Performed Drug Screening Research Articles

Generation of iPSC-derived human venous endothelial cells for the modeling of vascular malformations and drug discovery

Venous malformations (VMs) represent prevalent vascular anomalies typically attributed to non-inherited somatic mutations within venous endothelial cells (VECs). The lack of robust disease models for VMs impedes drug discovery. Here, we devise a robust protocol for the generation of human induced VECs (iVECs) through manipulation of cell-cycle dynamics via the retinoic signaling pathway. We introduce an L914F mutation into the TIE2 gene locus of induced pluripotent stem cells (iPSCs) and show that the mutated iVECs form dilated blood vessels after transplantation into mice, thereby recapitulating the phenotypic characteristics observed in VMs. Moreover, utilizing a deep neural network and a high-throughput digital RNA with perturbation of genes sequencing (DRUG-seq) approach, we perform drug screening and demonstrate that bosutinib effectively rescues the disease phenotype invitro and invivo. In summary, by leveraging genome editing and stem cell technology, we generate VM models that enable the development of additional therapeutics.

Endothelin-1 receptor blockade impairs invasion patterns in engineered 3D high-grade serous ovarian cancer tumouroids.

High-grade serous ovarian cancer (HG-SOC), accounting for 70-80% of ovarian cancer deaths, is characterized by a widespread and rapid metastatic nature, influenced by diverse cell types, cell-cell interactions, and acellular components of the tumour microenvironment (TME). Within this tumour type, autocrine and paracrine activation of the endothelin-1 receptors (ET-1R), expressed in tumour cells and stromal elements, drives metastatic progression. The lack of three-dimensional models that faithfully recapitulate the unique HG-SOC TME has been the bottleneck in performing drug screening for personalized medicine. Herein, we developed HG-SOC tumouroids by engineering a dense central artificial cancer mass (ACM) containing HG-SOC cells, nested within a compressed hydrogel recapitulating the stromal compartment comprising type I collagen, laminin, fibronectin, and stromal cells (fibroblasts and endothelial cells). ET-1-stimulated HG-SOC cells in the tumouroids showed an altered migration pattern and formed cellular aggregates, mimicking micrometastases that invaded the stroma. Compared with control cells, ET-1-stimulated tumouroids showed a higher number of invasive bodies, which were reduced by treatment with the dual ET-1 receptor (ET-1R) antagonist macitentan. In addition, ET-1 increased the size of the invading aggregates compared with control cells. This study establishes an experimental 3D multicellular model eligible for mechanical research, investigating the impact of matrix stiffness and TME interactions, which will aid drug screening to guide therapeutic decisions in HG-SOC patients.

Conditional lethality profiling reveals anticancer mechanisms of action and drug-nutrient interactions.

Chemical screens across hundreds of cell lines have shown that the drug sensitivities of human cancers can vary by genotype or lineage. However, most drug discovery studies have relied on culture media that poorly reflect metabolite levels in human blood. Here, we perform drug screens in traditional and Human Plasma-Like Medium (HPLM). Sets of compounds that show conditional anticancer activity span different phases of global development and include non-oncology drugs. Comparisons of the synthetic and serum-derived components that comprise typical media trace sets of conditional phenotypes to nucleotide synthesis substrates. We also characterize a unique dual mechanism for brivudine, a compound approved for antiviral use. Brivudine selectively impairs cell growth in low folate conditions by targeting two enzymes involved in one-carbon metabolism. Cataloged gene essentiality data further suggest that conditional phenotypes for other compounds are linked to off-target effects. Our findings establish general strategies for identifying drug-nutrient interactions and mechanisms of action by exploiting conditional lethality in cancer cells.

Skeletal muscle-on-a-chip in microgravity as a platform for regeneration modeling and drug screening

Microgravity has been shown to lead to both muscle atrophy and impaired muscle regeneration. The purpose was to study the efficacy of microgravity to model impaired muscle regeneration in an engineered muscle platform and then to demonstrate the feasibility of performing drug screening in this model. Engineered human muscle was launched to the International Space Station National Laboratory, where the effect of microgravity exposure for 7days was examined by transcriptomics and proteomics approaches. Gene set enrichment analysis of engineered muscle cultured in microgravity, compared to normal gravity conditions, highlighted a metabolic shift toward lipid and fatty acid metabolism, along with increased apoptotic gene expression. The addition of pro-regenerative drugs, insulin-like growth factor-1 (IGF-1) and a 15-hydroxyprostaglandin dehydrogenase inhibitor (15-PGDH-i), partially inhibited the effects of microgravity. In summary, microgravity mimics aspects of impaired myogenesis, and the addition of these drugs could partially inhibit the effects induced by microgravity.

