A Comparative Analysis of Effect of HIV Infection on Outcomes of Cervical Cancer Treated with Radiotherapy

PURPOSE/OBJECTIVE(S)

There is paucity of data on management of human immunodeficiency virus (HIV) positive cervical cancer and its clinical outcomes in Indian women. The primary objective of this study was to compare disease free survival (DFS) and overall survival (OS) between HIV-positive and HIV-negative patients receiving radiotherapy (RT) for cervical cancer. The secondary endpoints were toxicity and various factors affecting DFS and OS.

MATERIALS/METHODS

Patients diagnosed with cervical cancer on histopathology and treated with RT with or without concomitant chemotherapy (CT) at an institution between 2015 and 2020 were included in this retrospective analysis. On the basis of HIV serology test, 70 patients were included in each arm, Arm A had HIV-negative patients and Arm B had HIV-positive patients. In both the arms, external beam radiotherapy (EBRT) in adjuvant or radical setting was given with a total dose of 46-50 Gy to whole pelvis and iliac nodes; 2 Gy/fraction daily as 5 fractions/week by conventional four-field box technique or conformal 3-dimensional radiotherapy (3DCRT) or Intensity modulated radiotherapy (IMRT). Concurrent cisplatin was administered as weekly 40mg/m2 to patients with ECOG< = 2, creatinine clearance >40mL/min in radical and adjuvant patients as indicated. CD4 counts ≥200 cells/mm3 was a prerequisite for concurrent cisplatin in Arm B. Intracavitary or interstitial brachytherapy was delivered as indicated. Statistical analysis was done using statistical software. Kaplan-Meier method used for all survival analysis. Log rank test was used to calculate statistical significance for various prognostic factors followed by Cox regression test for multivariate analysis.

RESULTS

Median age was 46.5 years (range: 30-76). In Arm A, 62 patients (88.57%) and 5 patients (7.14%) received radical and adjuvant RT. In Arm B 61 patients (87.14%) and 2 patients (2.85%) were given radical and adjuvant RT. 66 patients (94.28%) in Arm A and 52 patients (74.28%) in Arm B received concurrent cisplatin. At a median follow up of 33.8 months (range: 1.2 to 85.4), 2-year DFS was 88.9% for Arm-A and 86.5% for Arm-B (p = 0.134) and 2-year OS was 91.4% and 82.9% for Arm-A and Arm-B (p = 0.001), respectively. Grade III/IV skin toxicity was seen in and 4 patients (5.71%) in Arm A and 12 patients (17.14%) in Arm B (p = 0.34). Grade III/IV gastrointestinal toxicity was seen in 2(2.85%) patients and 4(5.7%) patients in Arm A and Arm B respectively (p = 0.40). 14(20%) patients in Arm A and 27(38.5%) patients in Arm B had Grade III/IV hematologic toxicity (p = 0.016). On multivariate analysis, anemia (Hb≤12 gm/dl) and OTT ≥56 days were associated with unfavorable DFS (p = 0.03 and p = 0.001) and OS (p = 0.04 and p = 0.01) in Arm B.

CONCLUSION

In view of comparable DFS outcomes in both the arms, HIV-positive cervical cancer patients can be managed with the standard treatment protocol as HIV-negative patients. HIV-positive patients are more likely to experience poorer DFS and OS. However, results need to be validated on prospective study.

Correlation of Dose Volume Parameters with Dysphagia and Pharyngeal Constrictor Muscle Thickness in Dysphagia Optimized IMRT

PURPOSE/OBJECTIVE(S)

Reduced radiation dose to the pharyngeal constrictor muscles (PCM) using dysphagia optimized intensity-modulated RT (DO-IMRT) is associated with improved swallowing outcomes in oropharyngeal cancers (OPCs). Purpose was to evaluate the relationship between dose of radiation delivered and acute dysphagia in patients with OPC treated with IMRT, after delineation of PCM.

MATERIALS/METHODS

Twenty-five patients with newly diagnosed OPC who underwent definitive IMRT with concurrent cisplatin were included in the study. PCM mean dose < 50 Gy was used as the dose constraint. Target volume was divided into high, intermediate and low risk areas receiving doses in the range of 60-66 Gy, 54-58 Gy, 51-56 Gy in 30-33 fractions over 6-6.5 weeks, respectively. PCM dose-volume parameters were collected and logistic regression was used to analyze these data relative to percent weight loss during RT and duration of feeding tube use. Thickness of constrictor muscle in pre-treatment and 3 months post-therapy CT scan were assessed. Weekly assessment of dysphagia was based on RTOG toxicity gradings. Aim of the study was to evaluate the correlation between dysphagia grades with dose-volume parameters and PCM thickness.

