Wang, Hong

TPS9607 Background: The majority of 100,000 annual new U.S. cases of mel consist of localized early-stage disease that undergo wide local excision (WLE) +/- SLN biopsy (SLNB). The tumor draining lymph node is the initial site of immune response including formation of tumor mediated immune suppression and pre-metastatic niches. SLN positivity is a key prognostic factor in early stage mel. Thus, the SLN is a target for local immune intervention to boost the antitumor response. Vusolimogene oderparepvec (RP1) is an intratumorally administered oncolytic immunotherapy with unique potential for neo-adjuvant therapeutic application. RP1 is constructed from a high potency HSV1 strain (RH018A) modified to replicate selectively in tumors (deletion of neurovirulence factors ICP34.5 and ICP47). RP1 encodes GM-CSF and a fusogenic GALV-GP R- protein to maximize oncolytic potency and induce immunogenic cell death. Preclinical and clinical data demonstrate robust antitumor efficacy (including non-injected lesions) of RP1 alone and in combination with checkpoint inhibitors in advanced mel. This trial addresses a crucial gap in understanding the impact of RP1 on SLN dynamics and preventing disease recurrence in high-risk patients (pts). We hypothesize that in pts with high risk, clinically node negative mel (pT3b-T4b), RP1 will reduce rates of SLN positivity as compared to a historic control by favorably reshaping the immune landscape of the primary tumor, SLN, and the peripheral blood. Methods: This is an investigator-initiated, single arm phase 1/2 trial (NCT06216938) designed to assess efficacy and safety of neo-adjuvant RP1 in high-risk, clinically node-negative, non-uveal mel. Eligibility criteria: pT3b, T4a, or T4b non-uveal mel with visible residual tumor or positive biopsy margins, ECOG ≤1, and no prior oncolytic virus therapy. Pts receive 3 doses of neo-adjuvant RP1 (10e6 PFU day 1, 10e7 PFU on days 15 and 21), injected at the primary tumor site followed by standard WLE and SLNB within 35 days of dose 1. Biopsy of residual tumor or archival tumor tissue is obtained pre-RP1 and archival tissue from WLE and SLNB is obtained post-RP1. Blood samples are obtained with each RP1 dose and 3 months post-therapy. Pts are followed for 3 years. Primary endpoint: rate of SLN positivity in the overall cohort. Secondary endpoints: treatment related adverse events (per CTCAE), recurrence free survival, and overall survival. Exploratory endpoints: immunophenotype and microenvironment of the primary tumor, SLN and peripheral blood pre- and post- RP1 (via IHC, IF, and flow cytometry). The observed rate of SLN positivity will be compared to the predicted rate (Melanoma Institute of Australia Prediction Tool for SLN metastatic risk) with a one-sided, one-sample proportion test. Kaplan-Meier estimates will be provided for survival endpoints. The trial is active with 13 of 25 pts enrolled in January 2025. Clinical trial information: NCT06216938 .

The current standard of care for patients with locally advanced rectal cancer (LARC) is neoadjuvant chemoradiation (nCRT) followed by total mesorectal excision surgery. However, the response to nCRT varies among patients and only about 20% of LARC patients achieve a pathologic complete response (pCR) at the time of surgery. Therefore, there is an unmet need for biomarkers that could predict the response to nCRT at an early time point, allowing for the selection of LARC patients who would or would not benefit from nCRT. To identify blood-based biomarkers for prediction of nCRT response, we performed in-depth quantitative proteomic analysis of pretreatment plasma from mice bearing rectal tumors treated with concurrent chemoradiation, resulting in the quantification of 567 proteins. Among the plasma proteins that increased in mice with residual rectal tumor after chemoradiation compared to mice that achieved regression, we selected three proteins (Vascular endothelial growth factor receptor 3 [VEGFR3], Insulin like growth factor binding protein 4 [IGFBP4], and Cathepsin B [CTSB]) for validation in human plasma samples. In addition, we explored whether four tissue protein biomarkers previously shown to predict response to nCRT (Epidermal growth factor receptor [EGFR], Ki-67, E-cadherin, and Prostaglandin G/H synthase 2 [COX2]) also act as potential blood biomarkers. Using immunoassays for these seven biomarker candidates as well as Carcinoembryonic antigen [CEA] levels on plasma collected before nCRT from 34 patients with LARC (6 pCR and 28 non-pCR), we observed that levels of VEGFR3 (p = 0.0451, AUC = 0.720), EGFR (p = 0.0128, AUC = 0.679), and COX2 (p = 0.0397, AUC = 0.679) were significantly increased in the plasma of non-pCR LARC patients compared to those of pCR LARC patients. The performance of the logistic regression model combining VEGFR3, EGFR, and COX2 was significantly improved compared with the performance of each biomarker, yielding an AUC of 0.869 (sensitivity 43% at 95% specificity). Levels of VEGFR3 and EGFR were significantly decreased 5 to 7 months after tumor resection in plasma from 18 surgically resected rectal cancer patients, suggesting that VEGFR3 and EGFR may emanate from tumors. These findings suggest that circulating VEGFR3 can contribute to the prediction of the nCRT response in LARC patients together with circulating EGFR and COX2.

