Evidence map›Paper›PMID 27240214›Full record

ReviewWiley interdisciplinary reviews. Systems biology and medicine2016

Systems medicine in colorectal cancer: from a mathematical model toward a new type of clinical trial.

Nicoletta Castagnino, Massimo Maffei, Lorenzo Tortolina, Gabriele Zoppoli, Daniela Piras, Alessio Nencioni, Eva Moran, Alberto Ballestrero, Franco Patrone, Silvio Parodi

Open access · hybridAbstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. Systems biology and medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Frontiers in systems biology · 2023
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Nicoletta CastagninoDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Massimo MaffeiDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Lorenzo TortolinaDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Gabriele ZoppoliDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Daniela PirasDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Alessio NencioniDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Eva MoranDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Alberto BallestreroDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Franco PatroneDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Silvio ParodiDepartment of Internal Medicine and Medical Specializations (DIMI), University of Genoa, Genoa, Italy.
Ospedale Policlinico San Martino · ITUniversity of Genoa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current colorectal cancer (CRC) treatment guidelines are primarily based on clinical features, such as cancer stage and grade. However, outcomes may be improved using molecular treatment guidelines. Potentially useful biomarkers include driver mutations and somatically inherited alterations, signaling proteins (their expression levels and (post) translational modifications), mRNAs, micro-RNAs and long noncoding RNAs. Moving to an integrated system is potentially very relevant. To implement such an integrated system: we focus on an important region of the signaling network, immediately above the G1-S restriction point, and discuss the reconstruction of a Molecular Interaction Map and interrogating it with a dynamic mathematical model. Extensive model pretraining achieved satisfactory, validated, performance. The model helps to propose future target combination priorities, and restricts drastically the number of drugs to be finally tested at a cellular, in vivo, and clinical-trial level. Our model allows for the inclusion of the unique molecular profiles of each individual patient's tumor. While existing clinical guidelines are well established, dynamic modeling may be used for future targeted combination therapies, which may progressively become part of clinical practice within the near future. WIREs Syst Biol Med 2016, 8:314-336. doi: 10.1002/wsbm.1342 For further resources related to this article, please visit the WIREs website.

Indexed as

Models, TheoreticalBiomarkers, TumorCell Cycle CheckpointsColorectal NeoplasmsHumansMicroRNAsPolymorphism, Single NucleotidePractice Guidelines as TopicRNA, MessengerBiomarkers, TumorMicroRNAsRNA, Messenger

Identifiers

PMID27240214
PMCPMC6680205
OpenAlexW2409501992

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.