Table 1.
Factors tested in qRT-PCR expression analysis with the validated primer catalog ID from IDT and their molecular function based on STRING database.
Fig 1.
Comparing RNA TK1 levels in metastatic and primary cell lines.
RNA-seq data from Cancer Cell Line Encyclopedia (CCLE) for primary and metastatic cell lines were analyzed for TK1 expression. Data was mined from a genomic RNA-seq database for well characterized cell lines. A permutation-based test was used to evaluate significance. Metastatic cell lines showed a significantly higher level for cytosolic TK1 than primary cell lines (p < 0.0001).
Fig 2.
Comparing TK1 protein levels in metastatic and primary breast cell lines.
I. a) Western blot analysis of cytosolic TK1 levels was performed in various types of breast cancer cell lines. b) Individual monomeric levels of TK1 were assessed in six different breast cancer cell lines. II. Cells were categorized as metastatic or primary based on current literature. A student’s t-test was performed comparing TK1 levels between metastatic and primary cells. Metastatic cell lines contained a higher level of cytosolic TK1 (p < 0.05).
Fig 3.
CRISPR-Cas9 TK1 knockdown confirmation.
I. a) Western Blot detection for TK1 and loading control (GAPDH) in HCC 1806 and L133 cell lysate. Lanes 1–3 contain cell lysate from HCC 1806 cells and lanes 4–6 contain cell lysate from L133 cells. b) Difference in mean relative expression for TK1 in HCC 1806 and L133 cells was evaluated by a student’s t-test in PRISM. L133 cells showed less expression of TK1 when compared to HCC 1806 cells (p < 0.001). II. a) PCR amplification of TK1 (lanes 1–6) from HCC 1806 and L133 cDNA. GAPDH was used as the reference sample (not shown). b) Fold change was calculated from qRT-PCR data for TK1 in HCC 1806 and L133 cells using GAPDH as the reference gene. L133 cells had a lower fold change for TK1 when compared to HCC 1806 cells (p < 0.01). III. A nitrophenyl growth assay was used to determine frequency (# of divisions/day) of L133 and HCC 1806 cells. Individual standard curves for HCC 1806 and L133 cells were used to determine the cell count based on color development readings over a 24-hour period. A student’s t-test was used to compare the difference in means. L133 cells had a lower frequency when compared to HCC 1806 cells (p < 0.05).
Fig 4.
Gene ontology enrichment analysis of gene product attributes from RNA-seq analysis of HCC 1806 and L133 cells.
I. Scatterplot of GO terms and the associated statistics from the GO Enrichment analysis. The legend associated with the scatterplot identifies gene number by circle size and p value by color intensity. Metal ion binding and extracellular region are some of the most prevalent GO terms. II. Bar plot of enriched GO terms shows number of genes associated to a given term and which system classification they belong. The legend above the graph shows the color associated with each system classification.
Fig 5.
Heatmap of differentially expressed genes comparing HCC 1806 and L133 cells.
Samples were tested in biological replicates (n = 3). Higher expressed factors are depicted by increasing red intensity where lower expression is depicted by increasing intensity of blue.
Fig 6.
Heatmap of differentially expressed transcripts comparing HCC 1806 and L133 cells.
Samples were tested in biological replicates (n = 3). Higher expressed factors are depicted by increasing red intensity where lower expression is depicted by increasing intensity of blue.
Fig 7.
The influence of TK1 on cell cycle progression, pathway, and its regulation.
I. HCC 1806 and L133 cell cycle analysis. Cell cycle progression was detected using propidium iodide staining and measured using flow cytometry. Quantification in each phase of the cell cycle was determined using the cell cycle analysis platform in FlowJo. A student’s t-test was used to compare mean differences between HCC 1806 (n = 3) and L133 (n = 3) cells within each cell cycle phase. L133 had significantly more cells in S phase and significantly less cells in G1 when compared to HCC 1806 cells (p < 0.0001). II. Relative transcript levels in HCC 1806 and L133 cells were quantified using qRT-PCR for a subset of factors involved in apoptosis. Samples were tested in biological replicates (n = 3) and transcript levels were normalized to GAPDH. Cells were harvested in exponential growth phase under normal cell-culturing conditions. Data are expressed as the mean fold change ± SEM of L133 cells relative to HCC 1806 cells… Aside fromPPP2R2B (average 2.3-fold change) (p<0.0001), all remaining significant factors showed lower expression. The lowest change was in p21 where the average fold change was 0.02 (p <0.0001). Asterisks in the figure denote the following significance levels: (*) p < 0.05; (**) p < 0.01; (***) p < 0.001; (****) p < 0.0001.