RESULTS

Median age was 55.0 years (mean 54.3) with 24 males and stage II:III-16:9 patients. Dmean to PCM was 49.86 Gy (range 48.22 -57.63) with median Dmax of 70.24 Gy. For patients with dysphagia (grade ≥1), V50 ranged from 48.2-57.23%, while in those with no dysphagia, it ranged from 47.92-52.18 % (Mean 51.36%). Nine patients needed feeding tube after RT end. Median feeding tube duration was 64 days. The correlation between Dmean ≥ 50 Gy and dysphagia at 1st, 2nd, 3rd and 6th month was found statistically significant (p < 0.01). Table 1 shows the Pearson correlation and P-value of the dosimetric parameters with dysphagia. The correlation of V50 was found statistically significant with grade of dysphagia at 3rd and 6th month post-treatment (p<0.001). The mean thickness range and median thickness of constrictors before and 3 months after treatment were 1.8-3.2 mm, 2.4 mm, and 2.8-6.2 mm,4.1 mm, respectively. The increase in thickness of constrictor muscle correlated significantly (p<0.05) with dysphagia grades and also with V50, V60 and Dmean (p<0.001) but no statistical significance was seen with Dmax (p = 0.232). With a median follow-up of 18 months (range 7-24), 1-year actuarial local control was 92%.

CONCLUSION

DO-IMRT may prove beneficial in the OPC by preventing dysphagia and aspiration post therapy and hence improving the quality of life of patients. Dmean ≥ 50Gy, V50 > 51.4% and V60 > 35.5% are the parameters correlating significantly with dysphagia (p<0.001) and change in mean thickness of PCM (p<0.001).

The effects of the DASH dietary pattern on clinical outcomes and quality of life in adults with uncontrolled asthma: Design and methods of the ALOHA Trial

BACKGROUND

Poor diet quality is an important risk factor for increased asthma prevalence and poor asthma control. To address the question of whether adults with asthma can benefit from following a healthy diet, this trial will test the efficacy and mechanisms of action of a behavioral intervention promoting the Dietary Approaches to Stop Hypertension (DASH) dietary pattern with sodium reduction among patients with uncontrolled asthma.

METHODS

In this 2-arm randomized clinical trial, 320 racially/ethnically and socioeconomically diverse adults with uncontrolled asthma on standard controller therapy will be randomized to either a control or an intervention group and assessed at baseline, 3, 6 and 12 months. Control and intervention participants will receive education on lung health, asthma, and other general health topics; additionally, the intervention group will receive DASH behavioral counseling over 12 months. The primary hypothesis is that the DASH behavioral intervention, compared with the education-only control, will lead to significantly more participants with minimum clinically important improvement (responders) in asthma-specific quality of life at 12 months. Secondary hypotheses will test the intervention effects on other asthma (e.g., asthma control, lung function) and non-asthma outcomes (e.g., quality of life). Additionally, therapeutic (e.g., short chain fatty acids, cytokines) and nutritional biomarkers (e.g., dietary inflammatory index, carotenoids) will be assessed to understand the mechanisms of the intervention effect.

CONCLUSION

This trial can substantially advance asthma care by providing rigorous evidence on the benefits of a behavioral dietary intervention and mechanistic insights into the role of diet quality in asthma.

CLINICALTRIALS

gov #: NCT05251402.

Targeting neddylation sensitizes colorectal cancer to topoisomerase I inhibitors by inactivating the DCAF13-CRL4 ubiquitin ligase complex

Colorectal cancers (CRCs) are prevalent worldwide, yet current treatments remain inadequate. Using chemical genetic screens, we identify that co-inhibition of topoisomerase I (TOP1) and NEDD8 is synergistically cytotoxic in human CRC cells. Combination of the TOP1 inhibitor irinotecan or its bioactive metabolite SN38 with the NEDD8-activating enzyme inhibitor pevonedistat exhibits synergy in CRC patient-derived organoids and xenografts. Mechanistically, we show that pevonedistat blocks the ubiquitin/proteasome-dependent repair of TOP1 DNA-protein crosslinks (TOP1-DPCs) induced by TOP1 inhibitors and that the CUL4-RBX1 complex (CRL4) is a prominent ubiquitin ligase acting on TOP1-DPCs for proteasomal degradation upon auto-NEDD8 modification during replication. We identify DCAF13, a DDB1 and Cullin Associated Factor, as the receptor of TOP1-DPCs for CRL4. Our study not only uncovers a replication-coupled ubiquitin-proteasome pathway for the repair of TOP1-DPCs but also provides molecular and translational rationale for combining TOP1 inhibitors and pevonedistat for CRC and other types of cancers.

