Huebner, Lucas J.

PURPOSE CALGB 40601 assessed whether dual versus single human epidermal growth factor receptor 2 (HER2) –targeting drugs added to neoadjuvant chemotherapy increased pathologic complete response (pCR). Here, we report relapse-free survival (RFS), overall survival (OS), and gene expression signatures that predict pCR and survival. PATIENTS AND METHODS Three hundred five women with untreated stage II and III HER2-positive breast cancer were randomly assigned to receive weekly paclitaxel combined with trastuzumab plus lapatinib (THL), trastuzumab (TH), or lapatinib (TL). The primary end point was pCR, and secondary end points included RFS, OS, and gene expression analyses. mRNA sequencing was performed on 264 pretreatment samples. RESULTS One hundred eighteen patients were randomly allocated to THL, 120 to TH, and 67 to TL. At more than 7 years of follow-up, THL had significantly better RFS and OS than did TH (RFS hazard ratio, 0.32; 95% CI, 0.14 to 0.71; P = .005; OS hazard ratio, 0.34; 95% CI, 0.12 to 0.94; P = .037), with no difference between TH and TL. Of 688 previously described gene expression signatures, significant associations were found in 215 with pCR, 45 with RFS, and only 22 with both pCR and RFS (3.2%). Specifically, eight immune signatures were significantly correlated with a higher pCR rate and better RFS. Among patients with residual disease, the immunoglobulin G signature was an independent, good prognostic factor, whereas the HER2-enriched signature, which was associated with a higher pCR rate, showed a significantly shorter RFS. CONCLUSION In CALGB 40601, dual HER2-targeting resulted in significant RFS and OS benefits. Integration of intrinsic subtype and immune signatures allowed for the prediction of pCR and RFS, both overall and within the residual disease group. These approaches may provide means for rational escalation and de-escalation treatment strategies in HER2-positive breast cancer.

e16076 Background: Median overall survival (mOS) of patients (pt) with metastatic colorectal cancer (mCRC) has improved steadily over the past two decades. However, epidemiological data suggest that cancer outcomes for rural compared to urban dwelling pts are worse. In this study, we retrospectively compared progression free survival (PFS) and OS among mCRC pts residing in urban versus rural areas enrolled in N9741 (1997-2004) and CALGB 80405 (2005-2012) clinical trials. Methods: Zip code data from the Centers for Disease Control (CDC) were used to classify pts into rural or urban dwellers. Chi-square and Kruskal Wallis analyses were used to compare the groups. Survival outcomes were evaluated using Kaplan-Meier estimates, compared by stratified log rank and cox proportional hazards models. Results: In N9741 and 80405 respectively, 217 (35%) and 521 (21%) pts resided in rural areas. Median age of mCRC pts at diagnosis was 60.5 yrs. (rural) compared to 58.6 yrs. (urban) in 80405 (P < 0.01) and 59.6 yrs. to 60.2 yrs. in N9741 (P = 0.4). In 80405, pts in rural areas were less likely to be female (35% vs 43%, P < 0.01) black (6.6% vs 15.1%, P < 0.01), unmarried (51% vs 62%, P < 0.01), and to have private insurance (PI) (45% vs 50%, P = 0.03) when compared to pts in urban areas. In N9741, gender (P = 0.8) and PI (P = 0.3) distribution was similar; pts in rural areas were less likely to be black (1.4% vs 9.1%, P < 0.01). Rural vs urban pt PFS was no different in either trial. MOS was worse in pts in rural areas when compared to urban dwellers in 80405 (Table). OS outcomes stratified based on the use of cetuximab based regimen in 80405 showed worse outcomes for pts in rural compared to urban dwellers (21.9 vs 26.3 mo. HR: 1.22 (1.03-1.44), P = 0.02). Conclusions: MCRC pts from rural areas had a significantly worse mOS when compared to pts in urban areas in 80405. Furthermore, mOS with cetuximab based regimens was 4.4 months shorter in rural pts. The observed rural vs urban dweller mOS disparities in 80405 pts justifies additional research searching for causal factors and the necessity to identify actionable approaches in order to improve pt outcomes in rural areas. Support: U10CA180821, U10CA180882, U10CA180888, UG1CA180830; Pfizer, Sanofi, BMS, Genentech, https://acknowledgments.alliancefound.org . ClinicalTrials.gov Identifier: NCT00003594, NCT00265850. [Table: see text]

