Fei Su1, Wei Zhang2, Dalei Zhang3, Yaqun Zhang3, Cheng Pang3, Yingying Huang4, Miao Wang3, Luwei Cui3, Lei He2, Jinsong Zhang2, Lihui Zou5, Junhua Zhang5, Wenqinq Li5, Lin Li4, Jianyong Shao6, Jie Ma7, Fei Xiao8, Ming Liu9. 1. Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China; The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. 2. Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China. 3. Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. 4. Department of Oncology, Beijing Hospital, National Center of Gerontology, Beijing, China. 5. The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. 6. Sun Yat-sen University Cancer Center, Guangzhou, China. 7. Center for Biotherapy, Beijing Hospital, National Center of Gerontology, Beijing, China; State Key Lab of Molecular Oncology, National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: majie4685@bjhmoh.cn. 8. Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, China; The Key Laboratory of Geriatrics, Beijing Hospital, National Center of Gerontology, Beijing, China. Electronic address: xiaofei3965@bjhmoh.cn. 9. Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, China. Electronic address: liuming3222@bjhmoh.cn.
Abstract
BACKGROUND: Prostate adenocarcinoma (PCa) is a complex genetic disease, and the implementation of personalized treatment in PCa faces challenges due to significant inter- and intrapatient tumor heterogeneities. OBJECTIVE: To systematically explore the genomic complexity of tumor cells with different Gleason scores (GSs) in PCa. DESIGN, SETTING, AND PARTICIPANTS: We performed single-cell whole genome sequencing of 17 tumor cells from localized lesions with distinct GS and matched four normal samples from two prostatectomy patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: All classes of genomic alterations were identified, including substitutions, insertions/deletions, copy number alterations, and rearrangements. RESULTS AND LIMITATIONS: Significant spatial, intra- and intertumoral heterogeneities were observed at the cellular level. In the patient 1, all cells shared the same TP53 driver mutation, implying a monoclonal origin of PCa. In the patient 2, only a subpopulation of cells contained the TP53 driver mutation, whereas other cells carried different driver mutations, indicating a typical polyclonal model with separate clonal cell expansions. The tumor cells from different sides of prostate owned various mutation patterns. Considerable neoantigens were predicted among different cells, implying unknown immune editing components helping prostate tumor cells escaping from immune surveillance. CONCLUSIONS: There is a significant spatial genomic heterogeneity even in the same PCa patient. Our study also provides the first genome-wide evidence at single-cell level, supporting that the origin of PCa could be either polyclonal or monoclonal, which has implications for treatment decisions for prostate cancer. PATIENT SUMMARY: We reported the first single-cell whole genomic data of prostate adenocarcinoma (PCa) from different Gleason scores. Identification of these genetic alterations may help understand PCa tumor progression and clonal evolution.
BACKGROUND:Prostate adenocarcinoma (PCa) is a complex genetic disease, and the implementation of personalized treatment in PCa faces challenges due to significant inter- and intrapatient tumor heterogeneities. OBJECTIVE: To systematically explore the genomic complexity of tumor cells with different Gleason scores (GSs) in PCa. DESIGN, SETTING, AND PARTICIPANTS: We performed single-cell whole genome sequencing of 17 tumor cells from localized lesions with distinct GS and matched four normal samples from two prostatectomy patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: All classes of genomic alterations were identified, including substitutions, insertions/deletions, copy number alterations, and rearrangements. RESULTS AND LIMITATIONS: Significant spatial, intra- and intertumoral heterogeneities were observed at the cellular level. In the patient 1, all cells shared the same TP53 driver mutation, implying a monoclonal origin of PCa. In the patient 2, only a subpopulation of cells contained the TP53 driver mutation, whereas other cells carried different driver mutations, indicating a typical polyclonal model with separate clonal cell expansions. The tumor cells from different sides of prostate owned various mutation patterns. Considerable neoantigens were predicted among different cells, implying unknown immune editing components helping prostate tumor cells escaping from immune surveillance. CONCLUSIONS: There is a significant spatial genomic heterogeneity even in the same PCa patient. Our study also provides the first genome-wide evidence at single-cell level, supporting that the origin of PCa could be either polyclonal or monoclonal, which has implications for treatment decisions for prostate cancer. PATIENT SUMMARY: We reported the first single-cell whole genomic data of prostate adenocarcinoma (PCa) from different Gleason scores. Identification of these genetic alterations may help understand PCa tumor progression and clonal evolution.
Authors: Michael C Haffner; Wilbert Zwart; Martine P Roudier; Lawrence D True; William G Nelson; Jonathan I Epstein; Angelo M De Marzo; Peter S Nelson; Srinivasan Yegnasubramanian Journal: Nat Rev Urol Date: 2020-12-16 Impact factor: 14.432
Authors: Sebnem Ece Eksi; Alex Chitsazan; Zeynep Sayar; George V Thomas; Andrew J Fields; Ryan P Kopp; Paul T Spellman; Andrew C Adey Journal: Nat Commun Date: 2021-12-15 Impact factor: 14.919