Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenges were overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE 2, powered by multistep parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE 2 speeds up 50 times more than MuSE 1 and eight to 80 times more than other popular callers. Our benchmark study suggests combining MuSE 2 and the recently accelerated Strelka2 achieves high efficiency and accuracy in analyzing large cancer genomic data sets.

Emergence of Long-Range Angular Correlations in Low-Multiplicity Proton-Proton Collisions

This Letter presents the measurement of near-side associated per-trigger yields, denoted ridge yields, from the analysis of angular correlations of charged hadrons in proton-proton collisions at sqrt[s]=13  TeV. Long-range ridge yields are extracted for pairs of charged particles with a pseudorapidity difference of 1.4<|Δη|<1.8 and a transverse momentum of 1 Collapse

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First Measurement of the |t| Dependence of Incoherent J/ψ Photonuclear Production

The first measurement of the cross section for incoherent photonuclear production of J/ψ vector mesons as a function of the Mandelstam |t| variable is presented. The measurement was carried out with the ALICE detector at midrapidity, |y|<0.8, using ultraperipheral collisions of Pb nuclei at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. This rapidity interval corresponds to a Bjorken-x range (0.3-1.4)×10^{-3}. Cross sections are given in five |t| intervals in the range 0.04<|t|<1  GeV^{2} and compared to the predictions by different models. Models that ignore quantum fluctuations of the gluon density in the colliding hadron predict a |t| dependence of the cross section much steeper than in data. The inclusion of such fluctuations in the same models provides a better description of the data.

DeMixSC: a deconvolution framework that uses single-cell sequencing plus a small benchmark dataset for improved analysis of cell-type ratios in complex tissue samples

Bulk deconvolution with single-cell/nucleus RNA-seq data is critical for understanding heterogeneity in complex biological samples, yet the technological discrepancy across sequencing platforms limits deconvolution accuracy. To address this, we introduce an experimental design to match inter-platform biological signals, hence revealing the technological discrepancy, and then develop a deconvolution framework called DeMixSC using the better-matched, i.e., benchmark, data. Built upon a novel weighted nonnegative least-squares framework, DeMixSC identifies and adjusts genes with high technological discrepancy and aligns the benchmark data with large patient cohorts of matched-tissue-type for large-scale deconvolution. Our results using a benchmark dataset of healthy retinas suggest much-improved deconvolution accuracy. Further analysis of a cohort of 453 patients with age-related macular degeneration supports the broad applicability of DeMixSC. Our findings reveal the impact of technological discrepancy on deconvolution performance and underscore the importance of a well-matched dataset to resolve this challenge. The developed DeMixSC framework is generally applicable for deconvolving large cohorts of disease tissues, and potentially cancer.

Concurrent Chemoradiotherapy plus Programmed Death-1 (PD-1) Blockade for Locally Advanced Cervical Cancer: Preliminary Results of a Single-Arm, Open-Label, Phase II Trial

PURPOSE/OBJECTIVE(S)

This study aims to assess the anti-tumor activity and safety of concurrent chemoradiotherapy plus PD-1 blockade in patients with locally advanced cervical cancer.

MATERIALS/METHODS

This is a single-arm, open-label, prospective phase II study. The key inclusion criteria were treatment-naive patients aged 18-75 years with stage II A2-IVA (FIGO 2018) locally advanced cervical cancer. All patients were treated with concurrent chemoradiotherapy including 2 cycle cisplatin (75mg/m2, for three days, every 3 weeks[Q3W]), nedaplatin or carboplatin can be selected for patients who can't tolerate cisplatin. After CCRT, patients achieving complete response (CR), partial responses(PR), stable disease(SD) received adjuvant chemotherapy (docetaxel 75 mg/m2 day 1+ cisplatin DDP 25 mg/m2 day 1-3, Q3W) for 2 cycle. PD-1 blockade Sintilimab and Tislelizumab was administered intravenously at 200 mg every 3 weeks up to 1 year or until disease progression, unacceptable toxicity, or withdrawal of consent. The primary endpoint was objective response rate (ORR) assessed by investigators per Response Evaluation Criteria In Solid Tumours (RECIST) version 1.1. Secondary endpoints were the 12, 24-month overall survival (OS) rates, the 12, 24-month disease free survival (DFS) rates and safety.

RESULTS

From February 2020 to June 2022, a total of 15 patients was enrolled. Median age was 57 years (range, 36-74 years). Stage IIA1 was documented in 2 patients, stage IIA2 in two patients, stage IIIA in one patient, stage IIIC1 in eight patients, and stage IVA in two patients. And 66.7% (10/15) of patients had Metastatic lymph node. Four patients received adjuvant chemotherapy. The ORR was 100%, with 4 patients achieving CR and 11 PR. The 12 and 24-month OS rates are 93.3% and 84%, the 12 and 24-month DFS rates are 86% and 75.4%, respectively. Treatment-related adverse events (TRAEs) occurred in 86.7% (13/15) of patients. Grade 3 TRAEs are leukocyte (n = 1), thrombocytopenia (n = 1), hepatitis (n = 1), skin reaction (n = 1). No treatment-related deaths occurred. And IFN-γ was significantly elevated after radiotherapy (p = 0.0073).