Analyzing the impact of close margins and extra-resection margins on failure rates in postoperative oral cavity cancers

BACKGROUND

Postoperative oral cancers with close margins belong to medium- to high-risk category for local failure. During re-surgery for close margins, there is sufficient doubt as to whether the re-excised tissue is from the same region as the close margin. Therefore, we planned a retrospective review of these cases of close margins that were re-excised with extra-resection margins (ERMs).

MATERIAL AND METHODS

Details of 2011 oral cavity patients resected at our hospital were retrieved. Cases with close margins were segregated and the status of ERMs was noted. The postoperative histopathological details, radiotherapy details, and failure patterns in all these cases were documented. The primary objective of the study was to assess the overall survival (OS) and disease-free survival (DFS) in cases with ERMs. The secondary objective was to assess the local and regional control rates and variation with the number and status of close and ERMs. OS, DFS, and local failure rates were defined from the date of registration. Statistical analysis was performed with the SPSS statistical software package. All survival analyses were performed using the Kaplan-Meier method. Log-rank test was used to test the statistical significance. A P-value of 0.05 was considered statistically significant.

RESULTS

Sixty-four cases with a median age of 47 years (range: 29-76) were considered for the final analysis. The median follow-up was 40 months (range: 9.5-56.5). The 2-year OS and DFS rates were 91.5% and 88.5%, respectively. The crude local and regional failure rates were 10.9% and 3.1%, respectively. The 3-year locoregional control rate was 90.2%. The 2-year locoregional control rate for one close margin was significantly better as compared to more than one close margin (P = 0.049). No difference in survival and failure rates was found between the number of ERMs resected (one vs. two) and ≤ vs. > 3 mm close margin status. Two patients developed bone metastases.

CONCLUSION

The survival rates and locoregional control rates did not differ much between the groups that had one or more ERMs. However, the locoregional control rates were better in cases with one close margin as compared to those with more than one close margin. A larger study with longer follow-up is needed to detect statistically significant differences in outcomes and identify the factors that portend poor prognosis in these cases with close margins and ERMs.

Direct Measurement of Resonances in ^{7}Be(α,γ)^{11}C Relevant to νp-Process Nucleosynthesis

We have performed the first direct measurement of two resonances of the ^{7}Be(α,γ)^{11}C reaction with unknown strengths using an intense radioactive ^{7}Be beam and the DRAGON recoil separator. We report on the first measurement of the 1155 and 1110 keV resonance strengths of 1.73±0.25(stat)±0.40(syst)  eV and 125_{-25}^{+27}(stat)±15(syst)  meV, respectively. The present results have reduced the uncertainty in the ^{7}Be(α,γ)^{11}C reaction rate to ∼9.4%-10.7% over T=1.5-3  GK, which is relevant for nucleosynthesis in the neutrino-driven outflows of core-collapse supernovae (νp process). We find no effect of the new, constrained reaction rate on νp-process nucleosynthesis.

Abstract 2949: Enabling single cell analysis of copy number variation in breast cancer

Breast cancer is arguably one of the solid tumors most comprehensively analyzed by massively parallel sequencing. Although the repertoire of clonal somatic genetic alterations in primary and metastatic breast cancers has been characterized, a complete characterization of the subclonal genetic alterations present in these cancers, as well as their clonal composition and clonal dynamics remain to be fully defined. Addressing these knowledge gaps is germane to the successful personalization of treatments for breast cancer patients. Single cell sequencing is uncovering many insights into the clonal evolution and heterogeneity of breast cancers and how this can be leveraged for clinical and therapeutic benefit. Bulk next generation sequencing has primarily focused on mutation profiling; however, there are several lines of evidence to demonstrate the biological and clinical importance of accurately detecting copy number alterations. Previous single cell sequencing studies focusing on copy number alterations were based on whole-genome amplification methods or could not concurrently define the repertoire of somatic mutations and copy number alterations in single cells. Here we report on a novel single cell DNA sequencing approach leveraging the Tapestri device and Insights bioinformatic pipeline to detect both copy number alterations and somatic mutations in individual cells derived from breast cancer specimens. The identification of targeted somatic genetic alterations at single cell resolution provides novel insights about the development, progression and therapeutic resistance of breast cancers, and enables the development of novel diagnostic tools and predictive biomarkers.

