Drug resistance is a major challenge in cancer therapy. Cancer cells with pre-existing or acquired mutations that confer resistance to a given drug treatment outgrow the susceptible cell population and cause cancer recurrence after an initial successful treatment response. Knowledge about resistance mutations before they occur in the clinic could prevent unnecessary patient treatment with ineffective drugs, in clinical trials as well as clinical practice, or potentially speed up the development of follow-up compounds. Here, we focused on on-target amino acid mutations that confer resistance to an inhibitor compound with a known binding mode. We evaluated whether a combination of physics-based free energy perturbation (FEP) affinity estimates and protein language model-based protein fitness estimates could improve the in silico identification of resistance mutations. Validation was done with data from deep mutational scanning (DMS) experiments that tested for resistance to single amino acid mutations. A public data set testing ERK2 resistance against the inhibitor SCH772984 and an internal data set testing resistance of an EGFR_exon20 mutant against a Bayer small molecule inhibitor were used. Our results show that protein fitness estimates can facilitate the identification of resistance mutations by filtering mutations with a low estimated fitness. Even though FEP has flagged such mutations as affinity-decreasing and thus potentially resistant, they were not resistant according to the DMS experiment and therefore correctly filtered out. This indicates that protein language model-based protein fitness estimates could be a computationally efficient method to filter mutations without having to model the negative impact of mutations on native function or protein stability, which is error-prone and computationally expensive.

The most common fusion oncoprotein in the most common pediatric solid tumor, pediatric low-grade glioma (pLGG), is KIAA1549::BRAF. Although MAPK inhibitors show early promise, they often fail to achieve durable cures, highlighting the need to develop new therapeutics for KIAA1549::BRAF-driven tumors. In this study we leverage genome-scale anti-transformation CRISPR screens to uncover KIAA1549::BRAF-specific genetic vulnerabilities. Across all genes, POMT1 and POMT2, the two members of the heterodimeric Protein O-mannosyltransferase (POMT) complex emerge as the strongest KIAA1549::BRAF-specific dependencies. We demonstrate that KIAA1549 is a direct substrate of this complex, and that glycosylation of KIAA1549::BRAF by POMT is necessary for its maturation through the secretory pathway and subsequent oncogenic signaling. These data highlight for the first time a new route to directly target KIAA1549::BRAF independent of the MAPK pathway. This work also uncovered an unexpected and previously unrecognized role for KIAA1549 in driving KIAA1549::BRAF oncogenic signaling. The prevailing dogma has been that BRAF fusions exert their transforming activity through truncation and removal of N-terminal regulatory domains, thereby rendering the BRAF kinase domain constitutively active. We demonstrate that BRAF fusion partners, including KIAA1549, contain domains that facilitate membrane localization, thereby enhancing BRAF signaling. These findings challenge the traditional view of BRAF fusion biology and establish a role for fusion partners in shaping oncogenic potential. Sean Misek, Anna Borgenvik, Daniel Christen, Gloria Kyrila, Alexander Zhang, Sarah Reel, Michelle Boisvert, Kelly Cai, Kevin Zhou, Elizabeth Gonzales, Lorena Lazo de la Vega, Timothy Ragnoni, Nicole Persky, Tanaz Abid, Esteban Miglietta, Sergey Vakhrushev, Michael Stumpe, Jacquelyn Jones, Seth Malinowski, Lobna Elsadek, Aaron Fultineer, Kira Tang, Antonio Maldera, Hyesung Jeon, Sangita Pal, Todd Golub, William Hahn, Eric Fischer, Jesse Boehm, Jörn Dengjel, Henrik Clausen, Nada Jabado, Till Milde, Anne Carpenter, Beth Cimini, Keith Ligon, Katherine Janeway, Michael Eck, David Root, David Jones, Timothy Phoenix, Rameen Beroukhim, Hiren Jitendra Joshi, Tilman Tilman, Adnan Halim, Pratiti Bandopadhayay. O-mannosylation and protein maturation checkpoints represent therapeutic opportunities in BRAF fusion protein oncogenesis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Fusion-Positive Cancer: From Discovery to Therapy; 2026 Jan 13-15; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(1_Suppl):Abstract nr B026.

