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Purpose: In the setting of biochemical failure (BCF) following primary treatment for prostate cancer, additional discrimination between clinically significant and non-clinically significant biochemical recurrence is critical in defining robust surrogate endpoints for prostate cancer and guiding salvage management decisions. We reviewed the literature to determine which prognostic factors are most significant for predicting prostate cancer-specific survival (PCSS), metastases-free survival (MFS), and/or overall survival (OS) after BCF.Materials and Methods: A search of PubMed from 1980 to 2013 yielded 999 studies that examined prognostic factors predictive for PCSS, MFS, and/or OS in prostate cancer patients with BCF following primary treatment. Eligibility criteria for inclusion were: 1) examined a prostate cancer population in the setting of BCF without overt clinical relapse following primary treatment with radical prostatectomy or radiotherapy; 2) based analyses on patient parameters obtained prior to the initiation of salvage therapies; and 3) determined clinical prognostic factors that were significant prognostic measures for at least one of three clinically relevant endpoints: OS, PCS, or MFS.Results: Nineteen eligible studies reported on 8,040 patients that experienced BCF from 1981-2013. The initial primary therapy was variable: radical prostatectomy alone (n=8), radiotherapy alone (n=4), radiotherapy/radical prostatectomy ± adjuvant therapy (n=5), and multiple treatment arms (n=2). There was also heterogeneity in which outcomes were assessed: PCSS (n=14), MFS (n=7), and OS (n=5). The prognostic factors most commonly found to be significant on multivariate analyses were PSA doubling time (PSADT), time to biochemical failure (TTBF), pathological Gleason score (pGS), and age.  Conclusions: Risk stratification in prostate cancer post-BCF is challenging because of limited predictive modeling that can determine which patients will optimally benefit from salvage therapy. Our systematic literature review has identified PSADT, TTBF, pGS, and age as the leading prognostic factors for the prediction of PCSS, MFS, and OS after BCF. We plan to leverage the Canadian ProCaRS database to perform predictive modeling using the putative findings in the present study in order to propose potential evidence-based surrogate endpoints for prostate cancer in the setting of BCF.

246 Background: Data suggests that changes in ctDNA quantity correlate with response to therapy in patients with advanced solid malignancies. However, there is little consistency on how to calculate and interpret such changes. Here, we apply a clinically-validated molecular response algorithm to a RW cohort of patients with aCRC to further evaluate its ability to assess treatment outcomes. Methods: We queried the Guardant INFORM database, which comprises aggregated commercial payer health claims and de-identified records from patients with comprehensive ctDNA testing via Guardant360 (G360) from September 2018-March 2022. Patients with aCRC who received G360 within 15 weeks prior to new treatment initiation (any line of therapy) and a second test 3-15 weeks after treatment initiation were retrospectively evaluated using the G360 Response algorithm. Cox proportional hazards (CPH) were used for RW time to next treatment (TTNT), time to treatment discontinuation (TTD), and overall survival (rwOS) analyses. Patients categorized as molecular responders had a >50% decrease in mean variant allele fraction (VAF) ratio from pre-treatment to on-treatment. Gender, age, line of therapy (LOT) and comorbidities were included as covariates. Median TTNT, TTD, and rwOS were calculated by Kaplan Meier. Results: Of 185 aCRC patients with eligible MR results, 65% received chemotherapy +/- VEGF, 21% received regimens containing anti-EGFR monoclonal antibodies, and 14% received other therapies. 43% of aCRC patients were classified as molecular responders, 42% were non-responders, and 15% were not evaluable by the algorithm due to no/low ctDNA at one or both timepoints. 16% of patients cleared their ctDNA on treatment (i.e., ctDNA became undetectable). Molecular responders had significantly longer TTNT (median 10.1 months vs 6.1 months; HR p < 0.005), TTD (median 5.2 Months vs 3.9 months, HR p=0.041), and rwOS (not reached vs 17.8 months, HR p=0.017). Conclusions: Patients with aCRC classified as molecular responders, as calculated by this algorithm, had prolonged time on treatment and overall survival. Compared to tumor markers, ctDNA has a short half-life, which can allow for early response assessment, as shown by our study. These findings are relevant for clinical care, with future potential to allow for adaptive clinical trial design. [Table: see text]

432 Background: Pancreatic cancer is associated with poor outcomes at any stage. A very small number of patients - approximately 3% of those with metastatic disease - experience long-term survival through 5 years but the biologic mechanisms underlying the benefit observed with these “exceptional responders” are incompletely understood. We explored potential genomic differences between exceptional responders and typical responders to treatment for advanced pancreatic cancer that could confer a more favorable biology. Methods: We included consecutive exceptional responders and matched controls (MCs) with advanced pancreatic cancer in a 1:3 ratio from the Cleveland Clinic from April, 2013 – August, 2017. ERs were defined as patients with overall survival (OS) > 18 months for metastatic disease and > 24 months for locally advanced disease. Controls were matched by age, gender, stage and type of chemotherapy given and experienced OS at or below median survival for their stages. Clinical variables including demographics, comorbidities, stage, histology and treatment history were collected. Next generation sequencing (NGS) was performed for DNA sequencing of 648 genes and tumor mutation burden (TMB) on available tissue. The study population initially comprised of 14 exceptional responders and 42 MCs. However, only 4 exceptional responders and 6 MCs were included for analysis due to insufficient tissue for NGS for the remaining patients. Descriptive statistics were used for statistical analysis. Differences in survival outcomes were assessed using the Kaplan-Meier method and log-rank test. Results: The median ages for the exceptional responders and MCs were 69 and 67.5 years, respectively. Both groups were at least 75% male and white. Of the exceptional responders, 50% had pancreatic tail primaries compared to 0% of the MCs. There were no differences between groups in first-line chemotherapy used. Exceptional responders had significantly fewer non-synonymous mutations compared to MCs (2.25 vs. 5.17, p = 0.014). Mutation count < 3 was associated with significantly better progression-free survival (PFS) and OS as shown in the Table. TMB did not differ between exceptional responders and MCs (4.88 vs. 5.70 Muts/Mb, p = 0.39). Of the exceptional responders, 50% had alterations in BAGE2 versus 0% of MCs. Conversely, 50% of MCs had alterations in LRP1B, CUL4B or APC vs. 0% of exceptional responders. Conclusions: Having a lower number of non-synonymous mutations may correlate with exceptional response to systemic therapy and therefore with improved survival in pancreatic cancer. Pancreatic tail primary may also be associated with improved outcomes. These findings, though limited by small sample size, should encourage future study into genomic signatures of exceptional response. [Table: see text]

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