Assessment of TROP2, CEACAM5 and DLL3 in metastatic prostate cancer: Expression landscape and molecular correlates.

Therapeutic approaches targeting proteins on the surface of cancer cells have emerged as an important strategy for precision oncology. To capitalize on the potential impact of drugs targeting surface proteins, detailed knowledge about the expression patterns of the target proteins in tumor tissues is required. In castration-resistant prostate cancer (CRPC), agents targeting prostate-specific membrane antigen (PSMA) have demonstrated clinical activity. However, PSMA expression is lost in a significant number of CRPC tumors. The identification of additional cell surface targets is necessary to develop new therapeutic approaches. Here, we performed a comprehensive analysis of the expression heterogeneity and co-expression patterns of trophoblast cell-surface antigen 2 (TROP2), delta-like ligand 3 (DLL3), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) in CRPC samples from a rapid autopsy cohort. We show that DLL3 and CEACAM5 exhibit the highest expression in neuroendocrine prostate cancer (NEPC), while TROP2 is expressed across different CRPC molecular subtypes, except for NEPC. We further demonstrated that AR alterations were associated with higher expression of PSMA and TROP2. Conversely, PSMA and TROP2 expression was lower in RB1-altered tumors. In addition to genomic alterations, we show a tight correlation between epigenetic states, particularly histone H3 lysine 27 methylation (H3K27me3) at the transcriptional start site and gene body of TACSTD2 (encoding TROP2), DLL3, and CEACAM5, and their respective protein expression in CRPC patient-derived xenografts. Collectively, these findings provide insights into patterns and determinants of expression of TROP2, DLL3, and CEACAM5 with implications for the clinical development of cell surface targeting agents in CRPC.

Molecular phenotyping of small cell lung cancer using targeted cfDNA profiling of transcriptional regulatory regions.

We report an approach for cancer phenotyping based on targeted sequencing of cell-free DNA (cfDNA) for small cell lung cancer (SCLC). In SCLC, differential activation of transcription factors (TFs), such as ASCL1, NEUROD1, POU2F3, and REST defines molecular subtypes. We designed a targeted capture panel that identifies chromatin organization signatures at 1535 TF binding sites and 13,240 gene transcription start sites and detects exonic mutations in 842 genes. Sequencing of cfDNA from SCLC patient-derived xenograft models captured TF activity and gene expression and revealed individual highly informative loci. Prediction models of ASCL1 and NEUROD1 activity using informative loci achieved areas under the receiver operating characteristic curve (AUCs) from 0.84 to 0.88 in patients with SCLC. As non-SCLC (NSCLC) often transforms to SCLC following targeted therapy, we applied our framework to distinguish NSCLC from SCLC and achieved an AUC of 0.99. Our approach shows promising utility for SCLC subtyping and transformation monitoring, with potential applicability to diverse tumor types.

Assay Validation of Cell-Free DNA Shallow Whole-Genome Sequencing to Determine Tumor Fraction in Advanced Cancers.

Blood-based liquid biopsy is increasingly used in clinical care of patients with cancer, and fraction of tumor-derived DNA in circulation (tumor fraction; TFx) has demonstrated clinical validity across multiple cancer types. To determine TFx, shallow whole-genome sequencing of cell-free DNA (cfDNA) can be performed from a single blood sample, using an established computational pipeline (ichorCNA), without prior knowledge of tumor mutations, in a highly cost-effective manner. We describe assay validation of this approach to facilitate broad clinical application, including evaluation of assay sensitivity, precision, repeatability, reproducibility, pre-analytic factors, and DNA quality/quantity. Sensitivity to detect TFx of 3% (lower limit of detection) was 97.2% to 100% at 1× and 0.1× mean sequencing depth, respectively. Precision was demonstrated on distinct sequencing instruments (HiSeqX and NovaSeq) with no observable differences. The assay achieved prespecified 95% agreement of TFx across replicates of the same specimen (repeatability) and duplicate samples in different batches (reproducibility). Comparison of samples collected in EDTA and Streck tubes from single venipuncture in 23 patients demonstrated that EDTA or Streck tubes were comparable if processed within 8 hours. On the basis of a range of DNA inputs (1 to 50 ng), 20 ng cfDNA is the preferred input, with 5 ng minimum acceptable. Overall, this shallow whole-genome sequencing of cfDNA and ichorCNA approach offers sensitive, precise, and reproducible quantitation of TFx, facilitating assay application in clinical cancer care.

FinaleMe: Predicting DNA methylation by the fragmentation patterns of plasma cell-free DNA.

