In-depth characterization of the secretome of colorectal cancer metastatic cells identifies key proteins in cell adhesion, migration, and invasion

Abstract

Liver metastasis in colorectal cancer is the major cause of cancer-related deaths. To identify and characterize proteins associated with colon cancer metastasis, we have compared the conditioned serum-free medium of highly metastatic KM12SM colorectal cancer cells with the parental, poorly metastatic KM12C cells using quantitative stable isotope labeling by amino acids in cell culture (SILAC) analyses on a linear ion trap-Orbitrap Velos mass spectrometer. In total, 1337 proteins were simultaneously identified in SILAC forward and reverse experiments. For quantification, 1098 proteins were selected in both experiments, with 155 proteins showing >1.5-fold change. About 52% of these proteins were secreted directly or using alternative secretion pathways. GDF15, S100A8/A9, and SERPINI1 showed capacity to discriminate cancer serum samples from healthy controls using ELISAs. In silico analyses of deregulated proteins in the secretome of metastatic cells showed a major abundance of proteins involved in cell adhesion, migration, and invasion. To characterize the tumorigenic and metastatic properties of some top up- and down-regulated proteins, we used siRNA silencing and antibody blocking. Knockdown expression of NEO1, SERPINI1, and PODXL showed a significant effect on cellular adhesion. Silencing or blocking experiments with SOSTDC1, CTSS, EFNA3, CD137L/TNFSF9, ZG16B, and Midkine caused a significant decrease in migration and invasion of highly metastatic cells. In addition, silencing of SOSTDC1, EFNA3, and CD137L/TNFSF9 reduced liver colonization capacity of KM12SM cells. Finally, the panel of six proteins involved in invasion showed association with poor prognosis and overall survival after dataset analysis of gene alterations. In summary, we have defined a collection of proteins that are relevant for understanding the mechanisms underlying adhesion, migration, invasion, and metastasis in colorectal cancer.

Fig. 1.

Identification, quantification, and data normalization of proteins. A, proteins identified and quantified in both SILAC experiments. About 64% of proteins were coincident in both SILAC analyses, forward and reverse. B, histogram plot of the fold-changes for all of the quantified proteins in log₂-transformed ratios after normalization for both SILAC experiments and the combined data. Data normalization was performed against the 5% trimmed mean to adjust log₂ protein ratio distribution to zero. Curves representing normal distribution and not normalized data curves are represented.

Fig. 2.

Validation of identified and quantified proteins. Conditioned media of KM12C and KM12SM CRC cells were concentrated using Vivaspin 500 centrifugal devices, separated by SDS-PAGE, transferred to nitrocellulose membranes, and probed with the indicated antibodies. Rho GDI was used as a control. Protein abundance was quantified by densitometry, and KM12SM/KM12C ratios were calculated to compare the expression with the SILAC ratios. The MS spectrum for each of the verified proteins is shown, including identified peptide sequence and heavy/light ratios for the corresponding peptides.

Fig. 3.

Analysis of the location and secretion of quantified proteins. A, location analysis of the differentially secreted proteins was based on Gene Ontology. B, secretion analysis of the 154 differentially expressed protein. Nonclassical secretion data were obtained using the SecretomeP and the SignalP software. Those proteins that showed an NN-score of >0.5 and did not contain signal peptide were considered as secreted proteins using nonconventional secretion.

Fig. 4.

Network alterations associated with secreted proteins in colorectal cancer metastasis. Protein networks were identified by IPA using the 154 differentially released proteins identified in the study. A, Cellular Movement, Cancer and Gastrointestinal Disease Network was identified with a score of 51. The network consisted of 24 up-regulated and four down-regulated proteins from a total of 35 interacting proteins, with seven proteins unidentified by SILAC. B, Post-Translational Modification, Cell-To-Cell Signaling and Interaction, Cardiovascular System Development, and Function Network were identified with a score of 46. The network consisted of 17 up-regulated and seven down-regulated proteins from a total of 34 proteins, and 10 proteins of the network remained unidentified. Green, down-regulated proteins in KM12SM cells. Red, up-regulated proteins in KM12SM cells. White, nondetected proteins. Light color, less deregulated. Dark color, more deregulated.

