TBC1 domain family member 3CGenealiases: PRC17 · TBC1D3 · TBC1D3A
Q-omics provides the consensus-scored TBC1D3C profile across patient tissues and cancer cell-line models. TBC1D3C expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in TGCT. Additionally, TBC1D3C RNA expression shows 8,232 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight TGCT, and THYM as cancer lineages where TBC1D3C 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 TBC1D3C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TBC1D3C survival associations across molecular data types. TBC1D3C RNA expression shows survival associations in the most cancer types (24). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TBC1D3C RNA expression–survival associations across cancer types. High TBC1D3C expression shows unfavorable associations in TGCT, UCS, KICH, ACC and CESC, but favorable associations in OV. The TGCT 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 TGCT as the clearest survival context for TBC1D3C RNA expression.
This table shows molecular features associated with TBC1D3C in patient tissues and cancer cell lines. In patient samples, TBC1D3C shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, TBC1D3C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
