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Published on: March 3, 2023
GSVD- and tensor GSVD-uncovered patterns of DNA copy-number alterations predict adenocarcinomas survival in general
Matthew W Bradley, Katherine A Aiello, Sri Priya Ponnapalli1
1Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112, USA.
Abstract:
More than a quarter of lung, uterine, and ovarian adenocarcinoma (LUAD, USEC, and OV) tumors are resistant to platinum drugs. Only recently and only in OV, patterns of copy-number alterations that predict survival in response to platinum were discovered, and only by using the tensor GSVD to compare Agilent microarray platform-matched profiles of patient-matched normal and primary tumor DNA. Here, we use the GSVD to compare whole-genome sequencing (WGS) and Affymetrix microarray profiles of patient-matched normal and primary LUAD, USEC, and OV tumor DNA. First, the GSVD uncovers patterns similar to one Agilent OV pattern, where a loss of most of the chromosome arm 6p combined with a gain of 12p encode for transformation. Like the Agilent OV pattern, the WGS LUAD and Affymetrix LUAD, USEC, and OV patterns are correlated with shorter survival, in general and in response to platinum. Like the tensor GSVD, the GSVD separates these tumor-exclusive genotypes from experimental inconsistencies. Second, by identifying the shorter survival phenotypes among the WGS- and Affymetrix-profiled tumors, the Agilent pattern proves to be a technology-independent predictor of survival, independent also of the best other indicator at diagnosis, i.e., stage. Third, like no other indicator, the pattern predicts the overall survival of OV patients experiencing progression-free survival, in general and in response to platinum. We conclude that comparative spectral decompositions, such as the GSVD and tensor GSVD, underlie a mathematically universal description of the relationships between a primary tumor's genotype and a patient's overall survival phenotype, which other methods miss.
Insights
Platinum drug resistance in lung, uterine, and ovarian adenocarcinomas is common. A specific copy-number alteration pattern predicts shorter survival, independent of technology or stage, and aids in personalized treatment strategies.
Area of Science:
- Genomics
- Cancer Research
- Bioinformatics
Background:
- Platinum-based chemotherapy is a cornerstone treatment for lung, uterine, and ovarian adenocarcinomas (LUAD, USEC, OV).
- A significant proportion of these tumors (over 25%) exhibit resistance to platinum drugs, necessitating improved predictive biomarkers.
- Previous studies identified copy-number alteration (CNA) patterns predicting survival in ovarian cancer (OV) using tensor generalized singular value decomposition (GSVD) on microarray data.
Purpose of the Study:
- To investigate the utility of GSVD for analyzing whole-genome sequencing (WGS) and Affymetrix microarray data in LUAD, USEC, and OV.
- To identify CNA patterns associated with patient survival and platinum drug response across these cancer types.
- To determine if identified CNA patterns are technology-independent and superior to existing prognostic indicators like tumor stage.
Main Methods:
- Applied GSVD to compare patient-matched normal and tumor DNA profiles from LUAD, USEC, and OV using WGS and Affymetrix microarray data.
- Identified CNA patterns, specifically a loss of 6p and gain of 12p, correlating with transformation and shorter survival.
- Validated the identified pattern as a technology-independent predictor of survival, outperforming tumor stage.
Main Results:
- GSVD uncovered CNA patterns similar to previously identified OV patterns, linking a specific chromosomal alteration (loss of 6p, gain of 12p) to shorter survival.
- These patterns were observed across WGS and Affymetrix data for LUAD, USEC, and OV, indicating technology independence.
- The identified CNA pattern proved to be a superior predictor of overall survival compared to tumor stage, particularly in OV patients, and predicted response to platinum therapy.
Conclusions:
- Comparative spectral decompositions like GSVD provide a universal mathematical framework for linking tumor genotype to patient survival phenotype.
- The identified CNA pattern is a robust, technology-independent biomarker for predicting survival and platinum response in LUAD, USEC, and OV.
- This finding has significant implications for personalized medicine, enabling more accurate prognostication and tailored treatment strategies.
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