Mulkerin, Daniel

179 Background: Neuroligins are a family of postsynaptic cell adhesion molecules that play a crucial role in synapse formation and function. Recent studies suggest Neuroligin family genes (NLGN1,2,3,4X) may promote cancer cell growth and metastasis in various cancers, including colorectal cancer. Here, we investigated the association between neuroligin family gene expression and first-line treatment outcomes in mCRC. Methods: We evaluated the expression of 4 genes in the neuroligin family (NLGN1, NLGN2, NLGN3 and NLGN4X) on treatment outcomes of 433 pts with mCRC treated with either bevacizumab (Bev, n = 226) or cetuximab (Cet, n = 207) in combination with first-line chemotherapy within the CALGB/SWOG 80405 trial. mRNA was isolated from FFPE tumor samples and sequenced on the HiSeq 2500 (Illumina). Overall survival (OS) and progression-free survival (PFS) were compared between groups of pts categorized by low expression (Q1) (≤25 percentile), medium expression (Q2-3) (25th-75th percentile) and high expression (Q4)(>75th percentile) of NLGN family genes. The associations between gene expression and clinical outcomes were assessed via the multivariable Cox model and plotted with Kaplan-Meier curve. Treatment-gene interactions were evaluated using the likelihood ratio test. False discovery rate (FDR) was controlled through the Benjamini-Hochberg procedure. Results: High NLGN2 expression was associated with shorter PFS (median 10.0 mos, 95% CI (8.3, 11.3)) and OS (median 25.2mos, 95%CI (20.9, 30.0)) compared to low NLGN2 expression (PFS: median 11.2mos, 95% CI (9.8,14.3))(HR 1.41, 95% CI (1.06, 1.89)), P = 0.029). (OS: (median 31.8mos, 95%CI (26.8, 37.5)( HR 1.49, 95% CI (1.10, 2.01) P =0.0095) in multivariate analysis. Patients treated in the cetuximab arm(n=207), high HLGN2 expression significantly associated with shorter PFS (median 8.0 vs 13.4, HR 2.02, 95% CI (1.35, 3.03), P = 0.0021) and OS (median19.6 vs 36.3, HR 2.30, 95% CI (1.50, 3.53), P =8.3e-05). High NLGN3 expression was associated with shorter OS (23.9 vs 36.0 mos, P =0.0083) in cetuximab treatment arms, no significance found in PFS. We found significant treatment interaction for OS with NLGN2 and NLGN3 favoring cetuximab. In pts treated with cetuximab, High NLGN2 expression was significantly associated with shorter OS (median 29.1vs 36.3) (p=0.024) compared to pts treated with bevacizumab. For NLGN3, pts treated with cetuximab, high NLGN3 expression was significantly associated with shorter OS (median 25.0 vs 36.0) (p=0.018) compared to pts treated with bevacizumab. No significant association was found in NLGN1 and NLGN4X. Conclusions: Our results suggest NLGN2/3 gene expression may predict mCRC treatment outcomes. Potential therapeutic drug target NLGN in combination with anti-EGFR treatment in mCRC is warranted.

3588 Background: The brain-gut axis, a bidirectional network between the central and enteric nervous systems, plays a critical role in modulating the gastrointestinal tract function. Increasing evidence suggests that neuronal signaling molecules can promote gastrointestinal cancers; however, the mechanisms remain unclear. Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter and dysregulated GABA signaling has been found in CRC, affecting both tumor and tumor microenvironment. Here, we investigated the association between tumor GABA pathway gene expression and first-line treatment outcomes in mCRC. Methods: We evaluated the impact of the expression of 25 genes in the GABA pathway ( GABBR1, GABBR2, GABRA1, GABRA2, GABRA4, GABRA5, GABRA6, GABRB1, GABRB3, GABRD, GABRE, GABRG1, GABRG2, GABRG3, GABRQ, GABRR1, GABRR2, ABAT, ALDH5A1, GAD1, GAD2, SLC6A1, SLC6A13, SLC6A11, SLC6A12) on treatment outcomes (overall survival: OS; progression free survival: PFS) of 433 pts enrolled in the randomized, phase III CALGB/SWOG 80405 trial. RNA extracted from FFPE tumor samples was sequenced using the HiSeq 2500 (Illumina). The associations between gene expression (continuous, per standard deviation increase) and outcomes were assessed via the multivariable Cox proportional framework, with hazard ratios (HR) and 95% confidence intervals (CI) computed. The likelihood ratio test was used for interaction tests. False discovery rate (FDR) was controlled at 5% with the Benjamini-Hochberg method. Results: Overall, low GAD1 (encoding for glutamate decarboxylase 1, the enzyme responsible for catalyzing the production of GABA from L-glutamic acid) was associated with longer PFS (HR: 1.26, 95% CI [1.13, 1.41], P = 3.2E-05) and OS (HR 1.27 [1.13, 1.43], P = 5.9E-05) across all treatment arms. High ABAT (encoding for the aminotransferase responsible for GABA catabolism) was also associated with longer OS (HR 0.81 [0.72, 0.91], P = 6E-04). To evaluate the predictive value, interactions with targeted therapies bevacizumab (n = 226) vs cetuximab (n = 207) were tested. We found significant interactions for PFS with ABAT ( P= 0.0017) and OS with SLC6A13 ( P= 0.0014 ).In pts treated with cetuximab, high ABAT expression was significantly associated with longer PFS (HR 0.73 [0.61, 0.87], P = 2.8E-04), and high SLC6A13 was marginally associated with worse OS (HR 1.18 [1.00, 1.39], P = 0.052). We did not observe similar associations in pts treated with bevacizumab. Conclusions: Our results highlight a potential role for GABA signaling in affecting mCRC treatment outcomes, suggesting that GABA pathway genes may be promising novel predictive and prognostic biomarkers and supporting the rationale to investigate GABA as a target for drug development. ClinicalTrials.gov Identifier: NCT00265850

PURPOSE Structured data elements within electronic health records are health-related information that can be entered, stored, and extracted in an organized manner at later time points. Tracking outcomes for cancer survivors is also enabled by structured data. We sought to increase structured data capture within oncology practices at multiple sites sharing the same electronic health records. METHODS Applying engineering approaches and the Plan-Do-Study-Act cycle, we launched dual quality improvement initiatives to ensure that a malignant diagnosis and stage were captured as structured data. Intervention: Close Visit Validation (CVV) requires providers to satisfy certain criteria before closing ambulatory encounters. CVV may be used to track open clinical encounters and chart delinquencies to encourage optimal clinical workflows. We added two cancer-specific required criteria at the time of closing encounters in oncology clinics: (1) the presence of at least one malignant diagnosis on the Problem List and (2) staging all the malignant diagnoses on the Problem List when appropriate. RESULTS Six months before the CVV implementation, the percentage of encounters with a malignant diagnosis on the Problem List at the time of the encounter was 65%, whereas the percentage of encounters with a staged diagnosis was 32%. Three months after cancer-specific CVV implementation, the percentages were 85% and 75%, respectively. Rates had increased to 90% and 88% more than 2 years after implementation. CONCLUSION Oncologist performance improved after the implementation of cancer-specific CVV criteria, with persistently high percentages of relevant malignant diagnoses and cancer stage structured data capture 2 years after the intervention.