Abstract: Colorectal cancer incidence in Korea is known to be one of the highest in the world. However, the detection methods from patients’ blood samples show relatively inefficient. Ribosomal protein S3 (rpS3), a multifunctional protein with a DNA repair endonuclease activity, has been known to be overexpressed and secreted from cancer cells but not from normal cells. Western blotting using antibodies against rpS3 protein revealed that this protein is overexpressed from cancer tissues of colorectal cancer patients comparing to normal tissues from the same patients. However, other proteins including other ribosomal proteins did not show this phenomenon. We also tested the secretion level of the protein using newly developed S3-1 antibody in the serum samples from 50 colorectal cancer patients and 50 healthy people to test the possibility as a cancer marker. All the diagnosed blood samples which were randomly selected among subjects in National Biobank of Korea were collected and serum was acquired by centrifugation. Samples were analyzed by dot blotting and ELISA methods. The detection level of S3-1 from the serum of colorectal cancer patients showed significantly higher than that from healthy control group. Also more than 60% from colorectal cancer patients’ serum showed sensitivity signals with 90% specificity which are significantly better than those of CEA or CA19-9 showing a possibility as a novel colorectal cancer biomarker. Citation Format: Joon Kim, Seon Hahn Kim, Kyung-Hwan Cho, Yeongkeun Kwon, Tae-Sung Kim, YouJin Jung, Hag Dong Kim. An efficient new detection method of colorectal cancers from blood samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3983.

Abstract: Clonal mosaicism, detectable in peripheral blood, can be an important predictor of developing a hematological malignancy. We sought to determine if mosaic events, in addition to clinical and demographic variables, contributed independent information about acute lymphoblastic leukemia (ALL) patient survival and risk of relapse after allogeneic hematopoietic cell transplant (HCT). HumanOmniExpress-12v1_A BeadChip SNP array data were used to detect mosaicisms & gt;=2Mb based on the log2 relative probe intensity ratio (LRR) and B allele frequency (BAF) for each SNP measured in 773 ALL patients from DISCOVeRY-BMT cohorts. DNA was extracted from recipient peripheral blood samples taken immediately prior to start of conditioning before allogeneic HCT for ALL (2000-2011). Mosaic events include copy-number gain (LRR & gt;0), loss (LRR & lt;0), or copy-neutral loss of heterozygosity (CNLOH), defined as a deviation from BAF heterozygosity without LRR changes. The impact of mosaicism on overall survival (OS) probability and cumulative incidence of relapse at 1-year post-HCT were calculated using the Kaplan-Meier estimator and cumulative incidence functions, respectively. The association of clonal mosaicism with OS was evaluated with multivariable Cox proportional hazard models. For disease relapse, competing risk models were used with transplant related mortality (TRM) treated as a competing event. Stratified survival analyses were performed by cytogenetic status at diagnosis. Statistical analyses were conducted using R 3.6.1. Thirty-four patients (4.4%) had 1 or more mosaicisms (82 total detected) with almost half having advanced disease (Table 1). The median proportion of affected cells was 61% (interquartile range = 39 - 93%). Copy-number losses on chromosomes 7 (13.4%) and 9 (8.54%) and 17 (6.10%) were the most frequently detected events (Figure 1). OS at 1-year post HCT in patients with and without a mosaic event was 26.5% and 60.1%, respectively, (P=8.2×10-8, Figure 2A) and normal cytogenetic patients with mosaicism had significantly lower survival compared to all other patients (OSnormal/mosaic+= 8.3% vs. OS= 60.6%, P=3.0×10-10, Figure 2B-C). ALL patients with a mosaic event also had an increased risk of disease relapse overall (Relapsemosaic+= 50% vs. Relapsemosaic-=26%, P=0.00067) and when stratified by cytogenetic abnormalities (P=0.015) and normal cytogenetics (P=0.041) (Figure 2D-F). Multivariable models of OS and relapse included age, race/ethnicity, complete