Molecular Mechanisms of Feline Cancers

Abstract

Feline cancers have not been studied as extensively as canine cancers, though they may offer similar advantages, with cats being immunocompetent animals subject to similar conditions as their human counterparts. The most common feline cancers include lymphoma, squamous cell carcinoma, sarcoma, and mammary tumors, though mast cell tumors were also investigated in this review. As the pathogenesis of many feline cancers remains unclear, this study seeks to elucidate some molecular mechanisms behind feline cancers. Feline lymphoma has been commonly associated with feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV), though in recent years it has appeared more as lymphoma of the gastrointestinal tract. Chromosomal alterations (translocations) due to the virus-associated lymphoma, as well as aberrant gene expression (such as in COX-2 and MDR1) have been identified in the past. While feline lymphoma may be divided into many subtypes, feline sarcoma may be divided into two broad classifications of feline injection site associated (FISS) sarcoma and spontaneous sarcoma, with FISS being a potential model for inflammation leading to tumorigenesis in humans. Previous studies have found multiple chromosomal alterations (including aneuploidy and chromosomal translocations), as well as aberrations in gene expression in feline sarcoma. In the past, oral squamous cell carcinoma has been proposed as a model for human head and neck cancer, and mammary tumors have been proposed as a model for human breast cancers due to similar prognosis and phenotype, as well as higher rate of occurrence in cats than in humans. Mutations have been identified in genes such as TP53, ERBB2, and TWIST1 in feline mammary tumors. c-KIT mutations were commonly located in feline mast cell tumors, though these findings were not particularly significant in terms of correlation to other prognostic indicators. This review seeks to elucidate pathways and treatments for feline cancers for the field of comparative genomics and oncology.

Genomic landscape and gene expression profiles of feline oral squamous cell carcinoma

“…While these findings were predicted given the remarkable clinical, pathological, and genetic parallels between both tumors ( 9 , 37 , 60 – 62 ) they in no way confirm comparative origins or outcomes. The functional gene and canonical pathway enrichment analyses provided us further insight into the possible activation of several pathways that were seen in FOSCC that included EMT, hypoxia- and inflammation-related pathways ( 61 – 65 ), indicating the complementary value of gene expression analysis in this study. EMT typically involves the expression of transcription factors that can activate this cellular program (i.e., SNAI1, TWIST1, ZEB1 , and ZEB2 ), and is characterized by the upregulation of mesenchymal-related genes (e.g., FN1, VIM, CDH2 , and metalloproteinases) and downregulation of epithelial-related genes (i.e., CDH1 and cytokeratins) ( 65 – 67 ).…”

Implementation of Machine Learning-Based System for Early Diagnosis of Feline Mammary Carcinomas through Blood Metabolite Profiling

“…To analyze mammary carcinoma metabolic pathways in combination with genes, the latter were extracted from two studies 13,14 and are presented in Table 2.…”

“…Significant genes in FMC shown in Table 2 13,14 and corresponding proteins were analyzed with the STRINGdb program, and their relationships were elucidated (Figure 2A).…”

“…The high connectivity of network confirms that the proteins and metabolites play a significant role in the same pathways and interact with each other. The proteins with highest connectivity are EGFR (18), STAT3 and CTNNB1 (17), CDH1, ERBB3, and TP53 (14), PDGFRA (13), the group of four plateletderived growth factors (PDGFA, PDGFB, PDGFC and PDGFD) and VEGFC (average connectivity 10.4) have a close relationship with each other and have a large impact on the disorder (Figure 3A). In FMC, these genes play a role in tumor growth, invasion, and metastasis.…”

“…30 In feline mammary cancer, these genes may be dysregulated, leading to abnormal activation of signaling pathways that promote tumor growth and metastasis. 13,14 Using enrichment analysis, additional five proteins were elucidated by STRINGdb-CBL, GRB2, NOTCH1, PDGFRB, and TEK (Figure 2B). Network presented in Figure 2A shows high-evidence associations of the proteins coded by selected genes.…”