Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics. Issue 1 (11th November 2021)
- Record Type:
- Journal Article
- Title:
- Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics. Issue 1 (11th November 2021)
- Main Title:
- Prediction of the differences in tumor mutation burden between primary and metastatic lesions by radiogenomics
- Authors:
- Hoshino, Isamu
Yokota, Hajime
Iwatate, Yosuke
Mori, Yasukuni
Kuwayama, Naoki
Ishige, Fumitaka
Itami, Makiko
Uno, Takashi
Nakamura, Yuki
Tatsumi, Yasutoshi
Shimozato, Osamu
Nagase, Hiroki - Abstract:
- Abstract: Tumor mutational burden (TMB) is gaining attention as a biomarker for responses to immune checkpoint inhibitors in cancer patients. In this study, we evaluated the status of TMB in primary and liver metastatic lesions in patients with colorectal cancer (CRC). In addition, the status of TMB in primary and liver metastatic lesions was inferred by radiogenomics on the basis of computed tomography (CT) images. The study population included 24 CRC patients with liver metastases. DNA was extracted from primary and liver metastatic lesions obtained from the patients and TMB values were evaluated by next‐generation sequencing. The TMB value was considered high when it equaled to or exceeded 10/100 Mb. Radiogenomic analysis of TMB was performed by machine learning using CT images and the construction of prediction models. In 7 out of 24 patients (29.2%), the TMB status differed between the primary and liver metastatic lesions. Radiogenomic analysis was performed to predict whether TMB status was high or low. The maximum values for the area under the receiver operating characteristic curve were 0.732 and 0.812 for primary CRC and CRC with liver metastasis, respectively. The sensitivity, specificity, and accuracy of the constructed models for TMB status discordance were 0.857, 0.600, and 0.682, respectively. Our results suggested that accurate inference of the TMB status is possible using radiogenomics. Therefore, radiogenomics could facilitate the diagnosis, treatment, andAbstract: Tumor mutational burden (TMB) is gaining attention as a biomarker for responses to immune checkpoint inhibitors in cancer patients. In this study, we evaluated the status of TMB in primary and liver metastatic lesions in patients with colorectal cancer (CRC). In addition, the status of TMB in primary and liver metastatic lesions was inferred by radiogenomics on the basis of computed tomography (CT) images. The study population included 24 CRC patients with liver metastases. DNA was extracted from primary and liver metastatic lesions obtained from the patients and TMB values were evaluated by next‐generation sequencing. The TMB value was considered high when it equaled to or exceeded 10/100 Mb. Radiogenomic analysis of TMB was performed by machine learning using CT images and the construction of prediction models. In 7 out of 24 patients (29.2%), the TMB status differed between the primary and liver metastatic lesions. Radiogenomic analysis was performed to predict whether TMB status was high or low. The maximum values for the area under the receiver operating characteristic curve were 0.732 and 0.812 for primary CRC and CRC with liver metastasis, respectively. The sensitivity, specificity, and accuracy of the constructed models for TMB status discordance were 0.857, 0.600, and 0.682, respectively. Our results suggested that accurate inference of the TMB status is possible using radiogenomics. Therefore, radiogenomics could facilitate the diagnosis, treatment, and prognosis of patients with CRC in the clinical setting. Abstract : This study evaluated the status of tumor mutation burden (TMB) in primary and liver metastatic lesions in patients with colorectal cancer using radiogenomics. In 7 out of 24 patients (29.2%), the TMB status differed between the primary and liver metastatic lesion. Radiogenomic analysis was used to accurately predict whether TMB status was high or low. … (more)
- Is Part Of:
- Cancer science. Volume 113:Issue 1(2022)
- Journal:
- Cancer science
- Issue:
- Volume 113:Issue 1(2022)
- Issue Display:
- Volume 113, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 113
- Issue:
- 1
- Issue Sort Value:
- 2022-0113-0001-0000
- Page Start:
- 229
- Page End:
- 239
- Publication Date:
- 2021-11-11
- Subjects:
- colorectal cancer -- heterogeneity -- metastasis -- radiogenomics -- tumor mutational burden
Cancer -- Periodicals
Neoplasms -- Periodicals
Research -- Periodicals
Electronic journals
616.994005 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=1347-9032;screen=info;ECOIP ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1349-7006 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/cas.15173 ↗
- Languages:
- English
- ISSNs:
- 1347-9032
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3046.603000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 25870.xml