A non-mutated TROP2 fingerprint in cancer genetics

Front Oncol. 2023 Jun 29:13:1151090. doi: 10.3389/fonc.2023.1151090. eCollection 2023.

Abstract

The advent of high throughput DNA sequencing is providing massive amounts of tumor-associated mutation data. Implicit in these analyses is the assumption that, by acquiring a series of hallmark changes, normal cells evolve along a neoplastic path. However, the lack of correlation between cancer risk and global exposure to mutagenic factors provides arguments against this model. This suggested that additional, non-mutagenic factors are at work in cancer development. A candidate determinant is TROP2, that stands out for its expression in the majority of solid tumors in human, for its impact on the prognosis of most solid cancers and for its role as driver of cancer growth and metastatic diffusion, through overexpression as a wild-type form. The Trop-2 signaling network encompasses CREB1, Jun, NF-κB, Rb, STAT1 and STAT3, through induction of cyclin D1 and MAPK/ERK. Notably, Trop-2-driven pathways vastly overlap with those activated by most functionally relevant/most frequently mutated RAS and TP53, and are co-expressed in a large fraction of individual tumor cases, suggesting functional overlap. Mutated Ras was shown to synergize with the TROP2-CYCLIND1 mRNA chimera in transforming primary cells into tumorigenic ones. Genomic loss of TROP2 was found to promote carcinogenesis in squamous cell carcinomas through modulation of Src and mutated Ras pathways. DNA methylation and TP53 status were shown to cause genome instability and TROP gene amplification, together with Trop-2 protein overexpression. These findings suggest that mutagenic and the TROP2 non-mutagenic pathways deeply intertwine in driving transformed cell growth and malignant progression of solid cancers.

Keywords: Trop-2; gelatinous drop-like corneal dystrophy (GDLD); gene expression profiles; genomic mutations; pancreatic cancer (PC); tumor progression.

Grants and funding

We thank the Italian Ministry of Development (FESR 2016-2018. SSI000651, art. 69 Reg. CE n. 1083/2006 and Reg. CE n. 1828/2006), the Italian Ministry of University and Research - Smart Cities and Communities and Social Innovation - “Health @ home” SCN_00558, the Marie Curie Transfer of Knowledge Fellowship “Advanced structure prediction methods” – EC VI Framework Programme (Contract 014541), the Horizon 2020-SMEINST-2015-1, PIC 944224288, Region Abruzzo (POR FESR 2007-2013: Activity 1.1.1 line B, C78C14000100005) for support. The sponsors had no role in the design and conduct of this study, nor in the collection, analysis and interpretation of the data, nor in the preparation, review or approval of the manuscript.