Validation of SSHN as a robust classifier for SCLC in two independent datasets from (A) high-throughput gene expression and (B) shotgun proteomic analysis. (A) Unsupervised clustering heatmap based on 287 SSHN genes (rows) of lung cancer patients (columns) in GSE6044 dataset . Red and green indicate high and low expression, respectively. The majority of SCLCs cluster by themselves on the far left of the dendrogram. Two SCLC specimens are excluded from this cluster, a trend to be investigated in more depth if confirmed in larger datasets (see Discussion). (B) SSHN-based unsupervised clustering heatmap of an in-house generated shotgun proteomic dataset comprised of control alveolar and bronchial epithelium, ADC, SCC and SCLC tissue specimens (for each tissue type, specimens from multiple patients, five in this case, were pooled as it is customary for shotgun proteomic analysis). Red and green as denoted in (A). Analysis is limited to 141 out of 287 SSHN proteins (rows), since the remainder proteins were not detect by shotgun proteomics. The 3 tumor specimens segregate together from normal tissue. Within the 3 tumor specimens, ADC and SCC are more similar to each other than to SCLC.