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy.

The nonphysiological nutrient levels found in traditional culture media have been shown to affect numerous aspects of cancer cell physiology, including how cells respond to certain therapeutic agents. Here, we comprehensively evaluated how physiological nutrient levels affect therapeutic response by performing drug screening in human plasma-like medium. We observed dramatic nutrient-dependent changes in sensitivity to a variety of FDA-approved and clinically trialed compounds, including rigosertib, an experimental cancer therapeutic that recently failed in phase III clinical trials. Mechanistically, we found that the ability of rigosertib to destabilize microtubules is strongly inhibited by the purine metabolism end product uric acid, which is uniquely abundant in humans relative to traditional in vitro and in vivo cancer models. These results demonstrate the broad and dramatic effects nutrient levels can have on drug response and how incorporation of human-specific physiological nutrient medium might help identify compounds whose efficacy could be influenced in humans.

Patient-derived follicular lymphoma spheroids recapitulate lymph node signaling and immune profile uncovering galectin-9 as a novel immunotherapeutic target

Follicular lymphoma (FL), the most common indolent non-Hodgkin lymphoma, constitutes a paradigm of immune tumor microenvironment (TME) contribution to disease onset, progression, and heterogenous clinical outcome. Here we present the first FL-Patient Derived Lymphoma Spheroid (FL-PDLS), including fundamental immune actors and features of TME in FL lymph nodes (LNs). FL-PDLS is organized in disc-shaped 3D structures composed of proliferating B and T cells, together with macrophages with an intermediate M1/M2 phenotype. FL-PDLS recapitulates the most relevant B-cell transcriptional pathways present in FL-LN (proliferation, epigenetic regulation, mTOR, adaptive immune system, among others). The T cell compartment in the FL-PDLS preserves CD4 subsets (follicular helper, regulatory, and follicular regulatory), also encompassing the spectrum of activation/exhaustion phenotypes in CD4 and CD8 populations. Moreover, this system is suitable for chemo and immunotherapy testing, recapitulating results obtained in the clinic. FL-PDLS allowed uncovering that soluble galectin-9 limits rituximab, rituximab, plus nivolumab/TIM-3 antitumoral activities. Blocking galectin-9 improves rituximab efficacy, highlighting galectin-9 as a novel immunotherapeutic target in FL. In conclusion, FL-PDLS maintains the crosstalk between malignant B cells and the immune LN-TME and constitutes a robust and multiplexed pre-clinical tool to perform drug screening in a patient-derived system, advancing toward personalized therapeutic approaches.

Abstract 4919: AI-enabled hit selection of drug screening on human pancreatic cancer organoids

Abstract Cancer remains one of the leading causes of death in the 21st century. Despite the latest advances in oncology, most cancer patients lack tailored therapeutic approaches with lasting benefit. Measuring the impact of anticancer compounds and their combinations is only possible on ex vivo assays. To this end, patient-derived organoids (PDOs) have been proposed as viable and efficient models for ex vivo testing. PDOs show long-term expansion potential while retaining tumor histopathology as well as cancer gene mutations. However, the translation of organoids in screening applications has so far been hampered by the lack of homogeneity and difficulties in handling and automation. Moreover, organoids are typically randomly distributed across the culture which complicates imaging and images analyses. To overcome these challenges, we set up a compound screening workflow with PDOs using Gri3D platform, comprising plates with micro-cavities suitable for high-throughput and reproducible organoid culture. Based on a standard 96 microtiter plate, each well contains a microwell array patterned in a cell repellent hydrogel. On Gri3D®, organoids are robustly generated in the microwells and are located in the same imaging plane. This greatly facilitates quantitative analyses in high content image-based screens. Furthermore, the pipetting port enables automation of cell seeding, media exchange and compound incubation with liquid-handlers, thus increasing assay reproducibility. In the presented work, we exposed human pancreatic cancer PDOs to a panel of anti-cancer compounds at different doses and followed their response to the drugs using viability dyes Calcein AM (live stain) and Ethidium Homodimer-1 (dead stain) with high-content confocal imaging. Using an AI-based approach, we efficiently detected each single organoid and extracted phenotypic features from all three channels (TL, live stain and dead stain) which correlate with cytotoxicity. The extracted features (more than 100) were first dimensionally reduced to 3 components using either PCA or UMAP, the treatments were then visualized in 3D scatter plots, ranked and clustered using machine learning. The data suggests that the compound treatment Palbociclib 50uM has significant cytotoxicity effects similar to the positive control, which is consistent with the traditional live/dead analysis. The AI approach demonstrates feasibility to perform drug screening in a robust and un-biased data analysis approach. Citation Format: Zhisong Tong, Angeline Lim, Marine Meyer, Maria Clapes, Oksana Sirenko, Nathalie Brandenberg. AI-enabled hit selection of drug screening on human pancreatic cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4919.

