A Proof of Concept for Biomarker-Guided Targeted Therapy against Ovarian Cancer Based on Patient-Derived Tumor Xenografts

Engineering Self-Assembled Nanomedicines Composed of Clinically Approved Medicines for Enhanced Tumor Nanotherapy

The traditional nanocarriers are typically constructed to deliver anticancer agents for improving drug bioavailability and enhancing chemotherapeutic efficacy, but this strategy suffers from the critical issue of nanocarrier biosafety that hinders further clinical translation. In this work, a unique nanomedicine (PTX@ICG) has been rationally constructed by combining two clinically approved agents, i.e., paclitaxel (PTX) and indocyanine green (ICG), by a facile ultrasound-assisted self-assembly methodology. The formation of the nanostructure can effectively increase the enrichment of PTX and ICG molecules in the tumor site, and improve the utilization factor of hydrophobic PTX. Moreover, since the molecule interaction in PTX@ICG is mainly Van der Waals forces, the self-assembled structure can be spontaneously dissociated under laser irradiation and release PTX in situ to achieve safe tumor-targeted chemotherapy. Simultaneously, the released ICG can act as photothermic agents for photothermal therapy (PTT), thus combining chemotherapy and PTT to obtain an enhanced tumor nanotherapy via facile self-assembly. The synergistic chemo/photothermal tumor nanotherapy achieved the efficient tumor cell-killing effect and tumor-ablation ability, as systematically demonstrated both in vitro and in vivo. This work provides a distinct paradigm of the self-assembled nanomedicine design for effectively improving the drug bioavailability to achieve high antitumor efficacy.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Therapeutic efficacy of a MMAE-based anti-DR5 drug conjugate Oba01 in preclinical models of pancreatic cancer

Pancreatic cancer (PC) is among the most aggressive malignancies associated with a 5-year survival rate of <9%, and the treatment options remain limited. Antibody-drug conjugates (ADCs) are a new class of anticancer agents with superior efficacy and safety profiles. We studied the antitumor activity of Oba01 ADC and the mechanism underlying the targeting of death receptor 5 (DR5) in preclinical PC models. Our data revealed that DR5 was highly expressed on the plasma membrane of PC cells and Oba01 showed potent in vitro antitumor activity in a panel of human DR5-positive PC cell lines. DR5 was readily cleaved by lysosomal proteases after receptor-mediated internalization. Monomethyl auristatin E (MMAE) was then released into the cytosol to induce G2/M-phase growth arrest, cell death via apoptosis induction, and the bystander effect. Furthermore, Oba01 mediated cell death via antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity. For improved potency, we investigated the synergetic effect of Oba01 in combination with approved drugs. Oba01 combined with gemcitabine showed better antiproliferative activity than either standalone treatment. In cell- and patient-derived xenografts, Oba01 showed excellent tumoricidal activity in mono- or combinational therapy. Thus, Oba01 may provide a novel biotherapeutic approach and a scientific basis for clinical trials in DR5-expressing patients with PC.

Using Patient-Derived Xenograft (PDX) Models as a 'Black Box' to Identify More Applicable Patients for ADP-Ribose Polymerase Inhibitor (PARPi) Treatment in Ovarian Cancer: Searching for Novel Molecular and Clinical Biomarkers and Performing a Prospective Preclinical Trial

(1) The accuracy of patient-derived xenografts (PDXs) in predicting ADP-ribose polymerase inhibitor (PARPi) efficacy in ovarian cancer was tested, novel biomarkers were investigated, and whether PARPis could replace platinum-based chemotherapy as a first-line therapy was explored. (2) PDXs were reconstructed for 40 patients with ovarian cancer, and niraparib, olaparib and paclitaxel, and carboplatin (TC) sensitivity tests were conducted. Whole exon sequencing and homologous recombination deficiency (HRD) scores were performed, and patient clinical information was collected. The molecular biomarkers were identified by reverse-transcription quantitative PCR and immunoblotting. (3) Niraparib and olaparib sensitivity were tested in 26 patients and showed high consistency. Approximately half of BRCA wild-type, HRD-negative, and platinum-resistant patients may benefit from PARPis. AKT1 enrichment indicated PARPi resistance; high KRAS expression indicated PARPi sensitivity. CA125 below 10 U/mL during chemotherapy has a sensitivity and specificity similar to platinum sensitivity in predicting PARPi efficacy. Niraparib and TC sensitivity tests were performed on 23 patients, and TC showed a better response in this preclinical trial. (4) PDX can indicate individualized PARPi efficacy. Decreased CA125 levels and KRAS and ATK1 expression levels may be novel biomarkers. The preclinical evidence does not support the implementation of PARPis as the first-line treatment in an unselected population.

