Tumor copy number alteration burden is a pan-cancer prognostic factor associated with recurrence and death
- Memorial Sloan Kettering Cancer Center, United States
- Memorial Sloan-Kettering Cancer Center, United States
- Icahn School of Medicine at Mount Sinai, United States
- Kings College London, United Kingdom
- Queen Mary University of London, United Kingdom
Abstract
The level of copy number alteration (CNA), termed CNA burden, in the tumor genome is associated with recurrence of primary prostate cancer. Whether CNA burden is associated with prostate cancer survival or outcomes in other cancers is unknown. We analyzed the CNA landscape of conservatively treated prostate cancer in a biopsy and transurethral resection cohort, reflecting an increasingly common treatment approach. We find that CNA burden is prognostic for cancer-specific death, independent of standard clinical prognostic factors. More broadly, we find CNA burden is significantly associated with disease-free and overall survival in primary breast, endometrial, renal clear cell, thyroid, and colorectal cancer in TCGA cohorts. To assess clinical applicability, we validated these findings in an independent pan-cancer cohort of patients whose tumors were sequenced using a clinically-certified next generation sequencing assay (MSK-IMPACT), where prognostic value varied based on cancer type. This prognostic association was affected by incorporating tumor purity in some cohorts. Overall, CNA burden of primary and metastatic tumors is a prognostic factor, potentially modulated by sample purity and measurable by current clinical sequencing.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files and reference materials. The conservative treatment TAPG copy number cohort array data was deposited in NCBI GEO under accession number GSE103665 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE103665, reviewer access token czwruyesnzqbbyn).
-
Copy number alteration burden is a pan-cancer prognostic factor associated with metastasis and death in conservatively treated prostate cancer: TAPG1 CNA cohort aCGH dataPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE103665).
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- Charles L Sawyers
National Institutes of Health (CA193837)
- Charles L Sawyers
Prostate Cancer Foundation
- Kamlesh Yadav
National Institutes of Health (CA092629)
- Charles L Sawyers
National Institutes of Health (CA155169)
- Charles L Sawyers
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Hieronymus et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 8,945
- views
-
- 1,081
- downloads
-
- 215
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Tumor copy number alteration burden is a pan-cancer prognostic factor associated with recurrence and death
eLife 7:e37294.
https://doi.org/10.7554/eLife.37294
Further reading
-
- Cancer Biology
- Evolutionary Biology
In asexual populations that don’t undergo recombination, such as cancer, deleterious mutations are expected to accrue readily due to genome-wide linkage between mutations. Despite this mutational load of often thousands of deleterious mutations, many tumors thrive. How tumors survive the damaging consequences of this mutational load is not well understood. Here, we investigate the functional consequences of mutational load in 10,295 human tumors by quantifying their phenotypic response through changes in gene expression. Using a generalized linear mixed model (GLMM), we find that high mutational load tumors up-regulate proteostasis machinery related to the mitigation and prevention of protein misfolding. We replicate these expression responses in cancer cell lines and show that the viability in high mutational load cancer cells is strongly dependent on complexes that degrade and refold proteins. This indicates that the upregulation of proteostasis machinery is causally important for high mutational burden tumors and uncovers new therapeutic vulnerabilities.
-
- Cancer Biology
- Cell Biology
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study, we addressed this gap by combining a specialized surface to enhance cell attachment, the FUCCI(CA)2 sensor, an automated image analysis pipeline, and a custom machine learning algorithm. This approach enabled precise measurement of cell cycle phase durations in non-adherent cells. This method was validated in acute myeloid leukemia cell lines NB4 and Kasumi-1, which have unique cell cycle characteristics, and we tested the impact of cell cycle-modulating drugs on NB4 cells. Our cell cycle analysis system, which is also compatible with adherent cells, is fully automated and freely available, providing detailed insights from hundreds of cells under various conditions. This report presents a valuable tool for advancing cancer research and drug development by enabling comprehensive, automated cell cycle analysis in both adherent and non-adherent cells.
