Small molecule drugs, or low molecular weight compounds, are used as therapeutics to modulate physiological processes to treat or prevent diseases. The discovery of novel small molecule drugs is one of the major research efforts in the pharmaceutical industry and follows an elaborate process as outlined in previous blogs. Small molecule drugs have unique advantages: most are able to permeate membranes to enter intracellular target molecules and can be administered orally.
Another path focuses on oligonucleotide or RNA-based therapeutics that have shown great potential to treat various infectious and hereditary diseases. RNA-based therapeutics also provide a means to target “undruggable” proteins, e.g., by affecting their synthesis (Zhu et al., 2022). For a more comprehensive introduction into RNA therapeutics and their potential visit our recent blogs on this topic.
RNA sequencing (RNA-Seq) has become an integral part of discovery workflows for all classes of molecules due to the vast information provided by the transcriptomic read-out.
Case Studies for RNA-Seq Applications in Drug Discovery
In the following blog, we will provide a few examples for applications of RNA-Seq in various stages of the drug discovery process, the type of information that could be gained and its impact on the studies. We will cover how RNA-Seq can help elucidate molecular modes of action, identify treatment heterogenicity in single organoid models, validate activity of anti-cancer siRNAs on a transcriptome-wide scale, and deliver fundamental insights for combinational therapies and drug repurposing.
Drugging the “undruggable” - the potential of molecular glue degraders
Conventional concepts in the design of these drugs focus on compounds that bind with high affinity to their target proteins and inhibit their activity. While this approach works well for proteins with enzymatic function or signaling receptors, ~80 % of the proteome cannot be targeted with such molecules. These targets are commonly referred to as the “undruggable”.
The group of Georg Winter at CeMM, the Research Center for Molecular Medicine of the Austrian Academy of Sciences, has developed novel strategies towards blocking these otherwise “undruggable” proteins. This promising new approach uses targeted protein degradation, which is based on small molecules, termed “degraders”. One group of these degraders are “molecular glues” that destabilize proteins by inducing proximity to E3 ubiquitin ligases. The discovery of molecular glues has previously been driven by serendipity impeding translational efforts. In the study by Mayor-Ruiz et al., the group describes a scalable strategy for the discovery of molecular glues based on chemical screening and multi-omics analysis.
Abstract
Targeted protein degradation is a new therapeutic modality based on drugs that destabilize proteins by inducing their proximity to E3 ubiquitin ligases. Of particular interest are molecular glues that can degrade otherwise unligandable proteins by orchestrating direct interactions between target and ligase. However, their discovery has so far been serendipitous, thus hampering broad translational efforts. Here, we describe a scalable strategy toward glue degrader discovery that is based on chemical screening in hyponeddylated cells coupled to a multi-omics target deconvolution campaign. This approach led us to identify compounds that induce ubiquitination and degradation of cyclin K by prompting an interaction of CDK12–cyclin K with a CRL4B ligase complex. Notably, this interaction is independent of a dedicated substrate receptor, thus functionally segregating this mechanism from all described degraders. Collectively, our data outline a versatile and broadly applicable strategy to identify degraders with nonobvious mechanisms and thus empower future drug discovery efforts.
The potential of this concept prompted the founding of Proxygen, a Biotech company dedicated to identification of molecular glue degraders. Georg Winter, Chief Scientific Advisor of Proxygen summarizes the findings and their implications in a webinar “Probing and Disrupting Oncogenic Gene Control via Targeted Protein Degradation”.
Whole transcriptome RNA-Seq was used throughout the study to validate the destabilization of cyclin K – a critical player for cancer cell growth and therapeutic resistance. In conjunction with proteomics, drug-affinity chromatography and biochemical reconstitution experiments, the mode of action leading to ubiquitination and proteasomal degradation of cyclin K could be elucidated. Other examples of how RNA-Seq, in this case 3′ expression profiling, can aid the understanding of a compounds mode of action are outlined in the following sections.
