Q-omics provides the consensus-scored SYNJ2 profile across patient tissues and cancer cell-line models. SYNJ2 expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SYNJ2 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, SYNJ2 protein abundance shows 22,304 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight MESO, KICH, and PDAC as cancer lineages where SYNJ2 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 SYNJ2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYNJ2 survival associations across molecular data types. SYNJ2 RNA expression shows survival associations in the most cancer types (30), followed by mutation status (8) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYNJ2 RNA expression–survival associations across cancer types. High SYNJ2 expression shows unfavorable associations in MESO, KIRP, UVM, KICH and ACC, but favorable associations in SCLC. The MESO 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 MESO as the clearest survival context for SYNJ2 RNA expression.
This table summarizes SYNJ2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SYNJ2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYNJ2 shows lower tumor expression in KICH and higher tumor expression in LUAD, STAD, LUSC, LIHC and BRCA. The KICH box plot shows higher SYNJ2 RNA expression in normal versus tumor tissue (log2 FC = −1.575, t-test p < 0.001).
This table shows molecular features associated with SYNJ2 in patient tissues and cancer cell lines. In patient samples, SYNJ2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, SYNJ2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and UPPER_AERODIGESTIVE_TRACT.
