Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse

AbstractProstate cancer is heterogeneous and patients would benefit from methods that stratify those who are likely to respond to systemic therapy. Here, we employ single-cell assays for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identify pre-existing and treatment-persistent cell subpopulations that possess regenerative potential when subjected to treatment. We find distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent cells are able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal as yet unrecognized molecular predictors of treatment response. This suggests that the application of single-cell methods with high analytical resolution in pre-clinical models may powerfully inform clinical decision-making.

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Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

10.21203/rs.3.rs-384422/v1 ◽

2021 ◽

Author(s):

Sinja Taavitsainen ◽

Nikolai Engedal ◽

Shaolong Cao ◽

Florian Handle ◽

Andrew Erickson ◽

...

Keyword(s):

Prostate Cancer ◽

Single Cell ◽

Treatment Response ◽

Rna Sequencing ◽

Clinical Decision Making ◽

Clinical Decision ◽

Early Treatment Response ◽

Cell Assays ◽

Clinical Models ◽

Cell Subpopulations

Abstract Prostate cancer is heterogeneous and patients would benefit from methods that stratify those who are likely to respond to systemic therapy. We employed single-cell assays for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that were linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that the high analytical resolution of pre-clinical models enabled by single-cell methods may powerfully inform clinical decision-making.

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Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

10.1101/2021.02.09.430114 ◽

2021 ◽

Author(s):

S Taavitsainen ◽

N Engedal ◽

S Cao ◽

F Handle ◽

S Prekovic ◽

...

Keyword(s):

Prostate Cancer ◽

Single Cell ◽

Treatment Response ◽

Rna Sequencing ◽

Clinical Decision Making ◽

Clinical Decision ◽

Early Treatment Response ◽

Clinical Models ◽

Cell Subpopulations ◽

Accessible Chromatin

AbstractProstate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

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Quantitative and Qualitative Analysis of Blood-based Liquid Biopsies to Inform Clinical Decision-making in Prostate Cancer

European Urology ◽

10.1016/j.eururo.2020.12.037 ◽

2021 ◽

Author(s):

Irene Casanova-Salas ◽

Alejandro Athie ◽

Paul C. Boutros ◽

Marzia Del Re ◽

David T. Miyamoto ◽

...

Keyword(s):

Prostate Cancer ◽

Decision Making ◽

Qualitative Analysis ◽

Clinical Decision Making ◽

Clinical Decision ◽

Liquid Biopsies

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Beyond the Development of Health-Related Quality-of-Life (HRQOL) Measures: A Checklist for Evaluating HRQOL Outcomes in Cancer Clinical Trials—Does HRQOL Evaluation in Prostate Cancer Research Inform Clinical Decision Making?

Journal of Clinical Oncology ◽

10.1200/jco.2003.12.121 ◽

2003 ◽

Vol 21 (18) ◽

pp. 3502-3511 ◽

Cited By ~ 182

Author(s):

Fabio Efficace ◽

Andrew Bottomley ◽

David Osoba ◽

Carolyn Gotay ◽

Henning Flechtner ◽

...

Keyword(s):

Prostate Cancer ◽

Decision Making ◽

Clinical Trials ◽

Clinical Decision Making ◽

Clinical Decision ◽

Cancer Clinical Trials ◽

Health Related Quality ◽

Related Quality ◽

Health Related

Purpose: The aim of this study was to evaluate whether the inclusion of health-related quality of life (HRQOL), as a part of the trial design in a randomized controlled trial (RCT) setting, has supported clinical decision making for the planning of future medical treatments in prostate cancer. Materials and Methods: A minimum standard checklist for evaluating HRQOL outcomes in cancer clinical trials was devised to assess the quality of the HRQOL reporting and to classify the studies on the grounds of their robustness. It comprises 11 key HRQOL issues grouped into four broader sections: conceptual, measurement, methodology, and interpretation. Relevant studies were identified in a number of databases, including MEDLINE and the Cochrane Controlled Trials Register. Both their HRQOL and traditional clinical reported outcomes were systematically analyzed to evaluate their consistency and their relevance for supporting clinical decision making. Results: Although 54% of the identified studies did not show any differences in traditional clinical end points between treatment arms and 17% showed a difference in overall survival, 74% of the studies showed some difference in terms of HRQOL outcomes. One third of the RCTs provided a comprehensive picture of the whole treatment including HRQOL outcomes to support their conclusions. Conclusion: A minimum set of criteria for assessing the reported outcomes in cancer clinical trials is necessary to make informed decisions in clinical practice. Using a checklist developed for this study, it was found that HRQOL is a valuable source of information in RCTs of treatment in metastatic prostate cancer.

