Apoptosis mapping in space and time of 3D tumor ecosystems reveals transmissibility of cytotoxic cancer death

Abstract

The emerging tumor-on-chip (ToC) approaches allow to address biomedical questions out of reach with classical cell culture techniques: in biomimetic 3D hydrogels they partially reconstitute ex vivo the complexity of the tumor microenvironment and the cellular dynamics involving multiple cell types (cancer cells, immune cells, fibroblasts, etc.). However, a clear bottleneck is the extraction and interpretation of the rich biological information contained, sometime hidden, in the cell co-culture videos. In this work, we develop and apply novel video analysis algorithms to automatically measure the cytotoxic effects on human cancer cells (lung and breast) induced either by doxorubicin chemotherapy drug or by autologous tumor-infiltrating cytotoxic T lymphocytes (CTL). A live fluorescent dye (red) is used to selectively pre-stain the cancer cells before co-cultures and a live fluorescent reporter for caspase activity (green) is used to monitor apoptotic cell death. The here described open-source computational method, named STAMP (spatiotemporal apoptosis mapper), extracts the temporal kinetics and the spatial maps of cancer death, by localizing and tracking cancer cells in the red channel, and by counting the red to green transition signals, over 2–3 days. The robustness and versatility of the method is demonstrated by its application to different cell models and co-culture combinations. Noteworthy, this approach reveals the strong contribution of primary cancer-associated fibroblasts (CAFs) to breast cancer chemo-resistance, proving to be a powerful strategy to investigate intercellular cross-talks and drug resistance mechanisms. Moreover, we defined a new parameter, the ‘potential of death induction’, which is computed in time and in space to quantify the impact of dying cells on neighbor cells. We found that, contrary to natural death, cancer death induced by chemotherapy or by CTL is transmissible, in that it promotes the death of nearby cancer cells, suggesting the release of diffusible factors which amplify the initial cytotoxic stimulus.

Deep-Manager: a versatile tool for optimal feature selection in live-cell imaging analysis

“…In this case study, we compared the individual discrimination performance of handcrafted features GFP derived in terms of the p-value of the Student t-test with and without the selection using DM-tool. For the task of characterizing and discriminating between natural and chemotherapy-induced death, we selected four independent videos for each condition (8 in total), with a duration of 70 h, acquired at a time point of 1 h. We then automatically identified 431 crops, each containing a dying cell (i.e., a cell that is going to die within 70 h) through the use of the STAMP code 10 , downloadable at https://cloudstore.bee.uniroma2.it/index.php/s/LEpHYTsPnDj4Ajt (password: STAMP2021).…”

“…To demonstrate the usefulness of DM, we apply the software to five distinct case studies. Case study #1: Fluorescence microscopy videos of chemotherapy-induced death of MDA-MB 231 breast cancer cells in the presence of a green fluorescent apoptosis reporter 10 . Case study #2: TL microscopy videos of PC3 human prostate cancer cells, moving in a 2D environment in the presence of the chemotherapeutic drug etoposide 11 .…”

“…Case study #3: phase-contrast TL microscopy videos of immune cells moving in a 3D collagen gel inside microfluidic tumor-on-chip devices that mimic the tumor microenvironment 12 . Case study #4: fluorescence microscopy videos of cancer cells forced to undergo apoptosis by cytotoxic T cells in 3D tumor-on-chip ; 10 Case study #5: Phase contrast TL microscopy static images of BT-474 breast cancer cells from the recently presented public dataset LIVECell 13 . In the following, we will refer to each case study simply using the case study number.…”

Isolation and characterization of head and neck cancer-derived peritumoral and cancer-associated fibroblasts

“…The different characteristics of CAFs and PtFs may be the consequence of their different spatial location. For example, tumor cell apoptosis within the tumor leads to a less organized and more loose ECM structure and, thus, provides more space for them to grow ( 30 , 45 ). The central area of the tumor often lacks oxygen and nutrients, which may cause CAFs to adopt a higher doubling time to adapt to hypoxia and scarce nutrients ( 46 ).…”

Clinical Application Perspectives of Lung Cancers 3D Tumor Microenvironment Models for In Vitro Cultures

“…Bioprinting technology gives a compatible platform to create tumor-on-chip, which includes tumor stromal elements and is suitable for obtaining multicellular tumor-spheroids on its surface [120]. Veith et al developed a spatiotemporal apoptosis mapper based on the tumor-on-chip model for monitoring tumor cell death under chemotherapy or induced by TILs [121]. To imitate metastasis, Ramamoorthy et al developed a metastatic tumor-on-dish model, which offers the potential to analyze cell phenotypes within DNA pharmacogenetics sensitivity [122].…”