scholarly journals MS.liverK: an R package for transcriptome-based computation of molecular subtypes and functional signatures in liver cancer

2019 ◽  
Author(s):  
Florent Petitprez ◽  
Léa Meunier ◽  
Eric Letouzé ◽  
Yujin Hoshida ◽  
Augusto Villanueva ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Molecular Subtypes ◽  
R Package ◽  
Molecular Characteristics ◽  
Molecular Heterogeneity ◽  
Biological Functions ◽  
Tumor Subtypes ◽  
Molecular Scores ◽  
Tumor Gene Expression ◽  
Tumor Gene

AbstractSummaryLiver cancer is a highly heterogeneous disease in terms of etiology, tissue and cellular morphology, tumor molecular characteristics, microenvironment composition and prognosis. Several studies, based on tumor gene-expression profiling (GEP) data, have dissected the molecular heterogeneity of liver cancer. They resulted in various tools, either delineating homogeneous tumor subtypes or calculating molecular scores of prognostic or biological functions. Here, we present MS.liverK, an easy-to-use R package providing a comprehensive implementation of these tools, for research use.Availability and implementationThe MS.liverK R package is available from GitHub (https://github.com/cit-bioinfo/MS.liverK).

Renal Cell and Urothelial Carcinoma: Biomarkers for New Treatments

2020 ◽  
pp. e197-e206
Author(s):  
Andrew L. Schmidt ◽  
Arlene Siefker-Radtke ◽  
David McConkey ◽  
Bradley McGregor
Keyword(s):  
Renal Cell ◽  
Large Scale ◽  
Kinase Inhibitor ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Immune Checkpoint Blockade ◽  
Molecular Characteristics ◽  
Molecular Heterogeneity ◽  
Prognostic Information ◽  
Similar Work

Therapies for genitourinary malignancies have evolved considerably in the past 5 years. Combination treatment targeting biologically relevant immune and angiogenic pathways is improving patient survival in metastatic renal cell carcinoma (RCC), whereas immune checkpoint blockade (ICB), novel targeted therapy, and antibody drug conjugates have changed the landscape of urothelial cancer (UC) treatment. A daily challenge for clinicians is identifying patients who derive a preferential benefit from the available therapeutic options. The completion of large-scale genomics projects has yielded comprehensive descriptions of the molecular heterogeneity present in RCC and UC, although clinical applications of these data continue to evolve. Major molecular subtypes of RCC align well with histology subtype, and although some molecular characteristics appear to carry prognostic information, biomarkers predicting benefit from tyrosine kinase inhibitor (TKI) or immunotherapy are generally lacking. Unexpectedly, similar work has demonstrated that UC can be grouped into “molecular subtypes” that share properties with those found in breast cancer and other solid tumors. Furthermore, this molecular subtype classification is prognostic and potentially predictive of differential benefit from conventional and targeted therapies. This article provides an update on the current state of molecular biomarker development and potential clinical utility in RCC and UC.

scholarly journals Molecular Tumor Subtypes of HPV-Positive Head and Neck Cancers: Biological Characteristics and Implications for Clinical Outcomes

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2721
Author(s):  
Tingting Qin ◽  
Shiting Li ◽  
Leanne E. Henry ◽  
Siyu Liu ◽  
Maureen A. Sartor
Keyword(s):  
Head And Neck ◽  
Stromal Cells ◽  
Clinical Characteristics ◽  
Molecular Subtypes ◽  
Squamous Cell Carcinomas ◽  
Head And Neck Cancers ◽  
Molecular Signatures ◽  
Tumor Subtypes ◽  
Mesenchymal Differentiation ◽  
High Incidence

Until recently, research on the molecular signatures of Human papillomavirus (HPV)-associated head and neck cancers mainly focused on their differences with respect to HPV-negative head and neck squamous cell carcinomas (HNSCCs). However, given the continuing high incidence level of HPV-related HNSCC, the time is ripe to characterize the heterogeneity that exists within these cancers. Here, we review research thus far on HPV-positive HNSCC molecular subtypes, and their relationship with clinical characteristics and HPV integration into the host genome. Different omics data including host transcriptomics and epigenomics, as well as HPV characteristics, can provide complementary viewpoints. Keratinization, mesenchymal differentiation, immune signatures, stromal cells and oxidoreductive processes all play important roles.

