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Sowalsky, A. G.

Publications and source records attributed to Sowalsky, A. G..

10 recordsLinked to original sources

Histone modifications define distinct nucleosome positions in cell-free DNA

Circulating cell-free DNA (cfDNA) fragmentation patterns reflect nucleosome positioning. We asked whether variation in nucleosome positions in cfDNA can reveal chromatin states and associated histone modifications. Using cell-free chromatin immunoprecipitation sequencing (cfChIP-seq) in plasma from patients with prostate cancer, we identified 35,120 modification-associated positions (MAPs), loci where nucleosomes bearing active (H3K4me2) and repressive (H3K9me3) histone marks occupy reproducibly offset positions. These offsets recurred across histone marks, an independent cfChIP-seq cohort, and nuclease-digested chromatin from cell lines. MAPs were enriched in transcribed genes but depleted near transcription start sites and CTCF-binding sites where nucleosome positioning is constrained. Across 2,535 cfDNA sequencing datasets, nucleosome protection at a subset of MAPs correlated with tumor fraction (TF), reflecting differences in histone modification status between cancer-derived and non-malignant chromatin. In targeted sequencing panels, a 50-MAP model using fragments from < 0.001% of the genome distinguished samples with tumor fractions [&ge;]3% vs 0% (AUCs = 0.91-0.96 across prostate, breast, and lung cancers) and outperformed a state-of-the-art fragmentomics-based tumor fraction predictor. MAP-derived estimates correlated with reference TFs (r = 0.89) and longitudinal changes in TF (r = 0.91). MAP protection at ASCL1 binding sites identified neuroendocrine transformation of prostate cancer from cfDNA. These findings establish histone-modification-associated nucleosome positioning as a mutation-independent readout of tumor fraction and cancer state from routine cfDNA sequencing.

cancer biology↗

Discovery and performance of DNA methylation panels for cancer detection and classification in blood

Examining DNA in a liquid biopsy for non-invasive cancer detection relies on identifying dilute signal in a high background. This study aims to identify DNA methylation biomarkers for multi-cancer detection. Utilizing large tissue datasets, we apply novel search algorithms to discover confined biomarker panels capable of distinguishing tumor from normal and determining the tissue of origin. We explore the applicability to blood-based testing using targeted methylation sequencing followed by machine learning classification. We present an 8-marker panel, which successfully predicts tumors across 14 types with a 91% average sensitivity, maintaining a low false positive rate (< 0.04%). Additionally, a panel of 39 CpG sites exhibits accuracies ranging from 69% to 98% for identifying tissue of origin. When tested on 114 patient plasma samples (colon, liver, pancreatic, prostate, and stomach cancer), the 8-marker panel obtains an AUC of 0.78 with a 78% sensitivity among 32 early-stage patients (stage I-II), and 60% overall. Using the 39-marker panel in a multi-class classification model selecting only the best match, 54% of tumor samples were on average correctly assigned to the tissue of origin, and up to 80% when allowing more inclusive criteria. Using a limited set of biomarkers, our work contributes to advancing non-invasive cancer diagnostics.

cancer biology↗

TMPRSS2-ERG confers resistance to antiandrogens: mechanism and therapeutic implications

Approximately 50% of prostate cancer (PCa) patients harbor fusions involving the TMPRSS2 and ERG genes. Despite this, tailored therapies targeting the fused gene, tERG, remain undeveloped. Our study analyzed biopsy samples from two clinical trials assessing the efficacies of androgen receptor (AR) signaling inhibitors (ARSIs). The results revealed that tERG promotes resistance to ARSIs and is associated with elevated levels of the glucocorticoid receptor (GR). Subsequent assays showed that GR directly interacts with tERG, alleviates allosteric autoinhibition and prevents chemotherapy-induced tERG degradation. In PCa models, either inhibiting GR or lowering cortisol levels suppressed tumor growth in tERG-positive models, but not in fusion-negative models. In addition, patient-derived fusion-positive xenografts displayed enhanced sensitivity to combined GR and AR inhibitors. Collectively, these findings highlight TMPRSS2-ERG as a new biomarker and propose that simultaneous inhibition of GR and AR may specifically benefit tERG-positine patients. However, GR stimulatory corticosteroid therapies may not be advisable for this patient subgroup.

cancer biology↗

Androgen deprivation-mediated activation of AKT is enhanced in prostate cancer with TMPRSS2:ERG fusion

