Image-based ex-vivo drug screening for patients with aggressive haematological malignancies: interim results from a single-arm, open-label, pilot study

Lymphoma and Leukemia Cell Vulnerabilities and Resistance Identified by Compound Library Screens

Response to anticancer agents is often restricted to subsets of patients. Recognition of factors underlying this heterogeneity and identification of biomarkers associated with response to drugs would greatly improve the efficacy of drug treatment. Platforms that can comprehensively map cellular response to compounds in high-throughput provide a unique tool to identify associated biomarkers and provide hypotheses for mechanisms underlying variable response. Such screens can be performed on cell lines and short-term cultures of primary cells to take advantage of the respective models' strength, which include, e.g., the ability to silence genes or introduce somatic mutations to cell lines. Cohorts of patient samples represent the natural diversity of cancers, including rarer mutations and combinatorial patterns of mutations that are often absent from existing cell lines. We here summarize a simple and scalable method for the measurement of viability after drug exposure based on ATP measurements as a surrogate for viability, which we use to measure and understand drug response in cell lines and primary cells.

Functional, patient-derived 3D tri-culture models of the uterine wall in a microfluidic array

STUDY QUESTION

Can a functional in vitro model, containing the main cellular components of the uterine wall, be generated from cells derived from patient tissues?

SUMMARY ANSWER

We present a three-dimensional (3D) physiologically relevant, organ-on-a-chip model of the uterine wall containing primary endometrial and myometrial cellular participants, generated from human uterine tissue.

WHAT IS KNOWN ALREADY

As a highly dynamic reproductive organ, the human uterus plays fundamental physiological roles in menstruation and childbirth. The endometrial-myometrial junction (EMJ) defines the interface between the inner mucosal layer (endometrium) and outer smooth muscle zone (myometrium) that comprises the uterine wall. The EMJ is implicit in several uterine pathologies of unknown aetiology, including adenomyosis and abnormally invasive placenta; however, despite this, no patient-derived in vitro models of the uterine wall containing all EMJ participants currently exist.

STUDY DESIGN, SIZE, DURATION

We employed microfluidic technology to characterize multiple miniaturized models of the uterine wall. Protocols were tested that included variations in the seeding order of endometrial and myometrial fractions, and the addition of a low viscosity extracellular matrix to influence cell behaviour. Ultimately, functional hormone responses of patient-derived uterine wall models were assessed.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Endometrial (n = 9) and myometrial biopsies (n = 4) were enzymatically dissociated to create epithelial, stromal and myometrial cellular fractions. Cell suspensions were seeded into non-adhesive poly(dimethylsiloxane) microfluidic devices containing 5 × 5 microwell arrays. The fate of individual cell types was monitored in real-time using fluorescent tracers, and cell phenotype was characterized by immunocytochemistry. Model functionality was assessed by measuring Ca2+ responses to agonist stimulation, and both insulin-like growth factor binding protein 1 (IGFBP-1) and osteopontin secretion in response to hormone stimulation.

MAIN RESULTS AND THE ROLE OF CHANCE

When subjected to microfluidic culture in isolation, endometrial stromal cells and smooth muscle myocytes formed compact spheroids, whilst epithelial cells produced diffuse aggregates. Tri-cultures were established by sequential seeding of individual or combined cell fractions at various ratios. Regardless of the protocol, epithelial cells localized to the outer periphery of tri-culture spheroids, which varied in morphology across the protocols. Incorporation of 5% [v/v] Matrigel® improved the reproducibility of 3D aggregates which exhibited robust self-assembly of a stromal/smooth muscle core encased in epithelium. Exposure of tri-cultures to oestradiol, medroxyprogesterone acetate and cyclic adenosine monophosphate (cAMP) increased secretion of IGFBP-1, which indicates stromal decidualization, and enhanced epithelial cell osteopontin secretion. Stimulation with endothelin-1 induced Ca2+ signalling in myocytes.

LIMITATIONS, REASONS FOR CAUTION

Endometrial and myometrial tissue was collected from relatively few donors. Myometrial tissue was collected from pregnant donors, which may have influenced the myocyte phenotype. Furthermore, endometrial tissue sampling was from women not having a hysterectomy, thus may not include the deeper basalis region, which may limit the physiological mimicry of the final models.

WIDER IMPLICATIONS OF THE FINDINGS

Our novel approach to modelling the uterine wall in 3D captures all of the main cell types in a medium-throughput system, enabling the screening of hundreds of cultures in parallel from a single biopsy. This system shows great promise for examining the cellular interplay between physiological cues and EMJ pathologies, such as the impact of uterine peristalsis and cyclical hormones on the pathogenesis of adenomyosis.

STUDY FUNDING/COMPETING INTEREST(S)

C.B. was supported by an Organ-on-a-Chip Technologies Network Pump Priming Project grant. C.J.H. was supported by a Wellbeing of Women project grant (RG2137), SRI/Bayer and Wellcome Trust IFFS3. D.K.H. was supported by a Wellbeing of Women project grant (RG2137) and MRC clinical research training fellowship (MR/V007238/1). M.Z. is Director and Co-Founder of ScreenIn3D Limited. The other authors declare no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

High-throughput identification of repurposable neuroactive drugs with potent anti-glioblastoma activity

Glioblastoma, the most aggressive primary brain cancer, has a dismal prognosis, yet systemic treatment is limited to DNA-alkylating chemotherapies. New therapeutic strategies may emerge from exploring neurodevelopmental and neurophysiological vulnerabilities of glioblastoma. To this end, we systematically screened repurposable neuroactive drugs in glioblastoma patient surgery material using a clinically concordant and single-cell resolved platform. Profiling more than 2,500 ex vivo drug responses across 27 patients and 132 drugs identified class-diverse neuroactive drugs with potent anti-glioblastoma efficacy that were validated across model systems. Interpretable molecular machine learning of drug-target networks revealed neuroactive convergence on AP-1/BTG-driven glioblastoma suppression, enabling expanded in silico screening of more than 1 million compounds with high patient validation accuracy. Deep multimodal profiling confirmed Ca2+-driven AP-1/BTG-pathway induction as a neuro-oncological glioblastoma vulnerability, epitomized by the anti-depressant vortioxetine synergizing with current standard-of-care chemotherapies in vivo. These findings establish an actionable framework for glioblastoma treatment rooted in its neural etiology.

Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia

Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine single-cell ex vivo drug profiling (pharmacoscopy) with single-cell and bulk DNA, RNA, and protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised data integration reveals reduced ex vivo response to the Bcl-2 inhibitor venetoclax (VEN) in patients treated with both a hypomethylating agent (HMA) and VEN, compared to those pre-exposed to chemotherapy or HMA alone. Integrative analysis identifies both known and unreported mechanisms of innate and treatment-related VEN resistance and suggests alternative treatments, like targeting increased proliferation with the PLK inhibitor volasertib. Additionally, high CD36 expression in VEN-resistant blasts associates with sensitivity to CD36-targeted antibody treatment ex vivo. This study demonstrates how single-cell multi-omic profiling can uncover drug resistance mechanisms and treatment vulnerabilities, providing a valuable resource for future AML research.