Microfluidic chips in female reproduction: a systematic review of status, advances, and challenges.

The female reproductive system is essential to women's health, human reproduction and societal well-being. However, the clinical translation of traditional research models is restricted due to the uncertain effects and low efficiency. Emerging evidence shows that microfluidic chips provide valuable platforms for studying the female reproductive system, while no paper has ever comprehensively discussed the topic. Here, a total of 161 studies out of 14,669 records are identified in PubMed, Scopus, Web of Science, ScienceDirect and IEEE Xplore databases. Among these, 61 studies focus on oocytes, which further involves culture, cell surgeries (oocyte separation, rotation, enucleation, and denudation), evaluation and cryopreservation. Forty studies investigate embryo manipulation via microfluidic chips, covering in vitro fertilization, cryopreservation and functional evaluation. Forty-six studies reconstitute both the physiological and pathological statuses of in vivo organs, mostly involved in placenta and fetal membrane research. Fourteen studies perform drug screening and toxicity testing. In this review, we summarize the current application of microfluidic chips in studying the female reproductive system, the advancements in materials and methods, and discuss the future challenges. The present evidence suggests that microfluidic chips-assisted reproductive system reconstruction is promising and more studies are urgently needed.

Establishment and Comprehensive Characterization of a Novel Preclinical Platform of Metastatic Retinoblastoma for Therapeutic Developments.

Although there have been improvements in the management of metastatic retinoblastoma, most patients do not survive, and all patients suffer from multiple short- and long-term treatment toxicities. Reliable and informative models to assist clinicians are needed. Thus we developed and comprehensively characterized a novel preclinical platform of primary cell cultures and xenograft models of metastatic retinoblastoma to provide insights into the molecular biology underlying metastases and to perform drug screening for the identification of hit candidates with the highest potential for clinical translation. Orbital tumor, bone marrow, cerebrospinal fluid, and lymph node tumor infiltration specimens were obtained from seven patients with metastatic retinoblastoma at diagnosis, disease progression, or relapse. Tumor specimens were engrafted in immunodeficient animals, and primary cell lines were established. Genomic, immunohistochemical/immunocytochemical, and pharmacological analysis were performed. We successfully established five primary cell lines: two derived from leptomeningeal, two from orbital, and one from lymph node tumor dissemination. After the intravitreal or intraventricular inoculation of these cells, we established cell-derived xenograft models. Both primary cell lines and xenografts accurately retained the histological and genomic features of the tumors from which they were derived and faithfully recapitulated the dissemination patterns and pharmacological sensitivity observed in the matched patients. Ours is an innovative and thoroughly characterized preclinical platform of metastatic retinoblastoma developed for the understanding of tumor biology of this highly aggressive tumor and has the potential to identify drug candidates to treat patients who currently lack effective treatment options.

Abstract A167: Cellular fitness of MYC-driven cancer cells to genetic and pharmacologic perturbations in normoxia, hypoxia and 3D culture

Abstract MYC and hypoxia gene clusters are two most commonly recurring transcriptional programs in a heterogenous tumor. Understanding the cellular fitness of MYC-driven cancer cells in normoxia and hypoxia may lead to identification of cancer cell vulnerabilities. Using genome-wide CRISPR screenings of MYC-driven liver cancer cells cultured in 21% and 1% oxygen in monolayer, and 21% oxygen in 3D spheroid over 4 weeks, we not only identify many targetable essential genes under all three conditions but also context-specific fitness genes and pathways. In parallel, we perform drug screening under three conditions. We find that cells respond to 125 FDA approved oncology drugs in different ways in normoxia, hypoxia and 3D. Our resource study highlights unique epigenetic and metabolic dependency of MYC-driven cancer cells in different tumor environments. Citation Format: Jun Yang. Cellular fitness of MYC-driven cancer cells to genetic and pharmacologic perturbations in normoxia, hypoxia and 3D culture [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A167.

