Dataset Information

Honeycomb-Like Hydrogel Microspheres for 3D Bulk Construction of Tumor Models.

ABSTRACT: A two-dimensional (2D) cell culture-based model is widely applied to study tumorigenic mechanisms and drug screening. However, it cannot authentically simulate the three-dimensional (3D) microenvironment of solid tumors and provide reliable and predictable data in response to in vivo, thus leading to the research illusions and failure of drug screening. In this study, honeycomb-like gelatin methacryloyl (GelMA) hydrogel microspheres are developed by synchronous photocrosslinking microfluidic technique to construct a 3D model of osteosarcoma. The in vitro study shows that osteosarcoma cells (K7M2) cultured in 3D GelMA microspheres have stronger tumorous stemness, proliferation and migration abilities, more osteoclastogenetic ability, and resistance to chemotherapeutic drugs (DOX) than that of cells in 2D cultures. More importantly, the 3D-cultured K7M2 cells show more tumorigenicity in immunologically sound mice, characterized by shorter tumorigenesis time, larger tumor volume, severe bone destruction, and higher mortality. In conclusion, honeycomb-like porous microsphere scaffolds are constructed with uniform structure by microfluidic technology to massively produce tumor cells with original phenotypes. Those microspheres could recapitulate the physiology microenvironment of tumors, maintain cell-cell and cell-extracellular matrix interactions, and thus provide an effective and convenient strategy for tumor pathogenesis and drug screening research.

SUBMITTER: He J

PROVIDER: S-EPMC8848337 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Honeycomb-Like Hydrogel Microspheres for 3D Bulk Construction of Tumor Models.

He Jiachen J Chen Chichi C Chen Liang L Cheng Ruoyu R Sun Jie J Liu Xingzhi X Wang Lin L Zhu Can C Hu Sihan S Xue Yuan Y Lu Jian J Yang Huiling H Cui Wenguo W Shi Qin Q

Research (Washington, D.C.) 20220207

A two-dimensional (2D) cell culture-based model is widely applied to study tumorigenic mechanisms and drug screening. However, it cannot authentically simulate the three-dimensional (3D) microenvironment of solid tumors and provide reliable and predictable data in response to <i>in vivo</i>, thus leading to the research illusions and failure of drug screening. In this study, honeycomb-like gelatin methacryloyl (GelMA) hydrogel microspheres are developed by synchronous photocrosslinking microflui ...[more]

PMID: 35233536

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Project description:BackgroundGastrointestinal (GI) cancers account for more than one-third of cancer-related mortality, and the prognosis for late-stage patients remains poor. Immunotherapy has been proven to extend the survival of patients at advanced stages; however, challenges persist in patient selection and overcoming drug resistance. Tumor-infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLS) in the tumor microenvironment (TME) have been found to be associated with anti-tumor immune responses. 'Hot tumors' with high levels of infiltration tend to respond better to immune checkpoint inhibitor (ICI) therapy, making them potential biomarkers for ICI treatment.MethodsTo explore potential biomarkers for predicting immunotherapy response and prognosis in GI cancers, we downloaded the gene expression profiles of seven GI cancers from The Cancer Genome Atlas (TCGA) database and characterized their TME, classifying the samples into hot/cold tumor subgroups. Furthermore, we developed a computational framework to construct cancer-specific hot tumor classification models with only a few genes. External independent datasets and qPCR experiments were used to verify the performance of our few-gene models.ResultsWe constructed cancer-specific few-gene models to identify hot tumors for GI cancers with only two to nine genes. The results showed that B cells are important for hot tumor determination, and the identified hot tumors are significantly associated with TLS. They not only overexpress TLS marker genes but are also associated with the presence of TLS in whole-slide images. Further, a two-gene qPCR model was developed to effectively distinguish between hot and cold tumor subgroups in cholangiocarcinoma, providing an opportunity for stratifying patients with hot tumors in clinical settings.ConclusionsIn conclusion, our established few-gene models, which can be easily integrated into clinical practice, can distinguish hot and cold tumor subgroups, and may serve as potential biomarkers for predicting ICI response.

Dataset Information

Honeycomb-Like Hydrogel Microspheres for 3D Bulk Construction of Tumor Models.

Publications

Honeycomb-Like Hydrogel Microspheres for 3D Bulk Construction of Tumor Models.

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