3519 Background: An understanding of the mechanisms of acquired resistance to CDK4 & 6 inhibitors, either alone or with endocrine therapy (ET), is an unmet need. Abemaciclib is a CDK4 & 6 inhibitor approved for treatment of HR+, HER2- advanced breast cancer (ABC). Here we evaluated acquired genomic alterations detected in circulating tumor DNA (ctDNA) from patients (pts) treated with abemaciclib + nonsteroidal aromatase inhibitor (AI) or placebo + AI in MONARCH 3 or abemaciclib monotherapy in nextMONARCH 1. Methods: MONARCH 3 randomized postmenopausal women with HR+, HER2- ABC with no prior systemic therapy in the advanced setting to abemaciclib (150 mg Q12H) or placebo + AI. nextMONARCH 1 randomized women with HR+, HER2- metastatic breast cancer who had progressed on or after prior ET and CT to abemaciclib (150 mg Q12H) + tamoxifen, abemaciclib (150 mg Q12H), or abemaciclib (200 mg Q12H) + loperamide. Plasma from pts in the abemaciclib or placebo + AI arms (MONARCH 3) or abemaciclib monotherapy arms (nextMONARCH 1) was analyzed by the Guardant360 assay to identify potential tumor-related genomic alterations including point mutations, indels, amplifications, and fusions acquired at EOT in comparison with baseline. Results: For MONARCH 3, commonly acquired alterations at EOT included ESR1 (17%), TP53 (10%), EGFR (8%), FGFR1 (7%), and PDGFRA (7%) in the abemaciclib + AI arm, and ESR1 (31%), TP53 (10%), and BRCA1 (7%) in the placebo + AI arm. Acquired alterations more frequent for abemaciclib + AI pts included RB1 (6%), MYC (5%), and AR (5%), compared to 0% in the placebo + AI arm (p = 0.008 RB1; p = 0.015 MYC or AR). In contrast, acquired ESR1 alterations were less frequent with abemaciclib + AI vs placebo + AI (17% vs 31%, p = 0.038). In nextMONARCH 1, the most commonly acquired alterations with abemaciclib monotherapy were in TP53 (10%), EGFR (9%), RB1 (9%), MYC (9%), and MET (8%). In addition, acquired alterations in ESR1 (6%) and AR (3%) were also found. PIK3CA alterations were not frequently acquired (abemaciclib + AI 1%, placebo + AI 6%, abemaciclib monotherapy 5%). Conclusions: Acquired genomic alterations potentially associated with emerging mechanisms of resistance to abemaciclib alone or in combination with AI may include RB1, MYC, or AR alterations, while the acquisition of ESR1 alterations was less common in pts treated with abemaciclib + AI compared to placebo + AI. These findings are hypothesis-generating and provide insight into mechanisms of resistance to abemaciclib vs ET. Clinical trial information: NCT02246621, NCT02747004 .