CONCLUSION

Concurrent chemoradiotherapy plus PD-1 blockade showed promising antitumor activity and manageable toxicities in patients with locally advanced cervical cancer. Long-term outcomes are still pending to further evaluate their therapeutic effects. (ChiCTR2000032856).

A Bidirectional Mendelian Randomization Analysis of Circulating Inflammatory Cytokines with Colon and Rectum Cancers

PURPOSE/OBJECTIVE(S)

Chronic inflammation has been proposed to be associated with tumor development and progression. Dynamic changes in serum cytokines induced by feedback mechanisms from tumors make differentiation of cause and effect difficult.

MATERIALS/METHODS

In this study, a bidirectional summary-level Mendelian randomization (MR) analysis was performed to elucidate the causal correlation between inflammatory regulators with colon (CC) and rectum (RC) carcinomas. Summary-level data on inflammation-related genetic variations were extracted from a genome-wide association meta-analysis. Corresponding data for CC and RC were obtained from the FinnGen (CC: 1396 cases vs. 174,006 controls; RC: 1,078 cases vs. 174,006 controls) and UK Biobank (CC: 2,226 cases vs. 358,968 controls; RC: 1,170 cases vs. 360,024 controls) consortiums. Inverse-variance weighted MR was used as the primary method, and sensitivity analysis was performed to assess the MR assumptions.

RESULTS

After P value correction and meta-analysis, there was evidence of direct associations between macrophage migration inhibitory factor (MIF) and CC (95% confidence interval (CI):1.001-1.003; P = 8.77×10-4) and inverse correlations between Interleukin-17 (IL-17) and RC (95% CI: 0.997-0.999; P = 1.15×10-3). Conversely, interleukin-1 receptor antagonist (IL1ra) was downregulated in patients at a higher risk of RC (P = 0.006), and no reliable results revealed a causal association between other cytokines and CC and RC.

CONCLUSION

Thus, this MR study suggests that downregulated serum MIF and elevated serum IL-17 concentrations may reduce the risk of CC and RC, respectively. Therefore, MIF and IL-17 may serve as potential therapeutic targets, and further exploration of their underlying mechanisms is warranted.

Prognostic Value of Naples Prognostic Score on Survival in Unresectable Small Cell Lung Cancer Patients Undergoing Chemoradiotherapy

PURPOSE/OBJECTIVE(S)

Chemoradiotherapy is a major modality for treatment of small cell lung cancer (SCLC). Naples prognosis score (NPS) is a novel prognostic biomarker-based immune and nutritional status and that can be used to evaluate prognosis. Our study aimed to investigate the prognostic role of NPS in unresectable SCLC patients.

MATERIALS/METHODS

Patients treated with chemoradiotherapy were retrospectively analyzed between June 2012 and August 2017. We divided patients into three groups depending on the NPS: group 0, n = 31; group 1, n = 100; and group 2, n = 48, and associations between clinical characteristics and NPS group were analyzed. Spearman correlation analyses were used to estimate the correlations among NPS parameters. The univariable and multivariable Cox analyses were used to evaluate the prognostic value of clinicopathological characteristics and laboratory indicators for overall survival (OS) and progression-free survival (PFS).

RESULTS

Data from 179 patients were analyzed. Treatment modality (P < 0.001) and serum CEA (P = 0.03) were significantly different among the NPS groups. The age, sex, smoking status, KPS, Karnofsky performance score (KPS), disease extent, and number of metastatic sites were not correlated with NPS (all P > 0.05). Spearman correlation analyses showed that neutrophil-to-lymphocyte ratio (NLR) had a significant correlation with lymphocyte-to-monocyte ratio (LMR) (r = -0.495, P < 0.001). KPS, disease extent, prophylactic cranial irradiation, treatment response and NPS Group were associated with OS. In addition, KPS, disease extent, prophylactic cranial irradiation, treatment response and NPS Group were associated with PFS. Multivariate analysis results showed that NPS was identified as an independent prognostic factor for OS (Group 1: hazard ratio [HR] = 2.704, 95% confidence interval [CI] = 1.403-5.210; P = 0.003; Group 2: HR = 5.154, 95% CI = 2.614-10.166; P < 0.001) and PFS (Group 1: HR = 2.018, 95% CI = 1.014-4.014; P = 0.045; Group 2: HR = 3.339, 95% CI = 1.650-6.756; P = 0.001).

