Lung CancerNSCLCNCT05541744
The Use of Molecular Radiogenomics in Non-small Cell Lung Cancer
An observational study of Lung Cancer, run by Buddhist Tzu Chi General Hospital at 1 site in Taiwan.
Trial summary
Lung cancer is currently the leading cause of cancer-related mortality worldwide, and the dominant histopathology is non-small cell lung cancer (NSCLC). Although many new targeted and immunomodulation therapies have emerged, not all patients are responsive to novel therapeutics. Read more about this study
- Who is it for?
- Ages 20 years and older
- Conditions the study is for
- Lung Cancer
- How many people
- 120 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Aug 2023to 31 Jul 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with non-small cell lung cancer, and able to be analyzed with radiomics of FDG PET and primary tumor whole exome sequencing.
Who may be able to join
- Age at least 20-years
- Pathological proven non-small cell lung cancer and received complete staging work-up
- Pre-treatment pathological specimen of the primary tumor
Who cannot join
- Coexistence of non-aerodigestive tract cancer.
- Unable to comply to FDG PET/CT exam or poor image quality
- Unable to determine the primary tumor
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
Hualien Tzu Chi Hospital
Hualien City
Yu-Hung Chen, 0963281152, jedimasterchen@hotmail.com
About this study
Lung cancer is currently the leading cause of cancer-related mortality worldwide, and the dominant histopathology is non-small cell lung cancer (NSCLC). Although many new targeted and immunomodulation therapies have emerged, not all patients are responsive to novel therapeutics. A more reliable and accurate risk stratification model to predict the treatment response and survival outcomes are still lacking. The 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) derived radiomics can be used to interrogate tumor biologies such as glycolytic activity and heterogeneity. It can, therefore, be used to predict treatment response and survival outcomes. Cancer genomics derived from gene sequencing can evaluate cancer's genetic alterations. It can be used to feature the genotype of the tumor. However, both tools have drawbacks; combining these two modalities may enable a more robust predictive model for more precise clinical decisions. During the investigator's former study project, the investigators published four Science Citation Index journal papers using the investigators' research results, which found that 18F-FDG PET radiomics can independently predict regional lymph node metastasis in NSCLC and cancer survival by stage. The preliminary findings of the investigator's former research project also disclosed an association between 18F-FDG PET-derived molecular radiomics with genomic heterogeneity and mutation of specific glucose metabolic genes. This time, the investigators plan to include deep radiomics in addition to traditional handcrafted radiomics. The investigators aim to investigate the radiogenomic patterns in different driver gene mutation statuses and clinical scenarios. Finally, the investigators seek to use radiogenomics as a prognostic stratification tool in patients with NSCLC.
Read the detailed description
This is a prospective study and The investigators use routine pathological specimens for whole exome sequencing (WES) and immunohistochemical stains.
Pathological examinations include PD-L1, EGFR status, ALK, and ROS-1.
WES: Total DNA were extracted from paraffin-embedded tumor specimens with the QIAamp DNA FFPE Tissue Kit (QIAGEN GmbH, Hilden, Germany). The coding size was 45 Mb. For DNA whole exome sequence, briefly, tumors were sonicated by Covaris M220 sonicator (Life Technologies Europe, Gent, Belgium) and then ligated to adaptor for further amplification (Illumina® TruSeq Exome Library Prep, USA). After library preparation, all samples were sequenced using the NextSeq500 system according to the manufacturer's instructions (Illumina, San Diego, USA). The investigators run sequencing with 12 samples simultaneously (a total of 100 Gb). The sequence length was 150 bp with a paired-end (2*150bp). The average depth of sequencing is 100X. After sequencing performance, quality of reads file (fastq) was assessed by FastQC and then mapped using human Hg19 as the reference. Bam files were used as input for the Varscan algorithm to identify germline and somatic mutations. Variants annotated and filtered are manually checked using IGV (Integrative Genomics Viewer), then confirmed by Sanger sequence. The investigators analyze the clinical related gene alterations including actionable gene mutations (EGFR, BRAF, KRAS, and MET.) Also, clinically important genes including the mutation status of TP53 and SDH genes are analyzed. The investigators also analyzed the mutation status of glucose metabolic cluster genes.
