bims-instec 2022-07-03 papers

Issue of 2022‒07‒03
four papers selected by
Maria-Virginia Giolito
IRFAC/UMR-S1113 INSERM

Am J Pathol. 2022 Jun 22. pii: S0002-9440(22)00180-8. [Epub ahead of print]

Organoids as a Model System for Studying Notch Signaling in Intestinal Epithelial Homeostasis and Intestinal Cancer.

Yingtong Dou, Theresa Pizarro, Lan Zhou.

Organoid culture is an approach that allows three-dimensional growth for stem cells to self-organize and develop multicellular structures. Intestinal organoids have been widely used to study cellular or molecular processes in stem cell and cancer research. These cultures possess the ability to maintain cellular complexity as well as recapitulate many properties of the human intestinal epithelium, thereby providing an ideal in vitro model to investigate cellular and molecular signaling pathways. These include, but are not limited to, the mechanisms required for maintaining balanced populations of epithelial cells. Notch signaling is one of the major pathways of regulating stem cell functions in the gut driving proliferation and controlling cell fate determination. Notch also plays an important role in regulating tumor progression and metastasis. Understanding how Notch pathway regulates epithelial regeneration and differentiation by using intestinal organoids is critical for studying both homeostasis and pathogenesis of intestinal stem cells (ISCs) that can lead to discoveries of new targets for drug development to treat intestinal diseases. Additionally, use of patient-derived organoids can provide effective personalized medicine. In this review, we summarize the current literature regarding epithelial Notch pathways regulating intestinal homeostasis and regeneration, highlighting the use of organoid cultures and their potential therapeutic applications.

DOI: https://doi.org/10.1016/j.ajpath.2022.06.008

Nat Cancer. 2022 Jun 30.

Mex3a marks drug-tolerant persister colorectal cancer cells that mediate relapse after chemotherapy.

Colorectal cancer (CRC) patient-derived organoids predict responses to chemotherapy. Here we used them to investigate relapse after treatment. Patient-derived organoids expand from highly proliferative LGR5+ tumor cells; however, we discovered that lack of optimal growth conditions specifies a latent LGR5+ cell state. This cell population expressed the gene MEX3A, is chemoresistant and regenerated the organoid culture after treatment. In CRC mouse models, Mex3a+ cells contributed marginally to metastatic outgrowth; however, after chemotherapy, Mex3a+ cells produced large cell clones that regenerated the disease. Lineage-tracing analysis showed that persister Mex3a+ cells downregulate the WNT/stem cell gene program immediately after chemotherapy and adopt a transient state reminiscent to that of YAP+ fetal intestinal progenitors. In contrast, Mex3a-deficient cells differentiated toward a goblet cell-like phenotype and were unable to resist chemotherapy. Our findings reveal that adaptation of cancer stem cells to suboptimal niche environments protects them from chemotherapy and identify a candidate cell of origin of relapse after treatment in CRC.

DOI: https://doi.org/10.1038/s43018-022-00402-0

iScience. 2022 Jul 15. 25(7): 104542

Organoid-derived intestinal epithelial cells are a suitable model for preclinical toxicology and pharmacokinetic studies.

Yu Takahashi, Makoto Noguchi, Yu Inoue, Shintaro Sato, Makoto Shimizu, Hirotatsu Kojima, Takayoshi Okabe, Hiroshi Kiyono, Yoshio Yamauchi, Ryuichiro Sato.

Intestinal organoids are physiologically relevant tools used for cellular models. However, the suitability of organoids to examine biological functions over existing established cell lines lacks sufficient evidence. Cytochrome P450 3A4 (CYP3A4) induction by pregnane X receptor ligands, glucose uptake via sodium/glucose cotransporter 1, and microsomal triglyceride transfer protein-dependent ApoB-48 secretion, which are critical for human intestinal metabolism, were observed in organoid-derived two-dimensional cells but little in Caco-2 cells. CYP3A4 induction evaluation involved a simplified method of establishing organoids that constitutively expressed a reporter gene. Compound screening identified several anticancer drugs with selective activities toward Caco-2 cells, highlighting their characteristics as cancer cells. Another compound screening revealed a decline in N-(4-hydroxyphenyl)retinamide cytotoxicity upon rifampicin treatment in organoid-derived cells, under CYP3A4-induced conditions. This study shows that organoid-derived intestinal epithelial cells (IECs) possess similar physiological properties as intestinal epithelium and can serve as tools for enhancing the prediction of biological activity in humans.

Keywords: Cell biology; Human metabolism; Stem cells research; Tissue engineering

DOI: https://doi.org/10.1016/j.isci.2022.104542

Nat Commun. 2022 Jun 28. 13(1): 3703

Network-based machine learning approach to predict immunotherapy response in cancer patients.

JungHo Kong, Doyeon Ha, Juhun Lee, Inhae Kim, Minhyuk Park, Sin-Hyeog Im, Kunyoo Shin, Sanguk Kim.

Immune checkpoint inhibitors (ICIs) have substantially improved the survival of cancer patients over the past several years. However, only a minority of patients respond to ICI treatment (~30% in solid tumors), and current ICI-response-associated biomarkers often fail to predict the ICI treatment response. Here, we present a machine learning (ML) framework that leverages network-based analyses to identify ICI treatment biomarkers (NetBio) that can make robust predictions. We curate more than 700 ICI-treated patient samples with clinical outcomes and transcriptomic data, and observe that NetBio-based predictions accurately predict ICI treatment responses in three different cancer types-melanoma, gastric cancer, and bladder cancer. Moreover, the NetBio-based prediction is superior to predictions based on other conventional ICI treatment biomarkers, such as ICI targets or tumor microenvironment-associated markers. This work presents a network-based method to effectively select immunotherapy-response-associated biomarkers that can make robust ML-based predictions for precision oncology.

DOI: https://doi.org/10.1038/s41467-022-31535-6