Distinct molecular profiles and shared drug vulnerabilities in pancreatic metastases of renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is the most common origin of pancreatic metastases (PM). Distinct genomic aberrations, favorable prognosis, and clinical observations on high angiogenesis, and succeeding tyrosine kinase inhibitor (TKI) sensitivity have been reported in PM-ccRCC. However, no functional or single-cell studies have been conducted thus far. We recruited five PM-ccRCC patients and investigated the genomic, single-cell transcriptomic, and drug sensitivity profiles of their patient-derived cells (PDCs). The PM depicted both expected and novel genomic alterations. Further, the transcriptomics differed from both primary and metastatic ccRCC, with upregulations of the PI3K/mTOR and - supporting the clinical observations - angiogenesis pathways. Data integration at pathway level showed that transcriptomics explained drug sensitivities the best. Accordingly, PM-ccRCC PDCs shared sensitivity to many PI3K/mTOR inhibitors. Altogether, we show distinct genomic and transcriptomic signatures in PM-ccRCC, highlight the superiority of transcriptomics in interpreting drug sensitivities, and encourage the use of TKIs and PI3K/mTOR inhibitors in PM-ccRCC.

Molecular and functional landscape of malignant serous effusions for precision oncology

Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells from patient biopsies. Here, we comprehensively characterize a pan-cancer cohort of 150 malignant serous effusion (MSE) samples at the cellular, molecular, and functional level. We find that MSE-derived cancer cells retain the genomic and transcriptomic profiles of their corresponding primary tumors, validating their use as a patient-relevant model system for solid tumor biology. Integrative analyses reveal that baseline gene expression patterns relate to global ex vivo drug sensitivity, while high-throughput drug-induced transcriptional changes in MSE samples are indicative of drug mode of action and acquired treatment resistance. A case study exemplifies the added value of multi-modal MSE profiling for patients who lack genetically stratified treatment options. In summary, our study provides a functional multi-omics view on a pan-cancer solid tumor cohort and underlines the feasibility and utility of MSE-based precision oncology.

In-vitro assays for immuno-oncology drug efficacy assessment and screening for personalized cancer therapy: scopes and challenges

INTRODUCTION

Immunotherapies have revolutionized cancer treatment, but often fail to produce desirable therapeutic outcomes in all patients. Due to the inter-patient heterogeneity and complexity of the tumor microenvironment, personalized treatment approaches are gaining demand. Researchers have long been using a range of in-vitro assays including 2D models, organoid co-cultures, and cancer-on-a-chip platforms for cancer drug screening. A comparative analysis of these assays with their suitability, high-throughput capacity, and clinical translatability is required for optimal translational use.

AREAS COVERED

The review summarized in-vitro platforms with their comparative advantages and limitations including construction strategies, and translational potential for immuno-oncology drug efficacy assessment. We also discussed end-point analysis strategies so that researchers can contextualize their usefulness and optimally design experiments for personalized immunotherapy efficacy prediction.

EXPERT OPINION

Researchers developed several in-vitro platforms that can provide information on personalized immunotherapy efficacy from different angles. Image-based assays are undoubtedly more suitable to gather a wide range of information including cellular morphology and phenotypical behaviors but need significant improvement to overcome issues including background noise, sample preparation difficulty, and long duration of experiment. More studies and clinical trials are needed to resolve these issues and validate the assays before they can be used in real-life scenarios.

A platform for rapid patient-derived cutaneous neurofibroma organoid establishment and screening

Localized cutaneous neurofibromas (cNFs) are benign tumors that arise in the dermis of patients affected by neurofibromatosis type 1 syndrome. cNFs are benign lesions: they do not undergo malignant transformation or metastasize. Nevertheless, they can cover a significant proportion of the body, with some individuals developing hundreds to thousands of lesions. cNFs can cause pain, itching, and disfigurement resulting in substantial socio-emotional repercussions. Currently, surgery and laser desiccation are the sole treatment options but may result in scarring and potential regrowth from incomplete removal. To identify effective systemic therapies, we introduce an approach to establish and screen cNF organoids. We optimized conditions to support the ex vivo growth of genomically diverse cNFs. Patient-derived cNF organoids closely recapitulate cellular and molecular features of parental tumors as measured by immunohistopathology, methylation, RNA sequencing, and flow cytometry. Our cNF organoid platform enables rapid screening of hundreds of compounds in a patient- and tumor-specific manner.

Myelomonocytic and monocytic acute myeloid leukemia demonstrate comparable poor outcomes with venetoclax-based treatment: a monocentric real-world study

Venetoclax (VEN), a BCL-2 inhibitor, has transformed treatment strategies for elderly and unfit acute myeloid leukemia (AML) patients by significantly improving response rates and survival. However, the predictive factors for VEN efficacy differ from traditional chemotherapy. The clinical relevance of the FAB (French-American-British) monocytic subtype, including M4 and M5, has been debated as a marker for VEN resistance. This real-world study examined 162 newly diagnosed (ND) and 85 relapsed/refractory (R/R) AML patients who received VEN-based therapy at West China Hospital, Sichuan University, from January 2019 to January 2023. We retrospectively collected clinical and treatment data from electronic medical records. The median age of the cohort was 55.5 years (range: 16.5-83.5). The composite complete remission (cCR) rate in the entire cohort was 60.7%. Specifically, among newly diagnosed (ND) patients, FAB monocytic subtypes exhibited lower cCR compared to non-monocytic subtypes (55.1% vs. 76.3%, P = 0.007). Additionally, there were no significant differences observed between M4 and M5 subtypes, both in the ND group (61.7% vs. 40.9%, p = 0.17) and the R/R group (38.2% vs. 40%, p > 0.9). Furthermore, the median follow-up was 238 (range: 7-1120) days. ND patients with monocytic subtypes had shorter overall survival compared to non-monocytic subtypes (295 days vs. not reached, p = 0.0017). Conversely, R/R patients showed no such difference (204 vs. 266 days, p = 0.72). In summary, our study suggests that the FAB monocytic subtype can predict VEN resistance and shorter survival in ND AML patients. Moreover, there is no significant distinction between M4 and M5 subtypes.

Feasibility of functional precision medicine for guiding treatment of relapsed or refractory pediatric cancers

Children with rare, relapsed or refractory cancers often face limited treatment options, and few predictive biomarkers are available that can enable personalized treatment recommendations. The implementation of functional precision medicine (FPM), which combines genomic profiling with drug sensitivity testing (DST) of patient-derived tumor cells, has potential to identify treatment options when standard-of-care is exhausted. The goal of this prospective observational study was to generate FPM data for pediatric patients with relapsed or refractory cancer. The primary objective was to determine the feasibility of returning FPM-based treatment recommendations in real time to the FPM tumor board (FPMTB) within a clinically actionable timeframe (<4 weeks). The secondary objective was to assess clinical outcomes from patients enrolled in the study. Twenty-five patients with relapsed or refractory solid and hematological cancers were enrolled; 21 patients underwent DST and 20 also completed genomic profiling. Median turnaround times for DST and genomics were within 10 days and 27 days, respectively. Treatment recommendations were made for 19 patients (76%), of whom 14 received therapeutic interventions. Six patients received subsequent FPM-guided treatments. Among these patients, five (83%) experienced a greater than 1.3-fold improvement in progression-free survival associated with their FPM-guided therapy relative to their previous therapy, and demonstrated a significant increase in progression-free survival and objective response rate compared to those of eight non-guided patients. The findings from our proof-of-principle study illustrate the potential for FPM to positively impact clinical care for pediatric and adolescent patients with relapsed or refractory cancers and warrant further validation in large prospective studies. ClinicalTrials.gov registration: NCT03860376 .

