A biomarker based detection and characterization of carcinomas exploiting two fundamental biophysical mechanisms in mammalian cells

Abstract

Background: Biomarkers allowing the characterization of malignancy and therapy response of oral squamous cell carcinomas (OSCC) or other types of carcinomas are still outstanding. The biochemical suicide molecule endonuclease DNaseX (DNaseI-like 1) has been used to identify the Apo10 protein epitope that marks tumor cells with abnormal apoptosis and proliferation. The transketolase-like protein 1 (TKTL1) represents the enzymatic basis for an anaerobic glucose metabolism even in the presence of oxygen (aerobic glycolysis/Warburg effect), which is concomitant with a more malignant phenotype due to invasive growth/metastasis and resistance to radical and apoptosis inducing therapies.

Methods: Expression of Apo10 and TKTL1 was analysed retrospectively in OSCC specimen (n = 161) by immunohistochemistry. Both markers represent independent markers for poor survival. Furthermore Apo10 and TKTL1 have been used prospectively for epitope detection in monocytes (EDIM)-blood test in patients with OSCC (n = 50), breast cancer (n = 48), prostate cancer (n = 115), and blood donors/controls (n = 74).

Results: Positive Apo10 and TKTL1 expression were associated with recurrence of the tumor. Multivariate analysis demonstrated Apo10 and TKTL1 expression as an independent prognostic factor for reduced tumor-specific survival. Apo10+/TKTL1+ subgroup showed the worst disease-free survival rate in OSCC.EDIM-Apo10 and EDIM-TKTL1 blood tests allowed a sensitive and specific detection of patients with OSCC, breast cancer and prostate cancer before surgery and in after care. A combined score of Apo10+/TKTL1+ led to a sensitivity of 95.8% and a specificity of 97.3% for the detection of carcinomas independent of the tumor entity.

Conclusions: The combined detection of two independent fundamental biophysical processes by the two biomarkers Apo10 and TKTL1 allows a sensitive and specific detection of neoplasia in a noninvasive and cost-effective way. Further prospective trials are warranted to validate this new concept for the diagnosis of neoplasia and tumor recurrence.

Figure 1

Immunohistochemical single staining of Apo10, TKTL1 and survival curves of OSCC patients measured by Apo10 and TKTL1 expression. Brown chromogen color (3,3′-Diaminobenzidine, DAB) indicates positive Apo10 staining (a, nuclear staining pattern) and positive TKTL1 expression (b, cytoplasmic staining pattern), the blue color shows the nuclear counterstaining by hematoxylin. Pseudo-colored images (c, d) show the staining components of computer-assisted quantitative analysis in Apo10+ and TKTL1+ tumor cells. Computer-assisted light brown label (c) indicates positive Apo10 staining and the computer-assisted light blue label marks the nuclei counterstained with hematoxylin. Computer-assisted red label (d) indicates strong or complete TKTL1 staining, the green label (d) indicates weak or incomplete staining. Apo10 staining is abolished after incubation with immunogenic peptide (e). Representative image of IgG control (f) shows no staining. Original magnification: ×200-fold. Kaplan-Meier (g, h, left panel) and Cox-regression (i, j, right panel) survival curves for disease-free survival (DFS) stratified by positive Apo10 and TKTL1 expression (Apo10+, TKTL1+, dashed lines) and negative Apo10, TKTL1 expression (Apo10-, TKTL1-, solid lines). In univariate Kaplan-Meier analysis positive Apo10 (g) and TKTL1 (h) expression is significantly associated with poorer survival. The times of the censored data are indicated by short vertical lines. Multivariate Cox-regression analysis shows positive Apo10 (i) and TKTL1 (j) expression as significant independent adverse prognostic factors.

Figure 2

EDIM-dotplots of Apo10 and TKTL1 staining. Dotplots show isotype controls (background staining, a, Apo10; b, TKTL1), healthy control (blood donor, c, Apo10; d, TKTL1), a patient with OSCC (e, Apo10; f, TKTL1). Score values indicate the relative amount of positive macrophages. FITC-A (Fluoresceinisothiocyanate area) and PE-A (Phycoerythrin area), red population; APC-A (Allophycocyanin area) blue population.

Figure 3

Receiver Operating Characteristics (ROC) analysis of EDIM-Apo10 and EDIM-TKTL1 score in OSCC (n = 50) compared with healthy individuals (n = 74), and interactive dot diagrams. The true positive rates (sensitivity) are plotted in function of the false positive rate (100-specificity) for measurement of the cut-off point: ROC analysis for the diagnosis of primary or recurrent OSCC shows calculated cut-off value with highest diagnostic accuracy (arrows) of EDIM-Apo10 (a) and EDIM-TKTL1 (b) score (a, EDIM-Apo10 score >109: sensitivity 90.0%, 95% CI 78.2–96.7%, specificity 94.6%, 95% CI 86.7–98.5%; b, EDIM-TKTL1 score >117: sensitivity 92.0%, 95% CI 80.8–97.8%, specificity 95.9%, 95% CI 88.6–99.2%). Dotted lines show 95% CI. OSCC, oral squamous cell carcinoma. In the interactive dot diagrams (part of ROC curve analysis, c, d) the data of healthy controls and OSCC group are displayed as dots on two vertical axes. The horizontal line indicates the cut-off points with the best separation/highest accuracy (minimal false negative and false positive results) between healthy controls and OSCC group. The corresponding test characteristics sensitivity and specificity are shown above.