Pathway-level information aids identification of the mode of action of small molecule compounds
A recent study by Jover et al. 2024 investigated compounds that can mediate read-through of premature termination codons – a frequent mutation in Recessive dystrophic epidermolysis bullosa (RDEB) patients. RDEB is a rare genetic disease caused by loss of function mutations in the gene coding for collagen VII often causing patients to have an extremely poor quality of life and short life expectancy. The team utilized high-throughput compound screening followed by immunoassays and HTPathwaySeq based on the Lexogen’s QuantSeq 3’-end RNA-Seq workfow. They could identify three new chemical series showing potential for the systemic treatment of RDEB following further investigation and optimization.
High-throughput pathway analysis using RNA-Seq enables researchers to identify the mode of action of active compounds at a low read depth. Furthermore, high-throughput pathway analyses enables researchers to gather information about the potential toxicity of compounds early on as it can reveal activation or (de)activation of toxicity pathways in a dose-dependent manner. RNA-Seq for pathway analysis is often applied as a cost-effective assay during early drug discovery workflows and is ideal to outsource to trusted sequencing services suppliers as it provides a general, hypothesis-free read-out. The study showcased below for example used HTPathwaySeq established at CellCarta, a global Contract Research Organization Laboratory (CRO) whose mission is to propel precision medicine forward to improve health for all.
Abstract
Recessive dystrophic epidermolysis bullosa (RDEB) is a rare genetic disease caused by loss of function mutations in the gene coding for collagen VII (C7) due to deficient or absent C7 expression. This disrupts structural and functional skin architecture, leading to blistering, chronic wounds, inflammation, important systemic symptoms affecting the mouth, gastrointestinal tract, cornea, and kidney function, and an increased skin cancer risk. RDEB patients have an extremely poor quality of life and often die at an early age. A frequent class of mutations in RDEB is premature termination codons (PTC), which appear in homozygosity or compound heterozygosity with other mutations. RDEB has no cure and current therapies are mostly palliative. Using patient-derived keratinocytes and a library of 8273 small molecules and 20,160 microbial extracts evaluated in a phenotypic screening interrogating C7 levels, we identified three active chemical series. Two of these series had PTC readthrough activity, and one upregulated C7 mRNA, showing synergistic activity when combined with the reference readthrough molecule gentamicin. These compounds represent novel potential small molecule-based systemic strategies that could complement topical-based treatments for RDEB.
Dose-dependent RNA-Seq to unravel molecular mechanisms underlying drug induced protein changes
Proteomics, the large-scale study of protein abundance, is a fundamental technology used during drug discovery processes. Proteins are the final functional output of any gene expression changes and therefore, monitoring protein levels is used to assess target deconvolution, investigate the mechanism of action of active compounds and candidates, and to identify biomarkers of drug response. Quantitative mass spectrometry is a general, hypothesis-free assay and the most comprehensive approach for the proteome-wide characterization of drugs. Following identification of drug-induced protein expression changes, RNA-Seq is often supplemented to elucidate the underlying molecular mechanisms and mode of action of the compound of interest or drug candidate. RNA-Seq can provide information whether a drug acts on the transcriptional level, e.g., by affecting transcriptional regulators, or pre-, co- and post-translational, e.g., by affecting translation efficiency, RNA stability, or the protein itself.
Dose-dependent RNA-Seq allows researchers to investigate drug effects in a dose-dependent manner directly on affected pathways. In addition to the information which dose is sufficient for a desired effect on the target (the lower the concentration of compound or drug needed, the more efficient), this type of analysis gives insights to other activated pathways. For example, pathways connected with cellular toxicity may be activated when a certain threshold concentration of the compound is reached allowing researchers to select the best candidates to progress into the next phase.
The following study by Eckert et al., provides an example how 3′ mRNA-Seq, in this case QuantSeq, was used for dose-dependent RNA-Seq to decipher the mechanism of action for selected compounds previously identified by proteomics. The sequencing experiments were conducted at Lexogen NGS Services and data analysis used the provided Lexogen pipelines.
Abstract
Proteomics is making important contributions to drug discovery, from target deconvolution to mechanism of action (MoA) elucidation and the identification of biomarkers of drug response. Here we introduce decryptE, a proteome-wide approach that measures the full dose–response characteristics of drug-induced protein expression changes that informs cellular drug MoA. Assaying 144 clinical drugs and research compounds against 8,000 proteins resulted in more than 1 million dose–response curves that can be interactively explored online in ProteomicsDB and a custom-built Shiny App. Analysis of the collective data provided molecular explanations for known phenotypic drug effects and uncovered new aspects of the MoA of human medicines. We found that histone deacetylase inhibitors potently and strongly down-regulated the T cell receptor complex resulting in impaired human T cell activation in vitro and ex vivo. This offers a rational explanation for the efficacy of histone deacetylase inhibitors in certain lymphomas and autoimmune diseases and explains their poor performance in treating solid tumors.