CONCLUSION

NPS is related to clinical outcomes in patients with unresectable SCLC. NPS as an innovative scoring system, can improves prediction of survival in unresectable SCLC patients.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenge was overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE2.0, powered by multi-step parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE2.0 speeds up 50 times than MuSE1.0 and 8-80 times than other popular callers. Our benchmark study suggests combining MuSE2.0 and the recently expedited Strelka2 can achieve high efficiency and accuracy in analyzing large cancer genomic datasets.

Abstract 4273: Integration with benchmark data of paired bulk and single-cell RNA sequencing data substantially improves the accuracy of bulk tissue deconvolution

The accuracy of current deconvolution methods largely relies on the quality of cell-type expression references. However, single-cell (sc) and single-nuclei (sn) RNA-seq data used for building the reference are usually generated from independent studies that are distinct from the bulk RNA-seq data to be deconvolved. This study design inherently introduces technical confounding factors as unwanted variations, which is not fully addressed by current methods. To evaluate the impact of this variation on deconvolution accuracy, we generated a benchmark dataset where bulk and snRNA-seq profiling were performed from the same aliquot of single-nuclei that were extracted from 24 healthy retina samples. All donor eye samples were collected within six hours post-mortem and were absent of any disease. This study design guarantees the matched sequencing data to present the same cell-type compositions, so that cross-platform technical artifacts become the remaining confounding factor. We used the benchmark dataset to evaluate the performance of seven current deconvolution methods and found they performed much worse in matched real-bulk data than in matched pseudo-bulks that were summations of the single-cell data. This finding suggests that none of these methods have fully addressed the major technical artifacts between bulk and single-cell sequencing platforms. We therefore propose DeMix.SC, a new deconvolution framework that optimizes deconvolution parameters using a small set of matched bulk and sc/snRNA-seq data from the same tissue type. DeMix.SC includes two major steps. First, we measure the technical variations across genes and across platforms using the benchmark data. Second, we introduce a new weight function for each gene that produces a ranking order that accounts for both the platform-specific technical variations and cell-type specific expressions at gene level. Using the benchmark data for retina, we applied DeMix.SC to previously published human retinal RNA-seq data from 523 individuals with different stages of age-related macular degeneration (AMD). We observed that DeMix.SC can accurately capture the cell-type composition shifts in the AMD retina. DeMix.SC revealed a significant drop of rod cells as well as increased astrocytes, bipolar cells, and Müller cells in the AMD retina compared to the non-AMD group. The proportion changes of the later three minor cell types were not identified by other methods, while DeMix.SC could reveal such tendency. In summary, DeMix.SC integrates benchmark data to improve the deconvolution accuracy in retina samples. Our method is generic and can be applied to other disease conditions, such as deciphering the cell-type heterogeneity in cancer. We expect DeMix.SC will help revolutionize the downstream cell-type specific analysis of bulk RNA-seq data and identify cellular targets of human diseases.

Citation Format: Shuai Guo, Xuesen Cheng, Andrew Koval, Shuangxi Ji, Qingnan Liang, Yumei Li, Leah A. Owen, Ivana K. Kim, John Weinstein, Scott Kopetz, John Paul Shen, Margaret M. DeAngelis, Rui Chen, Wenyi Wang. Integration with benchmark data of paired bulk and single-cell RNA sequencing data substantially improves the accuracy of bulk tissue deconvolution. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4273.

Abstract 4272: Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model

Subpopulations of tumor cells characterized by mutation profiles may confer differential fitness and consequently influence the prognosis of cancers. Understanding subclonal architecture has the potential to provide biological insight in tumor evolution and advance cancer precision treatment. Recent subclonal reconstruction methods require heavy computational resources, prior knowledge of the number of subclones, and extensive postprocessing. These drawbacks can be addressed by using a regularized likelihood modeling approach, which is novel to the field. Therefore, we propose a model-based method, Clonal structure identification through pair-wise Penalization, or CliP, to address these drawbacks. To evaluate the performance of CliP against other methods, we generated a benchmark dataset of 4,050 simulated samples with varied tumor purity, read depth, copy number alteration rate, and true numbers of clusters. Our results suggest that CliP outperforms popular methods such as PhyloWGS in accuracy and shows similar robustness in most scenarios. We further compared CliP performance against 10 other subclonal reconstruction methods to the consensus subclonal reconstruction results on whole-genome sequencing (WGS) data from the Pan-Cancer Analysis of Whole Genomes (PCAWG, n = 1,993). Our result shows that of all 11 methods, CliP achieves the highest correlation with the consensus calls. In terms of speed, CliP can finish running a sample with 5,000 SNVs within one minute, which is ~1,000 times faster than MCMC-based algorithms. Next, we profiled the subclonal structures of 7,711 patient samples with well-annotated clinical outcomes from The Cancer Genome Atlas (TCGA) across 32 cancer types applying CliP to the whole-exome sequencing (WES) data. This is the largest and most complete pan-cancer characterization of intratumor heterogeneity (ITH) through the lens of subclonal reconstruction. We further used CliP outputs to address a commonly asked question on which sequencing platform to use for cancer evolution studies: the cost-effect WES data at higher read depth versus the more comprehensive WGS data at lower read depth. There were a total of 588 tumor samples from 21 cancer types, for which both PCAWG and TCGA have profiled using the WGS and WES platform, respectively. Using both datasets to compare results from these samples as benchmark, we observed that for most cancer types, subclonal reconstruction from WES is as informative as that from the matched WGS data. In summary, our study represents a significant methodological advancement in subclonal reconstruction and highlights the importance of measuring tumor subclone structure.