TMB (tumor mutation burden) per megabase: The total number of mutations counted is divided by the size of the coding region of the targeted territory.
MATH (mutant-allele tumor heterogeneity): The investigators first obtain the MAF (the fraction of DNA that shows the mutated allele at a gene locus) of each tumor specimen. The MAF distribution will be used to calculate the median (center of distribution) and the MD (median deviation) of MAFs in a tumor. The MD is determined by obtaining the absolute differences of all MAFs from the median MAF. Then the median of the absolute differences is multiplied by a factor of 1.4826 to obtain the MD. The MATH is calculated as the percentage ratio of the MD to the median: MATH = (MD/median)×100 [45].
Shannon diversity index (Shannon entropy) [50]: The MAF distribution (histogram) of each patient's tumor specimen was obtained with different bin sizes (total bin size = S). The Shannon diversity index is then calculated according to the distribution of probabilities of each MAF bin.
The image features of FDG PET the investigators extracted as follows, <Handcrafted radiomics> The traditional image parameters include SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary tumor. The traditional FDG PET parameters are calculated using commercialized software (PBAS, PMOD 4.0). Radiomics (texture analysis) will be calculated only for pre-treatment FDG PET. The matrices of radiomic analysis include histogram analysis, Gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), gray-level size zone matrix (GLSZM), neighborhood gray-tone difference matrix (NGTDM), and shape features.
<Deep radiomics> The investigators put the segmented volume into convolutional neural network (CNN) for analysis. The investigators will use supervised CNN to analyze the relationship between imaging with other outcomes.
- Conditions
- Lung Cancer
- Keywords
- non-small cell lung cancer, Radiogenomics, 18F-FDG PET, whole exome sequencing, molecular imaging
- Medical subject headings
- Lung Neoplasms, Carcinoma, Non-Small-Cell Lung
What is being measured
The primary outcome is the main question the study is designed to answer.
Prognosis
Study the association of radiogenomics with the treatment response and survival
Measured: three years
Secondary outcomes (1)
Correlation of radiogenomics
Study the correlation of radiomics and genomics and pathological features
Measured: one year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Sep 2022
- Study start1 Aug 2023
- Primary completion31 Jul 2026 (estimated)
- Study completion31 Jul 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Buddhist Tzu Chi General Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05541744
- Sponsor's protocol ID
- IRB111-168-A
- Acronym
- NSCLC
- Status last verified
- Sep 2025
- First submitted
- 13 Sep 2022
- Last updated
- 19 Sep 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 19 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Use of Molecular Radiogenomics in Non-small Cell Lung Cancer
- ClinicalTrials.gov ID
- NCT05541744
- Acronym / sponsor ID
- NSCLC / IRB111-168-A
- Conditions
- Lung Cancer
- Keywords
- non-small cell lung cancer, Radiogenomics, 18F-FDG PET, whole exome sequencing, molecular imaging
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- Buddhist Tzu Chi General HospitalUniversity, hospital or other
- Study start
- 1 Aug 2023 (actual)
- Primary completion
- 31 Jul 2026 (estimated)
- Study completion
- 31 Jul 2028 (estimated)
- First posted
- 15 Sep 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Lung cancer is currently the leading cause of cancer-related mortality worldwide, and the dominant histopathology is non-small cell lung cancer (NSCLC). Although many new targeted and immunomodulation therapies have emerged, not all patients are responsive to novel therapeutics. A more reliable and accurate risk stratification model to predict the treatment response and survival outcomes are still lacking. The 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) derived radiomics can be used to interrogate tumor biologies such as glycolytic activity and heterogeneity. It can, therefore, be used to predict treatment response and survival outcomes. Cancer genomics derived from gene sequencing can evaluate cancer's genetic alterations. It can be used to feature the genotype of the tumor. However, both tools have drawbacks; combining these two modalities may enable a more robust predictive model for more precise clinical decisions. During the investigator's former study project, the investigators published four Science Citation Index journal papers using the investigators' research results, which found that 18F-FDG PET radiomics can independently predict regional lymph node metastasis in NSCLC and cancer survival by stage. The preliminary findings of the investigator's former research project also disclosed an association between 18F-FDG PET-derived molecular radiomics with genomic heterogeneity and mutation of specific glucose metabolic genes. This time, the investigators plan to include deep radiomics in addition to traditional handcrafted radiomics. The investigators aim to investigate the radiogenomic patterns in different driver gene mutation statuses and clinical scenarios. Finally, the investigators seek to use radiogenomics as a prognostic stratification tool in patients with NSCLC.