Single-organoid analysis to identify treatment-resistant, invasive subclones in pancreatic cancer
The following example, based on a study from Le Compte et al., from 2023 illustrates how RNA-Seq can help pave the way toward precision oncology and personalized medicine. The article focuses on the use of organoids as models for cancer treatment and describes the intra-patient response heterogeneity and intrinsic aggressive nature of pancreatic ductal adenocarcinoma – one of the most lethal cancers globally.
Despite the widespread use of tumor organoids in drug discovery and personalized medicine, the assessment of organoid response to treatments is still mostly based on viability and relies on traditional methods used in 2D cell cultures. RNA-Seq therefore provides a powerful tool that can be used to study gene expression in organoids, and allows identification of genes that are associated with cancer progression and drug resistance to develop new therapies for pancreatic cancer in the future.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases, characterized by a treatment-resistant and invasive nature. In line with these inherent aggressive characteristics, only a subset of patients shows a clinical response to the standard of care therapies, thereby highlighting the need for a more personalized treatment approach. In this study, we comprehensively unraveled the intra-patient response heterogeneity and intrinsic aggressive nature of PDAC on bulk and single-organoid resolution. We leveraged a fully characterized PDAC organoid panel (N = 8) and matched our artificial intelligence-driven, live-cell organoid image analysis with retrospective clinical patient response. In line with the clinical outcomes, we identified patient-specific sensitivities to the standard of care therapies (gemcitabine-paclitaxel and FOLFIRINOX) using a growth rate-based and normalized drug response metric. Moreover, the single-organoid analysis was able to detect resistant as well as invasive PDAC organoid clones, which was orchestrates on a patient, therapy, drug, concentration and time-specific level. Furthermore, our in vitro organoid analysis indicated a correlation with the matched patient progression-free survival (PFS) compared to the current, conventional drug response readouts. This work not only provides valuable insights on the response complexity in PDAC, but it also highlights the potential applications (extendable to other tumor types) and clinical translatability of our approach in drug discovery and the emerging era of personalized medicine.
Expression profiling RNA-Seq validates anti-miR activity of selected hit compounds
MicroRNAs (miRNAs) are key regulators of gene expression of diverse biological processes in eukaryotic organisms. They act by silencing their specific mRNA targets through RISC-assisted base-pairing either leading to translational repression or degradation of the target transcript. In cancer, miRNAs can act as tumor suppressors or oncogenes and dysregulation of miRNA expression is considered one of the hallmarks of cancer. MicroRNAs have therefore been recognized as key drivers in various cancer types and promising target for developing anti-cancer therapeutics. Several different strategies are explored by researchers to target cancer-associated miRNAs for more specific therapies with improved efficacy and reduced side effects:
- miRNA sponges: These molecules exhibit binding sites that are complementary to the miRNA target of interest. By exhibiting multiple binding sites, sponges can capture and titrate the target miRNA away from its endogenous target transcript – stabilizing the respective mRNA.
- miRNA mimics: Mimics are synthetic miRNAs that exhibit similarities to their natural counterparts. Mimics are used to compensate for the loss of the endogenous sRNA with its anti-cancer activity.
- miRNA inhibitors: Inhibitors are frequently small molecules targeting oncogenic miRNAs and reducing their expression or inhibiting their activity on the respective target.
Targeting miRNAs with small molecule inhibitors still remains a challenge. The authors of the following study present RiboStrike, a deep-learning framework, that can identify molecules capable of modulating the activity of miRNAs. Arshadi et al., demonstrate the activity of the in silico selected compounds using gene expression profiling to measure miR-21 activity in response to treatment. miR-21 is a known driver of metastasis in breast cancer. Using small RNA-seq, expression profiling with QuantSeq-Pool 3′ mRNA-Seq, and reporter assays, the authors show that a RiboStrike-selected compound reduced miR-21 expression and activity. Further, treatment also reduced metastatic lung colonization in xenografted mice, establishing RiboStrike as an effective platform for discovering compounds against miRNAs.
