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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.

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.

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.

SUMMARYA challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels to propagate cells. Which nutrients are available can influence how cancer cells use metabolism to proliferate and impact sensitivity to some drugs, but a general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To enable screening of compounds to determine how the nutrient environment impacts drug efficacy, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We used this system to screen several small molecule libraries and found that compounds targeting metabolic enzymes were enriched as having differential efficacy in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.

High-throughput phenotypic screens leveraging biochemical perturbations, high-content readouts, and complex multicellular models could advance therapeutic discovery yet remain constrained by limitations of scale. To address this, we establish a method for compressing screens by pooling perturbations followed by computational deconvolution. Conducting controlled benchmarks with a highly bioactive small molecule library and a high-content imaging readout, we demonstrate increased efficiency for compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening to examine transcriptional responses of patient-derived pancreatic cancer organoids to a library of tumor-microenvironment (TME)-nominated recombinant protein ligands. Using single-cell RNA-seq as a readout, we uncover reproducible phenotypic shifts induced by ligands that correlate with clinical features in larger datasets and are distinct from reference signatures available in public databases. In sum, our approach enables phenotypic screens that interrogate complex multicellular models with rich phenotypic readouts to advance translatable drug discovery as well as basic biology.

Tablets and capsules are a cornerstone of medicine, but these solid dosage forms can be challenging to swallow for geriatric and pediatric patients. While liquid formulations are easier to ingest, these formulations lack the capacity to localize therapeutics and excipients nor act as controlled release devices. To bridge the advantages of solid and liquid dosage forms, here we describe drug formulations based on liquidin situ-forming and tough (LIFT) hydrogels. Drug-loaded LIFT hydrogels are formed directly in the stomach through the sequential ingestion of a crosslinker solution of calcium and dithiol crosslinkers, followed by the ingestion of a drug-containing polymer solution of alginate and 4-arm poly(ethylene glycol)-maleimide. We show that LIFT hydrogels are mechanically tough and able to robustly form in the presence of complex gastric fluid andin vivoin rat and porcine stomachs. LIFT hydrogels are retained within the porcine stomach for up to 24 h, biocompatible, and safely cleared. These hydrogels deliver a total dose comparable to unencapsulated drug but with delayed and lower maximum drug plasma concentrations, providing a method for controlled release that may mitigate drug toxicity. Co-encapsulation of lactase as a model biologic drug and calcium carbonate mitigated gastric-mediated deactivation of encapsulated enzyme in rat and porcine models. We also demonstrate the potential of these hydrogels to encapsulate and protect a model therapeutic bacterium,E. coliNissle 1917, against acid. LIFT hydrogels present a biocompatible means of tough, double-network hydrogel formationin situin the gastric cavity, and may expand medication access for patients with difficulty swallowing.

Immune checkpoint blockade (ICB) therapy has improved long-term survival for patients with advanced melanoma. However, there is critical need to identify potential biomarkers of response and actionable strategies to improve response rates. Through generation and analysis of 148 chromatin modification maps for 36 melanoma samples from patients treated with anti-PD- 1, we identified significant enrichment of active enhancer states in non-responders at baseline. Analysis of an independent cohort of 20 samples identified a set of 437 enhancers that predicted response to anti-PD-1 therapy (Area Under the Curve of 0.8417). The activated non-responder enhancers marked a group of key regulators of several pathways in melanoma cells (including c- MET, TGFβ, EMT and AKT) that are known to mediate resistance to ICB therapy and several checkpoint receptors in T cells. Epigenetic editing experiments implicated involvement of c-MET enhancers in the modulation of immune response. Finally, inhibition of enhancers and repression of these pathways using bromodomain inhibitors along with anti-PD-1 therapy significantly decreased melanoma tumor burden and increased T-cell infiltration. Together, these findings identify a potential enhancer-based biomarker of resistance to anti-PD-1 and suggest enhancer blockade in combination with ICB as a potential strategy to improve responses.

