Profiling of conditionally reprogrammed cell lines for in vitro chemotherapy response prediction of pancreatic cancer

Lee, Jun Young; Kim, Eun Young; Lee, Jin Young; Park, Seung Joon; Hwang, Ho Kyoung; Park, Chan Hee; Jo, Se Young; Kang, Chang Moo; Hong, Seung Mo; Kang, Hyun Seung; Jo, Jung Hyun; Cho, In Rae; Chung, Moon Jae; Park, Jeong Youp; Song, Si Young; Han, Jung Min; Kim, Sang Woo; Bang, Seungmin

doi:10.1016/j.ebiom.2021.103218

Cited by 8 publications

(15 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies have reported an increase in VAF of somatic mutation and an enhanced ability to detect it upon enrichment of cancer cells in patient-derived models. 36,37 Furthermore, it is likely that, given tumor heterogeneity and the small samples size used, the patients enrolled here do not represent full coverage of the ICC spectrum. Thus, future investigations employing larger sample sizes are warranted.…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Lee

Han

Cho

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. However, there are no truly representative models of ICC subtypes for use in studying developmental differences, carcinogenesis, and personalized drug response. Here, we sought to develop ICC organoid models that reflect the phenotypic, molecular and genetic properties of the parent tumor, and performed integrative clustering of multiple genomic data—with subtype analysis—using these models. ICC organoids from 17 patients pathologically diagnosed with cholangiocarcinoma were prepared according to a previously established organoid culture protocol. ICC patients were subclassified into small-duct (SD) type and large-duct (LD) type according to histological characteristics and S100P, N-cadherin, and CD56 expression. ICC organoids were successfully established within one month and exhibited a morphology similar to that of their matching primary cancer. LD- and SD-type organoids exhibited histologic phenotypes and staining patterns characteristic of the corresponding ICC subtypes. ICC organoids showed high concordance of somatic mutations with primary tumors. Unsupervised principal component analysis clustering effectively separated each type of ICC. Differential gene expression revealed significant enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type ICC (P < 0.05). Gene set enrichment analysis further demonstrated that the cholangiocarcinoma class 2 signature, defined by Andersen et al., was significantly enriched in the LD-type (enrichment score = 2.19, P < 0.001). A protein-protein interaction network analysis identified ZNF217 as a significant hub protein (odds ratio = 4.96, P = 0.0105). We successfully performed prospective modeling of histological subtype specification using patient-derived ICC organoids. Moreover, gene expression profiling of ICC organoids enabled identification of type-specific targetable pathways.

show abstract

Section: Discussionmentioning

confidence: 99%

Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Lee

Han

Cho

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this study, we evaluated the efficacy of LDT target sequen-cing panel and CancerSCAN by detecting a sample with high mutation burden and comparing it with the WES results of surgically resected NSCLC (n = 100) samples. The CancerSCAN technique was applied at a clinical level to determine the genomic alterations of target therapy ( 26 - 33 ). In addition, CancerSCAN results showed that a definite number of mutations could be identified and processed as TMB for references.…”

Section: Discussionmentioning

confidence: 99%

Paired analysis of tumor mutation burden calculated by targeted deep sequencing panel and whole exome sequencing in non-small cell lung cancer

Park

Lee

et al. 2021

BMB Rep

View full text Add to dashboard Cite

Owing to rapid advancements in NGS (next generation sequen-cing), genomic alteration is now considered an essential pre-dictive biomarkers that impact the treatment decision in many cases of cancer. Among the various predictive biomarkers, tumor mutation burden (TMB) was identified by NGS and was con-sidered to be useful in predicting a clinical response in cancer cases treated by immunotherapy. In this study, we directly com-pared the lab-developed-test (LDT) results by target sequencing panel, K-MASTER panel v3.0 and whole-exome sequencing (WES) to evaluate the concordance of TMB. As an initial step, the reference materials (n = 3) with known TMB status were used as an exploratory test. To validate and evaluate TMB, we used one hundred samples that were acquired from surgically resected tissues of non-small cell lung cancer (NSCLC) patients. The TMB of each sample was tested by using both LDT and WES methods, which extracted the DNA from samples at the same time. In addition, we evaluated the impact of capture re-gion, which might lead to different values of TMB; the evalu-ation of capture region was based on the size of NGS and target sequencing panels. In this pilot study, TMB was evalu-ated by LDT and WES by using duplicated reference samples; the results of TMB showed high concordance rate (R 2 = 0.887). This was also reflected in clinical samples (n = 100), which showed R 2 of 0.71. The difference between the coding sequence ratio (3.49%) and the ratio of mutations (4.8%) indicated that the LDT panel identified a relatively higher number of mutations. It was feasible to calculate TMB with LDT panel, which can be useful in clinical practice. Furthermore, a customized approach must be developed for calculating TMB, which differs according to cancer types and specific clinical settings.

show abstract

“…Research by Lee et al (2019Lee et al ( , 2021 showed that CR technology can be used to establish pancreatic cancer cell lines through biopsies guided by endoscopic ultrasound. CRCs from pancreatic cancer tissues have the same genetic characteristics as those from the primary tumor and can be used for genomic research and drug sensitivity studies and can identify new diagnostic and therapeutic targets for pancreatic cancer (Lee et al, 2019(Lee et al, , 2021. The PDX model has become an important tool for translational research, but there are some limitations, including unsustainable in vitro growth.…”

Section: Application In Digestive Diseases Research Modeling Diseasesmentioning

confidence: 99%

“…However, tissue samples can only be obtained from many advanced cancer patients through fine-needle or core needle biopsy. Research by Lee et al (2019 , 2021) showed that CR technology can be used to establish pancreatic cancer cell lines through biopsies guided by endoscopic ultrasound. CRCs from pancreatic cancer tissues have the same genetic characteristics as those from the primary tumor and can be used for genomic research and drug sensitivity studies and can identify new diagnostic and therapeutic targets for pancreatic cancer ( Lee et al, 2019 , 2021 ).…”

Section: Application In Digestive Diseases Researchmentioning

confidence: 99%

Conditional Cell Reprogramming in Modeling Digestive System Diseases

Zhao

et al. 2021

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

Digestive diseases have become an important source of morbidity and mortality. The considerable financial and health burdens caused by digestive diseases confirm the importance of extensive research to better understand and treat these diseases. The development of reliable preclinical models is essential for understanding the pathogenesis of digestive diseases and developing treatment and prevention methods. However, traditional established cell lines and animal models still have many limitations in the study of the digestive system. Conditional reprogramming (CR) cell culture is a newly developed primary technology that uses irradiated Swiss-3T3-J2 mouse fibroblast cells and the Rho-associated kinase (ROCK) inhibitor Y-27632 to rapidly and efficiently generate many cells from diseased and normal tissues. CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and recapitulate the histological and genomic features of the original tissue. Moreover, after removing these conditions, the phenotype was completely reversible. Therefore, CR technology may represent an ideal model to study digestive system diseases, to test drug sensitivity, to perform gene profile analysis, and to undertake xenograft research and regenerative medicine. Indeed, together with organoid cultures, CR technology has been recognized as one of the key new technologies by NIH precision oncology and also used for NCI human cancer model initiatives (HCMI) program with ATCC. In this article, we review studies that use CR technology to conduct research on diseases of the digestive system.

show abstract

Profiling of conditionally reprogrammed cell lines for in vitro chemotherapy response prediction of pancreatic cancer

Cited by 8 publications

References 66 publications

Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Paired analysis of tumor mutation burden calculated by targeted deep sequencing panel and whole exome sequencing in non-small cell lung cancer

Conditional Cell Reprogramming in Modeling Digestive System Diseases

Contact Info

Product

Resources

About