Application of Organoid Models in Prostate Cancer Research

Complex heterogeneity is an important characteristic in the development of prostate cancer (PCa), which further leads to the failure of known therapeutic options. PCa research has been hampered by the current in vitro model systems that cannot fully reflect the biological characteristics and clinical diversity of PCa. The tumor organoid model in three-dimensional culture retains the heterogeneity of primary tumor tissues in vitro well and enables high-throughput screening and genome editing. Therefore, the establishment of a PCa organoid model that recapitulates the diverse heterogeneity observed in clinical settings is of great significance for the study of PCa. In this review, we summarize the culture conditions, establishments, and limitations of PCa organoids and further review their application for the study of pathogenesis, drug screening, mechanism of drug resistance, and individualized treatment for PCa. Additionally, we look forward to other potential developmental directions of PCa organoids, such as the interaction between prostate cancer tumor cells and their microenvironment, clinical individualized treatments, heterogeneous transformation model, tumor immunotherapy, and organoid models combined with liquid biopsy. Through this, we provide more effective preclinical experimental schemes using the PCa organoid model.

A Proteomic Atlas of Lineage and Cancer-Polarized Expression Modules in Myeloid Cells Modeling Immunosuppressive Tumor-Infiltrating Subsets

Monocytic and granulocytic myeloid-derived suppressor cells together with tumor-infiltrating macrophages constitute the main tumor-infiltrating immunosuppressive myeloid populations. Due to the phenotypic resemblance to conventional myeloid cells, their identification and purification from within the tumors is technically difficult and makes their study a challenge. We differentiated myeloid cells modeling the three main tumor-infiltrating types together with uncommitted macrophages, using ex vivo differentiation methods resembling the tumor microenvironment. The phenotype and proteome of these cells was compared to identify linage-dependent relationships and cancer-specific interactome expression modules. The relationships between monocytic MDSCs and TAMs, monocytic MDSCs and granulocytic MDSCs, and hierarchical relationships of expression networks and transcription factors due to lineage and cancer polarization were mapped. Highly purified immunosuppressive myeloid cell populations that model tumor-infiltrating counterparts were systematically analyzed by quantitative proteomics. Full functional interactome maps have been generated to characterize at high resolution the relationships between the three main myeloid tumor-infiltrating cell types. Our data highlights the biological processes related to each cell type, and uncover novel shared and differential molecular targets. Moreover, the high numbers and fidelity of ex vivo-generated subsets to their natural tumor-shaped counterparts enable their use for validation of new treatments in high-throughput experiments.

Engineered Porous/Hollow Burkholderia Pseudomallei Loading Tumor Lysate as a Vaccine

Due to its size, shape, and inherent expression of pathogen-associated molecular patterns and invasion-assistant adhesion proteins, Burkholderia pseudomallei can easily attach to, and then be internalized by, dendritic cells (DCs), leading to more efficient antigen cross-presentation if modified as carrier. Herein, we engineered Burkholderia pseudomallei as a porous/hollow carrier (SB) for loading tumor lysates (L) and CpG (C) to be used as a tumor vaccine (SB-LC). We found that the adhesion proteins of Burkholderia pseudomallei promote internalization of the SB-LC vaccine by DCs, and result in enhanced DC maturation and antigen cross-presentation. SB-LC induces robust cellular and humoral antitumor responses that synergistically inhibit tumor growth with minimal adverse side effects in several tumor models. Moreover, SB-LC vaccination reverses the immunosuppressive tumor microenvironment, apparently as a result of CD8+-induced tumor ferroptosis. Thus, SB-LC is a potential model tumor vaccine for translating into a clinically viable treatment option.

A Disintegrin and Metalloprotease 12 Promotes Tumor Progression by Inhibiting Apoptosis in Human Colorectal Cancer

A disintegrin and metalloprotease 12 (ADAM12) has been implicated in cell growth, tumor formation, and metastasis. Therefore, we evaluated the role of ADAM12 in colorectal cancer (CRC) progression and prognosis, and elucidated whether targeted downregulation of ADAM12 could lead to therapeutic sensitization. The effect of ADAM12 on tumor cell behavior was assessed in CRC cell lines, CRC tissues, and a mouse xenograft model. ADAM12 overexpression enhanced proliferation, inhibited apoptosis, and acted as positive regulator of cell cycle progression in CRC cells. Phosphorylation of PTEN was decreased and that of Akt was increased by ADAM12 overexpression. These results were reversed upon ADAM12 knockdown. ADAM12 overexpression was significantly associated with the cancer stage, depth of invasion, lymph node metastasis, distant metastasis, and poor survival in CRC patients. In a mouse xenograft model, tumor area, volume, and weight were significantly greater for the ADAM12-pcDNA6-myc-transfected group than for the empty-pcDNA6-myc-transfected group, and significantly lower for the ADAM12-pGFP-C-shLenti-transfected group than for the scrambled pGFP-C-shLenti-transfected group. In conclusion, ADAM12 overexpression is essential for the growth and progression of CRC. Furthermore, ADAM12 knockdown reveals potent anti-tumor activity in a mouse xenograft model. Thus, ADAM12 may serve as a promising biomarker and/or therapeutic target in CRC.