Citation Format: Saurabh Parikh, Arnaud Da Cruz Paula, Shirin Issa Bhaloo, Alex Li, Britta Weigelt, Khushali Patel, Ania Wronski, Anup Parikh, Khushali Patel, Jorge Reis-Filho. Enabling single cell analysis of copy number variation in breast cancer [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 2949.

Abstract 6171: A single-cell solution for solid tumors to detect mutations and quantify copy number variations

Cancer is a highly heterogeneous disease characterized by the presence of chromosomal structural copy number variation (CNV) and driver gene mutation events, which appear somatically at the early stages of oncogenesis and can drive tumor progression. Previously, we have developed a high throughput single cell DNA analysis platform that leverages droplet microfluidics and a multiplex-PCR based targeted DNA sequencing approach. It demonstrates high sensitivity detection of SNVs and indels in the same cells and generation of high resolution maps of clonal architecture based on mutational profiling. Here we expand upon the same approach and create an algorithm to accurately quantify CNVs along with genetic mutations from the same single cells. To estimate the CNV the amplicon read counts were corrected for artefacts related to cell to cell variability due sequencing efficiencies along with amplicon to amplicon variability that occur due to amplification efficiency differences. We used a spiked in diploid cell line as a reference to normalize all the cells. The spiked cell line was identified using its mutational profile. We validated the system using cell lines with known CNVs and found that we could at least accurately estimate copy numbers ranging from 0 through 5. Some of the regions were also validated orthogonally using droplet digital PCR. Another set of validation was performed using well characterized cell lines from NIST. We enable multiple visualizations of the copy number estimates in karyotype plots and line plots projected on SNV clones. With improved biochemistry, panel design and novel data analysis algorithms we develop a complete solution to detect amplification or loss of function in oncogenes and tumor suppressors reliably. Integration of CNVs and SNVs facilitates more accurate reconstruction of tumor evolution to better understand cancer progression mechanisms as well for quality control of gene edited cells, to further advance cancer research and therapy.

Citation Format: Saurabh Parikh, Khushali Patel, Alex Li, Anup Parikh. A single-cell solution for solid tumors to detect mutations and quantify copy number variations [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 6171.

190 Patient-derived tumor organoids reveal mechanisms of immune evasion which can guide decisions in adoptive cell therapy for common epithelial cancers

Background

Adoptive cellular transfer (ACT) of autologous tumor-infiltrating lymphocytes (TIL) is capable of inducing durable clinical responses in patients with advanced solid malignancies,1 however response rates are low. Limitations in personalized cancer modeling have been obstacles to understanding tumor-specific mechanisms of immune evasion. Patient-derived tumor organoids (PDTO) can be efficiently grown from common solid tumors and show genetic fidelity to whole exomic sequencing (WES) of the source tumor. We investigated their use in evaluating patient-specific immune responses in vitro and selecting T-cells for adoptive cellular immunotherapy.

Methods

PDTO were established from metastatic deposits from patients with colorectal, breast, and pancreatic cancers and with their tumors of origin, were subjected to WES and RNAseq. They were then included in immunologic recognition assays with autologous TIL and cloned T-cell receptors (TCR) against shared mutations. TIL neoantigen reactivity was defined by screening against mutations using minigenes or synthetic peptides expressed by autologous antigen presenting cells.

Results

PDTO were successfully grown from 18/22 tumors from 15 patients. These cultures demonstrated a high degree of genetic fidelity to their parental tumors with near-complete retention of clonally expressed mutations. Organoid lines from 11 of these patients were utilized in recognition screening with autologous TIL or PBL transduced with relevant TCRs. TIL recognized 5/7 organoids tested, and this allowed the isolation and cloning of many of the TCRs responsible. Nineteen available TCRs predicted to be reactive with patient-specific neoantigens were also tested against relevant organoids, and only nine were found to be reactive. In most instances where such TCRs could not recognize organoid, tumor-specific defects in neoantigen processing or presentation or HLA-LOH events were either functionally or genetically identified.

Conclusions

To improve response rates to neoantigen-directed adoptive T-cell therapy, a better understanding of tumor immune evasion mechanisms is needed. The inability to grow autologous tumor lines from common epithelial cancers has been a major obstacle. We demonstrate that PDTO can be efficiently established and are genetically representative of their parental tumors. Importantly, these organoids can reveal defects in neoantigen processing or surface presentation as well as HLA loss-of-heterozygosity that would preclude immune recognition. PDTO may be a valuable tool for screening for tumor reactivity and selecting T-cells and TCRs for clinical use.

Trial Registration

The study protocol was registered under https://clinicaltrials.gov under NCT00068003.

