Abstract
Background:
Three-dimensional chromosome loop conformations are powerful regulators of gene expression. These chromosome conformations can be detected both in tumour and in circulating cells and have significant disease biomarker potential. We have recently detected specific chromosome conformations in circulating cells of patients with prostate cancer (PCa) which were similar to ones found in their primary tumours, however, the possibility of horizontal transfer of chromosome conformations was not studied previously.
Methods:
Human monocytes (U937) were co-cultured in Boyden chambers through 0.4 uM membrane with or without PC-3 human PCa cells or their conditioned media and a custom DNA microarray for 900,000 chromosomal loops covering all coding loci and non-coding RNA genes was performed on each part of the co-culture system.
Results:
We have detected 684 PC-3 cell-specific chromosome conformations across the whole genome that were absent in naïve monocytes but appeared in monocytes co-cultured with PC-3 cells or with PC-3-conditioned media. Comparing PC3-specific conformations to the ones we have previously detected in systemic circulation of high-risk PCa patients revealed 9 positive loops present in both settings.
Conclusions:
Our results demonstrate for the first time a proof of concept for horizontal transfer of chromosome conformations without direct cell-cell contact. This carries high clinical relevance as we have previously observed chromatin conformations in circulating cells of patients with melanoma and PCa similar to ones in their primary tumours. These changes can be used as highly specific biomarkers for diagnosis and prognosis. Further studies are required to elucidate the specific mechanism of chromosome conformations transfer and its clinical significance in particular diseases.
Introduction
Genome-wide association studies have shown that surprisingly the majority of cancer-risk associated loci are located outside of known protein-coding regions (). It is now well established that epigenetic modifications (DNA methylation, histone acetylation and chromosome conformation) have an important role in aberrant gene expression and cancer progression. In prostate cancer (PCa) DNA methylation (hypo- and hypermethylation) is the best-characterized epigenetic alteration (, ). Histone modifications also contribute to PCa progression (, ), but the role of chromosome conformations is much less studied.
Our recent studies have shown significant involvement of 3D chromosome loop interactions in gene expression (). These dynamic loops can be detected using chromosome conformation capture (3C) technologies. Due to their apparent prevalence in disease, they have gained considerable attention as potential diagnostic markers (–). One of the main advantages of 3C-based chromatin interactions as biomarkers is that DNA cross-linking is relatively stable, and following proximity ligation, gives rise to a stable DNA product (Figure 1) ().
Figure 1
We have developed a novel epigenetic assay, as a next generation of the 3C technique (
Recently we have published distinct CCSs that were present both in circulating cells and primary tumours of PCa patients (
Methods
Cell culture
Human prostate cancer cell line PC-3 and human monocytes U937 were purchased from ATCC (Manassas, VA, USA). Cells were cultured and maintained in RPMI 1640 Medium, GlutaMAX™ Supplement containing 10% foetal bovine serum and penicillin-streptomycin (5,000 U/mL) (Gibco) at 37°C in a humidified atmosphere of 5% CO2. Cell lines were kept in culture for up to 30 passages. For co-cultures, PC-3 cells were seeded into the 6-well plates at 1x105 cells per well in complete medium, as shown in the Figure 1A. After 24 hours, media was changed to serum-free for a further 24 hours. Transwells (Corning®) containing U937 cells were placed in each well. Cells were harvested separately after 24h co-incubation. For conditioned media experiment, serum-free media incubated with PC-3 cells for 24 hours was collected, centrifuged at 2500rpm for 5 minutes and supernatant added to U937 cells.
Sample preparation
Whole cell lysate was obtained from individual components of co-culture system by harvesting the cells, centrifuging them 2500rpm for 5 minutes and resuspending them in lysis buffer as described before (
DNA CHIP analysis
Custom-made CGH Agilent microarray (8x60k) platform was designed to test technical and biological repeats for >900,000 potential chromosome conformations covering all coding loci and non-coding RNA genes. Gene sequences obtained from www.ensembl.org were used for computational prediction of interchromatin interactions using EpiSwitch™ software. Samples generated as described above were hybridized to the array, and differential presence or absence of each chromosome conformation was identified. LIMMA linear modelling with empirical Bayes moderation of the standard errors, subsequent abundance filtering and cluster analysis were used in data analysis as described before (
Nested polymerase chain reaction
Chromosome conformations identified using the DNA CHIP were confirmed using nested PCR performed as recently described (
Results
Identification of the group markers
PC3 cells were cultured alone or with U937 cells via membrane (Figure 1A) and compared to U937 cells cultured alone or co-cultured with PC3 cells or their conditioned medium. DNA from whole cells was isolated as described in materials and methods and intrachromatin associations were captured using formaldehyde crosslinking, restriction digestion and ligation as described before (
A customized CGH Agilent microarray platform (>900k chromosome conformations) was designed to identify chromosome conformations across the whole genome. LIMMA linear modelling with empirical Bayes moderation of the standard errors, subsequent abundance filtering and cluster analysis were used to define the presence or absence of each locus. Nested PCR was used to confirm identified biomarkers.
Group variance and presence of outlier samples were assessed using principal component analysis that showed that PC-3 cultured alone (points 1-3 in Figure 2A) had a separate 3C profile from PC-3 after co-culture (points 4-6 in Figure 2A). Similarly, U937 monocytes showed a clear distinction between cells cultured alone (points 7-9 in Figure 2B) and those co-cultured with PC3 cells (points 10-12 in Figure 2B) or PC3-conditioned media (points 14,15 in Figure 2).
