Rotavirus RNA chaperone mediates global transcriptome-wide increase in RNA backbone flexibility

Due to genome segmentation, rotaviruses must co-package a set of eleven distinct genomic RNAs. The packaging is mediated by virus-encoded RNA chaperones, such as the rotavirus (RV) NSP2 protein. While the activities of distinct viral RNA chaperones are well studied on synthetic RNA substrates, little is known about their global effect on the entire viral transcriptome. Here we used Selective 2′-hydroxyl Acylation Analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP) to systematically examine the secondary structure of the RV transcriptome composed of eleven distinct transcripts in the absence and presence of increasing concentrations of RV NSP2. Surprisingly, SHAPE-MaP data reveals that despite the well-documented helix-unwinding activity of NSP2 in vitro, its incubation with cognate RV transcripts does not induce a significant change in the SHAPE reactivities. However, a quantitative analysis of the per nucleotide mutation rate measured by mutational profiling, from which SHAPE reactivities are derived, reveals a global five-fold rate increase in the presence of molar excess of NSP2. We demonstrate that the standard normalization procedure used in deriving SHAPE reactivities from mutation rates can mask an important global effect of an RNA chaperone activity. Further analysis of the mutation rate in the context of structural classification reveals a larger effect on stems rather than loop elements. Together, these data provide the first experimentally derived secondary structure model of the RV transcriptome and reveal that NSP2 acts by globally increasing RNA backbone flexibility in a concentration-dependent manner, consistent with its promiscuous RNA-binding nature.

In vivo optical imaging-guided targeted sampling for precise diagnosis and molecular pathology

Conventional tissue sampling can lead to misdiagnoses and repeated biopsies. Additionally, tissue processed for histopathology suffers from poor nucleic acid quality and/or quantity for downstream molecular profiling. Targeted micro-sampling of tissue can ensure accurate diagnosis and molecular profiling in the presence of spatial heterogeneity, especially in tumors, and facilitate acquisition of fresh tissue for molecular analysis. In this study, we explored the feasibility of performing 1–2 mm precision biopsies guided by high-resolution reflectance confocal microscopy (RCM) and optical coherence tomography (OCT), and reflective metallic grids for accurate spatial targeting. Accurate sampling was confirmed with either histopathology or molecular profiling through next generation sequencing (NGS) in 9 skin cancers in 7 patients. Imaging-guided 1–2 mm biopsies enabled spatial targeting for in vivo diagnosis, feature correlation and depth assessment, which were confirmed with histopathology. In vivo 1-mm targeted biopsies achieved adequate quantity and high quality of DNA for next-generation sequencing. Subsequent mutational profiling was confirmed on 1 melanoma in situ and 2 invasive melanomas, using a 505-gene mutational panel called Memorial Sloan Kettering-Integrated mutational profiling of actionable cancer targets (MSK-IMPACT). Differential mutational landscapes, in terms of number and types of mutations, were found between invasive and in situ melanomas in a single patient. Our findings demonstrate feasibility of accurate sampling of regions of interest for downstream histopathological diagnoses and molecular pathology in both in vivo and ex vivo settings with broad diagnostic, therapeutic and research potential in cutaneous diseases accessible by RCM-OCT imaging.

TP53 Mutations Identify High-Risk Peripheral T-Cell Lymphoma Patients Treated with CHOP-Based Chemotherapy