Reference

Zacharakis N, Chinnasamy H, Black M, et al. Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer. Nat Med. 2018;24:724–730.

Ethics Approval

All samples were derived from study participants who granted written, informed consent to be enrolled on a clinical protocol approved by the Institutional Review Board at the NCI (Bethesda, MD).

mRNA vaccine-induced neoantigen-specific T cell immunity in patients with gastrointestinal cancer

BACKGROUNDTherapeutic vaccinations against cancer have mainly targeted differentiation antigens, cancer-testis antigens, and overexpressed antigens and have thus far resulted in little clinical benefit. Studies conducted by multiple groups have demonstrated that T cells recognizing neoantigens are present in most cancers and offer a specific and highly immunogenic target for personalized vaccination.METHODSWe recently developed a process using tumor-infiltrating lymphocytes to identify the specific immunogenic mutations expressed in patients' tumors. Here, validated, defined neoantigens, predicted neoepitopes, and mutations of driver genes were concatenated into a single mRNA construct to vaccinate patients with metastatic gastrointestinal cancer.RESULTSThe vaccine was safe and elicited mutation-specific T cell responses against predicted neoepitopes not detected before vaccination. Furthermore, we were able to isolate and verify T cell receptors targeting KRASG12D mutation. We observed no objective clinical responses in the 4 patients treated in this trial.CONCLUSIONThis vaccine was safe, and potential future combination of such vaccines with checkpoint inhibitors or adoptive T cell therapy should be evaluated for possible clinical benefit in patients with common epithelial cancers.TRIAL REGISTRATIONPhase I/II protocol (NCT03480152) was approved by the IRB committee of the NIH and the FDA.FUNDINGCenter for Clinical Research, NCI, NIH.

Abstract 861: Improvements in variant calling sensitivity and specificity in single-cell DNA sequencing using deep learning

Background: It is now possible to interrogate thousands of cells in a single experiment for studying genetic variability with the advancements in single-cell sequencing technologies. Single-cell DNA platforms like Tapestri is still susceptible to errors from polymerase incorporations, structure induced template switching, PCR mediated recombination in Tapestri workflow or DNA-damage. Errors from sequencing could propagate from cluster amplification, cycle sequencing or image analysis. All together these errors can be divided into substitutions, insertions and deletion errors and can range from 0.5% to 2% depending on the sequencer. This makes rare variant and minimal residual disease detection challenging. To address these challenges, we developed deep learning models for correcting the errors, reduce false-positive rates and predict true variants.

Method: First we build a consensus sequence from several reads to predict the correct sequence. The initial layers learn the motifs and local sequence contexts in classifying the patterns. The output of this network is a probability distribution over possible bases and the prediction is the base with highest probability. The bases in the reads are subsequently corrected to the predicted base from the first step model. After error correcting the reads, we used the variants called by Genome Analysis Toolkit to feed into a multi-class classifier network. Our features consists of percent of cells mutated, and the different genotype features including depth, AF and quality of each variant in these cells. The truth labels are generated using tapestri instrument from multiple experiments with known bulk truth. We trained the network on over 200k cells from 13 samples and tested on a larger set of samples. Class imbalance was handled using upsampling the truth data. Our training samples include diverse samples from cell mixtures at various dilution uptill 0.1% and clinical samples processed through tapestri instrument and sequenced on a diverse set of sequencers including miseq and novaseq.

Conclusion: To validate this method, we used two different targeted panels on a Latin square model system with known truth mutations. With our 2-step workflow using error correction and variant prediction model, we significantly improved our median PPV 2-3 fold at 0.5% LOD while maintaining the sensitivity. We are further optimizing the model by adding more training samples and feature optimization.

Citation Format: Manimozhi Manivannan, Sombeet Sahu, Kim Dong, Shu Wang, Saurabh Gulati, Saurabh Parikh, Nigel Beard, Anup Parikh. Improvements in variant calling sensitivity and specificity in single-cell DNA sequencing using deep learning [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 861.

Abstract 865: Using machine learning to detect heterogeneity in single cell multi-omics datasets

Background: While scRNA-seq helps in obtaining high-resolution views of single-cell heterogeneity through characterization of the functional state of cells, our understanding of the cellular properties and population architectures of heterogeneous tissues will be greatly advanced by the multi-omics investigation of single cells. Recently, several computational methods have been developed to integrate data from multiple different single cell experiments measuring individual analytes. But unambiguous inference that a cellular phenotype is caused by a genotype can only be achieved by their measurement from the same single cell. To address this gap, we have developed the Tapestri multi-omics workflow to analyze the RNA and DNA information from the same cell.

