A novel approach to analyze gene expression data demonstrates that the DeltaF508 mutation in CFTR downregulates the antigen presentation pathway

Abstract

Gene array studies comparing cystic fibrosis (CF) and non-CF genotypes should reveal factors that explain variability in CF lung disease progression, yielding insights that lead to improved CF care. To date, studies have reached conflicting conclusions, perhaps due to experimental differences and divergent statistical approaches. This review aims: 1) to summarize the findings of four recent gene studies comparing CF and non-CF genotypes, and 2) to reanalyze original data using a recently developed statistical approach, with the aim of identifying genes and paths consistently regulated by the CF genotype. We identified four studies evaluating the effect of the DeltaF508-CFTR mutation on human airway epithelial cell gene expression, restricting our investigation to human airway epithelial cell studies whose data were accessible in NCBI's Gene Expression Omnibus or the European Bioinformatic Institute's ArrayExpress. Gene expression patterns showed consistent repression of MHC class I antigen presentation genes in CF human airway epithelia, suggesting a novel mechanistic explanation for poor clearance of viral and bacterial infections by CF patients. We also examined proinflammatory and NF-kappaB genes, whose induction is widely accepted as a hallmark of the CF genotype, but found little evidence of induction, consistent with a recent review (Machen TE, Am J Physiol Cell Physiol 291: C218-C230, 2006.). In conclusion, our analysis suggests that the CF genotype may impair immune function in airway epithelial cells but may not increase inflammation. Additional studies are required to determine whether MHC class I gene repression in CF reduces antigen presentation at the protein level and whether repression impairs immune function.

Fig. 1.

Steps used in gene array analysis: data normalization, selection of differentially expressed genes, categorization, visualization, confirmation, and formation of a testable hypothesis. The exploratory process, discussed in the text, involves iterations, as shown by the lines leading back to previous steps.

Fig. 2.

Volcano plot showing the average fold change of individual genes (x-axis) compared with P value in a t-test (y-axis) from cystic fibrosis (CF) compared with non-CF nasal brushings (48). Genes marked with × were strongly regulated, with a fold change (FC) greater than 2.0 or less than 0.5. Genes marked with + were highly significant (P < 0.0001), but the fold change was relatively small. Genes marked in color were significant (P < 0.05) and changed by a factor of at least 1.4 or 0.7. Larger colored circles denote greater regulation upward (red) or downward (green).

Fig. 3.

Four-way Venn diagram showing genes in common among the 300 most induced (upregulated) genes selected from each of the 4 studies. Note that no genes were strongly induced in all 4 studies. For example, in the red circle [Virella-Lowell et al. (44) study], 265 refers to the number of genes upregulated in the Virella-Lowell data only, 10 refers to the number of genes that are upregulated in both the Virella-Lowell and Verhaeghe et al. (43) study (green circle), and 1 refers to the number of genes that are upregulated in both the Virella-Lowell and Wright et al. (47) study (blue circle). The number 0 in the center that is encircled by all colored circles indicates the number of genes that are upregulated in all 4 studies.

Fig. 4.

Hierarchically clustered heatmap of genes in IPA NF-κB path in the 4 studies discussed in this review. Fold change presented in log base 2 units (color key shown at top left). Genes (top to bottom): IKKβ, PRKCQ, BCL3, NFKBIE (includes EG:4794), JNK1, RelB, IL18, MAP4K4, IL1A, NFKBIA, IL1R1, A20, IL1B, CAMK4, BR3, IL1R2, TNFα, TLR6, LTA, MAP2K6, BMP2, MAP3K14, NF-κB2 p52, IL1F6, MAP2K7, Zap70, IL1F10, BIMP1, CALML5, CD40L, TRAF2, IRAK4, RANKL, IL1F5, TLR9, IKKβ, TAB1, TLR7, IL1F7, β-TrCP, PRKCB, TRAF6, TLR8, LCK, AKT2, NOS3, IL1F8, PKCζ, IL1F9, TIRAP, CD40, EGF, GH, TLR1, IRAK-M, RIP, NFKBIB, TRD@, MAP3K3, LTBR, TRA@, CALM3, NAK, TGFα, Bcl-10, GSK-3β, UBE2V1, MYD88, REL, TLR2, NAP1, NF-κB1 p50, TRAF3, IRAK1, IL1RN, MALT1, IKKα, p65/RelA, PLCγ2, TLR5, TLR3, AKT1, TTRAP, UBE2N, TAK1, BAFF, PKR, NCK1, BMP4, TLR4, Cot, AKT3, TRAF5.

Fig. 5.

Hierarchically clustered heatmap of genes in IPA protein ubiquitination path in the 4 studies discussed in this review. Fold change presented in log base 2 units. Genes (top to bottom): UCHL1, PSMD4, UBE2F, USP54, USP31, USP19, UBE2E2, UBE2D4, USP38, UBE3A, UBE2J2, THIMET, USP53, NEDD4, USP32, USP36, USP12, USP20, ZBTB12, PAN2 (includes EG:9924), USP29, USP18, UBE2C, BAP1, USP6, CDC34 (includes EG:997), SMURF1, USP2, USP5, USP39, USP27X, IFNG, TAP2, NEDD4L, HLA-C, HLA-A, USP40, SMURF2, PSMD2, USP3, UBE2I, UBE2B, B2M, USP4, UBE3B, PSMB9, PSMB8, TAP1, UBE2L6, UBE2D1, USP15, UBE2G2, USP13 (includes EG:8975), UBE2J1, USP10, BAG1, USP49, USP8, USP25, USP46, USP9Y, PSMD11, PSMD3, PSMC5, PSMD7, PSMB3, USP7, PSMC1, PSMD1, UBE2R2 (includes EG:54926), PSMD12, PSMD5, PSMB10, USO1, UBE2V2, USP14, PSME1, MED20, USP45, PSMC4, USP21 (includes EG:27005), USP24, E3 U box, UCHL5, UBE2H (includes EG:7328), USP34 (includes EG:9736), UBE2M, PSMC3, PSMD9, USP11, PSMD13, HLA-B, USP9X, USP47, PSMB6, UBE2G1, PSMC2, USP1, USP16, USP43, USP48, PSMA7, UBE2Q1, USP22, PSME2, PSMB4, PSMA5, UBE2D2, PSMD6, USP28, UBE2E3, PSMD14, UBE2N, UBE2L3, PSMB7, USP33, USP30, USP42, UBE2V1, UBE2A, PSMD8, E1, PSMC6, USP37 (includes EG:57695), PSMB2, PSMA2, PSMD10, PSMB5, UCHL3, UBE2D3, HSP90AA1, PSMB1, BIRC6, HSPA5, UBE2E1, USP26, UBE2S, PSMA4, HSPA8, PSMA1, PSMA3.

Fig. 6.

Hierarchically clustered heatmap of genes in IPA antigen presentation path in the 4 studies discussed in this review. Fold change presented in log base 2 units. Genes (top to bottom): HLA-DPA1, MR1, HLA-DOA, HLA-DOB, TAP2, HLA-DPB1, HLA-DMA, HLA-DRB1, HLA-E, HLA-C, HLA-B, HLA-A, MHC I-β. HLA-F, HLA-G, CALR, TAP1, HLA-DMB, CLIP, LMP7, LMP2, HLA-DQA1, LMPY, TPN, HLA-DRB4, LMPX, CNX, HLA-DRA.

Fig. 7.

Role of antigen presentation in the destruction of virally infected cells by cytotoxic T lymphocytes. Cells that fail to present viral antigen in sufficient quantity may escape immune surveillance. Reproduced with artist's permission: William Scavone.