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Chromosomal microarray technology represents the technical convergence of molecular genetics and cytogenetics, and is rapidly revolutionizing modern cytogenetics. Expected genomic aberrations are accurately identified and provide readily interpretable results that are suitable for clinical risk stratification and therapeutic strategies. The application of array technology in prenatal genetic diagnosis provides distinct advantages over conventional cytogenetic analysis in detecting both the majority of microscopic and submicroscopic chromosomal abnormalities. In the last few years, the validity of array technology has become obvious to medical and laboratory communities involved in prenatal diagnostic testing. However, whether or not microarray analysis is sufficient for the detection of cytogenetic abnormalities in prenatal diagnosis and if traditional cytogenetics continue to be important in this new era has yet to be confirmed. In the present study, we systematically reviewed the current status of microarray technology in the identification of pathogenic genomic imbalances and discussed practical considerations for its routine implementation in prenatal diagnosis.

Chromosomal alterations are a predominant genomic force contributing to the development of lung adenocarcinoma (ADC). High density genomic arrays were conducted to identify critical genetic landmarks that may be important mediators in the formation or progression of early‑stage ADC. In this study, the most noteworthy and consistent observation was a copy number gain on the short arm of chromosome 7, which was detected in 85.7% (12/14) of cases. Notably, three distinct regions of amplification were identified between the 7p22.3 and q11.2 regions in 28.6% (4/14) of cases; at a size of 4.1 Mbp (7p22.3‑p21.1), 2.6 Mbp (7p15.2-p14.1) and 1.5 Mbp (7p12.3‑p11.2). Variations of the 7p11.2 locus that encodes EGFR are known to be oncogenic. Furthermore, potential target genes were identified that were previously not assumed to be involved in the pathogenesis of ADC, including CALM1P2 (7p11.2), HOXA4, HOXA5, HOXA6, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA13 (7p15.2) and LOC442586, LOC442589, LOC442282, FAM20C and LOC442651 (7p22.3). The present study determined critical regions on the 7p arm of chromosome 7, which were implicated in ADC. The pattern of rearrangements on the 7p arm may be a consequence of the high density of potential targets and the identified genes at the 7p regions may aid in the development of therapeutic targets for ADC.

Microsatellite instability (MSI) is a hyper-mutable phenotype caused by the loss of DNA mismatch repair activity, and plays a crucial role in gastric carcinogenesis. To clarify the role of genetic instability in relation to clinicopathological variables, and to identify predictive MSI markers that facilitate the early detection and improve the classification of gastric carcinomas (GCs), 13 microsatellite (MS) loci, including the National Cancer Institute (NCI) panel of MS markers (D2S123, D5S346, D17S250, BAT25 and BAT26) and 8 dinucleotide repeats (D3S1260, D5S107, D5S409, D17S261, D17S520, D17S855, D18S34 and D18S61) were studied in GC patients. MSI was found in 88.2% (30/34) of GC cases and the number of high-frequency MSI (MSI-H, 23.5%, 8/34), low-frequency MSI (64.7%, 22/34), and stable MSI (11.8%, 4/34), was calculated. Among the MS loci analyzed, D18S34 and D17S261 (15/34, 44.1%) exhibited the highest frequency of MSI, followed by D2S123 (14/34, 41.2%), D5S107, D5S346, D5S409 and D18S61 (12/34, 35.3%) (MSI>35%). MSI-H was particularly prevalent in older patients and was mainly found in the antrum and poorly differentiated tumors. Furthermore, MSI-H was significantly associated with lymph node involvement cases in females. One notable finding in this analysis was that the markers, D17S250 and D17S520, exhibited a significantly higher percentage of MSI in advanced gastric carcinomas than in early gastric carcinomas (P=0.046 and 0.046, respectively), and the D17S520 and BAT26 loci represented significant different correlations between the tumor stages (P=0.038 and 0.042, respectively). This study indicates that the novel markers, D18S34 and D17S261, perform more favorably than the NCI panel for the detection of MSI, and the D17S520 locus presents a potential target for predicting the clinical impact of GC. These novel MS loci may prove to be beneficial and independent tools for the construction of a comprehensive genetic classification for GC cases.