Genomic features of lung cancer patients in Indonesia’s National Cancer Center
Data files
Jan 16, 2024 version files 36.65 KB
Abstract
Introduction: Advances in molecular biology bring advantages to lung cancer management. Moreover, high-throughput molecular tests are currently useful for revealing genetic variations among lung cancer patients. We investigated the genomics profile of the lung cancer patients at the National Cancer Centre of Indonesia.
Methods: A retrospective study enrolled 627 tissue biopsy samples using real time polymerase chain reaction (RT-PCR) and 80 circulating tumour DNA (ctDNA) liquid biopsy samples using next-generation sequencing (NGS) from lung cancer patients admitted to the Dharmais Cancer Hospital from January 2018 to December 2022. Data were obtained from medical records. Data statistically analysed with p<0.05 is considered significant.
Result: The EGFR test results revealed by RT-PCR were wild type (51.5%), single variant (38.8%), double variant (8.3%), and triple variant (1.4%), with 18.66% L85R, 18.22% Ex19del, and 11.08% L861Q variant. Liquid biopsy ctDNA using NGS showed only 2.5% EGFR wild type, 62.5% single variant and 35% co-variant, with EGFR/TP53 and EGFR/PIK3CA as the highest.
Conclusion: EGFR variants are the most found in our centre. Liquid biopsy with ctDNA using NGS examination could detect broad variants and co-variants that will influence the treatment planning.
README
This README file was generated on 2024-01-13 by Arif Riswahyudi Hanafi
General Information
Title of Dataset:Genomic features of lung cancer patients in Indonesia’s National Cancer Center
Author Information:
Principal Investigator contact information:
Name : Arif Riswahyudi Hanafi
Institution : Dharmais Cancer Hospital, National Cancer Centre, Indonesia
E-mail : arif.r.hanafi@gmail.comDate of data collection:2018-2022
Geographic location of data collection:Indonesia
Funding sources that support the collection of data:No funding
Data & File Overview
File list:
A) final_data_genomic_features_lung_cancer_indonesia.xlsx
B) README.mdRelationship between files, if important: None
Additional related data collected that was not included in the current data package: None
Are there multiple versions of the dataset? No
Data Specific information
for: final_data_genomic_features_lung_cancer_indonesia.xlsx
Sheet 1: PCR
1. Number of variables : 6
2. Number of rows : 628
3. Variable List:
* patient_code : code for all patients included in the study (coded randomly)
* age_range : patients'age categorize based on age range (0-39; 40-60; >60)
* sex : patient's sex (0= male; 1= female)
* diagnosis : patient's diagnosis when was included in the study (1= adenocarcinoma; 2= squamous cell carcinoma (SCC); 3= other non-small cell lung carcinoma (NSCLC); 4= small cell lung carcinoma (SCLC))
* smoking status: patient's smoking status (0= non-smoker; 1=smoker/passive smoker)
* result : genomic result based on the test (WT= wild-type; other results is written based on HGNC)
4. Missing data codes: None
5. Specialized formats or other abbreviations used: None
Sheet 2: NGS
1. Number of variables : 6
2. Number of rows : 81
3. Variable List:
* patient_code : code for all patients included in the study (coded randomly)
* age_range : patients'age categorize based on age range (0-39; 40-60; >60)
* sex : patient's sex (0= male; 1= female)
* diagnosis : patient's diagnosis when was included in the study (1= adenocarcinoma; 2= squamous cell carcinoma (SCC); 3= other non-small cell lung carcinoma (NSCLC); 4= small cell lung carcinoma (SCLC))
* smoking status: patient's smoking status (0= non-smoker; 1=smoker/passive smoker)
* result : genomic result based on the test (WT= wild-type; other genomic results is written based on HGNC)
4. Missing data codes: None
5. Specialized formats or other abbreviations used: None
Sharing/Access Information
Licenses/restrictions placed on the data: CC0 1.0 Universal (CC0 1.0) Public Domain
Links to publications that cite or use the data: Hanafi, AR et al. (2023). Genomic features of lung cancer patients in Indonesia’s National Cancer Center. BMC Pulmonary Medicine
Links to other publicly accessible locations of the data: None
Links/relationships to ancillary data sets: None
Was data derived from another source? No
Recommended citation for this dataset: Hanafi, Arif et al. (2024). Genomic features of lung cancer patients in Indonesia’s National Cancer Center [Dataset]. Dryad. https://doi.org/10.5061/dryad.1vhhmgr1m
Methods
The genomics data are secondary data from third-party company (a collaborative laboratory with Dharmais Cancer Hospital), while other data are extracted from medical records from the hospital database.