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This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

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On page 1 showing 1 ~ 7 papers out of 7 papers

Bioinformatic analysis revealing mitotic spindle assembly regulated NDC80 and MAD2L1 as prognostic biomarkers in non-small cell lung cancer development.

  • Rong Wei‎ et al.
  • BMC medical genomics‎
  • 2020‎

Lung cancer has been the leading cause of tumor related death, and 80% ~ 85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease.


Identification of SOFT syndrome caused by a pathogenic homozygous splicing variant of POC1A: a case report.

  • Guoqiang Li‎ et al.
  • BMC medical genomics‎
  • 2021‎

Pathogenic variants in POC1A led to SOFT syndrome and variant POC1A-related (vPOC1A) syndrome. SOFT syndrome is a rare primordial dwarfism condition characterized by short stature, onychodysplasia, facial dysmorphism and hypotrichosis.The main clinical differences between SOFT and vPOC1A syndrome include dyslipidemia with insulin resistance and acanthosis nigricans. To our knowledge, this is the first report of a SOFT syndrome patient diagnosed with a homozygous splicing variant, which could help to extend our understanding of the genotypic and phenotypic information of the disease.


Somatic mutations in benign breast disease tissues and association with breast cancer risk.

  • Stacey J Winham‎ et al.
  • BMC medical genomics‎
  • 2021‎

Benign breast disease (BBD) is a risk factor for breast cancer (BC); however, little is known about the genetic alterations present at the time of BBD diagnosis and how these relate to risk of incident BC.


Integrative genomic analysis identifies epigenetic marks that mediate genetic risk for epithelial ovarian cancer.

  • Devin C Koestler‎ et al.
  • BMC medical genomics‎
  • 2014‎

Both genetic and epigenetic factors influence the development and progression of epithelial ovarian cancer (EOC). However, there is an incomplete understanding of the interrelationship between these factors and the extent to which they interact to impact disease risk. In the present study, we aimed to gain insight into this relationship by identifying DNA methylation marks that are candidate mediators of ovarian cancer genetic risk.


Frequent POLE-driven hypermutation in ovarian endometrioid cancer revealed by mutational signatures in RNA sequencing.

  • Jaime I Davila‎ et al.
  • BMC medical genomics‎
  • 2021‎

DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT > TAT and TCG > TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC.


Methylation of leukocyte DNA and ovarian cancer: relationships with disease status and outcome.

  • Brooke L Fridley‎ et al.
  • BMC medical genomics‎
  • 2014‎

Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions.


Determining mutational burden and signature using RNA-seq from tumor-only samples.

  • Erik Jessen‎ et al.
  • BMC medical genomics‎
  • 2021‎

Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor.


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