The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

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Abstract

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

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Comprehensive Integration of Single-Cell Data

Tim Stuart, Andrew Butler, Paul Hoffman … (2019)

Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

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clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Tianzhi Wu, Erqiang Hu, Shuangbin Xu … (2021)

Summary Functional enrichment analysis is pivotal for interpreting high-throughput omics data in life science. It is crucial for this type of tool to use the latest annotation databases for as many organisms as possible. To meet these requirements, we present here an updated version of our popular Bioconductor package, clusterProfiler 4.0. This package has been enhanced considerably compared with its original version published 9 years ago. The new version provides a universal interface for functional enrichment analysis in thousands of organisms based on internally supported ontologies and pathways as well as annotation data provided by users or derived from online databases. It also extends the dplyr and ggplot2 packages to offer tidy interfaces for data operation and visualization. Other new features include gene set enrichment analysis and comparison of enrichment results from multiple gene lists. We anticipate that clusterProfiler 4.0 will be applied to a wide range of scenarios across diverse organisms.

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Cancer statistics, 2023

Rebecca L Siegel, Kimberly D Miller, Nikita Sandeep Wagle … (2023)

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes using incidence data collected by central cancer registries and mortality data collected by the National Center for Health Statistics. In 2023, 1,958,310 new cancer cases and 609,820 cancer deaths are projected to occur in the United States. Cancer incidence increased for prostate cancer by 3% annually from 2014 through 2019 after two decades of decline, translating to an additional 99,000 new cases; otherwise, however, incidence trends were more favorable in men compared to women. For example, lung cancer in women decreased at one half the pace of men (1.1% vs. 2.6% annually) from 2015 through 2019, and breast and uterine corpus cancers continued to increase, as did liver cancer and melanoma, both of which stabilized in men aged 50 years and older and declined in younger men. However, a 65% drop in cervical cancer incidence during 2012 through 2019 among women in their early 20s, the first cohort to receive the human papillomavirus vaccine, foreshadows steep reductions in the burden of human papillomavirus-associated cancers, the majority of which occur in women. Despite the pandemic, and in contrast with other leading causes of death, the cancer death rate continued to decline from 2019 to 2020 (by 1.5%), contributing to a 33% overall reduction since 1991 and an estimated 3.8 million deaths averted. This progress increasingly reflects advances in treatment, which are particularly evident in the rapid declines in mortality (approximately 2% annually during 2016 through 2020) for leukemia, melanoma, and kidney cancer, despite stable/increasing incidence, and accelerated declines for lung cancer. In summary, although cancer mortality rates continue to decline, future progress may be attenuated by rising incidence for breast, prostate, and uterine corpus cancers, which also happen to have the largest racial disparities in mortality.

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Author and article information

Contributors

De-Chao Feng:

ORCID: http://orcid.org/0000-0002-8267-9920

fdcfenix@stu.scu.edu.cn , dechao.feng@ucl.ac.uk

Qiang Wei: weiqiang@scu.edu.cn

Lu Yang: wycleflue@scu.edu.cn

Journal

Journal ID (nlm-ta): Mil Med Res

Journal ID (iso-abbrev): Mil Med Res

Title: Military Medical Research

Publisher: BioMed Central (London )

ISSN (Print): 2095-7467

ISSN (Electronic): 2054-9369

Publication date (Electronic): 11 April 2024

Publication date PMC-release: 11 April 2024

Publication date Collection: 2024

Volume: 11

Electronic Location Identifier: 21

Affiliations

[1 ]GRID grid.412901.f, ISNI 0000 0004 1770 1022, Department of Urology, Institute of Urology, , West China Hospital, Sichuan University, ; Chengdu, 610041 China

[2 ]Division of Surgery & Interventional Science, University College London, ( https://ror.org/02jx3x895) London, WC1E 6BT UK

Author information

De-Chao Feng http://orcid.org/0000-0002-8267-9920

Article

Publisher ID: 526

DOI: 10.1186/s40779-024-00526-7

PMC ID: 11007901

PubMed ID: 38605399

SO-VID: e62a39a1-aea5-425a-bccd-95618be5b302

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 18 May 2022

Date accepted : 25 March 2024

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100014718, Innovative Research Group Project of the National Natural Science Foundation of China;

Award ID: 81974099, 82170785, 81974098, 82170784

Award Recipient : Lu Yang

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Keywords: prostate cancer,single-cell rna sequencing (scrna-seq),tumor microenvironment,tumor heterogeneity,treatment resistance,precision medicine

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Keywords: prostate cancer, single-cell rna sequencing (scrna-seq), tumor microenvironment, tumor heterogeneity, treatment resistance, precision medicine

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

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Most cited references 162

Comprehensive Integration of Single-Cell Data

clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Cancer statistics, 2023

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