Immune checkpoint blockade (ICB) therapy has improved long-term survival for patients with advanced melanoma. However, there is critical need to identify potential biomarkers of response and actionable strategies to improve response rates. Through generation and analysis of over 200 chromatin modification maps for ICB-treated melanoma patient samples, melanoma cells and T cells, we identified significant enrichment of active enhancer states in non-responders at baseline. Enhancer mapping by bulk ChIP-Seq or single cell ATAC-Seq methods in two independent cohorts of ICB-treated melanoma samples identified an enhancer signature that predicted response to anti-PD-1 therapy. The activated non-responder enhancers marked a group of key regulators of several pathways in melanoma cells (including c-MET, TGFβ, EMT and AKT) that are known to mediate resistance to ICB therapy. In addition, several checkpoint receptors were alternatively activated by aberrant enhancers in T cells. Unbiased CRISPRi screening in melanoma cells and T cells identified novel functional enhancers, such as one upstream of c-MET, that mediate ICB response or T cell mediated killing. Finally, inhibition of enhancers and repression of these pathways using bromodomain inhibitors along with anti-PD-1 therapy significantly decreased melanoma tumor burden and increased T-cell infiltration. Epigenomic experiments identified a signature of 107 genes that could be used as pharmacodynamic marker for BET inhibitor response. Together, these findings identify enhancer upregulation as a key mechanism of adaptive resistance to ICB response, a potential enhancer-based biomarker of resistance to anti-PD-1 and enhancer blockade in combination with ICB as a potential strategy to improve responses. Citation Format: Kunal Rai, Mayinuer Maitituoheti, Alvin Shi, Ming Tang, Li-Lun Ho, Firas Youssef Kreidieh, Christopher Terranova, Kyriakitsa Galani, Emily Z. Keung, Caitlin A. Creasy, Manrong Wu, Jiajia Chen, Nana Chen, Anand K. Singh, Apoorvi Chaudhri, Nazanin E. Anvar, Giuseppe Tarrantino, Jiekun Yang, Sharmistha Sarkar, Shan Jiang, Jared Malke, Lauren Haydu, Elizabeth Burton, Michael A. Davies, Jeffrey E. Gershenwald, Patrick Hwu, Alexander Lazar, Jaime H. Cheah, Christian K. Soule, Stuart S. Levine, Chantale Bernatchez, Srinivas V. Saladi, David Liu, Hussein Tawbi, Jennifer Wargo, Genevieve M. Boland, Manolis Kellis. Functional roles of enhancers in immune microenvironment & immunotherapy response. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6425.

Kidney stones and ureteral stents can cause ureteral colic and pain. By decreasing contractions in the ureter, clinically prescribed oral vasodilators may improve spontaneous stone passage rates and reduce the pain caused by ureteral stenting. We hypothesized that ureteral relaxation can be improved via the local administration of vasodilators and other smooth muscle relaxants. Here, by examining 18 candidate small molecules in an automated screening assay to determine the extent of ureteral relaxation, we show that the calcium channel blocker nifedipine and the Rho-kinase inhibitor ROCKi significantly relax human ureteral smooth muscle cells. We also show, by using ex vivo porcine ureter segments and sedated pigs that, with respect to the administration of a placebo, the local delivery of a clinically deployable formulation of the two drugs reduced ureteral contraction amplitude and frequency by 90% and 50%, respectively. Finally, we show that standard oral vasodilator therapy reduced contraction amplitude by only 50% and had a minimal effect on contraction frequency. Locally delivered ureteral relaxants therefore may improve ureter-related conditions.

Nanoformulations are transforming our capacity to effectively deliver and treat a myriad of conditions. However, many nanoformulation approaches still suffer from high production complexity and low drug loading. One potential solution relies on harnessing co-assembly of drugs and small molecular excipients to facilitate nanoparticle formation through solvent exchange without the need for chemical synthesis, generating nanoparticles with up to 95% drug loading. However, there is currently no understanding which of the millions of possible combinations of small molecules can result in the formation of these nanoparticles. Here we report the development of a high-throughput screening platform coupled to machine learning to enable the rapid evaluation of such nanoformulations. Our platform identified 101 novel self-assembling drug nanoparticles from 2.1 million pairings derived from 788 candidate drugs with one of 2686 excipients, spanning treatments for multiple diseases and often harnessing well-known food additives, vitamins, or approved drugs as carrier materials – with potential for accelerated approval and translation. Given their long-term stability and potential for clinical impact, we further characterize novel sorafenib-glycyrrhizin and terbinafine-taurocholic acid nanoparticles ex vivo and in vivo. We anticipate that this platform could accelerate the development of safer and more efficacious nanoformulations with high drug loadings for a wide range of therapeutics.

Collagen overproduction is a feature of fibrosis and cancer, while insufficient deposition of functional collagen molecules and/or the secretion of malformed collagen is common in genetic disorders like osteogenesis imperfecta. Collagen secretion is an appealing therapeutic target in these and other diseases, as secretion directly connects intracellular biosynthesis to collagen deposition and biological function in the extracellular matrix. However, small molecule and biological methods to tune collagen secretion are severely lacking. Their discovery could prove useful not only in the treatment of disease, but also in providing tools for better elucidating mechanisms of collagen biosynthesis. We developed a cell-based, high-throughput luminescent assay of collagen type I secretion and used it to screen for small molecules that selectively enhance or inhibit that process. Among several validated hits, the Hsp90 inhibitor 17-allylaminogeldanamycin (17-AAG) robustly decreases the secretion of collagen-I by our model cell line and by human primary cells. In these systems, 17-AAG and other pan-isoform Hsp90 inhibitors reduce collagen-I secretion post-translationally and are not global inhibitors of protein secretion. Surprisingly, the consequences of Hsp90 inhibitors cannot be attributed to inhibition of the endoplasmic reticulum's Hsp90 isoform, Grp94. Instead, collagen-I secretion likely depends on the activity of cytosolic Hsp90 chaperones, even though such chaperones cannot directly engage nascent collagen molecules. Our results highlight the value of a cell-based high-throughput screen for selective modulators of collagen secretion and suggest an unanticipated role for cytosolic Hsp90 in collagen secretion.

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). Significance: We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses. Cancer Discov; 5(11); 1210–23. ©2015 AACR. See related commentary by Gray and Mills, p. 1130. This article is highlighted in the In This Issue feature, p. 1111