Virtual Library

Start Your Search

Robert J. Cardnell

Author of

  • +

    OA03 - Systemic Therapies for SCLC: Novel Targets and Patients' Selection (ID 121)

    • Event: WCLC 2019
    • Type: Oral Session
    • Track: Small Cell Lung Cancer/NET
    • Presentations: 1
    • Now Available
    • +

      OA03.06 - ASCL1, NEUROD1, and POU2F3 Drive Distinct Subtypes of Small Cell Lung Cancer with Unique Therapeutic Vulnerabilities (Now Available) (ID 1433)

      13:30 - 15:00  |  Author(s): Robert J. Cardnell

      • Abstract
      • Presentation
      • Slides


      Background: Accounting for 15% of all lung cancer diagnoses, small cell lung cancer (SCLC) is an aggressive malignancy with dismal clinical outcomes, due in part to failure to define clinical biomarkers predictive of unique, targetable vulnerabilities. Recent data has begun to delineate molecular subsets of SCLC by uncovering inter-tumoral heterogeneity in features such as DNA damage response, EMT, and neuroendocrine (NE) status. However, it remains unclear whether the subsets defined by these features are predictive of response to cancer therapies and could be employed as patient selection criteria.


      Methods: Using RNAseq data from 81 resected SCLC tumor samples and 62 SCLC cell lines, we applied non-negative matrix factorization (NMF) to optimize delineation of transcriptionally defined clusters. Reverse phase protein array (RPPA) and drug response data for cell lines were analyzed post-clustering to compare features between clusters. Clustering analyses were validated in vivo using CTC-derived patient xenograft (CDX) models, while single-cell RNAseq (scRNAseq) from these same models was used to assess intratumoral heterogeneity among clusters.


      Results: NMF identifies four biologically distinct clusters among SCLC tumor samples and cell lines, each defined almost solely by differential expression of the transcription factors ASCL1 (SCLC-A, 36%), NEUROD1 (SCLC-N, 31%), and POU2F3 (SCLC-P, 16%), including a cluster defined by the absence of all three (SCLC-Inflamed/Mesenchymal, or SCLC-IM, 17%). SCLC-A are neuroendocrine, epithelial tumors with susceptibility to drug classes including BCL-2 inhibitors. SCLC-N are neuroendocrine, cMYC-high tumors with susceptibilities including Aurora kinase inhibitors that are neither epithelial nor mesenchymal. SCLC-P are non-neuroendocrine, epithelial tumors vulnerable to PARP inhibitors and nucleoside analogs. Lastly, SCLC-IM consists of mesenchymal, non-neuroendocrine tumors with high-expression of immune checkpoints, STING-related genes, and inflammatory markers that may represent those SCLC which are sensitive to immune checkpoint blockade. scRNAseq reveals intratumoral heterogeneity among cluster assignment within tumors that fluctuates coincident with the onset of therapeutic resistance.


      Conclusions: SCLC tumors can be assigned to one of four molecular subtypes on the basis of differential expression of three transcription factors. These subtype assignments reflect profound distinctions in underlying biology and susceptibility to a range of candidate drug classes. While subtype assignment on a single-cell basis within a tumor is largely homogeneous, rare cells from distinct subtypes (or representing multiple subtypes), as well as shifting assignments following treatment indicate the possibility of subtype-switching, or subtype-selection, as mechanisms of therapeutic resistance.

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.