Citations

AbstractUnderstanding intratumor heterogeneity is critical for studying tumorigenesis and designing personalized treatments. To decompose the mixed cell population in a tumor, subclones are inferred computationally based on variant allele frequency (VAF) from bulk sequencing data. In this study, we showed that sequencing depth, mean VAF, and variance of VAF of a subclone are confounded. Without considering this effect, current methods require deep-sequencing data (>300× depth) to reliably infer subclones. Here, we present a novel algorithm that incorporates depth-variance and mean-variance dependencies in a clustering error model and successfully identifies subclones in tumors sequenced at depths of as low as 30×. We implemented the algorithm as a model-based adaptive grouping of subclones (MAGOS) method. Analyses of computer simulated data and empirical sequencing data showed that MAGOS outperformed existing methods on minimum sequencing depth, decomposition accuracy, and computation efficiency. The most prominent improvements were observed in analyzing tumors sequenced at depths between 30× and 200×, whereas the performance was comparable between MAGOS and existing methods on deeply sequenced tumors. MAGOS supports analysis of single-nucleotide variants and copy number variants from a single sample or multiple samples of a tumor. We applied MAGOS to whole-exome data of late-stage liver cancers and discovered that high subclone count in a tumor was a significant risk factor of poor prognosis. Lastly, our analysis suggested that sequencing multiple samples of the same tumor at standard depth is more cost-effective and robust for subclone characterization than deep sequencing a single sample. MAGOS is available at github (https://github.com/liliulab/magos).

AbstractBackgroundPlatelet transfusion carries risk of transfusion‐transmitted infection (TTI). Pathogen reduction of platelet components (PRPC) is designed to reduce TTI. Pulmonary adverse events (AEs), including transfusion‐related acute lung injury and acute respiratory distress syndrome (ARDS) occur with platelet transfusion.Study designAn open label, sequential cohort study of transfusion‐dependent hematology‐oncology patients was conducted to compare pulmonary safety of PRPC with conventional PC (CPC). The primary outcome was the incidence of treatment‐emergent assisted mechanical ventilation (TEAMV) by non‐inferiority. Secondary outcomes included: time to TEAMV, ARDS, pulmonary AEs, peri‐transfusion AE, hemorrhagic AE, transfusion reactions (TRs), PC and red blood cell (RBC) use, and mortality.ResultsBy modified intent‐to‐treat (mITT), 1068 patients received 5277 PRPC and 1223 patients received 5487 CPC. The cohorts had similar demographics, primary disease, and primary therapy. PRPC were non‐inferior to CPC for TEAMV (treatment difference −1.7%, 95% CI: (−3.3% to −0.1%); odds ratio = 0.53, 95% CI: (0.30, 0.94). The cumulative incidence of TEAMV for PRPC (2.9%) was significantly less than CPC (4.6%, p = .039). The incidence of ARDS was less, but not significantly different, for PRPC (1.0% vs. 1.8%, p = .151; odds ratio = 0.57, 95% CI: (0.27, 1.18). AE, pulmonary AE, and mortality were not different between cohorts. TRs were similar for PRPC and CPC (8.3% vs. 9.7%, p = .256); and allergic TR were significantly less with PRPC (p = .006). PC and RBC use were not increased with PRPC.DiscussionPRPC demonstrated reduced TEAMV with no excess treatment‐related pulmonary morbidity.

Abstract Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low overall survival rates and high molecular heterogeneity; therefore, few targeted therapies are available. The luminal androgen receptor (LAR) is the most consistently identified TNBC subtype, but the clinical utility has yet to be established. Here, we constructed a novel genomic classifier, LAR-Sig, that distinguishes the LAR subtype from other TNBC subtypes and provide evidence that it is a clinically distinct disease. A meta-analysis of seven TNBC datasets (n = 1086 samples) from neoadjuvant clinical trials demonstrated that LAR patients have significantly reduced response (pCR) rates than non-LAR TNBC patients (odds ratio = 2.11, 95% CI: 1.33, 2.89). Moreover, deconvolution of the tumor microenvironment confirmed an enrichment of luminal epithelium corresponding with a decrease in basal and myoepithelium in LAR TNBC tumors. Increased immunosuppression in LAR patients may lead to a decreased presence of cycling T-cells and plasma cells. While, an increased presence of myofibroblast-like cancer-associated cells may impede drug delivery and treatment. In summary, the lower levels of tumor infiltrating lymphocytes (TILs), reduced immune activity in the micro-environment, and lower pCR rates after NAC, suggest that new therapeutic strategies for the LAR TNBC subtype need to be developed.

The ability to regulate gene activity spatially and temporally is essential to investigate cell-type-specific gene function during development and in postembryonic processes and disease models. The Cre/ lox system has been widely used for performing cell and tissue-specific conditional analysis of gene function in zebrafish. However, simple and efficient methods for isolation of stable, Cre/ lox regulated zebrafish alleles are lacking. Here, we applied our GeneWeld CRISPR-Cas9 targeted integration strategy to generate floxed alleles that provide robust conditional inactivation and rescue. A universal targeting vector, UFlip, with sites for cloning short homology arms flanking a floxed 2A-mRFP gene trap, was integrated into an intron in rbbp4 and rb1. rbbp4 off and rb1 off integration alleles resulted in strong mRFP expression,>99% reduction of endogenous gene expression, and recapitulated known indel loss-of-function phenotypes. Introduction of Cre led to stable inversion of the floxed cassette, loss of mRFP expression, and phenotypic rescue. rbbp4 on and rb1 on integration alleles did not cause phenotypes in combination with a loss-of-function mutation. Addition of Cre led to conditional inactivation by stable inversion of the cassette, gene trapping and mRFP expression, and the expected mutant phenotype. Neural progenitor Cre drivers were used for conditional inactivation and phenotypic rescue to showcase how this approach can be used in specific cell populations. Together these results validate a simplified approach for efficient isolation of Cre/ lox -responsive conditional alleles in zebrafish. Our strategy provides a new toolkit for generating genetic mosaics and represents a significant advance in zebrafish genetics.