Methods: After pre-processing of the reads, cell calling is done by identifying the good barcodes using both DNA and RNA reads. DNA reads are processed to identify genetic variants in each cell. The variant cell matrix is then filtered for data completeness to ensure only high-quality data is used in downstream processing. Ploidy is estimated using by normalizing DNA reads, genetic variants and ploidy information together is used to identify subclones. The RNA reads are log normalized and scaled within each cell. Next we set the mean expression of each transcript to 0 and scale the variance to 1. This avoids downstream analysis being skewed by high expressors. We then trained a random forest classifier to identify significantly differentially expressed transcripts across subclones which were identified using genetic variants and ploidy information.

Results: Using the top differentially expressed transcripts we performed dimensionality reduction followed by clustering of cell types. The resulting visualization showed how well the genotypic and transcriptomic datasets integrated with one another. We tested this method on a model system with Raji and KG1 cell lines titrated at 50:50 ratio and were clearly able to associate the transcriptional variation with the genotypic variation of the 2 different cell lines. The method was also validated on a PBMC sample to ensure robustness of methods. We were able to identify the different cell types present the sample and were able to overlay that information with genetic variants to identify sub-clones in the identified cell types.

Citation Format: Saurabh Gulati, Shu Wang, Saurabh Parikh, Ben Liu, Kaustubh Gokhale, Manimozhi Manivannan, Sombeet Sahu, Dong Kim, Anup Parikh. Using machine learning to detect heterogeneity in single cell multi-omics datasets [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 865.

scOrange-a tool for hands-on training of concepts from single-cell data analytics

Motivation

Single-cell RNA sequencing allows us to simultaneously profile the transcriptomes of thousands of cells and to indulge in exploring cell diversity, development and discovery of new molecular mechanisms. Analysis of scRNA data involves a combination of non-trivial steps from statistics, data visualization, bioinformatics and machine learning. Training molecular biologists in single-cell data analysis and empowering them to review and analyze their data can be challenging, both because of the complexity of the methods and the steep learning curve.

Results

We propose a workshop-style training in single-cell data analytics that relies on an explorative data analysis toolbox and a hands-on teaching style. The training relies on scOrange, a newly developed extension of a data mining framework that features workflow design through visual programming and interactive visualizations. Workshops with scOrange can proceed much faster than similar training methods that rely on computer programming and analysis through scripting in R or Python, allowing the trainer to cover more ground in the same time-frame. We here review the design principles of the scOrange toolbox that support such workshops and propose a syllabus for the course. We also provide examples of data analysis workflows that instructors can use during the training.

Availability and implementation

scOrange is an open-source software. The software, documentation and an emerging set of educational videos are available at http://singlecell.biolab.si.

Predictors and Barriers to Condom Use in the African Cohort Study

Consistent condom use is an inexpensive and efficacious HIV prevention strategy. Understanding factors associated with condom use and barriers to use can inform strategies to increase condom uptake. The ongoing African Cohort Study prospectively enrolls adults at 12 clinical sites in Uganda, Kenya, Tanzania, and Nigeria. At enrollment, participants are asked about condom use at last sex with a regular partner. Robust Poisson regression models were used to evaluate predictors of self-reported condom use. Participants who reported not using condoms were asked to provide reasons. From January 2013 to September 2019, 2482 participants reported having at least one regular sexual partner in the preceding 6 months. Of those, 1577 (63.5%) reported using a condom at last sex. Condom use was more common among older participants, males, HIV-infected participants, and those with an HIV-infected partner. Married participants, those with a partner of unknown HIV status, and those reporting alcohol use were less likely to report condom use at last sex. Condom use at last sex also varied significantly by clinical site. Partner disapproval or refusal to use a condom was a consistent driver of disparities in condom use among participants who were HIV infected, female, and aged 18-24 years. Effective HIV prevention programs should integrate condom education with the tools necessary to negotiate condom use with regular partners.

Zileuton use and phenotypic features in asthma

Zileuton, a 5-lipoxygenase (5LPO) inhibitor exerts a broad influence in the arachidonic acid (AA) pathway by blocking upstream molecules that otherwise would lead to production of an array of inflammatory leukotrienes (LT) A4-E4. Hence, it has the potential to be a drug suitable to treat complicated asthmatics. Studies have shown modest response rates for zileuton in asthmatics.

OBJECTIVE

We sought to study our hypothesis that response to zileuton varies across specific asthmatic phenotypes.

