Functional activation of the AKT-mTOR signalling axis in a real-world metastatic breast cancer cohort.

BACKGROUND: Mutations of the PIK3CA/AKT/mTOR axis are common events in metastatic breast cancers (MBCs). This study was designed to evaluate the extent to which genetic alterations of the PIK3CA/AKT/mTOR can predict protein activation of this signalling axis in MBCs. METHODS: Molecular profiles were generated by CLIA-certified laboratories from a real-world evidence cohort of 171 MBC patients. Genetic alterations of the PIK3CA pathway were measured using next-generation sequencing. Activation levels of AKT and downstream signalling molecules were quantified using two orthogonal proteomic methods. Protein activity was correlated with underlying genomic profiles and response to CDK4/6 inhibition in combination with endocrine treatment (ET). RESULTS: Oncogenic alterations of the PIK3CA/AKT/PTEN pathway were identified in 49.7% of cases. Genomic profiles emerged as poor predictors of protein activity (AUC:0.69), and AKT phosphorylation levels mimicked those of mutant lesions in 76.9% of wild-type tumours. High phosphorylation levels of the PI3K/AKT/mTOR downstream target p70S6 Kinase (T389) were associated with shorter PFS in patients treated with CDK4/6 inhibitors in combination with ET (HR:4.18 95%CI:1.19-14.63); this association was not seen when patients were classified by mutational status. CONCLUSIONS: Phosphoprotein-based measurements of drug targets and downstream substrates should be captured along with genomic information to identify MBCs driven by the PI3K/AKT/mTOR signalling.

Signaling dynamics in coexisting monoclonal cell subpopulations unveil mechanisms of resistance to anti-cancer compounds.

BACKGROUND: Tumor heterogeneity is a main contributor of resistance to anti-cancer targeted agents though it has proven difficult to study. Unfortunately, model systems to functionally characterize and mechanistically study dynamic responses to treatment across coexisting subpopulations of cancer cells remain a missing need in oncology. METHODS: Using single cell cloning and expansion techniques, we established monoclonal cell subpopulations (MCPs) from a commercially available epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer cell line. We then used this model sensitivity to the EGFR inhibitor osimertinib across coexisting cell populations within the same tumor. Pathway-centered signaling dynamics associated with response to treatment and morphological characteristics of the MCPs were assessed using Reverse Phase Protein Microarray. Signaling nodes differentially activated in MCPs less sensitive to treatment were then pharmacologically inhibited to identify target signaling proteins putatively implicated in promoting drug resistance. RESULTS: MCPs demonstrated highly heterogeneous sensitivities to osimertinib. Cell viability after treatment increased > 20% compared to the parental line in selected MCPs, whereas viability decreased by 75% in other MCPs. Reduced treatment response was detected in MCPs with higher proliferation rates, EGFR L858R expression, activation of EGFR binding partners and downstream signaling molecules, and expression of epithelial-to-mesenchymal transition markers. Levels of activation of EGFR binding partners and MCPs' proliferation rates were also associated with response to c-MET and IGFR inhibitors. CONCLUSIONS: MCPs represent a suitable model system to characterize heterogeneous biomolecular behaviors in preclinical studies and identify and functionally test biological mechanisms associated with resistance to targeted therapeutics.

Enhancing precision in colorectal cancer surgery: development of an LGR5-targeting RSPO1 peptide mimetic as a contrast agent for intraoperative fluorescence molecular imaging.

