Evidence map›Paper›PMID 42098607›Full record

ArticleBMC genomic data2026

Single-cell genomic analysis of cancer cells from one treatment-naïve patient with metastatic prostate cancer.

Juan Jovel, Bernhard Polzer, Jordan Patterson, Hou Yong, Catalina Vasquez, Sandra O'keefe, Desmond Pink, Guibo Li, Adrian Fairey, Benjamin Adam and 17 more

Abstract readCase Reports
In one paragraph

Article in BMC genomic data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

27 authors.

Juan JovelOffice of Research, University of Alberta, Edmonton, AB, T6C 4G9, Canada.
Bernhard PolzerFraunhofer Institute for Toxicology and Experimental Medicine, 93053, Regensburg, Germany.
Jordan PattersonDepartment of Medicine, University of Alberta, Edmonton, AB, T6G 1Z1, Canada.
Hou YongBGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen, China.
Catalina VasquezDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada.
Sandra O'keefeDepartment of Medicine, University of Alberta, Edmonton, AB, T6G 1Z1, Canada.
Desmond PinkDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada.
Guibo LiBGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen, China.
Adrian FaireyDepartment of Surgery, University of Alberta, Edmonton, AB, Canada.
Benjamin AdamDepartment of Laboratory Medicine & Pathology, University of Alberta, Edmonton, AB, Canada.
Jeremy TeitelbaumDepartment of Mathematics, University of Connecticut, Storrs, CT, USA.
Amir SalimiDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.
Stefan KirshExperimental Medicine and Therapy Research, University of Regensburg, Regensburg, Germany.
Barbara AlberterFraunhofer Institute for Toxicology and Experimental Medicine, 93053, Regensburg, Germany.
Lori LowesDepartment of Anatomy and Cell Biology, Western University, London, ON, Canada.
Eric CarpenterDepartment of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
Michael KolinskyDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada.
Zhongyi ZhuBGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen, China.
Qing ZhouBGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen, China.
Peter VennerDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada.
Christopher VennerDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada.
David WilliamsDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada.
Alison AllanDepartment of Anatomy and Cell Biology, Western University, London, ON, Canada.
Paul C BoutrosDepartment of Human Genetics & Urology, University of California, Los Angeles, CA, USA.
Christoph A KleinFraunhofer Institute for Toxicology and Experimental Medicine, 93053, Regensburg, Germany.
Gane WongDepartment of Medicine, University of Alberta, Edmonton, AB, T6G 1Z1, Canada.
John D LewisDepartment of Oncology, University of Alberta, 5-142C Katz Group Building, Edmonton, AB, T6G 2E1, Canada. jdlewis@ualberta.ca.

Funding

Alberta Innovates Health Solutions CRIO Cancer Grant 3668
6 · The paper itself

Abstract

backgroundProstate cancer is among the most prevalent malignancies in men and a leading cause of cancer mortality worldwide. While localized prostate cancer is often curable, progression to metastatic and castration-resistant disease either in lymph nodes or bone/bone marrow remains the major cause of death. Understanding the genomic events that drive metastasis-particularly in treatment-naïve patients-is critical to improving early detection and individualized therapy. Bulk tumor sequencing has revealed key mutational signatures but cannot resolve the cellular heterogeneity and clonal dynamics underlying metastatic spread. Single-cell genomic approaches now enable high-resolution dissection of tumor evolution, uncovering the diversity of cancer clones across disease sites.

resultsWe performed whole-genome and whole-exome sequencing on single cancer cells from a treatment-naïve patient with metastatic prostate cancer, isolating cells from the primary tumor, circulating tumor cells (CTCs), disseminated tumor cells (DTCs) in bone marrow, and metastatic bone lesions. Copy number aberrations (CNAs) and single-nucleotide variants (SNVs) were characterized to define genomic heterogeneity and infer clonal relationships. Frequent monoallelic losses in tumor suppressors (PTEN, TP53, FOXO4, STAG2) and gains in oncogenes (MTOR, RAF1, HRAS) and an angiogenic growth factor (VEGFB), were observed. Metastatic cells displayed fewer genomic alterations than CTCs or DTCs. While this observation is consistent with the hypothesis that metastatic competence may be associated with relative genomic stability, normal cell contamination of the metastatic biopsy cannot be excluded, and this interpretation should be considered preliminary. Clonal evolution analysis revealed a complex branching pattern consistent with multidirectional dissemination, suggesting bidirectional seeding between the primary tumor, circulation, and metastatic sites as one possible model of spread, though alternative explanations including phylogenetic reconstruction artefacts cannot be excluded from a single-patient study.

conclusionsThis study provides a single-cell genomic map of metastatic prostate cancer from a treatment-naïve patient, highlighting the coexistence of diverse subclones across disease sites and supporting a multidirectional model of cancer spread.These findings raise the hypothesis that metastatic progression can emerge from multiple subclones with distinct CNA and SNV profiles. Single-cell genomic profiling of untreated tumors represents a promising approach to reconstruct clonal evolution and inform precision therapies targeting early metastatic lineages, though validation in larger patient cohorts will be required. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

GenomicsProstatic NeoplasmsSingle-Cell AnalysisBone NeoplasmsDNA Copy Number VariationsExome SequencingHumansMaleNeoplasm MetastasisNeoplastic Cells, CirculatingPolymorphism, Single NucleotideCirculating tumor cellsClonal evolutionCopy number aberrationsDisseminated tumor cellsMetastasisProstate cancerSingle-cell genomics

Identifiers

PMID42098607
PMCPMC13326455

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.