ТНЕ RELATIONSHIP BETWEEN A MALIGNANT TUMOR GROWTH AND PECULIARITIES OF BEHAVIOR OF LABORATORY ANIMALS

Laboratory rats' basic behavioral characteristics were studied in the experimental "Open field" test. A rat renal carcinoma cell line RA was used to model tumor growth. Free radical processes were assessed in normal condi-tions of organism and with tumor progression. Correla-tions were revealed between the levels of behavioral ac-tivity, the intensity of tumor growth, and free radical pro-cesses. The obtained data will serve as the basis for the development of risk management systems for the oncology and development of oncopathology in the population.

Heterotypic tumor models through freeform printing into photostabilized granular microgels

The tissue microenvironment contains a complex assortment of multiple cell types, matrices, and vessel structures, which is difficult to reconstruct in vitro. Here, we demonstrate model tumor microenvironments formed through...

Study on Development of Composite Hydrogels With Tunable Structures and Properties for Tumor-on-a-Chip Research

A major factor for developing new tumor models is to recreate a proper three-dimensional environment for 3D tumors culture. In this 3D microenvironment, extracellular matrices play important roles in regulation of hallmark features of cancer through biochemical and mechanical signals. The fabrication of a mechanical and biophysical controllable hydrogel, while sharing similarities with Matrigel in cancer invasiveness evaluation, is an urgent but unmet need. In this study, we developed a hybrid hydrogel system composed of GelMA and hydrolyzed collagen to model tumor micro-environment and tested with several cancer cells with different origin and characteristics. This hydrogel possesses a well-ordered homogenous microstructure, excellent permeability and an adjustable mechanical stiffness. This hydrogel demonstrated similar properties as Matrigel in tumor spheroids culture and 3D tumor invasiveness studies. It was further applied in a Tumor-on-a-Chip system with 3D-bioprinting. Our research demonstrated this hydrogel's effectiveness in tumor 3D culture, and its potential to replace Matrigel in cancer invasiveness evaluation.

Modeling collaterally sensitive drug cycles: shaping heterogeneity to allow adaptive therapy

In previous work, we focused on the optimal therapeutic strategy with a pair of drugs which are collaterally sensitive to each other, that is, a situation in which evolution of resistance to one drug induces sensitivity to the other, and vice versa. [1] Here, we have extended this exploration to the optimal strategy with a collaterally sensitive drug sequence of an arbitrary length, N(≥ 2). To explore this, we have developed a dynamical model of sequential drug therapies with N drugs. In this model, tumor cells are classified as one of N subpopulations represented as {Ri|i = 1,2,…, N}. Each subpopulation, Ri, is resistant to ‘Drug i’ and each subpopulation, Ri–1 (or RN, if i = 1), is sensitive to it, so that Ri increases under ‘Drug i’ as it is resistant to it, and after drug-switching, decreases under ‘Drug i + 1’ as it is sensitive to that drug(s).Similar to our previous work examining optimal therapy with two drugs, we found that there is an initial period of time in which the tumor is ‘shaped’ into a specific makeup of each subpopulation, at which time all the drugs are equally effective . After this shaping period, all the drugs are quickly switched with duration relative to their efficacy in order to maintain each subpopulation, consistent with the ideas underlying adaptive therapy. [2, 3]Additionally, we have developed methodologies to administer the optimal regimen under clinical or experimental situations in which no drug parameters and limited information of trackable populations data (all the subpopulations or only total population) are known. The therapy simulation based on these methodologies showed consistency with the theoretical effect of optimal therapy.

RNF43 and PWWP2B inhibit cancer cell proliferation and are predictive or prognostic biomarker for FDA-approved drugs in patients with advanced gastric cancer

Background The characterization of gastric cancer has necessitated the development of new therapeutics as well as the identification of prognostic markers to predict the response to novel drugs. In our study, we have performed RNA sequencing analysis on gastric cancer tissues that decreased levels of RNF43 and PWWP2B were significantly associated with recurrence (11/11, 100%, P < 0.001). Therefore, we investigated the screening of 1,449 FDA-approved drugs in HAP1, HAP1 RNF43 KO and HAP1 PWWP2B KO cells. Methods We demonstrated that RNF43 KO and PWWP2B KO cells showed significantly increased proliferation and migration abilities. Next, we investigated the inhibitory effects of 1,449 drugs in HAP1, HAP1 RNF43 KO and HAP1 PWWP2B KO cells. Results Among these FDA-approved drugs, three drugs (docetaxel trihydrate, pelitinib and uprosertib) showed strong inhibitory effects in RNF43 KO cells and PWWP2B KO cells. In RNF43 and PWWP2B down-regulated MKN45 xenograft model, tumor volumes were significantly reduced in the docetaxel trihydrate, uprosertib or pelitinib-treated group. Our data demonstrated that RNF43 and PWWP2B are a biomarker that predict recurrence of gastric cancer. Conclusion Our findings suggest that docetaxel trihydrate, uprosertib and pelitinib could be used as novel therapeutic agents for the prevention and treatment of gastric cancer with an aberrant decrease in RNF43 and PWWP2B expression.