Evidence map›Paper›PMID 42079038›Full record

ArticlebioRxiv : the preprint server for biology2026

C26 and CT26 colorectal cancer models exhibit divergent cachexia phenotypes, intramuscular inflammation, and protein turnover signaling.

Xinyue Lu, Hanan Tlais, Hamood Rehman, Ashtyn N Martens, Abigail L Hartz, Vandré C Figueiredo, James F Markworth

Abstract readPreprint
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

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

7 authors.

Xinyue LuDepartment of Animal Sciences, College of Agriculture, Purdue University, West Lafayette, IN, USA.ORCID 0009-0004-9011-8711
Hanan TlaisDepartment of Biological Sciences, Oakland University, Rochester, MI, USA.ORCID 0009-0000-5567-3841
Hamood RehmanDepartment of Animal Sciences, College of Agriculture, Purdue University, West Lafayette, IN, USA.
Ashtyn N MartensDepartment of Animal Sciences, College of Agriculture, Purdue University, West Lafayette, IN, USA.
Abigail L HartzDepartment of Animal Sciences, College of Agriculture, Purdue University, West Lafayette, IN, USA.
Vandré C FigueiredoDepartment of Biological Sciences, Oakland University, Rochester, MI, USA.ORCID 0000-0002-3012-7905
James F MarkworthDepartment of Animal Sciences, College of Agriculture, Purdue University, West Lafayette, IN, USA.ORCID 0000-0002-5348-1464

Funding

Reverse engineering cancer cachexia: muscle ribosome biogenesis in the etiology of cachexiaR15AR083675 · NIAMS · OAKLAND UNIVERSITY · PI FIGUEIREDO, VANDRE CASAGRANDE · 2024 to 2024
$591k
NIAMS NIH HHS R15 AR083675
6 · The paper itself

Abstract

Colorectal cancer (CRC) cachexia induces skeletal muscle dysfunction, impeding quality of life and worsening cancer prognosis. Multiple preclinical models, including the widely used mouse model of subcutaneous inoculation with the C26 colorectal carcinoma cell line, have been developed to study the biological mechanisms of CRC cachexia and elucidate potential new treatments. It has been proposed that a distinct cell line of the same origin, namely CT26, is relatively non-cachexic. However, studies evaluating the relative potential of C26 and CT26 cells to induce cancer cachexia in parallel have been limited. The differences in the biological mechanisms by which C26 and CT26 impact skeletal muscle mass and function have also not been fully elucidated. In the current study, we investigated the differential capacity of C26 and CT26 to induce cancer cachexia using both an

Identifiers

PMID42079038
PMCPMC13131556

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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.