Colorectal cancer (CRC) is the third most common cancer worldwide. In the United States alone, CRC was responsible for approximately 52,550 deaths in 2023, with an estimated 153,020 new cases. CRC presents with synchronous peritoneal spread in 5-10% of patients, and up to 20-50% of patients with recurrent disease will develop metachronous colorectal cancer peritoneal metastatic (CRC-PM) disease. Eradication of the tumor, tumor margins and microscopic residual disease is paramount, as microscopic residual disease is associated with local recurrences, with 5-year survival rates of less than 35%. The success of resection and reduction of residual disease depends on the accuracy with which cancer cells and normal tissue can be intra-operatively distinguished. Fluorescence Molecular Imaging (IFMI) and tumor-targeted contrast agents represent a promising approach for intraoperative detection and surgical intervention. Proper target selection, the development of scalable imaging agents and enhanced real-time tumor and tumor microenvironment imaging are critical to enabling enhanced surgical resection. LGR5 (leucine-rich repeat-containing G-protein-coupled receptor 5), a colonic crypt stem cell marker and the receptor for the R-spondins (RSPO) in the Wnt signaling pathway, is also expressed on colorectal cancer stem cells (CSC) and on CRC tumors and metastases, suggesting it could be a useful target for imaging of CRC. However, there are numerous diverging reports on the role of LGR5 in CRC therapy and outcomes. Herein, we report on the synthesis and validation of a 37 amino acid RSPO1-mimetic peptide, termed RC18, that was specifically designed to access the R-spondin binding site of LGR5 to potentially be used for interoperative imaging of CRC-PM. The receptor-binding capabilities of the RC18 indicate that direct interactions with LGR5 neither significantly increased LGR5 signaling nor blocked RSPO1 binding and signal transduction, suggesting that the RSPO1-mimetic is functionally inert, making it an attractive contrast agent for intraoperative CRC-PM imaging.

Determining the ERK-regulated phosphoproteome driving KRAS-mutant cancer.

To delineate the mechanisms by which the ERK1 and ERK2 mitogen-activated protein kinases support mutant KRAS-driven cancer growth, we determined the ERK-dependent phosphoproteome in KRAS-mutant pancreatic cancer. We determined that ERK1 and ERK2 share near-identical signaling and transforming outputs and that the KRAS-regulated phosphoproteome is driven nearly completely by ERK. We identified 4666 ERK-dependent phosphosites on 2123 proteins, of which 79 and 66%, respectively, were not previously associated with ERK, substantially expanding the depth and breadth of ERK-dependent phosphorylation events and revealing a considerably more complex function for ERK in cancer. We established that ERK controls a highly dynamic and complex phosphoproteome that converges on cyclin-dependent kinase regulation and RAS homolog guanosine triphosphatase function (RHO GTPase). Our findings establish the most comprehensive molecular portrait and mechanisms by which ERK drives KRAS-dependent pancreatic cancer growth.

Mediator kinase inhibition impedes transcriptional plasticity and prevents resistance to ERK/MAPK-targeted therapy in KRAS-mutant cancers.

Acquired resistance remains a major challenge for therapies targeting oncogene activated pathways. KRAS is the most frequently mutated oncogene in human cancers, yet strategies targeting its downstream signaling kinases have failed to produce durable treatment responses. Here, we developed multiple models of acquired resistance to dual-mechanism ERK/MAPK inhibitors across KRAS-mutant pancreatic, colorectal, and lung cancers, and then probed the long-term events enabling survival against this class of drugs. These studies revealed that resistance emerges secondary to large-scale transcriptional adaptations that are diverse and cell line-specific. Transcriptional reprogramming extends beyond the well-established early response, and instead represents a dynamic, evolved process that is refined to attain a stably resistant phenotype. Mechanistic and translational studies reveal that resistance to dual-mechanism ERK/MAPK inhibition is broadly susceptible to manipulation of the epigenetic machinery, and that Mediator kinase, in particular, can be co-targeted at a bottleneck point to prevent diverse, cell line-specific resistance programs.

Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities.

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

Targeting HER2/HER3 co-mutations in metastatic breast cancer: Case reports of exceptional responders to trastuzumab and pertuzumab therapy.

BACKGROUND: Overexpression of HER2 plays an important role in cancer progression and is the target of multiple therapies in HER2-positive breast cancer. Recent studies have also highlighted the presence of activating mutations in HER2, and HER3 that are predicted to enhance HER2 downstream pathway activation in a HER2-dependent manner. METHODS: In this report, we present two exceptional responses in hormone receptor-positive, HER2-nonamplified, HER2/HER3 co-mutated metastatic breast cancer patients who were treated with the anti-HER2-directed monoclonal antibodies, trastuzumab and pertuzumab. RESULTS: Both patients acheived exceptional responses to treatment, suggesting that combined trastuzumab, pertuzumab, and endocrine therapy could be a highly effective therapy for these patients and our observations could help prioritize trastuzumab deruxtecan as an early therapeutic choice for patients whose cancers have activating mutations in HER2.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling.

