## 4 Discussion  
CNV is a type of structural variation in the genome that results in an abnormal copy number of genes, such as deletions, losses, gains, and amplifications [2]. CNV is critical for the expression of coding and non-coding genes in the genome, significantly affecting the activity of a number of signaling pathways [18,19] and promoting cancer development. Therefore, targeting the amplified genes and the subsequent activation of oncogenic signaling pathways may be crucial for developing novel personalized therapies for GC. Identification of CNVs in either chromosomal or mitochondrial DNA from clinical samples (blood or tissue) may aid in diagnosis, prognosis, and personalized or targeted therapies for GC [20,21]. IPA analysis of the genetic gain- or loss-of-function datasets obtained from genomic sequencing data from control and GC groups revealed the biological impact downstream of canonical pathways, diseases, disorders, and biological functions. We used \"variant loss/gain\" to determine whether and how much activity each gene was lost or gained from a mutation. The \"variant loss/gain\" is determined on a scale of \(-2\), \(-1\), \(0\), \(1\), \(2\), where each number contains information about the loss or gain of activity of that gene and not at the variant level. IPA has more than 700 pre-defined canonical pathways or well-understood signaling pathways for the interpretation of loss or gain functions. In IPA, pathway overlap of significant dataset molecules of the control and GC groups with canonical pathways that are likely activated or inhibited can be obtained. IPA uses an algorithm that relates the effect on the gene from the mutation in the dataset to the pattern anticipated for the specific canonical pathway if it was activated. To understand the variant effects on these well-known pathways, canonical pathways were investigated using IPA to predict the involvement of signaling pathways in the control and disease groups. In the GC group, the PD-1/PD-L1 immunotherapy pathway had the highest impact on the canonical pathway. In line with our findings based on IPA, a high-throughput knowledge discovery platform,  
Figure 4: (**a**) Top diseases and biofunctions significantly affected in the GC group based on the negative logarithm of the Benjamini–Hochberg corrected \(p\)-value –log(B-H). \(p\leq 0.01\) was used as a cut-off to compute the B-H correction. (**b**) Heatmap constructed based on the Z-score showing the diseases and biofunctions significantly affected by the CNVs in the control group. (**c**) Heatmap constructed based on the Z-score showing the diseases and biofunctions, significantly affected by the CNVs in the GC group. (**d**) Heatmap constructed based on the Z-score showing the diseases and biofunctions impacted by CNVs unique to the control group. (**e**) Heatmap constructed based on the Z-score showing the diseases and biofunctions significantly affected by the CNVs common in control and the GC groups. (**f**) Heatmap constructed based on the Z-score showing the diseases and biofunctions significantly affected by the CNVs unique to the GC group. several studies have shown that PD-1 and PD-L1 are overexpressed in GC tissues [22; 23; 24]. Increased PD-1/PD-L1 expression augments the growth of GC cells [25]. Furthermore, our in silico validation study using iPPathwayGuide, another NGKD platform, based on RNAseq data derived from GC patients (14), proved that the genes implicated in the PD-1/PD-L1 pathway was differentially regulated and reduced T-cell activity and increased T-cell apoptosis and effector T-cell development. Cancer immunotherapy has been a success story in antitumor therapy over the past few years [26; 27]. PD-1 is one of the major factors that inhibits tumor-specific immune responses and induces immune tolerance or self-tolerance by promoting apoptosis of antigen-specific T cells, T-cell activity, and inhibiting apoptosis of Tr1 cells [28; 29].