Rhodopsin (RHO) missense variants are a leading cause of autosomal dominant retinitis pigmentosa (adRP), a progressive retinal degeneration with no currently approved therapies. Interpreting the pathogenicity of the growing number of identified RHO variants is a major clinical challenge, and understanding their disease mechanisms is essential for developing effective therapies. Here, we present a high-resolution map of RHO missense variant trafficking using two complementary deep mutational scanning (DMS) approaches based on a surface abundance immunoassay and a membrane proximity assay. We generated a comprehensive dataset encompassing all 6,612 possible single-residue missense variants, revealing a strong correlation between the two methods. Over 700 variants were identified with pathogenic trafficking scores, significantly expanding the number of RHO variants with functional evidence supporting pathogenicity. We demonstrate a high concordance between the trafficking scores and ClinVar pathogenicity classifications, highlighting this approach's utility in resolving variants of uncertain significance (VUS). The data also identified structurally clustered trafficking-deficient variants, predominantly within the N-terminal region and second extracellular loop, in and above the extracellular/intradiscal beta-plug region. Furthermore, we evaluated the efficacy of the non-retinoid pharmacological chaperone YC-001, observing significant rescue of trafficking defects in a majority of mistrafficking variants. This comprehensive functional map of RHO missense variants provides a valuable resource for pathogenicity assessment, genotype-phenotype correlations, and the development of targeted therapeutic strategies for RHO-adRP, paving the way for improved diagnosis and treatment for patients.

Supplementary figures and information

Drug resistance is a major challenge in cancer therapy. Cancer cells with pre-existing or acquired mutations that confer resistance to a given drug treatment outgrow the susceptible cell population and cause cancer recurrence after an initial successful treatment response. Knowledge about resistance mutations before they occur in the clinic could prevent unnecessary patient treatment with ineffective drugs, in clinical trials as well as clinical practice, or potentially speed up the development of follow-up compounds. Here, we focused on on-target amino acid mutations that confer resistance to an inhibitor compound with a known binding mode. We evaluated whether a combination of physics-based free energy perturbation (FEP) affinity estimates and protein language model-based protein fitness estimates could improve the in silico identification of resistance mutations. Validation was done with data from deep mutational scanning (DMS) experiments that tested for resistance to single amino acid mutations. A public data set testing ERK2 resistance against the inhibitor SCH772984 and an internal data set testing resistance of an EGFR_exon20 mutant against a Bayer small molecule inhibitor were used. Our results show that protein fitness estimates can facilitate the identification of resistance mutations by filtering mutations with a low estimated fitness. Even though FEP has flagged such mutations as affinity-decreasing and thus potentially resistant, they were not resistant according to the DMS experiment and therefore correctly filtered out. This indicates that protein language model-based protein fitness estimates could be a computationally efficient method to filter mutations without having to model the negative impact of mutations on native function or protein stability, which is error-prone and computationally expensive.

Chromatin remodeling complexes, such as the SWItch/Sucrose Non-Fermentable (SWI/SNF) complex, play key roles in regulating gene expression by modulating nucleosome positioning. The core subunit SMARCB1 is essential for these functions, as it anchors the complex to the nucleosome acidic patch, enabling effective chromatin remodeling. While biallelic inactivation of SMARCB1 is a hallmark of several aggressive pediatric malignancies, the functional implication of missense mutations is not fully understood. Current diagnostic approaches focus on detecting the presence or absence of SMARCB1 by immunohistochemistry often without consideration of mutation status. Here, we present a comprehensive deep mutational scanning of SMARCB1, encompassing 8418 alterations, to assess their functional impact. We show that RPT2 missense mutations disrupt SMARCB1 antiproliferation function by destabilizing the SWI/SNF complex and impairing chromatin remodeling and transcriptional regulation comparable to nonsense mutations. These functional defects occur despite maintaining detectable protein expression thereby challenging current diagnostic reliance on IHC. These findings provide deeper understanding of the role of SMARCB1 in chromatin remodeling and cancer biology, highlighting limitations of mutation classification approaches.