BACKGROUND: Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics. METHODS: Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor. RESULTS: LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ). CONCLUSIONS: Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

RHOAL57V drives the development of diffuse gastric cancer through IGF1R-PAK1-YAP1 signaling.

Cancer-associated mutations in the guanosine triphosphatase (GTPase) RHOA are found at different locations from the mutational hotspots in the structurally and biochemically related RAS. Tyr42-to-Cys (Y42C) and Leu57-to-Val (L57V) substitutions are the two most prevalent RHOA mutations in diffuse gastric cancer (DGC). RHOAY42C exhibits a gain-of-function phenotype and is an oncogenic driver in DGC. Here, we determined how RHOAL57V promotes DGC growth. In mouse gastric organoids with deletion of Cdh1, which encodes the cell adhesion protein E-cadherin, the expression of RHOAL57V, but not of wild-type RHOA, induced an abnormal morphology similar to that of patient-derived DGC organoids. RHOAL57V also exhibited a gain-of-function phenotype and promoted F-actin stress fiber formation and cell migration. RHOAL57V retained interaction with effectors but exhibited impaired RHOA-intrinsic and GAP-catalyzed GTP hydrolysis, which favored formation of the active GTP-bound state. Introduction of missense mutations at KRAS residues analogous to Tyr42 and Leu57 in RHOA did not activate KRAS oncogenic potential, indicating distinct functional effects in otherwise highly related GTPases. Both RHOA mutants stimulated the transcriptional co-activator YAP1 through actin dynamics to promote DGC progression; however, RHOAL57V additionally did so by activating the kinases IGF1R and PAK1, distinct from the FAK-mediated mechanism induced by RHOAY42C. Our results reveal that RHOAL57V and RHOAY42C drive the development of DGC through distinct biochemical and signaling mechanisms.

Mediator Kinase Inhibition Impedes Transcriptional Plasticity and Prevents Resistance to ERK/MAPK-Targeted Therapy in KRAS-Mutant Cancers.

Acquired resistance remains a major challenge for therapies targeting oncogene activated pathways. KRAS is the most frequently mutated oncogene in human cancers, yet strategies targeting its downstream signaling kinases have failed to produce durable treatment responses. Here, we developed multiple models of acquired resistance to dual-mechanism ERK/MAPK inhibitors across KRAS-mutant pancreatic, colorectal, and lung cancers, and then probed the long-term events enabling survival against this class of drugs. These studies revealed that resistance emerges secondary to large-scale transcriptional adaptations that are diverse and cell line-specific. Transcriptional reprogramming extends beyond the well-established early response, and instead represents a dynamic, evolved process that is refined to attain a stably resistant phenotype. Mechanistic and translational studies reveal that resistance to dual-mechanism ERK/MAPK inhibition is broadly susceptible to manipulation of the epigenetic machinery, and that Mediator kinase, in particular, can be co-targeted at a bottleneck point to prevent diverse, cell line-specific resistance programs.

Geographical Variation in Social Determinants of Female Breast Cancer Mortality Across US Counties.

