New functional signatures for understanding melanoma biology from tumor cell lineage-specific analysis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE67638 | GEO | 2015/09/30
SECONDARY ACCESSION(S): PRJNA280579
REPOSITORIES: GEO
Similar Datasets
Project description:Molecular signatures specific to particular tumor types are required to design treatments for resistant tumors. However, it remains unclear whether tumors and corresponding cell lines used for drug development share such signatures. We developed similarity core analysis (SCA), a universal and unsupervised computational framework for extracting core molecular features common to tumors and cell lines. We applied SCA to mRNA/miRNA expression data from various sources, comparing melanoma cell lines and metastases. The signature obtained was associated with phenotypic characteristics in vitro, and the core genes CAPN3 and TRIM63 were implicated in melanoma cell migration/invasion. About 90% of the melanoma signature genes belong to an intrinsic network of transcription factors governing neural development (TFAP2A, DLX2, ALX1, MITF, PAX3, SOX10, LEF1, and GAS7) and miRNAs (211-5p, 221-3p, and 10a-5p). The SCA signature effectively discriminated between two subpopulations of melanoma patients differing in overall survival, and classified MEKi/BRAFi-resistant and -sensitive melanoma cell lines.
| S-EPMC5970542 | biostudies-literature
Project description:The identification of molecular signatures specific to distinct tumor types is urgently required for the design of therapies overcoming treatment resistance. It remains unclear whether such signatures are shared among tumors and corresponding cell lines, a key issue given the use of cell lines for drug development. We developed SCA (similarity core analysis) an unsupervised computational framework for extracting the core molecular features common to tumors and corresponding cell lines. We applied this algorithm to mRNA and miRNA expression data from various sources, comparing melanoma cell lines with melanoma metastases as an example. The signature obtained was associated with phenotypic characteristics in vitro and the core genes CAPN3 and TRIM63 were identified as new actors in melanoma cell migration and invasion. About 90% of the genes in the melanoma signature are potentially regulated by an intrinsic network of transcription factors known to regulate neural development (TFAP2A, DLX2, ALX1, MITF, PAX3, SOX10, LEF1 and GAS7) and three miRNAs (211-5p, 221-3p, 10a-5p). The SCA signature effectively discriminated between two subpopulations of melanoma patients with significant difference in overall survival. Furthermore, it classified MEKi and BRAFi resistant and sensitive melanoma cell lines. The SCA algorithm is potentially applicable to any tumor cell type.
2015-09-30 | GSE67636 | GEO
Project description:The identification of molecular signatures specific to distinct tumor types is urgently required for the design of therapies overcoming treatment resistance. It remains unclear whether such signatures are shared among tumors and corresponding cell lines, a key issue given the use of cell lines for drug development. We developed SCA (similarity core analysis) an unsupervised computational framework for extracting the core molecular features common to tumors and corresponding cell lines. We applied this algorithm to mRNA and miRNA expression data from various sources, comparing melanoma cell lines with melanoma metastases as an example. The signature obtained was associated with phenotypic characteristics in vitro and the core genes CAPN3 and TRIM63 were identified as new actors in melanoma cell migration and invasion. About 90% of the genes in the melanoma signature are potentially regulated by an intrinsic network of transcription factors known to regulate neural development (TFAP2A, DLX2, ALX1, MITF, PAX3, SOX10, LEF1 and GAS7) and three miRNAs (211-5p, 221-3p, 10a-5p). The SCA signature effectively discriminated between two subpopulations of melanoma patients with significant difference in overall survival. Furthermore, it classified MEKi and BRAFi resistant and sensitive melanoma cell lines. The SCA algorithm is potentially applicable to any tumor cell type.
2015-09-30 | GSE67635 | GEO
Project description:New functional signatures for understanding melanoma biology from tumor cell lineage-specific analysis
| PRJNA280579 | ENA
Project description:From 1976 to 2010, only 2 medications were approved for treating metastatic melanoma. Between 2011 and 2013, 4 agents were approved and other therapies have shown great promise in clinical trials. Fundamental discoveries, such as the identification of oncogenic mutations in most melanomas, the elucidation of the molecular signaling resulting from these mutations, and the revelation that several cell surface molecules serve as regulators of immune activation, have been instrumental in this progress. This article summarizes the molecular pathogenesis of melanoma, describes the current efforts to target oncogene-driven signaling, and presents the rationale for combining immune and molecular targeting.