Development of Novel Models of Aggressive Variants of Castration-resistant Prostate Cancer

BackgroundGenomic studies have identified new subsets of aggressive prostate cancer (PCa) with poor prognosis (eg, neuroendocrine prostate cancer [NEPC], PCa with DNA damage response [DDR] alterations, or PCa resistant to androgen receptor pathway inhibitors [ARPIs]). Development of novel therapies relies on the availability of relevant preclinical models. ObjectiveTo develop new preclinical models (patient-derived xenograft [PDX], PDX-derived organoid [PDXO], and patient-derived organoid [PDO]) representative of the most aggressive variants of PCa and to develop a new drug evaluation strategy. Design, setting, and participantsNEPC (n = 5), DDR (n = 7), and microsatellite instability (MSI)-high (n = 1) PDXs were established from 51 patients with metastatic PCa; PDXOs (n = 16) and PDOs (n = 6) were developed to perform drug screening. Histopathology and treatment response were characterized. Molecular profiling was performed by whole-exome sequencing (WES; n = 13), RNA sequencing (RNA-seq; n = 13), and single-cell RNA-seq (n = 14). WES and RNA-seq data from patient tumors were compared with the models. Outcome measurements and statistical analysisRelationships with outcome were analyzed using the multivariable chi-square test and the tumor growth inhibition test. Results and limitationsOur PDXs captured both common and rare molecular phenotypes and their molecular drivers, including alterations of BRCA2, CDK12, MSI-high status, and NEPC. RNA-seq profiling demonstrated broad representation of PCa subtypes. Single-cell RNA-seq indicates that PDXs reproduce cellular and molecular intratumor heterogeneity. WES of matched patient tumors showed preservation of most genetic driver alterations. PDXOs and PDOs preserve drug sensitivity of the matched tissue and can be used to determine drug sensitivity. ConclusionsOur models reproduce the phenotypic and genomic features of both common and aggressive PCa variants and capture their molecular heterogeneity. Successfully developed aggressive-variant PCa preclinical models provide an important tool for predicting tumor response to anticancer therapy and studying resistance mechanisms. Patient summaryIn this report, we looked at the outcomes of preclinical models from patients with metastatic prostate cancer enrolled in the MATCH-R trial (NCT02517892).

Cardiovascular human organ-on-a-chip platform for disease modeling, drug development, and personalized therapy.

Cardiovascular organ-on-a-chip (OoC) devices are composed of engineered or native functional tissues that are cultured under controlled microenvironments inside microchips. These systems employ microfabrication and tissue engineering techniques to recapitulate human physiology. This review focuses on human OoC systems to model cardiovascular diseases, to perform drug screening, and to advance personalized medicine. We also address the challenges in the generation of organ chips that can revolutionize the large-scale application of these systems for drug development and personalized therapy.

Skeletal muscle cell protein dysregulation highlights the pathogenesis mechanism of myopathy-associated p97/VCP R155H mutations.

p97/VCP, a hexametric member of the AAA-ATPase superfamily, has been associated with a wide range of cellular protein pathways, such as proteasomal degradation, the unfolding of polyubiquitinated proteins, and autophagosome maturation. Autosomal dominant p97/VCP mutations cause a rare hereditary multisystem disorder called IBMPFD/ALS (Inclusion Body Myopathy with Paget's Disease and Frontotemporal Dementia/Amyotrophic Lateral Sclerosis), characterized by progressive weakness and subsequent atrophy of skeletal muscles, and impacting bones and brains, such as Parkinson's disease, Lewy body disease, Huntington's disease, and amyotrophic lateral ALS. Among all disease-causing mutations, Arginine 155 to Histidine (R155H/+) was reported to be the most common one, affecting over 50% of IBMPFD patients, resulting in disabling muscle weakness, which might eventually be life-threatening due to cardiac and respiratory muscle involvement. Induced pluripotent stem cells (iPSCs) offer an unlimited resource of cells to study pathology's underlying molecular mechanism, perform drug screening, and investigate regeneration. Using R155H/+ patients' fibroblasts, we generated IPS cells and corrected the mutation (Histidine to Arginine, H155R) to generate isogenic control cells before differentiating them into myotubes. The further proteomic analysis allowed us to identify differentially expressed proteins associated with the R155H mutation. Our results showed that R155H/+ cells were associated with dysregulated expression of several proteins involved in skeletal muscle function, cytoskeleton organization, cell signaling, intracellular organelles organization and function, cell junction, and cell adhesion. Our findings provide molecular evidence of dysfunctional protein expression in R155H/+ myotubes and offer new therapeutic targets for treating IBMPFD/ALS.

