Supplemental material for M. W. Bradley, K. A. Aiello, S. P. Ponnapalli,* H. A. Hanson* and O. Alter, "GSVD- and Tensor GSVD-Uncovered Patterns of DNA Copy-Number Alterations Predict Adenocarcinomas Survival in General and in Response to Platinum," Applied Physics Letters (APL) Bioengineering 3 (3), article 036104 (August 2019); doi: 10.1063/1.5099268.
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 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 relations between a primary tumor's genotype and a patient's overall survival phenotype, which other methods miss.
- The corresponding Mathematica 10.4.1 code file is:
- The corresponding WGS LUAD tumor and normal profiles are:
- The corresponding Affymetrix LUAD tumor and normal profiles are:
- The corresponding Affymetrix USEC tumor and normal profiles are:
- The corresponding Affymetrix OV tumor and normal profiles are:
- Segments previously identified by the circular binary segmentation (CBS) in the Agilent OV pattern, reproduced from Sankaranarayanan,* Schomay* et al.