Capivasertib combines with docetaxel to enhance anti-tumour activity through inhibition of AKT-mediated survival mechanisms in prostate cancer.

BACKGROUND/OBJECTIVE: To explore the anti-tumour activity of combining AKT inhibition and docetaxel in PTEN protein null and WT prostate tumours. METHODS: Mechanisms associated with docetaxel capivasertib treatment activity in prostate cancer were examined using a panel of in vivo tumour models and cell lines. RESULTS: Combining docetaxel and capivasertib had increased activity in PTEN null and WT prostate tumour models in vivo. In vitro short-term docetaxel treatment caused cell cycle arrest in the majority of cells. However, a sub-population of docetaxel-persister cells did not undergo G2/M arrest but upregulated phosphorylation of PI3K/AKT pathway effectors GSK3ß, p70S6K, 4E-BP1, but to a lesser extent AKT. In vivo acute docetaxel treatment induced p70S6K and 4E-BP1 phosphorylation. Treating PTEN null and WT docetaxel-persister cells with capivasertib reduced PI3K/AKT pathway activation and cell cycle progression. In vitro and in vivo it reduced proliferation and increased apoptosis or DNA damage though effects were more marked in PTEN null cells. Docetaxel-persister cells were partly reliant on GSK3ß as a GSK3ß inhibitor AZD2858 reversed capivasertib-induced apoptosis and DNA damage. CONCLUSION: Capivasertib can enhance anti-tumour effects of docetaxel by targeting residual docetaxel-persister cells, independent of PTEN status, to induce apoptosis and DNA damage in part through GSK3ß.

Population Pharmacokinetics of Capivasertib in Patients with Advanced or Metastatic Solid Tumours.

BACKGROUND AND OBJECTIVE: Overactivation of the PI3K/AKT pathway can occur in many cancers. Capivasertib is a potent, selective pan-AKT inhibitor. The objectives of this analysis were to develop a population pharmacokinetic model for capivasertib and to quantitatively assess the impact of intrinsic and extrinsic factors on the pharmacokinetics of capivasertib. METHODS: Pharmacokinetic data from four phase I and II studies were combined. Capivasertib was administered orally at a dose range of 80-800 mg twice daily over 28-day and 21-day cycles as monotherapy or in combination with paclitaxel or fulvestrant, using continuous dosing or one of two intermittent dosing schedules: either 4 days on, 3 days off (4/3) or 2 days on, 5 days off (2/5). Several models and approaches were tested for their ability to describe capivasertib disposition. The covariates assessed included dose, schedule, age, body weight, race, sex, creatinine clearance, hepatic function, renal function, smoking status, food effect, formulation, and concomitant use with paclitaxel, fulvestrant, cytochrome P450, family 3, subfamily A (CYP3A) inducers, CYP3A inhibitors and acid-reducing agents. RESULTS: A total of 3963 capivasertib plasma concentrations from 441 patients were included. Capivasertib pharmacokinetics was adequately described by a three-compartment model where the apparent clearance (CL/F) presented a moderate time-dependent and dose-dependent clearance. Following oral administration of multiple doses of capivasertib (400 mg twice daily; [4/3]), the initial CL/F was 62.2 L/h (between-subject variability 39.3%), and after approximately 120 hours, CL/F decreased by 18%. The effective half-life was 8.34 h. Steady state was predicted to be reached on every third and fourth dosing day each week from the second week with exposure levels that produced robust inhibition of AKT but not of other related kinases. The area under the plasma concentration-time curve and maximum plasma concentration of capivasertib were proportional between the dose levels of 80-480 mg after multiple doses but more than proportional beyond 480 mg. Schedule, age, race, sex, creatinine clearance, hepatic function, renal function, smoking status and concomitant use with fulvestrant, CYP3A inducers, CYP3A inhibitors or acid-reducing agents were not significant covariates for capivasertib pharmacokinetics. Concomitant use of paclitaxel, food effect and formulation statistically significantly affected capivasertib pharmacokinetics, but the effect was low. Body weight was statistically significantly related to capivasertib CL/F, with a 12% reduction in CL/F at steady state and a 14% increase in the area under the curve for 12 hours at steady state and maximum concentration at steady state at a lower body weight (47 kg vs 67 kg reference). CONCLUSIONS: Capivasertib pharmacokinetics showed moderate between-subject variability, and most covariates assessed had no significant impact. Body weight, dose, concomitant use of paclitaxel, food effect and formulation showed statistically significant effects. However, these were predicted to impact exposure to capivasertib by <20% and were not expected to be clinically relevant. Based on the population pharmacokinetics, no a priori dose adjustment is needed for intrinsic and extrinsic factors.

Accelerating Drug Development Using Spatial Multi-omics.

SUMMARY: Spatial biology approaches enabled by innovations in imaging biomarker platforms and artificial intelligence-enabled data integration and analysis provide an assessment of patient and disease heterogeneity at ever-increasing resolution. The utility of spatial biology data in accelerating drug programs, however, requires balancing exploratory discovery investigations against scalable and clinically applicable spatial biomarker analysis.