Abstract
MicroRNAs are recognized as key drivers in many cancers but targeting them with small molecules remains a challenge. We present RiboStrike, a deep-learning framework that identifies small molecules against specific microRNAs. To demonstrate its capabilities, we applied it to microRNA-21 (miR-21), a known driver of breast cancer. To ensure selectivity toward miR-21, we performed counter-screens against miR-122 and DICER. Auxiliary models were used to evaluate toxicity and rank the candidates. Learning from various datasets, we screened a pool of nine million molecules and identified eight, three of which showed anti-miR-21 activity in both reporter assays and RNA sequencing experiments. Target selectivity of these compounds was assessed using microRNA profiling and RNA sequencing analysis. The top candidate was tested in a xenograft mouse model of breast cancer metastasis, demonstrating a significant reduction in lung metastases. These results demonstrate RiboStrike’s ability to nominate compounds that target the activity of miRNAs in cancer.
Transcriptome-wide evaluation of AGO-accessible anticancer siRNA activity with whole transcriptome sequencing
Similar to small molecules, RNA-based therapeutics face several challenges on the way to unfolding their potential to treat human diseases. Among them are delivery vehicles for cell-specific targeting of therapeutic RNAs and their specificity towards target transcripts.
An example is provided by a study from 2021 in which Gu et al. address the challenge of off-target effects when utilizing small interfering RNAs (siRNAs) to knock-down disease-related transcripts through aberrant seed-pairing. The authors developed siRNAs with miRNA-like activity. Typically, miRNAs function by associating with Argonaute (AGO) proteins into RNA-induced silencing complexes (RISCs) which bind to accessible sites along the target transcripts guided by the miRNA seed. By exploiting the seed-sequence of tumor-suppressive miRNAs based on previously identified AGO-miR binding sites, potent si/miRNAs were designed and validated. Whole transcriptome RNA-Seq is the gold standard to evaluate the functional consequences of the treatment with RNA therapeutics such as siRNAs. Lexogen’s CORALL RNA-Seq was used to confirm the anticancer activity of si/miRNAs against oncogenes in cervical cancer cells on a transcriptome-wide level.
Abstract
Small interfering RNAs (siRNAs) therapeutically induce RNA interference (RNAi) of disease-causing genes, but they also silence hundreds of seed-matched off-targets as behaving similar to microRNAs (miRNAs). miRNAs control the pathophysiology of tumors, wherein their accessible binding sites can be sequenced by Argonaute crosslinking immunoprecipitation (AGO CLIP). Herein, based on AGO CLIP, we develop potent anticancer siRNAs utilizing miRNA-like activity (mi/siRNAs). The mi/siRNAs contain seed sequences (positions 2–7) of tumor-suppressive miRNAs while maintaining perfect sequence complementarity to the AGO-accessible tumor target sites. Initially, host miRNA interactions with human papillomavirus 18 (HPV18) were identified in cervical cancer by AGO CLIP, revealing tumor-suppressive activity of miR-1/206 and miR-218. Based on the AGO-miRNA binding sites, mi/siRNAs were designed to target E6 and E7 (E6/E7) transcript with seed sequences of miR-1/206 (206/E7) and miR-218 (218/E7). Synergistic anticancer activity of 206/E7 and 218/E7 was functionally validated and confirmed via RNA sequencing and in vivo xenograft models (206/E7). Other mi/siRNA sequences were additionally designed for cervical, ovarian, and breast cancer, and available as an online tool (http://ago.korea.ac.kr/misiRNA); some of the mi/siRNAs were validated for their augmented anticancer activity (206/EphA2 and 206/Her2). mi/siRNAs could coordinate miRNA-like activity with robust siRNA function, demonstrating the potential of AGO CLIP analysis for RNAi therapeutics.