Molecular Subtypes and Tumor Microenvironment Characteristics of Small-Cell Lung Cancer Associated with Platinum-Resistance.

Although molecular subtypes of small-cell lung cancer (SCLC) have been proposed, their clinical relevance and therapeutic implications are not fully understood. Thus, we aimed to refine molecular subtypes and to uncover therapeutic targets. We classified the subtypes based on gene expression (n = 81) and validated them in our samples (n = 87). Non-SCLC samples were compared with SCLC subtypes to identify the early development stage of SCLC. Single-cell transcriptome analysis was applied to dissect the TME of bulk samples. Finally, to overcome platinum resistance, we performed drug screening of patient-derived cells and cell lines. Four subtypes were identified: the ASCL1+ (SCLC-A) subtype identified as TP53/RB-mutated non-SCLC representing the early development stage of SCLC; the immune activation (SCLC-I) subtype, showing high CD8+/PD-L1+ T-cell infiltration and endothelial-to-mesenchymal transition (EndMT); the NEUROD1 (SCLC-N) subtype, which showed neurotransmission process; and the POU2F3+ (SCLC-P) subtype with epithelial-to-mesenchymal transition (EMT). EndMT was associated with the worst prognosis. While SCLC-A/N exhibited platinum sensitivity, the EndMT signal of SCLC-I conferred platinum resistance. A BET inhibitor suppressed the aggressive angiogenesis phenotype of SCLC-I. We revealed that EndMT development contributed to a poor outcome in SCLC-I. Moreover, heterogenous TME development facilitated platinum resistance. BET inhibitors are novel candidates for overcoming platinum resistance.

Pilot study of a micro-organosphere drug screen platform to lead care in advanced breast cancer (MODEL-ABC).

1107 Background: ASCO guidelines suggest using single agent chemotherapy for patients with advanced breast cancer (ABC). Single agent chemotherapy provides modest response rates in ABC, causing patients to be exposed to unnecessary toxicity without benefit. Thus, there is an unmet clinical need to develop a clinically applicable assay to guide treatment. We recently reported the use of MicroOrganoSpheres (MOS), which are gel droplets that encapsulate tumor cells creating miniature avatars of a patient’s tumor and are amenable to high throughput dispensing and drug studies. In our current study, we evaluated the feasibility of generating and dosing MOS from ABC samples as a novel drug screen platform that led to the development and enrollment of a precision oncology trial, known as MODEL-ABC. Methods: We first performed a proof-of-concept study on 21 samples from patients with ABC and generated MOS. Drug screens were then performed on these MOS across 7 standard of care (SOC) chemotherapies commonly prescribed for ABC. These data resulted in a platform for the MODEL-ABC study that enrolled patients with ABC of any ER, PR, or HER2 subtype who were eligible for single agent chemotherapy to determine the feasibility of using MOS to predict response to therapy. In this study, biopsies from lesions ≥ 2 cm were obtained as part of SOC to generate MOS and perform drug screens. The patient subsequently received single agent chemotherapy per physicians’ choice with either carboplatin, capecitabine, paclitaxel, eribulin, liposomal doxorubicin, gemcitabine, or vinorelbine. MOS were treated using the same chemotherapy as the patient along with 1-3 alternative single agent chemotherapies. Results: We generated MOS from 19/21 samples (90% success rate) across several breast cancer subtypes. Dose response curves of MOS were successfully generated across the 7 chemotherapies with a mean turnaround time of 21±7 days validating the clinical applicability of MOS and leading to the MODEL-ABC trial. As of February 14, 2023, 4 of 15 patients have enrolled onto MODEL-ABC. All biopsies provided sufficient tissue for MOS generation, and drug screens were performed in 14-28 days across 2-4 chemotherapies. Two patients received capecitabine, one patient received eribulin, and one patient received paclitaxel. Full results of MODEL-ABC including correlation between MOS drug response and patient outcomes will be reported at the meeting. Conclusions: Our platform enables efficient establishment of MOS from ABC patient samples and allows for drug dosing studies to be performed in a clinically meaningful timeframe. Our preliminary data suggests it is feasible to obtain biopsies for MOS development and perform drug screens within 14 days. These findings provided the foundation for evaluating this technology as a potential ABC diagnostic tool and warrants further clinical development in ABC. Clinical trial information: NCT04655573 .