Introduction Mutational profiling in peripheral T-cell lymphoma (PTCL) is increasingly used to aid in diagnosis (Wang. Blood 2015), predicting response (Ghione. Blood Adv 2020), and prognosis (Watatani. Leukemia 2019). However, many analyses lack details of upfront treatment and survival outcomes. The Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) is a custom hybridization capture-based assay encompassing the protein-coding exons of >400 targeted genes (Cheng. J Molec Diag 2015). Using the MSK-IMPACT data generated from a large TCL patient (pt) population (N=396), we sought alterations which may predict resistance to or high rates of relapse after CHOP-based chemotherapy. Methods PTCL pts with MSK-IMPACT were detected in the CBioPortal online platform. We included histologies treated with curative intent CHOP-based induction +/- autologous stem cell transplant (ASCT). This included PTCL-not otherwise specified (PTCL-NOS), angioimmunoblastic T-cell lymphoma (AITL), PTCL with a T-follicular helper phenotype (FH-TCL), ALK+ and ALK- anaplastic large cell lymphoma (ALCL), and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL). Univariate analysis (UVA) for PFS and OS based on the presence of recurring genetic alterations was done using Cox proportional hazard regression analysis. Mutations (mut) assessed included TET2, DNMT3A, RHOA, IDH2, TP53, FAT1, STAT3, STAT5B, JAK1, SETD2, and copy number alterations (CNA) in TP53 and CDKN2A. Comparisons of survival curves were performed by log-rank test. As many pts were sequenced at relapse, to minimize bias, relevant findings were confirmed in the smaller set of pts sequenced at diagnosis and/or before relapse (prospective cohort). Results In total, 131 pts met inclusion criteria and had >1 MSK-IMPACT. One pt with a 49-gene panel was also included (N=132). The prospective cohort had 73 (55%) pts. Histologies were PTCL-NOS (N=36, 27%), AITL (N=62, 47%), FH-TCL (N=9, 7%), ALK-ALCL (N=15, 11%), ALK+ALCL (N=6, 5%), and MEITL (N=4, 3%). Regimens were CHOP + etoposide (N=59, 45%), CHOP (N=40, 30%), brentuximab + CHP (N=15, 11%), other CHOP-based (N=18, 14%). The most frequent mut were TET2 (N=69, 52%), RHOA (N=40, 30%), DNMT3A (N=25, 19%), TP53 (N=21, 16%), and IDH2 (N=15, 11%), and for CNA were losses of TP53 (N=9, 7%) and CDKN2A (N=9, 7%). TET2 mut were most frequent in AITL (N=51, 82%), FH-TCL (N=6, 67%), and PTCL-NOS (N=10, 28%). RHOA mut were found in 2 cases of PTCL-NOS (6%) with the rest in AITL (N=33, 53%) and FH-TCL (N=5, 56%). DNMT3A mut were most frequent in AITL (N=19, 31%) and FH-TCL (N=4, 44%). IDH2 mut were exclusive to AITL (N=14, 23%) and FH-TCL (N=1, 11%). TP53 mut were found in all histologies: ALK-ALCL (N=5, 33%), PTCL-NOS (N=10, 28%), FH-TCL (N=2, 22%), AITL (N=2, 3%), and in one case each of ALK+ALCL (17%) and MEITL (25%). The 24-month PFS was 28% for the entire cohort, and 42% for the prospective cohort. On UVA for genetic alterations, only TP53 mut (P=0.0011) and TP53 deletions (P=0.009) associated with inferior PFS. On MVA, only TP53 mut remained significant (HR 2.0 [95% CI 1.1-3.5] P=0.02). No alteration associated with inferior OS. For the entire cohort, median PFS was 4.5 mos for TP53 mut (N=21) vs. 10.5 mos for TP53 wild-type (WT) (N=111) (log-rank P=0.0008). This was similar in the prospective cohort with a median PFS of 4.1 vs. 19.7 mos (log-rank P=0.02) (Figure 1). Compared to TP53 WT, TP53 mut were more likely to have PTCL-NOS (P=0.03), concurrent deletions of TP53 (P=0.0005), and a higher median number of alterations (P=0.01). There were no differences in age, stage, marrow disease, or IPI/PIT scores between TP53 mut and TP53 WT pts. There was a trend towards fewer CR (P=0.054) in TP53 mut. There were no differences in ITT with ASCT between the groups (P=0.5). This was similar in the prospective cohort (P=0.4). Six total (29%) TP53 mut received ASCT, and PFS was similar to ASCT in TP53 WT (median 18.2 vs. 19.7 mos, P=0.5), but 5/6 (83%) ultimately relapsed. Conclusions TP53 mut correlated with lower rates of CR, higher rates of relapse, and shorter PFS in this dataset of PTCL treated with CHOP-based chemotherapy. OS was not different compared to TP53 WT tumors. The confounding impact of histology and other prognostic factors as well as the lack of uniform prospective mutational profiling in this retrospective series precludes definitive conclusions and requires prospective confirmation. Figure 1 Figure 1. Disclosures Sauter: Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Novartis: Consultancy; Genmab: Consultancy; Precision Biosciences: Consultancy; Kite/Gilead: Consultancy; Celgene: Consultancy, Research Funding; Gamida Cell: Consultancy; GSK: Consultancy; Bristol-Myers Squibb: Research Funding. Khan: Seattle Genetics: Research Funding. Moskowitz: ADC Therapeutics: Research Funding; Beigene: Research Funding; Seattle Genetics: Consultancy, Research Funding; Miragen: Research Funding; Bristol-Myers Squibb: Research Funding; Merck: Consultancy, Research Funding; Janpix Ltd.: Consultancy; Imbrium Therapeutics L.P./Purdue: Consultancy; Takeda: Consultancy; Incyte: Research Funding. Dogan: Seattle Genetics: Consultancy; Roche: Consultancy, Research Funding; Peer View: Honoraria; EUSA Pharma: Consultancy; Takeda: Consultancy, Research Funding; Physicians' Education Resource: Honoraria. Horwitz: ADC Therapeutics: Consultancy, Research Funding; Acrotech Biopharma: Consultancy; Affimed: Research Funding; Aileron: Research Funding; Celgene: Research Funding; C4 Therapeutics: Consultancy; Daiichi Sankyo: Research Funding; Forty Seven, Inc.: Research Funding; Kyowa Hakko Kirin: Consultancy, Research Funding; Janssen: Consultancy; Kura Oncology: Consultancy; Millennium /Takeda: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Trillium Therapeutics: Consultancy, Research Funding; SecuraBio: Consultancy, Research Funding; Myeloid Therapeutics: Consultancy; ONO Pharmaceuticals: Consultancy; Shoreline Biosciences, Inc.: Consultancy; Tubulis: Consultancy; Vividion Therapeutics: Consultancy; Verastem: Research Funding.