Abstract To elucidate the functional impact of KRAS variants, we conducted deep mutational scanning (DMS) screens targeting both wild-type and KRASG12D mutant alleles. This comprehensive approach enabled us to characterize the oncogenic potential of nearly all possible KRAS variants, leading to the identification of several novel transforming alleles. We developed a model linking the frequency of KRAS mutations in human cancers to their transforming capability, inherent mutational probabilities, and tissue-specific mutational signatures. Biochemical and structural analyses of second-site suppressor variants discovered in the KRASG12D DMS screen revealed that attenuation of oncogenic KRAS activity can result from protein instability or increased conformational rigidity. These changes diminish KRAS’s binding affinity for effector proteins such as RAF and PI3-kinases, or reduce its SOS-mediated nucleotide exchange activity. Collectively, our findings map the landscape of single amino acid substitutions that regulate KRAS function, providing a crucial resource for clinical interpretation of KRAS variants and uncovering mechanisms by which oncogenic KRAS can be inactivated for therapeutic development. Citation Format: Jason Kwon, Julien Dilly, Shengwu Liu, Eejung Kim, Yuemin Bian, Srisathiyanarayanan Dharmaiah, Timothy Tran, Kevin Kapner, Seav Huong Ly, Xiaoping Yang, Dana Rabara, Timothy Waybright, Andrew Giacomelli, Andrew Hong, Sean Misek, Arvind Ravi, Chris Lemke, Kevin Haigis, David Root, Dominic Esposito, Dwight Nissley, Andrew Stephen, Frank McCormick, Dhirendra Simanshu, William Hahn, Andrew Aguirre. Comprehensive structure-function analysis reveals gain- and loss-of-function mechanisms impacting oncogenic KRAS activity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RAS Oncogenesis and Therapeutics; 2026 Mar 5-8; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(5_Suppl_1):Abstract nr PR006.

Supplementary Table S5: Molecular features of patient-derived LMS models from Champions Oncology used in in vivo validation studies (five LMS PDX), including clinical and morphological features of LMS tumors from which they were derived.

Supplementary Figure S2: A. Counts of small deletions (<30kb) are compared in Sig3+ and Sig3- LMS tumors (analyzed by OncoPanel v3 and v 3.1, n=166). B. Counts of small deletions (<30kb) are significantly higher in tumors with deleterious alterations in POLH, POLD1, FANCM or XRCC1, all of which are implicated in DNA double strand break repair during different phases of the cell cycle (**** = p < 0.0001; n.s.= not significant)

Riboflavin is a diet-derived vitamin in higher organisms that serves as a precursor for flavin mononucleotide and flavin adenine dinucleotide, key cofactors that participate in oxidoreductase reactions. Here, using proteomic, metabolomic and functional genomics approaches, we describe a specific riboflavin dependency in acute myeloid leukemia and demonstrate that, in addition to energy production via oxidative phosphorylation, a key biological role of riboflavin is to enable nucleotide biosynthesis and iron-sulfur cluster metabolism. Genetic perturbation of riboflavin metabolism pathways or exogenous depletion in physiological culture medium induce nucleotide imbalance and DNA damage responses, as well as impair the stability and activity of proteins which utilize [4Fe-4S] iron-sulfur clusters as cofactors. We identify a window of therapeutic opportunity upon riboflavin starvation or chemical riboflavin metabolism perturbation and demonstrate that this strongly synergizes with BCL-2 inhibition. Our work identifies riboflavin as a critical metabolic dependency in leukemia, with functions beyond energy production.

To identify genes and pathways required for the survival of MYC-amplified cancers, we engineered and screened at genome scale an isogenic cell system where transformation is driven by oncogenic MYC. We found that the mitochondrial membrane transporter, TIMM17A, was uniquely essential for survival of MYC-transformed cells. This dependency arises due to MYC-driven suppression of TIMM17B, the paralog of TIMM17A. TIMM17A/B is an essential component of the mitochondrial TIM23 transporter complex, and MYC-induced suppression of TIMM17B creates a strong dependency on TIMM17A. N-acetylaspartate supplementation rescues TIMM17A dependency in MYC-amplified cell lines, highlighting the unique and crucial role of this metabolite in the viability of MYC-amplified cancers. These observations identify a paralog dependency required for the survival of a subset of MYC-driven cancers. Sydney M. Moyer, Nina Ilic, Sydney Gang, Jasmine Stavridi, Gaia Taig, Joseph D. DeAngelo, Andrea Jiang, Brian H. Shim, Jonathan P. Rennhack, Melis A. Akinci, Jonathan So, Helen Wang, Federica Piccioni, Jessica A. Talamas, David E. Root, William C. Hahn. MYC primes a paralog synthetic lethality involving the mitochondrial transporters TIMM17A and TIMM17B and N-acetylaspartate [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB318.

