multiplexed-live-cell-imaging-for-drug-responses-patient-derived

Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell ...

University of New Mexico Comprehensive Cancer Center, University of New Mexico Health Sciences Center

Histone deacetylase (HDAC) inhibitors and proteasome inhibitors have been approved by the FDA for the treatment of multiple myeloma and lymphoma, respectively, but have not achieved similar activity as single agents in solid tumors. Preclinical studies have demonstrated the activity of the combination of an HDAC inhibitor and a proteasome inhibitor in a variety of tumor models. However, the mechanisms underlying sensitivity and resistance to this combination are not well-understood. This study explores the role of autophagy in adaptive resistance to dual HDAC and proteasome inhibition. Studies focus on ovarian and endometrial gynecologic cancers, two diseases with high mortality and a need for novel treatment approaches. We found that nanomolar concentrations of the proteasome inhibitor ixazomib and HDAC inhibitor romidepsin synergistically induce cell death in the majority of gynecologic cancer cells and patient-derived organoid (PDO) models created using endometrial and ovarian patient tumor tissue. However, some models were not sensitive to this combination, and mechanistic studies implicated autophagy as the main mediator of cell survival in the context of dual HDAC and proteasome inhibition. Whereas the combination of ixazomib and romidepsin reduces autophagy in sensitive gynecologic cancer models, autophagy is induced following drug treatment of resistant cells. Pharmacologic or genetic inhibition of autophagy in resistant cells reverses drug resistance as evidenced by an enhanced anti-tumor response both in vitro and in vivo. Taken together, our findings demonstrate a role for autophagic-mediated cell survival in proteasome inhibitor and HDAC inhibitor-resistant gynecologic cancer cells. These data reveal a new approach to overcome drug resistance by inhibiting the autophagy pathway.

Blocking autophagy overcomes resistance to dual histone deacetylase and proteasome inhibition in gynecologic cancer.

The status of p53 in a tumor can be inferred by next-generation sequencing (NGS) or by immunohistochemistry (IHC). We examined the association between p53 IHC and sequence and whether p53 IHC alone, or integrated with  NGS, predicts the outcome.

 Sequencing and p53 Immunohistochemistry Predict Outcomes When Bevacizumab Is Added to Frontline Chemotherapy in Endometrial Cancer: An NRG Oncology/Gynecologic Oncology Group Study.

Most endometrial cancers express the hormone receptor estrogen receptor alpha (ER) and are driven by excess estrogen signaling. However, evaluation of the estrogen response in endometrial cancer cells has been limited by the availability of hormonally responsive in vitro models, with one cell line, Ishikawa, being used in most studies. Here, we describe a novel, adherent endometrioid endometrial cancer (EEC) cell line model, HCI-EC-23. We show that HCI-EC-23 retains ER expression and that ER functionally responds to estrogen induction over a range of passages. We also demonstrate that this cell line retains paradoxical activation of ER by tamoxifen, which is also observed in Ishikawa and is consistent with clinical data. The mutational landscape shows that HCI-EC-23 is mutated at many of the commonly altered genes in EEC, has relatively few copy-number alterations, and is microsatellite instable high (MSI-high). In vitro proliferation of HCI-EC-23 is strongly reduced upon combination estrogen and progesterone treatment. HCI-EC-23 exhibits strong estrogen dependence for tumor growth in vivo and tumor size is reduced by combination estrogen and progesterone treatment. Molecular characterization of estrogen induction in HCI-EC-23 revealed hundreds of estrogen-responsive genes that significantly overlapped with those regulated in Ishikawa. Analysis of ER genome binding identified similar patterns in HCI-EC-23 and Ishikawa, although ER exhibited more bound sites in Ishikawa. This study demonstrates that HCI-EC-23 is an estrogen- and progesterone-responsive cell line model that can be used to study the hormonal aspects of endometrial cancer.

Characterization of HCI-EC-23 a novel estrogen- and progesterone-responsive endometrial cancer cell line.