Importance: Breast cancer mortality is complex and traditional approaches that seek to identify determinants of mortality assume that their effects on mortality are stationary across geographic space and scales. Objective: To identify geographic variation in the associations of population demographics, environmental, lifestyle, and health care access with breast cancer mortality at the US county-level. Design, Setting, and Participants: This geospatial cross-sectional study used data from the Surveillance, Epidemiology, and End Results (SEER) database on adult female patients with breast cancer. Statistical and spatial analysis was completed using adjusted mortality rates from 2015 to 2019 for 2176 counties in the US. Data were analyzed July 2022. Exposures: County-level population demographics, environmental, lifestyle, and health care access variables were obtained from open data sources. Main Outcomes and Measures: Model coefficients describing the association between 18 variables and age-adjusted breast cancer mortality rate. Compared with a multivariable linear regression (OLS), multiscale geographically weighted regression (MGWR) relaxed the assumption of spatial stationarity and allowed for the magnitude, direction, and significance of coefficients to change across geographic space. Results: Both OLS and MGWR models agreed that county-level age-adjusted breast cancer mortality rates were significantly positively associated with obesity (OLS: ß, 1.21; 95% CI, 0.88 to 1.54; mean [SD] MGWR: ß, 0.72 [0.02]) and negatively associated with proportion of adults screened via mammograms (OLS: ß, -1.27; 95% CI, -1.70 to -0.84; mean [SD] MGWR: ß, -1.07 [0.16]). Furthermore, the MGWR model revealed that these 2 determinants were associated with a stationary effect on mortality across the US. However, the MGWR model provided important insights on other county-level factors differentially associated with breast cancer mortality across the US. Both models agreed that smoking (OLS: ß, -0.65; 95% CI, -0.98 to -0.32; mean [SD] MGWR: ß, -0.75 [0.92]), food environment index (OLS: ß, -1.35; 95% CI, -1.72 to -0.98; mean [SD] MGWR: ß, -1.69 [0.70]), exercise opportunities (OLS: ß, -0.56; 95% CI, -0.91 to -0.21; mean [SD] MGWR: ß, -0.59 [0.81]), racial segregation (OLS: ß, -0.60; 95% CI, -0.89 to -0.31; mean [SD] MGWR: ß, -0.47 [0.41]), mental health care physician ratio (OLS: ß, -0.93; 95% CI, -1.44 to -0.42; mean [SD] MGWR: ß, -0.48 [0.92]), and primary care physician ratio (OLS: ß, -1.46; 95% CI, -2.13 to -0.79; mean [SD] MGWR: ß, -1.06 [0.57]) were negatively associated with breast cancer mortality, and that light pollution was positively associated (OLS: ß, 0.48; 95% CI, 0.24 to 0.72; mean [SD] MGWR: ß, 0.27 [0.04]). But in the MGWR model, the magnitude of effect sizes and significance varied across geographical regions. Inversely, the OLS model found that disability was not a significant variable for breast cancer mortality, yet the MGWR model found that it was significantly positively associated in some geographical locations. Conclusions and Relevance: This cross-sectional study found that not all social determinants associated with breast cancer mortality are spatially stationary and provides spatially explicit insights for public health practitioners to guide geographically targeted interventions.

Automated Classification of Lung Cancer Subtypes Using Deep Learning and CT-Scan Based Radiomic Analysis.

Artificial intelligence and emerging data science techniques are being leveraged to interpret medical image scans. Traditional image analysis relies on visual interpretation by a trained radiologist, which is time-consuming and can, to some degree, be subjective. The development of reliable, automated diagnostic tools is a key goal of radiomics, a fast-growing research field which combines medical imaging with personalized medicine. Radiomic studies have demonstrated potential for accurate lung cancer diagnoses and prognostications. The practice of delineating the tumor region of interest, known as segmentation, is a key bottleneck in the development of generalized classification models. In this study, the incremental multiple resolution residual network (iMRRN), a publicly available and trained deep learning segmentation model, was applied to automatically segment CT images collected from 355 lung cancer patients included in the dataset "Lung-PET-CT-Dx", obtained from The Cancer Imaging Archive (TCIA), an open-access source for radiological images. We report a failure rate of 4.35% when using the iMRRN to segment tumor lesions within plain CT images in the lung cancer CT dataset. Seven classification algorithms were trained on the extracted radiomic features and tested for their ability to classify different lung cancer subtypes. Over-sampling was used to handle unbalanced data. Chi-square tests revealed the higher order texture features to be the most predictive when classifying lung cancers by subtype. The support vector machine showed the highest accuracy, 92.7% (0.97 AUC), when classifying three histological subtypes of lung cancer: adenocarcinoma, small cell carcinoma, and squamous cell carcinoma. The results demonstrate the potential of AI-based computer-aided diagnostic tools to automatically diagnose subtypes of lung cancer by coupling deep learning image segmentation with supervised classification. Our study demonstrated the integrated application of existing AI techniques in the non-invasive and effective diagnosis of lung cancer subtypes, and also shed light on several practical issues concerning the application of AI in biomedicine.

AKT/mTOR signaling modulates resistance to endocrine therapy and CDK4/6 inhibition in metastatic breast cancers.