Fig 8.
Investigating the influence of cytosolic TK1 levels in apoptotic response and factors.
I. Apoptosis under serum deprivation and hypoxic conditions for L133 and HCC 1806 cells. Apoptosis was detected by Annexin VFITC and propidium iodide (PI) staining and measured using flow cytometry. a. Comparing apoptosis levels in HCC 1806 and L133 samples that were subjected to serum deprived conditions (2% FBS) (n = 5). L133 samples showed higher levels of early apoptotic signs (Annexin V) in both 12- and 30-hour samples. Later apoptotic stages measured with both Annexin V and PI staining showed that HCC 1806 samples stayed relatively stable while L133 samples experienced higher levels of cell death overtime (p< 0.01). b. Comparing apoptosis levels in HCC 1806 and L133 samples under hypoxic conditions using CoCl2 6H2O [50μm] (n = 5). L133 samples showed higher levels of early apoptotic signs (Annexin V) in both 12- and 30-hour samples. Later apoptotic stages measured with both Annexin V and PI staining showed that HCC 1806 samples stayed relatively stable while L133 samples experienced higher levels of cell death overtime (p< 0.001). II. Relative transcript levels in HCC 1806 and L133 cells were quantified using qRT-PCR for a subset of factors involved in apoptosis. Samples were tested in biological replicates (n = 3) and transcript levels were normalized to GAPDH. Cells were harvested in exponential growth phase under normal cell-culturing conditions. Data are expressed as the mean fold change ± SEM of L133 cells relative to HCC 1806 cells. L133 cells showed lower expression for all factors tested (p <0.0001). Asterisks in the figure denote the following significance levels: (*) p < 0.05; (**) p < 0.01; (***) p < 0.001; (****) p < 0.0001.
Fig 9.
Exploring the relationship of TK1 on cellular invasion.
I. Wound healing assay comparing migration between L133 and HCC 1806 cells. a. The migration ability of HCC 1806 and L133 cells was performed over a 24-hour period in biological replicates (n = 4). Gap area was normalized prior to analysis. HCC 1806 samples showed faster gap closure than L133 samples using a simple linear regression to compare slopes (p<0.01). b. Visual representation of HCC 1806 and L133 cell migration at hour 1 and hour 6. II. Relative transcript levels in HCC 1806 and L133 cells were quantified using qRT-PCR for a subset of factors involved in apoptosis. Samples were tested in biological replicates (n = 3) and transcript levels were normalized to GAPDH.. Cells were harvested in exponential growth phase under normal cell-culturing conditions. Data are expressed as the mean fold change ± SEM of L133 cells relative to HCC 1806 cells.. L133 cells showed lower expression for all factors tested (p <0.0001). Asterisks in the figure denote the following significance levels: (**) p < 0.01 and (****) p < 0.0001.
Fig 10.
A TK1 protein-protein interaction network.
Protein nodes are represented by protein symbol and the interactions between these proteins are shown by lines (edges). The legend in the top right corner shows colors associated with the processes of each protein (e.g. apoptosis, cell cycle, invasion, or a combination).
Table 2.
Factors included in each pathway were gathered through PathCard and GeneCard databases.
Fig 11.
Elucidating TK1 levels in patient samples.
I. Immunohistochemistry analysis of a breast cancer tissue array. Tissue samples from invasive ductal and infiltrating lobular primary carcinoma patients with matching normal and metastatic samples were stained for TK1 using an HRP conjugated antibody. A) Normal human isotype B) GADPH control C) Metastatic ductal D) Metastatic lobular E) Invasive ductal F) Infiltrating lobular. Assessing associations between gene expression of TK1 and tumor presence through TCGA. II. An ANOVA test was computed in PRISM to test differences between means of 3,3′-Diaminobenzidine (DAB) development in tissue samples. Metastatic tissues had a higher presence of TK1 in comparison to normal and primary tumor tissue samples (p value <0.0001).