Biology subjects

Melhuish, T. A.

Publications and source records attributed to Melhuish, T. A..

2 recordsLinked to original sources

bioRxiv2026

Increased expression of a subset of genes within reduced copy number regions across multiple cancer types

The TGIF1 transcription factor gene is present on chromosome 18, which is subject to whole chromosome copy number reduction in colon cancer. Despite this, TGIF1 expression is significantly higher in cancer than in normal. In mice complete deletion of Tgif1 reduced tumor burden in an Apc mutant model of intestinal cancer. Here we show that reducing TGIF1 expression in a human colon cancer cell line slows proliferation and reduces growth of orthotopic xenografts. To ask if additional genes with copy number loss are more highly expressed in tumors we identified chromosomal regions subject to copy number reductions from ten TCGA cancer datasets. Within these regions a small proportion of genes, generally less than 10%, are expressed at higher levels in the tumor than in corresponding normal samples. Enrichment analysis using a set of 435 genes that have copy number reduction and increased expression identified mitosis as the most enriched gene set and FOXM1 and E2F family transcription factors as potential regulators. For mitotic genes, the average expression increase in tumor compared to normal is independent of copy number. In contrast, while DepMap common essential genes are generally more highly expressed in cancer than normal tissue, the relative increase in expression tracks well with copy number. Similarly, expression differences for gene sets such as S-phase, rRNA processing and DNA repair show increased expression in cancer versus normal, but changes also track with copy number. Thus, genes with increased expression despite copy number reduction may represent the output of key pro-tumorigenic transcriptional programs and could be potential therapeutic targets.

cancer biology↗

bioRxiv2026

A simple method for analyzing competitive growth of multiple cell types in xenograft tumors

Low take rates and inter-tumor variability in growth rates can limit the effectiveness of mouse xenograft models when comparing between groups. To address this problem we developed a simple method to compare multiple cell types within a single mixed xenograft. Individual cell lines or clones were transduced with a lentiviral vector that includes a unique PCR tag, allowing the use of qPCR to determine the proportion of each tagged cell type within a mixed xenograft tumor. We generated vectors with six distinct PCR tags, and two different selectable markers, and have optimized the approach for determining their relative proportions within a mix. An initial pre-amplification step is used to increase the amount of material for subsequent qPCR reactions. This also removes the bulk of the genomic DNA, increasing the specificity of the qPCR step. Samples are then used for qPCR with specific pairs of primers that distinguish between each of the individual PCR tags, and the relative proportion of each tag is determined relative to that in the starting mix. We have tested this approach for in vitro growth of mixed cell cultures and in an orthotopic cecal xenograft model using a human colon cancer cell line. Since each individual tumor is initiated with a mix of cells, multiple tumors within a single animal can be analyzed separately, and overall tumor size is not important. Similarly, multiple metastatic lesions from the same animal can be analyzed individually. Thus, each tumor provides a direct comparison between individually tagged cell lines or clones. This low throughput "bar-coding" approach is simple and cost effective and has the potential to reduce the number of animals needed for xenograft experiments.

cancer biology↗