Citation Format: Yujie Jiang, Kaixian Yu, Matthew D. Montierth, Shuangxi Ji, Seung Jun Shin, Shuai Guo, Shaolong Cao, Yuxin Tang, Scott Kopetz, Pavlos Msaouel, Jennifer R. Wang, Marek Kimmel, Peter Van Loo, Hongtu Zhu, Wenyi Wang. Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4272.

Abstract 2070: Accelerated somatic mutation calling tool for whole-genome and whole-exome sequencing data from heterogenous tumor samples

As constantly improving in capacity and reducing in price, genomic sequencing is becoming a routine part of medical practice for cancer patients. Variant calling in sequencing data is a fundamental prerequisite for any downstream analysis, thus playing a critical role in both basic research and clinical care of cancers. However, it remains notably time-consuming for most available tools (e.g., ~2 days for MuSE 1.0 and MuTect2 to complete running on one tumor-normal pair of whole-genome sequencing (WGS) data). Here, we launch MuSE 2.0, which maintains the same input and output as our previously released MuSE 1.0, but speeds up significantly for both whole-exome sequencing (WES) and WGS data. MuSE 2.0 employs a multithreaded producer-consumer model and the OpenMP library for parallel computing, including parsing and uncompressing reads from BAM files, detecting and filtering variants, and writing output. Using sample data from ICGC and TCGA, we have benchmarked the speed performance of MuSE 2.0 against MuSE 1.0, MuTect2, SomaticSniper and VarScan2, which are chosen as the somatic mutation callers in the GDC DNA-seq analysis pipeline (https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline/). Compared to MuSE 1.0, MuSE 2.0 with 80 cores reduces the time cost of SNV calling from ∼40 hours per pair of tumor-normal WGS data down to less than 1 hour, and from 2-4 hours per pair of tumor-normal WES data down to 4-5 minutes (~50-60 times speedup). It is also faster than three other methods (up to 60 times), i.e., MuTect2, VarScan2 and SomaticSniper, for both WGS and WES data. These results show that MuSE 2.0 is a time-efficient tool and is expected to remove somatic mutation calling as a time-consuming obstacle for cancer genomic studies and clinicians decision making. MuSE 1.0 was adopted in multiple large-scale pipelines, including as a major contributing caller to reach final consensus calls by the TCGA PanCanAtlas project across 13,000 tumor samples, and the ICGC Pan-Cancer Analysis of Whole Genomes (PCAWG) initiative across 2,700 tumor samples. We therefore expect MuSE 2.0 to significantly accelerate the variant calling process and benefit the scientific and clinical communities. MuSE 2.0 is implemented in C++ and is freely available at GitHub https://github.com/wwylab/MuSE.

Citation Format: Shuangxi Ji, Tong Zhu, Ankit Sethia, Matthew D. Montierth, Wenyi Wang. Accelerated somatic mutation calling tool for whole-genome and whole-exome sequencing data from heterogenous tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2070.

Spatial-temporal lipidomics profile of acute myocardial injury

Background

Lipidome disturbance has long been recognized to occur after myocardial infarction (MI). Accumulation of excessive fatty acids induces production of reactive oxygen species and consequently deteriorates cardiac injury in MI. However, the spatial and temporal lipid profile in the heart following ischemic injury remains unknown.

Purpose

We aim to uncover the temporal-spatial lipidome profile of the heart following ischemia reperfusion (I/R) injury and identify circulating lipids released from injured myocardium that are potentially useful for diagnosis of ischemic heart disease.

Methods

C57/BL6 mice were subjected to 30 min myocardial ischemia followed by removal of the ligature to establish reperfusion injury. Porcine I/R injury was induced by 105 min myocardial ischemia followed by reperfusion. Human plasma was obtained from 143 post-MI patients. Myocardial lipid profiles were generated by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MALDI-MSI) in different regions (infarct, remote and peri-infarct) at different time points. Moreover, the lipids in the heart and plasma were analysed by LC-MS/MS.

