H2020Индивидуална стипендия2021–2022

SpatialOrganoids · Profiling the emergence of phenotypic heterogeneity in breast cancer organoids

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2021-01-01 → 2022-12-31
Финансиране от ЕС: 191 149 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Органоидите на рак на гърдата се използват, за да се проследи как раковите клетки се различават по вид и разположение. Разбирането на тези разлики помага за подобряване на терапиите и предвиждане на появата на клетки, устойчиви на лекарства.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Profiling the emergence of phenotypic heterogeneity in breast cancer organoids

Breast cancer shows the highest cancer incidence in women and extensive research focused on elucidating the mechanisms for the onset and progression of the disease. On a cellular level, breast cancer is characterized by extensive intra- and inter-patient heterogeneity in cellular and molecular phenotypes. Intra-tumor heterogeneity often limits the effect of cancer therapies due to the outgrowths of therapy-resistant clones of cancer cells. Inter-patient heterogeneity on the other hand limits the broad applicability of therapies across patient groups and personalized cancer therapies need to be developed. To date, the molecular events on a cell-to-cell level that lead to the emergence of tumor heterogeneity are largely unknown. Understanding the mechanisms of how intra- and inter-tumor heterogeneity forms will open avenues to improving cancer therapies against breast cancer which forms 13% of all new cancer cases worldwide. The overall objectives of the project include the generation of breast cancer model systems, specifically breast cancer organoids, to profile the emergence of phenotypic heterogeneity. I use imaging mass cytometry (IMC) as a type of multi-parametric microscopy technology to study phenotypic changes over time (the growths of organoids) and space (location differences in cellular phenotypes). Finally, I perturb the growth of organoids using common cancer drugs to study their effect on the emergence of phenotypic heterogeneity. The final dataset allows me to predict possible clonal outgrowths of cancer cells within breast cancer organoids and derive targeted therapies. The project resulted in datasets of three organoid lines treated with seven anti-cancer drugs over time periods of two to four weeks. I observed heterogeneous expression patterns between organoid lines and between time-points while treatment often had an “all or nothing” effect on organoid growth either inducing growth arrest or no phenotypic changes at all. In parallel, the project resulted in an extensive computational framework to support in-depth analysis of multiplexed imaging data.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Cell-to-cell heterogeneity in biological systems has been broadly studied in unicellular organisms and mammals. Furthermore, non-genetic, in addition to genetic heterogeneity has been recently proposed to support tumour growth and to induce resistance to cancer therapy. However, the molecular events on a spatial and temporal level that lead to the emergence of tumour heterogeneity are largely unknown. To address this question, I will study breast cancer, which shows the highest cancer incidence in women and is characterised by extensive intra- and inter-patient heterogeneity in cellular and molecular phenotypes. As model system, I select 3D organoid cultures, which are gaining popularity in cancer research due to their ability to reconstruct tumour-like molecular features and to recapitulate treatment response. Here, I propose experimental and computational time-course analyses of breast cancer organoids to understand molecular and spatial determinants that underlie the emergence of heterogeneity in cancer cell phenotypes. On the experimental side, I will use imaging mass cytometry and perturbation experiments to capture and validate spatio-temporal changes in cellular phenotypes, interactions and signalling networks. Statistical modelling will quantify dynamic changes in phenotypic heterogeneity over the time-course of organoid growth. Finally, I will predict the emergence of intra-organoid heterogeneity across multiple organoid lines, which allows me to derive targeted treatment strategies.In sum, the proposed work will disentangle and perturb the spatio-temporal emergence of phenotypic intra-tumour heterogeneity, which is characteristic of breast cancer tissues.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITAT ZURICH · ZurichКоординаторШвейцария