Detailed description
This is a prospective study and The investigators use routine pathological specimens for whole exome sequencing (WES) and immunohistochemical stains.
Pathological examinations include PD-L1, EGFR status, ALK, and ROS-1.
WES: Total DNA were extracted from paraffin-embedded tumor specimens with the QIAamp DNA FFPE Tissue Kit (QIAGEN GmbH, Hilden, Germany). The coding size was 45 Mb. For DNA whole exome sequence, briefly, tumors were sonicated by Covaris M220 sonicator (Life Technologies Europe, Gent, Belgium) and then ligated to adaptor for further amplification (Illumina® TruSeq Exome Library Prep, USA). After library preparation, all samples were sequenced using the NextSeq500 system according to the manufacturer's instructions (Illumina, San Diego, USA). The investigators run sequencing with 12 samples simultaneously (a total of 100 Gb). The sequence length was 150 bp with a paired-end (2*150bp). The average depth of sequencing is 100X. After sequencing performance, quality of reads file (fastq) was assessed by FastQC and then mapped using human Hg19 as the reference. Bam files were used as input for the Varscan algorithm to identify germline and somatic mutations. Variants annotated and filtered are manually checked using IGV (Integrative Genomics Viewer), then confirmed by Sanger sequence. The investigators analyze the clinical related gene alterations including actionable gene mutations (EGFR, BRAF, KRAS, and MET.) Also, clinically important genes including the mutation status of TP53 and SDH genes are analyzed. The investigators also analyzed the mutation status of glucose metabolic cluster genes.
TMB (tumor mutation burden) per megabase: The total number of mutations counted is divided by the size of the coding region of the targeted territory.
MATH (mutant-allele tumor heterogeneity): The investigators first obtain the MAF (the fraction of DNA that shows the mutated allele at a gene locus) of each tumor specimen. The MAF distribution will be used to calculate the median (center of distribution) and the MD (median deviation) of MAFs in a tumor. The MD is determined by obtaining the absolute differences of all MAFs from the median MAF. Then the median of the absolute differences is multiplied by a factor of 1.4826 to obtain the MD. The MATH is calculated as the percentage ratio of the MD to the median: MATH = (MD/median)×100 [45].
Shannon diversity index (Shannon entropy) [50]: The MAF distribution (histogram) of each patient's tumor specimen was obtained with different bin sizes (total bin size = S). The Shannon diversity index is then calculated according to the distribution of probabilities of each MAF bin.
The image features of FDG PET the investigators extracted as follows, <Handcrafted radiomics> The traditional image parameters include SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary tumor. The traditional FDG PET parameters are calculated using commercialized software (PBAS, PMOD 4.0). Radiomics (texture analysis) will be calculated only for pre-treatment FDG PET. The matrices of radiomic analysis include histogram analysis, Gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), gray-level size zone matrix (GLSZM), neighborhood gray-tone difference matrix (NGTDM), and shape features.
<Deep radiomics> The investigators put the segmented volume into convolutional neural network (CNN) for analysis. The investigators will use supervised CNN to analyze the relationship between imaging with other outcomes.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with non-small cell lung cancer, and able to be analyzed with radiomics of FDG PET and primary tumor whole exome sequencing.
Key inclusion criteria (3 listed)
- Age at least 20-years
- Pathological proven non-small cell lung cancer and received complete staging work-up
- Pre-treatment pathological specimen of the primary tumor
Key exclusion criteria (3 listed)
- Coexistence of non-aerodigestive tract cancer.
- Unable to comply to FDG PET/CT exam or poor image quality
- Unable to determine the primary tumor
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Prognosis
Time frame: three years
Study the association of radiogenomics with the treatment response and survival
1 secondary outcome
Correlation of radiogenomics
Time frame: one year
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Sep 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer, run by Buddhist Tzu Chi General Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 19 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yu-Hung Chen, M.D. (886-3-8561825 ext. 12024, jedimasterchen@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Prognosis (time frame: three years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Sep 2025.