Results

We observed a drastic alteration in the lipidome with distinct spatial-temporal features in the injured heart by both MALDI-MSI and LC-MS/MS. In the infarct heart tissue, as revealed by LC-MS/MS, we observed an elevation of glycerolipids that peaked at 3 hours after I/R, and a sustained elevation of phospholipids and sphingolipids up to 3 days. Similar alternations in lipid profile was observed but much weaker in the remote and peri-infarct heart tissue compared to the infarct tissue. Among those lipids, PC 32:0 detected by MALDI-MSI highly overlapped CD68 staining at a single-cell level, showing a strong correlation of PC 32:0 with macrophage infiltration in mouse hearts (R2=0.93, p&lt;0.0001). A similar increase of PC 32:0 in the infarct area was also observed in porcine hearts following I/R injury. Surprisingly, plasma levels of PC 32:0 in the mice decreased after I/R injury. In humans, plasma levels of PC 32:0 in post-MI patients were lower than that in healthy individuals (p=0.03). Further analysis demonstrated that plasma levels of PC 32:0 determined within 72 hours after percutaneous coronary intervention were negatively correlated with the 6-month post-MI cardiac ejection fraction in patients (R2=0.08, p&lt;0.001).

Conclusions

A temporal-spatial lipidome profile was established in heart injury by synergizing LC-MS/MS and mass spectrometry imaging. PC 32:0 levels are positively correlated with myocardial macrophage infiltration but negatively correlated with cardiac function in cardiac I/R injury. Our findings indicate that PC 32:0 is a potential biomarker for cardiac injury and the inflammatory status in the injured heart.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Singapore Ministry of Health's National Medical Research Council

Improved tenderness of beef from bulls supplemented with active dry yeast is related to matrix metalloproteinases and reduced oxidative stress

Supplementing diets with active dry yeast (ADY, Saccharomyces cerevisiae) improves the carcass quality grade of beef cattle and the tenderness of beef. The relevant mechanisms have not been fully elucidated, but may be related to the effect of ADY on oxidative stress and the activity of matrix metalloproteinases (MMPs). To provide further insight into these mechanisms, this study evaluated the influence of ADY supplementation on growth performance, carcass traits, meat quality, concentrations of MMPs in serum (MMP-2, MMP-9 and MMP-13), oxidative stress indices and antioxidant capacity indices in beef cattle. Forty-six crossbred Simmental × Yanbian bulls (∼18 months of age, BW 436 ± 35 kg) participated in a 145-day finishing trial. ADY supplementation significantly improved marbling deposition, intramuscular fat content, and beef tenderness (P < 0.05); altered individual fatty acid proportions in the beef and increased saturated fatty acids while decreasing polyunsaturated fatty acids (P < 0.05); significantly decreased the abundance of reactive oxygen species in serum and meat; significantly increased the level of superoxide dismutase in meat (P < 0.05); tended to increase the level of catalase (P = 0.075) in serum and glutathione reductase (P = 0.066) in meat; and increased the secretion of MMPs. The improvement of beef tenderness following ADY supplementation of finishing bulls is related to the effects of ADY on the secretion of MMPs and the lowering of oxidative stress.

MuSE: A Novel Approach to Mutation Calling with Sample-Specific Error Modeling

Accurate detection of somatic mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We have developed MuSE, Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of tumor and normal tissue at each reference base. It adopts a sample-specific error model to depict inter-tumor heterogeneity, which greatly improves the overall accuracy. Here, we describe the method and provide a tutorial on the installation and application of MuSE.

Novel Anaplastic Thyroid Cancer PDXs and Cell Lines: Expanding Preclinical Models of Genetic Diversity

CONTEXT

Anaplastic thyroid cancer (ATC) is a rare, aggressive, and deadly disease. Robust preclinical thyroid cancer models are needed to adequately develop and study novel therapeutic agents. Patient-derived xenograft (PDX) models may resemble patient tumors by recapitulating key genetic alterations and gene expression patterns, making them excellent preclinical models for drug response evaluation.

OBJECTIVE

We developed distinct ATC PDX models concurrently with cell lines and characterized them in vitro and in vivo.

METHODS

Fresh thyroid tumor from patients with a preoperative diagnosis of ATC was surgically collected and divided for concurrent cell line and PDX model development. Cell lines were created by generating single cells through enzymatic digestion. PDX models were developed following direct subcutaneous implantation of fresh tumor on the flank of immune compromised/athymic mice.

RESULTS

Six ATC PDX models and 4 cell lines were developed with distinct genetic profiles. Mutational characterization showed one BRAF/TP53/CDKN2A, one BRAF/CDKN2A, one BRAF/TP53, one TP53 only, one TERT-promoter/HRAS, and one TERT-promoter/KRAS/TP53/NF2/NFE2L2 mutated phenotype. Hematoxylin-eosin staining comparing the PDX models to the original patient surgical specimens show remarkable resemblance, while immunohistochemistry stains for important biomarkers were in full concordance (cytokeratin, TTF-1, PAX8, BRAF). Short tandem repeats DNA fingerprinting analysis of all PDX models and cell lines showed strong concordance with the original tumor. PDX successful establishment rate was 32%.

