Positive controls were observed on all slides indicating successful overall staining using the Ventana machine. However, staining of some individual samples within each slide was unsuccessful. Table 1 in additional file 1 summarises the proportion of successful stains for each biomarker.

Of the 143 samples stained for CK7, 119 (83.2%) were primary and 24 (16.8%) were non-primary. Of the 119 primary tumours, 111 (93.3%) stained positive and 8 (6.7%) stained negative. Of the 24 non-primary tumours, 14 (58.3%) stained negative and 10 (41.7%) stained positive [Table 2 in additional file 1].

Of the 146 samples stained for Napsin-A, 125 (85.6%) were primary and 21 (14.4%) were non-primary. Of the 125 primary tumours, 95 (76.0%) stained positive and 30 (24.0%) stained negative. Of the 21 non-primary tumours, 19 (90.5%) stained negative and 2 (9.5%) stained positive [Table 3 in additional file 1].

Of the 166 samples stained for TTF1, 139 (83.7%) were primary and 27 (16.3%) were non-primary. Of the 139 primary tumours, 113 (81.3%) stained positive and 26 (18.7%) stained negative. Of the 27 non-primary tumours, 25 (92.6%) stained negative and 2 (7.4%) stained positive [Table 4 in additional file 1].

Of the 123 samples stained for CK20, 109 (88.6%) were primary and 14 (11.4%) were non-primary. Of the 109 primary tumours, 105 (96.3%) stained negative and 4 (3.7%) stained positive. Of the 14 non-primary tumours, 8 (57.1%) stained positive and 6 (42.9%) stained negative [Table 5 in additional file 1].

Of the 121 samples stained for CDX2, 104 (86.0%) were primary and 17 (14.0%) were non-primary. Of the 104 primary tumours, 100 (96.2%) stained negative and 4 (3.8%) stained positive. Of the 17 non-primary tumours, 16 (94.1%) stained positive and 1 (5.9%) stained negative [Table 6 in additional file 1].

Of the 119 samples stained for SATB2, 99 (83.2%) were primary and 20 (16.8%) were non-primary. Of the 119 primary tumours, 90 (90.9%) stained negative and 9 (9.1%) stained positive. Of the 20 non-primary tumours, 15 (75.0%) stained positive and 5 (25.0%) stained negative [Table 7 in additional file 1].

Univariate binary logistic regression models showed a significant OR (p < 0.05) of 19.4, 30.1, 54.3, 0.029, 0.003, and 0.033 for CK7, Napsin-A, TTF1, CK20, CDX2, and SATB2 respectively. Table 1 also summarises the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each marker.

Multivariate analysis was performed for each of the 15 2-biomarker combinations. Of the 15, 11 had statistically significant ORs (p < 0.05). ROC curves of the 11 combinations showed all 11 to have statistically significant (p < 0.05) AUC, with the combination of TTF1/CDX2 having the highest (0.983, 0.960–1.000 95% CI) [Table 2]. The sensitivity, specificity, PPV, and NPV of the TTF1/CDX2 panel were 75.7, 100, 100, and 37.5% respectively.

Multivariate analysis was performed for each of the 20 3-biomarker combinations. Of the 20, only 4 had statistically significant ORs (p < 0.05). ROC curves of the 4 combinations showed all 4 to have statistically significant (p < 0.05) AUC, with the combination of CK7/CK20/SATB2 having the highest (0.965, 0.930–1.000 95% CI) [Table 3]. The sensitivity, specificity, PPV, and NPV of the CK7/CK20/SATB2 panel were 85.1, 100, 100, and 41.7% respectively.

Multivariate analysis was performed for each of the 15 4-biomarker combinations, however, none of the combinations had statistically significant ORs (p < 0.05).

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