By understanding Matrix Metalloprotease (MMP) dysregulation from a pan-cancer perspective, this study sheds light on the diagnostic potentials of MMPs across multiple neoplasms. MMPs are intriguing genes related to cancer disease progression, functional promotion of angiogenesis, invasion, metastasis, and avoidance of immune surveillance. Many studies have noted these genes are frequently upregulated in cancer. However, expression patterns of all MMPs and their diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. The Cancer Genome Atlas (TCGA) data were used to evaluate diagnostic and prognostic potential of 24 MMPs in fifteen different cancer types. Gene expression measured by RNA-seq was analyzed by differential expression, hierarchical clustering, and ROC analysis for individual genes and in combination. MMP1, MMP9, MMP10, MMP11, and MMP13 were almost universally upregulated across all cancers, with significant (p < 0.05) fold change (FC > 2) in ten of fifteen cancers. MMP3, MMP7, MMP12 and MMP14) are significantly up-regulated in at least 10 cancer types. Interestingly, MMP2, MMP7, MMP23B, MMP27 and MMP28) are significantly down-regulated in seven to nine cancer types. Multiple MMPs possess AUC’s > 0.9 in more than one cancer. However, survival analyses suggest that the prognostic value of MMPs is limited to clear cell renal carcinoma. Most MMPs have consistently increased gene expression across cancers, while several MMPs have consistently decreased expression in several cancer types. Many MMPs have diagnostic value individually or in combination, while the prognostic value of MMPs is restricted to one subtype of kidney cancer.

Genome-wide association (GWA) studies revealed a number of single nucleotide polymorphisms (SNPs) significantly associated with type 1 diabetes (T1D). In an attempt to confirm some of these candidate associations, we genotyped 2046 Caucasian patients and 2417 normal controls from the United States for SNPs in five genomic regions. While no evidence was obtained for four genomic regions (rs2929366/ NM_144715 on chromosome 3, rs9127/ Q7Z4C4 on chromosome 5, rs1445898/ CAPSL on chromosome 5 and rs2302188/ NM_033543 on chromosome 19), we provide strong evidence for association between T1D and multiple SNPs in the IFIH1 linkage disequilibrium (LD) block on chromosome 2q. Among the 10 SNPs genotyped for the 2q region, four SNPs located within the IFIH1 gene or at the 5′ region of IFIH1 showed significant association with T1D in the Georgia population [odds ratio (OR) = 1.7–1.9] with the best P -value found at SNP rs1990760 ( P = 8 × 10 ⁻⁸ and OR = 1.9). Several SNPs outside of the IFIH1 gene also showed significant but weaker associations. Furthermore, IFIH1 gene expression levels in peripheral blood mononuclear cells are significantly correlated with IFIH1 genotypes, and higher IFIH1 levels are found in individuals with the susceptible genotypes ( P = 0.005). Thus, both genetic association and gene expression data suggest that IFIH1 is the most plausible candidate gene implicated in T1D in this LD block.

The present study was conducted to assess genetic associations for type 1 diabetes (T1D) reported in previous genome-wide association studies (GWAS). A total of 21 previously reported single-nucleotide polymorphisms (SNPs) were genotyped by TaqMan assays in 1434 Caucasian T1D patients and 1864 normal controls from Georgia. Analysis of the samples identified 18 SNPs (PTPN22, INS, IFIH1, SH2B3, ERBB3, CTLA4, C14orf181, CTSH, CLEC16A, CD69, ITPR3, C6orf173, SKAP2, PRKCQ, RNLS, IL27, SIRPG and CTRB2) with putative association.

Glycan-binding proteins (GBPs) play critical roles in diverse cellular functions such as cell adhesion, signal transduction and immune response. Studies of the interaction between GBPs and glycans have been hampered by the availability of high throughput and high-content technologies. Here we report multiplex glycan bead array (MGBA) that allows simultaneous analyses of 384 samples and up to 500 glycans in a single assay. The specificity, sensitivity and reproducibility of MGBA are evaluated using 39 plant lectins, 13 recombinant anti-glycan antibodies, and mammalian GBPs. We demonstrate the utility of this platform by the analyses of natural anti-glycan IgM and IgG antibodies in 961 human serum samples and the discovery of anti-glycan antibody biomarkers for ovarian cancer. Our data indicate that the MGBA platform is particularly suited for large population-based studies that require the analyses of large numbers of samples and glycans.

Transcriptomic analysis identifies progression signatures facilitating prediction of individual T1D risk from 18 months of age in independent cohorts.