scholarly journals Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Peter W. Eide ◽  
Seyed H. Moosavi ◽  
Ina A. Eilertsen ◽  
Tuva H. Brunsell ◽  
Jonas Langerud ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Principal Components ◽  
Prognostic Value ◽  
Tumor Heterogeneity ◽  
Molecular Subtypes ◽  
R Package ◽  
Data Set ◽  
Primary Tumors ◽  
External Data

AbstractGene expression-based subtypes of colorectal cancer have clinical relevance, but the representativeness of primary tumors and the consensus molecular subtypes (CMS) for metastatic cancers is not well known. We investigated the metastatic heterogeneity of CMS. The best approach to subtype translation was delineated by comparisons of transcriptomic profiles from 317 primary tumors and 295 liver metastases, including multi-metastatic samples from 45 patients and 14 primary-metastasis sets. Associations were validated in an external data set (n = 618). Projection of metastases onto principal components of primary tumors showed that metastases were depleted of CMS1-immune/CMS3-metabolic signals, enriched for CMS4-mesenchymal/stromal signals, and heavily influenced by the microenvironment. The tailored CMS classifier (available in an updated version of the R package CMScaller) therefore implemented an approach to regress out the liver tissue background. The majority of classified metastases were either CMS2 or CMS4. Nonetheless, subtype switching and inter-metastatic CMS heterogeneity were frequent and increased with sampling intensity. Poor-prognostic value of CMS1/3 metastases was consistent in the context of intra-patient tumor heterogeneity.

Heterogeneity Within Molecular Subtypes of Breast Cancer

2021 ◽  
Author(s):  
Kevin M. Turner ◽  
Syn Kok Yeo ◽  
Tammy M Holm ◽  
Elizabeth Shaughnessy ◽  
Jun-Lin Guan
Keyword(s):  
Breast Cancer ◽  
Molecular Subtypes ◽  
Tumor Biology ◽  
Treatment Resistance ◽  
Intratumoral Heterogeneity ◽  
Molecular Heterogeneity ◽  
Improve Treatment ◽  
Therapeutic Decisions ◽  
Single Tumor

Breast cancer is the quintessential example of how molecular characterization of tumor biology guides therapeutic decisions. From the discovery of the estrogen receptor to current clinical molecular profiles to evolving single cell analytics, the characterization and compartmentalization of breast cancer into divergent subtypes is clear. However, competing with this divergent model of breast cancer is the recognition of intratumoral heterogeneity, which acknowledges the possibility that multiple different subtypes exist within a single tumor. Intratumoral heterogeneity is driven by both intrinsic effects of the tumor cells themselves as well as extrinsic effects from the surrounding microenvironment. There is emerging evidence that these intratumoral molecular subtypes are not static; rather, plasticity between divergent subtypes is possible. Inter-conversion between seemingly different subtypes within a tumor drives tumor progression, metastases, and treatment resistance. Therapeutic strategies must therefore contend with changing phenotypes in an individual patient's tumor. Identifying targetable drivers of molecular heterogeneity may improve treatment durability and disease progression.

Dual Hypergraph Regularized PCA for Biclustering of Tumor Gene Expression Data

2019 ◽  
Vol 31 (12) ◽  
pp. 2292-2303 ◽  
Author(s):  
Xuesong Wang ◽  
Jian Liu ◽  
Yuhu Cheng ◽  
Aiping Liu ◽  
Enhong Chen
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Expression Data ◽  
Tumor Gene Expression ◽  
Tumor Gene

scholarly journals Single cell transcriptomic analysis reveals cellular diversity of murine esophageal epithelium and age-associated mitochondrial dysfunction

