway were the most predictive for drug efficacy in the PDXs. The PDXs were also treated with a panel of over 350 drugs and demonstrated high sensitivity to histone deacetylase and proteasome inhibitors. Our study revealed significant differences between the paired BCBM and primary breast tumors with the pathways involved in metabolisms and immune functions. While molecular targeted drug therapy based on genomic profiling of tumors is currently evaluated in clinical trials for patients with brain metastases, a functional precision medicine strategy may complement such an approach by expanding potential therapeutic options, even for BCBM without known targetable molecular alterations. Significance: Examining genomic alterations and differentially expressed pathways in brain metastases may inform future therapeutic strategies. This study supports genomically-guided therapy for BCBM and further investigation into incorporating real-time functional evaluation will increase confidence in efficacy estimations during drug development and predictive biomarker assessment for BCBM.

Metastatic prostate cancer diagnosed by fine-needle aspiration: Contemporary cytopathologic and biomarker assessment with clinical correlates.

INTRODUCTION: The diagnosis of metastatic prostatic cancer (MPC) by fine needle aspiration (FNA) can usually be rendered by typical cytomorphologic and immunohistochemical (IHC) features. However, MPC diagnosis may be complicated by transformation to atypical phenotypes such as small cell carcinoma, typically under pressure from androgen deprivation therapy (ADT). Predictive and prognostic biomarkers can also be assessed by IHC. This study illustrates how careful assessment of cytologic and biomarker features may provide therapeutic and prognostic information in MPC. DESIGN: We reviewed our anatomic pathology archives for MPC diagnosed by FNA from January 2014 to June 2021. Clinical histories, cytology slides, and cell blocks were reviewed. Extensive IHC biomarker workup was performed, including markers of prostate lineage, cell-cycle dysfunction, Ki-67, neuroendocrine markers, PDL1, and androgen receptor splice variant 7. Cases were reclassified into three categories: conventional type, intermediary type, and high-grade neuroendocrine carcinoma (HGNC). RESULTS: Eighteen patients were identified. Twelve had conventional MPC, including six of six ADT-naive patients. Six of twelve (50%) with prior ADT were reclassified as intermediary or HGNC. Four intermediary cases included two with squamous differentiation and two with pro-proliferative features. Two HGNC cases had typical small cell carcinoma cytomorphology. Expression of PDL1 was identified in two cases and ARv7 in three cases. Five of five intermediary and HGNC patients died of disease versus six of eleven with with conventional type. CONCLUSIONS: Aggressive cytomorphologic variants were commonly identified in patients with prior ADT. Identification of nonconventional cytomorphology and increased proliferation can provide important prognostic information. Recognition of these changes is important for an accurate diagnosis, and the identification of high-grade variants can affect therapeutic decision-making. Clinically actionable biomarkers such as PDL1 and ARv7 can be assessed by IHC.

Assessment of Clinical Benefit of Integrative Genomic Profiling in Advanced Solid Tumors.

IMPORTANCE: Use of next-generation sequencing (NGS) to identify clinically actionable genomic targets has been incorporated into routine clinical practice in the management of advanced solid tumors; however, the clinical utility of this testing remains uncertain. OBJECTIVE: To determine which patients derived the greatest degree of clinical benefit from NGS profiling. DESIGN, SETTING, AND PARTICIPANTS: Patients in this cohort study underwent fresh tumor biopsy and blood sample collection for genomic profiling of paired tumor and normal DNA (whole-exome or targeted-exome capture with analysis of 1700 genes) and tumor transcriptome (RNA) sequencing. Somatic and germline genomic alterations were annotated and classified according to degree of clinical actionability. Results were returned to treating oncologists. Data were collected from May 1, 2011, to February 28, 2018, and analyzed from May 1, 2011, to April 30, 2020. MAIN OUTCOMES AND MEASURES: Patients' subsequent therapy and treatment response were extracted from the medical record to determine clinical benefit rate from NGS-directed therapy at 6 months and exceptional responses lasting 12 months or longer. RESULTS: During the study period, NGS was attempted on tumors from 1138 patients and was successful in 1015 (89.2%) (MET1000 cohort) (538 men [53.0%]; mean [SD] age, 57.7 [13.3] years). Potentially clinically actionable genomic alterations were discovered in 817 patients (80.5%). Of these, 132 patients (16.2%) received sequencing-directed therapy, and 49 had clinical benefit (37.1%). Exceptional responses were observed in 26 patients (19.7% of treated patients). Pathogenic germline variants (PGVs) were identified in 160 patients (15.8% of cohort), including 49 PGVs (4.8% of cohort) with therapeutic relevance. For 55 patients with carcinoma of unknown primary origin, NGS identified the primary site in 28 (50.9%), and sequencing-directed therapy in 13 patients resulted in clinical benefit in 7 instances (53.8%), including 5 exceptional responses. CONCLUSIONS AND RELEVANCE: The high rate of therapeutically relevant PGVs identified across diverse cancer types supports a recommendation for directed germline testing in all patients with advanced cancer. The high frequency of therapeutically relevant somatic and germline findings in patients with carcinoma of unknown primary origin and other rare cancers supports the use of comprehensive NGS profiling as a component of standard of care for these disease entities.