remission or advanced disease status (Figure 3). Patients with a mosaic event had ~2.5 fold increase risk of death (P=2.5×10-5), independent from cytogenetics (P=8.6×10-5, Figure 3). OS associations are likely driven by the 2.8 fold increase risk of relapse (P= 5.9×10-5) which remains highly significant when stratified by cytogenetics (Figure 3). Almost half of the copy-number losses included well-known regions on chromosomes 7, 9 and 17 (Figure 1). Deletions of 7p have been shown to correlate with lower event-free survival in ALL pediatric patients. Our findings suggest mosaic loss of 7p might be an important indicator of poor OS across the lifespan, with 5/6 patients with 7p losses aged & gt;18 years. Higher mortality was also associated with the loss of the chr9p21.3 locus, seen in all patients (N=5) with chromosome 9p losses. This region harbors tumor suppressor CDKN2A; inactivation of CDKN2A can lead to poor survival in both children and adults with ALL. Lastly, we found that all patients (N=4) with copy-number loss of 17p13.1, which contains tumor suppressor TP53 died within 1-year post-HCT. We identified detectable mosaicism prior to transplant in 4.4% of patients and showed that mosaicism was associated with lower survival and higher disease relapse at 1-year post-HCT. While mosaicism is more common in patients with advanced disease stage, mosaic events are an independent contributor to lower survival and higher relapse in the first year after transplant. This is the first study to show that mosaic events detectable in pre-transplant peripheral blood from ALL patients are correlated with poor survival. Future studies replicating these associations in different ethnicities and age groups and evaluating specific chromosomal regions could be informative in classifying patient risk post-HCT attributable to mosaic events. Disclosures McCarthy: Karyopharm: Consultancy, Honoraria; Magenta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Genentech: Consultancy, Honoraria; Starton: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Juno Therapeutics, a Bristol-Myers Squibb Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board , Research Funding is to Roswell Park, Research Funding. Pasquini:Bristol Myers Squibb: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Other; Novartis: Research Funding; Kite: Research Funding. Lee:Pfizer: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Research Funding; Amgen: Research Funding; Kadmon: Research Funding; Incyte: Consultancy, Research Funding; AstraZeneca: Research Funding; Syndax: Research Funding.

Abstract: Introduction: Clinical cytogenetics is the most important prognostic test for patients with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS); however, current tools do not provide a complete genome-wide picture of somatic chromosomal aberrations in those patients. We used a high-resolution genome-wide single-nucleotide polymorphism (SNP) array to identify large clonal chromosomal aberrations in pre-hematopoietic cell transplant (HCT) peripheral blood samples of patients with de novo or therapy-related AML and MDS. Methods: We used the HumanOmniExpress-24 BeadChip SNP array genotyping data generated in the DISCOVeRY-BMT study (includes patients with acute leukemia or MDS who received unrelated donor HCT between 2000-2011). Clinical data and biospecimens were obtained from the Center for International Blood and Marrow Transplant Research. Blood samples were collected at median of 7 days before HCT. We limited our analysis to patients with AML (N=1,982) and MDS (N=608). We calculated the log2 R ratio and B allele frequency (BAF) and used the Circular Binary Segmentation (SBC) algorithm to identify chromosomal aberrations spanning ≥2Mb. Results: Median age at sample collection was 48.2 (range=0.6-78.0) and 53.0 (range=0.0-74.0) years for AML and MDS, respectively. About 53% of AML and 59% of MDS patients were males, and 7.4% of AML and 15.8% of MDS patients had therapy-related disease. Among AML patients, 47.9% were in 1st complete remission and 22.8% in 2nd complete remission. For MDS, 56.1% of patients were in early stage (refractory anemia with or without ringed sideroblasts) at