APOBEC SBS13 Mutational Signature-A Novel Predictor of Radioactive Iodine Refractory Papillary Thyroid Carcinoma

Cancer mutational signatures identification in clinical assays using neural embedding-based representations

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

Mutational signatures and their association with survival and gene expression in urological carcinomas

Different sources of mutagenesis cause consistently identifiable patterns of mutations and mutational signatures that mirror the various carcinogenetic processes. We used publicly available data from the Cancer Genome Atlas to evaluate the associations between the activity of the mutational signatures and various survival endpoints in six types of urological cancers after adjusting for established prognostic factors. The predictive power of the signatures was evaluated with dynamic area under curve models. In addition, links between mutational signature activities and differences in gene expression patterns were analysed. APOBEC-related signature SBS2 was associated with improved overall survival (OS) and disease-specific survival (DSS) in bladder carcinomas in the multivariate analysis, while clock-like signature SBS1 predicted shortened DSS and progression-free interval (PFI) in clear cell renal cell carcinomas (ccRCC). In papillary renal cell carcinomas (pRCC), SBS45 was a predictor of improved outcomes, and APOBEC-related SBS13 was a predictor of worse outcomes. Gene expression analyses revealed various enriched pathways between the low- and high-signature groups. Interestingly, in both the ccRCC and pRCC cohorts, the genes of several members of the melanoma antigen (MAGE) family were highly upregulated in the signatures, which predicted poor outcomes, and downregulated in signatures, which were associated with improved survival. To summarize, SBS signatures provide substantial prognostic value compared with just the traditional prognostic factors in certain cancer types. APOBEC-related SBS2 and SBS13 seem to provide robust prognostic information for particular urological cancers, maybe driven by the expression of specific groups of genes, including the MAGE gene family.

Advances in transcriptomics and proteomics in differentiated thyroid cancer: An updated perspective (Review)

Thyroid cancer (TC) is a broad classification of neoplasms that includes differentiated thyroid cancer (DTC) as a common histological subtype. DTC is characterized by an increased mortality rate in advanced stages, which contributes to the overall high mortality rate of DTC. This progression is mainly attributed to alterations in molecular driver genes, resulting in changes in phenotypes such as invasion, metastasis and dedifferentiation. Clinical management of DTC is challenging due to insufficient diagnostic and therapeutic options. The advent of-omics technology has presented a promising avenue for the diagnosis and treatment of DTC. Identifying molecular markers that can predict the early progression of DTC to a late adverse outcome is essential for precise diagnosis and treatment. The present review aimed to enhance our understanding of DTC by integrating big data with biological systems through-omics technology, specifically transcriptomics and proteomics, which can shed light on the molecular mechanisms underlying carcinogenesis.

USP13 genetics and expression in a family with thyroid cancer

PURPOSE

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma and its incidence has greatly increased in the last 30 years. Ubiquitin-specific protease 13 (USP13) is a class of deubiquitinating enzymes (DUBs) and plays an important role in cellular functions such as cell cycle regulation, DNA damage repair, and different cell signaling pathways. Studies regarding the role of USP13 in cancer development and progression are divergent and there are no previous data regarding the role of USP13 gene in PTCs. In this study, we investigated the genetic cause of PTC diagnosed in multiple members of a Brazilian family.

METHODS

Whole exome sequencing (WES) was performed to identify the genetic cause of PTC. Cycloheximide chase assay and clonogenic assay were performed to study USP13 stability and function in vitro.

RESULTS

WES analysis identified a heterozygous missense variant c.1483G > A (p.V495M) in the USP13 gene that fully segregates with the disease. In silico modeling suggests that this variant may cause protein structural perturbations. USP13 overexpression increased the potential of a single cell to form colonies. The USP13 c.1483G > A variant enhanced the effects seen in USP13 overexpression and preserved protein stability for longer hours compared to the non-mutated USP13 protein.

CONCLUSION

Our study suggests that USP13 overexpression may play a role in tumorigenesis of PTCs; and that the USP13 p.V495M (c.1483G > A) variant enhances USP13 estability.

Advances in Thyroid Carcinoma

"Thyroid cancer" encompasses a heterogeneous group of tumors that range from the predominant papillary thyroid cancer (PTC) subtype, which shows excellent survival rates, to the poorly differentiated (PDTC) and anaplastic thyroid cancer (ATC) forms, accounting for most of the disease-related morbidity and mortality [...].