Integrative genotyping of cancer and immune phenotypes by long-read sequencing

Livius Penter; Mehdi Borji; Adi Nagler; Haoxiang Lyu; Wesley S Lu; Nicoletta Cieri; Katie Maurer; Giacomo Oliveira; Aziz M Al'Khafaji; Kiran V Garimella; Shuqiang Li; Donna S Neuberg; Jerome Ritz; Robert J Soiffer; Jacqueline S Garcia; Kenneth J Livak; Catherine J Wu

doi:10.1038/s41467-023-44137-7

Integrative genotyping of cancer and immune phenotypes by long-read sequencing

Nat Commun. 2024 Jan 2;15(1):32. doi: 10.1038/s41467-023-44137-7.

Authors

Livius Penter^#^{1

2

3

4

5}, Mehdi Borji^#^{1

2

6}, Adi Nagler^#^{1

2}, Haoxiang Lyu⁶, Wesley S Lu⁶, Nicoletta Cieri^{1

2

3}, Katie Maurer^{1

2

3}, Giacomo Oliveira^{1

2

3}, Aziz M Al'Khafaji², Kiran V Garimella², Shuqiang Li^{1

2

6}, Donna S Neuberg⁷, Jerome Ritz^{1

3

8}, Robert J Soiffer^{1

3

8}, Jacqueline S Garcia^{1

3}, Kenneth J Livak^{1

6}, Catherine J Wu^{9

10

11

12}

Affiliations

¹ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
² Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
³ Harvard Medical School, Boston, MA, USA.
⁴ Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
⁵ Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, 10117, Berlin, Germany.
⁶ Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA.
⁷ Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
⁸ Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁹ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. catherine_wu@dfci.harvard.edu.
¹⁰ Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA. catherine_wu@dfci.harvard.edu.
¹¹ Harvard Medical School, Boston, MA, USA. catherine_wu@dfci.harvard.edu.
¹² Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. catherine_wu@dfci.harvard.edu.

^# Contributed equally.

Abstract

Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural 'barcodes', we define the optimal targets for nanoranger, namely those loci close to the 5' end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Gene Expression Profiling / methods
Genotype
High-Throughput Nucleotide Sequencing* / methods
Humans
Leukemia, Myeloid, Acute* / genetics
Leukemia, Myeloid, Acute* / pathology
Phenotype

Abstract

Publication types

MeSH terms

Grants and funding