CONCLUSION

We have developed and characterized 6 novel ATC PDX models with 4 matching cell lines. Each PDX model harbors a distinct genetic profile, making them excellent tools for preclinical therapeutic trials.

The impact of hospital teaching status in atrial fibrillation hospital admission outcomes: a national inpatient analysis in the united states

Background

Teaching hospitals are are usually larger and have a higher level of complexity. Admissions for atrial fibrillation are commonly encountered by residents and fellows and they carry a hight cost, morbidity and mortality.

Purpose

Our aim is to do a retrospective analysis of the National Impatient Sample (NIS) from 2016 to 2018 and determine the impact of the hospital teaching status and rural Vs urban location in the atrial fibrillation admission outcomes.

Methods

We combined the NIS from 2016–2018. A primary diagnosis of atrial fibrillation was identified identified. We stratified the admissions based on the hospital teaching status. We defined as primary outcomes the length of stay (LOS), in hospital mortality and total charges/cost per admission. The secondary outcomes were the rates acute kidney injury (AKI), acute blood loss anemia (ABLA) and embolic stroke (ES). We used the Charlson comorbidity index. We used univariate and multivariate linear regressions for the continuous outcomes and logistic regressions for the binary outcomes.

Results

We identified 981,739 admissions with a primary diagnosis of atrial fibrillation; 513,914 (47%) were female patients, the average age was 70.5 years. In the teaching hospitals, the LOS was 0.3 days longer [95% CI: 0.22–0.37]; p=0.000 and the total hospital charges were higher (8406.32 dollar more per admission [95% CI: 6510.89–10301.76]; p=0.000); there was no difference in mortality compared to the non-teaching institutions (OR 1.03 [95% CI: 0.87–1.21]; p=0.628). In teaching hospitals, the rates of AKI, ABLA and ES were higher (OR 1.2, 95% CI [1.12–1.27]; p=0.000), (OR 1.29, 95% CI [1.09–1.53]; p=0.003) and (OR 1.72, 95% CI [1.11–2.66]; p=0.014)respectively. In a subgroup analysis comparing urban teaching hospitals Vs urban non-teaching Vs rural non-teaching hospitals, we found that the primary outcomes were similar than the above but the results in the secondary outcomes were driven mainly by a marked difference between rural and urban institutions regardless of teaching status, which makes us think that there might be under diagnosis of atrial fibrillation related complications in lower complexity rural hospitals. The difference in costs per admission was not as high when comparing urban teaching with non-teaching hospitals (5103.96 dollar higher, 95% [CI: 3008.70–7199.23]; p=0.000).

Conclusion

Amongst admissions for atrial fibrillation, the total cost per admission was higher in teaching hospitals which was concordant with a longer LOS. Although our results show higher rates of AKI, ABLA and ES in teaching hospitals, this might be caused by underdiagnosis of such conditions in non-teaching rural institutions compared to large teaching hospital systems and these were not associated with an increase rate of mortality. There is need for more research to determine the factors impacting the higher costs of atrial fibrillation admissions amongst teaching institutions.

Funding Acknowledgement

Type of funding sources: None.

A United States national analysis of basic demographics and commodities in sudden cardiac arrest

Background

Cardiac arrest is a condition associated with high mortality rate and can cause significant social-economical burden in United States. Our study aim is to analyze the basic demographic of patients admitted for cardiac arrest and the incidence of complications following cardiac arrest.

Methods

Using the National Inpatient Sample from 2016–2018, we identified all the hospital admissions with a primary diagnosis code at discharge for cardiac arrest during the study period. We identified the basic characteristics including age, gender, race and admitting hospital status. The set primary outcome was inpatient mortality, length of stay (LOS) and total costs of admission. The secondary outcomes were the incidence of acute kidney injury, acute blood loss anemia, acute embolism and thrombosis of deep veins of lower extremity (DVT), pulmonary embolism, non-traumatic intracranial hemorrhage, and thromboembolic stroke. Multivariable logistic regression model analysis was performed to address potential confounders. The Charlson Comorbidity Index (CCI) was used to adjust for the severity of each patient's co-morbidities.