Transcriptomic heterogeneity in multifocal prostate cancer.

BACKGROUND: Commercial gene expression assays are guiding clinical decision making in patients with prostate cancer, particularly when considering active surveillance. Given heterogeneity and multifocality of primary prostate cancer, such assays should ideally be robust to the coexistence of unsampled higher grade disease elsewhere in the prostate in order to have clinical utility. Herein, we comprehensively evaluated transcriptomic profiles of primary multifocal prostate cancer to assess robustness to clinically relevant multifocality. METHODS: We designed a comprehensive, multiplexed targeted RNA-sequencing assay capable of assessing multiple transcriptional classes and deriving commercially available prognostic signatures, including the Myriad Prolaris Cell Cycle Progression score, the Oncotype DX Genomic Prostate Score, and the GenomeDX Decipher Genomic Classifier. We applied this assay to a retrospective, multi-institutional cohort of 156 prostate cancer samples. Derived commercial biomarker scores for 120 informative primary prostate cancer samples from 44 cases were determined and compared. RESULTS: Derived expression scores were positively correlated with tumor grade (rS = 0.53-0.73; all P < 0.001), both within the same case and across the entire cohort. In cases of extreme grade-discordant multifocality (co-occurrence of grade group 1 [GG1] and ≥GG4 foci], gene expression scores were significantly lower in low- (GG1) versus high-grade (≥GG4) foci (all P < 0.001). No significant differences in expression scores, however, were observed between GG1 foci from prostates with and without coexisting higher grade cancer (all P > 0.05). CONCLUSIONS: Multifocal, low-grade and high-grade prostate cancer foci exhibit distinct prognostic expression signatures. These findings demonstrate that prognostic RNA expression assays performed on low-grade prostate cancer biopsy tissue may not provide meaningful information on the presence of coexisting unsampled aggressive disease. FUNDING: Prostate Cancer Foundation, National Institutes of Health (U01 CA214170, R01 CA183857, University of Michigan Prostate Specialized Program of Research Excellence [S.P.O.R.E.] P50 CA186786-05, Weill Cornell Medicine S.P.O.R.E. P50 CA211024-01A1), Men of Michigan Prostate Cancer Research Fund, University of Michigan Comprehensive Cancer Center core grant (2-P30-CA-046592-24), A. Alfred Taubman Biomedical Research Institute, and Department of Defense.

Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine.

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine.

Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment.

BACKGROUND: TMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers. OBJECTIVE: Validate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy. DESIGN, SETTING, AND PARTICIPANTS: T2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Area under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit. RESULTS AND LIMITATIONS: Among informative validation cohort samples (n=1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p<0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p<0.001; PCPTrc: 0.754 vs 0.707, p=0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p<0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities. CONCLUSIONS: Incorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy. PATIENT SUMMARY: Incorporation of two prostate cancer (PCa)-specific biomarkers (TMPRSS2:ERG and PCA3) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates.

Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.

Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ∼68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value < 2 × 10(-16)). We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.

A latent variable approach for meta-analysis of gene expression data from multiple microarray experiments.

BACKGROUND: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. RESULTS: In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE). The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC) techniques. The second method is a faster algorithm based on the expectation-maximization (EM) algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. CONCLUSION: The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

Comprehensive assessment of TMPRSS2 and ETS family gene aberrations in clinically localized prostate cancer.

Novel recurrent gene fusions between the androgen-regulated gene TMPRSS2 and the ETS family members ERG, ETV1, or ETV4 have been recently identified as a common molecular event in prostate cancer development. We comprehensively analyzed the frequency and risk of disease progression for the TMPRSS2 and ETS family genes rearrangements in a cohort of 96 American men surgically treated for clinically localized prostate cancer. Using three break apart (TMPRSS2, ERG, ETV4) and one fusion (TMPRSS:ETV1) fluorescence in situ hybridization (FISH) assays, we identified rearrangements in TMPRSS2, ERG, ETV1, and ETV4 in 65, 55, 2, and 2% of cases, respectively. Overall, 54 and 2% of cases demonstrated TMPRSS2:ERG and TMPRSS2:ETV1 fusions, respectively. As intronic loss of genomic DNA between TMPRSS2 and ERG has been identified as a mechanism of TMPRSS2:ERG fusion, our assays allowed us to detect deletion of the 3' end of TMPRSS2 and the 5' end of ERG in 41 and 39% of cases rearranged for respective genes. Prostate cancers demonstrating TMPRSS2 gene rearrangement were associated with high pathologic stage (P=0.04). Our results confirm that recurrent chromosomal aberrations in TMPRSS2 and/or ETS family members are found in about 70% of prostate cancers. Importantly, we define a novel approach to study these gene fusions and identified cases where TMPRSS2 was rearranged without rearrangement of ERG, ETV1 or ETV4 and cases with ETS family gene rearrangement without TMPRSS2 rearrangement, suggesting that novel 5' and 3' partners may be involved in gene fusions in prostate cancer.