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[Analysis of first-line chemoresistance and prediction of chemo-response in non-small cell lung cancer by comparative genomic hybridization].

OBJECTIVE
To explore the association between chromosomal disequilibrium and chemoresistance/chemosensitivity in non-small cell lung cancer (NSCLC) using comparative genomic hybridization (CGH).


METHODS
Genomic DNA samples were prepared from the tumor tissues in paraffin-embedded sections derived from 88 patients with advanced NSCLC (18 with chemosensitivity and 16 with chemoresistance). The DNAs were first amplified by a degenerate oligonucleotide prime-polymerase chain reaction protocol and then labeled with fluorescence as probes for CGH analyses. The correlations of the resulting chromosomal imbalances with the chemo-sensitivity and other pathological features of the patients were analyzed.


RESULTS
A total of 640 abnormal chromosome regions including 96.12% gains and 3.88% losses were detected in 88 specimens. The results indicated that the most frequently gained chromosome regions were 19p13.1-13.3 (39/88, 44.12%), followed by 9q12-q22 (26/88, 29.41%), 22q12-q13 (26/88, 29.41%), and Xq (29/88, 32.35%). The total number of abnormal regions related with chemo-sensitivity was 188( 182 gains and 6 losses), while the number of the abnormal regions linked to the chemoresistance was 452 (431 gains and 21 losses) (P=0.005). Gains of 14p12-p13 and 19p were significantly correlated with the chemosensitivity of the NSCLC (P=0.006). Gains of 1q12-q22, 10q25-q26, 5p15.1-p15.3, 19q13.2-13.4, 20p11.2-p12, 21q22, and Xp 21-p22.1 were also significantly correlated with the chemoresistance (P]0.005, 0.029, 0.039, 0.029, 0.039, 0.016, and 0.006, respectively). No correlation between the chromosome abnormalities and other clinical features was observed.


CONCLUSIONS
The specific gains and losses of chromosome region is correlated with platinum-based first-line chemotherapy in NSCLC patients,as confirmed by CGH detection. This finding is useful for further identifying the chemosensitivity-related functional genes, predicting clinical effectiveness, and achieve individualized treatment in the future.