DRAP: a toolbox for drug response analysis and visualization tailored for preclinical drug testing on patient-derived xenograft models

Transcriptomic analysis of the immune response to in vivo gene electrotransfer in colorectal cancer

Gene electrotransfer (GET) has recently emerged as an effective nonviral approach for plasmid DNA (pDNA) delivery in gene therapy for several pathologies, including cancer. Multiple mechanisms have been identified that influence cell biology after GET, as electroporation significantly increases pDNA uptake and immunogenicity, which may directly influence target cell death. However, the molecular effects of in vivo electroporation-mediated DNA delivery have yet to be fully elucidated. In this study, we evaluated the transcriptomes of murine colorectal tumors treated with two protocols, short- and high-voltage (SHV) electric pulses or an adapted high-voltage-low-voltage (HV-LV) pulse protocol, both of which are used for reversible electroporation. Although no significant differences in clinical outcomes were observed, variations in intratumoral macrophage infiltration were reported between the two treatment methods. Transcriptomic analysis revealed that apoptosis is a predominant mode of cell death after GET by SHV pulses, whereas GET by HV-LV pulses is associated with immunogenic necrotic pathways as well as the activation of both the innate and adaptive immune response. We demonstrated that specific pulse parameters can induce distinct immunomodulatory profiles in the tumor microenvironment; therefore, these aspects should be considered carefully when selecting the most suitable GET-based approach for antitumor immunization.

Targeted redox-responsive peptide for arterial chemoembolization therapy of orthotropic hepatocellular carcinoma

OBJECTIVE

Transcatheter Arterial Chemoembolization (TACE) is the first choice for the treatment of advanced-stage hepatocellular carcinoma (HCC). However, TACE suffers from a lack of specificity and rapid drug release. Herein, a targeted redox-responsive peptide (TRRP) was synthesized and used as a carrier of doxorubicin (DOX) to enhance the efficacy of TACE through tumor cells targeting and controlled drug release.

METHODS

TRRP has a high loading capacity of DOX and a sensitive drug release behavior at high glutathione (GSH) concentration. Moreover, TRRP could bind to the transferrin receptor on the surface of tumor cells, which enhanced the efficacy of TACE and reduced side effects of TACE. TACE with TRRP@DOX dispersed in lipiodol shows an enhanced therapeutic outcome compared to the treatment with DOX + lipiodol emulsion in orthotopic rat HCC models.

RESULTS

TRRP has a high loading capacity of DOX and a sensitive drug release behavior at GSH concentration. Moreover, TRRP could bind to the transferrin receptor on the surface of tumor cells, which enhanced the efficacy of TACE and reduced side effects of TACE. TACE with TRRP@DOX dispersed in lipiodol shows an enhanced therapeutic outcome compared to the treatment with DOX + lipiodol emulsion in orthotopic rat HCC models.

CONCLUSIONS

This study demonstrated that TRRP was a promising therapeutic agent for enhancing TACE therapy for HCC treatment.

Assessment of Patient-Derived Xenograft Growth and Antitumor Activity: The NCI PDXNet Consensus Recommendations

Although patient-derived xenografts (PDX) are commonly used for preclinical modeling in cancer research, a standard approach to in vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating the comparison of different studies and determination of whether a PDX experiment has produced evidence needed to consider a new therapy promising. We present consensus recommendations for assessment of PDX growth and antitumor activity, providing public access to a suite of tools for in vivo growth analyses. We expect that harmonizing PDX study design and analysis and assessing a suite of analytical tools will enhance information exchange and facilitate identification of promising novel therapies and biomarkers for guiding cancer therapy.

Functional analysis of recurrent CDC20 promoter variants in human melanoma

Small nucleotide variants in non-coding regions of the genome can alter transcriptional regulation, leading to changes in gene expression which can activate oncogenic gene regulatory networks. Melanoma is heavily burdened by non-coding variants, representing over 99% of total genetic variation, including the well-characterized TERT promoter mutation. However, the compendium of regulatory non-coding variants is likely still functionally under-characterized. We developed a pipeline to identify hotspots, i.e. recurrently mutated regions, in melanoma containing putatively functional non-coding somatic variants that are located within predicted melanoma-specific regulatory regions. We identified hundreds of statistically significant hotspots, including the hotspot containing the TERT promoter variants, and focused on a hotspot in the promoter of CDC20. We found that variants in the promoter of CDC20, which putatively disrupt an ETS motif, lead to lower transcriptional activity in reporter assays. Using CRISPR/Cas9, we generated an indel in the CDC20 promoter in human A375 melanoma cell lines and observed decreased expression of CDC20, changes in migration capabilities, increased growth of xenografts, and an altered transcriptional state previously associated with a more proliferative and less migratory state. Overall, our analysis prioritized several recurrent functional non-coding variants that, through downregulation of CDC20, led to perturbation of key melanoma phenotypes.

