Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq

被引:312
|
作者
Karaayvaz, Mihriban [1 ,2 ]
Cristea, Simona [3 ,4 ,5 ]
Gillespie, Shawn M. [1 ,2 ,6 ]
Patel, Anoop P. [2 ,7 ]
Mylvaganam, Ravindra [1 ,2 ,6 ]
Luo, Christina C. [1 ,2 ,6 ]
Specht, Michelle C. [2 ,8 ]
Bernstein, Bradley E. [1 ,2 ,6 ,9 ,10 ]
Michor, Franziska [3 ,4 ,5 ,9 ,10 ,11 ]
Ellisen, Leif W. [1 ,2 ]
机构
[1] Massachusetts Gen Hosp, Ctr Canc Res, Boston, MA 02114 USA
[2] Harvard Med Sch, Boston, MA 02114 USA
[3] Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02115 USA
[4] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02215 USA
[5] Harvard Univ, Dept Stem Cell & Regenerat Biol, Cambridge, MA 02138 USA
[6] Massachusetts Gen Hosp, Dept Pathol, Boston, MA 02114 USA
[7] Massachusetts Gen Hosp, Dept Neurosurg, Boston, MA 02114 USA
[8] Massachusetts Gen Hosp, Dept Surg Oncol, Boston, MA 02114 USA
[9] Broad Inst Harvard & MIT, Cambridge, MA 02139 USA
[10] Ludwig Ctr Harvard, Boston, MA 02215 USA
[11] Dana Farber Canc Inst, Ctr Canc Evolut, Boston, MA 02115 USA
基金
瑞士国家科学基金会;
关键词
NEGATIVE BREAST-CANCER; TUMOR-INFILTRATING LYMPHOCYTES; STEM-CELLS; EXPRESSION; EVOLUTION; GLYCOSPHINGOLIPIDS; PATTERNS; SURVIVAL;
D O I
10.1038/s41467-018-06052-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conducted single-cell RNA-sequencing (scRNA-seq) of >1500 cells from six primary TNBC. Here, we show that intercellular heterogeneity of gene expression programs within each tumor is variable and largely correlates with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation predicts long-term outcomes for TNBC patients in a large cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Comprehensive analysis of single-cell RNA-seq and bulk RNA-seq revealed the heterogeneity and convergence of the immune microenvironment in renal cell carcinoma
    Lv, Shihui
    Tao, Liping
    Liao, Hongbing
    Huang, Zhiming
    Lu, Yongyong
    FUNCTIONAL & INTEGRATIVE GENOMICS, 2023, 23 (02)
  • [22] Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq data
    Fustero-Torre, Coral
    Jimenez-Santos, Maria Jose
    Garcia-Martin, Santiago
    Carretero-Puche, Carlos
    Garcia-Jimeno, Luis
    Ivanchuk, Vadym
    Di Domenico, Tomas
    Gomez-Lopez, Gonzalo
    Al-Shahrour, Fatima
    GENOME MEDICINE, 2021, 13 (01)
  • [23] Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer
    Fasterius, Erik
    Uhlen, Mathias
    Szigyarto, Cristina Al-Khalili
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [24] Unveiling functional heterogeneity in breast cancer multicellular tumor spheroids through single-cell RNA-seq
    Andres Mucino-Olmos, Erick
    Vazquez-Jimenez, Aaron
    Avila-Ponce de Leon, Ugo
    Matadamas-Guzman, Meztli
    Maldonado, Vilma
    Lopez-Santaella, Tayde
    Hernandez-Hernandez, Abrahan
    Resendis-Antonio, Osbaldo
    SCIENTIFIC REPORTS, 2020, 10 (01)
  • [25] Transcriptional landscape associated with TNBC resistance to neoadjuvant chemotherapy revealed by single-cell RNA-seq
    Vishnubalaji, Radhakrishnan
    Alajez, Nehad M.
    MOLECULAR THERAPY ONCOLYTICS, 2021, 23 : 151 - 162
  • [26] Correlation Imputation for Single-Cell RNA-seq
    Gan, Luqin
    Vinci, Giuseppe
    Allen, Genevera I.
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2022, 29 (05) : 465 - 482
  • [27] Unveiling functional heterogeneity in breast cancer multicellular tumor spheroids through single-cell RNA-seq
    Erick Andrés Muciño-Olmos
    Aarón Vázquez-Jiménez
    Ugo Avila-Ponce de León
    Meztli Matadamas-Guzman
    Vilma Maldonado
    Tayde López-Santaella
    Abrahan Hernández-Hernández
    Osbaldo Resendis-Antonio
    Scientific Reports, 10
  • [28] PRECISION AND ACCURACY IN SINGLE-CELL RNA-SEQ
    Dai, Rujia
    Zhang, Ming
    Chu, Tianyao
    Kopp, Richard
    Zhang, Chunling
    Liu, Kefu
    Wang, Yue
    Wang, Xusheng
    Chen, Chao
    Liu, Chunyu
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2024, 87 : 21 - 21
  • [29] Single-cell RNA-seq—now with protein
    Vesna Todorovic
    Nature Methods, 2017, 14 : 1028 - 1029
  • [30] Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data
    Fan, Jean
    Lee, Hae-Ock
    Lee, Soohyun
    Ryu, Da-eun
    Lee, Semin
    Xue, Catherine
    Kim, Seok Jin
    Kim, Kihyun
    Barkas, Nikolaos
    Park, Peter J.
    Park, Woong-Yang
    Kharchenko, Peter V.
    GENOME RESEARCH, 2018, 28 (08) : 1217 - 1227