This study has utilized a prospective approach to identify a miRNA signature for gastric cancer vs. normal stomach epithelium and a miRNA signature that predicts response to standard CF therapy.
Since routine histopathology techniques sometimes do not lead to a definitive diagnosis of gastric cancer, the addition of a miRNA signature from such patient samples may improve the accuracy of a diagnosis of gastric cancer. In previous miRNA microarray studies of gastric cancer, control tissues were obtained from regions of the stomach of gastric cancers patients that were determined to be histologically normal and not from stomach tissue of healthy normal volunteers [6, 7]. Since molecular abnormalities are often found in histologically normal-appearing tissue adjacent to tumor tissue, we chose to obtain control tissues from endoscopic biopsy samples from normal, cancer-free volunteers. Most of the differentially expressed miRNAs reported to be characteristic of gastric cancer in previous microarray studies [6, 7] were also identified within the gastric cancer signature in our current analyses. However, in addition to these previously reported miRNAs in gastric cancer, we additionally identified potential tumor suppressor miRNAs (at P<0.05 and P<0.01, including miR-1[8, 9] and let-7  that we found to be underexpressed in gastric cancer (at P<0.001) (Table 2). Interestingly, Oh et al found expression of miR-486 to be reduced in many gastric cancers, in some cases, associated with a genomic loss of that region . We found miR-486 to be overexpressed in our gastric cancer cohort by both microarray and Taqman PCR analysis (Additional file 1: Figure S1). It is possible that this difference in results is due to very different patient populations studied.
In this study, we report for the first time to our knowledge, a miRNA predictor for response to CF therapy. The 58 miRNA signature that provides an index for assessing potential response to CF therapy may be useful in stratifying patients into a group that should receive standard therapy and a group that will likely not benefit from such therapy and should be placed on a different therapeutic trial. Several of the 58 miRNAs we identified in Table 2 that are associated with TTP are consistent with published reports relating their expression with chemoresistance and tumor biology. Prominent among the upregulated miRNAs associated with a prolonged TTP (defined by a hazards ratio <1) were miRNAs that have been shown to induce apoptosis in gastric and other cancer cells, such as miR-16, let-7g, miR-181, miR-342, miR-1, and miR-34 [8, 12–18]. miR-16 augments apoptosis induction by nutlin and genistein, and modulates multidrug resistance of human gastric cancer cells.
Overexpression of let-7c or let-7g has been shown to decrease expression of Bcl-xL in Huh7 and HepG2 cell lines . Let-7g and miR-181b are positively correlated with clinical responsiveness of colon cancer to S-1, an oral fluorouracil . miR-181a and miR-181b have been shown to function as tumor suppressors which trigger growth inhibition, induce apoptosis and inhibit invasion in glioma cells. Reconstitution of hsa-miR-342 in the colorectal cancer cell line HT-29 induces apoptosis . miR-1 sensitizes lung cancer cells to doxorubicin-induced apoptosis . Ectopic miR-34 expression induces apoptosis, cell-cycle arrest or senescence in normal and tumor cells . Thus, overexpression of these pro-apoptotic miRNAs in primary tumors appears to be a highly consistent feature of patients who benefits from CF.
Interestingly, we identified six *miRNAs that were associated with chemoresistance, including miR-518f*, miR-520a, miR-520d*, miR-519e*, miR-363*, and miR-517*, whereas no miRNAs were associated with chemosensitivity. Only one miR, miR-302*, was identified in the gastric cancer miR signature. miR*s are considered to be passenger strands that are thought to normally be degraded from the pre-miR which results in the mature 22 nt strand that enters the RISC complex. The functions of *miRNAs remain unclear, although it is possible that they result from impaired processing of pre-miRNAs (Tchernitsa et al J of Pathology, 2010) or may play a role in targeting mRNA translation (Gu and Lu, Plos One, 2010).
We also observed that while 21 miRNAs were found in common between the GC and chemoresistance miRNA signatures, 37 miRNAs were unique to the chemosensitivity signature.
Analysis of the sample pairs pre- and post-treatment from 8 patients who initially responded to CF therapy but later became resistant to therapy served as a proof-of-principle for demonstrating that the predictive index of the 58 miRNA signature would switch from a favourable index (at the pre-treatment stage) to an unfavourable index (post-treatment when resistance developed). Unfortunately, it was not possible to obtain additional matched pairs of samples from similar patients to provide a more robust statistical analysis. Nevertheless, the results are consistent with a model of clonal selection of pre-existing resistant tumors cells residing within the primary tumor.
According to the conventional clonal selection model for the development of acquired resistance to chemotherapy resistance, resistance of initially responsive tumors develops due to the selective outgrowth of chemoresistant clones that already exist within the tumor . Given that a rapid TTP specifically indicates an intrinsic resistance to chemotherapy , the 58 miRNAs whose expression levels are correlated with a short TTP may represent chemoresistance-related miRNAs already present in the majority of the tumor cells in the primary tumor. However, primary tumors that appear not to express this miRNA signature of resistance, initially respond to therapy until preexisting, resistant cells selectively grow despite CF therapy. At the time a sample is obtained when resistance is observed, the bulk of the tumor expresses the unfavourable, chemoresistant miRNA signature. Given that resistance in most of these patients develops over a relatively short period of time (months, not years), it seems unlikely that resistance results from the accumulation of multiple individual genetic changes.
The results of this study provide important new data and miRNA signatures, especially predicting response to CF therapy and regarding the emergence of tumor resistance. However, larger studies need to be conducted in the future to further validate these findings and determine whether they can be applied in a clinical setting.