Kai Wang

Supplementary Table 1: Atomic modelling, refinement, and validation statistics. Supplementary Table 2: Cryo-EM data collection and image analysis. Supplementary Table 3: Lymphoma cell lines evaluated in golcadomide study. Supplementary Table 4: Densitometry-based quantification of protein expression of selected markers within DLBCL cell line panel. Supplementary Table 5: Summary of the IC50 and proliferation AUC of lymphoma cell lines treated with golcadomide or other compounds. Supplementary Table 6: Genes with a significant modulation and temporal pattern in the golcadomide sensitive models. Supplementary Table 7: Pathway analysis of genes enriched for interferon signalling and immune system. Supplementary Table 8: BioMAP diversity plus panel result of golcadomide. Supplementary Table 9: Tissue distribution profile in rats treated with 10 mg/kg golcadomide. Supplementary Table 10: Plasma and brain pharmacokinetics of golcadomide in the OCI-Ly10 central nervous system lymphoma model. Supplementary Table 11. List of golcadomide enriched or depleted genes (FDR <= 0.05) in SU-DHL-4 CRISPR screen. Supplemental Table 12: Summary of apoptosis and proliferation of lymphoma cell lines treated with single agent or in combination with golcadomide. Supplementary Table 13: Summary of synergy score and max synergy area from the golcadomide combination therapies. Supplementary Table 14: Gene enrichment scores of FACS competition assays in DLBCL cell lines with golcadomide treatment. Supplementary Table 15: List of antibodies. Supplementary Table 16: List of genes and guide sequences used for CRISPR-Cas9 knockout assay and genome wide CRISPR screen.

Supplementary Fig. 1. Golcadomide induced transition from CRBNopen to CRBNclosed for efficient recruitment and degradaion. Supplementary Fig. 2. Antiproliferative effect of golcadomide is mediated via CRBN-based IKZF1/3 degradation. Supplementary Fig. 3. Golcadomide is broadly active with potent cell autonomous antiproliferative activity. Supplementary Fig. 4. Antiproliferative effect of golcadomide is mediated via CRBN based IKZF1/3 degradation. Supplementary Fig. 5. Golcadomide demonstrated minimal broad cytotoxicity and reversible effects on neutrophil maturation. Supplementary Fig. 6. Golcadomide stimulated immune activation, reversed T cell exhaustion, and exhibited potent antitumor synergy with rituximab. Supplementary Fig. 7. Overview of different treatment conditions and technical replicates in the CRISPR screen. Supplementary Fig. 8. CRISPR screen identified genes and pathways that exacerbated or attenuated antiproliferative effects of golcadomide in SU-DHL-4 upon inactivation. Supplementary Fig. 9. KO of PRC2 complex components enhanced cell antiproliferation by golcadomide. Supplementary Fig. 10. Apoptosis induction is linked to the antiproliferative effects of golcadomide. Supplementary Fig. 11. NF-κB hyperactivation reduced golcadomide-induced DLBCL cell apoptosis. Supplementary Fig. 12. XPO1 inhibitor enhances antiproliferative effects of golcadomide. Supplementary Fig. 13. AMBRA1 knockout renders resistance to golcadomide via cyclin D3/CDK4/6/Rb axis in DLBCL. Supplementary Fig. 14. KCTD5 ameliorated the antiproliferative effects of golcadomide via GNG5. Supplementary Fig. 15. Chemical synthesis of golcadomide. Supplementary Fig. 16. Representative gating strategies for flow cytometry-based assays.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive and heterogeneous disease with limited treatment options and a poor prognosis, especially for patients refractory to standard therapies. We report the discovery of golcadomide (CC-99282), an oral cereblon-modulating CELMoD agent designed using target-specific knowledge and optimized pharmacologic properties for the treatment of DLBCL. Golcadomide exhibited rapid, deep, and sustained degradation of transcription factors IKZF1 and IKZF3, surpassing the antitumor activity of the IMiD agent lenalidomide in preclinical models. In human lymphoma cell lines, golcadomide downregulated MYC, activated IFN-stimulated genes, and promoted antiproliferation, apoptosis, and immunogenic cell death. In mouse xenografts, golcadomide preferentially distributed to tissues known to be affected by lymphoma, resulting in enhanced tumor regression and tumor-free outcomes. Pharmacologic and CRISPR screening further revealed genes and pathways underlying golcadomide’s antitumor efficacy. These findings supported golcadomide as a promising drug candidate for DLBCL, providing a strong rationale for future golcadomide-based regimens. Significance: Golcadomide is an oral cereblon-modulating agent for the treatment of DLBCL. It exhibited rapid, deep, and sustained degradation of IKZF1 and IKZF3, preferentially accumulated in lymphoma residence tissues, and delivered robust antitumor activity. These results provide a strong rationale for continued clinical investigation of golcadomide for patients with DLBCL.

