PPS21. Clonality analysis reveals a right upper quadrant origin of malignant peritoneal mesothelioma

Thursday, March 5, 2026

10:00 AM - 10:30 AM MST

Location: HUB Poster Park - West Hall 1-3

Primary Author(s)

Shruthi R. Perati, MD

PGY-3 General Surgery Resident
Surgical Oncology Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
NW Washington, District of Columbia, United States

Co-Author(s)

CW

Chih Hao Wu, B.S.

Predoctoral Fellow, Cancer Data Science Lab
National Institutes of Health
Bethesda, Maryland, United States
EA

Evsen Arikan, M.D.

Clinical Fellow of Pathology
National Institutes of Health
Bethesda, Maryland, United States
EG

Edward Michael Gertz, PhD

Computational Biologist, Cancer Data Science Lab
National Institutes of Health
Bethesda, Maryland, United States
CD

Chi-Ping Day, PhD

Senior Research Biologist
National Institutes of Health
Bethesda, Maryland, United States
AW

Andrew Warner, n/a

Research Associate
Molecular Histopathology Laboratory, Frederick National Laboratory for Cancer Research
Bethesda, Maryland, United States
JM

Jennifer Matta, n/a

Research Associate
Molecular Histopathology Laboratory, Frederick National Laboratory for Cancer Research
Bethesda, Maryland, United States
JK

Jiyeun Kim, n/a

Research Associate
Molecular Histopathology Laboratory, Frederick National Laboratory for Cancer Research
Bethesda, Maryland, United States
JS

Jyoti Shetty, PhD

Center for Cancer Research, Genomics Core
National Institutes of Health
Bethesda, Maryland, United States
YZ

Yongmei Zhao, PhD

Bioinformatician
National Institutes of Health
Bethesda, Maryland, United States
XW

Xiaolin Wu, PhD

Bioinformatician
National Institutes of Health
Bethesda, Maryland, United States
Rachael Lowney, MD (she/her/hers)

Surgical Oncology Research Fellow
Surgical Oncology Program/ National Cancer Institute/ National Institute of Health
Bethesda, Maryland, United States

Poster Presenter(s)

Haarika Chalasani, MD

Surgical Oncology Research Fellow
National Institutes of Health
Bethesda, Maryland, United States

Co-Author(s)

SG

Stephanie Gregory, MD

General Surgery Resident
National Institutes of Health
New Brunswick, New Jersey, United States
SC

Stephanie Canady, n/a

Research Nurse Specialist
National Institutes of Health
Bethesda, Maryland, United States
SJ

Stacy Joyce, n/a

Surgical Oncology Physician Assistant
National Institutes of Health
Bethesda, Maryland, United States
MS

Molly Sullivan, n/a

Surgical Oncology Nurse Practitioner
National Institutes of Health
Bethesda, Maryland, United States
DA

Diane Ahn, n/a

Surgical Oncology Patient Care Coordinator
National Institutes of Health
Bethesda, Maryland, United States
BT

Bao Tran, PhD

Head, Next-Generation Sequencing Production Group
National Institutes of Health
Bethesda, Maryland, United States
CS

Cenk Sahinalp, PhD

Senior Investigator, Cancer Data Science Lab
National Institutes of Health
Bethesda, Maryland, United States
Andrew M. Blakely, MD

Surgical Oncologist
Surgical Oncology Branch / National Cancer Institute / National Institute of Health
Bethesda, Maryland, United States

Introduction: Malignant peritoneal mesothelioma (MPeM) is staged using the Peritoneal Carcinomatosis Index (PCI) to quantify tumor burden and guide resectability. Although the PCI assigns equal weight to all abdominopelvic regions, it remains unclear whether MPeM in specific regions reflects early or late disease. We investigated peritoneal clonality to delineate spatiotemporal progression of MPeM and refine staging.

Methods: Peritoneal samples were studied from patients with epithelioid MPeM who underwent cytoreductive surgery on trial NCT04847063 from 2021-2024. Representative tissue sections were selected for laser capture microdissection and whole exome sequencing with matched normal peripheral blood (PBMCs) (Figure A). Somatic single-nucleotide variants (SNVs) were jointly called across multiple samples from each patient. Copy number-neutral SNVs were grouped to form mutational clusters or “subclones”. Subclones were mapped to phylogenetic trees using combinatorial optimization to minimize frequency discrepancies. Spatial migration history was inferred from subclone prevalences implied by the optimized trees.

Results:

Of 52 MPeM samples sequenced from 12 patients (median age 46 years), 67% (8/12) were male and 75% (9/12) received neoadjuvant therapy. Median PCI at time of cytoreductive surgery was 24 (IQR 20-30), and 58% (7/12) had germline mutations (n=6 BAP1, n=1 MUTYH). Clonal mutations were identified for all samples and organized into clusters of mutations that tended to co-occur. Heat maps demonstrated the relative abundance of subclones of mutations in each tumor sample (Figures B-C). Stepwise, conserved mutational patterns were observed across upper abdominal regions, with distinct new subclones emerging at higher prevalence in pelvic sites (Figure D). These findings were independent of germline status and suggest direct local extension within the upper abdomen, as well as potential peritoneal seeding to the pelvis along the typical clockwise peritoneal fluid currents; evidence of ‘backflow’ of subclones further indicates bidirectional tumor migration. (Figure F).

Conclusions:

MPeM originates from an initial clone, most often localizable to the right upper quadrant parietal peritoneum, with subsequent migration to other peritoneal regions. This pattern is particularly evident in BAP1 germline-mutant MPeM, as its indolent disease course enables clearer delineation of clonal phylogeny and migratory trajectories over time. Such insights may inform MPeM-specific disease staging and resectability decisions.

Learning Objectives:

Describe how spatial and phylogenetic analyses can be used to trace clonal evolution and migration patterns in malignant peritoneal mesothelioma (MPeM).
Recognize evidence supporting a likely right upper quadrant parietal peritoneal origin of MPeM and its directional spread along peritoneal fluid currents.
Discuss how insights from clonal and spatial mapping may refine MPeM staging frameworks.