Endocrine therapy (ET) in combination with CDK4/6 inhibition is routinely used as first-line treatment for HR+/HER2- metastatic breast cancer (MBC) patients. However, 30-40% of patients quickly develop disease progression. In this open-label multicenter clinical trial, we utilized a hypothesis-driven protein/phosphoprotein-based approach to identify predictive markers of response to ET plus CDK4/6 inhibition in pre-treatment tissue biopsies. Pathway-centered signaling profiles were generated from microdissected tumor epithelia and surrounding stroma/immune cells using the reverse phase protein microarray. Phosphorylation levels of the CDK4/6 downstream substrates Rb (S780) and FoxM1 (T600) were higher in patients with progressive disease (PD) compared to responders (p = 0.02). Systemic PI3K/AKT/mTOR activation in tumor epithelia and stroma/immune cells was detected in patients with PD. This activation was not explained by underpinning genomic alterations alone. As the number of FDA-approved targeted compounds increases, functional protein-based signaling analyses may become a critical component of response prediction and treatment selection for MBC patients.

Combination Therapies with CDK4/6 Inhibitors to Treat KRAS-Mutant Pancreatic Cancer.

Mutational loss of CDKN2A (encoding p16INK4A) tumor-suppressor function is a key genetic step that complements activation of KRAS in promoting the development and malignant growth of pancreatic ductal adenocarcinoma (PDAC). However, pharmacologic restoration of p16INK4A function with inhibitors of CDK4 and CDK6 (CDK4/6) has shown limited clinical efficacy in PDAC. Here, we found that concurrent treatment with both a CDK4/6 inhibitor (CDK4/6i) and an ERK-MAPK inhibitor (ERKi) synergistically suppresses the growth of PDAC cell lines and organoids by cooperatively blocking CDK4/6i-induced compensatory upregulation of ERK, PI3K, antiapoptotic signaling, and MYC expression. On the basis of these findings, a Phase I clinical trial was initiated to evaluate the ERKi ulixertinib in combination with the CDK4/6i palbociclib in patients with advanced PDAC (NCT03454035). As inhibition of other proteins might also counter CDK4/6i-mediated signaling changes to increase cellular CDK4/6i sensitivity, a CRISPR-Cas9 loss-of-function screen was conducted that revealed a spectrum of functionally diverse genes whose loss enhanced CDK4/6i growth inhibitory activity. These genes were enriched around diverse signaling nodes, including cell-cycle regulatory proteins centered on CDK2 activation, PI3K-AKT-mTOR signaling, SRC family kinases, HDAC proteins, autophagy-activating pathways, chromosome regulation and maintenance, and DNA damage and repair pathways. Novel therapeutic combinations were validated using siRNA and small-molecule inhibitor-based approaches. In addition, genes whose loss imparts a survival advantage were identified (e.g., RB1, PTEN, FBXW7), suggesting possible resistance mechanisms to CDK4/6 inhibition. In summary, this study has identified novel combinations with CDK4/6i that may have clinical benefit to patients with PDAC. SIGNIFICANCE: CRISPR-Cas9 screening and protein activity mapping reveal combinations that increase potency of CDK4/6 inhibitors and overcome drug-induced compensations in pancreatic cancer.

Genetically manipulating endogenous Kras levels and oncogenic mutations in vivo influences tissue patterning of murine tumorigenesis.

Despite multiple possible oncogenic mutations in the proto-oncogene KRAS, unique subsets of these mutations are detected in different cancer types. As KRAS mutations occur early, if not being the initiating event, these mutational biases are ostensibly a product of how normal cells respond to the encoded oncoprotein. Oncogenic mutations can impact not only the level of active oncoprotein, but also engagement with proteins. To attempt to separate these two effects, we generated four novel Cre-inducible (LSL) Kras alleles in mice with the biochemically distinct G12D or Q61R mutations and encoded by native (nat) rare or common (com) codons to produce low or high protein levels. While there were similarities, each allele also induced a distinct transcriptional response shortly after activation in vivo. At one end of the spectrum, activating the KrasLSL-natG12D allele induced transcriptional hallmarks suggestive of an expansion of multipotent cells, while at the other end, activating the KrasLSL-comQ61R allele led to hallmarks of hyperproliferation and oncogenic stress. Evidence suggests that these changes may be a product of signaling differences due to increased protein expression as well as the specific mutation. To determine the impact of these distinct responses on RAS mutational patterning in vivo, all four alleles were globally activated, revealing that hematolymphopoietic lesions were permissive to the level of active oncoprotein, squamous tumors were permissive to the G12D mutant, while carcinomas were permissive to both these features. We suggest that different KRAS mutations impart unique signaling properties that are preferentially capable of inducing tumor initiation in a distinct cell-specific manner.

