<p>Introduction & Objectives: Gene expression is a very tidy and well coordinated procedure. Consecutive genes are often similarly expressed. We hypothesized that correlations might exist between genes of the same chromosome, yet belonging to different urinary bladder cancer (BC) samples, in order to indicate a common regulation for genes following this pattern.</p>
<p>Materials & Methods: We analyzed BC gene expression profiles, with emphasis in linear correlations of gene expression based on their chromosomal locations. Samples from 10 human BCs and 5 normal tissues were analyzed by whole genome microarrays, along with a computational approach, for their expression profiles. After raw data normalization and classification, differentially expressed genes (DE) were sorted according to their chromosome distributions and were further investigated for linear correlations among them. Chromosomal activity in terms of gene expression was measured by calculating the average expression of all DE genes for each chromosome, both for tumour and control samples.</p>
<p>Results: Chromosome-based expression analysis predicted that among the most active chromosomes were chromosomes 9 and X. Similarly, control samples also manifested high expression activity on the X chromosome. The genes that exhibited significant linear correlations (p<0.05) among tumor samples on chromosomes 4, 8, 13, 21 and 22, were as follows: TACR3, RNF150, ANXA10, CENTD1, EXOC1, GRSF1 for chromosome 4; ANXA13, DENND3, FGF20, EFHA2, DNAJC5B, MRPS28, FABP5 for chromosome 8; ITGBL1, RXFP2, KL, MYCBP2, FARP1 for chromosome 13; KRTAP19-1, IFNAR1, SON for chromosome 21; MORC2, PLA2G6, ACO2, ARHGAP8 for chromosome 22; SERPINA7, TMEM164, ARHGAP6, APLN, FHL1, PNMA6A, UBL4A, PRDX4, POLA1, MXRA5 for chromosome X.</p>
<p>Conclusions: Despite the fact that linear correlations occurred among distinct patients, the expression of the genes appeared to be correlated among them, in a similar manner. We have previously reported that there are hints of common mechanisms between BCs of different stage/grade, employing microarray analysis. Chromosomal correlation analysis comes to support our previous findings, since it revealed genes bearing common regulation among samples of different histology. Gene expression correlations can further assist us to understand more in-depth the mechanisms underlying tumour progression and biology.</p