the time of HCT. Chromosomal aberrations were detected in 14.6% of the AML patients (n=289) and 34.7% of the MDS patients (n=211). In AML, 6.6% of those with hematological or molecular remission vs. 35.9% of those with advanced disease (not in remission) had SNP-array detected aberrations, with 0.7% of the patients vs. 8.9%, respectively carrying aberrations in ≥3 chromosomes. For MDS, chromosomal aberrations were detected in 31.4 vs. 39.0% of patients with early and advanced MDS, respectively. No differences by patient sex or race were detected in both AML and MDS (p & gt;0.05). Figure 1 shows disease-specific type and frequency of detected chromosomal aberrations. Copy-losses in chr7 (chr7-), chr5 (chr5-), and copy-neutral loss of heterozygosity (CNLOH) in chromosome 17 (chr17-CNLOH) were the most common aberrations in both diseases, with higher frequencies in MDS (chr7-, 13.8 vs. 2.4%, respectively; chr5-, 7.2 vs. 1.8%; chr17-CNLOH, 4.4 vs. 1.5%, respectively, all p & lt;0.0001). In comparison, CNLOH in chr13 was more frequent in AML than MDS (1.5 vs. 0.2%, respectively, p & lt;0.01). Figure 2A shows detected chromosomal aberrations in de novo and therapy-related AML (tAML). The following were more frequently detected in tAML than de novo disease: copy-losses of chr5 (4.8 vs. 1.6%, p=0.02) and chr13 (2.7 vs. 0.6%, p=0.02). Aberrations in chromosomes 3, 10, 14, 15, 16 and 22 were found in de novo but not in tAML. The frequencies of chr7- (4.1 vs. 2.0%, in tAML and de novo, respectively, p=0.12) and copy-gain in chr8 (0.7 vs. 1.3%, p & gt;0.99) were similar in the two disease subtypes. Figure 2B shows detected chromosomal aberrations in de novo and treatment-related MDS (tMDS). The following were more common in tMDS than de Novo MDS: copy losses in chr5 (16.7 vs. 5.5%, p & lt;0.001), chr7 (26.0 vs. 11.5%, p & lt;0.001), and chr18 (7.3 vs. 1.6%, p & lt;0.01); also copy-gain in chr11 (4.2 vs. 0.4%, p & lt;0.01), and chr17-CNLOH (9.4 vs. 3.5%, p=0.03). Unique aberrations in de novo MDS included CNLOHs in chr7 (2.5%), chr14 (1.2%), chr1 (1.0%), chr4 (1.0%) and copy-gain in chr17 (1.0%). Conclusion: High-resolution SNP array analysis provided a genome-wide landscape of large chromosomal aberrations in patients with AML and MDS. Detected aberrations were more frequent in MDS than AML patients; this is possibly affected by differences in pre-HCT initial therapy. This study showed the expected genomic landscape similarities between AML and MDS, but differences were also present (most noted was chr13-CNLOH predominance in AML). The observed differences between de novo and t-AML or t-MDS likely reflect distinct pathogenic processes. Differences between t-AML and t-MDS could be related to antecedent malignancy and/or therapeutic regimen. The impact of these detected aberrations on HCT outcomes is under investigation. Disclosures Griffiths: Novartis Inc.: Consultancy; Celgene, Inc: Consultancy, Research Funding; Celgene, Inc: Consultancy, Research Funding; New Link Genetics: Consultancy; New Link Genetics: Consultancy; Persimmune: Consultancy; Boston Scientific: Consultancy; Boston Scientific: Consultancy; Persimmune: Consultancy; Genentech, Inc.: Research Funding; Abbvie, Inc.: Consultancy, PI on a clinical trial; Astex Phramaceuticals/Otsuka Pharmaceuticals: Consultancy, Research Funding; Abbvie, Inc.: Consultancy; Astex Phramaceuticals/Otsuka Pharmaceuticals: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Novartis Inc.: Consultancy; Appelis Pharmaceuticals: Other: PI on a clinical trial; Onconova Therapeutics: Other: PI on a clinical trial; Appelis Pharmaceuticals: Other: PI on a clinical trial; Onconova Therapeutics: Other: PI on a clinical trial; Partner Therapeutics: Consultancy; Partner Therapeutics: Consultancy. Thota:Incyte, Inc.: Speakers Bureau. Pasquini:Novartis: Research Funding; Kit Pharma: Research Funding; BMS: Research Funding; Medigene: Consultancy; Amgen: Consultancy; Pfizer: Other: Advisory Board. Lee:Takeda: Research Funding; Novartis: Research Funding; Amgen: Research Funding; Syndax: Research Funding; Incyte: Research Funding; Kadmon: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; AstraZeneca: Research Funding.