Background: SCLC (15% of lung cancers) exhibits: 1) rapid growth and early fatal metastasis; 2) neuroendocrine features; 3) high initial responsiveness to chemotherapy and radiation; 4) aggressive recurrence with 5% 5-year patient survival. Gene expression and mutation profiling efforts to identify oncogenic mutations, gene amplifications or signatures with clinical utility in SCLC have thus far been unfruitful. In addition, prognostic or diagnostic markers for SCLC are scarce. Hence, there is a dire need for investigating molecular subtypes and oncogenic drivers in SCLC. We hypothesize that deregulated networks, rather than single genes, drive SCLC phenotype.

Results: We previously identified a SCLC-specific gene co-expression network (Blue module, by Weighted Gene Co-expression Network Analysis - WGCNA) from a lung cancer patient dataset, and derived a SCLC-specific hub network (SSHN) signature that: 1) separated SCLC from other lung cancer types and normal lung in both genomic and proteomic independent datasets; 2) identified 2 SCLC subtypes with high and low SSHN expression in both patient specimens and cultured cell lines. Spleen tyrosine kinase (SYK) was validated as a candidate oncogenic driver of one subtype, as SYK targeted small-interfering RNA significantly decreased viability via increased death in high SYK-expressing SCLC cell lines.

Due to the lack of larger SCLC patient datasets, we have now applied the SSHN classifier to the 53 SCLC cell lines from the Cancer Cell Line Encyclopedia (CCLE) and validated the SSHN-high and low subtypes. From this larger dataset, it is evident that the SSHN-defined subtypes are not totally separate. Rather, they are connected by gradual intermediate shades. This gradation became clearer by applying WGCNA to SCLC cell lines from CCLE, which identified 2 gene co-expression modules – Blue and Turquoise, that overlap with modules from patient datasets described above. The Blue module is enriched in neuroendocrine signaling, the Turquoise in mesenchymal adhesion-related pathways. Eigengene expression of the 2 modules (MEblue, MEturquoise) is anti-correlated, and all 53 SCLC cell lines are distributed along this anti-correlation diagonal. Expression of the neuroendocrine marker CD56 is highest in cells at one end of this diagonal (MEblue-high cell lines), and decreases towards the other end (MEturquoise-high cell lines), whereas the mesenchymal marker CD44 has an opposite trend. Multi-dimensional flow cytometry data, visualized with viSNE, indicated that SCLC cell lines are heterogeneous with respect to several additional cell surface and cytoplasmic markers and that, in general, there is a gradient of expression of these markers that tends to correlate with the neuroendocrine (e.g., SYK) to mesenchymal (e.g., TGFbeta receptor II) phenotype gradient. Finally, at the neuroendocrine end of the phenotypic spectrum (MEblue-high) cells grow in suspension, whereas they become increasingly adherent towards the mesenchymal end (MEturquoise-high).

Conclusion: Our data provide strong evidence for a heterogeneous phenotypic space in SCLC that may define distinct subtypes. This heterogeneity was previously unsuspected in human SCLC, although evidence for it was reported in genetic mouse models of SCLC {Calbo J, et.al, Cancer Cell, 2011}. Classification of human SCLC cell lines along a neuroendocrine to mesenchymal differentiation gradient should apply to human tumors as well, since the WGCNA network classifiers overlap. However, further studies in patients are warranted to prove the existence of distinct SCLC subtypes, as well as to probe their translational value for biomarkers and targeted treatment.

Citation Format: Akshata Ramrao Udyavar, Megan Hoeksema, Kirsten Diggins, Jonathan Irish, Pierre P. Massion, Vito Quaranta. Phenotypic plasticity and heterogeneity in small cell lung cancer (SCLC): Novel molecular subtypes and potential for targeted therapy. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr B27.