Myriocin suppresses tumor growth by modulating macrophage polarization and function through the PI3K/Akt/mTOR pathway

Macrophages within the tumor microenvironment (TME), referred to as tumor-associated macrophages (TAMs), are involved in various aspects of tumor progression including initiation, angiogenesis, metastasis, immunosuppression, and resistance to therapy. Myriocin, a natural compound isolated from Mycelia sterilia, is an immunosuppressant that inhibits tumor growth and angiogenesis. However, the mechanisms underlying the effects of myriocin on TAMs and TAM-mediated tumor growth have not yet been elucidated. In this study, we determined the effects of myriocin on TAMs and the underlying mechanism in vitro and in vivo. Myriocin significantly suppressed monocyte-macrophage differentiation and M2 polarization of macrophages but not M1 polarization. In addition, myriocin inhibited the expression of anti-inflammatory cytokines and secretion of proangiogenic factors, such as vascular endothelial growth factor, in M2 macrophages as well as M2-induced endothelial cell permeability. Myriocin also inhibited the PI3K/Akt/mTOR signaling pathway in M2 macrophages. Myriocin reduced the population of M2-like TAMs within the tumor tissue of a mouse allograft tumor model but not that of M1-like TAMs. Moreover, combined treatment with myriocin and cisplatin synergistically suppressed tumor growth and enhanced survival rate in mice by reducing the population of M2-like TAMs. Overall, these results suggest that myriocin inhibits tumor growth by remodeling the TME through suppression of differentiation and polarization of M2-like TAMs via the PI3K/Akt/mTOR signaling pathway.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Optimizing Drug Response Study Design in Patient-Derived Tumor Xenografts

Patient-derived tumor xenograft (PDX) models were used to evaluate the effectiveness of preclinical anticancer agents. A design using 1 mouse per patient per drug (1 × 1 × 1) was considered practical for large-scale drug efficacy studies. We evaluated modifiable parameters that could increase the statistical power of this design based on our consolidated PDX experiments. Real studies were used as a reference to investigate the relationship between statistical power with treatment effect size, inter-mouse variation, and tumor measurement frequencies. Our results showed that large effect sizes could be detected at a significance level of .2 or .05 under a 1 × 1 × 1 design. We found that the minimum number of mice required to achieve 80% power at an alpha level of .05 under all situations explored was 21 mice per group for a small effect size and 5 mice per group for a medium effect size.

Targeting BCL-XL in fibrolamellar hepatocellular carcinoma

Fibrolamellar hepatocellular carcinoma (FLC) is a rare and often lethal liver cancer with no proven effective systemic therapy. Inhibition of the antiapoptotic protein BCL-XL was found to synergize with a variety of systemic therapies in vitro using cells dissociated from patient-derived xenografts (PDX) of FLC or cells dissociated directly from surgical patient resections. As BCL-XL is physiologically expressed in platelets, prior efforts to leverage this vulnerability in other cancers have been hampered by severe thrombocytopenia. To overcome this toxicity, we treated FLC models with DT2216, a proteolysis targeting chimera (PROTAC) that directs BCL-XL for degradation via the von Hippel-Lindau (VHL) E3 ligase, which is minimally expressed in platelets. The combination of irinotecan and DT2216 in vitro on cells directly acquired from patients or in vivo using several xenografts derived from patients with FLC demonstrated remarkable synergy and at clinically achievable doses not associated with significant thrombocytopenia.

In vivo antitumor activity study of targeted chlorambucil-loaded nanolipid carrier for breast cancer

Chlorambucil (CBL) is an efficient anticancer drug. It is a lipophilic agent with serious adverse effects. The objective of this study was to formulate a CBL-loaded nanolipid carrier and target breast cancer using folic acid as a targeting probe. Characterizations of the optimum formulation were 79.9±3% EE after the addition of 4mg CBL, 119±6nm particle size which is considered appropriate for parenteral use, 0.3±0.02 PDI, -42±1mV ZP that stabilized the formulation. Tumor volume, body weight, and tumor mass weight were recorded to evaluate tumor volume doubling time, tumor growth inhibition rate, and systemic toxicity. It appeared there was a significant antitumor activity of targeted formulation compared with non-targeted one and free CBL. Moreover, the systemic toxicity was less after body weight evaluation concerning the targeted formulation when compared with other formulations.