Ex-vivo drug screening of surgically resected glioma stem cells to replace murine avatars and provide personalise cancer therapy for glioblastoma patients

With diminishing returns and high clinical failure rates from traditional preclinical and animal-based drug discovery strategies, more emphasis is being placed on alternative drug discovery platforms. Ex vivo approaches represent a departure from both more traditional preclinical animal-based models and clinical-based strategies and aim to address intra-tumoural and inter-patient variability at an earlier stage of drug discovery. Additionally, these approaches could also offer precise treatment stratification for patients within a week of tumour resection in order to direct tailored therapy. One tumour group that could significantly benefit from such ex vivo approaches are high-grade gliomas, which exhibit extensive heterogeneity, cellular plasticity and therapy-resistant glioma stem cell (GSC) niches. Historic use of murine-based preclinical models for these tumours has largely failed to generate new therapies, resulting in relatively stagnant and unacceptable survival rates of around 12-15 months post-diagnosis over the last 50 years. The near universal use of DNA damaging chemoradiotherapy after surgical resection within standard-of-care (SoC) therapy regimens provides an opportunity to improve current treatments if we can identify efficient drug combinations in preclinical models that better reflect the complex inter-/intra-tumour heterogeneity, GSC plasticity and inherent DNA damage resistance mechanisms. We have therefore developed and optimised a high-throughput ex vivo drug screening platform; GliExP, which maintains GSC populations using immediately dissociated fresh surgical tissue. As a proof-of-concept for GliExP, we have optimised SoC therapy responses and screened 30+ small molecule therapeutics and preclinical compounds against tumours from 18 different patients, including multi-region spatial heterogeneity sampling from several individual tumours. Our data therefore provides a strong basis to build upon GliExP to incorporate combination-based oncology therapeutics in tandem with SoC therapies as an important preclinical alternative to murine models (reduction and replacement) to triage experimental therapeutics for clinical translation and deliver rapid identification of effective treatment strategies for individual gliomas.

Preclinical Characterization of the Anti-Leukemia Activity of the CD33/CD16a/NKG2D Immune-Modulating TriNKET® CC-96191

Increasing efforts are focusing on natural killer (NK) cell immunotherapies for AML. Here, we characterized CC-96191, a novel CD33/CD16a/NKG2D immune-modulating TriNKET®. CC-96191 simultaneously binds CD33, NKG2D, and CD16a, with NKG2D and CD16a co-engagement increasing the avidity for, and activation of, NK cells. CC-96191 was broadly active against human leukemia cells in a strictly CD33-dependent manner, with maximal efficacy requiring the co-engagement of CD16a and NKG2D. A frequent CD33 single nucleotide polymorphism, R69G, reduced CC-96191 potency but not maximal activity, likely because of reduced CD33 binding. Similarly, the potency, but not the maximal activity, of CC-96191 was reduced by high concentrations of soluble CD33; in contrast, the soluble form of the NKG2D ligand MICA did not impact activity. In the presence of CD33+ AML cells, CC-96191 activated NK cells but not T cells; while maximum anti-AML efficacy was similar, soluble cytokine levels were 10- to >100-fold lower than with a CD33/CD3 bispecific antibody. While CC-96191-mediated cytolysis was not affected by ABC transporter proteins, it was reduced by anti-apoptotic BCL-2 family proteins. Finally, in patient marrow specimens, CC-96191 eliminated AML cells but not normal monocytes, suggesting selectivity of TriNKET-induced cytotoxicity toward neoplastic cells. Together, these findings support the clinical exploration of CC-96191 as in NCT04789655.

Delineating functional and molecular impact of ex vivo sample handling in precision medicine

Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.

A New Microfluidic Device to Facilitate Functional Precision Medicine Assays

Functional precision medicine (FPM) has emerged as a new approach to improve cancer treatment. Despite its potential, FPM assays present important limitations such as the number of cells and trained personnel required. To overcome these impediments, here we describe a novel microfluidic platform that can be used to perform FPM assays, optimizing the use of primary cancer cells and simplifying the process by using microfluidics to automatize the process.

Cellular Mass Response to Therapy Correlates With Clinical Response for a Range of Malignancies

PURPOSE

Cancer patients with advanced-stage disease have poor prognosis, typically having limited options for efficacious treatment, and genomics-based therapy guidance continues to benefit only a fraction of patients. Next-generation ex vivo approaches, such as cell mass-based response testing (MRT), offer an alternative precision medicine approach for a broader population of patients with cancer, but validation of clinical feasibility and potential impact remain necessary.

MATERIALS AND METHODS

We evaluated the clinical feasibility and accuracy of using live-cell MRT to predict patient drug sensitivity. Using a unified measurement workflow with a 48-hour result turnaround time, samples were subjected to MRT after treatment with a panel of drugs in vitro. After completion of therapeutic course, clinical response data were correlated with MRT-based predictions of outcome. Specimens were collected from 104 patients with solid (n = 69) and hematologic (n = 35) malignancies, using tissue formats including needle biopsies, malignant fluids, bone marrow aspirates, and blood samples. Of the 81 (78%) specimens qualified for MRT, 41 (51%) patients receiving physician-selected therapies had treatments matched to MRT.

RESULTS

MRT demonstrated high concordance with clinical responses with an odds ratio (OR) of 14.80 (P = .0003 [95% CI, 2.83 to 102.9]). This performance held for both solid and hematologic malignances with ORs of 20.67 (P = .0128 [95% CI, 1.45 to 1,375.57]) and 8.20 (P = .045 [95% CI, 0.77 to 133.56]), respectively. Overall, these results had a predictive accuracy of 80% (P = .0026 [95% CI, 65 to 91]).

CONCLUSION

MRT showed highly significant correlation with clinical response to therapy. Routine clinical use is technically feasible and broadly applicable to a wide range of samples and malignancy types, supporting the need for future validation studies.

PI3Kδ Inhibition Potentiates Glucocorticoids in B-lymphoblastic Leukemia by Decreasing Receptor Phosphorylation and Enhancing Gene Regulation

Glucocorticoids are the cornerstone of B-lymphoblastic leukemia (B-ALL) therapy. Because response to glucocorticoids alone predicts overall outcomes for B-ALL, enhancing glucocorticoid potency should improve treatment. We previously showed that inhibition of the lymphoid-restricted PI3Kδ with idelalisib enhances glucocorticoid activity in B-ALL cells. Here, we show that idelalisib enhances glucocorticoid potency in 90% of primary B-ALL specimens and is most pronounced at sub-saturating doses of glucocorticoids near the EC50. Potentiation is associated with enhanced regulation of all glucocorticoid-regulated genes, including genes that drive B-ALL cell death. Idelalisib reduces phosphorylation of the glucocorticoid receptor (GR) at PI3Kδ/MAPK1 (ERK2) targets S203 and S226. Ablation of these phospho-acceptor sites enhances sensitivity to glucocorticoids with ablation of S226 in particular reducing synergy. We also show that phosphorylation of S226 reduces the affinity of GR for DNA in vitro. We propose that PI3Kδ inhibition improves glucocorticoid efficacy in B-ALL in part by decreasing GR phosphorylation, increasing DNA binding affinity, and enhancing downstream gene regulation. This mechanism and the response of patient specimens suggest that idelalisib will benefit most patients with B-ALL, but particularly patients with less responsive, including high-risk, disease. This combination is also promising for the development of less toxic glucocorticoid-sparing therapies.

