MOBCdb: a comprehensive database integrating multi-omics data on breast cancer for precision medicine

Abstract The advancement of technologies to measure highly multiplexed spatial data requires the development of scalable methods that can leverage the spatial information. We present MISTy, a flexible, scalable and explainable machine learning framework for extracting interactions from any spatial omics data. MISTy builds multiple views focusing on different spatial or functional contexts to dissect different effects, such as those from direct neighbours versus those from distant cells. MISTy can be applied to different spatially resolved omics data with dozens to thousands of markers, without the need to perform cell-type annotation. We evaluate the performance of MISTy on an in silico dataset and demonstrate its applicability on three breast cancer datasets, two measured by imaging mass cytometry and one by Visium spatial transcriptomics. We show how we can estimate interactions coming from different spatial contexts that we can relate to tumor progression and clinical features. Our analysis also reveals that the estimated interactions in triple negative breast cancer are associated with clinical outcomes which could improve patient stratification. Finally, we demonstrate the flexibility of MISTy to integrate different kinds of views by modeling activities of pathways estimated from gene expression in a spatial context to analyse intercellular signaling.

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Personomics – an innovative tool of precision medicine and its role in the individualized treatment of patients with breast cancer

Asia-Pacific Journal of Oncology ◽

10.32948/ajo.2020.01.10 ◽

2020 ◽

pp. 1-8

Author(s):

Katarzyna Rygiel

Keyword(s):

Breast Cancer ◽

Precision Medicine ◽

Growth Factor Receptor ◽

Personal Characteristics ◽

Biological Properties ◽

Clinical Tool ◽

Her2 Positive ◽

Number Of Patients ◽

Health Related ◽

Standard Medical Treatment

Precision medicine considers specific biological characteristics of each individual patient to tailor diagnostic and therapeutic strategies to a given patient. This approach is particularly important for a growing number of patients with malignancies. Currently, some unique biological properties in the terms of different “omics” platforms (e.g., genomics, proteomics, transcriptomics, metabolomics, epigenomics, and pharmacogenomics) have been introduced to precision medicine. In addition, specific personal characteristics of the patients have been described as personomics. It should be highlighted that personomics include an individual patient’s personality type, set of personal values, priorities, preferences, health-related beliefs, goals, economical status, and different life circumstances, which influence when and how a certain disease (e.g., breast cancer (BC)) can be manifested in a given person. As a consequence, personomics are considered to be an innovative clinical tool that is crucial for making a connection between the existing and emerging, more individualized model of medical care. This is particularly important among patients suffering from the most difficult to treat cancers (e.g., BC subtypes, such as the triple-negative BC (TNBC), and the human epidermal growth factor receptor 2 (HER2)-positive BC). This mini-review addresses some research concepts in personalized medicine, focusing on personomics, which apply individualized data of the patient to the therapeutic plan. In this light, personomics can facilitate the transition from standard medical treatment to personalized medical management of individual women with BC.

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