Analysis of DNA methylation in cell-free DNA reveals clinically relevant biomarkers but requires specialized protocols such as whole-genome bisulfite sequencing. Meanwhile, millions of cell-free DNA samples are being profiled by whole-genome sequencing. Here, we develop FinaleMe, a non-homogeneous Hidden Markov Model, to predict DNA methylation of cell-free DNA and, therefore, tissues-of-origin, directly from plasma whole-genome sequencing. We validate the performance with 80 pairs of deep and shallow-coverage whole-genome sequencing and whole-genome bisulfite sequencing data.

FinaleMe: Predicting DNA methylation by the fragmentation patterns of plasma cell-free DNA.

Analysis of DNA methylation in cell-free DNA (cfDNA) reveals clinically relevant biomarkers but requires specialized protocols and sufficient input material that limits its applicability. Millions of cfDNA samples have been profiled by genomic sequencing. To maximize the gene regulation information from the existing dataset, we developed FinaleMe, a non-homogeneous Hidden Markov Model (HMM), to predict DNA methylation of cfDNA and, therefore, tissues-of-origin directly from plasma whole-genome sequencing (WGS). We validated the performance with 80 pairs of deep and shallow-coverage WGS and whole-genome bisulfite sequencing (WGBS) data.

Multi-level functional genomics reveals molecular and cellular oncogenicity of patient-based 3' untranslated region mutations.

3' untranslated region (3' UTR) somatic mutations represent a largely unexplored avenue of alternative oncogenic gene dysregulation. To determine the significance of 3' UTR mutations in disease, we identify 3' UTR somatic variants across 185 advanced prostate tumors, discovering 14,497 single-nucleotide mutations enriched in oncogenic pathways and 3' UTR regulatory elements. By developing two complementary massively parallel reporter assays, we measure how thousands of patient-based mutations affect mRNA translation and stability and identify hundreds of functional variants that allow us to define determinants of mutation significance. We demonstrate the clinical relevance of these mutations, observing that CRISPR-Cas9 endogenous editing of distinct variants increases cellular stress resistance and that patients harboring oncogenic 3' UTR mutations have a particularly poor prognosis. This work represents an expansive view of the extent to which disease-relevant 3' UTR mutations affect mRNA stability, translation, and cancer progression, uncovering principles of regulatory functionality and potential therapeutic targets in previously unexplored regulatory regions.

Are Patients with HHV-8 Associated Castleman Disease Successfully Treated with Rituximab at Risk of Subsequently Developing HHV-8 Negative (Idiopathic) Castleman Disease?

Introduction: Multicentric Castleman disease (MCD) is a lymphoproliferative disorder characterized by lymph node histopathology and systemic symptoms. To our knowledge, there are no descriptions in the literature of long-term outcomes of human herpesvirus-8 (HHV-8)-associated MCD. Case Description: We report a case of a 70-year-old male living with human immunodeficiency virus and a history of human herpesvirus-8 (HHV-8)-associated MCD. The patient reported having had low-grade fever for two weeks. Extensive workup revealed systemic lymphadenopathy without evidence of autoimmune disease or malignancy. Lymph node biopsy was consistent with HHV-8-negative idiopathic MCD (iMCD). The patient was subsequently scheduled for anti-interleukin-6 therapy. Discussion: The present case is the first report of probable development of iMCD after long-term follow-up for HHV-8-associated MCD. The case illustrates the possible long-term consequences of MCD, suggesting the necessity of further research on the pathogenesis of CD. Conclusion: Given the uncertainty in the long-term outcomes of HHV-8-associated MCD, periodic surveillance of patients with a history of HHV-8-associated MCD is warranted. Prospective nationwide cohort studies comparing characteristics of HHV-8-associated MCD and iMCD would bring further insights. LEARNING POINTS: This is the first case describing the probable development of HHV-8-negative idiopathic MCD after HHV-8-associated MCD.Little is known of long-term outcomes of HHV-8-associated MCD and idiopathic MCD, necessitating periodic surveillance.HHV-8-negative idiopathic MCD patients are treated with siltuximab, an interleukin-6 inhibitor, unlike patients with HHV-8-associated MCD, who benefit most from rituximab.

Cancer aneuploidies are shaped primarily by effects on tumour fitness.

Aneuploidies-whole-chromosome or whole-arm imbalances-are the most prevalent alteration in cancer genomes1,2. However, it is still debated whether their prevalence is due to selection or ease of generation as passenger events1,2. Here we developed a method, BISCUT, that identifies loci subject to fitness advantages or disadvantages by interrogating length distributions of telomere- or centromere-bounded copy-number events. These loci were significantly enriched for known cancer driver genes, including genes not detected through analysis of focal copy-number events, and were often lineage specific. BISCUT identified the helicase-encoding gene WRN as a haploinsufficient tumour-suppressor gene on chromosome 8p, which is supported by several lines of evidence. We also formally quantified the role of selection and mechanical biases in driving aneuploidy, finding that rates of arm-level copy-number alterations are most highly correlated with their effects on cellular fitness1,2. These results provide insight into the driving forces behind aneuploidy and its contribution to tumorigenesis.