Standardized assays to monitor drug sensitivity in hematologic cancers

The principle of drug sensitivity testing is to expose cancer cells to a library of different drugs and measure its effects on cell viability. Recent technological advances, continuous approval of targeted therapies, and improved cell culture protocols have enhanced the precision and clinical relevance of such screens. Indeed, drug sensitivity testing has proven diagnostically valuable for patients with advanced hematologic cancers. However, different cell types behave differently in culture and therefore require optimized drug screening protocols to ensure that their ex vivo drug sensitivity accurately reflects in vivo drug responses. For example, primary chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) cells require unique microenvironmental stimuli to survive in culture, while this is less the case for acute myeloid leukemia (AML) cells. Here, we present our optimized and validated protocols for culturing and drug screening of primary cells from AML, CLL, and MM patients, and a generic protocol for cell line models. We also discuss drug library designs, reproducibility, and quality controls. We envision that these protocols may serve as community guidelines for the use and interpretation of assays to monitor drug sensitivity in hematologic cancers and thus contribute to standardization. The read-outs may provide insight into tumor biology, identify or confirm treatment resistance and sensitivity in real time, and ultimately guide clinical decision-making.

Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis

Myelofibrosis is a hematopoietic stem cell disorder belonging to the myeloproliferative neoplasms. Myelofibrosis patients frequently carry driver mutations in either JAK2 or Calreticulin (CALR) and have limited therapeutic options. Here, we integrate ex vivo drug response and proteotype analyses across myelofibrosis patient cohorts to discover targetable vulnerabilities and associated therapeutic strategies. Drug sensitivities of mutated and progenitor cells were measured in patient blood using high-content imaging and single-cell deep learning-based analyses. Integration with matched molecular profiling revealed three targetable vulnerabilities. First, CALR mutations drive BET and HDAC inhibitor sensitivity, particularly in the absence of high Ras pathway protein levels. Second, an MCM complex-high proliferative signature corresponds to advanced disease and sensitivity to drugs targeting pro-survival signaling and DNA replication. Third, homozygous CALR mutations result in high endoplasmic reticulum (ER) stress, responding to ER stressors and unfolded protein response inhibition. Overall, our integrated analyses provide a molecularly motivated roadmap for individualized myelofibrosis patient treatment.

Comparing the value of mono- vs coculture for high-throughput compound screening in hematological malignancies

Large-scale compound screens are a powerful model system for understanding variability of treatment response and discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we established a high-throughput platform to measure ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52% of compounds in chronic lymphocytic leukemia (CLL) and 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, B-cell receptor inhibitors, proteasome inhibitors, and Bromodomain and extraterminal domain inhibitors. Only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations strongly correlated between monoculture and coculture. However, effect sizes were lower in coculture, with more drug-gene associations detected in monoculture than in coculture. Our results justify a 2-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

Novel precision medicine approaches and treatment strategies in hematological malignancies

Genetic testing has been applied for decades in clinical routine diagnostics of hematological malignancies to improve disease (sub)classification, prognostication, patient management, and survival. In recent classifications of hematological malignancies, disease subtypes are defined by key recurrent genetic alterations detected by conventional methods (i.e., cytogenetics, fluorescence in situ hybridization, and targeted sequencing). Hematological malignancies were also one of the first disease areas in which targeted therapies were introduced, the prime example being BCR::ABL1 inhibitors, followed by an increasing number of targeted inhibitors hitting the Achilles' heel of each disease, resulting in a clear patient benefit. Owing to the technical advances in high-throughput sequencing, we can now apply broad genomic tests, including comprehensive gene panels or whole-genome and whole-transcriptome sequencing, to identify clinically important diagnostic, prognostic, and predictive markers. In this review, we give examples of how precision diagnostics has been implemented to guide treatment selection and improve survival in myeloid (myelodysplastic syndromes and acute myeloid leukemia) and lymphoid malignancies (acute lymphoblastic leukemia, diffuse large B-cell lymphoma, and chronic lymphocytic leukemia). We discuss the relevance and potential of monitoring measurable residual disease using ultra-sensitive techniques to assess therapy response and detect early relapses. Finally, we bring up the promising avenue of functional precision medicine, combining ex vivo drug screening with various omics technologies, to provide novel treatment options for patients with advanced disease. Although we are only in the beginning of the field of precision hematology, we foresee rapid development with new types of diagnostics and treatment strategies becoming available to the benefit of our patients.

Cytokine-directed cellular cross-talk imprints synovial pathotypes in rheumatoid arthritis

INTRODUCTION

Structural reorganisation of the synovium with expansion of fibroblast-like synoviocytes (FLS) and influx of immune cells is a hallmark of rheumatoid arthritis (RA). Activated FLS are increasingly recognised as a critical component driving synovial tissue remodelling by interacting with immune cells resulting in distinct synovial pathotypes of RA.

METHODS

Automated high-content fluorescence microscopy of co-cultured cytokine-activated FLS and autologous peripheral CD4+ T cells from patients with RA was established to quantify cell-cell interactions. Phenotypic profiling of cytokine-treated FLS and co-cultured T cells was done by flow cytometry and RNA-Seq, which were integrated with publicly available transcriptomic data from patients with different histological synovial pathotypes. Computational prediction and knock-down experiments were performed in FLS to identify adhesion molecules for cell-cell interaction.

RESULTS

Cytokine stimulation, especially with TNF-α, led to enhanced FLS-T cell interaction resulting in cell-cell contact-dependent activation, proliferation and differentiation of T cells. Signatures of cytokine-activated FLS were significantly enriched in RA synovial tissues defined as lymphoid-rich or leucocyte-rich pathotypes, with the most prominent effects for TNF-α. FLS cytokine signatures correlated with the number of infiltrating CD4+ T cells in synovial tissue of patients with RA. Ligand-receptor pair interaction analysis identified ICAM1 on FLS as an important mediator in TNF-mediated FLS-T cell interaction. Both, ICAM1 and its receptors were overexpressed in TNF-treated FLS and co-cultured T cells. Knock-down of ICAM1 in FLS resulted in reduced TNF-mediated FLS-T cell interaction.

CONCLUSION

Our study highlights the role of cytokine-activated FLS in orchestrating inflammation-associated synovial pathotypes providing novel insights into disease mechanisms of RA.

