Dataset Information

Integration of human inspection and artificial intelligence-based morphological typing of patient-derived organoids reveals interpatient heterogeneity of colorectal cancer.

ABSTRACT: Colorectal cancer (CRC) is a heterogenous disease, and patients have differences in therapeutic response. However, the mechanisms underlying interpatient heterogeneity in the response to chemotherapeutic agents remain to be elucidated, and molecular tumor characteristics are required to select patients for specific therapies. Patient-derived organoids (PDOs) established from CRCs recapitulate various biological characteristics of tumor tissues, including cellular heterogeneity and the response to chemotherapy. Patient-derived organoids established from CRCs show various morphologies, but there are no criteria for defining these morphologies, which hampers the analysis of their biological significance. Here, we developed an artificial intelligence (AI)-based classifier to categorize PDOs based on microscopic images according to their similarity in appearance and classified tubular adenocarcinoma-derived PDOs into six types. Transcriptome analysis identified differential expression of genes related to cell adhesion in some of the morphological types. Genes involved in ribosome biogenesis were also differentially expressed and were most highly expressed in morphological types showing CRC stem cell properties. We identified an RNA polymerase I inhibitor, CX-5641, to be an upstream regulator of these type-specific gene sets. Notably, PDO types with increased expression of genes involved in ribosome biogenesis were resistant to CX-5461 treatment. Taken together, these results uncover the biological significance of the morphology of PDOs and provide novel indicators by which to categorize CRCs. Therefore, the AI-based classifier is a useful tool to support PDO-based cancer research.

SUBMITTER: Okamoto T

PROVIDER: S-EPMC9357621 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Integration of human inspection and artificial intelligence-based morphological typing of patient-derived organoids reveals interpatient heterogeneity of colorectal cancer.

Okamoto Takuya T Natsume Yasuko Y Doi Motomichi M Nosato Hirokazu H Iwaki Toshiyuki T Yamanaka Hitomi H Yamamoto Mayuko M Kawachi Hiroshi H Noda Tetsuo T Nagayama Satoshi S Sakanashi Hidenori H Yao Ryoji R

Cancer science 20220607 8

Colorectal cancer (CRC) is a heterogenous disease, and patients have differences in therapeutic response. However, the mechanisms underlying interpatient heterogeneity in the response to chemotherapeutic agents remain to be elucidated, and molecular tumor characteristics are required to select patients for specific therapies. Patient-derived organoids (PDOs) established from CRCs recapitulate various biological characteristics of tumor tissues, including cellular heterogeneity and the response t ...[more]

PMID: 35585758

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Project description:The cranium is an anatomically complex structure. One source of its complexity is due to its modular organization. Cranial modules are distinct and partially independent units that interact substantially during ontogeny thus generating morphological integration. Artificial Cranial Deformation (ACD) occurs when the human skull is intentionally deformed, through the use of different deforming devices applied to the head while it is developing. Hence, ACD provides an interesting example to assess the degree to which biomechanical perturbations of the developing neurocranium impact on the degree of morphological integration in the skull as a whole. The main objective of this study was to assess how ACD affects the morphological integration of the skull. This was accomplished by comparing a sample of non-deformed crania and two sets of deformed crania (i.e. antero-posterior and oblique). Both developmental and static modularity and integration were assessed through Generalized Procrustes Analysis by considering the symmetric and asymmetric components of variation in adults, using 3D landmark coordinates as raw data. The presence of two developmental modules (i.e. viscero and neurocranium) in the skull was tested. Then, in order to understand how ACD affects morphological integration, the covariation pattern between the neuro and viscerocranium was examined in antero-posterior, oblique and non-deformed cranial categories using Partial Least-Squares. The main objective of this study was to assess how ACD affects the morphological integration of the skull. This was accomplished by comparing a sample of deformed (i.e. antero-posterior and oblique) and non-deformed crania. Hence, differences in integration patterns were compared between groups. The obtained results support the modular organization of the human skull in the two analyzed modules. The integration analyses show that the oblique ACD style differentially affects the static morphological integration of the skull by increasing the covariance between neuro and viscerocranium in a more constrained way than in antero-posterior and non-deformed skulls. In addition, the antero-posterior ACD style seems to affect the developmental integration of the skull by directing the covariation pattern in a more defined manner as compared to the other cranial categories.

Dataset Information

Integration of human inspection and artificial intelligence-based morphological typing of patient-derived organoids reveals interpatient heterogeneity of colorectal cancer.

Publications

Integration of human inspection and artificial intelligence-based morphological typing of patient-derived organoids reveals interpatient heterogeneity of colorectal cancer.

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