Combination therapy targeting factors underlying acquired drug resistance has the potential to improve cancer therapy and patient outcomes
Forkhead box protein M1 (FOXM1) is a transcription factor involved in the regulation of genes related to proliferation, the cell cycle, migration, and apoptosis and as such often dysregulated in various cancers, including ovarian, colorectal, breast, esophageal, and prostate cancers. Overexpression and relocation of FOXM1 confers resistance to chemotherapy and is associated with poor patient outcomes. FOXM1 is therefore a promising target to sensitize therapy-resistant solid cancers (Raghuwanshi et al., 2024). The authors highlight the anticancer potential of STL001, a first-generation modification drug of a previously identified FOXM1 inhibitor. STL001 effectively downregulates FOXM1 expression by targeting its transcriptional activity. This inhibition leads to a reduction in the expression of FOXM1 target genes involved in cell proliferation, survival, and drug resistance. Further, treatment with STL001 significantly increased the sensitivity of cancer cells to various chemotherapeutic agents, including cisplatin, gemcitabine, and doxorubicin, across multiple cancer types, such as lung cancer, ovarian cancer, and colorectal cancer suggesting it’s potential in targeting chemotherapy-resistance solid tumors.
Whole transcriptome sequencing using RiboCop rRNA depletion and CORALL RNA-Seq helped to confirm the mechanism of action for STL001 by comparison with the predecessor compound and a FOXM1 knock-down on the transcriptome-wide level in multiple cancer systems. The authors identified known FOXM1 targeted pathways as well as new activities and demonstrated that STL001 exhibits a favorable safety profile with minimal adverse effects, suggesting its potential for combination therapy and clinical translation.
Abstract
Forkhead box protein M1 (FOXM1) is often overexpressed in human cancers and strongly associated with therapy resistance and less good patient survival. The chemotherapy options for patients with the most aggressive types of solid cancers remain very limited because of the acquired drug resistance, making the therapy less effective. NPM1 mutation through the inactivation of FOXM1 via FOXM1 relocalization to the cytoplasm confers more favorable treatment outcomes for AML patients, confirming FOXM1 as a crucial target to overcome drug resistance. Pharmacological inhibition of FOXM1 could be a promising approach to sensitize therapy-resistant cancers. Here, we explore a novel FOXM1 inhibitor STL001, a first-generation modification drug of our previously reported FOXM1 inhibitor STL427944. STL001 preserves the mode of action of the STL427944; however, STL001 is up to 50 times more efficient in reducing FOXM1 activity in a variety of solid cancers. The most conventional cancer therapies studied here induce FOXM1 overexpression in solid cancers. The therapy-induced FOXM1 overexpression may explain the failure or reduced efficacy of these drugs in cancer patients. Interestingly, STL001 increased the sensitivity of cancer cells to conventional cancer therapies by suppressing both the high-endogenous and drug-induced FOXM1. Notably, STL001 does not provide further sensitization to FOXM1-KD cancer cells, suggesting that the sensitization effect is conveyed specifically through FOXM1 suppression. RNA-seq and gene set enrichment studies revealed prominent suppression of FOXM1-dependent pathways and gene ontologies. Also, gene regulation by STL001 showed extensive overlap with FOXM1-KD, suggesting a high selectivity of STL001 toward the FOXM1 regulatory network. A completely new activity of FOXM1, mediated through steroid/cholesterol biosynthetic process and protein secretion in cancer cells was also detected. Collectively, STL001 offers intriguing translational opportunities as combination therapies targeting FOXM1 activity in a variety of human cancers driven by FOXM1.
For more examples of applications of RNA-Seq in drug discovery, including high-throughput kinetic RNA sequencing and its potential to unravel primary and secondary effects, i.e., the sequence of action of a drug or compound, visit our previous blog discussing RNA Sequencing in Drug Discovery and Development.
Summary: RNA-Seq in Drug Discovery
RNA-Seq is a versatile tool that significantly enhances drug discovery efforts by facilitating the development of more effective and targeted therapies. RNA-Seq is used throughout the drug discovery process contributing to the understanding of a compounds mode-of-action, efficacy and safety, overall increasing the likelihood of the successful transition of a candidate to the next stage. A few key examples for the application of RNA-Seq in drug discovery are summarized below:
- RNA-Seq for All Drug Classes: RNA-Seq provides an unbiased, general assay to interrogate transcriptomic data, making it an invaluable tool for understanding the effects of all drug classes, from small molecules to RNA therapeutics.