Targeting the Siglec-sialic acid axis promotes antitumor immune responses in preclinical models of glioblastoma

Glioblastoma (GBM) is the most aggressive form of primary brain tumor, for which effective therapies are urgently needed. Cancer cells are capable of evading clearance by phagocytes such as microglia- and monocyte-derived cells through engaging tolerogenic programs. Here, we found that high expression of sialic acid-binding immunoglobulin-like lectin 9 (Siglec-9) correlates with reduced survival in patients with GBM. Using microglia- and monocyte-derived cell-specific knockouts of Siglec-E, the murine functional homolog of Siglec-9, together with single-cell RNA sequencing, we demonstrated that Siglec-E inhibits phagocytosis by these cells, thereby promoting immune evasion. Loss of Siglec-E on monocyte-derived cells further enhanced antigen cross-presentation and production of pro-inflammatory cytokines, which resulted in more efficient T cell priming. This bridging of innate and adaptive responses delayed tumor growth and resulted in prolonged survival in murine models of GBM. Furthermore, we showed the combinatorial activity of Siglec-E blockade and other immunotherapies demonstrating the potential for targeting Siglec-9 as a treatment for patients with GBM.

Ex vivo venetoclax sensitivity testing predicts treatment response in acute myeloid leukemia

The BCL-2 inhibitor venetoclax has revolutionized the treatment of acute myeloid leukemia (AML) in patients not benefiting from intensive chemotherapy. Nevertheless, treatment failure remains a challenge, and predictive markers are needed, particularly for relapsed or refractory AML. Ex vivo drug sensitivity testing may correlate with outcomes, but its prospective predictive value remains unexplored. Here we report the results of the first stage of the prospective phase II VenEx trial evaluating the utility and predictiveness of venetoclax sensitivity testing using different cell culture conditions and cell viability assays in patients receiving venetoclax-azacitidine. Participants with de novo AML ineligible for intensive chemotherapy, relapsed or refractory AML, or secondary AML were included. The primary endpoint was the treatment response in participants showing ex vivo sensitivity and the key secondary endpoints were the correlation of sensitivity with responses and survival. Venetoclax sensitivity testing was successful in 38/39 participants. Experimental conditions significantly influenced the predictive accuracy. Blast-specific venetoclax sensitivity measured in conditioned medium most accurately correlated with treatment outcomes; 88% of sensitive participants achieved a treatment response. The median survival was significantly longer for participants who were ex vivo-sensitive to venetoclax (14.6 months for venetoclax-sensitive patients vs. 3.5 for venetoclax-insensitive patients, P<0.001). This analysis illustrates the feasibility of integrating drug-response profiling into clinical practice and demonstrates excellent predictivity. This trial is registered with ClinicalTrials.gov identifier: NCT04267081.

Vienna Cancer Stem Cell Club (VCSCC): 20 year jubilee and future perspectives

INTRODUCTION

The Vienna Cancer Stem Cell Club (VCSCC) was launched by a group of scientists in Vienna in 2002.

AREAS COVERED

Major aims of the VCSCC are to support research on cancer stem cells (CSC) in hematopoietic malignancies and to translate CSC-related markers and targets into clinical application. A primary focus of research in the VCSCC is the leukemic stem cell (LSC). Between 2013 and 2021, members of the VCSCC established a special research program on myeloproliferative neoplasms and since 2008, members of the VCSCC run the Ludwig Boltzmann Institute for Hematology and Oncology. In all these years, the VCSCC provided a robust intellectual platform for translational hematology and LSC research in Vienna. Furthermore, the VCSCC interacts with several national and international study groups and societies in the field. Representatives of the VCSCC also organized a number of international meetings and conferences on neoplastic stem cells, including LSC, in the past 15 years, and contributed to the definition and classification of CSC/LSC and related pre-malignant and malignant conditions.

EXPERT OPINION

The VCSCC will continue to advance the field and to develop LSC-detecting and LSC-eradicating concepts through which diagnosis, prognostication, and therapy of blood cancer patients should improve.

Ex vivo drug response heterogeneity reveals personalized therapeutic strategies for patients with multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy defined by complex genetics and extensive patient heterogeneity. Despite a growing arsenal of approved therapies, MM remains incurable and in need of guidelines to identify effective personalized treatments. Here, we survey the ex vivo drug and immunotherapy sensitivities across 101 bone marrow samples from 70 patients with MM using multiplexed immunofluorescence, automated microscopy and deep-learning-based single-cell phenotyping. Combined with sample-matched genetics, proteotyping and cytokine profiling, we map the molecular regulatory network of drug sensitivity, implicating the DNA repair pathway and EYA3 expression in proteasome inhibitor sensitivity and major histocompatibility complex class II expression in the response to elotuzumab. Globally, ex vivo drug sensitivity associated with bone marrow microenvironmental signatures reflecting treatment stage, clonality and inflammation. Furthermore, ex vivo drug sensitivity significantly stratified clinical treatment responses, including to immunotherapy. Taken together, our study provides molecular and actionable insights into diverse treatment strategies for patients with MM.

Comparison of two supporting matrices for patient-derived cancer cells in 3D drug sensitivity and resistance testing assay (3D-DSRT)

Central to the success of functional precision medicine of solid tumors is to perform drug testing of patient-derived cancer cells (PDCs) in tumor-mimicking ex vivo conditions. While high throughput (HT) drug screening methods have been well-established for cells cultured in two-dimensional (2D) format, this approach may have limited value in predicting clinical responses. Here, we describe the results of the optimization of drug sensitivity and resistance testing (DSRT) in three-dimensional (3D) growth supporting matrices in a HT mode (3D-DSRT) using the hepatocyte cell line (HepG2) as an example. Supporting matrices included widely used animal-derived Matrigel and cellulose-based hydrogel, GrowDex, which has earlier been shown to support 3D growth of cell lines and stem cells. Further, the sensitivity of ovarian cancer PDCs, from two patients included in the functional precision medicine study, was tested for 52 drugs in 5 different concentrations using 3D-DSRT. Shortly, in the optimized protocol, the PDCs are embedded with matrices and seeded to 384-well plates to allow the formation of the spheroids prior to the addition of drugs in nanoliter volumes with acoustic dispenser. The sensitivity of spheroids to drug treatments is measured with cell viability readout (here, 72 h after addition of drugs). The quality control and data analysis are performed with openly available Breeze software. We show the usability of both matrices in established 3D-DSRT, and report 2D vs 3D growth condition dependent differences in sensitivities of ovarian cancer PDCs to MEK-inhibitors and cytotoxic drugs. This study provides a proof-of-concept for robust and fast screening of drug sensitivities of PDCs in 3D-DSRT, which is important not only for drug discovery but also for personalized ex vivo drug testing in functional precision medicine studies. These findings suggest that comparing results of 2D- and 3D-DSRT is essential for understanding drug mechanisms and for selecting the most effective treatment for the patient.

Histology Image Viewer and Converter (HIVC): A High-Speed Freeware Software to View and Convert Whole Slide Histology Images

Histology images are widely used to assess the microstructure of biological tissues, but scanners often save images in bulky SVS and multi-layered TIFF formats. These formats were designed to archive image blocks and high-resolution textual information and are not compatible with conventional image analysis software. Our goal was to create a freeware Histology Image Viewer and Converter (HIVC) with a graphical user interface that allows viewing and converting whole-slide images in batch. HIVC was developed using C# Language for Windows x64 operating system. HIVC's performance was assessed by converting 20 whole-slide images to a JPG format at 20x and 40x resolution and comparing the results to ImageJ, Cell Profiler, QuPath, Nanoborb, and Aperio ImageScope. HIVC was more than 8-times faster in converting images than other software packages. This software allows high-speed batch conversion of histology images to traditional formats, permitting platform-independent secondary analyses.