Results

A total of 44,655 patients was admitted for cardiac arrest during the study period. Mean age was 64 years; 56% were men; 63% were white, 20.7% were black, 9.2% were latino, 2.8% were Asian or pacific Islander. The total in-hospital mortality was 73.5%. The average length of stay was 4.2 days and the average total costs of admission was 83,516 dollars. Among the seven demographic characteristics: age, gender, race, hospital size, hospital region, hospital teaching status, insurance type; only hospital teaching status and hospital size were found to significantly impact the mortality. Acute kidney injury was the most common complication in post-cardiac arrest patient (42%), followed by acute blood loss anemia (3.6%), pulmonary embolism (2.3%) and DVT (2.1%). Thromboembolic stroke (0.2%) and non-traumatic intracranial hemorrhage (0.1%) are less common. During subgroup analysis, acute kidney injury was also found out to be a predictive factor of increased mortality (OR 1.64, p&lt;0.001).

Conclusion

Cardiac arrest remains one of the conditions with highest mortality rate. In our study, age, gender or race dit not impact on the outcome of cardiac arrest. Among all the complications from cardiac arrest, acute kidney injury was the most common one and was associated with higher mortality rate.

Funding Acknowledgement

Type of funding sources: None.

[Correlation between systemic inflammation level and emphysema degree and bone mineral density in chronic obstructive pulmonary disease patients and its mechanism]

Objective: To study the correlation between systemic inflammation level and emphysema degree and bone mineral density in chronic obstructive pulmonary disease (COPD) patients and its possible mechanism. Methods: 90 patients with stable COPD who met the inclusion criteria and 50 controls in the physical examination center during the same period were recruited. All the enrolled objects have collected general clinical data, analyzed peripheral blood samples, measuring the Low-attenuation area of lung and CT value of lumbar 1 vertebra (L1-CT) by chest spiral CT. According to LAA%, COPD patients were divided into 36 cases of the non-emphysema group, 32cases of mild to moderate emphysema group, and 22 cases of severe emphysema group. The correlation between L1-CT value, LAA%, peripheral blood inflammatory factors, and pulmonary function indices in each group was analyzed and compared. Results: The HU value of L1-CT (107±32) in the COPD group was significantly lower than that in the control group (153±30), and the difference was statistically significant (P<0.05). The higher the LAA% in COPD patients was, the lower the value of L1-CT was, and the difference between groups was statistically significant. Compared with COPD patients in the non-emphysema group, peripheral blood neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and C-reactive protein (CRP) were all increased in the emphysema group, and the differences were statistically significant (P<0.05). L1-CT was negatively correlated with LAA, PLR, NLR, and CRP while uncorrelated with serum concentration of calcium and phosphorus. Conclusion: The decrease in bone density in COPD patients is closely related to the degree of emphysema. It is associated with increased levels of systemic inflammation caused by COPD itself. Early and timely broad-spectrum anti-inflammatory treatment may have certain clinical significance for the prevention and treatment of comorbidity with osteoporosis.

Peripheral blood T-cell receptor repertoire as a predictor of clinical outcomes in gastrointestinal cancer patients treated with PD-1 inhibitor

BACKGROUND

Identifying valid biomarkers for patient selection impressively promotes the success of anti-PD-1 therapy. However, the unmet need for biomarkers in gastrointestinal (GI) cancers remains significant. We aimed to explore the predictive value of the circulating T-cell receptor (TCR) repertoire for clinical outcomes in GI cancers who received anti-PD-1 therapy.

METHODS

137 pre- and 79 post-treated peripheral blood samples were included. The TCR repertoire was evaluated by sequencing of complementarity-determining region 3 (CDR3) in the TRB gene. The Shannon index was used to measure the diversity of the TCR repertoire, and Morisita's overlap index was used to determine TCR repertoire similarities between pre- and post-treated samples.

RESULTS

Among all enrolled patients, 76 received anti-PD-1 monotherapy and 61 received anti-PD-1 combination therapy. In the anti-PD-1 monotherapy cohort, patients with higher baseline TCR diversity exhibited a significantly higher disease control rate (77.8% vs. 47.2%; hazard ratio [HR] 3.92; 95% confidence interval [CI] 1.14-13.48; P = 0.030) and a longer progression-free survival (PFS) (median: 6.47 months vs. 2.77 months; HR 2.10; 95% CI 1.16-3.79; P = 0.014) and overall survival (OS) (median: NA vs. 8.97 months; HR 3.53; 95% CI 1.49-8.38; P = 0.004) than those with lower diversity. Moreover, patients with a higher TCR repertoire similarity still showed a superior PFS (4.43 months vs. 1.84 months; HR 13.98; 95% CI 4.37-44.68; P < 0.001) and OS (13.40 months vs. 6.12 months; HR 2.93; 95% CI 1.22-7.03; P = 0.016) even in the cohort with lower baseline diversity. However, neither biomarker showed predictive value in the anti-PD-1 combination therapy cohort. Interestingly, the combination of TCR diversity and PD-L1 expression can facilitate patient stratification in a pooled cohort.

CONCLUSION

The circulating TCR repertoire can serve as a predictor of clinical outcomes in anti-PD-1 therapy in GI cancers.