Fig. 5.

Diagnostic value of S100A8/A9, GDF15, and SERPINI1 in serum samples. A, S100A8/A9, GDF15, and SERPINI1 were assayed by ELISA using 60 serum samples (40 from CRC and 20 from healthy individuals) at 1:50, 1:20, and 1:10 dilution, respectively. Data are represented in dot plots depicting the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum). Horizontal bar in the box plot represents the median of the ELISA values data set. B, specificity and sensitivity were calculated using ROC curves for each marker. AUC is indicated. C, ROC curve was calculated for the combinations of the three markers.

Fig. 6.

In vitro functional studies to determine the effect of differentially released protein in CRC metastasis. Adhesion, migration, invasion, and proliferation assays were performed with KM12SM CRC cells to study the effect of siRNAS or blocking antibodies against indicated targets on CRC metastasis. Experiments were performed three times, with consistent results. Error bar, standard deviation. (*, p < 0.05; **, p < 0.01; ***, p < 0.001.) A, adhesion assays were performed after 48 h of transfection of KM12SM cells with siRNAs directed against the indicated targets and, alternatively, with blocking antibodies using parental KM12SM cells. B–D, migration, invasion, and proliferation assays, respectively, were performed 24 h after transfection of KM12SM cells with siRNAs directed against the indicated targets and, alternatively, with blocking antibodies using parental KM12SM cells.

Fig. 7.

SOSTDC1, CD137L, or EFNA3 silencing suppresses liver metastasis in KM12SM cells. Nude mice were inoculated intrasplenically with KM12SM cells transfected with the indicated siRNAs and were sacrificed 24 h after injection. RNA was isolated from the liver and subjected to RT-PCR to amplify human GAPDH. A representative experiment out of three is shown. Murine β-actin was amplified as loading control.

Fig. 8.

Prognostic role of CD137L, CTSS, SOSTDC1, ZG16B, EFNA3, and MDK at mRNA level in colorectal cancer and other tumors. A, using cBioCancer Genomics Portal database, Kaplan-Meier estimates of survival showed that patients with alterations in the six-gene invasion panel had worse overall survival than those without alterations (log-rank test p: 0.03). B–D, no significant association with overall survival of the six protein invasion panel was obtained for breast cancer, glioblastoma, and lung cancer, respectively.

Fig. 9.

Common regulatory pathways associated with the proteins identified in this study. A, proteins involved in the different processes. In black, proteins that promote these processes are shown, and in red proteins that inhibit them are shown. B, pathways affected by the proteins regulating cell adhesion, migration, invasion, or proliferation (from left to right and top to bottom). EFNA3 binds and activates EphA receptors (75); these receptors trigger activation of PI3K and Src (72) and inhibit MAPK (73). CTSS increases expression of MET, EGFR, ITGA2, and MMP3 (54). In turn, MET activates PI3K (76); ITGA2 activates MAPK (77), and both molecules are also activated by EGFR (78). SERPINI1 is an inhibitor of tissue plasminogen activator (tPA) (57), which inhibits ITGB1 (79). TNFSF9 triggers activation of PI3K and Src (61). PODXL promotes ITGB1-mediated cell adhesion (48). NEO1 is a receptor of Netrin, which also binds ITGB1 (80), inducing a collaborative signaling that enhances cell adhesion (51). NEO1 also inhibits focal adhesion kinase (FAK) activation, which is an activator of Ras (81). SOSTDC1, also known as USAG1, is an inhibitor of several BMPs (82). BMP4 inhibits activation of MMP9 (83), whose expression is inhibited by BMP2 (84), which also reduces PTEN expression (85). Midkine binds to ITGB1 (60), inducing ITGB1/TSPAN1 interaction that activates STAT1, which in turn promotes expression of MMP2 and MMP26 (86). ZG16B increases CXCR4 expression (66), which can stimulate PI3K (65).