Overcoming osimertinib resistance with AKT inhibition in EGFRm-driven Non-Small-Cell-Lung-Cancer with PIK3CA/PTEN alterations.

PURPOSE: Osimertinib is an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) indicated for the treatment of EGFR mutated (EGFRm)-driven lung adenocarcinomas. Osimertinib significantly improves progression-free survival in first-line treated patients with EGFRm advanced NSCLC. Despite the durable disease control, the majority of patients receiving osimertinib eventually develop disease progression. EXPERIMENTAL DESIGN: ctDNA profiling analysis on-progression plasma samples from patients treated with osimertinib in both first (Phase 3, FLAURA trial) and second-line trials (Phase 3, AURA3 trial) revealed a high prevalence of PIK3CA/AKT/PTEN alterations. In vitro and in vivo evidence using CRISPR engineered NSCLC cell lines and PXD models support a functional role for PIK3CA and PTEN mutations in the development of osimertinib resistance. RESULTS: These alterations are functionally relevant as EGFRm NSCLC cells with engineered PIK3CA/AKT/PTEN alterations develop resistance to osimertinib and can be re-sensitized by treatment with the combination of osimertinib and the AKT inhibitor capivasertib. Moreover, xenograft and PDX in vivo models with PIK3CA/AKT/PTEN alterations display limited sensitivity to osimertinib relative to models without alteration, and in these double mutant models capivasertib and osimertinib combination elicits an improved anti-tumor effect versus osimertinib alone. CONCLUSIONS: Together, this approach offers a potential treatment strategy for patients with EGFRm-driven NSCLC that have a sub-optimal response, or develop resistance, to osimertinib through PIK3CA/AKT/PTEN alterations.

Morphological and molecular preservation through universal preparation of fresh-frozen tissue samples for multimodal imaging workflows.

The landscape of tissue-based imaging modalities is constantly and rapidly evolving. While formalin-fixed, paraffin-embedded material is still useful for histological imaging, the fixation process irreversibly changes the molecular composition of the sample. Therefore, many imaging approaches require fresh-frozen material to get meaningful results. This is particularly true for molecular imaging techniques such as mass spectrometry imaging, which are widely used to probe the spatial arrangement of the tissue metabolome. As high-quality fresh-frozen tissues are limited in their availability, any sample preparation workflow they are subjected to needs to ensure morphological and molecular preservation of the tissues and be compatible with as many of the established and emerging imaging techniques as possible to obtain the maximum possible insights from the tissues. Here we describe a universal sample preparation workflow, from the initial step of freezing the tissues to the cold embedding in a new hydroxypropyl methylcellulose/polyvinylpyrrolidone-enriched hydrogel and the generation of thin tissue sections for analysis. Moreover, we highlight the optimized storage conditions that limit molecular and morphological degradation of the sections. The protocol is compatible with human and plant tissues and can be easily adapted for the preparation of alternative sample formats (e.g., three-dimensional cell cultures). The integrated workflow is universally compatible with histological tissue analysis, mass spectrometry imaging and imaging mass cytometry, as well as spatial proteomic, genomic and transcriptomic tissue analysis. The protocol can be completed within 4 h and requires minimal prior experience in the preparation of tissue samples for multimodal imaging experiments.

Multiomic profiling of breast cancer cells uncovers stress MAPK-associated sensitivity to AKT degradation.

More than 50% of human tumors display hyperactivation of the serine/threonine kinase AKT. Despite evidence of clinical efficacy, the therapeutic window of the current generation of AKT inhibitors could be improved. Here, we report the development of a second-generation AKT degrader, INY-05-040, which outperformed catalytic AKT inhibition with respect to cellular suppression of AKT-dependent phenotypes in breast cancer cell lines. A growth inhibition screen with 288 cancer cell lines confirmed that INY-05-040 had a substantially higher potency than our first-generation AKT degrader (INY-03-041), with both compounds outperforming catalytic AKT inhibition by GDC-0068. Using multiomic profiling and causal network integration in breast cancer cells, we demonstrated that the enhanced efficacy of INY-05-040 was associated with sustained suppression of AKT signaling, which was followed by induction of the stress mitogen-activated protein kinase (MAPK) c-Jun N-terminal kinase (JNK). Further integration of growth inhibition assays with publicly available transcriptomic, proteomic, and reverse phase protein array (RPPA) measurements established low basal JNK signaling as a biomarker for breast cancer sensitivity to AKT degradation. Together, our study presents a framework for mapping the network-wide signaling effects of therapeutically relevant compounds and identifies INY-05-040 as a potent pharmacological suppressor of AKT signaling.

Metabolic imaging across scales reveals distinct prostate cancer phenotypes.

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.

