In-born genomes contribute to tumorigenesis and metastasis much more than previously expected

Published in Cancer

Share this post

Choose a social network to share with, or copy the shortened URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

It has been debated for years whether genetic, extrinsic factors [1] (i.e., exposure to pathogen infection and environmental agents contributes to tumorigenesis) or intrinsic factors [2] (‘bad luck hypothesis’ – random error mutations during DNA replication in a small fraction of stem cells may be implicated in two-thirds of variation of cancer risk in 25 cancer types) contribute to tumorigenesis and metastasis. Both ‘bad luck’ and ‘extrinsic factor’ hypotheses are dominate in the field. Although both hypotheses disagree each other in terms of intrinsic and extrinsic factors for contributing tumorigenesis, they agree that heredity plays a minimal role in tumorigenesis. Indeed, from cancer cell point of view, family history and a handful of known cancer genes may only explain <5% of cancer population. However, both hypotheses are cancer cell-centered and ignored the immune system.

From a systems point of view, we have proposed that genetic variants of the pre-existing genome (i.e., in-born genome or germline genome) could work together with somatic mutations to induce a transformation of a normal cell into a cancer cell, cancer progression and metastasis [3]. Meanwhile, the immune system combats cancer cells as well. Thus, in-born genomes and the immune system could contribute significantly to tumorigenesis and metastasis. In this study, we set out to test a hypothesis that in-born genomes and the immune system play an important role in metastasis. Thus far, none of a single gene bearing pathogenic germline variants is able to predict survival for the whole patient population of any cancer type. We applied our recently developed algorithm, eTumorMetastasis which enables to construct predictive models based on genome-wide mutations, to ER+ breast cancer using genome-wide pathogenic germline variants. We showed that genes bearing pathogenic germline variants significantly distinguished recurred and non-recurred patients in two ER+ breast cancer independent cohorts (n = 200 and 295) [4]. These results suggest that in-born genomes contribute to tumorigenesis and metastasis much more than previously expected. Further analyses of gene signatures which are able to predict metastases suggest that pathogenic germline variants could shape metastasis via regulating tumor-infiltrating leukocytes (TILs), for example, pathogenic germline variants predicted high-risk tumors contain significantly less CD8+ T, dendritic cells (DC), NK (natural killer) and B cells than low-risk tumors predicted by the pathogenic germline variants. These results suggest that inborn genomes could contribute tumor metastasis by modulating TILs. Because germline genomic information can be obtained vis sequencing of blood samples, practically, this study opens a new window for a non-invasive means for predicting cancer prognosis.      

Along the same line, we showed that the number of inherited pathogenic germline variants in NK cells is positively correlated with cancer risk and negatively correlated with the fractions of TILs and patient survival [5]. These two studies strongly support our hypothesis that inherited pathogenic germline variants associated with immune system play a significant role in tumorigenesis and metastasis. In summary, from the view of cancer cell, hereditary plays a minimal role in tumorigenesis, however, from the view of the immune system, hereditary plays a critical role in both tumorigenesis and metastasis. 


[1] Wu et al., Substantial contribution of extrinsic risk factors to cancer development. Nature, 529:43, 2016

[2] Tomasetti et al., Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention, Science, 355:1330, 2017

[3] Edwin Wang et al., Predictive Genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data, Seminars in Cancer Biology, 30:4-12, 2015

[4] Milanese et al., Germline variants associated with leukocyte-genes predict tumor recurrence in breast cancer patients, npj Precision Oncology, 3:28, 2019

[5] Xu et al., Association of germline variants in natural killer cells with tumor immune microenvironment subtypes, tumor-infiltrating lymphocytes, immunotherapy response, clinical outcomes, and cancer risk, JAMA Network Open, 2:e199292, 2019

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Subscribe to the Topic

Cancer Biology
Life Sciences > Biological Sciences > Cancer Biology

Related Collections

With collections, you can get published faster and increase your visibility.

AI in precision oncology

This Collection is a partnership between npj Precision Oncology and npj Breast Cancer. It will bring together articles on all facets of AI in cancer research.

Publishing Model: Open Access

Deadline: Apr 19, 2024

Innovations in cancers of the central nervous system

This Collection invites research on tumors involving the central nervous system, including primary glial tumors, meningiomas and metastatic tumors in adults.

Publishing Model: Open Access

Deadline: Mar 01, 2024