Somatic mutation but not aneuploidy differentiates lung cancer in never-smokers and smokers.

Lung cancer in never-smokers disproportionately affects older women. To understand the mutational landscape of this cohort, we performed detailed genome characterization of 73 lung adenocarcinomas from participants of the Women’s Health Initiative (WHI). We find enrichment of EGFR mutations in never-/light-smokers and KRAS mutations in heavy smokers as expected, but we also show that the specific variants of these genes differ by smoking status, with important therapeutic implications. Mutational signature analysis revealed signatures of clock, APOBEC, and DNA repair deficiency in never-/light-smokers; however, the mutational load of these signatures did not differ significantly from those found in smokers. Last, tumors from both smokers and never-/light-smokers shared copy number subtypes, with no significant differences in aneuploidy. Thus, the genomic landscape of lung cancer in never-/light-smokers and smokers is predominantly differentiated by somatic mutations and not copy number alterations.

Nucleosome Patterns in Circulating Tumor DNA Reveal Transcriptional Regulation of Advanced Prostate Cancer Phenotypes.

Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology. SIGNIFICANCE: This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517.

Genomic Characterization of Prostatic Basal Cell Carcinoma.

Basal cell carcinoma (BCC) of the prostate is a rare tumor. Compared with the more common acinar adenocarcinoma (AAC) of the prostate, BCCs show features of basal cell differentiation and are thought to be biologically distinct from AAC. The spectrum of molecular alterations of BCC has not been comprehensively described, and genomic studies are lacking. Herein, whole genome sequencing was performed on archival formalin-fixed, paraffin-embedded specimens of two cases with BCC. Prostatic BCCs were characterized by an overall low copy number and mutational burden. Recurrent copy number loss of chromosome 16 was observed. In addition, putative driver gene alterations in KIT, DENND3, PTPRU, MGA, and CYLD were identified. Mechanistically, depletion of the CYLD protein resulted in increased proliferation of prostatic basal cells in vitro. Collectively, these studies show that prostatic BCC displays distinct genomic alterations from AAC and highlight a potential role for loss of chromosome 16 in the pathogenesis of this rare tumor type.

Bipolar androgen therapy plus olaparib in men with metastatic castration-resistant prostate cancer.

BACKGROUND: Bipolar androgen therapy (BAT) results in rapid fluctuation of testosterone (T) between near-castrate and supraphysiological levels and has shown promise in metastatic castration-resistant prostate cancer (mCRPC). Its clinical effects may be mediated through induction of DNA damage, and preclinical studies suggest synergy with PARP inhibitors. PATIENTS AND METHODS: This was a single-center, Phase II trial testing olaparib plus BAT (T cypionate/enanthate 400 mg every 28 days) with ongoing androgen deprivation. Planned recruitment was 30 subjects (equal proportions with/without homologous recombination repair [HRR] gene mutations) with mCRPC post abiraterone and/or enzalutamide. The primary objective was to determine PSA50 response (PSA decline ≥50% from baseline) rate at 12-weeks. The primary analysis utilized the entire (intent-to-treat [ITT]) cohort, with those dropping out early counted as non-responders. Secondary/exploratory analyses were in those treated beyond 12-weeks (response-evaluable cohort). RESULTS: Thirty-six patients enrolled and 6 discontinued prior to response assessment. In the ITT cohort, PSA50 response rate at 12-weeks was 11/36 (31%; 95% CI 17-48%), and 16/36 (44%, 95% CI 28-62%) had a PSA50 response at any time on-study. After a median follow-up of 19 months, the median clinical/radiographic progression-free survival in the ITT cohort was 13.0 months (95% CI 7-17). Clinical outcomes were similar regardless of HRR gene mutational status. CONCLUSIONS: BAT plus olaparib is associated with high response rates and long PFS. Clinical benefit was observed regardless of HRR gene mutational status.

ASSESSMENT OF CELL SURFACE TARGETS IN METASTATIC PROSTATE CANCER: EXPRESSION LANDSCAPE AND MOLECULAR CORRELATES.

