Automated imaging and identification of proteoforms directly from ovarian cancer tissue

John P McGee; Pei Su; Kenneth R Durbin; Michael A R Hollas; Nicholas W Bateman; G Larry Maxwell; Thomas P Conrads; Ryan T Fellers; Rafael D Melani; Jeannie M Camarillo; Jared O Kafader; Neil L Kelleher

doi:10.1038/s41467-023-42208-3

Automated imaging and identification of proteoforms directly from ovarian cancer tissue

Nat Commun. 2023 Oct 14;14(1):6478. doi: 10.1038/s41467-023-42208-3.

Authors

John P McGee^#¹, Pei Su^#¹, Kenneth R Durbin², Michael A R Hollas², Nicholas W Bateman^{3

4}, G Larry Maxwell^{4

5}, Thomas P Conrads^{4

5}, Ryan T Fellers², Rafael D Melani¹, Jeannie M Camarillo^{1

6}, Jared O Kafader^{1

6}, Neil L Kelleher^{7

8

9}

Affiliations

¹ Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA.
² Proteomics Center of Excellence, Evanston, IL, USA.
³ Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA.
⁴ Department of Gynecologic Surgery and Obstetrics and the Gynecologic Cancer Center of Excellence, John P. Murtha Cancer Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
⁵ Women's Health Integrated Research Center, Inova Women's Service Line, Inova Health System, Falls Church, VA, USA.
⁶ Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
⁷ Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA. n-kelleher@northwestern.edu.
⁸ Proteomics Center of Excellence, Evanston, IL, USA. n-kelleher@northwestern.edu.
⁹ Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA. n-kelleher@northwestern.edu.

^# Contributed equally.

Abstract

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS²) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS² identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer.

Publication types

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

MeSH terms

Female
Humans
Ovarian Neoplasms* / diagnostic imaging
Proteome* / analysis
Software
Tandem Mass Spectrometry / methods
Tumor Microenvironment

Substances

Proteome

Abstract

Publication types

MeSH terms

Substances

Grants and funding