Figure 2

Principal component analysis for the CCSs distribution between samples. Principal component analysis for the CCSs in PC-3 (A) and U937 (B) before and after co-cultures demonstrating a change in CCSs distribution.
VENN diagram of PC3-specific CCSs (Figure 3A) shows 684 CCSs are shared between PC3 cells and U937 cells cultured with PC-3 cells via membrane or in PC3 conditioned media. Each set has interaction frequency over 1.2 and p value ≤0.05. Of note, these statistically significant CCSs are absent in U937 cultured alone. It appears conditioned media induces more CCSs transfer (1960 conformations) than membrane co-culture (917 conformations). Interestingly, functional enrichment analysis of 684 CCSs switching to PC3 profile under both co-culture and conditioned media treatment fit into well-characterized single compact protein interaction network (Figure S1). This network has direct relationship to the genetic loci captured by the validated 3C markers that we have identified in the circulating cells of PCa patients (in the loci of BMP6, ERG, MSR1, MUC1, ACAT1 and DAPK1 genes) (
Figure 3

Venn diagrams of CCSs overlap between treatment groups and high-risk PCa patients. (A–D). Venn diagrams indicating the number of overlapping CCSs between various groups.
We have then compared the PC3-specific CCSs to the ones we have detected in systemic circulation of high-risk PCa patients (
Table S2 shows the 9 Positive loops present in both high risk PCa patients (
Of interest, Figure 3C shows 122 CCSs that are present either in naïve U937 cells or in U937 cells co-cultured with PC-3 cells or their conditioned media. Each set has interaction frequency over 1.2, p value ≤0.05 and represents U937 specific CCS, which are not affected by co-culturing. When compared to the systemic PCa signatures identified in our previous study (
Discussion
The CCSs have a well-recognized advantage for the biomarker use (
Our data demonstrate that co-culturing monocytes with PCa cells leads to new stable chromatin loops in the loci of multiple genes (Figure 3 and Table S2) including those we have previously detected in systemic circulation of high-risk PCa patients (
Multiple previous studies have demonstrated horizontal transfer of genetic information (
In this study, we have used classical exosome experiment settings (Figure 1) to demonstrate how indirect contact between cells (either though a membrane or via conditioned media) can mediate this process. In our recent publication we have demonstrated the CCCs that are detected in circulating cells of PCa patients that strongly resemble CCCs detected in primary prostate tumours (
Throughout the exosome research two of the most important questions pertaining are: a) what is the effector target of exosome traffic and b) what is the mechanism by which exosomes lead to change in phenotype. Our data points that at least partly the exosome traffic targets and switches regulatory 3D architecture in effector cells. That switch is binary, stable and works over the threshold similarly both in cell-cell and cell-conditioned media settings. The switch observed in in vitro treatments is consistent with systemic validated switches observed in patients (
The results of this study provide mechanistic explanation of the concordance between CCCs detected in circulating cells of PCa patients and in their primary tumours (
Conclusions
In this pilot study, reported in this rapid communication, we have identified stable CCSs that are acquired by cells upon indirect co-culture demonstrating for the first-time direct transfer of 3D genome architecture between cancer and circulating cells. These CCSs are similar to the ones we have identified in PCa patients and have significant potential for the development of quick diagnostic and prognostic blood tests for PCa. Future studies are required to address: a) the means of epigenetic information transfer (e.g. exosomes, long non-coding RNA) and b) the potential mechanisms of their effect on the 3D chromosome conformations.
Funding
This work was funded by Oxford BioDynamics.
Acknowledgments
The authors would like to thank members of Oxford BioDynamics; Benjamin Foulkes, Chloe Bird, Diana Jaramillo Mahecha, Emily Corfield, Warren Elvidge, Ryan Powell for the laboratory work.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
EH, AR, AA, and DP conceived the study. HA, EH, MS, AR, AA and DP planned, performed and reviewed experiments and analyzed the data. JG, WW and MW provided critical assessment of the manuscript. All authors participated in writing and editing the manuscript. All authors contributed to the article and approved the submitted version.
Conflict of interest
EH, MS, AR, WW, JG and AA are employees of Oxford BioDynamics. AA and AR are company directors. Oxford BioDynamics holds patents on the EpiSwitch™ technology.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2022.990842/full#supplementary-material
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Summary
Keywords
prostate cancer, nucleome, 3C, blood test, horizontal gene transfer
Citation
Alshaker H, Hunter E, Salter M, Ramadass A, Westra W, Winkler M, Green J, Akoulitchev A and Pchejetski D (2022) Monocytes acquire prostate cancer specific chromatin conformations upon indirect co-culture with prostate cancer cells. Front. Oncol. 12:990842. doi: 10.3389/fonc.2022.990842
Received
10 July 2022
Accepted
02 August 2022
Published
19 August 2022
Volume
12 - 2022
Edited by
Mustafa Ozen, Baylor College of Medicine, United States
Reviewed by
Vadim V. Sumbayev, University of Kent, United Kingdom; Elizaveta Fasler-Kan, Bern University Hospital, Switzerland
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Copyright
© 2022 Alshaker, Hunter, Salter, Ramadass, Westra, Winkler, Green, Akoulitchev and Pchejetski.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dmitri Pchejetski, d.pshezhetskiy@uea.ac.uk
This article was submitted to Genitourinary Oncology, a section of the journal Frontiers in Oncology
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.