In recent years, several chemical language models have been developed, inspired by the success of protein language models and advancements in natural language processing. In this study, we explore whether pre-training a chemical language model on billion-scale compound datasets, such as Enamine and ZINC20, can lead to improved compound representation in the drug space. We compare the learned representations of these models with the de facto standard compound representation, and evaluate their potential application in drug discovery and development by benchmarking them on biophysics, physiology, and physical chemistry datasets. Our findings suggest that the conventional masked language modeling approach on these extensive pre-training datasets is insufficient in enhancing compound representations. This highlights the need for additional physicochemical inductive bias in the modeling beyond scaling the dataset size.

Gastric cancer (GC) is the most common gastrointestinal malignancy worldwide. However, the molecular mechanisms of the progression of GC are not fully understood. Ras-responsive element binding protein 1 (RREB1) is an oncogene in many types of cancer that is involved in various biological processes, such as DNA damage repair, cell growth and proliferation, cell differentiation, fat development, and fasting glucose balance. In this study, we demonstrate the role of RREB1 in gastric cancer. First, by immunohistochemistry staining (IHC) and bioinformatics analysis, we demonstrated the expression of RREB1 in gastric cancer and paired normal gastric tissues. Then, we established RREB1 overexpression and knockdown cell lines via lentiviral transfection and detected cell proliferation by using MTT, colony-forming, cell cycle and apoptosis assays in vitro. We demonstrated the effect of RREB1 on cell proliferation in vivo by using a subcutaneous xenograft tumor model in nude mice. Finally, by using Western blotting and IHC, we demonstrated the possible mechanism by which RREB1 affects cell proliferation. The IHC and bioinformatics analyses demonstrated that RREB1 was highly expressed in gastric cancer and showed that RREB1-expressing patients had a larger tumor size and more lymphovascular invasion than RREB1-negative patients. Knockdown of RREB1 inhibited cell proliferation in vivo and in vitro. Knockdown of RREB1 enhanced p16 expression in vivo and in vitro, and p16 expression was negatively related to RREB1 in gastric cancer tissue. RREB1 was highly expressed in gastric cancer, and knockdown of RREB1 inhibited cell proliferation via enhanced p16 expression.

The multiplexed cancer cell line screening platform PRISM demonstrated its utility in testing hundreds of cell lines in a single run, possessing the potential to speed up anti-cancer drug discovery, validation and optimization. Here we described the development and implementation of a next-generation PRISM platform combining Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9-mediated gene editing, cell line DNA barcoding and next-generation sequencing to enable genetic and/or pharmacological assessment of target addiction in hundreds of cell lines simultaneously. Both compound and CRISPR-knockout PRISM screens well recapitulated the results from individual assays and showed high consistency with a public database.

CC-122 is a next-generation cereblon E3 ligase–modulating agent that has demonstrated promising clinical efficacy in patients with relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL). Mechanistically, CC-122 induces the degradation of IKZF1/3, leading to T-cell activation and robust cell-autonomous killing in DLBCL. We report a genome-wide CRISPR/Cas9 screening for CC-122 in a DLBCL cell line SU-DHL-4 with follow-up mechanistic characterization in 6 DLBCL cell lines to identify genes regulating the response to CC-122. Top-ranked CC-122 resistance genes encode, not only well-defined members or regulators of the CUL4/DDB1/RBX1/CRBN E3 ubiquitin ligase complex, but also key components of signaling and transcriptional networks that have not been shown to modulate the response to cereblon modulators. Ablation of CYLD, NFKBIA, TRAF2, or TRAF3 induces hyperactivation of the canonical and/or noncanonical NF-κB pathways and subsequently diminishes CC-122–induced apoptosis in 5 of 6 DLBCL cell lines. Depletion of KCTD5, the substrate adaptor of the CUL3/RBX1/KCTD5 ubiquitin ligase complex, promotes the stabilization of its cognate substrate, GNG5, resulting in CC-122 resistance in HT, SU-DHL-4, and WSU-DLCL2. Furthermore, knockout of AMBRA1 renders resistance to CC-122 in SU-DHL-4 and U-2932, whereas knockout of RFX7 leads to resistance specifically in SU-DHL-4. The ubiquitous and cell line–specific mechanisms of CC-122 resistance in DLBCL cell lines revealed in this work pinpoint genetic alternations that are potentially associated with clinical resistance in patients and facilitate the development of biomarker strategies for patient stratification, which may improve clinical outcomes of patients with R/R DLBCL.