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Harnessing the patient voice in prostate cancer research: Systematic review on the use of patient‐reported outcomes in randomized controlled trials to support clinical decision‐making

Cancer Medicine ◽

10.1002/cam4.3018 ◽

2020 ◽

Vol 9 (12) ◽

pp. 4039-4058 ◽

Cited By ~ 1

Author(s):

Mieke Van Hemelrijck ◽

Francesco Sparano ◽

Lisa Moris ◽

Katharina Beyer ◽

Francesco Cottone ◽

...

Keyword(s):

Prostate Cancer ◽

Systematic Review ◽

Patient Reported Outcomes ◽

Clinical Decision Making ◽

Clinical Decision ◽

Controlled Trials ◽

Randomized Controlled ◽

Patient Voice ◽

Patient Reported ◽

Prostate Cancer Research

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Early prostate cancer: clinical decision-making

The Lancet ◽

10.1016/s0140-6736(03)12833-4 ◽

2003 ◽

Vol 361 (9362) ◽

pp. 1045-1053 ◽

Cited By ~ 158

Author(s):

Ashesh B Jani ◽

Samuel Hellman

Keyword(s):

Prostate Cancer ◽

Decision Making ◽

Clinical Decision Making ◽

Clinical Decision ◽

Early Prostate Cancer

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Single-Cell RNA Sequencing of Childhood Ependymoma Reveals Neoplastic Cell Subpopulations That Impact Molecular Classification and Etiology

Cell Reports ◽

10.1016/j.celrep.2020.108023 ◽

2020 ◽

Vol 32 (6) ◽

pp. 108023 ◽

Cited By ~ 1

Author(s):

Austin E. Gillen ◽

Kent A. Riemondy ◽

Vladimir Amani ◽

Andrea M. Griesinger ◽

Ahmed Gilani ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Molecular Classification ◽

Neoplastic Cell ◽

Single Cell Rna Sequencing ◽

Cell Subpopulations

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State-of-the-Art Management for the Patient with Castration-Resistant Prostate Cancer in 2012

American Society of Clinical Oncology Educational Book ◽

10.14694/edbook_am.2012.32.174 ◽

2012 ◽

pp. 289-291 ◽

Cited By ~ 2

Author(s):

Oliver Sartor

Keyword(s):

Prostate Cancer ◽

Clinical Decision Making ◽

Clinical Decision ◽

Phase Iii ◽

Castration Resistant Prostate Cancer ◽

Optimal Sequence ◽

Molecular Stratification ◽

Castration Resistant ◽

Radium 223 ◽

Phase Iii Trials

Overview: Much progress has been made in metastatic castration-resistant prostate cancer (CRPC), and multiple new U.S. Food and Drug Administration (FDA)-approved survival-prolonging drugs are now available. In 2004, docetaxel/prednisone was the first therapy shown to prolong survival. In 2010 and 2011, sipuleucel-T, cabazitaxel/prednisone, and abiraterone/prednisone were FDA approved. Two new agents, radium-223 and MDV-3100, have recently reported large phase III trials prolonging overall survival and will be submitted for regulatory approval in 2012. One can now begin to ask, is there an optimal sequence for therapies in metastatic CRPC? Despite the recent progress, there is much we do not know and virtually no information on this important question. We know that abiraterone/prednisone and cabazitaxel/prednisone are appropriate choices for a patient after receiving docetaxel, but we do not know what, if anything, represents the optimal sequence for abiraterone and cabazitaxel. In fact we do not understand how one therapy may affect the response to a subsequent therapy. We are also aware that the pre- and postdocetaxel spaces represent regulatory rather than biologic divisions. In addition, despite the proven role of docetaxel/prednisone, many patients with CRPC are not considered to be suitable for chemotherapy, and worldwide many never receive any form of chemotherapy. What is the optimal management for these patients? Taken together it is reasonable to assess patient preferences, prior therapies and response/tolerance to prior therapies, burden of disease, comorbidities, current symptoms, drug toxicities, out-of-pocket costs, etc., in clinical decision making. Given the many factors we do not know, it is hard to be dogmatic in approaching the therapeutic options for the patient with CRPC. We will likely soon move beyond the current sequencing paradigm and begin to assess new combinations in a systematic and rational fashion. Perhaps one day, in the not too distant future, we will develop molecular “stratification systems” to better guide therapeutic choices in CRPC.

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