Based on molecular modeling, the effect of this mutation over protein stability is probably independent of p.D322G mutation found on the same allele.
When protein-coding genes are subjected to occasional mutations over long time periods, they manage to undergo substantial sequence change while maintaining their original function.
Oncology is the frontier of Precision Medicine and typically focus is on identification of gene fusions (e.g. crizotinib, an ALK inhibitor for ALK fusion proteins in lung cancer), mutations (as in the case of vemurafinib, a BRAF inhibitor for melanoma patients with the BRAF V600E mutation) and protein over- expression (e.g. Trastuzumab a HER2-targeted antibody for breast cancer).
Those patients with a p53 gene mutation and nuclear over-expression of the p53 protein had an 8.6-fold higher risk of death compared with patients who had neither mutation nor protein over-expression.
In addition to mutation, over- or ectopic expression, antigenicity of a protein expressed by tumor cells may be determined by post-translational modifications or altered accessibility.
Consistent with these clinical observations, AR gene mutation, amplification and protein over-expression are commonly observed in the majority of prostate cancer cell lines derived from castrate-resistant hosts [14], [15].
In a second subtype of AR-expressing prostate cancer cells derived from castrated patients (e.g., LNCaP, LAPC-4, MDA-PC-2B, VCAP, etc), the cells have developed castration resistance mechanisms (i.e., mutation, gene amplification, protein over-expression) to activate AR signaling for their continued growth even in the presence of castrate levels of androgen [7].
We applied bioinformatics methods to investigate the effects of known disease-related mutations on protein targeting and localization by analyzing over 22,000 missense mutations in more than 1,500 proteins with two complementary prediction approaches.
Average frequencies in over-/underexpression and mutation across protein families were generated for each cancer type by summing frequencies shown in Figure 1 (after changing the Log2 cutoff from 1 to 2 to focus on transcriptional changes of higher amplitude) and dividing by the total number of genes present within the indicated protein family.
The robust quantification of over 9,000 proteins and 11,000 phosphopeptides on average enabled the de novo construction of a functional protein correlation network, which ultimately exposed the collateral effects of mutations on protein complexes.
