scholarly journals An R Implementation of Tumor-Stroma-Immune Transcriptome Deconvolution Pipeline using DeMixT

2019 ◽  
Author(s):  
Shaolong Cao ◽  
Zeya Wang ◽  
Fan Gao ◽  
Jingxiao Chen ◽  
Feng Zhang ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Expression Profiles ◽  
Progression Free Survival ◽  
Tumor Stroma ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Biological Information ◽  
Computationally Efficient ◽  
Multiple Cancer ◽  
Cancer Genome Atlas

AbstractThe deconvolution of transcriptomic data from heterogeneous tissues in cancer studies remains challenging. Available software faces difficulties for accurately estimating both component-specific proportions and expression profiles for individual samples. To address these challenges, we present a new R-implementation pipeline for the more accurate and efficient transcriptome deconvolution of high dimensional data from mixtures of more than two components. The pipeline utilizes the computationally efficient DeMixT R-package with OpenMP and additional cancer-specific biological information to perform three-component deconvolution without requiring data from the immune profiles. It enables a wide application of DeMixT to gene expression datasets available from cancer consortium such as the Cancer Genome Atlas (TCGA) projects, where, other than the mixed tumor samples, a handful of normal samples are profiled in multiple cancer types. We have applied this pipeline to two TCGA datasets in colorectal adenocarcinoma (COAD) and prostate adenocarcinoma (PRAD). In COAD, we found varying distributions of immune proportions across the Consensus Molecular Subtypes, from the highest to the lowest being CMS1, CMS3, CMS4 and CMS2. In PRAD, we found the immune proportions are associated with progression-free survival (p<0.01) and negatively correlated with Gleason scores (p<0.001). Our DeMixT-centered analysis protocol opens up new opportunities to investigate the tumor-stroma-immune microenvironment, by providing both proportions and component-specific expressions, and thus better define the underlying biology of cancer progression.Availability and implementation: An R package, scripts and data are available: https://github.com/wwylab/DeMixTallmaterials.

Regulation of the Effect of Physical Activity Through MicroRNAs in Breast Cancer

2021 ◽  
Author(s):  
Bok Sil Hong
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Cancer Progression ◽  
Target Genes ◽  
Expression Profiles ◽  
Breast Cancer Progression ◽  
The Cancer Genome Atlas ◽  
Circulating Micrornas ◽  
Tumor Stages ◽  
Cancer Genome Atlas

AbstractPhysical activity and exercise can induce beneficial molecular and biological regulations that have been associated with an incidence of various diseases, including breast cancer. Recent studies demonstrated that the potential links between physical activity-induced circulating microRNAs (miRNAs) and cancer risk and progression. Here, we investigated whether altered miRNAs by exercise could influence breast cancer progression. After primary searching in PubMed and reviewing the full-text papers, candidate miRNAs altered by exercise in breast cancer were identified. Analysis of expression profiles and clinical outcomes of altered miRNAs using The Cancer Genome Atlas datasets showed altered miRNAs expressions were significantly associated with the patient's prognosis, whereas prognostic values of each miRNA varied in different stages and subtypes. In addition, altered miRNAs profiles regulated various target genes and key signaling pathways in tumorigenesis, including pathways in cancer and the PI3K-Akt signaling pathway; however, miRNAs regulated the expression of target genes differently according to tumor stages and subtypes. These results indicate that circulating miRNAs are promising noninvasive stable biomarkers for early detection, diagnosis, prognosis, and monitoring the response to clinical therapies of breast cancer. Moreover, stages and subtype-stratified approaches for breast cancer progression would be needed to evaluate the prognostic value of miRNAs for biomarkers and therapeutic targets.

scholarly journals Identification of Prognostic Biomarkers Originating From the Tumor Stroma of Betel Quid-Associated Oral Cancer Tissues

2021 ◽  
Vol 11 ◽  
Author(s):  
Yi-Hong Liu ◽  
Yu-Lian Chen ◽  
Ting-Yu Lai ◽  
Ying-Chieh Ko ◽  
Yu-Fu Chou ◽  
...  
Keyword(s):  
Overall Survival ◽  
Oral Cancer ◽  
Cancer Progression ◽  
Tumor Stroma ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Cancer Tissues ◽  
Genome Atlas

BackgroundPartial epithelial-mesenchymal transition (p-EMT) is a distinct clinicopathological feature prevalent in oral cavity tumors of The Cancer Genome Atlas. Located at the invasion front, p-EMT cells require additional support from the tumor stroma for collective cell migration, including track clearing, extracellular matrix remodeling and immune evasion. The pathological roles of otherwise nonmalignant cancer-associated fibroblasts (CAFs) in cancer progression are emerging.MethodsGene set enrichment analysis was used to reveal differentially enriched genes and molecular pathways in OC3 and TW2.6 xenograft tissues, representing mesenchymal and p-EMT tumors, respectively. R packages of genomic data science were executed for statistical evaluations and data visualization. Immunohistochemistry and Alcian blue staining were conducted to validate the bioinformatic results. Univariate and multivariate Cox proportional hazards models were performed to identify covariates significantly associated with overall survival in clinical datasets. Kaplan–Meier curves of estimated overall survival were compared for statistical difference using the log-rank test.ResultsCompared to mesenchymal OC3 cells, tumor stroma derived from p-EMT TW2.6 cells was significantly enriched in microvessel density, tumor-excluded macrophages, inflammatory CAFs, and extracellular hyaluronan deposition. By translating these results to clinical transcriptomic datasets of oral cancer specimens, including the Puram single-cell RNA-seq cohort comprising ~6000 cells, we identified the expression of stromal TGFBI and HYAL1 as independent poor and protective biomarkers, respectively, for 40 Taiwanese oral cancer tissues that were all derived from betel quid users. In The Cancer Genome Atlas, TGFBI was a poor marker not only for head and neck cancer but also for additional six cancer types and HYAL1 was a good indicator for four tumor cohorts, suggesting common stromal effects existing in different cancer types.ConclusionsAs the tumor stroma coevolves with cancer progression, the cellular origins of molecular markers identified from conventional whole tissue mRNA-based analyses should be cautiously interpreted. By incorporating disease-matched xenograft tissue and single-cell RNA-seq results, we suggested that TGFBI and HYAL1, primarily expressed by stromal CAFs and endothelial cells, respectively, could serve as robust prognostic biomarkers for oral cancer control.

scholarly journals Screening and Comprehensive Analysis of Cancer-Associated tRNA-Derived Fragments

2022 ◽  
Vol 12 ◽  
Author(s):  
Yiran Zhou ◽  
Qinghua Cui ◽  
Yuan Zhou
Keyword(s):  
Signaling Pathway ◽  
Cancer Progression ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Composition Analysis ◽  
Multiple Cancer ◽  
Systematic Analysis ◽  
Cancer Subtypes ◽  
Cancer Types

tRNA-derived fragments (tRFs) constitute a novel class of small non-coding RNA cleaved from tRNAs. In recent years, researches have shown the regulatory roles of a few tRFs in cancers, illuminating a new direction for tRF-centric cancer researches. Nonetheless, more specific screening of tRFs related to oncogenesis pathways, cancer progression stages and cancer prognosis is continuously demanded to reveal the landscape of the cancer-associated tRFs. In this work, by combining the clinical information recorded in The Cancer Genome Atlas (TCGA) and the tRF expression profiles curated by MINTbase v2.0, we systematically screened 1,516 cancer-associated tRFs (ca-tRFs) across seven cancer types. The ca-tRF set collectively combined the differentially expressed tRFs between cancer samples and control samples, the tRFs significantly correlated with tumor stage and the tRFs significantly correlated with patient survival. By incorporating our previous tRF-target dataset, we found the ca-tRFs tend to target cancer-associated genes and onco-pathways like ATF6-mediated unfolded protein response, angiogenesis, cell cycle process regulation, focal adhesion, PI3K-Akt signaling pathway, cellular senescence and FoxO signaling pathway across multiple cancer types. And cell composition analysis implies that the expressions of ca-tRFs are more likely to be correlated with T-cell infiltration. We also found the ca-tRF expression pattern is informative to prognosis, suggesting plausible tRF-based cancer subtypes. Together, our systematic analysis demonstrates the potentially extensive involvements of tRFs in cancers, and provides a reasonable list of cancer-associated tRFs for further investigations.

scholarly journals Semi-supervised identification of cancer subgroups using survival outcomes and overlapping grouping information

2018 ◽  
Vol 28 (7) ◽  
pp. 2137-2149 ◽  
Author(s):  
Wei Wei ◽  
Zequn Sun ◽  
Willian A da Silveira ◽  
Zhenning Yu ◽  
Andrew Lawson ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
High Throughput ◽  
Genomic Data ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Integrative Genomics ◽  
Molecular Features ◽  
Biological Interpretation ◽  
Cancer Genome Atlas

Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because of low reproducibility and instability of identified cancer subgroups and molecular features. In order to address this challenge, we developed Integrative Genomics Robust iDentification of cancer subgroups (InGRiD), a statistical approach that integrates information from biological pathway databases with high-throughput genomic data to improve the robustness for identification and interpretation of molecularly-defined subgroups of cancer patients. We applied InGRiD to the gene expression data of high-grade serous ovarian cancer from The Cancer Genome Atlas and the Australian Ovarian Cancer Study. The results indicate clear benefits of the pathway-level approaches over the gene-level approaches. In addition, using the proposed InGRiD framework, we also investigate and address the issue of gene sharing among pathways, which often occurs in practice, to further facilitate biological interpretation of key molecular features associated with cancer progression. The R package “InGRiD” implementing the proposed approach is currently available in our research group GitHub webpage ( https://dongjunchung.github.io/INGRID/ ).

scholarly journals Immune-Related Circulating miR-125b-5p and miR-99a-5p Reveal a High Recurrence Risk Group of Pancreatic Cancer Patients after Tumor Resection

2019 ◽  
Vol 9 (22) ◽  
pp. 4784
Author(s):  
Vietsch ◽  
Peran ◽  
Suker ◽  
van den Bosch ◽  
Sijde ◽  
...  
Keyword(s):  
Cancer Progression ◽  
B Lymphocyte ◽  
Immune Cell ◽  
Tumor Resection ◽  
Progression Free Survival ◽  
Tumor Stroma ◽  
Recurrence Risk ◽  
High Serum ◽  
Ductal Adenocarcinoma ◽  
Before And After

Clinical follow-up aided by changes in the expression of circulating microRNAs (miRs) may improve prognostication of pancreatic ductal adenocarcinoma (PDAC) patients. Changes in 179 circulating miRs due to cancer progression in the transgenic KrasG12D/+; Trp53R172H/+; P48-Cre (KPC) animal model of PDAC were analyzed for serum miRs that are altered in metastatic disease. In addition, expression levels of 250 miRs were profiled before and after pancreaticoduodenectomy in the serum of two patients with resectable PDAC with different progression free survival (PFS) and analyzed for changes indicative of PDAC recurrence after resection. Three miRs that were upregulated ≥3-fold in progressive PDAC in both mice and patients were selected for validation in 26 additional PDAC patients before and after resection. We found that high serum miR-125b-5p and miR-99a-5p levels after resection are significantly associated with shorter PFS (HR 1.34 and HR 1.73 respectively). In situ hybridization for miR detection in the paired resected human PDAC tissues showed that miR-125b-5p and miR-99a-5p are highly expressed in inflammatory cells in the tumor stroma, located in clusters of CD79A expressing cells of the B-lymphocyte lineage. In conclusion, we found that circulating miR-125b-5p and miR-99a-5p are potential immune-cell related prognostic biomarkers in PDAC patients after surgery.

scholarly journals Iron-Bound Lipocalin-2 from Tumor-Associated Macrophages Drives Breast Cancer Progression Independent of Ferroportin

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 180
Author(s):  
Christina Mertens ◽  
Matthias Schnetz ◽  
Claudia Rehwald ◽  
Stephan Grein ◽  
Eiman Elwakeel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Progression ◽  
Tumor Cells ◽  
Cancer Progression ◽  
Lung Metastases ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Lipocalin 2 ◽  
Tumor Associated Macrophages

Macrophages supply iron to the breast tumor microenvironment by enforced secretion of lipocalin-2 (Lcn-2)-bound iron as well as the increased expression of the iron exporter ferroportin (FPN). We aimed at identifying the contribution of each pathway in supplying iron for the growing tumor, thereby fostering tumor progression. Analyzing the expression profiles of Lcn-2 and FPN using the spontaneous polyoma-middle-T oncogene (PyMT) breast cancer model as well as mining publicly available TCGA (The Cancer Genome Atlas) and GEO Series(GSE) datasets from the Gene Expression Omnibus database (GEO), we found no association between tumor parameters and Lcn-2 or FPN. However, stromal/macrophage-expression of Lcn-2 correlated with tumor onset, lung metastases, and recurrence, whereas FPN did not. While the total iron amount in wildtype and Lcn-2−/− PyMT tumors showed no difference, we observed that tumor-associated macrophages from Lcn-2−/− compared to wildtype tumors stored more iron. In contrast, Lcn-2−/− tumor cells accumulated less iron than their wildtype counterparts, translating into a low migratory and proliferative capacity of Lcn-2−/− tumor cells in a 3D tumor spheroid model in vitro. Our data suggest a pivotal role of Lcn-2 in tumor iron-management, affecting tumor growth. This study underscores the role of iron for tumor progression and the need for a better understanding of iron-targeted therapy approaches.

scholarly journals HNRNPH1-stabilized LINC00662 promotes ovarian cancer progression by activating the GRP78/p38 pathway

