In recent years, high-throughput technologies have provided unprecedented opportunities for analyzing cancer samples at multiple molecular levels. Each type of multi-omics dataset contributes to the identification of molecular differences associated with cancer, providing insights into the biological pathways that contribute to the disease.
In a recent study, led by Drs. ChenWei Lin and Regine M Schoenherr, staff scientists in Dr. Amanda Paulovich’s lab in the Translational Science and Therapeutics Division at Fred Hutch, the authors generated RNA sequencing and phosphoproteomic datasets to investigate the functional signatures of TP53 and PTEN loss. The authors hope that these datasets “may be used to advance our understanding of the TP53 and PTEN tumor suppressor genes and to provide functional signatures for bioinformatic analyses of proteogenomic datasets.” According to Dr. Paulovich, “Cancer transcriptomics data are commonly analyzed using a ‘gene set enrichment approach,’ which uses sets of related genes (e.g., mutation signatures, functional signatures, curated genes in the same biochemical pathway, co-regulated genes, or genes localized to the same chromosomal band, protein complex, or organelle) to look for differences in expression between two sample types (e.g., mutant vs wild type, treatment-sensitive vs -resistant). This approach is used to deepen our understanding of the mechanisms of cancer and how biological pathways are adversely altered in hopes of improving treatment strategies.” We lack sufficient datasets for applying mutant signatures at the proteomic level to such an approach.
Towards this goal, the authors “developed phosphoprotein and RNA signatures associated with mutations of the tumor suppressor proteins PTEN and TP53.” Specifically, the authors “profiled the RNA and phosphoproteomes of the MCF10A breast epithelial cell line, along with its congenic TP53- or PTEN-knockout derivatives, upon perturbation with the monofunctional DNA alkylating agent methyl methanesulfonate (MMS) vs. mock-treatment.” MMS is a DNA alkylating agent mechanistically similar to several agents commonly used in cancer chemotherapy. Alkylating agents “are known to induce replication stress, potentially mimicking the activation of the DNA damage response network observed in early-stage human breast cancers” Dr. Paulovich stated.
To accomplish this, wild type MCF10A cells, along with knockouts of TP53 or PTEN with or without MMS treatment, were metabolically labeled by stable isotope labeling with amino acids in cell culture (SILAC). The SILAC technique labels cellular proteomes by incorporating non-radioactive, stable isotope-containing amino acids into newly synthesized proteins. Cells are incubated in growth medium where natural (“light”) amino acids containing carbon-12 (12-C) are replaced by “heavy” SILAC amino acids containing carbon-13 (13-C). When light and heavy cell populations are mixed, they remain distinguishable by mass spectrometry (MS), and protein abundances can be determined from relative MS signal intensities. The samples were analyzed either by RNA-seq or by phosphoproteomic analysis. The authors created specific datasets of genes that are differentially expressed in TP53- and PTEN-knockout cells compared with control cells as well as phosphoprotein datasets. “Datasets such as these enable a ‘gene set enrichment approach,’ which has been used for 2 decades to analyze transcriptional data, to be used at the level of the proteome in the setting of functional analyses of PTEN and TP53 alterations,” Dr. Paulovich commented. “The data are also of use to investigators studying the biology of PTEN and TP53 in the presence and absence of DNA damage,” she added.
The authors validated these datasets by examining the expression of known genes and phosphoproteins that are known to be induced during DNA damage, including CDKN1A and nibrin (NBN). The authors found that MMS treatment induced upregulation of CDKN1A as well as phosphorylation of the S343 site of NBN, as expected. The authors conducted Gene Set Variation analysis in order to validate previously identified TP53 gene signatures. The WT TP53 signatures in MCF10A samples were higher than those in MCF10A-TP53-KO samples, indicating the validity of their approach.
“The dataset has been made publicly available to add to our knowledgebase of the biological effects of these mutations, and to provide empirical functional signatures associated with these mutations to aid in the bioinformatic analysis of cancer proteogenomic profiles,” Dr. Paulovich concluded.
Fred Hutch/University of Washington/Seattle Children’s Cancer Consortium member Dr. Amanda Paulovich contributed to this work.
This work was funded by the National Institutes of Health.
Lin C, Schoenherr RM, Voytovich UJ, Ivey RG, Kennedy JJ, Whiteaker JR, Wang P, Paulovich AG. RNA and phosphoprotein profiles of TP53- and PTEN-knockouts in MCF10A at baseline and responding to DNA damage. Sci Data. 2024.