Dataset Information

Detection and genomic characterization of a mammary-like adenocarcinoma.

ABSTRACT: Whole-genome and transcriptome sequencing were performed to identify potential therapeutic strategies in the absence of viable treatment options for a patient initially diagnosed with vulvar adenocarcinoma. Genomic events were prioritized by comparison against variant distributions in the TCGA pan-cancer data set and complemented with detailed transcriptome sequencing and copy-number analysis. These findings were considered against published scientific literature in order to evaluate the functional effects of potentially relevant genomic events. Analysis of the transcriptome against a background of 27 TCGA cancer types led to reclassification of the tumor as a primary HER2+ mammary-like adenocarcinoma of the vulva. This revised diagnosis was subsequently confirmed by follow-up immunohistochemistry for a mammary-like adenocarcinoma. The patient was treated with chemotherapy and targeted therapies for HER2+ breast cancer. The detailed pathology and genomic findings of this case are presented herein.

SUBMITTER: Grewal JK

PROVIDER: S-EPMC5701302 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Detection and genomic characterization of a mammary-like adenocarcinoma.

Grewal Jasleen K JK Eirew Peter P Jones Martin M Chiu Kenrry K Tessier-Cloutier Basile B Karnezis Anthony N AN Karsan Aly A Mungall Andy A Zhou Chen C Yip Stephen S Tinker Anna V AV Laskin Janessa J Marra Marco M Jones Steven J M SJM

Cold Spring Harbor molecular case studies 20171121 6

Whole-genome and transcriptome sequencing were performed to identify potential therapeutic strategies in the absence of viable treatment options for a patient initially diagnosed with vulvar adenocarcinoma. Genomic events were prioritized by comparison against variant distributions in the TCGA pan-cancer data set and complemented with detailed transcriptome sequencing and copy-number analysis. These findings were considered against published scientific literature in order to evaluate the functio ...[more]

PMID: 28877932

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Project description:Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and is the leading cause of cancer death worldwide. Its progression is characterized by genomic instability. In turn, the level of genomic instability affects the prognosis and immune status of patients with LUAD. However, the impact of molecular features associated with genomic instability on the tumor microenvironment (TME) has not been well characterized. In addition, the effect of the genes related to genomic instability in LUAD on individualized treatment of LUAD is unknown. The RNA-Sequencing, somatic mutation, and clinical data of LUAD patients were downloaded from publicly available databases. A genetic signature associated with genomic instability (GSAGI) was constructed by univariate Cox regression, Lasso regression, and multivariate Cox regression analysis. Bioinformatics analysis investigated the differences in prognosis, immune characteristics, and the most appropriate treatment strategy among different subtypes of LUAD patients. CCK-8 and colony formation verified the various effects of Etoposide on different subtypes of LUAD cell lines. Cell-to-cell communication analysis was performed using the "CellChat" R package. The expression of the risk factors in the GSAGI was verified using real-time quantitative PCR (qRT-PCR) and Immunohistochemistry (IHC). We constructed and validated the GSAGI, consisting of five genes: ANLN, RHOV, KRT6A, SIGLEC6, and KLRG2. The GSAGI was an independent prognostic factor for LUAD patients. Patients in the high-risk group distinguished by the GSAGI are more suitable for chemotherapy. More immune cells are infiltrating the tumor microenvironment of patients in the low-risk group, especially B cells. Low-risk group patients are more suitable for receiving immunotherapy. The single-cell level analysis confirmed the influence of the GSAGI on TME and revealed the Mode of action between tumor cells and other types of cells. qRT-PCR and IHC showed increased ANLN, RHOV, and KRT6A expression in the LUAD cells and tumor tissues. This study confirms that genes related to genomic instability can affect the prognosis and immune status of LUAD patients. The GSAGI we identified has the potential to guide clinicians in predicting clinical outcomes, assessing immunological status, and even developing personalized treatment plans for LUAD patients.

Dataset Information

Detection and genomic characterization of a mammary-like adenocarcinoma.

Publications

Detection and genomic characterization of a mammary-like adenocarcinoma.

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