[Influenza virus activates toll-like receptor 7/nuclear factor-κB signaling pathway to regulate airway inflammatory response in patients with acute exacerbation of chronic obstructive pulmonary diseases]

Objective: To explore how influenza A virus (IAV) regulates airway inflammation via activating Toll-like receptor 7(TLR7)/nuclear factor of κB (NF-κB) signaling pathway in patients with acute exacerbation of chronic obstructive pulmonary disease (COPD). Methods: Primary bronchial epithelial cells were isolated and cultured from normal controls and COPD patients. Samples were divided into 6 groups according to different in vitro treatment, including normal epithelial cell group (A), normal cells+IAV group (B), COPD epithelial cell group (C), COPD cells+IAV group (D), normal cells+TLR7 small interference RNA (si-RNA) group (E), COPD cells+TLR7 siRNA group (F). Protein expressions of TLR7 and NF-κB were detected by Western blot after 24h co-culture with IAV and TLR7 siRNA. Interleukin-6 (IL-6) and tumor necrosis factor α (TNF α) were detected by enzyme-linked immunosorbent assay (ELISA). Results: (1) Compared with group A [0.350±0.075 and 0.470±0.034, (53.000±6.532)pg/ml and (17.000±1.625)pg/ml],TLR7, NF-κB protein expression and IL-6, TNF α levels were significantly increased in group B[0.950±0.075 and 1.090±0.078,(185.000±7.874)pg/ml and (32.000±0.838)pg/ml], group C[0.780±0.056 and 0.910±0.045,(138.000±5.100)pg/ml and 29.000±1.323)pg/ml) and group D[1.280±0.031 and 1.540±0.051,(432.000±5.734)pg/ml and (52.000±3.453)pg/ml] (all P<0.01). Compared with group C TLR7, NF-κB protein expression and IL-6, TNF α levels were significantly increased in group D (P<0.01). (2) Compared with the group A[0.530±0.023 and 0.800±0.046,(51.000±0.327)pg/ml and (14.000±0.314)pg/ml], TLR7, NF-κB protein expression and IL-6, TNF α levels were significantly decreased in the group E[0.350±0.047 and 0.510±0.067,(26.000±1.081)pg/ml and(8.000±0.526)pg/ml] (P<0.05). Compared with group C[1.080±0.078 and 1.280±0.034,(125.000±2.249)pg/ml and (28.000±1.010)pg/ml], TLR7, NF-κB protein expression and IL-6, TNF α levels decreased in the group F[0.880±0.056 and 1.040±0.029,(83.000±1.125)pg/ml and (21.000±0.429)pg/ml] (P<0.05). Conclusion: Influenza viruses activate TLR7/NF-κB signaling pathway to regulate airway inflammation storms in patients with acute exacerbation of COPD. New therapeutic targets of acute exacerbation COPD may be studied based on these inflammation responses to influenza viruses.

Effects of crocin on frozen-thawed sperm apoptosis, protamine expression and membrane lipid oxidation in Yanbian yellow cattle

Glycerol is used as a bovine semen osmotic cryoprotectant that greatly improves the quality of frozen and thawed bovine sperm. However, high glycerol concentrations can have a toxic effect on frozen and thawed bovine sperm. Therefore, this experiment investigated the effect of replacing a portion of the glycerol in a cryoprotectant solution with crocin on the sperm apoptosis, protamine deficiency and membrane lipid oxidation of frozen and thawed Yanbian yellow cattle sperm. The experiment included a control group (6% glycerol) and four treatment groups: I (3% glycerol), II (3% glycerol +0.5 mM crocin), III (3% glycerol + 1 mM crocin) and IV (3% glycerol + 2 mM crocin). Computer assisted semen analysis was used to detect sperm motility, Hoechst 33,342, propidium iodide, and JC-1 staining were used to analyse sperm viability and mitochondrial membrane potential, chromomycin A3 staining was used to detect protamine deficiency and DNA damage, flow cytometry was used for sperm membrane lipid disorder detection and analysis, and real-time quantitative RT-qPCR was used to detect the mRNA expression levels of protamine-related genes (PRM2, PRM3), sperm acrosome-associated genes (SPACA3), oxidative stress-related genes (ROMO1) and apoptosis-related genes (BCL2, BAX). Compared to the control group, replacing a portion of glycerol with 1 mM crocin significantly improved sperm motility, plasma membrane integrity, membrane lipid disorders (p < .05) and viability, mitochondrial membrane potential, protamine deficiency (p < .01). The expression level of PRM2, PRM3, SPACA3 and BCL2 significantly increased (p < .05), while the expression levels of ROMO1 and BAX significantly decreased (p < .05). Accordingly, the BCL2/BAX ratio significantly increased (p < .05). In summary, the substitution of a portion of glycerol with crocin in cryoprotective solution improved the quality of Yanbian yellow cattle sperm after freezing and thawing.