Abstract Background: Venous thromboembolism (VTE) is an important cause of morbidity and mortality in patients with hematologic malignancies (HMs). The national burden of inpatient VTE in patients with HMs is not known. Methods: We used the National Inpatient Sample (NIS), one of the largest publicly-available inpatient dataset in United States (U.S.), which represents a 20% stratified random sample of discharges from all hospitals, excluding rehabilitation and long-term acute care hospitals. The NIS is drawn from all States participating in Healthcare Cost and Utilization Project, representing more than 95 percent of the U.S. population. Discharge weights are used to generate national estimates. Patients with HMs were identified using ICD9 codes published by NIS and VTE was defined by ICD9 codes 451 - 453 and 415.1. Annual rates of inpatient VTE were calculated from 1993 to 2012 by HM type. Multivariate odds of inpatient VTE was determined by logistic regression controlling for confounders (age, sex, Charlson co-morbidity index, metastasis, chemotherapy, transfusion of blood products, major operating room procedure, primary hypercoagulable state, disseminated intravascular coagulation, heparin induced thrombocytopenia and thrombosis, antiphospholipid syndrome, obesity and calendar year). The malignancies with non-specific designation (e.g. unspecified leukemia) or with less than 1000 patients (weighted number) were excluded from results. Results: 8.42million hospitalized patients (weighted number) with HMs were identified, and 335,240had VTE (3.98%). In patients with HMs, rates of inpatient VTE increased from 2.59% to 5.22% between 1993 and 2012 (p<0.01). A detailed analysis of VTE rates for various HMs is presented in Table 1. The HMs with highest odds of inpatient VTE are peripheral T-cell lymphoma (PTCL), anaplastic large cell lymphoma (ALCL) and primary central nervous system (CNS) lymphoma (OR 1.56, 1.53, and 1.39, p<0.05) as compared to all other HM. Among leukemias, hairy cell leukemia had higher odds of VTE (OR 1.19, p<0.05). The HMs with the least odds of VTE were acute lymphoid leukemia, chronic monocytic leukemia and plasma cell leukemia (OR 0.65, 0.66 and 0.71, p<0.05). The HMs with the highest rates of VTE were PTCL, large cell lymphoma and ALCL (6.96%, 6.35% and 6.27%). The HMs with lowest rate of VTE were megakaryocytic leukemia, acute lymphoid leukemia and acute monocytic leukemia (1.42%, 2.04%, and 2.73%). Conclusions: Our study provides national estimates of inpatient VTE in HM, which are increasing over the last 20 years. Certain HMs have higher rates and odds of VTE as compared to others. Identification of these differences provides valuable information for the use of prophylaxis in HM with high risk of VTE. Table 1. Multivariate Odds and Rates of Inpatient Venous Thromboembolism in Patients with Hematologic Malignancies (Total weighted N = 8.42 million) Hematologic malignancy Inpatient VTE rate (%) Adjusted OR (95% CI) of inpatient VTE compared to all other HM Hodgkin's disease Hodgkin's disease - lymphocyte rich 3.86 1.15 (0.82 - 1.61) Hodgkin's disease - nodular sclerosing 4.04 1.3 (1.18 - 1.43) Hodgkin's disease - mixed cellularity 4.02 1.22 (0.89 - 1.68) Hodgkin's disease - lymphocyte depleted 3.88 1.14 (0.73 - 1.77) Non-hodgkin's lymphoma Nodular lymphoma 4.89 1.2 (1.13 - 1.28) Mycosis fungoides 4.83 1.25 (1.16 - 1.35) Sezary's disease 3.99 1.08 (0.72 - 1.62) Peripheral t-cell lymphoma 6.96 1.56 (1.32 - 1.85) Burkitt's lymphoma 3.44 1.05 (0.97 - 1.15) Marginal zone lymphoma 5.57 1.07 (0.91 - 1.26) Mantle cell lymphoma 4.91 1.03 (0.92 - 1.15) Primary CNS lymphoma 6.18 1.39 (1.18 - 1.64) Anaplastic large cell lymphoma 6.27 1.53 (1.21 - 1.94) Large cell lymphoma 6.35 1.36 (1.22 - 1.51) Sarcoma Myeloid sarcoma 4.24 1.14 (0.9 - 1.44) Myeloma and leukemia Multiple myeloma 4.57 1.14 (1.1 - 1.18) Plasma cell leukemia 2.85 0.71 (0.5 - 1) Lymphoid leukemia - acute 2.04 0.65 (0.61 - 0.69) Lymphoid leukemia - chronic 3.43 0.76 (0.73 - 0.78) Myeloid leukemia - acute 3.71 0.97 (0.93 - 1) Myeloid leukemia - chronic 2.93 0.72 (0.68 - 0.76) Monocytic leukemia - acute 2.73 0.75 (0.59 - 0.96) Monocytic leukemia - chronic 2.74 0.66 (0.44 - 0.98) Erythrocytic leukemia - acute 2.95 0.81 (0.5 - 1.32) Megakaryocytic leukemia 1.42 0.48 (0.23 - 1.02) Hairy cell leukemia 4.72 1.19 (1.07 - 1.32) Disclosures No relevant conflicts of interest to declare.