Abstract LB069: Predictive modeling of drug sensitivity based on the genetic dependency

Abstract Functional genetic screens have been frequently used to repurpose existing drugs or to identify new drug targets. However, the associations between hits on screens and candidate drugs have been unclear, and a manual approach to directly infer drug candidates from “druggable” candidates suffers from its laborious, ad hoc investigation and low accuracy. Here, we describe a systematic approach to explore the associations between genetic dependencies and drug sensitivity of cancer cell lines and to identify potential drug repositioning opportunities. We first developed drug sensitivity predictive models trained on genome-wide CRISPR-Cas9 knockout viability profiles and large-scale drug response screens of 4,518 drugs from DepMap. We obtained the highest predictive power from the decision-tree-based models and observed previously reported associations between gene perturbation and drug response. For example, cancer cells that are more sensitive to TP53 or MDM2 perturbation were more sensitive to MDM inhibitors, and EGFR or ERBB2 dependency strongly predicted the sensitivity of cells to EGFR inhibitors. Interestingly, for 3,260 drugs with known targets, only 1.5% of these genes were selected as top features to predict drug sensitivity, indicating that genes that are not the direct targets of drugs should be considered. In addition, we applied our models to the CRISPR-Cas9 knockout screens that target 1,805 “druggable” genes and predicted the sensitivity of cancer cells to known and novel drugs. Furthermore, we were able to validate the candidate drugs using cell viability assays. Finally, a multi-class classification deep learning model, based on the TorchDrug framework, reaches higher recall values than a decision-tree-based method but with much lower precision values. Our study provided the first systematic evaluation between large-scale gene dependency and drug responses. The machine learning predictive model provides an in-silico approach to perform drug screens from functional genetic screens. Citation Format: Bicna Song, Lumen Chao, Xiaolong Cheng, Yuan Gao, Ruocheng Shan, Wei Li. Predictive modeling of drug sensitivity based on the genetic dependency [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB069.

A novel patient-derived 3D model recapitulates mantle cell lymphoma lymph node signaling, immune profile and in vivo ibrutinib responses

Mantle cell lymphoma (MCL), a rare and aggressive B-cell non-Hodgkin lymphoma, mainly develops in the lymph node (LN) and creates a protective and immunosuppressive niche that facilitates tumor survival, proliferation and chemoresistance. To capture disease heterogeneity and tumor microenvironment (TME) cues, we have developed the first patient-derived MCL spheroids (MCL-PDLS) that recapitulate tumor oncogenic pathways and immune microenvironment in a multiplexed system that allows easy drug screening, including immunotherapies. MCL spheroids, integrated by tumor B cells, monocytes and autologous T-cells self-organize in disc-shaped structures, where B and T-cells maintain viability and proliferate, and monocytes differentiate into M2-like macrophages. RNA-seq analysis demonstrated that tumor cells recapitulate hallmarks of MCL-LN (proliferation, NF-kB and BCR), with T cells exhibiting an exhaustion profile (PD1, TIM-3 and TIGIT). MCL-PDLS reproduces in vivo responses to ibrutinib and demonstrates that combination of ibrutinib with nivolumab (anti-PD1) may be effective in ibrutinib-resistant cases by engaging an immune response with increased interferon gamma and granzyme B release. In conclusion, MCL-PDLS recapitulates specific MCL-LN features and in vivo responses to ibrutinib, representing a robust tool to study MCL interaction with the immune TME and to perform drug screening in a patient-derived system, advancing toward personalized therapeutic approaches.

Patient Derived Organoids (PDOs), Extracellular Matrix (ECM), Tumor Microenvironment (TME) and Drug Screening: State of the Art and Clinical Implications of Ovarian Cancer Organoids in the Era of Precision Medicine.

