Molecular drivers of tumor progression in microsatellite stable APC mutation-negative colorectal cancers

Grant, Adam; Xicola, Rosa M.; Nguyen, Vivian T.; Lim, James; Thorne, Curtis A.; Salhia, Bodour; Llor, Xavier; Ellis, Nathan A.; Padi, Megha

doi:10.1038/s41598-021-02806-x

Cited by 6 publications

(4 citation statements)

References 53 publications

(55 reference statements)

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“…DEGs were enriched for 104 gene ontology terms [ 33 , 34 ], as well as three KEGG terms: “Wnt signaling pathway” (FDR = 5.30 × 10 −5 ), “Hippo signaling pathway (FDR = 3.80 × 10 −3 ) and “mitophagy—animal” (FDR = 0.016) ( Supplementary Table S3 ). Extracellular Wnt sensitivity and/or Wnt signaling has previously been suggested to be important for earlier onset of CRC development in other studies [ 40 , 41 ].…”

Section: Resultsmentioning

confidence: 96%

Insights into Early Onset Colorectal Cancer through Analysis of Normal Colon Organoids of Familial Adenomatous Polyposis Patients

Devall

Eaton

Ali

et al. 2022

Cancers

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Early onset colorectal cancer (EOCRC) rates have increased in recent decades. While lowering the recommended age for routine colonoscopies to 45 may reduce this burden, such measures do not address those who develop CRC before that age. Additional measures are needed to identify individuals at-risk for CRC. To better define transcriptomic events that precede the development of CRC, we performed RNA-sequencing analysis in colon organoids derived from seven healthy and six familial adenomatous polyposis (FAP) patients. This led to the identification of 2635 significant differentially expressed genes (FDR < 0.05). Through secondary analysis of publicly available datasets, we found that these genes were enriched for significant genes also present in FAP CRC and non-hereditary CRC datasets, including a subset that were unique to EOCRC. By exposing FAP colon organoids to a three-day ethanol treatment, we found that two EOCRC-relevant genes were also targets of CRC related lifestyle factors. Our data provides unique insight into the potential, early mechanisms of CRC development in colon epithelial cells, which may provide biomarkers for patient monitoring. We also show how modifiable lifestyle factors may further alter genes relevant to EOCRC, adding weight to the hypothesis that such factors represent an important contributor to increased EOCRC incidence.

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Section: Resultsmentioning

confidence: 96%

Insights into Early Onset Colorectal Cancer through Analysis of Normal Colon Organoids of Familial Adenomatous Polyposis Patients

Devall

Eaton

Ali

et al. 2022

Cancers

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“…These are synergistic milestones in COAD progression [30,33]. Specifically, KRAS and BRAF mutations are alternative ways of RAS pathway deregulation [13,44] and APC and RNF43 are alternative ways of Wnt signalling deregulation [21,23]. Additionally, the synergy within the pairs as well as the antagonism between them are clearly reflected in the conditional selection analysis of [29].…”

Section: Colon Adenocarcinomamentioning

confidence: 99%

Overcoming Observation Bias for Cancer Progression Modeling

Schill,

Klever,

Lösch

et al. 2024

Lecture Notes in Computer Science

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Cancers evolve by accumulating genetic alterations, such as mutations and copy number changes. The chronological order of these events is important for understanding the disease, but not directly observable from cross-sectional genomic data. Cancer progression models (CPMs), such as Mutual Hazard Networks (MHNs), reconstruct the progression dynamics of tumors by learning a network of causal interactions between genetic events from their co-occurrence patterns. However, current CPMs fail to include effects of genetic events on the observation of the tumor itself and assume that observation occurs independently of all genetic events. Since a dataset contains by definition only tumors at their moment of observation, neglecting any causal effects on this event leads to the "conditioning on a collider" bias: Events that make the tumor more likely to be observed appear anti-correlated, which results in spurious suppressive effects or masks promoting effects among genetic events. Here, we extend MHNs by modeling effects from genetic progression events on the observation event, thereby correcting for the collider bias. We derive an efficient tensor formula for the likelihood function and learn two models on somatic mutation datasets from the MSK-IMPACT study. In colon adenocarcinoma, we find a strong effect on observation by mutations in TP53, and in lung adenocarcinoma by mutations in EGFR. Compared to classical MHNs, this explains away many spurious suppressive interactions and uncovers several promoting effects.The data, code, and results are available at https://github.com/cbg-ethz/ObservationMHN.

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Section: Colon Adenocarcinomamentioning

confidence: 99%

Overcoming Observation Bias for Cancer Progression Modeling

Schill,

Klever,

Lösch

et al. 2023

Preprint

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Cancers evolve by accumulating genetic alterations, such as mutations and copy number changes. The chronological order of these events is important for understanding the disease, but not directly observable from cross-sectional genomic data. Cancer progression models (CPMs), such as Mutual Hazard Networks (MHNs), reconstruct the progression dynamics of tumors by learning a network of causal interactions between genetic events from their co-occurrence patterns. However, current CPMs fail to include effects of genetic events on the observation of the tumor itself and assume that observation occurs independently of all genetic events. Since a dataset contains by definition only tumors at their moment of observation, neglecting any causal effects on this event leads to the “conditioning on a collider” bias: Events that make the tumor more likely to be observed appear anti-correlated, which results in spurious suppressive effects or masks promoting effects among genetic events. Here, we extend MHNs by modeling effects from genetic progression events on the observation event, thereby correcting for the collider bias. We derive an efficient tensor formula for the likelihood function and learn two models on somatic mutation datasets from the MSK-IMPACT study. In colon adenocarcinoma, we find a strong effect on observation by mutations in TP53, and in lung adenocarcinoma by mutations in EGFR. Compared to classical MHNs, this explains away many spurious suppressive interactions and uncovers several promoting effects.The data, code, and results are available athttps://github.com/cbg-ethz/ObservationMHN.

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Molecular drivers of tumor progression in microsatellite stable APC mutation-negative colorectal cancers

Cited by 6 publications

References 53 publications

Insights into Early Onset Colorectal Cancer through Analysis of Normal Colon Organoids of Familial Adenomatous Polyposis Patients

Insights into Early Onset Colorectal Cancer through Analysis of Normal Colon Organoids of Familial Adenomatous Polyposis Patients

Overcoming Observation Bias for Cancer Progression Modeling

Overcoming Observation Bias for Cancer Progression Modeling

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