Microfluidic-based dynamic BH3 profiling predicts anticancer treatment efficacy

Precision medicine is starting to incorporate functional assays to evaluate anticancer agents on patient-isolated tissues or cells to select for the most effective. Among these new technologies, dynamic BH3 profiling (DBP) has emerged and extensively been used to predict treatment efficacy in different types of cancer. DBP uses synthetic BH3 peptides to measure early apoptotic events ('priming') and anticipate therapy-induced cell death leading to tumor elimination. This predictive functional assay presents multiple advantages but a critical limitation: the cell number requirement, that limits drug screening on patient samples, especially in solid tumors. To solve this problem, we developed an innovative microfluidic-based DBP (µDBP) device that overcomes tissue limitations on primary samples. We used microfluidic chips to generate a gradient of BIM BH3 peptide, compared it with the standard flow cytometry based DBP, and tested different anticancer treatments. We first examined this new technology's predictive capacity using gastrointestinal stromal tumor (GIST) cell lines, by comparing imatinib sensitive and resistant cells, and we could detect differences in apoptotic priming and anticipate cytotoxicity. We then validated µDBP on a refractory GIST patient sample and identified that the combination of dactolisib and venetoclax increased apoptotic priming. In summary, this new technology could represent an important advance for precision medicine by providing a fast, easy-to-use and scalable microfluidic device to perform DBP in situ as a routine assay to identify the best treatment for cancer patients.

A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements

Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient's tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of cancer drug response.

Selective Inhibition of Bruton's Tyrosine Kinase by a Designed Covalent Ligand Leads to Potent Therapeutic Efficacy in Blood Cancers Relative to Clinically Used Inhibitors

Bruton's tyrosine kinase (BTK) is a member of the TEC-family kinases and crucial for the proliferation and differentiation of B-cells. We evaluated the therapeutic potential of a covalent inhibitor (JS25) with nanomolar potency against BTK and with a more desirable selectivity and inhibitory profile compared to the FDA-approved BTK inhibitors ibrutinib and acalabrutinib. Structural prediction of the BTK/JS25 complex revealed sequestration of Tyr551 that leads to BTK's inactivation. JS25 also inhibited the proliferation of myeloid and lymphoid B-cell cancer cell lines. Its therapeutic potential was further tested against ibrutinib in preclinical models of B-cell cancers. JS25 treatment induced a more pronounced cell death in a murine xenograft model of Burkitt's lymphoma, causing a 30-40% reduction of the subcutaneous tumor and an overall reduction in the percentage of metastasis and secondary tumor formation. In a patient model of diffuse large B-cell lymphoma, the drug response of JS25 was higher than that of ibrutinib, leading to a 64% "on-target" efficacy. Finally, in zebrafish patient-derived xenografts of chronic lymphocytic leukemia, JS25 was faster and more effective in decreasing tumor burden, producing superior therapeutic effects compared to ibrutinib. We expect JS25 to become therapeutically relevant as a BTK inhibitor and to find applications in the treatment of hematological cancers and other pathologies with unmet clinical treatment.

Multiplexed high-throughput immune cell imaging reveals molecular health-associated phenotypes

Phenotypic plasticity is essential to the immune system, yet the factors that shape it are not fully understood. Here, we comprehensively analyze immune cell phenotypes including morphology across human cohorts by single-round multiplexed immunofluorescence, automated microscopy, and deep learning. Using the uncertainty of convolutional neural networks to cluster the phenotypes of eight distinct immune cell subsets, we find that the resulting maps are influenced by donor age, gender, and blood pressure, revealing distinct polarization and activation-associated phenotypes across immune cell classes. We further associate T cell morphology to transcriptional state based on their joint donor variability and validate an inflammation-associated polarized T cell morphology and an age-associated loss of mitochondria in CD4⁺ T cells. Together, we show that immune cell phenotypes reflect both molecular and personal health information, opening new perspectives into the deep immune phenotyping of individual people in health and disease.

Deep Morphology Learning Enhances Ex Vivo Drug Profiling-Based Precision Medicine

Drug testing in patient biopsy-derived cells can identify potent treatments for patients suffering from relapsed or refractory hematologic cancers. Here we investigate the use of weakly supervised deep learning on cell morphologies (DML) to complement diagnostic marker-based identification of malignant and nonmalignant cells in drug testing. Across 390 biopsies from 289 patients with diverse blood cancers, DML-based drug responses show improved reproducibility and clustering of drugs with the same mode of action. DML does so by adapting to batch effects and by autonomously recognizing disease-associated cell morphologies. In a post hoc analysis of 66 patients, DML-recommended treatments led to improved progression-free survival compared with marker-based recommendations and physician's choice-based treatments. Treatments recommended by both immunofluorescence and DML doubled the fraction of patients achieving exceptional clinical responses. Thus, DML-enhanced ex vivo drug screening is a promising tool in the identification of effective personalized treatments.

SIGNIFICANCE

We have recently demonstrated that image-based drug screening in patient samples identifies effective treatment options for patients with advanced blood cancers. Here we show that using deep learning to identify malignant and nonmalignant cells by morphology improves such screens. The presented workflow is robust, automatable, and compatible with clinical routine. This article is highlighted in the In This Issue feature, p. 476.

Pharmacogenomic Profiling of Pediatric Acute Myeloid Leukemia to Identify Therapeutic Vulnerabilities and Inform Functional Precision Medicine

Despite the expanding portfolio of targeted therapies for adults with acute myeloid leukemia (AML), direct implementation in children is challenging due to inherent differences in underlying genetics. Here we established the pharmacologic profile of pediatric AML by screening myeloblast sensitivity to approved and investigational agents, revealing candidates of immediate clinical relevance. Drug responses ex vivo correlated with patient characteristics, exhibited age-specific alterations, and concorded with activities in xenograft models. Integration with genomic data uncovered new gene-drug associations, suggesting actionable therapeutic vulnerabilities. Transcriptome profiling further identified gene-expression signatures associated with on- and off-target drug responses. We also demonstrated the feasibility of drug screening-guided treatment for children with high-risk AML, with two evaluable cases achieving remission. Collectively, this study offers a high-dimensional gene-drug clinical data set that could be leveraged to research the unique biology of pediatric AML and sets the stage for realizing functional precision medicine for the clinical management of the disease.

SIGNIFICANCE

We conducted integrated drug and genomic profiling of patient biopsies to build the functional genomic landscape of pediatric AML. Age-specific differences in drug response and new gene-drug interactions were identified. The feasibility of functional precision medicine-guided management of children with high-risk AML was successfully demonstrated in two evaluable clinical cases. This article is highlighted in the In This Issue feature, p. 476.

