Proteomic profile of KSR1-regulated signalling in response to genotoxic agents in breast cancer

Abstract

Kinase suppressor of Ras 1 (KSR1) has been implicated in tumorigenesis in multiple cancers, including skin, pancreatic and lung carcinomas. However, our recent study revealed a role of KSR1 as a tumour suppressor in breast cancer, the expression of which is potentially correlated with chemotherapy response. Here, we aimed to further elucidate the KSR1-regulated signalling in response to genotoxic agents in breast cancer. Stable isotope labelling by amino acids in cell culture (SILAC) coupled to high-resolution mass spectrometry (MS) was implemented to globally characterise cellular protein levels induced by KSR1 in the presence of doxorubicin or etoposide. The acquired proteomic signature was compared and GO-STRING analysis was subsequently performed to illustrate the activated functional signalling networks. Furthermore, the clinical associations of KSR1 with identified targets and their relevance in chemotherapy response were examined in breast cancer patients. We reveal a comprehensive repertoire of thousands of proteins identified in each dataset and compare the unique proteomic profiles as well as functional connections modulated by KSR1 after doxorubicin (Doxo-KSR1) or etoposide (Etop-KSR1) stimulus. From the up-regulated top hits, several proteins, including STAT1, ISG15 and TAP1 are also found to be positively associated with KSR1 expression in patient samples. Moreover, high KSR1 expression, as well as high abundance of these proteins, is correlated with better survival in breast cancer patients who underwent chemotherapy. In aggregate, our data exemplify a broad functional network conferred by KSR1 with genotoxic agents and highlight its implication in predicting chemotherapy response in breast cancer.

Fig. 1

Strategy to identify global protein changes induced by KSR1 in response to doxorubicin or etoposide. a Three SILAC labeled cell populations were subjected to DMSO (Control), treatment with KSR1 overexpression in the presence of doxorubicin, and treatment with doxorubicin alone. Subsequently, total protein lysates were prepared, and light, medium, and heavy cell populations were mixed 1:1:1, digested and fractionated to peptides. SILAC labelled peptides were then processed through LC–MS/MS. The peptides were then identified and quantified using quantitation software MaxQuant. b Similarly, cells were treated with DMSO (Control), treatment with KSR1 overexpression in the presence of etoposide, and treatment with etoposide alone. The acquired lysates were subject to same protocol as described above

Fig. 2

Global proteomic alterations affected by KSR1 in the presence of doxorubicin or etoposide. a Venn diagram showing a very high degree of overlap and consistency of the proteome identified in Doxo-KSR1 and Etop-KSR1 datasets. b Venn diagram showing the counts of proteins significantly modulated upon doxorubicin or etoposide stimulus (H/L), and proteins markedly differentiated by KSR1 in the presence of doxorubicin or etoposide (M/L), according to Significant B test (P < 0.05). c Venn diagram showing the numbers of proteins significantly up- or down-regulated in each dataset. d Heatmaps showing the commonly and exclusively regulated proteins upon doxorubicin or etoposide stimulus (upper panel), and proteins significantly affected by KSR1 in the presence of doxorubicin or etoposide (lower panel)

Fig. 3

Distribution of protein ratios from identified proteome in two datasets. Volcano plots showing the Log2 ‘normalized ratios’ (M/L) against Log10 ‘intensity’ (M/L) for each characterised protein in response to doxorubicin or etoposide stimulus (a), and affected by KSR1 in the presence of doxorubicin or etoposide (b). Proteins are displayed based on P values from Significant B test. Blue circles are proteins with a P value of <0.001; yellow are proteins with a P value between 0.001 and 0.01; red represent P values between 0.01 and 0.05; grey are proteins whose fold change is not significant (P > 0.05). KSR1 is highlighted showing a pronounced increase in its protein abundance, supporting a good reproducibility and accuracy of the technique (b)

Fig. 4

Characterization of the functional portrait conferred by KSR1 in the presence of doxorubicin or etoposide. a Functional profiles of top GO biologic processes affected by doxorubicin or etoposide stimulus (H/L), or by KSR1 in the presence of doxorubicin or etoposide (M/L) are presented. x-axis shows the percentage of hits that belong to a GO biologic process term. b The functional protein–protein interaction networks belonging exclusively to Doxo-KSR1 or Etop-KSR1 are shown. Protein nodes with lighter colour are up-regulated, whereas darker colour represents down-regulation

Fig. 5

Clinical significance of SILAC-based proteomics identified targets in breast cancer. a The correlation analysis of KSR1 mRNA with ISG15, STAT1, TAP1, MX1 and HLA-C gene expressions from TCGA dataset. b Kaplan–Meier curves show associations of expression levels of KSR1, STAT1, ISG15, TAP1 and HLA-C with relapse free survival (RFS) in breast cancer patients who underwent systematic chemotherapy