Dataset Information

Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers.

ABSTRACT: The study of response to cancer treatments has benefited greatly from the contribution of different omics data but their interpretation is sometimes difficult. Some mathematical models based on prior biological knowledge of signaling pathways facilitate this interpretation but often require fitting of their parameters using perturbation data. We propose a more qualitative mechanistic approach, based on logical formalism and on the sole mapping and interpretation of omics data, and able to recover differences in sensitivity to gene inhibition without model training. This approach is showcased by the study of BRAF inhibition in patients with melanomas and colorectal cancers who experience significant differences in sensitivity despite similar omics profiles. We first gather information from literature and build a logical model summarizing the regulatory network of the mitogen-activated protein kinase (MAPK) pathway surrounding BRAF, with factors involved in the BRAF inhibition resistance mechanisms. The relevance of this model is verified by automatically assessing that it qualitatively reproduces response or resistance behaviors identified in the literature. Data from over 100 melanoma and colorectal cancer cell lines are then used to validate the model's ability to explain differences in sensitivity. This generic model is transformed into personalized cell line-specific logical models by integrating the omics information of the cell lines as constraints of the model. The use of mutations alone allows personalized models to correlate significantly with experimental sensitivities to BRAF inhibition, both from drug and CRISPR targeting, and even better with the joint use of mutations and RNA, supporting multi-omics mechanistic models. A comparison of these untrained models with learning approaches highlights similarities in interpretation and complementarity depending on the size of the datasets. This parsimonious pipeline, which can easily be extended to other biological questions, makes it possible to explore the mechanistic causes of the response to treatment, on an individualized basis.

SUBMITTER: Beal J

PROVIDER: S-EPMC7872233 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers.

Béal Jonas J Pantolini Lorenzo L Noël Vincent V Barillot Emmanuel E Calzone Laurence L

PLoS computational biology 20210128 1

The study of response to cancer treatments has benefited greatly from the contribution of different omics data but their interpretation is sometimes difficult. Some mathematical models based on prior biological knowledge of signaling pathways facilitate this interpretation but often require fitting of their parameters using perturbation data. We propose a more qualitative mechanistic approach, based on logical formalism and on the sole mapping and interpretation of omics data, and able to recove ...[more]

PMID: 33507915

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Project description:IntroductionLikely due to ignored heterogeneity in disease pathophysiology, osteoarthritis (OA) has become the most common disabling joint disease, without effective disease-modifying treatment causing a large social and economic burden. In this study we set out to explore responses of aged human osteochondral explants upon different OA-related perturbing triggers (inflammation, hypertrophy and mechanical stress) for future tailored biomimetic human models.MethodsHuman osteochondral explants were treated with IL-1β (10 ng/ml) or triiodothyronine (T3; 10 nM) or received 65% strains of mechanical stress (65% MS). Changes in chondrocyte signalling were determined by expression levels of nine genes involved in catabolism, anabolism and hypertrophy. Breakdown of cartilage was measured by sulphated glycosaminoglycans (sGAGs) release, scoring histological changes (Mankin score) and mechanical properties of cartilage.ResultsAll three perturbations (IL-1β, T3 and 65% MS) resulted in upregulation of the catabolic genes MMP13 and EPAS1. IL-1β abolished COL2A1 and ACAN gene expression and increased cartilage degeneration, reflected by increased Mankin scores and sGAGs released. Treatment with T3 resulted in a high and significant upregulation of the hypertrophic markers COL1A1, COL10A1 and ALPL. However, 65% MS increased sGAG release and detrimentally altered mechanical properties of cartilage.ConclusionWe present consistent and specific output on three different triggers of OA. Perturbation with the pro-inflammatory IL-1β mainly induced catabolic chondrocyte signalling and cartilage breakdown, while T3 initiated expression of hypertrophic and mineralization markers. Mechanical stress at a strain of 65% induced catabolic chondrocyte signalling and changed cartilage matrix integrity. The major strength of our ex vivo models was that they considered aged, preserved, human cartilage of a heterogeneous OA patient population. As a result, the explants may reflect a reliable biomimetic model prone to OA onset allowing for development of different treatment modalities.

Project description:BRAF and KRAS genes are known to play a similar role in the activation of RAS-RAF-MEK-ERK signaling pathway in colorectal tumorigenesis. However, BRAF-mutated colorectal cancers (CRCs) have distinct clinicopathologic characteristics different from those of the KRAS mutated ones as in comparison the BRAF-mutated CRCs are associated with a much worse prognosis for the afflicted patients. This study aimed to determine the different miRNA expression signatures associated with BRAF-mutated CRCs in comparison to KRAS-mutated ones, and to identify the specific miRNAs possibly mediating the aggressive phenotype of the BRAF-mutated CRCs. We screened 535 formalin-fixed paraffin-embedded CRC tissue samples for the BRAF V600E mutation, and selected 7 BRAF-mutated and 7 KRAS-mutated CRCs that were tumor size, stage, and microsatellite status-matched. Affymetrix GeneChip® miRNA 4.0 Array was used for detection of miRNA expression differences in the selected samples. We validated the array results by quantitative reverse transcription polymerase chain reaction (qRT-PCR) for selected miRNAs. A total of 10 differentially expressed (DE) miRNAs associated with BRAF-mutated CRCs were obtained, including miR-31-5p, miR-877-5p, miR-362-5p, and miR-425-3p. miR-31-5p showed the highest fold change (8.3-fold) among all of the miRNAs analyzed. From the analyses of GO biological processes, the DE-miRNAs were functionally relevant to cellular proliferation such as positive regulation of gene expression (P?=?1.26?×?10(-10)), transcription (P?=?9.70?×?10(-10)), and RNA metabolic process (P?=?1.97?×?10(-9)). Bioinformatics analysis showed that the DE-miRNAs were significantly enriched in cancer-associated pathways including neutrophin signaling (P?=?6.84?×?10(-5)), pathways in cancer (P?=?0.0016), Wnt signaling (P?=?0.0027), and MAPK signaling pathway (P?=?0.0036). Our results suggest that the DE-miRNAs in BRAF-mutated CRCs in comparison to KRAS-mutated CRCs are implicated in the aggressive phenotype of the BRAF-mutated CRCs. Further experimental validation is required to confirm these results.

Dataset Information

Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers.

Publications

Personalized logical models to investigate cancer response to BRAF treatments in melanomas and colorectal cancers.

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