Version 1
: Received: 31 January 2022 / Approved: 1 February 2022 / Online: 1 February 2022 (11:08:51 CET)
How to cite:
Patkulkar, P.A.; Subbalakshmi, A.R.; Jolly, M.K.; Sinharay, S. Mapping Spatiotemporal Heterogeneity in Tumour Progression by Integrating High-Throughput Imaging and Omics Analysis. Preprints.org2022, 2022020004. https://doi.org/10.20944/preprints202202.0004.v1
Patkulkar, P.A.; Subbalakshmi, A.R.; Jolly, M.K.; Sinharay, S. Mapping Spatiotemporal Heterogeneity in Tumour Progression by Integrating High-Throughput Imaging and Omics Analysis. Preprints.org 2022, 2022020004. https://doi.org/10.20944/preprints202202.0004.v1
Cite as:
Patkulkar, P.A.; Subbalakshmi, A.R.; Jolly, M.K.; Sinharay, S. Mapping Spatiotemporal Heterogeneity in Tumour Progression by Integrating High-Throughput Imaging and Omics Analysis. Preprints.org2022, 2022020004. https://doi.org/10.20944/preprints202202.0004.v1
Patkulkar, P.A.; Subbalakshmi, A.R.; Jolly, M.K.; Sinharay, S. Mapping Spatiotemporal Heterogeneity in Tumour Progression by Integrating High-Throughput Imaging and Omics Analysis. Preprints.org 2022, 2022020004. https://doi.org/10.20944/preprints202202.0004.v1
Abstract
Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics and spatial transcriptomics now allow recording the patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multi-scale dynamics of its evolution. Here, we review latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed a burgeoning growth in recent past in terms of mapping heterogeneity within tumor cell types as well as stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor, and a more systematic investigation of implications of heterogeneity for the patient outcomes.
Biology and Life Sciences, Biology and Biotechnology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
