Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ~19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters, and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2).

Hydroides elegans is an indirectly developing polychaete with equal spiral cleavage, gastrulation by invagination, and a feeding trochophore. Expression of several transcription factors and differentiation genes has been characterized. Comparative analysis reveals evolutionarily conserved roles. For example, the synexpression of transcription factors FoxA and Brachyury suggests homology of primary and secondary gut openings in protostomes and deuterostomes, and the expression of Sall suggests similar regulatory controls in the posterior growth zone of bilaterians. Differences in gene expression suggest regulatory differences control gastrulation by invagination in polychaetes with a feeding trochophore and gastrulation by epiboly in polychaetes without a feeding trochophore. Association of histone variant H2A.Z with transcriptional potency and its expression suggest a developmental role during both embryogenesis and the larva-to-adult transformation. Methods are being developed for experimental exploration of the gene regulatory networks involved in trochophore development in Hydroides. It is unknown if polychaete feeding trochophores evolved from a larval stage already present in the life cycle of the last common ancestor of protostomes and deuterostomes. Previous evolutionary scenarios about larval origins overemphasize the discontinuity between larval and adult development and require the early evolution of undifferentiated and transcriptionally potent "set aside" cells. Indirect development may proceed by developmental remodeling of differentiated cells and could have evolved after gradual transformation of juveniles into larvae; undifferentiated and transcriptionally potent cells would have evolved secondarily. Comprehensive characterization of gene regulatory networks for feeding trochophore development may help resolve these major evolutionary questions. KEY WORDS: bilaterian, posterior growth, serpulid, annelidHydroides elegans, a polychaete with a feeding trochophore Characterization of polychaetes with a feeding trochophore, such as Hydroides elegans ( Fig. 1 and Table 1), is relevant to understand the developmental evolution of complex life cycles in spiralians. Embryonic development in polychaetes conforms to the presence or absence of a feeding trochophore (Fig. 2). In the genus Hydroides (Eupomatus), embryogenesis ends in a feeding trochophore endowed with an equatorial ciliary band, a protonephridium, various sensory organs, and a functional gut formed after gastrulation by invagination (Hatschek, 1885;Shearer, 1911). Blastomeres 4d and 2d22 are inconspicuous and fated to contribute to the mesodermal and ectodermal portions of the segmented body that will have primarily a reproductive role; the Int. J. Dev. Biol. 58: 575-583 (2014) growth and proliferation of 4d and 2d22 are feeding-dependent. In contrast, during embryogenesis in polychaetes without feeding larvae, blastomeres 4d and 2d are relatively large and immediately engage in the formation of segments (Fig. 2). In addition to la...

<p>Supplemental Table S1. Small-molecule Informer Set Description of the small-molecule informer set used in the sensitivity profiling experiment, including protein target or activity. Supplemental Table S2.Cancer cell-line panel Description of the cancer cell lines profiled in this experiment; for a clarification of growth media compositions, see Supplemental Table S10. Supplemental Table S3. Area-under-sensitivity-curve values Area-under-sensitivity-curve (AUC) values for each compound-cell line pair using the indices provided in Supplemental Table S1 and Supplemental Table S2. Supplemental Table S4. Compound target annotations. Compound target annotations used for ACME analysis of the compound dendrogram. Supplemental Table S5. Cellular feature annotations Cellular feature annotations used for ACME analysis of the cell-line dendrogram. Supplemental Table S6. Cell-line mutation annotations Mutation annotations of the cancer cell lines used in ACME analysis of the cell-line dendrogram. Supplemental Table S7. ACME results table Results of ACME analysis of sensitivity profiling data.</p>

<p>Supplemental Figure S1. Further characterization of the small-molecule Informer Set and comparisons between CTRP v1 and v2. Supplemental Figure S2. Cellular features of the CCL panel. Supplemental Figure S3. Details on ACME analysis described in this paper. Supplemental Figure S4. ACME identifies clinically relevant associations between small-molecule sensitivity and cancer cell features. Supplemental Figure S5. Using ACME to investigate small-molecule mechanism of action. Supplemental Figure S6. Microtubule regrowth assay in NCIH661 cells. Supplemental Figure S7. Combined IGF1R and ALK inhibition in ALK overexpressed neuroblastoma. Supplemental Figure S8. Using ACME to inform combination screening.</p>

<p>Supplementary figure legends. Supplementary methods, including additional filtering and heuristics for sensitivity data processing and ACME analysis and additional methods for western blotting and immunostaining. Supplementary Table S8. Small molecules used in validation studies. Supplementary Table S9. CCLs used in the validation studies. Supplementary Table S10. Clarification of growth media. Supplementary Table S11. Significant synergistic and antagonistic combinations in LS513 cells.</p>

<p>Supplemental Figure S1. Further characterization of the small-molecule Informer Set and comparisons between CTRP v1 and v2. Supplemental Figure S2. Cellular features of the CCL panel. Supplemental Figure S3. Details on ACME analysis described in this paper. Supplemental Figure S4. ACME identifies clinically relevant associations between small-molecule sensitivity and cancer cell features. Supplemental Figure S5. Using ACME to investigate small-molecule mechanism of action. Supplemental Figure S6. Microtubule regrowth assay in NCIH661 cells. Supplemental Figure S7. Combined IGF1R and ALK inhibition in ALK overexpressed neuroblastoma. Supplemental Figure S8. Using ACME to inform combination screening.</p>

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