Harnessing preclinical models for the interrogation of ovarian cancer

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.

Patient-derived tumor models are attractive tools to repurpose drugs for ovarian cancer treatment: Pre-clinical updates

Despite advances in understanding of ovarian cancer biology, the progress in translation of research findings into new therapies is still slow. It is associated in part with limitations of commonly used cancer models such as cell lines and genetically engineered mouse models that lack proper representation of diversity and complexity of actual human tumors. In addition, the development of de novo anticancer drugs is a lengthy and expensive process. A promising alternative to new drug development is repurposing existing FDA-approved drugs without primary oncological purpose. These approved agents have known pharmacokinetics, pharmacodynamics, and toxicology and could be approved as anticancer drugs quicker and at lower cost. To successfully translate repurposed drugs to clinical application, an intermediate step of pre-clinical animal studies is required. To address challenges associated with reliability of tumor models for pre-clinical studies, there has been an increase in development of patient-derived xenografts (PDXs), which retain key characteristics of the original patient’s tumor, including histologic, biologic, and genetic features. The expansion and utilization of clinically and molecularly annotated PDX models derived from different ovarian cancer subtypes could substantially aid development of new therapies or rapid approval of repurposed drugs to improve treatment options for ovarian cancer patients.

Independent Drug Action in Combination Therapy: Implications for Precision Oncology

Combination therapies are superior to monotherapy for many cancers. This advantage was historically ascribed to the ability of combinations to address tumor heterogeneity, but synergistic interaction is now a common explanation as well as a design criterion for new combinations. We review evidence that independent drug action, described in 1961, explains the efficacy of many practice-changing combination therapies: it provides populations of patients with heterogeneous drug sensitivities multiple chances of benefit from at least one drug. Understanding response heterogeneity could reveal predictive or pharmacodynamic biomarkers for more precise use of existing drugs and realize the benefits of additivity or synergy.

DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal

Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases.

Structurally Dynamic Hydrogels for Biomedical Applications: Pursuing a Fine Balance between Macroscopic Stability and Microscopic Dynamics

Owing to their unique chemical and physical properties, hydrogels are attracting increasing attention in both basic and translational biomedical studies. Although the classical hydrogels with static networks have been widely reported for decades, a growing number of recent studies have shown that structurally dynamic hydrogels can better mimic the dynamics and functions of natural extracellular matrix (ECM) in soft tissues. These synthetic materials with defined compositions can recapitulate key chemical and biophysical properties of living tissues, providing an important means to understanding the mechanisms by which cells sense and remodel their surrounding microenvironments. This review begins with the overall expectation and design principles of dynamic hydrogels. We then highlight recent progress in the fabrication strategies of dynamic hydrogels including both degradation-dependent and degradation-independent approaches, followed by their unique properties and use in biomedical applications such as regenerative medicine, drug delivery, and 3D culture. Finally, challenges and emerging trends in the development and application of dynamic hydrogels are discussed.

Impact of ERCC1, XPF and DNA Polymerase β Expression on Platinum Response in Patient-Derived Ovarian Cancer Xenografts

Platinum resistance is an unmet medical need in ovarian carcinoma. Molecular biomarkers to predict the response to platinum-based therapy could allow patient stratification and alternative therapeutic strategies early in clinical management. Sensitivity and resistance to platinum therapy are partially determined by the tumor’s intrinsic DNA repair activities, including nucleotide excision repair (NER) and base excision repair (BER). We investigated the role of the NER proteins—ERCC1, XPF, ERCC1/XPF complex—and of the BER protein DNA polymerase β, as possible biomarkers of cisplatin (DDP) response in a platform of recently established patient-derived ovarian carcinoma xenografts (OC-PDXs). ERCC1 and DNA polymerase β protein expressions were measured by immunohistochemistry, the ERCC1/XPF foci number was detected by proximity ligation assay (PLA) and their mRNA levels by real-time PCR. We then correlated the proteins, gene expression and ERCC1/XPF complexes with OC-PDXs’ response to platinum. To the best of our knowledge, this is the first investigation of the role of the ERCC1/XPF complex, detected by PLA, in relation to the response to DDP in ovarian carcinoma. None of the proteins in the BER and NER pathways studied predicted platinum activity in this panel of OC-PDXs, nor did the ERCC1/XPF foci number. These results were partially explained by the experimental evidence that the ERCC1/XPF complex increases after DDP treatment and this possibly better associates with the cancer cells’ abilities to activate the NER pathway to repair platinum-induced damage than its basal level. Our findings highlight the need for DNA functional assays to predict the response to platinum-based therapy.