METHODS

We retrospectively analyzed data from 129 patients with asthma that were prescribed zileuton at the University of Pittsburgh's Comprehensive Lung Clinic. A total of 75 patients from the above population had requisite lung function data and zileuton usage that would help assess a drug response effect. A zileuton responder was defined as having at least or greater than 5% annualized increase in post-bronchodilator FEV1% from baseline. Using a multivariate logistic regression analysis, we determined the association between responder status and the underlying phenotypic characteristics.

RESULTS

Using generalized estimating equations (GEE) analysis of 331 individual lung function test data-points as well as logistic regression analysis for predictors of 5% or more annualized increase in FEV1%, 21 of 75 patients (28%) met criteria for having a differential response to zileuton. Severe asthma was associated less often with responder status (OR 0.12; p 0.004). Obesity was less often associated with responder status, however did not reach significance (OR 0.46; p 0.15).

CONCLUSION

In this retrospective study, zileuton response varies across asthmatics, with poorer response rates being associated with those with severe asthma and possibly obesity. Although prescription trends for zileuton may predominate amongst severe asthmatics, this tendency does not seem to mirror the actual likelihood to respond. As against the trivial role for zileuton per current GINA algorithms, our study brings forward a notion that zileuton may well be considered along with LTRAs (like montelukast) for non-severe asthma.

Abstract 2725: The single-cell atlas of driver mutations in acute myeloid leukemia

Assessment of intratumor genetic heterogeneity by next-generation sequencing (NGS) is confounded by tumor purity and zygosity of mutations. Furthermore, bulk NGS cannot visualize the cell-level co-occurrence or exclusivity among multiple mutations, causing the inaccurate inference of subclonal architecture. Here, we performed single cell DNA sequencing (scDNA seq) in 82 bone marrow samples from 70 patients with acute myeloid leukemia (AML) using a novel microfluidics-based platform covering 40 amplicons in 19 AML genes (Tapestri, Mission Bio). All samples were concurrently sequenced by the bulk NGS using 295 gene exome capture sequencing. Selected cases were also analyzed by SNP array (Illuminia Omni 2.5 array) to obtain allele-specific copy number data. In total, 319,406 cells (median 3,755 cells/sample) were genotyped with median allele drop-out rate of 8.7% (population frequency inferred from commonly heterozygous SNP loci). Each amplicon was covered at a median 24x/cell. The scDNA seq detected 230 of 238 (97%) bulk NGS-confirmed mutations. RUNX1 mutations were frequently detected as homozygous mutations and concurrent SNP array analysis detected copy number neutral loss-of-heterozygosity of RUNX1 in these cases. Additionally, in cases with homozygous FLT3-ITD mutations, SNP array detected allele-specific copy number gain of mutant loci, which likely resulted in homozygous calls. scDNA seq data unambiguously resolved the single-cell level co-occurrence of driver mutations in AML such as DNMT3A/FLT3-ITD/NPM1, SRSF2/IDH2, and ASXL1/RUNX1, confirming the cooperative function of these driver mutations. On the other hand, the data also revealed mutually exclusive relationships at cellular level between IDH1/IDH2, FLT3-ITD/TKD, NRAS/KRAS, NRAS/PTPN11, and SRSF2/EZH2 mutations, which supports the functional redundancy of these genes in leukemogenesis. Inference of phylogenetic trees using SCITE algorithm (Jahn et al. Genome Biology 2016) uncovered distinct patterns of clonal evolution in AML. The majority of the analyzed cases had a linear evolution pattern where the founder mutations linearly acquired sub-clonal mutations in a step-wise manner. We also detected convergent evolution in some cases where functionally similar driver mutations were acquired in parallel. DNMT3A, IDH1, IDH2 and U2AF1 mutations were frequently detected as trunk mutations, whereas FLT3, NRAS, and NPM1 mutations were usually detected as branch mutations. Analysis of longitudinal samples from 11 patients revealed the remodeling of clonal architecture at relapse. Patients who had 2 or more major subclones at baseline had significantly worse overall survival than those with one subclone (2-year OS 13 vs. 70 months, p = 0.0493). For the first time our data provides a comprehensive landscape of driver mutations and detailed clonal evolution history in AML at the single-cell level using high-throughput scDNA seq genotype information.

