A Non-interventional, International, Multicentre Clinical Research Study to Build the Largest Collection of Multimodal Data (Including Clinical Data, Imaging Data and Omics Data) in Oncology

Study Summary

Cancer is amongst the leading causes of disease-related morbidity and mortality. A major challenge in cancer treatment is the development of biology-informed, personalised treatment strategies. Recent advances in artificial intelligence (AI) and next-generation sequencing (NGS) technologies have shed further insights into disease biology and treatment pathways, thus identifying new, precision medicine-based therapeutic opportunities. The biological mechanisms leading to cancer development and progression arise from complex and plastic networks of dysregulated cellular programs involving many signalling pathways and effector molecules. Cancer cells alter their surrounding environment via cell-cell interactions with non-tumor cells or by secreting cytokines, chemokines and other factors. This reprogramming of the tumour microenvironment (TME) is critical for cancer progression, invasion, and metastasis. Moreover, there are increasing studies that show that both innate and adaptive immune cell types contribute to tumorigenesis and treatment resistance when present within the TME. Understanding the crosstalk between cancer cells and the surrounding TME will inform on mechanisms of sensitivity and resistance to treatment, including immunotherapy (IO) and targeted therapies. Spatially resolved-Omics is an emerging field that characterises cell types by gene/protein expressions within their spatial context in the tissue organisation. Recent high profile spatial transcriptomics studies have uncovered specific cell identities that define the surrounding TME. The MOSAIC study, a collaborative initiative across industry and top oncology hospitals, proposes to go way beyond current cancer molecular profiling projects by combining the generation and analysis of multiple data modalities (3 essential mandatory modalities: Clinical Data, Hematoxylin and Eosin (H\&E) microscopic image, Spatial transcriptomics; up to 3 high priority data modalities depending on technical feasibili

Primary Outcome

Unsupervised data analysis and outcome measures will be used to achieve this, such as prognosis under treatment, response to specific therapies. The response to therapy will be assessed based on the data related to the treatment and its efficacy collected via an electronic Case Report Form. For each patient at baseline and throughout the MOSAIC follow up period, the following data will help to assess this: all the different cancer treatments (surgery,…) and their outcomes ; the concurrent treatm

Conditions Studied

Study Locations (5)