Integrated Imaging and Molecular Analysis to Decipher Tumor Microenvironment in the Era of Immunotherapy

Authors

Jia Wu
Aaron T Mayer
Ruijiang Li

Publication Date

9-1-2022

Journal

Seminars in Cancer Biology

Abstract

Radiological imaging is an integral component of cancer care, including diagnosis, staging, and treatment response monitoring. It contains rich information about tumor phenotypes that are governed not only by cancer cellintrinsic biological processes but also by the tumor microenvironment, such as the composition and function of tumor-infiltrating immune cells. By analyzing the radiological scans using a quantitative radiomics approach, robust relations between specific imaging and molecular phenotypes can be established. Indeed, a number of studies have demonstrated the feasibility of radiogenomics for predicting intrinsic molecular subtypes and gene expression signatures in breast cancer based on MRI. In parallel, promising results have been shown for inferring the amount of tumor-infiltrating lymphocytes, a key factor for the efficacy of cancer immunotherapy, from standard-of-care radiological images. Compared with the biopsy-based approach, radiogenomics offers a unique avenue to profile the molecular makeup of the tumor and immune microenvironment as well as its evolution in a noninvasive and holistic manner through longitudinal imaging scans. Here, we provide a systematic review of the state of the art radiogenomics studies in the era of immunotherapy and discuss emerging paradigms and opportunities in AI and deep learning approaches. These technical advances are expected to transform the radiogenomics field, leading to the discovery of reliable imaging biomarkers. This will pave the way for their clinical translation to guide precision cancer therapy.

Keywords

Biomarkers, Tumor, Breast Neoplasms, Female, Genomics, Humans, Immunotherapy, Lymphocytes, Tumor-Infiltrating, Tumor Microenvironment, Immunotherapy, Machine learning, Radiogenomics, Radiomics, Tumor immune microenvironment

DOI

10.1016/j.semcancer.2020.12.005

PMID

33290844

PMCID

PMC8319834

PubMedCentral® Posted Date

9-1-2023

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes