Characterization of the tumor microenvironment landscape and deep learning-guided prediction of prognosis in lung adenocarcinoma with bulk RNA sequencing data.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21025-e21025
Author(s):  
Philippe Gui ◽  
Wei Wu ◽  
Elizabeth Yu ◽  
Caroline Elizabeth McCoach ◽  
Robert Charles Doebele ◽  
...  
Keyword(s):  
Deep Learning ◽  
Lung Adenocarcinoma ◽  
Residual Disease ◽  
Smoking History ◽  
Cell Populations ◽  
Sequencing Data ◽  
Stroma Cell ◽  
Stage Disease ◽  
Late Stage Disease ◽  
Key Features

e21025 Background: The tumor microenvironment (TME) plays an important role in tumor progression and treatment response, therefore profoundly affecting patient outcomes. Efforts to characterize the TME in lung adenocarcinoma are emerging but have been limited by the sample size and lack of treatment timepoints. Methods: We characterized changes in lung TME using the xCell algorithm to distinguish 64 immune and stroma cell types from bulk RNA sequencing data. The correlation between subtype cell population in lung TME and various clinical and biological characteristics was analyzed from over 500 lung adenocarcinoma (LUAD) samples from The Cancer Genome Atlas and an independent cohort of 48 advanced LUAD patients with treatment annotations (treatment-naive, residual disease, and progressive disease). In addition, we used key features in lung TME to predict prognosis using deep learning algorithms. Results: We found significant changes in both immune and stroma cell populations according to various clinical parameters such as smoking history, cancer stage, and treatment status. Specific sub-populations within lung TME correlate with survival outcomes based on Kaplan-Meier survival analyses. CD4- and CD8-positive T-cells are enriched in early stage disease and depleted in late stage disease, suggesting evolution of the TME during cancer progression. Consistent with previous reports, scores of immune cell populations associated with worse survival, such as T helper type 2 cells, are increased in late stage disease. Smoking history also reshapes the lung TME as populations correlated with better survival are decreased in smokers. We also found variations in sub-populations according to the driver oncogenes, with a less abundant lymphoid compartment in EGFR mutant samples compared to KRAS driven samples. Interestingly, we found higher scores of macrophage populations in residual disease following targeted-therapy treatment compared to pre-treatment. Finally, using machine and deep learning methods we identified a panel of 12 key features within the lung TME which could be used to predict prognosis. Conclusions: We comprehensively characterized immune and stroma cell type changes in the lung TME utilizing bulk RNA-seq data, and evaluated the association of sub-type cell populations with different clinical and biological features. Key features in lung TME could be used to predict prognosis.

scholarly journals Single-cell transcriptomic analysis of mIHC images via antigen mapping

2021 ◽  
Vol 7 (10) ◽  
pp. eabc5464
Author(s):  
Kiya W. Govek ◽  
Emma C. Troisi ◽  
Zhen Miao ◽  
Rachael G. Aubin ◽  
Steven Woodhouse ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Patterns ◽  
Cell Types ◽  
Level Of Detail ◽  
Cell Populations ◽  
Sequencing Data ◽  
Spatially Resolved ◽  
Murine Spleen ◽  
Single Cell Rna Sequencing ◽  
Antibody Panel

Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ.

scholarly journals Resistance to antibody neutralization in HIV-2 infection occurs in late stage disease and is associated with X4 tropism

AIDS ◽  
2012 ◽  
Vol 26 (18) ◽  
pp. 2275-2284 ◽  
Author(s):  
José M. Marcelino ◽  
Pedro Borrego ◽  
Charlotta Nilsson ◽  
Carlos Família ◽  
Helena Barroso ◽  
...  
Keyword(s):  
Late Stage ◽  
Antibody Neutralization ◽  
Stage Disease ◽  
Late Stage Disease

Receipt of Screening Mammography by Insured Women Diagnosed With Breast Cancer and Impact on Outcomes

2021 ◽  
Author(s):  
Marissa B. Lawson ◽  
Christoph I. Lee ◽  
Daniel S. Hippe ◽  
Shasank Chennupati ◽  
Catherine R. Fedorenko ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Late Stage ◽  
Breast Cancer Diagnosis ◽  
Screening Mammography ◽  
Socioeconomic Deprivation ◽  
Tumor Characteristics ◽  
Stage Disease ◽  
Increased Risk ◽  
Late Stage Disease

Background: The purpose of this study was to determine factors associated with receipt of screening mammography by insured women before breast cancer diagnosis, and subsequent outcomes. Patients and Methods: Using claims data from commercial and federal payers linked to a regional SEER registry, we identified women diagnosed with breast cancer from 2007 to 2017 and determined receipt of screening mammography within 1 year before diagnosis. We obtained patient and tumor characteristics from the SEER registry and assigned each woman a socioeconomic deprivation score based on residential address. Multivariable logistic regression models were used to evaluate associations of patient and tumor characteristics with late-stage disease and nonreceipt of mammography. We used multivariable Cox proportional hazards models to identify predictors of subsequent mortality. Results: Among 7,047 women, 69% (n=4,853) received screening mammography before breast cancer diagnosis. Compared with women who received mammography, those with no mammography had a higher proportion of late-stage disease (34% vs 10%) and higher 5-year mortality (18% vs 6%). In multivariable modeling, late-stage disease was most associated with nonreceipt of mammography (odds ratio [OR], 4.35; 95% CI, 3.80–4.98). The Cox model indicated that nonreceipt of mammography predicted increased risk of mortality (hazard ratio [HR], 2.00; 95% CI, 1.64–2.43), independent of late-stage disease at diagnosis (HR, 5.00; 95% CI, 4.10–6.10), Charlson comorbidity index score ≥1 (HR, 2.75; 95% CI, 2.26–3.34), and negative estrogen receptor/progesterone receptor status (HR, 2.09; 95% CI, 1.67–2.61). Nonreceipt of mammography was associated with younger age (40–49 vs 50–59 years; OR, 1.69; 95% CI, 1.45–1.96) and increased socioeconomic deprivation (OR, 1.05 per decile increase; 95% CI, 1.03–1.07). Conclusions: In a cohort of insured women diagnosed with breast cancer, nonreceipt of screening mammography was significantly associated with late-stage disease and mortality, suggesting that interventions to further increase uptake of screening mammography may improve breast cancer outcomes.

Oxidative stress in chronic hepatitis C: not just a feature of late stage disease

2002 ◽  
Vol 36 (6) ◽  
pp. 805-811 ◽  
Author(s):  
Sanjiv K. Jain ◽  
Philip W. Pemberton ◽  
Alexander Smith ◽  
Raymond F.T. McMahon ◽  
Peter C. Burrows ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Chronic Hepatitis ◽  
Hepatitis C ◽  
Chronic Hepatitis C ◽  
Late Stage ◽  
Stage Disease ◽  
Late Stage Disease

Importance of bleomycin in favorable-prognosis disseminated germ cell tumors: an Eastern Cooperative Oncology Group trial.

1995 ◽  
Vol 13 (2) ◽  
pp. 470-476 ◽  
Author(s):  
P J Loehrer ◽  
D Johnson ◽  
P Elson ◽  
L H Einhorn ◽  
D Trump
Keyword(s):  
Germ Cell ◽  
Residual Disease ◽  
Eastern Cooperative Oncology Group ◽  
Germ Cell Tumors ◽  
Staging System ◽  
Patient Characteristics ◽  
Significant Incidence ◽  
Stage Disease ◽  
Radiographic Disease ◽  
Clinically Significant

PURPOSE This prospective, randomized trial was designed to determine if three cycles of cisplatin plus etoposide (PVP16) can produce therapeutic results comparable to three cycles of cisplatin, etoposide, and bleomycin (PVP16B) in patients with disseminated germ cell tumors. PATIENTS AND METHODS One hundred seventy-eight patients with minimal- or moderate-stage disease (Indiana staging system) were randomized to receive cisplatin (20 mg/m2 on days 1 to 5) plus etoposide (100 mg/m2 on days 1 to 5) with or without weekly bleomycin (30 IU/wk for 9 consecutive weeks). Following three cycles of chemotherapy over 9 weeks, patients with residual radiographic disease underwent surgical resection. If persistent carcinoma was noted, two additional 3-week courses of chemotherapy were administered. RESULTS One hundred seventy-one patients were fully assessable for response and survival. The two treatment groups were similar with respect to patient characteristics. The toxicities were comparable between the two arms. No clinically significant incidence of pulmonary toxicity occurred with PVP16B. Overall, 81 of 86 patients (94%) who received PVP16B and 75 of 85 patients (88%) who received PVP16 achieved a disease-free status with chemotherapy and/or surgery. However, greater numbers of treatment failures, including persistent carcinoma in postchemotherapy resected residual disease and relapses from complete remission, occurred on the arm without bleomycin (overall adverse outcome, P = .004). The failure-free (86% v 69%; P = .01) and overall survival (95% v 86%; P = .01) rates were inferior on the PVP16 arm. CONCLUSION Bleomycin is an essential component of PVP16B therapy in patients who receive three cycles of treatment for minimal- or moderate-stage disseminated germ cell tumors.

scholarly journals DISMIR: a deep learning-based cancer-detection method by integrating DNA sequence and methylation information of individual cell-free DNA reads

