Q-omics provides the consensus-scored FBN2 profile across patient tissues and cancer cell-line models. FBN2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, FBN2 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, FBN2 protein abundance shows 27,732 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight BLCA, HNSC, and LSCC as cancer lineages where FBN2 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for FBN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FBN2 survival associations across molecular data types. FBN2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (14) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FBN2 RNA expression–survival associations across cancer types. High FBN2 expression shows unfavorable associations in BLCA, STAD, MESO, ACC and DLBC, but favorable associations in COAD. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify BLCA as the clearest survival context for FBN2 RNA expression.
This table summarizes FBN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FBN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FBN2 shows higher tumor expression in HNSC, BLCA, LUAD, UCEC, LUSC and BRCA. The HNSC box plot shows higher FBN2 RNA expression in tumor versus normal tissue (log2 FC = +2.911, t-test p < 0.001).
This table shows molecular features associated with FBN2 in patient tissues and cancer cell lines. In patient samples, FBN2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, FBN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