Biliary tract cancers (BTC) are aggressive malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we report integrative analysis of 63 BTC cell lines via multi-omics and genome-scale CRISPR screens. We identify widespread EGFR dependency in BTC, alongside dependencies selective to anatomic subtypes. Additionally, we delineate strategies to overcome therapeutic resistance, with combined EGFR inhibition potentiating targeting of KRAS-mutant and FGFR2 fusion-driven models and SHP2 inhibition effective in the latter context. Clustering RNA/protein expression and dependencies data revealed functional relationships transcending single-gene alterations, with biliary, squamous, or dual biliary/hepatocyte lineage signatures stratifying BTC models. These subtypes exhibit distinct dependency profiles-including cell fate transcription factors GRHL2, TP63, and HNF1B, respectively-and demonstrate prognostic significance in patient samples. Potential subtype-specific targetable vulnerabilities include integrinα3 and the detoxification enzyme UXS1. This cell line atlas reveals therapeutic targets in molecularly defined BTCs, unveils disease subtypes, and provides a resource for therapeutic development. SIGNIFICANCE:This integrative analysis of BTC cell lines defines the landscape of vulnerabilities across BTCs, stratifying distinct subtypes, and provides a key resource for studying disease heterogeneity. The findings highlight strategies for targeting BTCs with specific genomic alterations, as well as broader approaches based on shared molecular programs and essential pathways.

Supplementary Figure S10: Effect of peposertib (100 mg/kg bid), low-dose pegylated liposomal doxorubicin (3 mg/kg qw) and combination on additional LMS PDX. A. CTG-1182. B. CTG-1005. C. CTG-1079.

Cell Painting images offer valuable insights into a cell's state and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP Cell Painting Consortium perturbed roughly 75% of the protein-coding genome in human U-2 OS cells, generating a rich resource of single-cell images and extracted features. These profiles capture the phenotypic impacts of perturbing 15,243 human genes, including overexpressing 12,609 genes (using open reading frames) and knocking out 7,975 genes (using CRISPR-Cas9). Here we mitigated technical artifacts by rigorously evaluating data processing options and validated the dataset's robustness and biological relevance. Analysis of phenotypic profiles revealed previously undiscovered gene clusters and functional relationships, including those associated with mitochondrial function, cancer and neural processes. The JUMP Cell Painting genetic dataset is a valuable resource for exploring gene relationships and uncovering previously unknown functions.

Supplementary Figure S6 Representative cell culture images of LMS04 cultures untreated or treated with 2nM doxorubicin, 400 nM peposertib, or the combination of both, utilized for computationally assisted cell culture confluence analysis (See Supplementary Figure S7).

Supplementary Figure S9: Cell proliferation assay (BrdU incorporation) demonstrates that combination of DNA-PK inhibition with low-dose doxorubicin reduces LMS03 and LMS05 cell proliferation compared to either drug alone. Peposertib and AZD7648 are structurally unrelated DNA-PK inhibitors. Cells were treated for 7 days with each drug and the combinations at the indicated doses; BrdU incorporation over 24h was measured at day 7 with a luminescence-based ELISA assay (Roche)

Supplementary Figure S8: Synergistic effects of peposertib and low-dose doxorubicin combinations in LMS cells. Cell proliferation assay (BrdU incorporation) demonstrates that addition of low-dose doxorubicin to DNA-PKi treatment results in synergistic effects on LMS03, LMS04 and LMS05 cell proliferation. Cells were treated for 7 days with the drug combinations at the indicated doses; BrdU incorporation over 24h was measured at day 7 with a luminescence-based ELISA assay (Roche). Synergy scores and heatmap / surface plots were generated using SynergyFinder (RRID:SCR_019318)(35).