| S-EPMC4116747 | biostudies-literature
Project description:Cellular membrane fluidity is a critical modulator of cell adhesion and migration, prompting us to define the systematic landscape of lineage-specific cellular fluidity throughout differentiation. Here, we have unveiled membrane fluidity landscapes in various lineages ranging from human pluripotency to differentiated progeny: (1) membrane rigidification precedes the exit from pluripotency, (2) membrane composition modulates activin signaling transmission, and (3) signatures are relatively germ layer specific presumably due to unique lipid compositions. By modulating variable lineage-specific fluidity, we developed a label-free "adhesion sorting (AdSort)" method with simple cultural manipulation, effectively eliminating pluripotent stem cells and purifying target population as a result of the over 1,150 of screened conditions combining compounds and matrices. These results underscore the important role of tunable membrane fluidity in influencing stem cell maintenance and differentiation that can be translated into lineage-specific cell purification strategy.
| S-EPMC6178887 | biostudies-other
Project description:A systemic analysis of the tumor-immune interactions within the heterogeneous tumor microenvironment is of particular importance for understanding the antitumor immune response. We used multiplexed immunofluorescence to elucidate cellular spatial interactions and T-cell infiltrations in metastatic melanoma tumor microenvironment. We developed two novel computational approaches that enable infiltration clustering and single cell analysis-cell aggregate algorithm and cell neighborhood analysis algorithm-to reveal and to compare the spatial distribution of various immune cells relative to tumor cell in sub-anatomic tumor microenvironment areas. We showed that the heterogeneous tumor human leukocyte antigen-1 expressions differently affect the magnitude of cytotoxic T-cell infiltration and the distributions of CD20+ B cells and CD4+FOXP3+ regulatory T cells within and outside of T-cell infiltrated tumor areas. In a cohort of 166 stage III melanoma samples, high tumor human leukocyte antigen-1 expression is required but not sufficient for high T-cell infiltration, with significantly improved overall survival. Our results demonstrate that tumor cells with heterogeneous properties are associated with differential but predictable distributions of immune cells within heterogeneous tumor microenvironment with various biological features and impacts on clinical outcomes. It establishes tools necessary for systematic analysis of the tumor microenvironment, allowing the elucidation of the "homogeneous patterns" within the heterogeneous tumor microenvironment.
| S-EPMC6550385 | biostudies-literature
Project description:The tumor microenvironment contributes important information in gene expression signatures but may be susceptible to sampling variance. Mesenchymal signatures in particular may be influenced by sampling of nonrepresentative regions with high stromal content. Appropriate pathology quality control is required to ensure reproducibility of gene expression signatures. Clin Cancer Res; 22(16); 3989-91. ©2016 AACRSee related article by Dunne et al., p. 4095.
| S-EPMC4987158 | biostudies-other
Project description:The management of locally-advanced rectal cancer involves a combination of chemotherapy, chemoradiation, and surgical resection to provide excellent local tumor control and overall survival. However, aspects of this multimodality approach are associated with significant morbidity and long-term sequelae. In addition, there is growing evidence that patients with a clinical complete response to chemotherapy and chemoradiation treatments may be safely offered initial non-operative management in a rigorous surveillance program. Weighed against the morbidity and significant sequelae of rectal resection, recognizing how to best optimize non-operative strategies without compromising oncologic outcomes is critical to our understanding and treatment of this disease.
| S-EPMC6252165 | biostudies-literature
Project description:Background and study aims
Bowel cancer is one of the commonest cancers worldwide. Early diagnosis is vital for improving outcomes but challenging as symptoms are not specific and are common to other non-cancer conditions. The current gold standard for diagnosis of bowel cancer is colonoscopy. However, colonoscopy is not without risk and services are under huge pressure due to increasing demand causing long waiting times for the patients who need it most. In collaboration with Swansea University, we have developed a blood test that works by shining a laser light onto a blood sample and measuring how much light is scattered off molecules in that sample. This creates a unique ‘fingerprint’ result that is specific to cancer. Our early results show that the test is very good at identifying patients with a high likelihood of having bowel cancer. We aim to understand the underlying causes of the differences between the blood sample fingerprints measured in patients with and without bowel cancer. By better understanding the origin of the signals, the accuracy of the test could be improved, leading to better cancer detection. The study will achieve this by tracking the patterns measured in the blood test from the blood samples back to the tumour. This will include investigating the role of the gut organisms that inhabit the bowel, the effect of the fasting state, lipids and bowel preparation on the results of the blood test.
Who can participate?
Adult participants with a diagnosis of bowel cancer, significant bowel disease requiring an operation, patients who undergo routine lipid, or procedures requiring bowel preparation and control participants
What does the study involve?
Participants will undergo blood tests and provide faecal samples. For patients having an operation as part of their care, a small portion of tissue that has been removed will be studied.
| 15066 | ecrin-mdr-crc