Abstract Background: Over 20 susceptibility single-nucleotide polymorphisms (SNP) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett esophagus (BE), explaining a small portion of heritability. Methods: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene-expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTL), and set-based SKAT association using selected eQTLs that predict the gene expression. Results: Although the standard approach did not identify significant signals, the eQTL set–based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641, and HSP90AA1). Conclusions: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set–based genetic association approach. Impact: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set–based genetic association approach as an alternative method for TWAS analysis.

Abstract Background: We compared the predictive and prognostic value of ctDNA dynamics in high-risk hormone receptor-positive/HER2-negative (HR+/HER2-) and triple negative breast cancer (TNBC) receiving neoadjuvant chemotherapy (NAC) enrolled in the I-SPY 2 trial (NCT01042379). To our knowledge, this is the largest ctDNA study in breast cancer in the neoadjuvant setting. Methods: Blood samples were collected at pre-treatment (T0), during treatment (T1 at 3 weeks, and T2 at 12 weeks) and after NAC (T3 at 24 weeks) from 106 HR+/HER2- and 97 TNBC patients. Plasma samples (n=734) were analyzed using a personalized and tumor-informed mPCR NGS-based ctDNA test (SignateraTM). Patients, all high risk for recurrence by MammaPrint, received paclitaxel-based treatment +/- experimental therapy followed by anthracycline. The median follow-up was 3.0 years (0.5 to 6.5). The predictive and prognostic value of ctDNA dynamics and status at different timepoints were examined. Our analysis is exploratory and does not adjust for other biomarkers. Results: Pretreatment ctDNA positivity (Fisher p<0.0001) and levels (mean tumor molecules/mL, MTM/mL, t test p=0.0062) were significantly higher in TNBC (90.7%, 14.7 MTM/mL) than in high risk HR+/HER2- (66.0%, 5.5 MTM/mL). Early and late ctDNA clearance during treatment (3 and 12 weeks of NAC) was predictive of pathologic complete response (pCR) and residual cancer burden (RCB), class 0-III, in TNBC but not HR+/HER2- (Table). In both subtypes: (1) ctDNA was a significant negative prognostic factor for distant recurrence-free survival (DRFS) at all timepoints (p<0.05) except at pretreatment; (2) all patients who achieved pCR were ctDNA-negative after NAC; (3) among non-responding patients, ctDNA-negativity after NAC was associated with improved DRFS (Table). Conclusions: The predictive value of ctDNA for prediction of pCR and RCB differed between subtypes (HR+/HER2- vs. TNBC), while similar prognostic value was observed. In TNBC, early clearance of ctDNA at 3 weeks was a significant predictor of favorable response to NAC. Compared to patients who were ctDNA-positive after NAC, ctDNA-negative status in both subtypes was associated with improved DRFS even in patients with residual cancer (no pCR or RCB-II/III). These findings could inform on the design of future studies that seek to demonstrate the utility of ctDNA in the curative setting. Predictive and prognostic significance of ctDNA in early breast cancer in the neoadjuvant setting HR+HER2- (n=106) TNBC (n=97) Predictive value for prediction of pCR and RCB Fisher p-value Fisher p-value Early ctDNA clearance (between T0 and T1) and pCR 0.4521 <0.0001 Late ctDNA clearance (between T0 and T2) and pCR 0.8071 0.0004 Early ctDNA clearance (between T0 and T1) and RCB (0-III) 0.1360 <0.0001 Late ctDNA clearance (between T0 and T2) and RCB (0-III) 0.4869 0.0004 Early ctDNA clearance at T1 and pCR rates pCR rate pCR rate ctDNA clearance (ctDNA+ at T0/ctDNA- at T1) 21% 67% Late ctDNA clearance (betweeNo early clearance (ctDNA+ at T0/ctDNA+ at T1) 13% 14% Prognostic value for prediction of DRFS Log rank p-value Log rank p-value ctDNA at T3 and pCR vs no PCR 0.0002 <0.0001 ctDNA at T3 and RCB (0-I vs II-III) 0.0110 <0.0001 Timepoints: T0 - pretreatment; T1 - three weeks after treatment initiation; T2 - at 12 weeks, between paclitaxel-based and anthracycline regimens; T3- after neoadjuvant chemotherapy prior to surgery Citation Format: Mark Jesus Mendoza Magbanua, Lamorna Brown Swigart, Derrick Renner, Svetlana Shchegrova, Gillian L. Hirst, Christina Yau, Denise M. Wolf, Hsin-Ta Wu, Ekaterina Kalashnikova, Amy L. Delson, A. Jo Chien, Debu Tripathy, Smita Asare, Raheleh Salari, Angel Rodriguez, Bernhard Zimmermann, Himanshu Sethi, Alexey Aleshin, Paul Billings, Rita Nanda, Hope S. Rugo, Laura J. Esserman, Minetta C. Liu, Angela DeMichele, Laura van 't Veer. Comparison of the predictive and prognostic significance of circulating tumor DNA in patients with high risk HER2-negative breast cancer receiving neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB111.