Oncogene ◽  
2021 ◽  
Author(s):  
Yong Wu ◽  
Qinhao Guo ◽  
Xingzhu Ju ◽  
Zhixiang Hu ◽  
Lingfang Xia ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
Prognostic Indicator ◽  
Mapk Signaling ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Proliferation And Metastasis ◽  
Nuclear Ribonucleoprotein

AbstractNumerous studies suggest an important role for copy number alterations (CNAs) in cancer progression. However, CNAs of long intergenic noncoding RNAs (lincRNAs) in ovarian cancer (OC) and their potential functions have not been fully investigated. Here, based on analysis of The Cancer Genome Atlas (TCGA) database, we identified in this study an oncogenic lincRNA termed LINC00662 that exhibited a significant correlation between its CNA and its increased expression. LINC00662 overexpression is highly associated with malignant features in OC patients and is a prognostic indicator. LINC00662 significantly promotes OC cell proliferation and metastasis in vitro and in vivo. Mechanistically, LINC00662 is stabilized by heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1). Moreover, LINC00662 exerts oncogenic effects by interacting with glucose-regulated protein 78 (GRP78) and preventing its ubiquitination in OC cells, leading to activation of the oncogenic p38 MAPK signaling pathway. Taken together, our results define an oncogenic role for LINC00662 in OC progression mediated via GRP78/p38 signaling, with potential implications regarding therapeutic targets for OC.

scholarly journals An R Package for Divergence Analysis of Omics Data

2019 ◽  
Author(s):  
Wikum Dinalankara ◽  
Qian Ke ◽  
Donald Geman ◽  
Luigi Marchionni
Keyword(s):  
High Throughput Sequencing ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
High Dimensional ◽  
Omics Data ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Ternary Code ◽  
Cancer Genome Atlas ◽  
Level Analysis

AbstractGiven the ever-increasing amount of high-dimensional and complex omics data becoming available, it is increasingly important to discover simple but effective methods of analysis. Divergence analysis transforms each entry of a high-dimensional omics profile into a digitized (binary or ternary) code based on the deviation of the entry from a given baseline population. This is a novel framework that is significantly different from existing omics data analysis methods: it allows digitization of continuous omics data at the univariate or multivariate level, facilitates sample level analysis, and is applicable on many different omics platforms. The divergence package, available on the R platform through the Bioconductor repository collection, provides easy-to-use functions for carrying out this transformation. Here we demonstrate how to use the package with sample high throughput sequencing data from the Cancer Genome Atlas.

scholarly journals 90-Gene Expression Profiling for Tissue Origin Diagnosis of Cancer of Unknown Primary

2021 ◽  
Vol 11 ◽  
Author(s):  
Yi Zhang ◽  
Lei Xia ◽  
Dawei Ma ◽  
Jing Wu ◽  
Xinyu Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Cancer Of Unknown Primary ◽  
The Cancer Genome Atlas ◽  
Unknown Primary ◽  
Gene Expression Assay ◽  
Primary Location ◽  
Cancer Genome Atlas ◽  
Expression Characteristics

Cancer of unknown primary (CUP), in which metastatic diseases exist without an identifiable primary location, accounts for about 3–5% of all cancer diagnoses. Successful diagnosis and treatment of such patients are difficult. This study aimed to assess the expression characteristics of 90 genes as a method of identifying the primary site from CUP samples. We validated a 90-gene expression assay and explored its potential diagnostic utility in 44 patients at Jiangsu Cancer Hospital. For each specimen, the expression of 90 tumor-specific genes in malignant tumors was analyzed, and similarity scores were obtained. The types of malignant tumors predicted were compared with the reference diagnosis to calculate the accuracy. In addition, we verified the consistency of the expression profiles of the 90 genes in CUP secondary malignancies and metastatic malignancies in The Cancer Genome Atlas. We also reported a detailed description of the next-generation coding sequences for CUP patients. For each clinical medical specimen collected, the type of malignant tumor predicted and analyzed by the 90-gene expression assay was compared with its reference diagnosis, and the overall accuracy was 95.4%. In addition, the 90-gene expression profile generally accurately classified CUP into the cluster of its primary tumor. Sequencing of the exome transcriptome containing 556 high-frequency gene mutation oncogenes was not significantly related to the 90 genes analysis. Our results demonstrate that the expression characteristics of these 90 genes can be used as a powerful tool to accurately identify the primary sites of CUP. In the future, the inclusion of the 90-gene expression assay in pathological diagnosis will help oncologists use precise treatments, thereby improving the care and outcomes of CUP patients.

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