Background and objectives Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open‐source software tailored for this purpose and describe its validation with three blood group systems. Materials and methods The DTM‐Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long‐read NGS platform. Results Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases. Conclusion DTM‐Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM‐Tools is open‐source and in continuous development.
Adenosquamous carcinoma of the prostate is an exceedingly rare and aggressive histologic variant of prostate cancer, which is composed of glandular and squamous components. Up to two-thirds of these cases are identified in patients with a history of adenocarcinoma after treatment with androgen deprivation therapy or radiation therapy; however, multiple cases have been reported arising de novo. Patients frequently present with obstructive urinary complaints and bony osteolytic metastases. Serum prostate-specific antigen is usually normal or slightly elevated. We describe a rare case of de novo metastatic adenosquamous carcinoma in a patient presenting with a markedly elevated serum prostate-specific antigen and multiple osteoblastic lesions. The prognosis for patients with adenosquamous carcinoma of the prostate has historically been dismal, with death occurring within 12 to 24 months of diagnosis.
Introduction: Red blood cell (RBC) transfusions are central in the management of sickle cell disease (SCD), an inherited hemoglobinopathy characterized by hemolysis, acute pain, and multi-systemic complications. Extended matching of patient and donor RBC antigens is an established strategy to minimize alloimmunization, which can make provision of compatible blood difficult and can result in severe, even lethal hemolytic transfusion reactions. While RBC genotype matching has proven valuable in SCD transfusion practice, current technologies are often limited in throughput and focus on selected blood groups and known variants. Limited information is available comparing whole genome sequencing (WGS) with other blood typing platforms in SCD. Design/Methods: WGS was performed on stored blood samples from 621 SCD patients recruited into two clinical studies. We utilized our open-source Python application (RyLAN), to translate WGS data into a predicted extended RBC and platelet phenotype. The 467 genomic variants interpreted by RyLAN in 41 genes were correlated with clinical and laboratory data in the immunohematology and electronic health records (Figure 1). Results: The 621 patients included 485 HbSS, 21 HbSb0, 29 HbSβ+, 84 HbSC, 1HbS O Arab, and 1 HbSD. The mean age was 34.3 ± 12.1 years, and 54% were female. Health records indicated that 383 (62%) patients had previously received RBC transfusions and 17(3%) had never been transfused; the status of the remaining 221 was unknown. RyLAN software was executed as a singularity container in multithreaded mode, completing the analysis of all 621 bam WGS files in 8.5 hours (8 CPUs and 16GB of memory per file). The average read depth for genomic positions of interest was 33 and the average QUAL value was 644. The highest variant allele frequency was detected at the Fyb, ACKR1 promoter, and the KCAM- loci (94%, 86% and 82%, respectively). Each of the 621 participants demonstrated a unique extended blood group genotype through WGS. RyLAN predicted 237 unique extended platelet phenotype combinations in this cohort, including HPA-25bw and HPA-13bw positive patients. Blood antigen WGS predictions were correlated with other typing methods in 112 individuals: 192 total serologic reactions for 8 antigens; 55 documented alloantibodies; 25 genomic variants in 71 participants by probe-elongation array; and PCR with sequence-specific primers for 8 variants in 13 individuals (Figure 1). Two instances of heterozygosity (Jka/Jkb and Doa/Dob) were undetected due to low read depth, and 8 unresolved discrepancies were identified: 2 with serology, 1 with a reported historical alloantibody, 2 with probe-elongation array determinations, and 1 with the PCR method. WGS detected multiple weak blood group variants, surpassing the sensitivity of serology in one complex case, as well as rare phenotypes including 4 Yka-, 5 Kna/Knb, 1 FORS1-, and 2 Jra- cases. The algorithm correctly predicted an Sla-negative RBC phenotype in a patient with documented anti-Sla alloantibody. Conclusion: We describe an efficient, open-source algorithm used to interpret 35 minor blood group and 6 platelet antigen genes from WGS in a large SCD cohort. Eight unresolved discrepancies were identified from 2126 correlation events with serology, alloimmunization history, and other genotyping methods in a subset of 112 individuals. WGS demonstrated higher sensitivity for weak antigen detection compared with serology, and a capacity to detect rare phenotypes not readily determined by other methods. Sanger resequencing is currently in progress to validate rare phenotype predictions and resolve remaining discrepancies. Future studies are needed to refine WGS algorithms in SCD, and determine the value of this technology for alloantibody identification, optimal blood group allocation, and donor recruitment. Figure 1. Figure 1. Disclosures No relevant conflicts of interest to declare.
Introduction: Patients with sickle cell disease (SCD) are at increased risk of alloimmunization. Platelet refractoriness is a serious known complication and often seen in SCD patients who are heavily transfused and/or in the bone marrow transplantation (BMT) setting. Next generation sequencing (NGS) is an emerging and promising genotyping strategy in the context of blood typing, due its high throughput and its ability to detect both known and novel variants in the patient and donor population. Here we describe an algorithm to predict common and rare human platelet antigens (HPA) from NGS data, and its validation through Sanger sequencing. Design/Methods: Whole genome sequencing (WGS) was performed on stored blood samples from 621 SCD patients enrolled in 2 IRB-approved clinical studies. Our open source software RyLAN (Red Cell and Lymphocyte Antigen prediction from NGS) was utilized to translate WGS data into predicted RBC and platelet phenotypes. The 29 genomic variants interpreted by RyLAN in 6 HPA genes were correlated with Sanger sequencing. Results: Our study cohort consisted of 621 SCD patients (485 HbSS, 21 HbSβ0, 29 HbSβ+, 84 HbSC, 1HbS O Arab, and 1 HbSD). The mean age was 34.3 years, and 46% were male. Previous red cell transfusions were recorded in 62% of patients, and 3% were documented as never transfused. RyLAN software was executed as a singularity container in multithreaded mode, completing analysis of all 621 .bam WGS files in 18 hours. RyLAN predicted 237 unique extended platelet phenotype combinations in this cohort, with an average read depth of 33 in genomic areas of interest. Predictions for 10 platelet antigens in 26 participants, including rare phenotypes like HPA-25bw+ and HPA-13bw+, were confirmed by bidirectional Sanger. Conclusions: We describe an efficient, open-source algorithm used to interpret 6 HPA genes from WGS in a large SCD cohort. WGS, in conjunction with the RyLAN algorithm, demonstrated 100% accuracy in predicting common and rare HPA genomic variants. Future studies are needed to refine WGS algorithms in SCD, and to examine the possible value of this technology in HPA alloantibody identification workups, optimal platelet product allocation, and donor recruitment. Disclosures No relevant conflicts of interest to declare.
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