TPS594 Background: Effective treatment options are very limited for patients with advanced refractory biliary tract cancer (BTC). Fluoropyrimidine-based chemotherapy regimen such as 5-fluorouracil and irinotecan are frequently utilized for these patients after first-line therapy despite lack of FDA approval. Trifluridine/tipiracil (FTD/TPI) is a novel oral nucleoside with antitumor activity in both fluoropyrimidine sensitive and resistant tumors due to its unique mechanisms of action. Given early toxicity and efficacy data from our previous study on single-agent trifluridine/tipiracil (FTD/TPI) in advanced BTC, the clinical evaluation of its combination with irinotecan represents a rational approach for the treatment of advanced refractory BTC. Methods: This is a single-arm phase II trial with a two-stage design to assess the efficacy of trifluridine/tipiracil (FTD/TPI) and irinotecan in advanced refractory BTC. Key eligibility criteria include histologically confirmed advanced, unresectable BTC who have progressed on at least one line of systemic therapy and have measurable disease per RECIST v1.1. Target accrual is 25. Treatment includes trifluridine/tipiracil (FTD/TPI) 25 mg/m2 on days 1-5 and irinotecan 180 mg/m2 on day 1 in 14-day cycles. Patients will be evaluated for response every 4 cycles and in the absence of disease progression, therapy may be given up to 2 years. The primary end point is the progression-free survival rate at 16 weeks. Secondary endpoints include overall response rate, disease control rate, progression-free survival, overall survival, and incidence of adverse events. Correlative biomarker studies include evaluations of circulating tumor DNA and circulating tumor cells at baseline, after 4 cycles and at progression; and development of patient-derived tumor organoids from pre-treatment biopsies for parallel treatments. This study was approved and funded in part by the National Comprehensive Cancer Network (NCCN) Oncology Research Program from general research support provided by Taiho Oncology, Inc. Clinical trial information: NCT 04072445.

3532 Background: Colorectal cancer with dMMR display heterogeneity in the extent of intratumoral T-cell infiltration which may explain their variable responsiveness to PD-1 blockade. We examined the association of intratumoral CD3+ and CD8+ T-cell densities (TCD) with objective response rate (ORR) and response duration in patients with dMMR mCRCs receiving pembrolizumab (PEM). Methods: Record review was performed on 12 patients with dMMR mCRC treated with PEM (200 mg intravenously every 3 weeks) after failure of prior chemotherapy [median no. of regimens was 1 (range 1-4)] between 01/2015 and 12/2017. CD3+ and CD8+ TCDs were analyzed in the primary tumor core (CT) and at the invasive margin (IM) by immunohistochemistry and automated image analysis to determine density score (0 to 100) for each T-cell subtype and compartment (Ventana Medical Systems, Inc.). Patients were categorized as 1) responders [CR (complete response) + PR (partial response)] vs. non responders [SD (stable disease) + PD (progressive disease)] per RECIST version 1.1, and 2) by duration of response (< or > 12 months). Results: Median follow-up post PEM was 19.5 (9-41) months. Responders included 2 CR and 5 PR; non-responders included 4 SD and 1 PD. The ORR and median time to response were 58.3% (7/12) and 12 weeks (range 9-40), respectively. CD3+ and CD8+ TCD scores were higher in responders vs. in non-responders as well as in patients who had disease control for > 12 months; differences were greatest for CD8+ CT (Table). Conclusions: Among patients treated with PEM, data suggest higher intratumoral CD3+ and CD8+ TCDs in responders versus non-responders and in those with a longer duration of disease control. If confirmed, TCDs may potentially predict responsiveness to PD-1 blockade in dMMR mCRCs. [Table: see text]

3520 Background: Duration of adjuvant FOLFOX or CAPOX for stage III CC is being guided by pt stratification into low (T1-3N1) and high (T4 or N2) risk groups based on the IDEA study. We determined the relative contributions of clinical and molecular features for prediction of time-to-recurrence (TTR) and survival after recurrence (SAR) within each risk group. Methods: Stage III CC (N=5,430) from 2 trials of adjuvant FOLFOX ± cetuximab with similar outcome by study arm [NCCTG N0147 (Alliance), PETACC-8] were used. Tumors were analyzed for mismatch repair (dMMR vs pMMR), mutations in KRAS (exon 2) and BRAFV600E. Median pt follow-up was 83.4 months. Relative contributions to predicting outcome were assessed using χ2 (Harrell’s rms) based on multivariable (MV) Cox models. Results: N (50.8%) and T (31.8%) stage were the top two contributors to prediction of TTR which supports risk grouping. High risk (n=2566) vs low risk (n=2774) pts had poorer TTR (HR 2.7, 95% CI, 2.4-3.0) and SAR [HR 1.6 (1.4-1.9)], both p<.0001. TTR: KRAS contributed the most to predicting TTR among high (58.6%) and low (51.1%) risk pts (Table). Contribution of MMR (16%) to predicting TTR was limited to low risk pts. Contribution of BRAFV600E to TTR was nearly 3-fold increased in high vs low risk pts. SAR: BRAFV600E contributed the most to predicting SAR, especially in high vs low risk pts (2-fold increase). Tumor sidedness and performance status (PS) were key contributors to SAR, but not TTR. MV associations: TTR: low risk, KRAS [HR 1.7 (1.4-2.3], MMR [HR 0.55 (.35-.87), gender (M/F) [HR 1.3 (1.0-1.5)], all p<.04]; high risk: BRAF [HR 1.3 (1.1-1.7)], sidedness (R vs L) [HR 1.14 (1.0-1.3)], KRAS [HR 1.4 (1.2-1.6)], all p<.04]. SAR: BRAF, sidedness, PS (all p<.05). Conclusions: KRAS mutation was the strongest predictor of shorter TTR in both risk groups whereas BRAFV600E was the primary driver of SAR, especially in high risk pts. Support: U10CA180821, U10CA180882, U24CA196171; BMS, Pfizer, Sanofi. NCT00079274.[Table: see text]