Preprint Review Version 1 This version is not peer-reviewed

The Impact of Tumor Eco-Evolution in Tumor Sampling

Version 1 : Received: 5 November 2018 / Approved: 6 November 2018 / Online: 6 November 2018 (13:30:54 CET)

A peer-reviewed article of this Preprint also exists.

López-Fernández, E.; López, J.I. The Impact of Tumor Eco-Evolution in Renal Cell Carcinoma Sampling. Cancers 2018, 10, 485. López-Fernández, E.; López, J.I. The Impact of Tumor Eco-Evolution in Renal Cell Carcinoma Sampling. Cancers 2018, 10, 485.

Journal reference: Cancers 2018, 10, 485
DOI: 10.3390/cancers10120485

Abstract

Malignant tumors behave dynamically as cell communities governed by ecological principles. Massive sequencing tools are unveiling the true dimension of the heterogeneity of these communities along their evolution in most human neoplasms, clear cell renal cell carcinomas (CCRCC) included. Although initially thought to be purely stochastic processes, very recent genomic analyses have shown that temporal tumor evolution in CCRCC may follow some deterministic pathways that give rise to different clones and sub-clones randomly spatially distributed across the tumor. This fact makes each case unique, unrepeatable and unpredictable. Precise and complete molecular information is crucial for patients with cancer since it may help in establishing a personalized therapy. Intratumor heterogeneity (ITH) detection relies on the correctness of tumor sampling and this is part of the pathologist’s daily work. International protocols for tumor sampling are insufficient today. They were conceived decades ago, when ITH was not an issue, and have remained unchanged until now. Noteworthy, an alternative and more efficient sampling method for detecting ITH has been developed recently. This new method, called multisite tumor sampling (MSTS), is specifically addressed to large tumors that are impossible to be totally sampled, and represent an opportunity to improve ITH detection without extra costs.

Subject Areas

clear cell renal cell carcinoma; tumor evolution; tumor ecology; intratumor heterogeneity; multisite tumor sampling; targeted therapy

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