DOI: 10.5061/dryad.1vhhmgr1m
title: Genomic features of lung cancer patients in Indonesia’s National Cancer Center

description: 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&lt;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.
description: 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.
description: This README file was generated on 2024-01-13 by Arif Riswahyudi Hanafi ##
 General Information 1. Title of Dataset:Genomic features of lung cancer
 patients in Indonesia’s National Cancer Center 2. Author Information:
 Principal Investigator contact information: Name : Arif Riswahyudi Hanafi
 Institution : Dharmais Cancer Hospital, National Cancer Centre, Indonesia
 E-mail : 3. Date of data
 collection:2018-2022 4. Geographic location of data collection:Indonesia
 5. Funding sources that support the collection of data:No funding ## Data
 & File Overview 1. File list: A)
 final_data_genomic_features_lung_cancer_indonesia.xlsx B) README.md 2.
 Relationship between files, if important: None 3. Additional related data
 collected that was not included in the current data package: None 4. 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; &gt;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; &gt;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 1. Licenses/restrictions placed on the data: CC0 1.0 Universal
 (CC0 1.0) Public Domain 2. 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 3. Links to
 other publicly accessible locations of the data: None 4.
 Links/relationships to ancillary data sets: None 5. Was data derived from
 another source? No 6. Recommended citation for this dataset: Hanafi, Arif
 et al. (2024). Genomic features of lung cancer patients in Indonesia’s
 National Cancer Center [Dataset]. Dryad.