Recovering Tumor Subtypes and Aneuploidy Patterns in Prostate Cancer Using Spatial Transcriptomics Restricted; Files Only

Abstract

Background: Prostate cancer (PC) exhibits extensive heterogeneity, particularly between adenocarcinoma (ADPC) and neuroendocrine prostate cancer (NEPC), which differ markedly in clinical behavior and molecular features. Understanding the spatial and molecular organization of these subtypes is crucial for elucidating tumor progression and therapeutic resistance.

Methods: We applied VisiumHD spatial transcriptomic technique to a prostate tumor sample predominantly composed of NEPC. To characterize tumor heterogeneity, we first used unsupervised clustering to separate tumor and non-tumor regions. Next, within tumor regions, we identified tumor subtypes by scoring marker gene sets associated with five prostate cancer subtypes. Then, we identified their tumor clones based on copy number variation (CNV) inferred from spatial transcriptomics data. Finally, we performed spatial analyses to investigate the distribution and evolutionary relationships among subclones.

Results: We found that tumor subtypes displayed distinct spatial arrangements. The subclone analysis revealed widespread aneuploidy concentrated in NEPC and regions co-expressing NEPC features and other subtypes. Three CNV-defined subclones were identified, exhibiting a vertical spatial gradient consistent with progressive genomic instability. Notably, subpopulation3, with the least CNV burden, localized to the bottom of the gradient, suggesting a potential evolutionary origin.

Conclusion: By leveraging VisiumHD spatial transcriptomics, we systematically mapped the molecular subtypes and subclone architecture of a heterogeneous prostate tumor, revealing spatially distinct subtypes and evolutionary relationships. These findings may help improve our understanding of treatment resistance and guide the development of more tailored therapeutic strategies in prostate cancer.

Table of Contents

Chapter 1. Introduction 1

Chapter 2. Method 2

2.1 Data Preparation and Preprocessing 2

2.2 Tumor and Non-Tumor Separation 3

2.3 Tumor Subtype Classification 3

2.4 Identification of Aneuploid Cells and Subclone Populations 5

Chapter 3. Result 5

3.1 Spatial Classification of Tumor Regions and Subtypes in Prostate Cancer Tissue 5

3.2 Identification of Aneuploid Tumor Cells and Their Spatial Subclone Architecture 9

Chapter 4.Discussion 12

Reference 13

About this Master's Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.S.P.H.
Submission	Master's Thesis
Language	English
Research Field	Biology, Molecular Biology, Bioinformatics Biology, Biostatistics
Stichwort	Spatial transcriptomics Prostate cancer Tumor heterogeneity
Committee Chair / Thesis Advisor	Jian Hu, Emory University
Committee Members	Jingjing Yang, Emory University

Zuletzt geändert

Primary PDF

Thumbnail	Title	Date Uploaded	Actions
	File download under embargo until 15 May 2027	2025-04-17 12:44:10 -0400	File download under embargo until 15 May 2027

Supplemental Files

Thumbnail	Title	Date Uploaded	Actions