Analysis of neuroendocrine clones in NSCLCs using an immuno-guided laser-capture microdissection-based approach.

Clonal evolution and lineage plasticity are key contributors to tumor heterogeneity and response to treatment in cancer. However, capturing signal transduction events in coexisting clones remains challenging from a technical perspective. In this study, we developed and tested a signal-transduction-based workflow to isolate and profile coexisting clones within a complex cellular system like non-small cell lung cancers (NSCLCs). Cooccurring clones were isolated under immunohistochemical guidance using laser-capture microdissection, and cell signaling activation portraits were measured using the reverse-phase protein microarray. To increase the translational potential of this work and capture druggable vulnerabilities within different clones, we measured expression/activation of a panel of key drug targets and downstream substrates of FDA-approved or investigational agents. We isolated intermixed clones, including poorly represented ones (<5% of cells), within the tumor microecology and identified molecular characteristics uniquely attributable to cancer cells that undergo lineage plasticity and neuroendocrine transdifferentiation in NSCLCs.

Functional and biological heterogeneity of KRASQ61 mutations.

Missense mutations at the three hotspots in the guanosine triphosphatase (GTPase) RAS-Gly12, Gly13, and Gln61 (commonly known as G12, G13, and Q61, respectively)-occur differentially among the three RAS isoforms. Q61 mutations in KRAS are infrequent and differ markedly in occurrence. Q61H is the predominant mutant (at 57%), followed by Q61R/L/K (collectively 40%), and Q61P and Q61E are the rarest (2 and 1%, respectively). Probability analysis suggested that mutational susceptibility to different DNA base changes cannot account for this distribution. Therefore, we investigated whether these frequencies might be explained by differences in the biochemical, structural, and biological properties of KRASQ61 mutants. Expression of KRASQ61 mutants in NIH 3T3 fibroblasts and RIE-1 epithelial cells caused various alterations in morphology, growth transformation, effector signaling, and metabolism. The relatively rare KRASQ61E mutant stimulated actin stress fiber formation, a phenotype distinct from that of KRASQ61H/R/L/P, which disrupted actin cytoskeletal organization. The crystal structure of KRASQ61E was unexpectedly similar to that of wild-type KRAS, a potential basis for its weak oncogenicity. KRASQ61H/L/R-mutant pancreatic ductal adenocarcinoma (PDAC) cell lines exhibited KRAS-dependent growth and, as observed with KRASG12-mutant PDAC, were susceptible to concurrent inhibition of ERK-MAPK signaling and of autophagy. Our results uncover phenotypic heterogeneity among KRASQ61 mutants and support the potential utility of therapeutic strategies that target KRASQ61 mutant-specific signaling and cellular output.

P2RY2-AKT activation is a therapeutically actionable consequence of XPO1 inhibition in acute myeloid leukemia.

Selinexor is a first-in-class inhibitor of the nuclear exportin XPO1 that was recently approved by the US Food and Drug Administration for the treatment of multiple myeloma and diffuse large B-cell lymphoma. In relapsed/refractory acute myeloid leukemia (AML), selinexor has shown promising activity, suggesting that selinexor-based combination therapies may have clinical potential. Here, motivated by the hypothesis that selinexor's nuclear sequestration of diverse substrates imposes pleiotropic fitness effects on AML cells, we systematically catalog the pro- and anti-fitness consequences of selinexor treatment. We discover that selinexor activates PI3Kγ-dependent AKT signaling in AML by upregulating the purinergic receptor P2RY2. Inhibiting this axis potentiates the anti-leukemic effects of selinexor in AML cell lines, patient-derived primary cultures and multiple mouse models of AML. In a syngeneic, MLL-AF9-driven mouse model of AML, treatment with selinexor and ipatasertib outperforms both standard-of-care chemotherapy and chemotherapy with selinexor. Together, these findings establish drug-induced P2RY2-AKT signaling as an actionable consequence of XPO1 inhibition in AML.