The DOCK3 gene encodes the Dedicator of cytokinesis 3 (DOCK3) protein, which belongs to the family of guanine nucleotide exchange factors and is expressed almost exclusively in the brain and spinal cord. We used whole exome sequencing (WES) to investigate the molecular cause of developmental delay and hypotonia in three unrelated probands. WES identified truncating and splice site variants in Patient 1 and compound heterozygous and homozygous missense variants in Patients 2 and 3, respectively. We studied the effect of the three missense variants in vitro by using site-directed mutagenesis and pull-down assay and show that the induction of Rac1 activation was significantly lower in DOCK3 mutant cells compared with wild type human DOCK3 (P < 0.05). We generated a protein model to further examine the effect of the two missense variants within or adjacent to the DHR-2 domain in DOCK3 and this model supports pathogenicity. Our results support a loss of function mechanism but the data on the patients with missense variants should be cautiously interpreted because of the variability of the phenotypes and limited number of cases. Prior studies have described DOCK3 biallelic loss of function variants in two families with ataxia, hypotonia, and developmental delay. Here, we report on three patients with DOCK3-related developmental delay, wide-based or uncoordinated gait, and hypotonia, further supporting DOCK3's role in a neurodevelopmental syndrome and expanding the spectrum of phenotypic and genotypic variability.

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Background: Comprehensive Genomic Profiling (CGP) is performed routinely in patients (pts) with metastatic solid tumors (MSTs) to guide treatment. However, there is variability in the interval between metastatic diagnosis (MDx) and performance of CGP based on histology and/or provider preference. We analyzed the CGP utilization patterns and its impact on outcomes at our academic medical center. Methods: All MST pts with CGP data (January 2012 - April 2020), their date of MDx, and the date of CGP were identified by electronic medical record review. Pts who had CGP after MDx were divided into tertiles (T1-earliest, T3-latest) within each cancer type, while some pts had CGP performed prior to MDx (pre-mets). Overall survival (OS) was estimated from the time of MDx with left truncation at the CGP time. Cox regression model was used to estimate the impact of ‘timing of CGP' on survival for individual cancer (CA) types. Results: Among 1,358 pts identified, 710 (52%) were female, 1,109 (82%) Caucasian, 186 (14%) Afro-Americans, and 1,320 (97%) non-Hispanic. Lung (254; 19%), colorectal (203; 15%), gynecologic (121; 8.9%), pancreatic (106; 7.8%) and connective tissue/soft tissue CAs (95; 7%) were the most frequently identified. Sex, race, and ethnicity had no impact on the time interval between MDx and CGP with 2 exceptions - Hispanics with lung CA and females with pancreas CA had delayed CGP compared to non-Hispanics and males respectively (p =0.019, p =0.025). The median time to CGP after MDx was shortest for urothelial CA (2.4 months) and longest for prostate CA (22 months). Pts with lung [T2 Hazard ratio (HR) of 2.25, p&lt;0.001; T3 HR of 2.67, p&lt;0.001], gastro-esophageal (T2 HR of 1.88, p=0.079; T3 HR of 2.49, p= 0.024), and gynecologic CAs (T2 HR of 2.58, p=0.012; T3 HR of 5.19, p=0.003) had better survival if they had CGP performed during the first tertile after MDx. Conclusion: Early CGP after MDx may have a greater impact on OS in CA types with more actionable therapeutic targets. The inherent bias associated with limiting the analyses only to pts who had CGP performed hampers our ability to contrast these results with those who did not have CGP performed. The establishment of national quality metrics for CGP utilization by CA type is imperative. Citation Format: Bicky Thapa, Gulrayz Ahmed, Matthew Lasowski, James P. Thomas, Honey V. Reddi, Michael T. Zimmerman, Raul Urrutia, Aniko Szabo, Ben George. Comprehensive genomic profiling - does timing matter [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2243.