Worse outcome and distinct mutational pattern in follicular lymphoma with anti-HBc positivity

Epidemiological studies have demonstrated the association between hepatitis B virus (HBV) infection and B-cell non-Hodgkin lymphomas (NHL), mainly for diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). We studied a cohort of 121 FL patients for HBV infection status, clinical features and gene mutational profile. Anti-HBc was detectable in sixteen patients (13.2%), although all had undetectable HBV DNA. Anti-HBc+ cases presented with older age at diagnosis than anti-HBc- cases (68.1 vs. 57.2 years, P=0.007) and higher β2-microglobulin (56.3% vs. 28.9%, P=0.04). All patients included in the study fulfilled criteria for treatment and received therapy with rituximab or rituximab-containing chemotherapy. There were no episodes of HBV reactivation or HBV-hepatitis during treatment and/or maintenance. Remarkably, anti-HBc+ patients had significantly lower 10-year PFS (12.9% vs 58.3%; P<0.0001) and OS (22.0% vs. 86.2%, P<0.0001), that remained at multivariate analysis. Gene mutational profiling of all cases showed that anti-HBc+ cases had higher incidence of ARID1A mutations and absence of EP300 mutations, two key epigenetic regulators in FL. Overall, our study shows that FL patients with resolved HBV infection have a worse outcome independently of other well-known clinical risk factors and a distinct gene mutational profile.

Assessment of Comprehensive Mutational Profiling in T-lymphoblastic leukemia/lymphoma (T-ALL/LBL): A Single Center Experience

Introduction/Objective T-lymphoblastic leukemia/lymphoma (T-ALL/LBL) is a malignancy arising from immature precursor T cells with T-ALL involving bone marrow/blood and T-LBL occurring in the thymus and nodal/extranodal sites. Studies have now revealed >100 recurrently altered genes that are not necessarily disease initiating but can provide diagnostic, prognostic, and predictive information which can then be utilized in personalized therapy. Methods/Case Report Next-generation sequencing was performed on DNA and/or RNA extracted from blood/marrow aspirates or tissue at an external CLIA-certified, CAP-accredited laboratory. The hematology panel sequenced DNA of 406 genes, introns of 31 gene rearrangements, and RNA of 265 genes. This retrospective single-center study highlights salient findings noted in genomic profiles of 15 T-ALL/LBL cases out of 83 total patients with ALL from 2018-2021. While the majority were B-ALL cases, T-ALL accounted for 18%, and all but 1 case were pediatric patients (ages 9-21 years). Results (if a Case Study enter NA) In our pediatric cohort (14 patients; 9 males, 5 females), as in literature, NOTCH signaling was most frequently involved with NOTCH1 (50%) and FBXW7 (36%) mutations, followed by those in cell cycle process CDKN2A/2B (36%) and PTEN (28%) mutations. Other mutations: PHF6 (21%), BCOR and TAL1 (14%) each. The prognostic effect of mutations: NOTCH1 favorable, FBXW7 no effect but trend toward favorable when FBXW7 co-occurs with NOTCH1 while PTEN is unfavorable (3 patients had relapses). Some unusual or useful findings: a patient diagnosed initially as AML with aberrant CD3 was re-classified as early T-cell precursor ALL, supported by RELN mutation (occurs in 4% ETP-ALL). The adult with NOTCH1 and BCOR mutations in addition to BCR-ABL1 fusion was diagnosed as having T-ALL blasts with CML. We could not study detailed nuances in mutational profiles of T-ALL vs T-LBL with only 1 case of T-LBL showing FBXW7, PTEN, NF1, RB1, BCOR and NRAS mutations (latter is typically noted in pediatric T-LBL cases). Conclusion Clinical molecular testing in our pediatric T-ALL patients revealed gene alterations that provide refinement of diagnosis, prognosis, and risk stratification. It also contributes a useful data set for further analysis and potential use of clinically actionable therapeutic targets in some cases. Longer term follow-up incorporating therapy and outcomes information would be valuable.