ID

45171

Descrizione

Principal Investigator: Zemin Zhang, PhD, Genentech Inc., South San Francisco, CA, USA MeSH: Lung Neoplasms,Carcinoma, Non-Small-Cell Lung https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000299 Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

collegamento

dbGaP study = phs000299

Keywords

  1. 22/08/22 22/08/22 - Simon Heim
  2. 12/10/22 12/10/22 - Adrian Schulz
Titolare del copyright

Zemin Zhang, PhD, Genentech Inc., South San Francisco, CA, USA

Caricato su

12 ottobre 2022

DOI

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Licenza

Creative Commons BY 4.0

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dbGaP phs000299 Genentech Lung Cancer Sequencing

The data table contains limited subject phenotype for subjects with non-small cell lung cancer. Included variables are sex, race, age, and smoking.

pht001553
Descrizione

pht001553

De-identified Subject ID
Descrizione

SUBJID

Tipo di dati

string

Alias
UMLS CUI [1,1]
C2346787
UMLS CUI [1,2]
C2348585
Disease onset age
Descrizione

Age

Tipo di dati

text

Alias
UMLS CUI [1,1]
C0206132
Gender of participant
Descrizione

Sex

Tipo di dati

text

Alias
UMLS CUI [1,1]
C0079399
Race
Descrizione

Race

Tipo di dati

string

Alias
UMLS CUI [1,1]
C0034510
Smoker
Descrizione

SMK

Tipo di dati

text

Alias
UMLS CUI [1,1]
C0543414

Similar models

The data table contains limited subject phenotype for subjects with non-small cell lung cancer. Included variables are sex, race, age, and smoking.

Name
genere
Description | Question | Decode (Coded Value)
Tipo di dati
Alias
Item Group
pht001553
SUBJID
Item
De-identified Subject ID
string
C2346787 (UMLS CUI [1,1])
C2348585 (UMLS CUI [1,2])
Age
Item
Disease onset age
text
C0206132 (UMLS CUI [1,1])
Item
Gender of participant
text
C0079399 (UMLS CUI [1,1])
Code List
Gender of participant
CL Item
Female (F)
CL Item
Male (M)
Race
Item
Race
string
C0034510 (UMLS CUI [1,1])
Item
Smoker
text
C0543414 (UMLS CUI [1,1])
Code List
Smoker
CL Item
No (N)
CL Item
Yes (Y)

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