A Platform for Validating Colorectal Cancer Driver Genes Using Mouse Organoids

Takeda, Hisashi

doi:10.3389/fgene.2021.698771

Cited by 9 publications

(4 citation statements)

References 41 publications

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“…The genetic reconstitution model recapitulated the stepwise carcinogenesis process through the accumulation of multiple genetic alterations in the primary murine intestinal cells. Similar phenomena have been induced in human intestinal cells using CRISPR/Cas9-mediated gene editing 16 , 17 and other organ/tissue-derived organoids 18 , 19 , 20 .…”

Section: Introductionsupporting

confidence: 58%

The potential of organoids in toxicologic pathology: Histopathological and immunohistochemical evaluation of a mouse normal tissue-derived organoid-based carcinogenesis model

Ishigamori¹,

Naruse²,

Hirata

et al. 2022

J Toxicol Pathol

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Recently, we introduced an organoid-based chemical carcinogenesis model using mouse normal tissue-derived organoids. In the present review article, the histopathological and immunohistochemical characteristics of mouse normal tissue-derived organoids and tumors derived from these organoids after their in vitro treatment with genotoxic carcinogens and injection into nude mouse are reviewed. In organoids treated in vitro with genotoxic carcinogens, we confirmed macroscopic tumorigenicity and histopathological findings, including neoplastic characteristics, such as multilayered epithelia and/or invasion of epithelia into the surrounding interstitium. In contrast glandular/cystic structures with monolayered epithelia were clearly demarcated from the surrounding Matrigel/interstitium in the untreated control groups. In addition to macroscopic tumorigenicity, these microscopic epithelial changes, which are characteristic of the early stages of carcinogenesis, are included in the requirements for carcinogenicity-positive judgement of the organoid-based carcinogenesis model. Immunohistochemistry of cytokeratins (CKs), used to determine the origin of epithelia and distribution of extraductal invasive lesions, or oncogenic kinases, which reflect molecular activation in epithelia following chemical treatment, is helpful for accurate diagnosis and molecular evaluation in the early stages of carcinogenesis. This information improves our biological understanding of organoid-based chemical carcinogenesis models.

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Section: Introductionsupporting

confidence: 58%

The potential of organoids in toxicologic pathology: Histopathological and immunohistochemical evaluation of a mouse normal tissue-derived organoid-based carcinogenesis model

Ishigamori¹,

Naruse²,

Hirata

et al. 2022

J Toxicol Pathol

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“…Altering the expression of CDGs can increase cell proliferation and survival, leading to clonal expansion and tumor growth [ 10 ]. Different cancer types may be associated with both common and specific driver genes, and different genes may play different roles in various cancer types.…”

Section: Discussionmentioning

confidence: 99%

Establishing a cancer driver gene signature-based risk model for predicting the prognoses of gastric cancer patients

Zhou

Liu

2022

Aging

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Despite the high prevalence of gastric cancer (GC), molecular biomarkers that can reliably detect GC are yet to be discovered. The present study aimed to establish a robust gene signature based on cancer driver genes (CDGs) that can predict GC prognosis. Transcriptional profiles and clinical data from GC patients were analyzed using univariate Cox regression analysis and the least absolute shrinkage and selection (LASSO)-penalized Cox regression analysis to select optimal prognosis-related genes for modeling. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analyses were done to assess the predictive power of this gene signature. A nomogram model for prediction of survival of GC patients was established using the CDG signature and clinical information, and a seven-CDG signature was identified. Risk scores were calculated using this signature, and patients were subsequently divided into high-and low-risk groups; high-risk patients in the training and validation datasets had poorer prognoses than low-risk patients. Cox regression analysis revealed that the CDG signature is an independent prognostic factor for GC. The signature and other clinical features were used to construct a nomogram for predicting overall GC patient survival. Calibration and decision curve analysis showed that the nomogram accurately predicted survival, highlighting its clinical utility. Thus, we established a novel CDG signature and nomogram for predicting GC prognosis, which may facilitate personalized treatment of GC.

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“…The early onset of COVID-19 requires all four mutations of the D614G group and the later Delta strain has 31 mutations accrued in three batches (Ruan, Hou, et al 2022; Ruan, Wen, et al 2022). While cancer research has often proceeded one mutation at a time, each of the mutations has been shown to be insufficient for tumorigenesis until many (Ortmann et al 2015; Takeda 2021; Hodis et al 2022) are co-introduced.…”

Section: Introductionmentioning

confidence: 99%

“…mutations has been shown to be insufficient for tumorigenesis until many (Ortmann et al 2015;Takeda 2021;Hodis et al 2022) are co-introduced. We now aim for the identification of all (or at least most) of the driver mutations in each patient.…”

mentioning

confidence: 99%

The theory of massively repeated evolution and full identifications of Cancer Driving Nucleotides (CDNs)

Zhang,

Deng,

Liufu

et al. 2024

Preprint

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Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are Cancer Driving Nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample sizen= 300 - 1000), point mutations may recur iniout ofnpatients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (i*) driven solely by neutral evolution. Since no neutral mutation can reachi* = 3, all mutations recurring ati≥ 3 are CDNs. The theory shows the feasibility of identifying almost all CDNs ifnincreases to 100,000 for each cancer type. At present, only < 10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.

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A Platform for Validating Colorectal Cancer Driver Genes Using Mouse Organoids

Cited by 9 publications

References 41 publications

The potential of organoids in toxicologic pathology: Histopathological and immunohistochemical evaluation of a mouse normal tissue-derived organoid-based carcinogenesis model

The potential of organoids in toxicologic pathology: Histopathological and immunohistochemical evaluation of a mouse normal tissue-derived organoid-based carcinogenesis model

Establishing a cancer driver gene signature-based risk model for predicting the prognoses of gastric cancer patients

The theory of massively repeated evolution and full identifications of Cancer Driving Nucleotides (CDNs)

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