Enzyme function and catalysis is often dictated by the vibrational dynamics and flexibility of the protein. Since the catalytic functions of enzymes are necessary

Background: Patients (pts) diagnosed with multiple myeloma (MM) are at risk for developing secondary hematologic malignancies (SHM). The etiology of SHM-associated genetic alterations (GAs) is unclear. We hypothesized that the GAs present in MM-associated SHMs would have a distinct profile compared to de novo or other therapy related hematologic malignancies. Aims: For MM pts who develop SHM, compare GAs at Autologous Stem Cell Transplant (ASCT) and at diagnosis of SHM. Assess for presence of previously reported deleterious myeloid GAs and determine if there is clonal evolution from the autograft. Methods: We retrospectively identified 9 MM pts with SHM post-ASCT. Autograft (auto) cells and SHM Fresh Frozen Plasma Extraction (FFPE) samples underwent whole exome sequencing. GAs with known clinical significance, variant allele frequency (VAF) ≥0.05 or ≤0.9, and high or moderate impact on the gene-encoded protein were included for analysis. From literature review, we identified 89 reported GAs (kmGAs) in myeloid malignancies. Targeted deep sequencing for these mutations was performed to obtain the VAF in both the auto and SHM FFPE samples. Results: 9 adult pts (age 56-71) with MDS, AML, or ALL were included. 8 auto samples and 9 SHM samples were available. All pts received induction therapy prior to ASCT (44% and 55% with lenalidomide/thalidomide or bortezomib containing regimens, respectively). Lenalidomide maintenance was utilized in 60% of pts. Whole exome sequencing revealed 118,614 GAs in all samples. 2074 GAs were included. Average mutational burden was similar between the auto and SHM samples. For paired samples (matched auto and SHM samples for each pt), 1173 GAs with kmGAs of GATA2, SETBP1, and ATM were present. GATA2 and SETBP1 were present in 3 and 5 auto samples, and 4 and 6 SHM samples, respectively. SETBP1 and GATA2 were present in paired samples for 3 and 1 pt, respectively. Targeted deep sequencing revealed significant mutations in SHM samples, but not auto samples, for ABCA12, ASXL1, BCOR, BRAF, EXH2, KDM5A, KMT2A, KMT2D, NOTCH1, PRPF8, TET2, and TP53. The most highly represented mutation was TP53 which was present in 6 pts, followed by KMT2A in 3 pts, KMT2D in 3 pts, PRPF8 in 2 pts, and TET2 in 2 pts. The patient who carried the most significant mutations carried the diagnosis of ALL, harboring 11 genetic mutations in the SHM sample only. For paired samples, KDM5A, KMT2D, FLT3, SETBP1, ZRSR2, PRPF8, TET2, and TP53 showed mutations in both auto and SHM samples, showing stable or decreased VAFs. GATA2 showed two moderate impact missense mutations, one in a pt with a VAF of 0.58 in the auto sample and 0.40 in the SHM. The other GATA2 variant appeared as a novel mutation in one pt's SHM sample and was also present in two other pts with VAFs of 0.5 and 0.49 in the auto sample increasing to 0.81 and 0.70 in the SHM sample, respectively. TP53 showed the highest number of variants. Analysis showed 6 high impact variants with VAFs ranging from 0.05-0.80 and 3 moderate impact variants with VAFs ranging from 0.08-0.89. These mutations were represented in both the auto and SHM samples included. There were several TP53 alterations with the most frequent being structural interaction variants, missense variants, and frameshift variants. Conclusion: This limited cohort demonstrates that mutational profile for pts with SHM is distinct from de-novo myeloid malignancies, and the average mutational burden did not change from pre-transplant to the development of SHM. In this population, TP53, KMT2A, GATA2, and KMT2D represented the most frequent SHM mutations. Targeted deep sequencing revealed that most significant variants were present only in SHM samples suggesting a novel mutation rather than clonal evolution from the auto sample. Disclosures Hari: Incyte Corporation: Consultancy; Takeda: Consultancy; BMS: Consultancy; Amgen: Consultancy; GSK: Consultancy; Janssen: Consultancy.