Targeting Cholesterol Biosynthesis with Statins Synergizes with AKT Inhibitors in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is responsible for a disproportionate number of breast cancer patient deaths due to extensive molecular heterogeneity, high recurrence rates and lack of targeted therapies. Dysregulation of the phosphoinositide 3-kinase (PI3K)/AKT pathway occurs in approximately 50% of TNBC patients. Here, we performed a genome-wide CRISPR/Cas9 screen with PI3Kα and AKT inhibitors to find targetable synthetic lethalities in TNBC. Cholesterol homeostasis was identified as a collateral vulnerability with AKT inhibition. Disruption of cholesterol homeostasis with pitavastatin synergized with AKT inhibition to induce TNBC cytotoxicity in vitro, in mouse TNBC xenografts and in patient-derived, estrogen receptor (ER)-negative breast cancer organoids. Neither ER-positive breast cancer cell lines nor ER-positive organoids were sensitive to combined AKT inhibitor and pitavastatin. Mechanistically, TNBC cells showed impaired sterol regulatory element-binding protein 2 (SREBP-2) activation in response to single agent or combination treatment with AKT inhibitor and pitavastatin, which was rescued by inhibition of the cholesterol trafficking protein Niemann-Pick C1 (NPC1). NPC1 loss caused lysosomal cholesterol accumulation, decreased endoplasmic reticulum cholesterol levels, and promoted SREBP-2 activation. Taken together, these data identify a TNBC-specific vulnerability to the combination of AKT inhibitors and pitavastatin mediated by dysregulated cholesterol trafficking. These findings support combining AKT inhibitors with pitavastatin as a therapeutic modality in TNBC. .

Histopathological biomarkers for predicting the tumour accumulation of nanomedicines.

The clinical prospects of cancer nanomedicines depend on effective patient stratification. Here we report the identification of predictive biomarkers of the accumulation of nanomedicines in tumour tissue. By using supervised machine learning on data of the accumulation of nanomedicines in tumour models in mice, we identified the densities of blood vessels and of tumour-associated macrophages as key predictive features. On the basis of these two features, we derived a biomarker score correlating with the concentration of liposomal doxorubicin in tumours and validated it in three syngeneic tumour models in immunocompetent mice and in four cell-line-derived and six patient-derived tumour xenografts in mice. The score effectively discriminated tumours according to the accumulation of nanomedicines (high versus low), with an area under the receiver operating characteristic curve of 0.91. Histopathological assessment of 30 tumour specimens from patients and of 28 corresponding primary tumour biopsies confirmed the score's effectiveness in predicting the tumour accumulation of liposomal doxorubicin. Biomarkers of the tumour accumulation of nanomedicines may aid the stratification of patients in clinical trials of cancer nanomedicines.

Biomarker-directed targeted therapy plus durvalumab in advanced non-small-cell lung cancer: a phase 2 umbrella trial.

For patients with non-small-cell lung cancer (NSCLC) tumors without currently targetable molecular alterations, standard-of-care treatment is immunotherapy with anti-PD-(L)1 checkpoint inhibitors, alone or with platinum-doublet therapy. However, not all patients derive durable benefit and resistance to immune checkpoint blockade is common. Understanding mechanisms of resistance-which can include defects in DNA damage response and repair pathways, alterations or functional mutations in STK11/LKB1, alterations in antigen-presentation pathways, and immunosuppressive cellular subsets within the tumor microenvironment-and developing effective therapies to overcome them, remains an unmet need. Here the phase 2 umbrella HUDSON study evaluated rational combination regimens for advanced NSCLC following failure of anti-PD-(L)1-containing immunotherapy and platinum-doublet therapy. A total of 268 patients received durvalumab (anti-PD-L1 monoclonal antibody)-ceralasertib (ATR kinase inhibitor), durvalumab-olaparib (PARP inhibitor), durvalumab-danvatirsen (STAT3 antisense oligonucleotide) or durvalumab-oleclumab (anti-CD73 monoclonal antibody). Greatest clinical benefit was observed with durvalumab-ceralasertib; objective response rate (primary outcome) was 13.9% (11/79) versus 2.6% (5/189) with other regimens, pooled, median progression-free survival (secondary outcome) was 5.8 (80% confidence interval 4.6-7.4) versus 2.7 (1.8-2.8) months, and median overall survival (secondary outcome) was 17.4 (14.1-20.3) versus 9.4 (7.5-10.6) months. Benefit with durvalumab-ceralasertib was consistent across known immunotherapy-refractory subgroups. In ATM-altered patients hypothesized to harbor vulnerability to ATR inhibition, objective response rate was 26.1% (6/23) and median progression-free survival/median overall survival were 8.4/22.8 months. Durvalumab-ceralasertib safety/tolerability profile was manageable. Biomarker analyses suggested that anti-PD-L1/ATR inhibition induced immune changes that reinvigorated antitumor immunity. Durvalumab-ceralasertib is under further investigation in immunotherapy-refractory NSCLC.ClinicalTrials.gov identifier: NCT03334617.

Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations.

Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific "emergent" biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets. SIGNIFICANCE: We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of "emergent" combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses. This article is featured in Selected Articles from This Issue, p. 695.