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Page 286 Cancer Drug Resist 2018;1:266-302 I http://dx.doi.org/10.20517/cdr.2018.18

for which we postulate a mechanism for conferring treatment resistance in GBM, the testing of which is
the focus of our ongoing work.

37. Single-cell analysis of cancer-associated fibroblast heterogeneity in non-small cell lung
cancer: mapping molecular phenotypes in tumours

#
Sara Waise, Rachel Parker, Matthew Rose-Zerilli, Christian Ottemsmeier, Christopher Hanley ,
Gareth Thomas #

Cancer Sciences Unit, Somers Building, University of Southampton, Tremona Road, Southampton SO16 6YD, UK
# The two authors contributed equally to this Abstract

Aim: To characterise the heterogeneity and spatial relationships of the cancer-associated fibroblast (CAF)
population in non-small cell lung cancer.

Methods: Fresh primary lung tissue was dissociated to extract the maximum possible proportion of CAF
(using collagenase P for sixty minutes). Single-cell RNA sequencing was performed using a droplet-barcod-
ed sequencing platform. Bioinformatic analysis was carried out in R, with cell type identification and gene
set enrichment using the ToppFun tool and GSEA program. Spatial relationships between cell types were
characterised using a multi-immunohistochemical staining protocol.

Results: Analysis of 12 non-small cell lung cancer (NSCLC) tumours and 6 matched non-involved lung
samples revealed the presence of 5 CAF subtypes. Three subgroups showed transcriptomic overlap with
normal fibroblasts. Of the distinct CAF populations, one showed enrichment and expression of genes as-
sociated with the ‘myofibroblastic’ CAF phenotype. The second CAF cluster showed higher expression of
growth factors and immune cell exclusion on histology. Multiplexed IHC using identified cluster markers
demonstrated that these subtypes have different spatial distribution and relationships to other cell types.
Of the remaining three subtypes, one showed gene expression and enrichment consistent with the previ-
ously-described ‘inflammatory’ fibroblast subtype. The remaining two clusters show significant prognostic
impact, but their functions have yet to be elucidated.

Conclusion: Despite their abundance in most solid cancers, CAF remain a poorly-characterised population.
No single marker reliably identifies all CAF and is not yet clear whether distinct CAF phenotypes exist or
whether such subgroups have different functions. We have identified six stromal populations in NSCLC.
The fibroblast subtypes show differential gene set enrichment, spatial distribution and prognostic impact,
suggestive of functional differences. Clinical trials of stromal targeting agents have so far shown disap-
pointing results: identification of pro-malignant CAF subgroups may facilitate the development of more
specific strategies.

38. The unfolded protein response in prostate cancer: developing novel strategies for

therapeutic intervention

Ana Maria Isac, Filippo Prischi, Philip Reeves, Greg Brooke

School of Biological Sciences, University of Essex, Colchester, UK

Prostate cancer (PCa) cells grow in an environment which is known to cause endoplasmic reticulum (ER)
stress. This leads to the activation of a process called the unfolded protein response (UPR) which tumour