Evidence map›Paper›PMID 42124675›Full record

ArticlebioRxiv : the preprint server for biology2026

Modeling Microbiome Modulation of Tumor Metabolic Networks to Predict Synergistic Therapies.

Annie J Badenoch, Zeyang Pang, Carolina H Chung, Aaron Robida, Bretton Badenoch, Ritish Natesan, Layth Kakish, Jiahe Li, Sriram Chandrasekaran

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Annie J BadenochGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Zeyang PangDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0003-3949-4928
Carolina H ChungDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0003-2490-1842
Aaron RobidaCenter for Chemical Genomics, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0003-4867-9641
Bretton BadenochDepartment of Molecular and Cellular Pathology, University of Michigan, Ann Arbor, MI, 48103, USA.ORCID 0000-0001-8985-4325
Ritish NatesanDepartment of Computer Science and Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Layth KakishDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Jiahe LiDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Sriram ChandrasekaranGilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-8405-5708

Funding

Linking metabolic activity with drug sensitivity using metabolic influence networksR35GM137795 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sriram Chandrasekaran · 2020 to 2026
$2.6M
NIGMS NIH HHS R35 GM137795
6 · The paper itself

Abstract

Differences in microbiome composition profoundly influence drug response, yet methods to model the metabolic interplay between tumors, microbes, and therapeutics remain limited. We present a generalizable framework combining machine-learning and genome-scale metabolic modeling to prioritize combination therapies for colorectal cancer (CRC) in the presence of

Identifiers

PMID42124675
PMCPMC13160092

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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 OpenQuestion graph.