2021 ◽  
Author(s):  
Jiaqi Li ◽  
Lei Wei ◽  
Xianglin Zhang ◽  
Wei Zhang ◽  
Haochen Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Dna Sequence ◽  
Cancer Detection ◽  
High Throughput Sequencing ◽  
Detection Method ◽  
Low Cost ◽  
Sequencing Data ◽  
Cell Free Dna ◽  
Free Dna ◽  
Novel Approach

ABSTRACTDetecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel non-invasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise prediction with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as “switching region” to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state, and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultra-low sequencing depths. Analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites’ methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.

scholarly journals Natural alteration of HIV-1 co-receptor tropism by contemporaneous HIV-2 infection

2018 ◽  
Author(s):  
Joakim Esbjörnsson ◽  
Fredrik Månsson ◽  
Hans Norrgren ◽  
Sarah L. Rowland-Jones
Keyword(s):  
Late Stage ◽  
Stage Disease ◽  
Late Stage Disease ◽  
Underlying Mechanisms ◽  
Disease Understanding ◽  
Hiv 1 ◽  
The Way

In this study, we show that the pathogenic HIV-1 CXCR4-tropism is more common in HIV-1 single (79%) than in HIV-1 and HIV-2 dual-infected individuals (35%), suggesting that contemporaneous HIV-2 infection can affect HIV-1 co-receptor tropism in late-stage disease. Understanding the underlying mechanisms responsible for this natural alteration by HIV-2 could pave the way towards a deeper understanding of the AIDS pathogenesis.

scholarly journals A Deep-Learning Pipeline for TSS Coverage Imputation From Shallow Cell-Free DNA Sequencing

2021 ◽  
Vol 8 ◽  
Author(s):  
Bo-Wei Han ◽  
Xu Yang ◽  
Shou-Fang Qu ◽  
Zhi-Wei Guo ◽  
Li-Min Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Nucleosome Occupancy ◽  
Sequencing Data ◽  
Cell Free Dna ◽  
Transcription Start Sites ◽  
Free Dna ◽  
Coverage Accuracy ◽  
Moderate Cost ◽  
Coverage Profile ◽  
High Depth

Cell-free DNA (cfDNA) serves as a footprint of the nucleosome occupancy status of transcription start sites (TSSs), and has been subject to wide development for use in noninvasive health monitoring and disease detection. However, the requirement for high sequencing depth limits its clinical use. Here, we introduce a deep-learning pipeline designed for TSS coverage profiles generated from shallow cfDNA sequencing called the Autoencoder of cfDNA TSS (AECT) coverage profile. AECT outperformed existing single-cell sequencing imputation algorithms in terms of improvements to TSS coverage accuracy and the capture of latent biological features that distinguish sex or tumor status. We built classifiers for the detection of breast and rectal cancer using AECT-imputed shallow sequencing data, and their performance was close to that achieved by high-depth sequencing, suggesting that AECT could provide a broadly applicable noninvasive screening approach with high accuracy and at a moderate cost.

scholarly journals Cytosine methylation dynamics during post-testicular sperm maturation in mammals

2020 ◽  
Author(s):  
Carolina Galan ◽  
Ryan W. Serra ◽  
Fengyun Sun ◽  
Vera D. Rinaldi ◽  
Colin C. Conine ◽  
...  
Keyword(s):  
Germ Cell ◽  
Cytosine Methylation ◽  
Reproductive Tract ◽  
Extracellular Dna ◽  
Cell Populations ◽  
Epididymal Sperm ◽  
Sequencing Data ◽  
Testicular Germ Cell ◽  
Mammalian Sperm ◽  
The Stability

ABSTRACTBeyond the haploid genome, mammalian sperm contribute a payload of epigenetic information which can modulate offspring phenotypes. Recent studies have shown that the small RNA payload of sperm undergoes extensive remodeling during post-testicular maturation in the epididymis. Intriguingly, epididymal maturation has also been linked to changes in the sperm methylome, suggesting that the epididymis might play a broader role in remodeling the sperm epigenome. Here, we build on prior studies of the maturing sperm methylation landscape, further characterizing the genome-wide methylation landscape in seven germ cell populations collected from throughout the male reproductive tract. Overall, we find very few changes in the cytosine methylation landscape between testicular germ cell populations and cauda epididymal sperm, demonstrating that the sperm methylome is largely stable throughout post-testicular maturation. Intriguingly, although our sequencing data suggested that caput epididymal sperm exhibit a highly unusual methylome, follow-up studies revealed that this resulted from contamination of caput sperm by extracellular DNA. Extracellular DNA formed web-like structures that ensnared sperm, was present only in the caput epididymis of virgin males, where it was associated with citrullinated histone H3 and presumably resulted from a PAD-driven genome decondensation process. Taken together, our data emphasize the stability of the cytosine methylation landscape in mammalian sperm, and identify a surprising but transient period during which immature sperm are associated with extracellular DNA.

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