TMPRSS2:ERG gene fusion (T:E fusion) in prostate adenocarcinoma (PCa) puts ERG under androgen receptor (AR) regulated TMPRSS2 expression. T:E fusion is associated with PTEN loss, and is highly associated with decreased INPP4B expression, which together may compensate for ERG-mediated suppression of AKT signaling. We confirmed in PCa cells and a mouse PCa model that ERG suppresses IRS2 and AKT activation. In contrast, ERG downregulation did not increase INPP4B, suggesting its decrease is indirect and reflects selective pressure to suppress INPP4B function. Notably, INPP4B expression is decreased in PTEN-intact and PTEN-deficient T:E fusion tumors, suggesting selection for a nonredundant function. As ERG in T:E fusion tumors is AR regulated, we further assessed whether AR inhibition increases AKT activity in T:E fusion tumors. A T:E fusion positive PDX had increased AKT activity in vivo and response to AKT inhibition in vitro after androgen deprivation. Moreover, two clinical trials of neoadjuvant AR inhibition prior to radical prostatectomy showed greater increases in AKT activation in the T:E fusion positive versus negative tumors. These findings indicate that AKT activation may mitigate the efficacy of AR targeted therapy in T:E fusion PCa, and that these patients may most benefit from combination therapy targeting AR and AKT.

cancer biology↗

A genotoxic antibody drug conjugate targeting CD276/B7H3 demonstrates efficacy across multiple biomarker defined classes of treatment refractory metastatic prostate cancer

Antibody-drug conjugates (ADCs) are promising targeted cancer therapy; however, patient selection based solely on target antigen expression without consideration for cytotoxic payload vulnerabilities has plateaued clinical benefits. Biomarkers to capture patients who might benefit from specific ADCs have not been systematically determined for any cancer. We present a comprehensive therapeutic and biomarker analysis of a B7H3-ADC with pyrrolobenzodiazepine(PBD) payload in 26 treatment-resistant, metastatic prostate cancer(mPC) models. B7H3 is a tumor-specific surface protein widely expressed in mPC, and PBD is a DNA cross-linking agent. B7H3 expression was necessary but not sufficient for B7H3-PBD-ADC responsiveness. RB1 deficiency and/or replication stress, characteristics of poor prognosis, conferred sensitivity and were associated with complete tumor regression in both neuroendocrine (NEPC) and androgen receptor positive(ARPC) prostate cancer models, even with low B7H3 levels. Non-ARPC models, which are currently lacking efficacious treatment, demonstrated the highest replication stress and were most sensitive to treatment. In RB1 wild-type ARPC tumors, SLFN11 expression or select DNA repair mutations in SLFN11 non-expressors governed response. Significantly, wild-type TP53 predicted non-responsiveness (7/8 models). Overall, biomarker-focused selection of models led to high efficacy of in vivo treatment. These data enable a paradigm shift to biomarker-driven trial designs for maximizing clinical benefit of ADC therapies.

cancer biology↗

A cancer stem cell population underlies a multi-lineage phenotype and drug resistance in prostate cancer

PurposeTo resist lineage-dependent therapies such as androgen receptor inhibition in prostate cancer, cancer cells often adopt a stem-like state resulting in lineage-plasticity and phenotypic heterogeneity. We assessed the dynamics of lineage determination and cellular subpopulation expansion in treatment-resistant adenocarcinoma, amphicrine, and small cell neuroendocrine castrate resistant prostate cancers (CRPCs). Experimental DesignWe developed CRPC patient-derived organoid models that preserve heterogeneity of the originating tumor, including an amphicrine model harboring epigenetic driver mutations, ARID1A and ARID1B, and displaying a range of luminal and neuroendocrine phenotypes. We used single-cell RNA-seq, barcode lineage-tracing, single-cell ATAC-seq, and RNA-FISH to delineate the subpopulation structure of the heterogeneous organoids and define the lineage hierarchy, determine potential transcriptional regulators of amphicrine lineage-plasticity, and identify subpopulation-specific molecular targets for therapeutic intervention. ResultsTranscriptionally similar stem/progenitor cells were identified for all lineage populations. Lineage tracing in amphicrine CRPC showed that heterogeneity originated from distinct subclones of infrequent stem/progenitor cells that produced mainly quiescent differentiated amphicrine progeny. Amphicrine cells were enriched for secretory luminal, mesenchymal, and enzalutamide treatment persistent signatures. By contrast, adenocarcinoma CRPC had a less defined hierarchy, as progeny originated from stem/progenitor cells and self-renewing differentiated luminal cells. NEPC was composed almost exclusively of self-renewing stem/progenitor cells. Amphicrine stem cells demonstrated concurrent transcription factor activities associated with stem/progenitor, luminal epithelial and mesenchymal lineages. Finally, the amphicrine stem/progenitor subpopulation was specifically depleted with an AURKA inhibitor, which blocked tumor growth. ConclusionsThese data illuminate distinct origins and dynamics of subtype-specific CRPC plasticity in addition to demonstrating a strategy for targeting differentiation-competent stem cells. Translational RelevanceFor advanced prostate cancer, therapeutic resistance to androgen signaling suppression increasingly involves the development of lineage plasticity. The cellular states of transition and subpopulation heterogeneity that underlie lineage-plasticity are not well understood, which is an ongoing challenge to the design of effective treatments. Using patient-derived organoid models of various CRPC lineage subtypes, we observed distinct patterns with respect to stem/progenitor activity and associated growth phenotypes. The simultaneous expression of AR-driven and neuroendocrine identities, so-called amphicrine tumors, are thought to be an early dedifferentiation stage in plasticity-mediated resistance. We observed in an epigenetically-driven, amphicrine model of CRPC that a rare but necessary bipotent stem/progenitor population is suppressed by AURKA inhibitors, leading to tumor regression, while ARPC demonstrates both self-renewing differentiated luminal cells and stem/progenitors. These data suggest that AURKA inhibition may block the amplification of a resistance dedifferentiation pathway and should be considered in combination with AR signaling inhibitors for ARPC with characteristics of lineage plasticity.