Mutations in the receptor tyrosine kinase gene fibroblast growth factor receptor 2 (FGFR2) occur at a high frequency in endometrial cancer (EC) and have been linked to advanced and recurrent disease. However, little is known about how these mutations drive carcinogenesis.

FGFR2 mutations promote endometrial cancer progression through dual engagement of EGFR and Notch signalling pathways.

Endometrial cancer is the most common gynecological malignancy worldwide and unfortunately has a much higher mortality rate in Black women compared with White women. Many potential factors contribute to these mortality rates, including the underlying effects of systemic and interpersonal racism. Furthermore, other trends in medicine have potential links to these rates including participation in clinical trials, hormone therapy, and pre-existing health conditions. Addressing the high incidence and disparate mortality rates in endometrial cancer requires novel methods, such as nanoparticle-based therapeutics. These therapeutics have been growing in increasing prevalence in pre-clinical development and have far-reaching implications in cancer therapy. The rigor of pre-clinical studies is enhanced by the likeness of the model to the human body. In systems for 3D cell culture, for example, the extracellular matrix mimics the tumor more closely. The increasing emphasis on precision medicine can be applied to cancer using nanoparticle-based methods and applied to pre-clinical models by using patient-derived model data. This review highlights the intersections of nanomedicine, precision medicine, and racial disparities within endometrial cancer and provides insights into reducing health disparities using recent scientific advances on the nanoscale.

Particles and Prejudice: Nanomedicine Approaches to Reducing Health Disparities in Endometrial Cancer.

Progesterone prevents development of endometrial cancers through its receptor (PR) although the molecular mechanisms have yet to be fully characterized. In this study, we performed a global analysis of gene regulation by progesterone using human endometrial cancer cells that expressed PR endogenously or exogenously. We found progesterone strongly inhibits multiple components of the platelet derived growth factor receptor (PDGFR), Janus kinase (JAK), signal transducer and activator of transcription (STAT) pathway through PR. The PDGFR/JAK/STAT pathway signals to control numerous downstream targets including AP-1 transcription factors Fos and Jun. Treatment with inhibitors of the PDGFR/JAK/STAT pathway significantly blocked proliferation in multiple novel patient-derived organoid models of endometrial cancer, and activation of this pathway was found to be a poor prognostic signal for the survival of patients with endometrial cancer from The Cancer Genome Atlas. Our study identifies this pathway as central to the growth-limiting effects of progesterone in endometrial cancer and suggests that inhibitors of PDGFR/JAK/STAT should be considered for future therapeutic interventions.

Global expression analysis of endometrial cancer cells in response to progesterone identifies new therapeutic targets.

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to simultaneously quantitate cell health and apoptosis. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Article	Year
Blocking autophagy overcomes resistance to dual histone deacetylase and proteasome inhibition in gynecologic cancer. Cell death & disease\| PubMed ID: 35039480	2022
Sequencing and p53 Immunohistochemistry Predict Outcomes When Bevacizumab Is Added to Frontline Chemotherapy in Endometrial Cancer: An NRG Oncology/Gynecologic Oncology Group Study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology\| PubMed ID: 35658479	2022
Characterization of HCI-EC-23 a novel estrogen- and progesterone-responsive endometrial cancer cell line. Scientific reports\| PubMed ID: 36396974	2022
FGFR2 mutations promote endometrial cancer progression through dual engagement of EGFR and Notch signalling pathways. Clinical and translational medicine\| PubMed ID: 37165578	2023
Particles and Prejudice: Nanomedicine Approaches to Reducing Health Disparities in Endometrial Cancer. Small (Weinheim an der Bergstrasse, Germany)\| PubMed ID: 37312613	2023
Global expression analysis of endometrial cancer cells in response to progesterone identifies new therapeutic targets. The Journal of steroid biochemistry and molecular biology\| PubMed ID: 37716459	2023
Multiplexed live-cell imaging for drug responses in patient-derived organoid models of cancer. bioRxiv : the preprint server for biology\| PubMed ID: 38014133	2023

Kimberly K. Leslie

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