Multifunctional mRNA-Based CAR T Cells Display Promising Antitumor Activity Against Glioblastoma

PURPOSE

Most chimeric antigen receptor (CAR) T-cell strategies against glioblastoma have demonstrated only modest therapeutic activity and are based on persistent gene modification strategies that have limited transgene capacity, long manufacturing processes, and the risk for uncontrollable off-tumor toxicities. mRNA-based T-cell modifications are an emerging safe, rapid, and cost-effective alternative to overcome these challenges, but are underexplored against glioblastoma.

EXPERIMENTAL DESIGN

We generated mouse and human mRNA-based multifunctional T cells coexpressing a multitargeting CAR based on the natural killer group 2D (NKG2D) receptor and the proinflammatory cytokines IL12 and IFNα2 and assessed their antiglioma activity in vitro and in vivo.

RESULTS

Compared with T cells that either expressed the CAR or cytokines alone, multifunctional CAR T cells demonstrated increased antiglioma activity in vitro and in vivo in three orthotopic immunocompetent mouse glioma models without signs of toxicity. Mechanistically, the coexpression of IL12 and IFNα2 in addition to the CAR promoted a proinflammatory tumor microenvironment and reduced T-cell exhaustion as demonstrated by ex vivo immune phenotyping, cytokine profiling, and RNA sequencing. The translational potential was demonstrated by image-based single-cell analyses of mRNA-modified T cells in patient glioblastoma samples with a complex cellular microenvironment. This revealed strong antiglioma activity of human mRNA-based multifunctional NKG2D CAR T cells coexpressing IL12 and IFNα2 whereas T cells that expressed either the CAR or cytokines alone did not demonstrate comparable antiglioma activity.

CONCLUSIONS

These data provide a robust rationale for future clinical studies with mRNA-based multifunctional CAR T cells to treat malignant brain tumors.

An ex vivo platform to guide drug combination treatment in relapsed/refractory lymphoma

Although combination therapy is the standard of care for relapsed/refractory non-Hodgkin's lymphoma (RR-NHL), combination treatment chosen for an individual patient is empirical, and response rates remain poor in individuals with chemotherapy-resistant disease. Here, we evaluate an experimental-analytic method, quadratic phenotypic optimization platform (QPOP), for prediction of patient-specific drug combination efficacy from a limited quantity of biopsied tumor samples. In this prospective study, we enrolled 71 patients with RR-NHL (39 B cell NHL and 32 NK/T cell NHL) with a median of two prior lines of treatment, at two academic hospitals in Singapore from November 2017 to August 2021. Fresh biopsies underwent ex vivo testing using a panel of 12 drugs with known efficacy against NHL to identify effective single and combination treatments. Individualized QPOP reports were generated for 67 of 75 patient samples, with a median turnaround time of 6 days from sample collection to report generation. Doublet drug combinations containing copanlisib or romidepsin were most effective against B cell NHL and NK/T cell NHL samples, respectively. Off-label QPOP-guided therapy offered at physician discretion in the absence of standard options (n = 17) resulted in five complete responses. Among patients with more than two prior lines of therapy, the rates of progressive disease were lower with QPOP-guided treatments than with conventional chemotherapy. Overall, this study shows that the identification of patient-specific drug combinations through ex vivo analysis was achievable for RR-NHL in a clinically applicable time frame. These data provide the basis for a prospective clinical trial evaluating ex vivo-guided combination therapy in RR-NHL.

Precision oncology using ex vivo technology: a step towards individualised cancer care?

Despite advances in cancer genomics and the increased use of genomic medicine, metastatic cancer is still mostly an incurable and fatal disease. With diminishing returns from traditional drug discovery strategies, and high clinical failure rates, more emphasis is being placed on alternative drug discovery platforms, such as ex vivo approaches. Ex vivo approaches aim to embed biological relevance and inter-patient variability at an earlier stage of drug discovery, and to offer more precise treatment stratification for patients. However, these techniques also have a high potential to offer personalised therapies to patients, complementing and enhancing genomic medicine. Although an array of approaches are available to researchers, only a minority of techniques have made it through to direct patient treatment within robust clinical trials. Within this review, we discuss the current challenges to ex vivo approaches within clinical practice and summarise the contemporary literature which has directed patient treatment. Finally, we map out how ex vivo approaches could transition from a small-scale, predominantly research based technology to a robust and validated predictive tool. In future, these pre-clinical approaches may be integrated into clinical cancer pathways to assist in the personalisation of therapy choices and to hopefully improve patient experiences and outcomes.

Explainable artificial intelligence for precision medicine in acute myeloid leukemia

Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of “black box” in AI limits the potential of this approach to be translated into the clinical practice. In contrast, explainable AI (XAI) focuses on making AI results understandable to humans. Here, we present a novel XAI method -called multi-dimensional module optimization (MOM)- that associates drug screening with genetic events, while guaranteeing that predictions are interpretable and robust. We applied MOM to an acute myeloid leukemia (AML) cohort of 319 ex-vivo tumor samples with 122 screened drugs and WES. MOM returned a therapeutic strategy based on the FLT3, CBFβ-MYH11, and NRAS status, which predicted AML patient response to Quizartinib, Trametinib, Selumetinib, and Crizotinib. We successfully validated the results in three different large-scale screening experiments. We believe that XAI will help healthcare providers and drug regulators better understand AI medical decisions.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

Pharmacogenomic landscape of head and neck squamous cell carcinoma informs precision oncology therapy

Head and neck squamous cell carcinoma (HNSCC) is a common and frequently lethal cancer with few therapeutic options. In particular, there are few effective targeted therapies. Development of highly effective therapeutic strategies tailored to patients with HNSCC remains a pressing challenge. To address this, we present a pharmacogenomic study to facilitate precision treatments for patients with HNSCC. We established a large collection of 56 HNSCC patient-derived cells (PDCs), which recapitulated the molecular features of the original tumors. Pharmacological assessment of HNSCCs was conducted using a three-tiered high-throughput drug screening using 2248 compounds across these PDC models and an additional 18 immortalized cell lines. We integrated genomic, transcriptomic, and pharmacological analysis to predict biomarkers, gene-drug associations, and validated biomarkers. These results supported drug repurposing for multiple HNSCC subtypes, including the JAK2 inhibitor fedratinib, for low KRT18-expressing HNSCC cases, and the topoisomerase inhibitor mitoxantrone, for IL6R-activated HNSCC cases. Our results demonstrated concordance between susceptibility predictions from the PDCs and the matched patients' responses to standard clinical medication. Moreover, we identified and experimentally confirmed that high expression of ITGB1 elicited therapeutic resistance to docetaxel and high SOD1 expression conferred resistance to afatinib. We further validated ITGB1 as a predictive biomarker for the efficacy of docetaxel therapy in a phase 2 clinical trial. In summary, our study shows that this HNSCC cell resource, as well as the resulting pharmacogenomic profiles, is effective for biomarker discovery and for guiding precision oncology therapies in HNSCCs.