cancer biology↗

Defining cellular population dynamics at single cell resolution during prostate cancer progression

Advanced prostate malignancies are a leading cause of cancer-related deaths in men, in large part due to our incomplete understanding of cellular drivers of disease progression. We investigated prostate cancer cell dynamics at single-cell resolution from disease onset to the development of androgen independence in vivo. We observe a dramatic expansion of a castration-resistant intermediate luminal cell type that correlates with treatment resistance and poor prognosis in human patients. Moreover, transformed epithelial cells and associated fibroblasts create a microenvironment conducive to pro-tumorigenic immune infiltration, which is in part androgen responsive. Androgen independent prostate cancer leads to significant diversification of intermediate luminal cell populations characterized by a range of androgen signaling activity inversely correlated with proliferation and mRNA translation. Accordingly, distinct epithelial populations are exquisitely sensitive to translation inhibition which leads to epithelial cell death, loss of pro-tumorigenic signaling, and decreased tumor heterogeneity. Our findings reveal a complex tumor environment largely dominated by castration-resistant luminal cells and immunosuppressive infiltrates.

cancer biology↗

Comparison of Approaches to Transcriptomic Analysis in Multi-Sampled Tumors

Intratumoral heterogeneity is a well-documented feature of human cancers associated with outcome and treatment resistance. However, a heterogeneous tumor transcriptome contributes an unknown level of variability to analyses of differentially expressed genes that may contribute to phenotypes of interest, including treatment response. Although current clinical practice and the vast majority of research studies use a single sample from each patient, decreasing costs in sequencing technologies and computing costs have made repeated-measures analyses increasingly economical. Repeatedly sampling the same tumor increases the statistical power of differentially expressed gene analysis that is indispensable towards downstream analysis and also increases ones understanding of within-tumor variance that may affect conclusions. Here, we compared five different methods for analyzing gene expression profiles derived from repeated sampling of human prostate tumors in two separate cohorts of patients. We also benchmarked the sensitivity of generalized linear models to linear mixed models for identifying differentially expressed genes contributing to relevant prostate cancer pathways based on a ground truth model.

bioinformatics↗

MEIS1 down-regulation by MYC mediates prostate cancer development through elevated HOXB13 expression and AR activity

Localized prostate cancer develops very slowly in most men, with the androgen receptor (AR) and MYC transcription factors amongst the most well-characterized drivers of prostate tumorigenesis. Canonically, MYC up-regulation in luminal prostate cancer cells functions to oppose the terminally differentiating effects of AR. However, the effects of MYC up-regulation are pleiotropic and inconsistent with a poorly proliferative phenotype. Here we show that increased MYC expression and activity are associated with the down-regulation of MEIS1, a HOX-family transcription factor. Using RNA-seq to profile a series of human prostate cancer specimens laser capture microdissected on the basis of MYC immunohistochemistry, MYC activity and MEIS1 expression were inversely correlated. Knockdown of MYC expression in prostate cancer cells increased expression of MEIS1 and increased occupancy of MYC at the MEIS1 locus. Finally, we show in laser capture microdissected human prostate cancer samples and the prostate TCGA cohort that MEIS1 expression is inversely proportional to AR activity as well as HOXB13, a known interacting protein of both AR and MEIS1. Collectively, our data demonstrate that elevated MYC in a subset of primary prostate cancers functions in a negative role in regulating MEIS1 expression, and that this down-regulation may contribute to MYC-driven development and progression.

cancer biology↗

Low abundance of circulating tumor DNA in localized prostate cancer

Despite decreased screening-based detection of clinically insignificant tumors, most diagnosed prostate cancers are still indolent, indicating a need for better strategies for detection of clinically significant disease prior to treatment. We hypothesized that patients with detectable circulating tumor DNA (ctDNA) were more likely to harbor aggressive disease. We applied ultra-low pass whole genome sequencing to profile cell-free DNA from 112 patients diagnosed with localized prostate cancer and performed targeted resequencing of plasma DNA for somatic mutations previously identified in matched solid tumor in nine cases. We also performed similar analyses on patients with metastatic prostate cancer. In all cases of localized disease, even in clinically high-risk patients who subsequently recurred, we did not detect ctDNA by either method in plasma acquired before surgery or before recurrence. In contrast, ctDNA was detected from patients with metastatic disease. Our findings demonstrate clear differences between localized and advanced prostate cancer with respect to the dissemination and detectability of ctDNA. Because allele-specific alterations in ctDNA are below the threshold for detection in localized prostate cancer, other approaches to identify cell-free nucleic acids of tumor origin may demonstrate better specificity for aggressive disease.

genomics↗