industrialized-artificial-intelligence-guided-laser-microdissection

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell ...

Uniformed Services University and Walter Reed National Military Medical Center

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor "purity." Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.

Christine Rojas

Women’s Health Integrated Research Center,
Gynecologic Cancer Center of Excellence,
Department of Obstetrics and Gynecology,
Women’s Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Obstetrics and Gynecology

Uniformed Services University and Walter Reed National Military Medical Center

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Christine Rojas

Women’s Health Integrated Research Center,Gynecologic Cancer Center of Excellence,Department of Obstetrics and Gynecology,Women’s Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Obstetrics and Gynecology

Uniformed Services University and Walter Reed National Military Medical Center

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Women’s Health Integrated Research Center,
Gynecologic Cancer Center of Excellence,
Department of Obstetrics and Gynecology,
Women’s Health Integrated Research Center, Gynecologic Cancer Center of Excellence, Department of Obstetrics and Gynecology