7084 results for "canc*"

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• Integrated Exome and RNA Sequencing of Dedifferentiated Liposarcoma

  Multiomics analysis of rare cancers to identify genetic alterations related with pathogenesis and prognosis. To identification of genetics alterations of Dedifferentiated liposarcoma, DNAs and RNAs were extracted from dedifferentiated liposarcoma and paired non-cancer (normal) tissues. NGS libaraies were prepared by using Agilent SureSelect XT Human All Exon V5 + IncRNA kit for whole exome sequencing (WES) and TruSeq Stranded mRNA Prep kit or TruSeq RNA Access Library Prep kit (RNA seq). Sequencing was perfomred by Illumina HiSeq 2500.

  Study JGAS000177

• Comprehensive analyses of clinicopathological features and genomic mutations of combined hepatocellular-cholangiocarcinoma

  Combined hepatocellular and cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer. We performed whole exome sequencing to clarify the relationship between genetic mutations and clinicopathological features in cHCC-CCA.

  Study JGAS000599

• The RNA, ChIP and whole exome sequencing analysis of human colorectal cancer organoids and normal colon organoids treated with (+)-JQ1

  To reveal the mechanism of anti-tumor effect of (+)-JQ1, we performed RNA, ChIP and whole exome sequencing using human colorectal cancer and normal colon organoids.

  Study JGAS000378

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• Whole genome analysis of liver cancer by long-read sequencing

  Aberrant integration of Hepatitis B virus DNA promotes major restructuring of human hepatocellular carcinoma genome architecture

  Study JGAS000361

• Research on the identification of cancer stem cells for peidatric and adult malignancies.

  In recent years, "cancer stem cells" have been reported to exist in many cancers. Many reports have shown that they are the main cause of cancer recurrence. The aim of this study is to test whether cancer stem cells can be identified using patient samples. We will perform omics analysis of rare pediatric cancers by integrating genomics, transcriptomics, proteomics and metabolomics, including somatic and germline mutations, to deepen our understanding of the biological characteristics of the target disease. Based on the knowledge gained and clinical information from patients, we will conduct preclinical pharmacological studies using mouse models and in vitro models to investigate the therapeutic effects of novel therapeutic agents and novel therapeutic strategies such as cellular therapies.

  Study JGAS000623

• Long-read methylation analysis of breast cancer using the enzymatic base conversion and the nanopore sequencing

  Long-read methylation analysis by a nanopore sequnecer PromethION was performed using breast samples collected from breast cacner patients.

  Study JGAS000265

• Genetic analysis of non-small cell lung cancer patients and PDX tumor harboring driver gene alteration

  Genetic analysis of non-small cell lung cancer patients and PDX tumors with EGFR mutation, ALK fusion, ROS1 fusion, etc.

  Study JGAS000413

• Immunogenomic analysis of tumor infiltrating B cells in gastric cancer

  Despite the accumulating evidences of the significance of humoral cancer immunity, its molecular mechanisms have largely remained elusive. This study aimed at profiling the global picture of the humoral cancer immunity in view of immune repertoire characteristics of tumor-infiltrating B cells. In this study, we investigated B-cell repertoire (BCR) / immunoglobulin (Ig) sequencing of tumor infiltrating B cells in 102 clinical gastric cancers. First, total RNAs were extracted from frozen gastric cancer tissues and corresponding normal gastric mucosa; then, BCR/Ig repertoires of tumor-infiltrating B cells were amplified by target PCR using multiplex primer sets available from iRepertoire(R), inc. Subsequent next-generation sequencing data obtained by the Illumina platform were aligned onto human BCR/Ig repertoire sequence. This dataset contains the repertoire sequencing data of 102 gastric cancer cases analyzed in this study.

  Study JGAS000242

• Whole exome sequencing of uterine adenomyosis

  Uterine adenomyosis, defined by proliferation of the ectopic endometrial glands in myometrium, is a common benign uterine disorder that significantly impairs the quality of life of the women it affects. Adenomyosis lesions have chronic inflammatory reactions as well as cancer-like features such as invasive capacity into the normal myometrium. In contrast to endometriosis and leiomyoma, the genomic characterization of adenomyosis has yet to be reported. We conducted high-coverage whole exome sequencing analyses of freshly frozen adenomyosis samples, as well as co-occurring leiomyoma. Our WES analyses showed that adenomyosis is a clonal disorder with somatic mutations.

  Study JGAS000169