2021 ◽  
Author(s):  
Mohammad Faujul Kabir ◽  
Adam Karami ◽  
Ricardo Cruz-Acuna ◽  
Alena Klochkova ◽  
Reshu Saxena ◽  
...  
Keyword(s):  
Mitochondrial Dysfunction ◽  
Single Cell ◽  
Molecular Characteristics ◽  
Molecular Heterogeneity ◽  
Basal Cells ◽  
Esophageal Epithelium ◽  
Squamous Differentiation ◽  
Cell Clusters ◽  
Tissue Aging ◽  
The Impact

ABSTRACTStratified squamous epithelium of the esophagus is comprised of basal keratinocytes that execute a terminal differentiation program in overlying suprabasal and superficial cell layers. Although morphologic progression coupled with expression of specific molecular markers has been characterized along the esophageal epithelial differentiation gradient, the molecular heterogeneity within the cell types along this trajectory has yet to be classified at the level of single cell resolution. To explore the molecular characteristics of esophageal keratinocytes along the squamous differentiation continuum, we performed single cell RNA-Sequencing transcriptomic profiling of 7,972 cells from murine esophageal epithelial sheets. We identified 8 distinct cell clusters in esophageal epithelium, unveiling an unexpected level of diversity, particularly among basal cells. We further mapped the cellular pathways and lineage trajectories within basal, suprabasal, and superficial clusters as well as within the heterogeneous basal cell populations, providing a comprehensive molecular view of esophageal epithelial cells in the context of squamous differentiation. Finally, we explored the impact of tissue aging upon esophageal epithelial cell clusters and demonstrated that mitochondrial dysfunction is a feature of aging in normal esophageal epithelium. These studies provide an unparalleled molecular perspective on murine esophageal keratinocytes that will serve as a valuable resource for dissecting cell type-specific roles in esophageal biology under conditions of homeostasis, aging, and tissue pathology.

scholarly journals Clinicopathological significance and prognostic value of Wilms' tumor gene expression in colorectal cancer

2015 ◽  
Vol 15 (6) ◽  
pp. 789-797 ◽  
Author(s):  
Yukinaga Miyata ◽  
Kenichi Kumagai ◽  
Tomoko Nagaoka ◽  
Kazutaka Kitaura ◽  
Goro Kaneda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Prognostic Value ◽  
Wilms Tumor ◽  
Wilms Tumor Gene ◽  
Clinicopathological Significance ◽  
Tumor Gene Expression ◽  
Tumor Gene

scholarly journals Alpha-Fetoprotein and Hepatocellular Carcinoma Immunity

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoping Wang ◽  
Qiaoxia Wang
Keyword(s):  
Liver Cancer ◽  
Cancer Immunotherapy ◽  
Antitumor Immunity ◽  
Immune Cell ◽  
Diagnostic Marker ◽  
Peptide Vaccine ◽  
Alpha Fetoprotein ◽  
Cell Vaccine ◽  
Biological Functions

Hepatocarcinoma is one of the most prevalent gastroenterological cancers in the world with less effective therapy. As an oncofetal antigen and diagnostic marker for liver cancer, alpha-fetoprotein (AFP) possesses a variety of biological functions. Except for its diagnosis in liver cancer, AFP has become a target for liver cancer immunotherapy. Although the immunogenicity of AFP is weak and it could induce the immune escapes through inhibiting the function of dendritic cells, natural killer cells, and T lymphocytes, AFP has attracted more attention in liver cancer immunotherapy. By in vitro modification, the immunogenicity and immune response of AFP could be enhanced. AFP-modified immune cell vaccine or peptide vaccine has displayed the specific antitumor immunity against AFP-positive tumor cells and laid a better foundation for the immunotherapy of liver cancer.

scholarly journals Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Julien Racle ◽  
Kaat de Jonge ◽  
Petra Baumgaertner ◽  
Daniel E Speiser ◽  
David Gfeller
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cell Types ◽  
Response To Therapy ◽  
Expression Data ◽  
Cell Type ◽  
Tumor Gene Expression ◽  
Tumor Gene

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

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