Citation Format: Kiyomi Morita, Feng Wang, Katharina Jahn, Yuanqing Yan, Robert Durruthy-Durruthy, Anup Parikh, Jairo Matthews, Latasha Little, Curtis Gumbs, Jianhua Zhang, Xingzhi Song, Erika Thompson, Keyur Patel, Carlos Bueso-Ramos, Courtney DiNardo, Farhad Ravandi, Elias Jabbour, Michael Andreeff, Jorge Cortes, Marina Konopleva, Guillermo Garcia-Manero, Hagop Kantarjian, Dennis J. Eastburn, P Andrew Futreal, Niko Beerenwinkel, Koichi Takahashi. The single-cell atlas of driver mutations in acute myeloid leukemia [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 2725.

Abstract 1663: Analytical methods to identify tumor heterogeneity and rare subclones in single cell DNA sequencing data from targeted panels

Current bulk sequencing paradigms are inadequate to characterize complicated biological systems where somatic variation is buried in the landscape of populations. Single-cell DNA sequencing can simultaneously identify zygosity, rare alleles and determine whether mutations co-occur within the same cell. While high-throughput single-cell DNA analysis has been a recent innovation, it is essential to develop new capabilities for assessing genetic variation present in rare cells and to better understand the role that these cells play in the evolution of tumor progression. To address these challenges and enable the characterization of genetic diversity in cancer cell populations, we developed analytical methods to identify mutation signatures which define subclones present in a tumor population. Here we present a workflow for subclone identification using data generated on the Tapestri single-cell DNA platform. The analytical pipeline steps include obtaining raw reads from the sequencer, removing adapters, aligning and mapping the reads, calling individual cells, error correction of reads assigned to cells and identifying genetic variants within each cell. After filtering for high quality variants, we then filter for data completeness to ensure high quality data is used in downstream processing. The variant-cell matrix is then subjected to clustering to identify subclones. Top variants that define the signature of each subclone are also identified. To validate our methodology, we used data from two different targeted panels on different model systems with known truth mutations. Our pipeline shows the distinct clusters correlating with titration and cell line ratios. Cluster associated signature mutations were also identified. The pipeline can be used for multi sample analysis with time-series data from diagnosis to relapse or from primary site to metastasis to understand clonal diversity. These data demonstrate the utility of the Tapestri platform, the analytical pipeline, and associated data visualization capability. Our approach addresses key issues of identifying rare subpopulations of cells down to 0.1%, and transforms the ability to accurately characterize clonal heterogeneity in tumor samples. This high throughput method advances research efforts to improve patient stratification and therapy selection for various cancer indications.

Citation Format: Manimozhi Manivannan, Sombeet Sahu, Shu Wang, Dong Kim, Niranjan Vissa, Jordan Wilheim, Adam Sciambi, Nianzhen Li, Robert Durruthy-Durruthy, Anup Parikh, Keith Jones. Analytical methods to identify tumor heterogeneity and rare subclones in single cell DNA sequencing data from targeted panels [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 1663.

Nonrestorative Treatments for Caries: Systematic Review and Network Meta-analysis

The goal of nonrestorative or non- and microinvasive caries treatment (fluoride- and nonfluoride-based interventions) is to manage the caries disease process at a lesion level and minimize the loss of sound tooth structure. The purpose of this systematic review and network meta-analysis was to summarize the available evidence on nonrestorative treatments for the outcomes of 1) arrest or reversal of noncavitated and cavitated carious lesions on primary and permanent teeth and 2) adverse events. We included parallel and split-mouth randomized controlled trials where patients were followed for any length of time. Studies were identified with MEDLINE and Embase via Ovid, Cochrane CENTRAL, and Cochrane Database of Systematic Reviews. Pairs of reviewers independently conducted the selection of studies, data extraction, risk-of-bias assessments, and assessment of the certainty in the evidence with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Data were synthesized with a random effects model and a frequentist approach. Forty-four trials (48 reports) were eligible, which included 7,378 participants and assessed the effect of 22 interventions in arresting or reversing noncavitated or cavitated carious lesions. Four network meta-analyses suggested that sealants + 5% sodium fluoride (NaF) varnish, resin infiltration + 5% NaF varnish, and 5,000-ppm F (1.1% NaF) toothpaste or gel were the most effective for arresting or reversing noncavitated occlusal, approximal, and noncavitated and cavitated root carious lesions on primary and/or permanent teeth, respectively (low- to moderate-certainty evidence). Study-level data indicated that 5% NaF varnish was the most effective for arresting or reversing noncavitated facial/lingual carious lesions (low certainty) and that 38% silver diamine fluoride solution applied biannually was the most effective for arresting advanced cavitated carious lesions on any coronal surface (moderate to high certainty). Preventing the onset of caries is the ultimate goal of a caries management plan. However, if the disease is present, there is a variety of effective interventions to treat carious lesions nonrestoratively.