- Unveiling Drug Mechanisms: RNA-Seq can elucidate a drug’s mechanism of action by revealing changes in gene expression patterns. This can be done at different levels identifying pathways or networks, or to study individual genes.
- Identifying Treatment Heterogeneity: Techniques like single-organoid analysis with RNA-Seq offer insights into patient-specific responses and the presence of treatment-resistant subclones within tumors opening the possibility for personalization of cancer treatments and improving patient outcomes.
- Validating Activity of RNA Therapeutics: RNA-Seq helps validate the activity of RNA therapeutics, such as siRNAs, by measuring changes in target gene expression on a transcriptome-wide scale.
- Exploring Combination Therapies: RNA-Seq provides valuable information for designing effective combination therapies by identifying potential synergistic interactions between drugs or compounds.
- Drug Repositioning: RNA-Seq can be used to understand the effects of existing drugs on new targets, potentially leading to drug repurposing opportunities.
Overall, next-generation sequencing (NGS) and the advance of novel technologies such as single-cell sequencing, spatial transcriptomics and the combination of multiple omics interrogating genome, transcriptome and proteome have an immense potential to improve human health and the fight against diseases by accelerating drug discoveries, optimizing combination therapies and personalizing treatment options.
References
Arshadi, K., Salem, M.,, Karner, H., Garcia, K., rab, A., Yuan, J. S., and Goodarzi, H. (2024). Functional microRNA-targeting drug discovery by graph-based deep learning. Patterns 5, 100909. DOI: 10.1016/j.patter.2023.100909
Eckert, S., Berner, N., Kramer, K., Schneider, A., Müller, J., Lechner, S., Brajkovic, S., Sakhteman, A., Graetz, C., Fackler, J., Dudek, M., Pfaffl, M. W., Knolle, P., Wilhelm, S, and Kuster, B. (2024). Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics. Nat Biotechnol. DOI:10.1038/s41587-024-02218-y
Gu, D., Ahn, S. H., Eom, S., Lee, H., Ham., J., Lee., D. H., Cho., Y. K., Koh, Y., Ignatova, E., Jang E., Chi., S. W. (2021) AGO-accessible anticancer siRNAs designed with synergistic miRNA-like activity. Molecular Therapy: Nucleic Acids, 23. DOI: 10.1016/j.omtn.2021.01.018
Jover, I., Ramos, M.C., Escámez, M.J. et al. (2024) Identification of novel small molecule-based strategies of COL7A1 upregulation and readthrough activity for the treatment of recessive dystrophic epidermolysis bullosa. Sci Rep 14, 18969. DOI: 10.1038/s41598-024-67398-8.
Le Compte, M., De La Hoz, E.C., Peeters, S., Rodrigues Fortes, F., Hermans, C., Domen, A., Smits, E., Lardon, F., Vandamme, T., Lin, A., Vanlanduit, S., Roeyen, G., Van Laere, S., Prenen, H., Peeters, M., and Deben, C. (2023) Single-organoid analysis reveals clinically relevant treatment-resistant and invasive subclones in pancreatic cancer. npj Precis. Onc. 7, 128. DOI: 10.1038/s41698-023-00480-y
Mayor-Ruiz, C., Bauer, S., Brand, M. Kozicka, Z., Siklos, M., Imrichova, H., Kaltheuner, I. H., Hahn, E., Seiler, K., Koren, A., Petzhold, G., Fellner, M., Bock, C., Müller, A. C., Zuber, J., Geyer, M., Thomä, N. H., Kubicek, S., and Winter, G. E. (2020) Rational discovery of molecular glue degraders via scalable chemical profiling. Nat Chem Biol 16, 1199–1207. DOI:10.1038/s41589-020-0594-x
Raghuwanshi, S., Zhang, X., Arbieva, Z., Khan, I., Mohammed, H., Wang, Z., Domling, A., Camacho, C. J., and Gartel, A. L. (2024) Novel FOXM1 inhibitor STL001 sensitizes human cancers to a broad-spectrum of cancer therapies. Cell Death Discov. 10, 211. DOI: 10.1038/s41420-024-01929-0
Zhu, Y., Zhu, L., and Wang, X.; Jin, Hongchuan (2022). RNA-based therapeutics: an overview and prospectus. Cell Death & Disease 13, 644. DOI: 10.1038/s41419-022-05075-2.