Modelling acute myeloid leukemia (AML): What's new? A transition from the classical to the modern

Acute myeloid leukemia (AML) is a heterogeneous malignancy affecting myeloid cells in the bone marrow (BM) but can spread giving rise to impaired hematopoiesis. AML incidence increases with age and is associated with poor prognostic outcomes. There has been a disconnect between the success of novel drug compounds observed in preclinical studies of hematological malignancy and less than exceptional therapeutic responses in clinical trials. This review aims to provide a state-of-the-art overview on the different preclinical models of AML available to expand insights into disease pathology and as preclinical screening tools. Deciphering the complex physiological and pathological processes and developing predictive preclinical models are key to understanding disease progression and fundamental in the development and testing of new effective drug treatments. Standard scaffold-free suspension models fail to recapitulate the complex environment where AML occurs. To this end, we review advances in scaffold/matrix-based 3D models and outline the most recent advances in on-chip technology. We also provide an overview of clinically relevant animal models and review the expanding use of patient-derived samples, which offer the prospect to create more "patient specific" screening tools either in the guise of 3D matrix models, microphysiological "organ-on-chip" tools or xenograft models and discuss representative examples.

A toolbox for class I HDACs reveals isoform specific roles in gene regulation and protein acetylation

The class I histone deacetylases are essential regulators of cell fate decisions in health and disease. While pan- and class-specific HDAC inhibitors are available, these drugs do not allow a comprehensive understanding of individual HDAC function, or the therapeutic potential of isoform-specific targeting. To systematically compare the impact of individual catalytic functions of HDAC1, HDAC2 and HDAC3, we generated human HAP1 cell lines expressing catalytically inactive HDAC enzymes. Using this genetic toolbox we compare the effect of individual HDAC inhibition with the effects of class I specific inhibitors on cell viability, protein acetylation and gene expression. Individual inactivation of HDAC1 or HDAC2 has only mild effects on cell viability, while HDAC3 inactivation or loss results in DNA damage and apoptosis. Inactivation of HDAC1/HDAC2 led to increased acetylation of components of the COREST co-repressor complex, reduced deacetylase activity associated with this complex and derepression of neuronal genes. HDAC3 controls the acetylation of nuclear hormone receptor associated proteins and the expression of nuclear hormone receptor regulated genes. Acetylation of specific histone acetyltransferases and HDACs is sensitive to inactivation of HDAC1/HDAC2. Over a wide range of assays, we determined that in particular HDAC1 or HDAC2 catalytic inactivation mimics class I specific HDAC inhibitors. Importantly, we further demonstrate that catalytic inactivation of HDAC1 or HDAC2 sensitizes cells to specific cancer drugs. In summary, our systematic study revealed isoform-specific roles of HDAC1/2/3 catalytic functions. We suggest that targeted genetic inactivation of particular isoforms effectively mimics pharmacological HDAC inhibition allowing the identification of relevant HDACs as targets for therapeutic intervention.

Application of precision medicine in clinical routine in haematology-Challenges and opportunities

Precision medicine is revolutionising patient care in cancer. As more knowledge is gained about the impact of specific genetic lesions on diagnosis, prognosis and treatment response, diagnostic precision and the possibility for optimal individual treatment choice have improved. Identification of hallmark genetic aberrations such as the BCR::ABL1 gene fusion in chronic myeloid leukaemia (CML) led to the rapid development of efficient targeted therapy and molecular follow-up, vastly improving survival for patients with CML during recent decades. The assessment of translocations, copy number changes and point mutations are crucial for the diagnosis and risk stratification of acute myeloid leukaemia and myelodysplastic syndromes. Still, the often heterogeneous and complex genetic landscape of haematological malignancies presents several challenges for the implementation of precision medicine to guide diagnosis, prognosis and treatment choice. This review provides an introduction and overview of the important molecular characteristics and methods currently applied in clinical practice to guide clinical decision making in haematological malignancies of myeloid and lymphoid origin. Further, experimental ways to guide the choice of targeted therapy for refractory patients are reviewed, such as functional precision medicine using drug profiling. An example of the use of pipeline studies where the treatment is chosen according to the molecular characteristics in rare solid malignancies is also provided. Finally, the future opportunities and remaining challenges of precision medicine in the real world are discussed.

Distinct immune stimulatory effects of anti-human VISTA antibodies are determined by Fc-receptor interaction

VISTA (PD-1H) is an immune regulatory molecule considered part of the next wave of immuno-oncology targets. VISTA is an immunoglobulin (Ig) superfamily cell surface molecule mainly expressed on myeloid cells, and to some extent on NK cells and T cells. In previous preclinical studies, some VISTA-targeting antibodies provided immune inhibitory signals, while other antibodies triggered immune stimulatory signals. Importantly, for therapeutic antibodies, the isotype backbone can have a strong impact on antibody function. To elucidate the mode of action of immune stimulatory anti-VISTA antibodies, we studied three different anti-human VISTA antibody clones, each on three different IgG isotypes currently used for therapeutic antibodies: unaltered IgG1 (IgG1-WT), IgG1-KO (IgG1-LL234,235AA-variant with reduced Fc-effector function), and IgG4-Pro (IgG4- S228P-variant with stabilized hinge region). Antibody functionality was analysed in mixed leukocyte reaction (MLR) of human peripheral blood mononuclear cells (PBMCs), as a model system for ongoing immune reactions, on unstimulated human PBMCs, as a model system for a resting immune system, and also on acute myeloid leukemia (AML) patient samples to evaluate anti-VISTA antibody effects on primary tumor material. The functions of three anti-human VISTA antibodies were determined by their IgG isotype backbones. An MLR of healthy donor PBMCs was effectively augmented by anti-VISTA-IgG4-Pro and anti-VISTA-IgG1-WT antibodies, as indicated by increased levels of cytokines, T cell activation markers and T cell proliferation. However, in a culture of unstimulated PBMCs of single healthy donors, only anti-VISTA-IgG1-WT antibodies increased the activation marker HLA-DR on resting myeloid cells, and chemokine levels. Interestingly, interactions with different Fc-receptors were required for these effects, namely CD64 for augmentation of MLR, and CD16 for activation of resting myeloid cells. Furthermore, anti-VISTA-IgG1-KO antibodies had nearly no impact in any model system. Similarly, in AML patient samples, anti-VISTA-antibody on IgG4-Pro backbone, but not on IgG1-KO backbone, increased interactions, as a novel readout of activity, between immune cells and CD34+ AML cancer cells. In conclusion, the immune stimulatory effects of antagonistic anti-VISTA antibodies are defined by the antibody isotype and interaction with different Fc-gamma-receptors, highlighting the importance of understanding these interactions when designing immune stimulatory antibody therapeutics for immuno-oncology applications.

Functional Drug Screening in the Era of Precision Medicine

The focus of precision medicine is providing the right treatment to each unique patient. This scientific movement has incited monumental advances in oncology including the approval of effective, targeted agnostic therapies. Yet, precision oncology has focused largely on genomics in the treatment decision making process, and several recent clinical trials demonstrate that genomics is not the only variable to be considered. Drug screening in three dimensional (3D) models, including patient derived organoids, organs on a chip, xenografts, and 3D-bioprinted models provide a functional medicine perspective and necessary complement to genomic testing. In this review, we discuss the practicality of various 3D drug screening models and each model's ability to capture the patient's tumor microenvironment. We highlight the potential for enhancing precision medicine that personalized functional drug testing holds in combination with genomic testing and emerging mathematical models.