Prediction of Radiation Pneumonitis Using Genome-Scale Flux Analysis of RNA-Seq Derived From Peripheral Blood

Purpose: Radiation pneumonitis (RP) frequently occurs during a treatment course of chest radiotherapy, which significantly reduces the clinical outcome and efficacy of radiotherapy. The ability to easily predict RP before radiotherapy would allow this disease to be avoided.

Methods and Materials: This study recruited 48 lung cancer patients requiring chest radiotherapy. For each participant, RNA sequencing (RNA-Seq) was performed on a peripheral blood sample before radiotherapy. The RNA-Seq data was then integrated into a genome-scale flux analysis to develop an RP scoring system for predicting the probability of occurrence of RP. Meanwhile, the clinical information and radiation dosimetric parameters of this cohort were collected for analysis of any statistical associations between these parameters and RP. A non-parametric rank sum test showed no significant difference between the predicted results from the RP score system and the clinically observed occurrence of RP in this cohort.

Results: The results of the univariant analysis suggested that the tumor stage, exposure dose, and bilateral lung dose of V5 and V20 were significantly associated with the occurrence of RP. The results of the multivariant analysis suggested that the exposure doses of V5 and V20 were independent risk factors associated with RP and a level of RP ≥ 2, respectively. Thus, our results indicate that our RP scoring system could be applied to accurately predict the risk of RP before radiotherapy because the scores were highly consistent with the clinically observed occurrence of RP.

Conclusion: Compared with the standard statistical methods, this genome-scale flux-based scoring system is more accurate, straightforward, and economical, and could therefore be of great significance when making clinical decisions for chest radiotherapy.

A Novel Monoclonal Antibody Targeting Cancer-Specific Plectin Has Potent Antitumor Activity in Ovarian Cancer

Cancer-specific plectin (CSP) is a pro-tumorigenic protein selectively expressed on the cell surface of major cancers, including ovarian cancer (OC). Despite its assessable localization, abundance, and functional significance, the therapeutic efficacy of targeting CSP remains unexplored. Here, we generated and investigated the anticancer effects of a novel CSP-targeting monoclonal antibody, 1H11, in OC models. Its therapeutic efficacy as a monotherapy and in combination with chemotherapy was evaluated in vitro using two OC cell lines and in vivo by a subcutaneous ovarian cancer model. 1H11 demonstrated rapid internalization and high affinity and specificity for both human and murine CSP. Moreover, 1H11 induced significant and selective cytotoxicity (EC₅₀ = 260 nM), G0/G1 arrest, and decreased OC cell migration. Mechanistically, these results are associated with increased ROS levels and reduced activation of the JAK2-STAT3 pathway. In vivo, 1H11 decreased Ki67 expression, induced 65% tumor growth inhibition, and resulted in 30% tumor necrosis. Moreover, 1H11 increased chemosensitivity to cisplatin resulting in 60% greater tumor growth inhibition compared to cisplatin alone. Taken together, CSP-targeting with 1H11 exhibits potent anticancer activity against ovarian cancer and is deserving of future clinical development.

A reliable method to determine which candidate chemotherapeutic drugs effectively inhibit tumor growth in patient-derived xenografts (PDX) in single mouse trials

PURPOSE

We report on a statistical method for grouping anti-cancer drugs (GRAD) in single mouse trials (SMT). The method assigns candidate drugs into groups that inhibit or do not inhibit tumor growth in patient-derived xenografts (PDX). It determines the statistical significance of the group assignments without replicate trials of each drug.

METHODS

The GRAD method applies a longitudinal finite mixture model, implemented in the statistical package PROC TRAJ, to analyze a mixture of tumor growth curves for portions of the same tumor in different mice, each single mouse exposed to a different drug. Each drug is classified into an inhibitory or non-inhibitory group. There are several advantages to the GRAD method for SMT. It determines that probability that the grouping is correct, uses the entire longitudinal tumor growth curve data for each drug treatment, can fit different shape growth curves, accounts for missing growth curve data, and accommodates growth curves of different time periods.

RESULTS

We analyzed data for 22 drugs for 18 human colorectal tumors provided by researchers in a previous publication. The GRAD method identified 18 drugs that were inhibitory against at least one tumor, and 10 tumors for which there was at least one inhibitory drug. Analysis of simulated data indicated that the GRAD method has a sensitivity of 84% and a specificity of 98%.

CONCLUSION

A statistical method, GRAD, can group anti-cancer drugs into those that are inhibitory and those that are non-inhibitory in single mouse trials and provide probabilities that the grouping is correct.