A number of clinically validated drugs have been developed by repurposing the CUL4-DDB1-CRBN-RBX1 (CRL4CRBN) E3 ubiquitin ligase complex with molecular glue degraders to eliminate disease-driving proteins. Here, we present the identification of a first-in-class GSPT1-selective cereblon E3 ligase modulator, CC-90009. Biochemical, structural, and molecular characterization demonstrates that CC-90009 coopts the CRL4CRBN to selectively target GSPT1 for ubiquitination and proteasomal degradation. Depletion of GSPT1 by CC-90009 rapidly induces acute myeloid leukemia (AML) apoptosis, reducing leukemia engraftment and leukemia stem cells (LSCs) in large-scale primary patient xenografting of 35 independent AML samples, including those with adverse risk features. Using a genome-wide CRISPR-Cas9 screen for effectors of CC-90009 response, we uncovered the ILF2 and ILF3 heterodimeric complex as a novel regulator of cereblon expression. Knockout of ILF2/ILF3 decreases the production of full-length cereblon protein via modulating CRBN messenger RNA alternative splicing, leading to diminished response to CC-90009. The screen also revealed that the mTOR signaling and the integrated stress response specifically regulate the response to CC-90009 in contrast to other cereblon modulators. Hyperactivation of the mTOR pathway by inactivation of TSC1 and TSC2 protected against the growth inhibitory effect of CC-90009 by reducing CC-90009-induced binding of GSPT1 to cereblon and subsequent GSPT1 degradation. On the other hand, GSPT1 degradation promoted the activation of the GCN1/GCN2/ATF4 pathway and subsequent apoptosis in AML cells. Collectively, CC-90009 activity is mediated by multiple layers of signaling networks and pathways within AML blasts and LSCs, whose elucidation gives insight into further assessment of CC-90009s clinical utility. These trials were registered at www.clinicaltrials.gov as #NCT02848001 and #NCT04336982).

Bulk tissue DNA methylation profiling has been used to examine epigenetic mechanisms and biomarkers of complex diseases such as cancer. However, heterogeneity of cellular content in tissues complicates result interpretation and utility. In silico deconvolution of cellular fractions from bulk tissue data offers a fast and inexpensive alternative to experimentally measuring such fractions. In this study, we report the design, implementation, and benchmarking of MethylResolver, a Least Trimmed Squares regression-based method for inferring leukocyte subset fractions from methylation profiles of tumor admixtures. Compared to previous approaches MethylResolver is more accurate as unknown cellular content in the mixture increases and is able to resolve tumor purity-scaled immune cell-type fractions without a cancer-specific signature. We also present a pan-cancer deconvolution of TCGA, recapitulating that high eosinophil fraction predicts improved cervical carcinoma survival and identifying elevated B cell fraction as a previously unreported predictor of poor survival for papillary renal cell carcinoma.

Ultra-deep next-generation sequencing of circulating tumor DNA (ctDNA) holds great promise as a tool for the early detection of cancer and for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection. To achieve high accuracy of variant calling via better distinguishing low-frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors. The results on both simulated data and real data from healthy subjects demonstrate that the proposed algorithm consistently outperforms a current, state-of-the-art, position-specific error polishing model, particularly when the sample size of healthy subjects is small. TNER significantly enhances the specificity of downstream ctDNA mutation detection without sacrificing sensitivity. The tool is publicly available at https://github.com/ctDNA/TNER .