Therapeutic approaches targeting proteins on the surface of cancer cells have emerged as an important strategy for precision oncology. To fully capitalize on the potential impact of drugs targeting surface proteins, detailed knowledge about the expression patterns of the target proteins in tumor tissues is required. In castration-resistant prostate cancer (CRPC), agents targeting prostate-specific membrane antigen (PSMA) have demonstrated clinical activity. However, PSMA expression is lost in a significant number of CRPC tumors, and the identification of additional cell surface targets is necessary in order to develop new therapeutic approaches. Here, we performed a comprehensive analysis of the expression and co-expression patterns of trophoblast cell-surface antigen 2 (TROP2), delta-like ligand 3 (DLL3), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) in CRPC samples from a rapid autopsy cohort. We show that DLL3 and CEACAM5 exhibit the highest expression in neuroendocrine prostate cancer (NEPC), while TROP2 is expressed across different CRPC molecular subtypes, except for NEPC. We observed variable intra-tumoral and inter-tumoral heterogeneity and no dominant metastatic site predilections for TROP2, DLL3, and CEACAM5. We further show that AR amplifications were associated with higher expression of PSMA and TROP2 but lower DLL3 and CEACAM5 levels. Conversely, PSMA and TROP2 expression was lower in RB1-altered tumors. In addition to genomic alterations, we demonstrate a tight correlation between epigenetic states, particularly histone H3 lysine 27 methylation (H3K27me3) at the transcriptional start site and gene body of TACSTD2 (encoding TROP2), DLL3, and CEACAM5, and their respective protein expression in CRPC patient-derived xenografts. Collectively, these findings provide novel insights into the patterns and determinants of expression of TROP2, DLL3, and CEACAM5 with important implications for the clinical development of cell surface targeting agents in CRPC.

A framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA.

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

Comprehensive assessment of anaplastic lymphoma kinase in localized and metastatic prostate cancer reveals targetable alterations.

Anaplastic lymphoma kinase (ALK) is a tyrosine kinase with genomic and expression changes in many solid tumors. ALK inhibition is first line therapy for lung cancers with ALK alterations, and an effective therapy in other tumor types, but has not been well-studied in prostate cancer. Here, we aim to delineate the role of ALK genomic and expression changes in primary and metastatic prostate cancer. We determined ALK expression by immunohistochemistry and RNA-Seq, and genomic alterations by NGS. We assessed functional consequences of ALK overexpression and pharmacological ALK inhibition by cell proliferation and cell viability assays. Among 372 primary prostate cancer cases we identified one case with uniformly high ALK protein expression. Genomic analysis revealed a SLC45A3-ALK fusion which promoted oncogenesis in in vitro assays. We observed ALK protein expression in 5/52 (9%) of metastatic prostate cancer cases, of which 4 of 5 had neuroendocrine features. ALK-expressing neuroendocrine prostate cancer had a distinct transcriptional program, and earlier disease progression. An ALK-expressing neuroendocrine prostate cancer model was sensitive to pharmacological ALK inhibition. In summary, we found that ALK overexpression is rare in primary prostate cancer, but more frequent in metastatic prostate cancers with neuroendocrine differentiation. Further, ALK fusions similar to lung cancer are an occasional driver in prostate cancer. Our data suggest that ALK-directed therapies could be an option in selected patients with advanced prostate cancer.

Patterns of structural variation define prostate cancer across disease states.

The complex genomic landscape of prostate cancer evolves across disease states under therapeutic pressure directed toward inhibiting androgen receptor (AR) signaling. While significantly altered genes in prostate cancer have been extensively defined, there have been fewer systematic analyses of how structural variation shapes the genomic landscape of this disease across disease states. We uniformly characterized structural alterations across 531 localized and 143 metastatic prostate cancers profiled by whole genome sequencing, 125 metastatic samples of which were also profiled via whole transcriptome sequencing. We observed distinct significantly recurrent breakpoints in localized and metastatic castration-resistant prostate cancers (mCRPC), with pervasive alterations in noncoding regions flanking the AR, MYC, FOXA1, and LSAMP genes enriched in mCRPC and TMPRSS2-ERG rearrangements enriched in localized prostate cancer. We defined 9 subclasses of mCRPC based on signatures of structural variation, each associated with distinct genetic features and clinical outcomes. Our results comprehensively define patterns of structural variation in prostate cancer and identify clinically actionable subgroups based on whole genome profiling.

DNA-based copy number analysis confirms genomic evolution of PDX models.

Genomic evolution of patient-derived xenografts (PDXs) may lead to their gradual divergence away of their tumors of origin. We previously reported the genomic evolution of the copy number (CN) landscapes of PDXs during their engraftment and passaging1. However, whether PDX models are highly stable throughout passaging2, or can evolve CNAs rapidly1,3, remains controversial. Here, we reassess the genomic evolution of PDXs using DNA-based CN profiles. We find strong evidence for genomic evolution in the DNA-based PDX data: a median of ~10% of the genome is differentially altered between matched primary tumors (PTs) and PDXs across cohorts (range, 0% to 73% across all models). In 24% of the matched PT-PDX samples, over a quarter of the genome is differentially affected by CN alterations. Moreover, in matched analyses of PTs and their derived PDXs at multiple passages, later-passage PDXs are significantly less similar to their parental PTs than earlier-passage PDXs, indicative of genomic divergence. We conclude that PDX models indeed evolve throughout their derivation and propagation, and that the phenotypic consequences of this evolution ought to be assessed in order to determine its relevance to the proper application of these valuable cancer models.

Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma.

Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.