MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1186/s12863-026-01435-5

Медицинская библиотека · BMC genomic data · 2026

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

Jovel Juan, Polzer Bernhard, Patterson Jordan, Yong Hou, Vasquez Catalina, O'keefe Sandra, Pink Desmond, Li Guibo, Fairey Adrian, Adam Benjamin, Teitelbaum Jeremy, Salimi Amir, Kirsh Stefan, Alberter Barbara, Lowes Lori, Carpenter Eric, Kolinsky Michael, Zhu Zhongyi, Zhou Qing, Venner Peter, Venner Christopher, Williams David, Allan Alison, Boutros Paul C, Klein Christoph A, Wong Gane, Lewis John D

СтатьяКлинический случайПеревод в очереди

Аннотация

BACKGROUND

Prostate 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.

RESULTS

We 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.

CONCLUSIONS

This 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.

Для цитирования: Jovel Juan, Polzer Bernhard, Patterson Jordan, Yong Hou, Vasquez Catalina, O'keefe Sandra, Pink Desmond, Li Guibo, Fairey Adrian, Adam Benjamin, Teitelbaum Jeremy, Salimi Amir, Kirsh Stefan, Alberter Barbara, Lowes Lori, Carpenter Eric, Kolinsky Michael, Zhu Zhongyi, Zhou Qing, Venner Peter, Venner Christopher, Williams David, Allan Alison, Boutros Paul C, Klein Christoph A, Wong Gane, Lewis John D. Single-cell genomic analysis of cancer cells from one treatment-naïve patient with metastatic prostate cancer.. BMC genomic data. 2026. DOI: 10.1186/s12863-026-01435-5.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.