Ovarian cancer (OC) has the highest mortality rate of all gynecological malignancies due to the high prevalence of advanced stages of diagnosis and the high rate of recurrence. Furthermore, the heterogeneity of OC tumors contributes to the rapid development of resistance to conventional chemotherapy. In recent years, in order to overcome these problems, targeted therapies have been introduced in various types of tumors, including gynecological cancer. However, the lack of predictive biomarkers showing different clinical benefits limits the effectiveness of these therapies. This requires the development of preclinical models that can replicate the histological and molecular characteristics of OC subtypes. In this scenario, organoids become an important preclinical model for personalized medicine. In fact, patient-derived organoids (PDO) recapture tumor heterogeneity with the possibility of performing drug screening. However, to best reproduce the patient's characteristics, it is necessary to develop a specific extracellular matrix (ECM) and introduce a tumor microenvironment (TME), which both represent an actual object of study to improve drug screening, particularly when used in targeted therapy and immunotherapy to guide therapeutic decisions. In this review, we summarize the current state of the art for the screening of PDOs, ECM, TME, and drugs in the setting of OC, as well as discussing the clinical implications and future perspectives for the research of OC organoids.

Ex Vivo Drug Testing in Patient-derived Papillary Renal Cancer Cells Reveals EGFR and the BCL2 Family as Therapeutic Targets

BackgroundImmune checkpoint inhibitors and antiangiogenic agents are used for first-line treatment of advanced papillary renal cell carcinoma (pRCC) but pRCC response rates to these therapies are low. ObjectiveTo generate and characterise a functional ex vivo model to identify novel treatment options in advanced pRCC. Design, setting, and participantsWe established patient-derived cell cultures (PDCs) from seven pRCC samples from patients and characterised them via genomic analysis and drug profiling. Outcome measurements and statistical analysisComprehensive molecular characterisation in terms of copy number analysis and whole-exome sequencing confirmed the concordance of pRCC PDCs with the original tumours. We evaluated their sensitivity to novel drugs by generating drug scores for each PDC. Results and limitationsPDCs confirmed pRCC-specific copy number variations such as gains in chromosomes 7, 16, and 17. Whole-exome sequencing revealed that PDCs retained mutations in pRCC-specific driver genes. We performed drug screening with 526 novel and oncological compounds. Whereas exposure to conventional drugs showed low efficacy, the results highlighted EGFR and BCL2 family inhibition as the most effective targets in our pRCC PDCs. ConclusionsHigh-throughput drug testing on newly established pRCC PDCs revealed that inhibition of EGFR and BCL2 family members could be a therapeutic strategy in pRCC. Patient summaryWe used a new approach to generate patient-derived cells from a specific type of kidney cancer. We showed that these cells have the same genetic background as the original tumour and can be used as models to study novel treatment options for this type of kidney cancer.

Therapeutic drug combinations against COVID-19 obtained by employing a collaborative filtering method

The outbreak of coronavirus disease 2019 (COVID-19) has severely harmed human society and health. Because there is currently no specific drug for the treatment and prevention of COVID-19, we used a collaborative filtering algorithm to predict which traditional Chinese medicines (TCMs) would be effective in combination for the prevention and treatment of COVID-19. First, we performed drug screening based on the receptor structure prediction method, molecular docking using q-vina to measure the binding ability of TCMs, TCM formulas, and neo-coronavirus proteins, and then performed synergistic filtering based on Laplace matrix calculations to predict potentially effective TCM formulas. Combining the results of molecular docking and synergistic filtering, the new recommended formulas were analyzed by reviewing data platforms or tools such as PubMed, Herbnet, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the Guide to the Dispensing of Medicines for Clinical Evidence, and the Dictionary of Chinese Medicine Formulas, as well as medical experts' treatment consensus in terms of herbal efficacy, modern pharmacological studies, and clinical identification and typing of COVID-19 pneumonia, to determine the recommended solutions. We found that the therapeutic effect of a combination of six TCM formulas on the COVID-19 virus is the result of the overall effect of the formula rather than that of specific components of the formula. Based on this, we recommend a formula similar to that of Jinhua Qinggan Granules for the treatment of COVID-19 pneumonia. This study may provide new ideas and new methods for future clinical research. ClassificationBiological Science.